Search results for: multiple stream model

Authors: Muleya Nqobile, Winston Garira

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We presented a compartmental deterministic multi-scale model which encompass internal plant defensive mechanism and pathogen interaction, then we consider nesting the model into the epidemiological model. The objective was to improve our understanding of the transmission dynamics of within host and between host of Guignardia citricapa Kiely. The inflow of infected class was scaled down to individual level while the outflow was scaled up to average population level. Conceptual model and mathematical model were constructed to display a theoretical framework which can be used for predicting or identify disease pattern.

Keywords: epidemiological model, mathematical modelling, multi-scale modelling, immunological model

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Authors: Feng Tao, Han Ye, Shaoyi Liao

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City constructions collapse after earthquake and people will be buried under ruins. Search and rescue should be conducted as soon as possible to save them. Therefore, according to the complicated environment, irregular aftershocks and rescue allow of no delay, a kind of target localization method based on RSSI (Received Signal Strength Indication) is proposed in this article. The target localization technology based on RSSI with the features of low cost and low complexity has been widely applied to nodes localization in WSN (Wireless Sensor Networks). Based on the theory of RSSI transmission and the environment impact to RSSI, this article conducts the experiments in five scenes, and multiple filtering algorithms are applied to original RSSI value in order to establish the signal propagation model with minimum test error respectively. Target location can be calculated from the distance, which can be estimated from signal propagation model, through improved centroid algorithm. Result shows that the localization technology based on RSSI is suitable for large-scale nodes localization. Among filtering algorithms, mixed filtering algorithm (average of average, median and Gaussian filtering) performs better than any other single filtering algorithm, and by using the signal propagation model, the minimum error of distance between known nodes and target node in the five scene is about 3.06m.

Keywords: signal propagation model, centroid algorithm, localization, mixed filtering, RSSI

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Authors: Selma Sbit, Mohamed Bechir Dadi, Belgacem Chibani Rhaimi

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Incorporating Home eNodeB (HeNB) in cellular networks, e.g. Long Term Evolution Advanced (LTE-A), is beneficial for extending coverage and enhancing capacity at low price especially within the non-line-of sight (NLOS) environments such as homes. HeNB or femtocell is a small low powered base station which provides radio coverage to the mobile users in an indoor environment. This deployment results in a heterogeneous network where the available spectrum becomes shared between two layers. Therefore, a problem of Inter Cell Interference (ICI) appears. This issue is the main challenge in LTE-A. To deal with this challenge, various techniques based on frequency, time and power control are proposed. This paper deals with the impact of carrier aggregation and higher order MIMO (Multiple Input Multiple Output) schemes on the LTE-Advanced performance. Simulation results show the advantages of these schemes on the system capacity (4.10⁹ b/s/Hz when bandwidth B=100 MHz and when applying MIMO 8x8 for SINR=30 dB), maximum theoretical peak data rate (more than 4 Gbps for B=100 MHz and when MIMO 8x8 is used) and spectral efficiency (15 b/s/Hz and 30b/s/Hz when MIMO 4x4 and MIMO 8x8 are applying respectively for SINR=30 dB).

Keywords: capacity, carrier aggregation, LTE-Advanced, MIMO (Multiple Input Multiple Output), peak data rate, spectral efficiency

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Authors: Kamyar Kildashti, Rasoul Mirghaderi

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This paper describes the three-dimensional seismic performance assessment of a high-rise steel moment-frame setback tower, designed and detailed per the 2010 ASCE7, under multiple support excitations. The vulnerability analyses are conducted based on nonlinear history analyses under a set of multi-directional strong ground motion records which are scaled to design-based site-specific spectrum in accordance with ASCE41-13. Spatial variation of input motions between far distant supports of each part of the tower is considered by defining time lag. Plastic hinge monotonic and cyclic behavior for prequalified steel connections, panel zones, as well as steel columns is obtained from predefined values presented in TBI Guidelines, PEER/ATC72 and FEMA P440A to include stiffness and strength degradation. Inter-story drift ratios, residual drift ratios, as well as plastic hinge rotation demands under multiple support excitations, are compared to those obtained from uniform support excitations. Performance objectives based on acceptance criteria declared by TBI Guidelines are compared between uniform and multiple support excitations. The results demonstrate that input motion discrepancy results in detrimental effects on the local and global response of the tower.

Keywords: high-rise building, nonlinear time history analysis, multiple support excitation, performance-based design

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Authors: Jernice S. Y. Tan

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Introduction: Reliability within and between testers is vital to ensure the accuracy of any motor assessment instrument. However, reliability checks of the Movement Assessment Battery for Children-2 (MABC-2) age band 3 using multiple testers assigned to different MABC-2 tasks for the same group of participants are uncommon. Multiple testers were not stated as a choice in the MABC-2 manual. Therefore, the purpose of this study was to determine the inter- and intra-tester reliability for using multiple testers to administer the test protocols of MABC-2 age band 3. Methods: Thirty volunteered adolescents (n = 30; 15 males, 15 females; age range: 13 – 16 years) performed the eight tasks in a randomised sequence at three different test stations for the MABC-2 task components (Manual Dexterity, Aiming and Catching, Balance). Ethics approval and parental consent were obtained. The participants were videotaped while performing the test protocols of MABC-2 age band 3. Five testers were involved in the data collection process. They were Sports Science graduating students doing their final year project and were supervised by experienced motor assessor. Inter- and intra-tester reliability checks using intra-class coefficient (ICC) were carried out using the videotaped data. Results: The inter-tester reliability between the five testers for the eight tasks ranged from rᵢcc = 0.705 to rᵢcc = 0.995. This suggests that the average agreement between them was considered good to excellent. With the exception of one tester who had rᵢcc = 0.687 for one of the eight tasks (i.e. zip-zap hopping), the intra-tester reliability within each tester ranged from rᵢcc = 0.728 to rᵢcc = 1.000, and this also suggested good to excellent consistency within testers. Discussion: The use of multiple testers with good intra-tester reliability for different test stations is feasible. This method allows several participants to be assessed concurrently at different test stations and saves overall data collection time. Therefore, it is recommended that the administering of MABC-2 with multiple testers should be extended to other age bands ensuring the feasibility of such method for other age bands.

Keywords: adolescents, MABC, motor assessment, motor skills, reliability

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Authors: Toshitaka Higashino, Naoki Wakamiya

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Human beings perform a task by perceiving information from outside, recognizing them, and responding them. There have been various attempts to analyze and understand internal processes behind the reaction to a given stimulus by conducting psychological experiments and analysis from multiple perspectives. Among these, we focused on Model Human Processor (MHP). However, it was built based on psychological experiments and thus the relation with brain activity was unclear so far. To verify the validity of the MHP and propose our model from a viewpoint of neuroscience, EEG (Electroencephalography) measurements are performed during experiments in this study. More specifically, first, experiments were conducted where Latin alphabet characters were used as visual stimuli. In addition to response time, ERPs (event-related potentials) such as N100 and P300 were measured by using EEG. By comparing cycle time predicted by the MHP and latency of ERPs, it was found that N100, related to perception of stimuli, appeared at the end of the perceptual processor. Furthermore, by conducting an additional experiment, it was revealed that P300, related to decision making, appeared during the response decision process, not at the end. Second, by experiments using Japanese Hiragana characters, i.e. Japan's own phonetic symbols, those findings were confirmed. Finally, Japanese Kanji characters were used as more complicated visual stimuli. A Kanji character usually has several readings and several meanings. Despite the difference, a reading-related task and a meaning-related task exhibited similar results, meaning that they involved similar information processing processes of the brain. Based on those results, our model was proposed which reflects response time and ERP latency. It consists of three processors: the perception processor from an input of a stimulus to appearance of N100, the cognitive processor from N100 to P300, and the decision-action processor from P300 to response. Using our model, an application system which reflects brain activity can be established.

Keywords: brain activity, EEG, information processing model, model human processor

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Authors: Alvin Han, Reema Shafi, Alishba Afaq, Jennifer Gommerman, Valeria Ramaglia, Shannon E. Dunn

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Adolescents engaged in contact-sports can suffer from recurrent brain concussions with no loss of consciousness and no need for hospitalization, yet they face the possibility of long-term neurocognitive problems. Recent studies suggest that head concussive injuries during adolescence can also predispose individuals to multiple sclerosis (MS). The underlying mechanisms of how brain concussions predispose to MS is not understood. Here, we hypothesize that: (1) recurrent brain concussions prime microglial cells, the tissue resident myeloid cells of the brain, setting them up for exacerbated responses when exposed to additional challenges later in life; and (2) brain concussions lead to the sensitization of myelin-specific T cells in the peripheral lymphoid organs. Towards addressing these hypotheses, we implemented a mouse model of closed head injury that uses a weight-drop device. First, we calibrated the model in male 12 week-old mice and established that a weight drop from a 3 cm height induced mild neurological symptoms (mean neurological score of 1.6+0.4 at 1 hour post-injury) from which the mice fully recovered by 72 hours post-trauma. Then, we performed immunohistochemistry on the brain of concussed mice at 72 hours post-trauma. Despite mice having recovered from all neurological symptoms, immunostaining for leukocytes (CD45) and IBA-1 revealed no peripheral immune infiltration, but an increase in the intensity of IBA1+ staining compared to uninjured controls, suggesting that resident microglia had acquired a more active phenotype. This microglia activation was most apparent in the white matter tracts in the brain and in the olfactory bulb. Immunostaining for the microglia-specific homeostatic marker TMEM119, showed a reduction in TMEM119+ area in the brain of concussed mice compared to uninjured controls, confirming a loss of this homeostatic signal by microglia after injury. Future studies will test whether single or repetitive concussive injury can worsen or accelerate autoimmunity in male and female mice. Understanding these mechanisms will guide the development of timed and targeted therapies to prevent MS from getting started in people at risk.

Keywords: concussion, microglia, microglial priming, multiple sclerosis

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Authors: Wesley A. Saltarelli, Nicolas R. Finkler, Adriana C. P. Miwa, Maria C. Calijuri, Davi G. F. Cunha

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The metabolism of the streams is an indicator of ecosystem disturbance due to the influences of the catchment on the structure of the water bodies. The study of the respiration and photosynthesis allows the estimation of energy fluxes through the food webs and the analysis of the autotrophic and heterotrophic processes. We aimed at evaluating the metabolism in streams located in the Brazilian savannah, Cerrado (Sao Carlos, SP), by determining and modeling the daily changes of dissolved oxygen (DO) in the water during one year. Three water bodies with minimal anthropogenic interference in their surroundings were selected, Espraiado (ES), Broa (BR) and Canchim (CA). Every two months, water temperature, pH and conductivity are measured with a multiparameter probe. Nitrogen and phosphorus forms are determined according to standard methods. Also, canopy cover percentages are estimated in situ with a spherical densitometer. Stream flows are quantified through the conservative tracer (NaCl) method. For the metabolism study, DO (PME-MiniDOT) and light (Odyssey Photosynthetic Active Radiation) sensors log data for at least three consecutive days every ten minutes. The reaeration coefficient (k2) is estimated through the method of the tracer gas (SF6). Finally, we model the variations in DO concentrations and calculate the rates of gross and net primary production (GPP and NPP) and respiration based on the one station method described in the literature. Three sampling were carried out in October and December 2015 and February 2016 (the next will be in April, June and August 2016). The results from the first two periods are already available. The mean water temperatures in the streams were 20.0 +/- 0.8C (Oct) and 20.7 +/- 0.5C (Dec). In general, electrical conductivity values were low (ES: 20.5 +/- 3.5uS/cm; BR 5.5 +/- 0.7uS/cm; CA 33 +/- 1.4 uS/cm). The mean pH values were 5.0 (BR), 5.7 (ES) and 6.4 (CA). The mean concentrations of total phosphorus were 8.0ug/L (BR), 66.6ug/L (ES) and 51.5ug/L (CA), whereas soluble reactive phosphorus concentrations were always below 21.0ug/L. The BR stream had the lowest concentration of total nitrogen (0.55mg/L) as compared to CA (0.77mg/L) and ES (1.57mg/L). The average discharges were 8.8 +/- 6L/s (ES), 11.4 +/- 3L/s and CA 2.4 +/- 0.5L/s. The average percentages of canopy cover were 72% (ES), 75% (BR) and 79% (CA). Significant daily changes were observed in the DO concentrations, reflecting predominantly heterotrophic conditions (respiration exceeded the gross primary production, with negative net primary production). The GPP varied from 0-0.4g/m2.d (in Oct and Dec) and the R varied from 0.9-22.7g/m2.d (Oct) and from 0.9-7g/m2.d (Dec). The predominance of heterotrophic conditions suggests increased vulnerability of the ecosystems to artificial inputs of organic matter that would demand oxygen. The investigation of the metabolism in the pristine streams can help defining natural reference conditions of trophic state.

Keywords: low-order streams, metabolism, net primary production, trophic state

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Authors: Venkata Ramanaiah, Shabina Khanam

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Enormous potential for saving energy is available in coal-based sponge iron plants as these are associated with the high percentage of energy wastage per unit sponge iron production. An energy integration option is proposed, in the present paper, to a coal based sponge iron plant of 100 tonnes per day production capacity, being operated in India using SL/RN (Stelco-Lurgi/Republic Steel-National Lead) process. It consists of the rotary kiln, rotary cooler, dust settling chamber, after burning chamber, evaporating cooler, electrostatic precipitator (ESP), wet scrapper and chimney as important equipment. Principles of process integration are used in the proposed option. It accounts for preheating kiln inlet streams like kiln feed and slinger coal up to 170ᴼC using waste gas exiting ESP. Further, kiln outlet stream is cooled from 1020ᴼC to 110ᴼC using kiln air. The working areas in the plant where energy is being lost and can be conserved are identified. Detailed material and energy balances are carried out around the sponge iron plant, and a modified model is developed, to find coal requirement of proposed option, based on hot utility, heat of reactions, kiln feed and air preheating, radiation losses, dolomite decomposition, the heat required to vaporize the coal volatiles, etc. As coal is used as utility and process stream, an iterative approach is used in solution methodology to compute coal consumption. Further, water consumption, operating cost, capital investment, waste gas generation, profit, and payback period of the modification are computed. Along with these, operational aspects of the proposed design are also discussed. To recover and integrate waste heat available in the plant, three gas-solid heat exchangers and four insulated ducts with one FD fan for each are installed additionally. Thus, the proposed option requires total capital investment of $0.84 million. Preheating of kiln feed, slinger coal and kiln air streams reduce coal consumption by 24.63% which in turn reduces waste gas generation by 25.2% in comparison to the existing process. Moreover, 96% reduction in water is also observed, which is the added advantage of the modification. Consequently, total profit is found as $2.06 million/year with payback period of 4.97 months only. The energy efficient factor (EEF), which is the % of the maximum energy that can be saved through design, is found to be 56.7%. Results of the proposed option are also compared with literature and found in good agreement.

Keywords: coal consumption, energy conservation, process integration, sponge iron plant

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Authors: Jaouadi Imen, Ben Djemaa Raoudha, Ben Abdallah Hanene

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The access to relevant information that is adapted to users’ needs, preferences and environment is a challenge in many applications running. That causes an appearance of context-aware systems. To facilitate the development of this class of applications, it is necessary that these applications share a common context meta-model. In this article, we will present our context meta-model that is defined using the OMG Meta Object facility (MOF). This meta-model is based on the analysis and synthesis of context concepts proposed in literature.

Keywords: context, meta-model, MOF, awareness system

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Authors: Charleen von Kolpinski, Karina Cagarman, Alina Blaute

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The circular economy concept is often framed by politicians, scientists and practitioners as being the solution to sustainability problems of our times. However, the focus of these discussions and publications is very often set on environmental and economic aspects. In contrast, the social dimension of sustainability has been neglected and only a few recent and mostly conceptual studies targeted the inclusion of social aspects and the SDGs into circular economy research. All stakeholders of this new circular system have to be included to represent a truly sustainable solution to all the environmental, economic and social challenges caused by the linear economic system. Hence, this empirical research aims to analyse, next to the environmental and economic dimension, also explicitly the social dimension of a sustainable circular business model. This inductive and explorative approach applies the single case study method. A multi-stakeholder view is adopted to shed light on social aspects of the circular business model. Different stakeholder views, tensions between stakeholders and conflicts of interest are detected. In semi-structured interviews with different stakeholders of the company, this study compares the different stakeholder views to profile the success factors of its business model in terms of sustainability implementation and to detect its shortcomings. These findings result in the development of propositions which cover different social aspects of sustainable circular business model implementation. This study is an answer to calls for future empirical research about the social dimension of the circular economy and contributes to sustainable business model thinking in entrepreneurial contexts of the circular economy. It helps identifying all relevant stakeholders and their needs to successfully and inclusively implement a sustainable circular business model. The method of a single case study has some limitations by nature as it only covers one enterprise with its special business model. Therefore, more empirical studies are needed to research sustainable circular business models from multiple stakeholder perspectives, in different countries and industries. Future research can build upon the developed propositions of this study and develop hypotheses to be tested.

Keywords: circular economy, single case study, social dimension, sustainable circular business model

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Authors: Jayahar Sivasubramanian

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Understanding laminar-turbulent transition process in hyper-sonic boundary layers is crucial for designing viable high speed flight vehicles. The study of transition becomes particularly important in the high speed regime due to the effect of transition on aerodynamic performance and heat transfer. However, even after many years of research, the transition process in hyper-sonic boundary layers is still not understood. This lack of understanding of the physics of the transition process is a major impediment to the development of reliable transition prediction methods. Towards this end, spatial Direct Numerical Simulations are conducted to investigate the instability waves generated by a localized disturbance in a hyper-sonic flat plate boundary layer. In order to model a natural transition scenario, the boundary layer was forced by a short duration (localized) pulse through a hole on the surface of the flat plate. The pulse disturbance developed into a three-dimensional instability wave packet which consisted of a wide range of disturbance frequencies and wave numbers. First, the linear development of the wave packet was studied by forcing the flow with low amplitude (0.001% of the free-stream velocity). The dominant waves within the resulting wave packet were identified as two-dimensional second mode disturbance waves. Hence the wall-pressure disturbance spectrum exhibited a maximum at the span wise mode number k = 0. The spectrum broadened in downstream direction and the lower frequency first mode oblique waves were also identified in the spectrum. However, the peak amplitude remained at k = 0 which shifted to lower frequencies in the downstream direction. In order to investigate the nonlinear transition regime, the flow was forced with a higher amplitude disturbance (5% of the free-stream velocity). The developing wave packet grows linearly at first before reaching the nonlinear regime. The wall pressure disturbance spectrum confirmed that the wave packet developed linearly at first. The response of the flow to the high amplitude pulse disturbance indicated the presence of a fundamental resonance mechanism. Lower amplitude secondary peaks were also identified in the disturbance wave spectrum at approximately half the frequency of the high amplitude frequency band, which would be an indication of a sub-harmonic resonance mechanism. The disturbance spectrum indicates, however, that fundamental resonance is much stronger than sub-harmonic resonance.

Keywords: boundary layer, DNS, hyper sonic flow, instability waves, wave packet

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Authors: Sina Mahdavi

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Background and Objective: Multiple sclerosis (MS) is the most common inflammatory autoimmune disease of the central nervous system (CNS) that affects the myelination process in the CNS. Complex interactions of various "environmental or infectious" factors may act as triggers in autoimmunity and disease progression. The association between viral infections, especially the John Cunningham virus (JCV) and MS is one potential cause that is not well understood. This study aims to summarize the available data on JCV infection in MS disease progression. Materials and Methods: For this study, the keywords "Multiple sclerosis", " John Cunningham virus ", and "central nervous system" in the databases PubMed, Google Scholar, Sid, and MagIran between 2019 and 2022 were searched, and 12 articles were chosen, studied, and analyzed. Results: MS patients are candidates for natalizumab therapy, which inhibits lymphocyte migration and increases the risk of progressive multifocal leukoencephalopathy (PML), a rare lytic infection of glial cells caused by JCV. Oligodendrocytes may be the target of JCV infection in the central nervous system (CNS). Conclusion: There is a high expression of JCV during the natalizumab treatment period for MS patients, suggesting that the virus may play a role in the development of MS by inducing an inflammatory state. Therefore, it is necessary to evaluate anti-JCV antibody serum as an important risk factor for the development of PML before deciding on the treatment course for these patients.

Keywords: multiple sclerosis, John Cunningham virus, central nervous system, autoimmunity

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Authors: Öykü Barutçu, Mehmet Özgür Kuzdan

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Aim: Laparoscopy is very risky in patients undergoing, multiple open abdominal surgeries. The aim of this study, to define a safe method for the first trocar placement in children with a history of multiple open abdominal surgeries. Methods: Children who underwent laparoscopic surgery between March 2019 and April 2020 with a history of three or more open abdominal surgeries were included in the retrospective study. Patient information was obtained from the hospital automation system. Ultrasonography was used to determine the location of adhesions preoperatively. The first trocar was placed according to ultrasonography findings, using the Hasson technique to create an air pocket with finger dissection. The patient's preoperative, perioperative, and postoperative findings are reported. Results: A total of 10 patients were included in the study. The median number of operations before laparoscopy was three. The most common site for the first trocar entry was Palmer's point (40%). No mortality or morbidity was observed amongst any patients. The average number of adhesions detected by USG and observed on laparoscopy were significantly positively correlated. Conclusion: In children with a history of multiple abdominal surgeries, abdominal wall ultrasonography for visualization of adhesions and finger dissection for the formation of an air pocket appears to be a safe method for the first trocar insertion.

Keywords: abdominal wall, child, laparoscopy, ultrasonography

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Authors: Ben Soltane Cheima, Ittansa Yonas Kelbesa

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Speaker Identification (SI) is the task of establishing identity of an individual based on his/her voice characteristics. The SI task is typically achieved by two-stage signal processing: training and testing. The training process calculates speaker specific feature parameters from the speech and generates speaker models accordingly. In the testing phase, speech samples from unknown speakers are compared with the models and classified. Even though performance of speaker identification systems has improved due to recent advances in speech processing techniques, there is still need of improvement. In this paper, a Closed-Set Tex-Independent Speaker Identification System (CISI) based on a Multiple Classifier System (MCS) is proposed, using Mel Frequency Cepstrum Coefficient (MFCC) as feature extraction and suitable combination of vector quantization (VQ) and Gaussian Mixture Model (GMM) together with Expectation Maximization algorithm (EM) for speaker modeling. The use of Voice Activity Detector (VAD) with a hybrid approach based on Short Time Energy (STE) and Statistical Modeling of Background Noise in the pre-processing step of the feature extraction yields a better and more robust automatic speaker identification system. Also investigation of Linde-Buzo-Gray (LBG) clustering algorithm for initialization of GMM, for estimating the underlying parameters, in the EM step improved the convergence rate and systems performance. It also uses relative index as confidence measures in case of contradiction in identification process by GMM and VQ as well. Simulation results carried out on voxforge.org speech database using MATLAB highlight the efficacy of the proposed method compared to earlier work.

Keywords: feature extraction, speaker modeling, feature matching, Mel frequency cepstrum coefficient (MFCC), Gaussian mixture model (GMM), vector quantization (VQ), Linde-Buzo-Gray (LBG), expectation maximization (EM), pre-processing, voice activity detection (VAD), short time energy (STE), background noise statistical modeling, closed-set tex-independent speaker identification system (CISI)

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Authors: Harisudha Kuresan, Dhanalakshmi Samiappan, T. Rama Rao

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In modern telecommunication applications, Glottal Closure Instants location finding is important and is directly evaluated from the speech waveform. Here, we study the GCI using Speech Event Detection using Residual Excitation and the Mean Based Signal (SEDREAMS) algorithm. Speech coding uses parameter estimation using audio signal processing techniques to model the speech signal combined with generic data compression algorithms to represent the resulting modeled in a compact bit stream. This paper proposes a sub-band coder SBC, which is a type of transform coding and its performance for GCI detection using SEDREAMS are evaluated. In SBCs code in the speech signal is divided into two or more frequency bands and each of these sub-band signal is coded individually. The sub-bands after being processed are recombined to form the output signal, whose bandwidth covers the whole frequency spectrum. Then the signal is decomposed into low and high-frequency components and decimation and interpolation in frequency domain are performed. The proposed structure significantly reduces error, and precise locations of Glottal Closure Instants (GCIs) are found using SEDREAMS algorithm.

Keywords: SEDREAMS, GCI, SBC, GOI

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Authors: Gabriel Legorreta Paulin, Marcus I. Bursik, Lilia Arana Salinas, Fernando Aceves Quesada

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In volcanic environments, landslides and debris flows occur continually along stream systems of large stratovolcanoes. This is the case on Pico de Orizaba volcano, the highest mountain in Mexico. The volcano has a great potential to impact and damage human settlements and economic activities by landslides. People living along the lower valleys of Pico de Orizaba volcano are in continuous hazard by the coalescence of upstream landslide sediments that increased the destructive power of debris flows. These debris flows not only produce floods, but also cause the loss of lives and property. Although the importance of assessing such process, there is few landslide inventory maps and landslide susceptibility assessment. As a result in México, no landslide susceptibility models assessment has been conducted to evaluate advantage and disadvantage of models. In this study, a comprehensive study of landslide susceptibility models assessment using GIS technology is carried out on the SE flank of Pico de Orizaba volcano. A detailed multi-temporal landslide inventory map in the watershed is used as framework for the quantitative comparison of two landslide susceptibility maps. The maps are created based on 1) the Stability Index MAPping (SINMAP) model by using default geotechnical parameters and 2) by using findings of volcanic soils geotechnical proprieties obtained in the field. SINMAP combines the factor of safety derived from the infinite slope stability model with the theory of a hydrologic model to produce the susceptibility map. It has been claimed that SINMAP analysis is reasonably successful in defining areas that intuitively appear to be susceptible to landsliding in regions with sparse information. The validations of the resulting susceptibility maps are performed by comparing them with the inventory map under LOGISNET system which provides tools to compare by using a histogram and a contingency table. Results of the experiment allow for establishing how the individual models predict the landslide location, advantages, and limitations. The results also show that although the model tends to improve with the use of calibrated field data, the landslide susceptibility map does not perfectly represent existing landslides.

Keywords: GIS, landslide, modeling, LOGISNET, SINMAP

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Authors: K. Sekulová, M. Šimon

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This article focuses on upper-extremity musculoskeletal disorders risk assessment model at workplace. In this model are used risk factors that are responsible for musculoskeletal system damage. Based on statistic calculations the model is able to define what risk of MSD threatens workers who are under risk factors. The model is also able to say how MSD risk would decrease if these risk factors are eliminated.

Keywords: ergonomics, musculoskeletal disorders, occupational diseases, risk factors

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Authors: Anthony Usoro

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In this paper, two classes of bilinear time series model are obtained under certain conditions from the general bilinear autoregressive moving average model. Bilinear Autoregressive (BAR) and Bilinear Moving Average (BMA) Models have been identified. From the general bilinear model, BAR and BMA models have been proved to exist for q = Q = 0, => j = 0, and p = P = 0, => i = 0 respectively. These models are found useful in modelling most of the economic and financial data.

Keywords: autoregressive model, bilinear autoregressive model, bilinear moving average model, moving average model

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Authors: Sina Mahdavi

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Background and Objective: Multiple sclerosis (MS) is an inflammatory autoimmune disease of the CNS that affects the myelination process in the central nervous system (CNS). Complex interactions of various "environmental or infectious" factors may act as triggers in autoimmunity and disease progression. The association between viral infections, especially Human Herpesvirus 6 (HHV-6), and MS is one potential cause that is not well understood. In this study, we aim to summarize the available data on HHV-6 infection in MS disease progression. Materials and Methods: For this study, the keywords "Multiple sclerosis", " Human Herpesvirus 6 ", and "central nervous system" in the databases PubMed and Google Scholar between 2017 and 2022 were searched, and 12 articles were chosen, studied, and analyzed. Results: HHV 6 tends towards TCD 4+ lymphocytes and enters the CNS due to the weakening of the blood-brain barrier due to inflammatory damage. Following the observation that the HHV-6 U24 protein has a seven amino acid sequence with myelin basic protein, which is one of the main components of the myelin sheath, it could cause a molecular mimicry mechanism followed by cross-reactivity. Reactivation of HHV-6 in the CNS can cause the release of proinflammatory cytokines, including TNF-α, leading to immune-mediated demyelination in patients with MS. Conclusion: There is a high expression of endogenous retroviruses during the course of MS, which indicates the relationship between HHV-6 and MS, and that this virus can play a role in the development of MS by creating an inflammatory state. Therefore, measures to modulate the expression of HHV-6 may be effective in reducing inflammatory processes in demyelinated areas of MS patients.

Keywords: multiple sclerosis, human herpesvirus 6, central nervous system, autoimmunity

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Authors: María D. Groppa, Andrea Trentini, Myriam Zawoznik, Roxana Bigi, Carlos Nadra, Patricia L. Marconi

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In the present work, a remediation bioprocess based on the use of a local isolate of the microalgae Chlorella vulgaris immobilized in alginate beads is proposed. This process was shown to be effective for the reduction of several chemical and microbial contaminants present in Cildáñez stream, a water course that is part of the Matanza-Riachuelo Basin (Buenos Aires, Argentina). The bioprocess, involving the culture of the microalga in autotrophic conditions in a stirred-tank bioreactor supplied with a marine propeller for 6 days, allowed a significant reduction of Escherichia coli and total coliform numbers (over 95%), as well as of ammoniacal nitrogen (96%), nitrates (86%), nitrites (98%), and total phosphorus (53%) contents. Pb content was also significantly diminished after the bioprocess (95%). Standardized cytotoxicity tests using Allium cepa seeds and Cildáñez water pre- and post-remediation were also performed. Germination rate and mitotic index of onion seeds imbibed in Cildáñez water subjected to the bioprocess was similar to that observed in seeds imbibed in distilled water and significantly superior to that registered when untreated Cildáñez water was used for imbibition. Our results demonstrate the potential of this simple and cost-effective technology to remove urban-water contaminants, offering as an additional advantage the possibility of an easy biomass recovery, which may become a source of alternative energy.

Keywords: bioreactor, bioremediation, Chlorella vulgaris, Matanza-Riachuelo Basin, microalgae

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Authors: Waqas Ahmed Khan Afridi, Subhas Chandra Mukhopadhyay, Bandita Mainali

Abstract:

The research paper presents a unique approach to evapotranspiration (ET) prediction using a Support Vector Machine (SVM) learning algorithm. The study leverages real-time sensor node data to develop an accurate and adaptable prediction model, addressing the inherent challenges of traditional ET estimation methods. The integration of the SVM algorithm with real-time sensor node data offers great potential to improve spatial and temporal resolution in ET predictions. In the model development, key input features are measured and computed using mathematical equations such as Penman-Monteith (FAO56) and soil water balance (SWB), which include soil-environmental parameters such as; solar radiation (Rs), air temperature (T), atmospheric pressure (P), relative humidity (RH), wind speed (u2), rain (R), deep percolation (DP), soil temperature (ST), and change in soil moisture (∆SM). The one-year field data are split into combinations of three proportions i.e. train, test, and validation sets. While kernel functions with tuning hyperparameters have been used to train and improve the accuracy of the prediction model with multiple iterations. This paper also outlines the existing methods and the machine learning techniques to determine Evapotranspiration, data collection and preprocessing, model construction, and evaluation metrics, highlighting the significance of SVM in advancing the field of ET prediction. The results demonstrate the robustness and high predictability of the developed model on the basis of performance evaluation metrics (R2, RMSE, MAE). The effectiveness of the proposed model in capturing complex relationships within soil and environmental parameters provide insights into its potential applications for water resource management and hydrological ecosystem.

Keywords: evapotranspiration, FAO56, KNIME, machine learning, RStudio, SVM, sensors

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Authors: Sixing Chen, Shuai Yang

Abstract:

Online celebrity business, also known as Internet celebrity business (or Wanghong business in Chinese), is an emerging relational C2C business model, and an alternative to traditional C2C transactional business models. There are already millions of these consumers, and this number is growing. In this model, consumer purchase decisions are driven by recommendations and endorsements in videos posted online by celebrities. The purpose of this paper is to determine the relational constructs within consumer relationships in the Internet celebrity business model and to investigate relationships between the constructs and consumer purchase intention. A questionnaire-based study was conducted with consumers who had an awareness of, or prior purchase experience with online celebrities. The results of exploratory factor analysis (EFA) and multiple regression analysis revealed three valid relational constructs: product experience sharing, lifestyle association, and real-time interaction. This study indicated that these constructs had the direct effect on consumer preference and purchase intention. The findings of this study provide insight into a business model in which online shopping is driven by celebrities. They suggest that online celebrities should pay more attention to product experience sharing, life style association and real-time interaction for managing their product promotions. These are the most salient factors with respect to the relational constructs identified in this study.

Keywords: customer relationship, customer to customer, Internet celebrity, online celebrity, online marketing, purchase intention

Procedia PDF Downloads 305

Authors: Tareq AlNuaim, Mubashir Alam, Abdulrazaq Aldowesh

Abstract:

The usage of micro-Unmanned Ariel Vehicles (UAVs) has witnessed an enormous increase recently. Detection of such drones became a necessity nowadays to prevent any harmful activities. Typically, such targets have low velocity and low Radar Cross Section (RCS), making them indistinguishable from clutter and phase noise. Multiple-Input Multiple-Output (MIMO) Radars have many potentials; it increases the degrees of freedom on both transmit and receive ends. Such architecture allows for flexibility in operation, through utilizing the direct access to every element in the transmit/ receive array. MIMO systems allow for several array processing techniques, permitting the system to stare at targets for longer times, which improves the Doppler resolution. In this paper, a 2×2 MIMO radar prototype is developed using Software Defined Radio (SDR) technology, and its performance is evaluated against a slow-moving low radar cross section micro-UAV used by hobbyists. Radar cross section simulations were carried out using FEKO simulator, achieving an average of -14.42 dBsm at S-band. The developed prototype was experimentally evaluated achieving more than 300 meters of detection range for a DJI Mavic pro-drone

Keywords: digital beamforming, drone detection, micro-UAV, MIMO, phased array

Procedia PDF Downloads 121

Authors: Jun Hong Lee

Abstract:

Background: Many dementia patients complain insomnia and depressive mood, and hypnotics and antidepressants are being prescribed. As prevalence of dementia is increasing, insomnia and depressive mood are becoming more important. Objective: We evaluated insomnia and depression in outpatients of dementia center. Patients and Methods/Material and Methods: We reviewed medical records of the patients who visited outpatients clinic of NHIS Ilsan Hospital Dementia Center during 2016. Results: Total 716 patients are included; Subjective Memory Impairment (SMI) : 143 patients (20%), non-amnestic Mild Cognitive Impairment (MCI): single domain 70 (10%), multiple domain 34 (5%), amnestic MCI: single domain 74 (10%), multiple domain 159 (22%), Early onset Alzheimer´s disease (AD): 9 (1%), AD 121 (17%), Vascular dementia: 62 (9%), Mixed dementia 44 (6%). Hypnotics and antidepressants are prescribed as follows; SMI : hypnotics 14 patients (10%), antidepressants 27 (19%), non-amnestic MCI: single domain hypnotics 9 (13%), antidepressants 12 (17%), multiple domain hypnotics 4 (12%), antidepressants 6 (18%), amnestic MCI: single domain hypnotics 10 (14%), antidepressants 16 (22%), multiple domain hypnotics 22 (14%), antidepressants 24 (15%), Early onset Alzheimer´s disease (AD): hypnotics 1 (11%), antidepressants 2 (22%), AD: hypnotics 10 (8%), antidepressants 36 (30%), Vascular dementia: hypnotics 8 (13%), antidepressants 20 (32%), Mixed dementia: hypnotics 4 (9%), antidepressants 17 (39%). Conclusion: Among the outpatients of Dementia Center, MCI and SMI are majorities, and the number of MCI patients are almost half. Depression is more prevalent in AD, and Vascular dementia than MCI and SMI, and about 22% of patients are being prescribed by antidepressants and 11% by hypnotics.

Keywords: insomnia, depression, dementia, antidepressants, hypnotics

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Authors: Shank Kulkarni, Alireza Tabarraei

Abstract:

The fantastic properties of polyurea such as flexibility, durability, and chemical resistance have brought it a wide range of application in various industries. Effective prediction of the response of polyurea under different loading and environmental conditions necessitates the development of an accurate constitutive model. Similar to most polymers, the behavior of polyurea depends on both strain and strain rate. Therefore, the constitutive model should be able to capture both these effects on the response of polyurea. To achieve this objective, in this paper, a nonlinear hyper-viscoelastic constitutive model is developed by the superposition of a hyperelastic and a viscoelastic model. The proposed constitutive model can capture the behavior of polyurea under compressive loading conditions at various strain rates. Four parameter Ogden model and Mooney Rivlin model are used to modeling the hyperelastic behavior of polyurea. The viscoelastic behavior is modeled using both a three-parameter standard linear solid (SLS) model and a K-BKZ model. Comparison of the modeling results with experiments shows that Odgen and SLS model can more accurately predict the behavior of polyurea. The material parameters of the model are found by curve fitting of the proposed model to the uniaxial compression test data. The proposed model can closely reproduce the stress-strain behavior of polyurea for strain rates up to 6500 /s.

Keywords: constitutive modelling, ogden model, polyurea, SLS model, uniaxial compression test

Procedia PDF Downloads 224

Authors: Hussein Altartouri

Abstract:

In this paper the kinematic and kinetic models of an omnidirectional holonomic mobile robot is presented. The kinematic and kinetic models form the OmniDrive model. Therefore, a mathematical model for the robot equipped with three- omnidirectional wheels is derived. This model which takes into consideration the kinematics and kinetics of the robot, is developed to state space representation. Relative analysis of the velocities and displacements is used for the kinematics of the robot. Lagrange’s approach is considered in this study for deriving the equation of motion. The drive train and the mechanical assembly only of the Festo Robotino® is considered in this model. Mainly the model is developed for motion control. Furthermore, the model can be used for simulation purposes in different virtual environments not only Robotino® View. Further use of the model is in the mechatronics research fields with the aim of teaching and learning the advanced control theories.

Keywords: mobile robot, omni-direction wheel, mathematical model, holonomic mobile robot

Procedia PDF Downloads 575

Authors: Tiao Chang, Ivan Caballero, Hong Zhou

Abstract:

Streams carry water and sediment naturally by maintaining channel dimensions, pattern, and profile over time. Watershed erosion as a natural process has occurred to contribute sediment to streams over time. The formation of channel dimensions is complex. This study is to relate quantifiable and consistent channel dimensions at the bankfull stage to the corresponding watershed erosion estimation by the Revised Universal Soil Loss Equation (RUSLE). Twelve sites of which drainage areas range from 7 to 100 square miles in the Hocking River Basin of Ohio were selected for the bankfull geometry determinations including width, depth, cross-section area, bed slope, and drainage area. The twelve sub-watersheds were chosen to obtain a good overall representation of the Hocking River Basin. It is of interest to determine how these bankfull channel dimensions are related to the soil erosion of corresponding sub-watersheds. Soil erosion is a natural process that has occurred in a watershed over time. The RUSLE was applied to estimate erosions of the twelve selected sub-watersheds where the bankfull geometry measurements were conducted. These quantified erosions of sub-watersheds are used to investigate correlations with bankfull channel dimensions including discharge, channel width, channel depth, cross-sectional area, and pebble distribution. It is found that drainage area, bankfull discharge and cross-sectional area correlates strongly with watershed erosion well. Furthermore, bankfull width and depth are moderately correlated with watershed erosion while the particle size, D50, of channel bed sediment is not well correlated with watershed erosion.

Keywords: watershed, stream, sediment, channel

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Authors: Morsy Ahmed Morsy Ismail

Abstract:

In this paper, the structure of a coherent homodyne receiver for the Binary Phase Shift Keying (BPSK) Optical Code Division Multiple Access (OCDMA) network is introduced based on the Multi-Length Weighted Modified Prime Code (ML-WMPC) for multimedia applications. The Bit Error Rate (BER) of this homodyne detection is evaluated as a function of the number of active users and the signal to noise ratio for different code lengths according to the multimedia application such as audio, voice, and video. Besides, the Mach-Zehnder interferometer is used as an external phase modulator in homodyne detection. Furthermore, the Multiple Access Interference (MAI) and the receiver noise in a shot-noise limited regime are taken into consideration in the BER calculations.

Keywords: OCDMA networks, bit error rate, multiple access interference, binary phase-shift keying, multimedia

Procedia PDF Downloads 155

Authors: Yijun Shao, Yan Cheng, Rashmee U. Shah, Charlene R. Weir, Bruce E. Bray, Qing Zeng-Treitler

Abstract:

Deep neural network (DNN) models are being explored in the clinical domain, following the recent success in other domains such as image recognition. For clinical adoption, outcome prediction models require explanation, but due to the multiple non-linear inner transformations, DNN models are viewed by many as a black box. In this study, we developed a deep neural network model for predicting 1-year mortality of patients who underwent major cardio vascular procedures (MCVPs), using temporal image representation of past medical history as input. The dataset was obtained from the electronic medical data warehouse administered by Veteran Affairs Information and Computing Infrastructure (VINCI). We identified 21,355 veterans who had their first MCVP in 2014. Features for prediction included demographics, diagnoses, procedures, medication orders, hospitalizations, and frailty measures extracted from clinical notes. Temporal variables were created based on the patient history data in the 2-year window prior to the index MCVP. A temporal image was created based on these variables for each individual patient. To generate the explanation for the DNN model, we defined a new concept called impact score, based on the presence/value of clinical conditions’ impact on the predicted outcome. Like (log) odds ratio reported by the logistic regression (LR) model, impact scores are continuous variables intended to shed light on the black box model. For comparison, a logistic regression model was fitted on the same dataset. In our cohort, about 6.8% of patients died within one year. The prediction of the DNN model achieved an area under the curve (AUC) of 78.5% while the LR model achieved an AUC of 74.6%. A strong but not perfect correlation was found between the aggregated impact scores and the log odds ratios (Spearman’s rho = 0.74), which helped validate our explanation.

Keywords: deep neural network, temporal data, prediction, frailty, logistic regression model

Procedia PDF Downloads 138