Search results for: time constraint

Authors: Giorgio Visentin, Alexei A. Buchachenko

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Recent proposals to use Yb dimer as an optical clock and as a sensor for non-Newtonian gravity imply the knowledge of its interaction potential. Here, the ground-state Born-Oppenheimer Yb₂ potential energy curve is represented by a semi-analytical function, consisting of short- and long-range contributions. For the former, the systematic ab initio all-electron exact 2-component scalar-relativistic CCSD(T) calculations are carried out. Special care is taken to saturate diffuse basis set component with the atom- and bond-centered primitives and reach the complete basis set limit through n = D, T, Q sequence of the correlation-consistent polarized n-zeta basis sets. Similar approaches are used to the long-range dipole and quadrupole dispersion terms by implementing the CCSD(3) polarization propagator method for dynamic polarizabilities. Dispersion coefficients are then computed through Casimir-Polder integration. The semiclassical constraint on the number of the bound vibrational levels known for the ¹⁷⁴Yb isotope is used to scale the potential function. The scaling, based on the most accurate ab initio results, bounds the interaction energy of two Yb atoms within the narrow 734 ± 4 cm⁻¹ range, in reasonable agreement with the previous ab initio-based estimations. The resulting potentials can be used as the reference for more sophisticated models that go beyond the Born-Oppenheimer approximation and provide the means of their uncertainty estimations. The work is supported by Russian Science Foundation grant # 17-13-01466.

Keywords: ab initio coupled cluster methods, interaction potential, semi-analytical function, ytterbium dimer

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Authors: Ouafa Amira, Jiangshe Zhang

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Clustering is an unsupervised machine learning technique; its aim is to extract the data structures, in which similar data objects are grouped in the same cluster, whereas dissimilar objects are grouped in different clusters. Clustering methods are widely utilized in different fields, such as: image processing, computer vision , and pattern recognition, etc. Fuzzy c-means clustering (fcm) is one of the most well known fuzzy clustering methods. It is based on solving an optimization problem, in which a minimization of a given cost function has been studied. This minimization aims to decrease the dissimilarity inside clusters, where the dissimilarity here is measured by the distances between data objects and cluster centers. The degree of belonging of a data point in a cluster is measured by a membership function which is included in the interval [0, 1]. In fcm clustering, the membership degree is constrained with the condition that the sum of a data object’s memberships in all clusters must be equal to one. This constraint can cause several problems, specially when our data objects are included in a noisy space. Regularization approach took a part in fuzzy c-means clustering technique. This process introduces an additional information in order to solve an ill-posed optimization problem. In this study, we focus on regularization by relative entropy approach, where in our optimization problem we aim to minimize the dissimilarity inside clusters. Finding an appropriate membership degree to each data object is our objective, because an appropriate membership degree leads to an accurate clustering result. Our clustering results in synthetic data sets, gaussian based data sets, and real world data sets show that our proposed model achieves a good accuracy.

Keywords: clustering, fuzzy c-means, regularization, relative entropy

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Authors: Christina Knorr

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Analysis of the evacuation of occupants of a building plays a significant role in Fire Safety Engineering. One of the tools used for the analysis is the concept of the Required Safe Egress Time (RSET). It is generally accepted that RSET is measured from the time the fire ignites until the time that all occupants have evacuated to a safe location. Instructions on how RSET is determined can be found in both the International Fire Engineering Guidelines and, more recently, in the Australian Fire Engineering Guidelines. The guidelines also specify measures that could be applied to reduce the RSET and hence improve the performance of fire-safety measures of a building. Further, it is suggested that the delay period can be reduced through “training programs.” This study examined the overall level of fire-safety awareness among occupants of residential apartment buildings in Australia and investigated the possible effects of fire-safety training on the delay period and, hence, the RSET. A questionnaire, interviews, and an experiment were conducted to collect data about people’s fire-safety knowledge, people’s behaviour and nature, and the duration of activities people are likely to undertake in the event of a fire. The study led to an investigation into the delay and response time approximations and the development of a new equation to incorporate the impact of training into the RSET calculations for the general use of the fire engineering community. Regardless of the RSET, it can be concluded that fire-safety education and training for residents of apartment buildings have a direct impact on improving their behaviour and firefighting equipment usage in a fire incident.

Keywords: fire safety engineering, fire safety training, occupant evacuation behaviour, required safe egress time

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Authors: Preeti Panthari, Harsha Kharkwal

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Myrica nagi belongs to Myricaceae family. It is known for its therapeutic use since ancient times. The leaves were extracted with methanol and further fractioned with different solvents with increasing polarity. The n-butanol fraction of methanol extract was passed through celite, on separation through silica gel column chromatography yielded ten fractions. For the first time we report isolation of Caffeic acid from n-butanol fraction of Myrica nagi leaves in Chloroform: methanol (70:30) fraction. The mobile phase used for analysis in HPLC was Methanol: water (60:40) at the flow rate of 1 ml/min at wavelength of 280 nm. The retention time was 2.66 mins.

Keywords: Myrica nagi, column chromatography, retention time, caffeic acid

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Authors: Ali W. Alattabi, Khalid S. Hashim, Hassnen M. Jafer, Ali Alzeyadi

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This study was performed to optimise the react time (RT) and study its effects on the removal rates of nitrogen compounds in a sequencing batch reactor (SBR) treating synthetic industrial wastewater. The results showed that increasing the RT from 4 h to 10, 16 and 22 h significantly improved the nitrogen compounds’ removal efficiency, it was increased from 69.5% to 95%, 75.7 to 97% and from 54.2 to 80.1% for NH₃-N, NO₃-N and NO₂-N respectively. The results obtained from this study showed that the RT of 22 h was the optimum for nitrogen compounds removal efficiency.

Keywords: ammonia-nitrogen, retention time, nitrate, nitrite, sequencing batch reactor, sludge characteristics

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Authors: Anne Gesare Timu, Megan Sheahan, Andrew Gache Mude, Rupsha Banerjee

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Women headed households are among the most vulnerable to negative climatic shocks and are often left poorer as a result. Credit provision has been recognized as one way of alleviating rural poverty and developing poor rural households’ resilience to shocks. Much has been documented about credit demand in small-holder agriculture settings in Kenya. However, little is known about demand for credit among pastoral women. This paper analyzes the determinants of demand for credit in the pastoral regions of Marsabit District of Northern Kenya. Using a five wave balanced panel data set of 820 households, a double hurdle model is employed to analyze if shocks, financial literacy and risk aversion affect credit demand among female and male headed households differently. The results show that borrowing goods on credit and monetary credit from informal market segments are the most common sources of credit in the study area. The impact of livestock loss and financial literacy on the decision to borrow and how much to borrow vary with gender. While the paper suggests that provision of credit is particularly valuable in the aftermath of a negative shock and more so for female-headed households, it also explores alternatives to the provision of credit where credit access is a constraint. It recommends further understanding of systems and institutions which could enhance access to credit, and particularly during times of stress, to enable households in the study area in particular and Northern Kenya in general to invest, engage in meaningful development and growth, and be resilient to persistent shocks.

Keywords: female headed households, pastoralism, rural financing, double hurdle model

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Authors: Tayyibah Khanam, Mohammad Saad Alam, Sanchari Deb, Yasser Rafat

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Electric vehicles are considered as viable replacements to gasoline cars since they help in reducing harmful emissions and stimulate power generation through renewable energy sources, hence contributing to sustainability. However, one of the significant obstacles in the mass deployment of electric vehicles is the charging time anxiety among users and, thus, the subsequent large waiting times for available chargers at charging stations. Data analytics, on the other hand, has revolutionized the decision-making tasks of management and operating systems since its arrival. In this paper, we attempt to optimize the choice of EV charging stations for users in their vicinity by minimizing the time taken to reach the charging stations and the waiting times for available chargers. Time taken to travel to the charging station is calculated by the Google Maps API and the waiting times are predicted by polynomial regression of the historical data stored. The proposed framework utilizes real-time data and historical data from all operating charging stations in the city and assists the user in finding the best suitable charging station for their current situation and can be implemented in a mobile phone application. The algorithm successfully predicts the most optimal choice of a charging station and the minimum required time for various sample data sets.

Keywords: charging data, electric vehicles, machine learning, waiting times

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Authors: Varsha Prasad, S. Sandya

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Cosmic Ray effects in microelectronics such as single event effect (SET) and total dose ionization (TID) have been of major concern in space electronics since 1970. Advanced CMOS technologies have demonstrated reduced sensitivity to TID effect. However, charge pump Phase Locked Loop is very much vulnerable to single event transient effect. This paper presents an SET analysis model, where the SET is modeled as a double exponential pulse. The time domain analysis reveals that the settling time of the voltage controlled oscillator (VCO) depends on the SET pulse strength, setting the time constant and the damping factor. The analysis of the proposed SET analysis model is confirmed by the simulation results.

Keywords: charge pump, phase locked loop, SET, VCO

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Authors: Mohd Ishfaq Bhat, Navin Chandra Shahi, Umesh Chandra Lohani

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The present study aimed to evaluate the effect of microwave application in synergy with the conventional sodium chlorite delignification of rice straw biomass. For the study, Box-Behnken experimental design involving four independent parameters, each with three levels viz. microwave power (480-800 W), irradiation time (4-12 min), bleaching solution concentration (0.4-3.0%), and bleaching time (1-5h) was used. The response was taken in the form of delignification percentage. The optimization of process parameters was done through response surface methodology. The respective optimum parameters of microwave power, irradiation time, bleaching solution concentration, and bleaching time were obtained as 671 W, 8.66 min, 2.67%, and 1h. The delignification percentage achieved at optimum conditions was 93.51%. The spectral, morphological, and x-ray diffraction characteristics of the rice straw powder after delignification showed a complete absence of lignin peaks, deconstruction of lignocellulose complex, and an increase of crystallinity (from 39.8 to 61.6 %).

Keywords: lignocellulosic biomass, delignification, microwaves, rice straw, characterization

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Authors: Rajeshwar S. Matche, Subhash V. Pawde, Suraj P, Sachin R. Chaudhari

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Time Temperature Indicator’s (TTI) are trending approach in a food packaging that will be insightful to have safe and hygienic food products. Currently, available TTI in the market are mostly a product specific and sometime even difficult to handle especially in supply chain as these are pre-activated and require specific storage conditions. In the present study, research focus is on the development of a cost-effective lactic acid based TTI that can work over a wide range of temperature and can be activated at time of packaging or on demand. The correlation between activation energies of colour change of the developed indicator and packed pasteurized milk spoilage with respect to time and temperature was established. Developed lactic acid based TTI strips have range of activation energy from 10.13 to 24.20 KJ/mol. We found that the developed TTI strip’s with activation energy 12.42, and 14.41KJ/mol can be correlated with spoilage activation energy of packed pasteurized milk which was 25.71 KJ/mol with factor of 2 at storage temperature 4°C. The implementation of these TTI on packed pasteurized milk allow us see visual colour change during the storage and can be fruitful to monitoring quality of the milk and understand its freshness especially in a cold supply chain, viz distributor and road vendor etc.

Keywords: pasteurised packed milk, time temperature indicator, spoilage, freshness

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Authors: Saeed Zeinali, Nasser Talebbeydokhti, Mehdi Saeidian, Shahrad Vosough

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In this article, bathymetry changes have been studied as a case study for Larak Island, located in The South of Iran. The advanced 2D model of Mike21 has been used for this purpose. A simple procedure has been utilized in this model. First, the hydrodynamic (HD) module of Mike21 has been used to obtain the required output for sediment transport model (ST module). The ST module modeled the area for tidal currents only. Bed level changes are resulted by series of modeling for both HD and ST module in 3 months time step. The final bathymetry in each time step is used as the primary bathymetry for next time step. This consecutive procedure been continued until bathymetry for the year 2020 is obtained.

Keywords: bed level changes, Larak Island, hydrodynamic, sediment transport

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Authors: Romain Ben Taleb, Aurélie Montarnal, Matthieu Lauras, Mathieu Dahan, Romain Miclo

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To be competitive and sustainable, any company has to maximize its value. However, unlike listed companies that can assess their values based on market shares, most Small and Medium Enterprises (SMEs) which are non-listed cannot have direct and live access to this critical information. Traditional accounting reports only give limited insights to SME decision-makers about the real impact of their day-to-day decisions on the company’s performance and value. Most of the time, an SME’s financial valuation is made one time a year as the associated process is time and resource-consuming, requiring several months and external expertise to be completed. To solve this issue, we propose in this paper a value-oriented metamodel that enables real-time and dynamic assessment of the SME’s value based on the large definition of their assets. These assets cover a wider scope of resources of the company and better account for immaterial assets. The proposal, which is illustrated in a case study, discusses the benefits of incorporating assets in the SME valuation.

Keywords: SME, metamodel, decision support system, financial valuation, assets

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Authors: Sani M. Lawal, Idris Musa, Aliyu D. Usman

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The Pareto approach of optimal solutions in a search space that evolved in multi-objective optimization problems is adopted in this paper, which stands for a set of solutions in the search space. This paper aims at presenting an optimal placement of Distributed Generation (DG) in radial distribution networks with an optimal size for minimization of power loss and voltage deviation as well as maximizing voltage profile of the networks. And these problems are formulated using particle swarm optimization (PSO) as a constraint nonlinear optimization problem with both locations and sizes of DG being continuous. The objective functions adopted are the total active power loss function and voltage deviation function. The multiple nature of the problem, made it necessary to form a multi-objective function in search of the solution that consists of both the DG location and size. The proposed PSO algorithm is used to determine optimal placement and size of DG in a distribution network. The output indicates that PSO algorithm technique shows an edge over other types of search methods due to its effectiveness and computational efficiency. The proposed method is tested on the standard IEEE 34-bus and validated with 33-bus test systems distribution networks. Results indicate that the sizing and location of DG are system dependent and should be optimally selected before installing the distributed generators in the system and also an improvement in the voltage profile and power loss reduction have been achieved.

Keywords: distributed generation, pareto, particle swarm optimization, power loss, voltage deviation

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Authors: H. J. Joshi, Satyajeet Patil, Parth Dandavate, Mihir Kulkarni, Harshita Agrawal

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As the world looks towards a sustainable future, electric vehicles have become increasingly popular. Millions worldwide are looking to switch to Electric cars over the previously favored combustion engine-powered cars. This demand has seen an increase in Electric Vehicle Charging Stations. The big challenge is that the randomness of electrical energy makes it tough for these charging stations to provide an adequate amount of energy over a specific amount of time. Thus, it has become increasingly crucial to model these patterns and forecast the energy needs of power stations. This paper aims to analyze how different machine learning models perform on Electric Vehicle charging time-series data. The data set consists of authentic Electric Vehicle Data from the Netherlands. It has an overview of ten thousand transactions from public stations operated by EVnetNL.

Keywords: forecasting, smart grid, electric vehicle load forecasting, machine learning, time series forecasting

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Authors: Ionel Zagan, Vasile Gheorghita Gaitan

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The development of CPUs and of real-time systems based on them made it possible to use time at increasingly low resolutions. Together with the scheduling methods and algorithms, time organizing has been improved so as to respond positively to the need for optimization and to the way in which the CPU is used. This presentation contains both a detailed theoretical description and the results obtained from research on improving the performances of the nMPRA (Multi Pipeline Register Architecture) processor by implementing specific functions in hardware. The proposed CPU architecture has been developed, simulated and validated by using the FPGA Virtex-7 circuit, via a SoC project. Although the nMPRA processor hardware structure with five pipeline stages is very complex, the present paper presents and analyzes the tests dedicated to the implementation of the CPU and of the memory on-chip for instructions and data. In order to practically implement and test the entire SoC project, various tests have been performed. These tests have been performed in order to verify the drivers for peripherals and the boot module named Bootloader.

Keywords: hardware scheduler, nMPRA processor, real-time systems, scheduling methods

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Authors: Nicolò Vaiana, Giorgio Serino

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The nonlinear time history analysis of seismically base-isolated structures can require a significant computational effort when the behavior of each seismic isolator is predicted by adopting the widely used differential equation Bouc-Wen model. In this paper, a nonlinear exponential model, able to simulate the response of seismic isolation bearings within a relatively large displacements range, is described and adopted in order to reduce the numerical computations and speed up the nonlinear dynamic analysis. Compared to the Bouc-Wen model, the proposed one does not require the numerical solution of a nonlinear differential equation for each time step of the analysis. The seismic response of a 3d base-isolated structure with a lead rubber bearing system subjected to harmonic earthquake excitation is simulated by modeling each isolator using the proposed analytical model. The comparison of the numerical results and computational time with those obtained by modeling the lead rubber bearings using the Bouc-Wen model demonstrates the good accuracy of the proposed model and its capability to reduce significantly the computational effort of the analysis.

Keywords: base isolation, computational efficiency, nonlinear exponential model, nonlinear time history analysis

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Authors: Mansouri Nabila, Ben Jemaa Yousra, Motamed Cina, Watelain Eric

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Research and development efforts in intelligent Advanced Driver Assistance Systems (ADAS) seek to save lives and reduce the number of on-road fatalities. For traffic and emergency monitoring, the essential but challenging task is vehicle detection and tracking in reasonably short time. This purpose needs first of all a powerful dynamic car detector model. In fact, this paper presents an optimized HOG process based on shape and motion parameters fusion. Our proposed approach mains to compute HOG by bloc feature from foreground blobs using configurable research window and pathway in order to overcome the shortcoming in term of computing time of HOG descriptor and improve their dynamic application performance. Indeed we prove in this paper that HOG by bloc descriptor combined with motion parameters is a very suitable car detector which reaches in record time a satisfactory recognition rate in dynamic outside area and bypasses several popular works without using sophisticated and expensive architectures such as GPU and FPGA.

Keywords: car-detector, HOG, motion, computing time

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Authors: Khoo Shin Yee, Lian Yee Cheng, Ong Zhi Chao, Zubaidah Ismail, Siamak Noroozi

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Structural frequency response testing is accurate in identifying the dynamic characteristic of a machinery structure. In practical perspective, conventional structural frequency response testing such as experimental modal analysis with impulse technique (also known as “impulse testing”) has limitation especially on its long acquisition time. The high acquisition time is mainly due to the redundancy procedure where the engineer has to repeatedly perform the test in 3 directions, namely the axial-, horizontal- and vertical-axis, in order to comprehensively define the dynamic behavior of a 3D structure. This is unfavorable to numerous industries where the downtime cost is high. This study proposes to reduce the testing time by using oblique impact. Theoretically, a single oblique impact can induce significant vibration responses and vibration modes in all the 3 directions. Hence, the acquisition time with the implementation of the oblique impulse technique can be reduced by a factor of three (i.e. for a 3D dynamic system). This study initiates an experimental investigation of impulse testing with oblique excitation. A motor-driven test rig has been used for the testing purpose. Its dynamic characteristic has been identified using the impulse testing with the conventional normal impact and the proposed oblique impact respectively. The results show that the proposed oblique impulse testing is able to obtain all the desired natural frequencies in all 3 directions and thus providing a feasible solution for a fast and time effective way of conducting the impulse testing.

Keywords: frequency response function, impact testing, modal analysis, oblique angle, oblique impact

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Authors: Salah Menouar, Sara Hassoul

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The dynamic of time-dependent three coupled oscillators is studied through an approach based on decoupling of them using the unitary transformation method. From a first unitary transformation, the Hamiltonian of the complicated original system is transformed to an equal but a simple one associated with the three coupled oscillators of which masses are unity. Finally, we diagonalize the matrix representation of the transformed hamiltonian by using a unitary matrix. The diagonalized Hamiltonian is just the same as the Hamiltonian of three simple oscillators. Through these procedures, the coupled oscillatory subsystems are completely decoupled. From this uncouplement, we can develop complete dynamics of the whole system in an easy way by just examining each oscillator independently. Such a development of the mechanical theory can be done regardless of the complication of the parameters' variations.

Keywords: schrödinger equation, hamiltonian, time-dependent three coupled oscillators, unitary transformation

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Authors: Walid Fantazi

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The development of sensor technology (such as microelectromechanical systems (MEMS), wireless communications, embedded systems, distributed processing and wireless sensor applications) has contributed to a broad range of WSN applications which are capable of collecting a large amount of spatiotemporal data in real time. These systems require real-time data processing to manage storage in real time and query the data they process. In order to cover these needs, we propose in this paper a Snapshot spatiotemporal data model based on object-oriented concepts. This model allows saving storing and reducing data redundancy which makes it easier to execute spatiotemporal queries and save analyzes time. Further, to ensure the robustness of the system as well as the elimination of congestion from the main access memory we propose a spatiotemporal indexing technique in RAM called Captree *. As a result, we offer an RIA (Rich Internet Application) -based SOA application architecture which allows the remote monitoring and control.

Keywords: WSN, indexing data, SOA, RIA, geographic information system

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Authors: Alejandro Rodríguez-Molinero, Carlos Pérez-López, Jorge Hernández-Vara, Àngels Bayes-Rusiñol, Juan Carlos Martínez-Castrillo, David A. Pérez-Martínez

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Background: Monitoring motor symptoms in Parkinson's patients is often a complex and time-consuming task for clinicians, as Hauser's diaries are often poorly completed by patients. Recently, new automatic devices (Parkinson's holter: STAT-ON®) have been developed capable of monitoring patients' motor fluctuations. The MoMoPa-EC clinical trial (NCT04176302) investigates which of the two methods produces better clinical results. In this sub-analysis, the concordance between both methods is analyzed. Methods: In the MoMoPa-EC clinical trial, 164 patients with moderate-severe Parkinson's disease and at least two hours a day of Off will be included. At the time of patient recruitment, all of them completed a seven-day motor fluctuation diary at home (Hauser’s diary) while wearing the Parkinson's holter. In this sub-analysis, 71 patients with complete data for the purpose of this comparison were included. The intraclass correlation coefficient was calculated between the patient diary entries and the Parkinson's holter data in terms of time On, Off, and time with dyskinesias. Results: The intra-class correlation coefficient of both methods was 0.57 (95% CI: 0.3-0.74) for daily time in Off (%), 0.48 (95% CI: 0.14-0.68) for daily time in On (%), and 0.37 (95% CI %: -0.04-0.62) for daily time with dyskinesias (%). Conclusions: Both methods have a moderate agreement with each other. We will have to wait for the results of the MoMoPa-EC project to estimate which of them has the greatest clinical benefits. Acknowledgment: This work is supported by AbbVie S.L.U, the Instituto de Salud Carlos III [DTS17/00195], and the European Fund for Regional Development, 'A way to make Europe'.

Keywords: Parkinson, sensor, motor fluctuations, dyskinesia

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Authors: Ersin Sener, Ibrahim Demir, Hasan Aykut Karaboga, Kadir Kilinc

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Bayesian methods, which have very wide range of applications, are implemented to the data obtained from the production of F class fly ash-based geopolymer bricks’ experimental design. In this study, dependent variable is compressive strength, independent variables are treatment type (oven and steam), treatment time, molding time, temperature, water absorbtion ratio and density. The effect of independent variables on compressive strength is investigated. There is no difference among treatment types, but there is a correlation between independent variables. Therefore, hierarchical Bayesian path analysis is applied. In consequence of analysis we specified that treatment time, temperature and density effects on compressive strength is higher, molding time, and water absorbtion ratio is relatively low.

Keywords: experimental design, F class fly ash, geopolymer bricks, hierarchical Bayesian path analysis

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Authors: Aswathi Thrivikraman, S. Advaith

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The study is aimed at designing encoders for deciphering intricacies in time series data by redescribing the dynamics operating on a lower-dimensional manifold. A semi-supervised LSTM autoencoder is devised and investigated to see if the latent representation of the time series data can better forecast the data. End-to-end training of the LSTM autoencoder, together with another LSTM network that is connected to the latent space, forces the hidden states of the encoder to represent the most meaningful latent variables relevant for forecasting. Furthermore, the study compares the predictions with those of a traditional seq2seq model.

Keywords: LSTM, autoencoder, forecasting, seq2seq model

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Authors: Savaş Karpuz, Sami Küçükşen

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The aim of this study is to investigate the effectiveness of neurological rehabilitation in patients with traumatic brain injury. Participants were 45 consecutive adults with traumatic brain injury who were received the neurologic rehabilitation. Sociodemographic characteristics of the patients, the cause of the injury, the duration of the coma and posttraumatic amnesia, the length of stay in the other inpatient clinics before rehabilitation, the time between injury and admission to the rehabilitation clinic, and the length of stay in the rehabilitation clinic were recorded. The differences in functional status between admission and discharge were determined with Disability Rating Scale (DRS), Functional Independence Measure (FIM), and Functional Ambulation Scale (FAS) and levels of cognitive functioning determined with Ranchos Los Amigos Scale (RLAS). According to admission time, there was a significant improvement identified in functional status of patients who had been given the intensive in-hospital cognitive rehabilitation program. At discharge time, the statistically significant differences were obtained in DRS, FIM, FAS and RLAS scores according to admission time. Better improvement in functional status was detected in patients with lower scores in DRS, and higher scores FIM and RLAS scores at the entry time. The neurologic rehabilitation significantly affects the recovery of functional status after traumatic brain injury.

Keywords: traumatic brain injury, rehabilitation, functional status, neurological

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Authors: Aziz Sezgin, Yuksel Hacioglu, Nurkan Yagiz

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Sliding mode controller for a vehicle active suspension system is designed in this study. The widely used quarter car model is preferred and it is aimed to improve the ride comfort of the passengers. The effect of the actuator time delay, which may arise due to the information processing, sensors or actuator dynamics, is also taken into account during the design of the controller. A sliding mode controller was designed that has taken into account the actuator time delay by using Smith predictor. The successful performance of the designed controller is confirmed via numerical results.

Keywords: sliding mode control, active suspension system, actuator, time delay, vehicle

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Authors: Fatemeh Sadat Miri, Morteza Ehsani, Seyed Farshid Hosseini

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The present research is concerned with the optimization of extrusion parameters of ABS sheets by the Taguchi experimental design method. In this design method, three parameters of % recycling ABS, processing temperature and degassing time on mechanical properties, hardness, HDT, and color matching of ABS sheets were investigated. The variations of this research are the dosage of recycling ABS, processing temperature, and degassing time. According to experimental test data, the highest level of tensile strength and HDT belongs to the sample with 5% recycling ABS, processing temperature of 230°C, and degassing time of 3 hours. Additionally, the minimum level of MFI and color matching belongs to this sample, too. The present results are in good agreement with the Taguchi method. Based on the outcomes of the Taguchi design method, degassing time has the most effect on the mechanical properties of ABS sheets.

Keywords: ABS, process optimization, Taguchi, mechanical properties

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Authors: Zhdanova A. O., Volkov R. S., Kuznetsov G. V., Strizhak P. A.

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Fires in different types of facilities are a serious problem worldwide.It is still an unaccomplished science and technology objective to establish the minimum number and type of sensors in automatic systems of compartment fire suppression which would turn the fire-extinguishing agent spraying on and off in real time depending on the state of the fire, minimize the amount of agent applied, delay time in fire suppression and system response, as well as the time of combustion suppression. Based on the results of experimental studies, the conclusion was made that it is reasonable to use a gas analysis system and heat sensors (in the event of their prior activation) to determine the effectiveness of fire suppression (fire-extinguishing composition interacts with the fire). Thus, the concentration of CO in the interaction of the firefighting liquid with the fire increases to 0.7–1.2%, which indicates a slowdown in the flame combustion, and heat sensors stop responding at a gas medium temperature below 80 ºC, which shows a gradual decrease in the heat release from the fire. The evidence from this study suggests that the information received from the video recording equipment (video camera) should be used in real time as an additional parameter confirming fire suppression. Research was supported by Russian Science Foundation (project No 21-19-00009, https://rscf.ru/en/project/21-19-00009/).

Keywords: compartment fires, fire suppression, continuous control of fire behavior, feedback systems

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Authors: Chin-Chia Jane

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In a transportation network, travel time refers to the transmission time from source node to destination node, whereas reliability refers to the probability of a successful connection from source node to destination node. With an increasing emphasis on quality of service (QoS), both performance indexes are significant in the design and analysis of transportation systems. In this work, we extend the well-known flow network model for transportation networks so that travel time and reliability are integrated into the QoS measurement simultaneously. In the extended model, in addition to the general arc capacities, each intermediate node has a time weight which is the travel time for per unit of commodity going through the node. Meanwhile, arcs and nodes are treated as binary random variables that switch between operation and failure with associated probabilities. For pre-specified travel time limitation and demand requirement, the QoS of a transportation network is the probability that source can successfully transport the demand requirement to destination while the total transmission time is under the travel time limitation. This work is pioneering, since existing literatures that evaluate travel time reliability via a single optimization path, the proposed QoS focuses the performance of the whole network system. To compute the QoS of transportation networks, we first transfer the extended network model into an equivalent min-cost max-flow network model. In the transferred network, each arc has a new travel time weight which takes value 0. Each intermediate node is replaced by two nodes u and v, and an arc directed from u to v. The newly generated nodes u and v are perfect nodes. The new direct arc has three weights: travel time, capacity, and operation probability. Then the universal set of state vectors is recursively decomposed into disjoint subsets of reliable, unreliable, and stochastic vectors until no stochastic vector is left. The decomposition is made possible by applying existing efficient min-cost max-flow algorithm. Because the reliable subsets are disjoint, QoS can be obtained directly by summing the probabilities of these reliable subsets. Computational experiments are conducted on a benchmark network which has 11 nodes and 21 arcs. Five travel time limitations and five demand requirements are set to compute the QoS value. To make a comparison, we test the exhaustive complete enumeration method. Computational results reveal the proposed algorithm is much more efficient than the complete enumeration method. In this work, a transportation network is analyzed by an extended flow network model where each arc has a fixed capacity, each intermediate node has a time weight, and both arcs and nodes are independent binary random variables. The quality of service of the transportation network is an integration of customer demands, travel time, and the probability of connection. We present a decomposition algorithm to compute the QoS efficiently. Computational experiments conducted on a prototype network show that the proposed algorithm is superior to existing complete enumeration methods.

Keywords: quality of service, reliability, transportation network, travel time

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Authors: Meng-Chyi Wu, Bonn Lin, Jyun-Hao Liao, Chein-Ju Chen, Yu-Cheng Jhuang, Mau-Phon Houng, Fang-Hsing Wang, Min-Chu Liu, Cheng-Fu Yang, Cheng-Shong Hong

Abstract:

Since the use of wireless communications has become critical nowadays, the available RF spectrum has become limited. Ultraviolet (UV) communication system can alleviate the spectrum constraint making UV communication system a potential alternative to future communication demands. Also, UV links can provide faster communication rate and can be used in combination with existing RF communication links, providing new communications diversity with higher user capacity. The UV region of electromagnetic spectrum has been of interest to detector, imaging and communication technologies because the stratospheric ozone layer effectively absorbs some solar UV radiation from reaching the earth surface. The wavebands where most of UV radiation is absorbed by the ozone are commonly known as the solar blind region. By operating in UV-C band (200-280 nm) the communication system can minimize the transmission power consumption since it will have less radiation noise. UV communication uses the UV ray as the medium. Electric signal is carried on this band after being modulated and then be transmitted within the atmosphere as channel. Though the background noise of UV-C communication is very low owing to the solar-blind feature, it leads to a large propagation loss. The 370 nm UV provides a much lower propagation loss than that the UV-C does and the recent device technology for UV source on this band is more mature. The fabricated 370 nm AlGaN light-emitting diodes (LEDs) with an aperture size of 45 m exhibit a modulation bandwidth of 165 MHz at 30 mA and a high power of 7 W/cm2 at 230 A/cm2. In order to solve the problem of low power in single UV LED, a UV LED array is presented in.

Keywords: ultraviolet (UV) communication, light-emitting diodes (LEDs), modulation bandwidth, LED array, 370 nm

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Authors: N. Ammouchi

Abstract:

We have studied the effect of milling time on the structural and hyperfine properties of Ni45Al45Fe10 compound elaborated by mechanical alloying. The elaboration was performed by using the planetary ball mill at different milling times. The as milled powders were characterized by X-ray diffraction (XRD) and Mӧssbauer spectroscopy. From XRD diffraction spectra, we show that the β NiAl(Fe) was completely formed after 24 h of milling time. When the milling time increases, the lattice parameter increases, whereas the grain size decreases to a few nanometres and the mean level of microstrains increases. The analysis of Mӧssbauer spectra indicates that, in addition to a ferromagnetic phase, α-Fe, a paramagnetic disordered phase Ni Al (Fe) solid solution is observed after 2h and only this phase is present after 12h.

Keywords: NiAlFe, nanostructured powders, X-ray diffraction, Mӧssbauer spectroscopy

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