Search results for: models synthesis

Authors: A. A. A. Aboalnour, Ahmed M. Amasaib, Mohammed-Almujtaba A. Mohammed-Farah, Abdelhakam, A. Noreldien

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This paper presents a design and study of Parabolic Trough Solar Collector (PTC). Mathematical models were used in this work to find the direct and reflected solar radiation from the air layer on the surface of the earth per hour based on the total daily solar radiation on a horizontal surface. Also mathematical models had been used to calculate the radiation of the tilted surfaces. Most of the ingredients used in this project as previews data required on several solar energy applications, thermal simulation, and solar power systems. In addition, mathematical models had been used to study the flow of the fluid inside the tube (receiver), and study the effect of direct and reflected solar radiation on the pressure, temperature, speed, kinetic energy and forces of fluid inside the tube. Finally, the mathematical models had been used to study the (PTC) performances and estimate its thermal efficiency.

Keywords: CFD, experimental, mathematical models, parabolic trough, radiation

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Authors: Alireza Vafaei Sadr, Vida Abedi, Jiang Li, Ramin Zand

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Missing data is a common challenge in medical research and can lead to biased or incomplete results. When the data bias leaks into models, it further exacerbates health disparities; biased algorithms can lead to misclassification and reduced resource allocation and monitoring as part of prevention strategies for certain minorities and vulnerable segments of patient populations, which in turn further reduce data footprint from the same population – thus, a vicious cycle. This study compares the performance of six imputation techniques grouped into Linear and Non-Linear models on two different realworld electronic health records (EHRs) datasets, representing 17864 patient records. The mean absolute percentage error (MAPE) and root mean squared error (RMSE) are used as performance metrics, and the results show that the Linear models outperformed the Non-Linear models in terms of both metrics. These results suggest that sometimes Linear models might be an optimal choice for imputation in laboratory variables in terms of imputation efficiency and uncertainty of predicted values.

Keywords: EHR, machine learning, imputation, laboratory variables, algorithmic bias

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Authors: Julio Macedo

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Several methodologies are now available to conceive the improvements of a process so that it becomes competitive as for example total quality, process reengineering, six sigma, define measure analysis improvement control method. These improvements are of different nature and can be external to the process represented by an optimization model or a discrete simulation model. In addition, the process stakeholders are several and have different desired performances for the process. Hence, the methodologies above do not have a tool to aid in the conception of the required improvements. In order to fill this void we suggest the use of intelligent reference models. A reference model is a set of qualitative differential equations and an objective function that minimizes the gap between the current and the desired performance indexes of the process. The reference models are intelligent so when they receive the current state of the problematic process and the desired performance indexes they generate the required improvements for the problematic process. The reference models are fuzzy cognitive maps added with an objective function and trained using the improvements implemented by the high performance firms. Experiments done in a set of students show the reference models allow them to conceive more improvements than students that do not use these models.

Keywords: continuous improvement, fuzzy cognitive maps, process competitiveness, qualitative simulation, system dynamics

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Authors: Suriya

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Rapid socio-economic development and urbanization have led to an increasingly serious air pollution problem in Ulaanbaatar (UB), the capital of Mongolia. PM₂.₅ pollution has become the most pressing aspect of UB air pollution. Therefore, monitoring and predicting PM₂.₅ concentration in UB is of great significance for the health of the local people and environmental management. As of yet, very few studies have used models to predict PM₂.₅ concentrations in UB. Using data from 0:00 on June 1, 2018, to 23:00 on April 30, 2020, we proposed two deep learning models based on Bayesian-optimized LSTM (Bayes-LSTM) and CNN-LSTM. We utilized hourly observed data, including Himawari8 (H8) aerosol optical depth (AOD), meteorology, and PM₂.₅ concentration, as input for the prediction of PM₂.₅ concentrations. The correlation strengths between meteorology, AOD, and PM₂.₅ were analyzed using the gray correlation analysis method; the comparison of the performance improvement of the model by using the AOD input value was tested, and the performance of these models was evaluated using mean absolute error (MAE) and root mean square error (RMSE). The prediction accuracies of Bayes-LSTM and CNN-LSTM deep learning models were both improved when AOD was included as an input parameter. Improvement of the prediction accuracy of the CNN-LSTM model was particularly enhanced in the non-heating season; in the heating season, the prediction accuracy of the Bayes-LSTM model slightly improved, while the prediction accuracy of the CNN-LSTM model slightly decreased. We propose two novel deep learning models for PM₂.₅ concentration prediction in UB, Bayes-LSTM, and CNN-LSTM deep learning models. Pioneering the use of AOD data from H8 and demonstrating the inclusion of AOD input data improves the performance of our two proposed deep learning models.

Keywords: deep learning, AOD, PM2.5, prediction, Ulaanbaatar

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Authors: Y. N. Phang, E. F. Loh

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Many researchers have suggested the use of zero inflated Poisson (ZIP) and zero inflated negative binomial (ZINB) models in modeling over-dispersed medical count data with extra variations caused by extra zeros and unobserved heterogeneity. The studies indicate that ZIP and ZINB always provide better fit than using the normal Poisson and negative binomial models in modeling over-dispersed medical count data. In this study, we proposed the use of Zero Inflated Inverse Trinomial (ZIIT), Zero Inflated Poisson Inverse Gaussian (ZIPIG) and zero inflated strict arcsine models in modeling over-dispersed medical count data. These proposed models are not widely used by many researchers especially in the medical field. The results show that these three suggested models can serve as alternative models in modeling over-dispersed medical count data. This is supported by the application of these suggested models to a real life medical data set. Inverse trinomial, Poisson inverse Gaussian, and strict arcsine are discrete distributions with cubic variance function of mean. Therefore, ZIIT, ZIPIG and ZISA are able to accommodate data with excess zeros and very heavy tailed. They are recommended to be used in modeling over-dispersed medical count data when ZIP and ZINB are inadequate.

Keywords: zero inflated, inverse trinomial distribution, Poisson inverse Gaussian distribution, strict arcsine distribution, Pearson’s goodness of fit

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Authors: Jihye Jeon

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This paper analyzes the conceptual framework of three statistical methods, multiple regression, path analysis, and structural equation models. When establishing research model of the statistical modeling of complex social phenomenon, it is important to know the strengths and limitations of three statistical models. This study explored the character, strength, and limitation of each modeling and suggested some strategies for accurate explaining or predicting the causal relationships among variables. Especially, on the studying of depression or mental health, the common mistakes of research modeling were discussed.

Keywords: multiple regression, path analysis, structural equation models, statistical modeling, social and psychological phenomenon

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Authors: Mehdi Rahimi-Nasrabadi, Seied Mahdi Pourmortazavi

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Taguchi robust design as a statistical method was applied for optimization of the process parameters in order to tunable, simple and fast synthesis of europium (III) tungstate nanoparticles. Europium (III) tungstate nanoparticles were synthesized by a chemical precipitation reaction involving direct addition of europium ion aqueous solution to the tungstate reagent solved in aqueous media. Effects of some synthesis procedure variables i.e., europium and tungstate concentrations, flow rate of cation reagent addition, and temperature of reaction reactor on the particle size of europium (III) tungstate nanoparticles were studied experimentally in order to tune particle size of europium (III) tungstate. Analysis of variance shows the importance of controlling tungstate concentration, cation feeding flow rate and temperature for preparation of europium (III) tungstate nanoparticles by the proposed chemical precipitation reaction. Finally, europium (III) tungstate nanoparticles were synthesized at the optimum conditions of the proposed method and the morphology and chemical composition of the prepared nano-material were characterized by means of X-Ray diffraction, scanning electron microscopy, transmission electron microscopy, FT-IR spectroscopy, and fluorescence.

Keywords: europium (III) tungstate, nano-material, particle size control, procedure optimization

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Authors: Jasneet Kaur, Swapandeep Singh Chimni

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The unfavorable use of metal-based catalysts that are often extortionate and toxic can be overcome by using small organic molecules known as organocatalysts. A variety of small organic molecules, including Brønsted/Lewis bases and acids, based on sulfonic acids, phosphoric acids, amines, phosphines or carbenes, Cinchona alkaloids, have been used as organocatalysts. One of the key reasons for using organocatalysis is their ability to be effectively removed from the final product in comparison to the metallic counterparts, which are exceedingly difficult to remove. The present investigation seeks to explore the catalytic nature of Cinchona alkaloids as an organocatalyst for enantioselective synthesis of 3-substituted-3-aminooxindole, which is known to exhibit a variety of biological activities and pharmacological activities. In this context, an organocatalytic asymmetric route for the synthesis of 3-aminooxindoles via reaction of isatin imine with α-acetoxy-β-ketoesters has been developed. The bifunctional Cinchona derived thiourea catalyzed the reaction of α-acetoxy-β-ketoesters derivatives with isatin imine to afford 3-substituted-aminooxindole derivatives in up to 93% yield, 95% enantiomeric excess and >20:1 diastereomeric ratio. The reaction was performed at room temperature for two hours using 10 mol% of catalyst, in the presence of 4Å molecular sieves in tetrahydrofuran as a solvent at ambient temperature. After the completion of the reaction, the pure product could be easily separated by using column chromatography using hexane and ethyl acetate as solvents. In conclusion, the catalytic potential of Cinchona derived chiral thiourea-tertiary amine catalyst was explored for an organocatalytic enantioselective Mannich reaction of β-ketoester derivatives with various isatin imine derivatives under mild conditions.

Keywords: asymmetric synthesis, aminooxindoles, enantioselective, isatin imine

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Authors: Tasnuva Tamanna, Aimin Yu

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Application of nanoscience in biomedical field has come across as a new era. This study involves the synthesis of nano drug carrier with antibiotic loading. Based on the founding that polydopamine (PDA) nanoparticles could be formed via self-polymerization of dopamine at alkaline pH, one-step synthesis of rifampicin coupled polydopamine (PDA-R) nanoparticles was achieved by adding rifampicin into the dopamine solution. The successful yield of PDA nanoparticles with or without the presence of rifampicin during the polymerization process was characterized by scanning electron microscopy, Fourier transform infrared spectroscopy, and Raman spectroscopy. Drug loading was monitored by UV-vis spectroscopy and the loading efficiency of rifampicin was calculated to be 76%. Such highly capacious nano-reservoir was found very stable with little drug leakage at pH 3.

Keywords: drug loading, nanoparticles, polydopamine, rifampicin

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Authors: Flavio Cordeiro Fontanella, Asla Medeiros e Sá, Moacyr Alvim Horta Barbosa da Silva

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In the present work, we analyse the performance of football results forecasting models. In order to do so, we have performed the data collection from eight different forecasting models during the 2021 Brazilian football season. First, we guide the analysis through visual representations of the data, designed to highlight the most prominent features and enhance the interpretation of differences and similarities between the models. We propose using a 2-simplex triangle to investigate visual patterns from the results forecasting models. Next, we compute the expected points for every team playing in the championship and compare them to the final league standings, revealing interesting contrasts between actual to expected performances. Then, we evaluate forecasts’ accuracy using the Ranked Probability Score (RPS); models comparison accounts for tiny scale differences that may become consistent in time. Finally, we observe that the Wisdom of Crowds principle can be appropriately applied in the context, driving into a discussion of results forecasts usage in practice. This paper’s primary goal is to encourage football forecasts’ performance discussion. We hope to accomplish it by presenting appropriate criteria and easy-to-understand visual representations that can point out the relevant factors of the subject.

Keywords: accuracy evaluation, Brazilian championship, football results forecasts, forecasting models, visual analysis

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Authors: Andrey V. Samokhin, Nikolay V. Alekseev, Mikhail A. Sinaiskii

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The report presents the results of R&D of plasma-chemical production of W, W-Cu, W-Ni-Fe nanopowders as well as spherical micropowders of these compounds for their use in modern 3D printing technologies. Plasma-chemical synthesis of nanopowdersis based on the reduction of tungsten oxide compounds powders in a stream of hydrogen-containing low-temperature thermal plasma generated in an electric arc plasma torch. The synthesis of W-Cu and W-Ni-Fe nanocompositesiscarried out using the reduction of a mixture of the metal oxides. Using the synthesized tungsten-based nanocomposites powders, spherical composite micropowders with a submicron structure canbe manufactured by spray dryinggranulation of nanopowder suspension and subsequent densification and spheroidization of granules by melting in a low-temperature thermal plasma flow. The DC arc plasma systems are usedfor the synthesis of nanopowdersas well as for the spheroidization of microgranuls. Plasma systems have a capacity of up to 1 kg/h for nanopowder and up to 5 kg/h for spheroidized powder. All synthesized nanopowders consist of aggregated particles with sizes less than 100 nm, and nanoparticles of W-Cu and W-Ni-Fe composites have core (W) –shell (Cu or Ni-Fe) structures. The resulting dense spherical microparticles with a size of 20-60 microns have a submicron structure with a uniform distribution of metals over the particle volume. The produced tungsten-based nano- and spherical micropowderscan be used to develop new materials and manufacture products using advanced modern technologies.

Keywords: plasma, powders, production, tungsten-based

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Authors: Haythem Barrak, Gaetan Laroche, Adel M’nif, Ahmed Hichem Hamzaoui

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The use of semiconductor oxides, as chemical or biological, requires their functionalization with appropriate dependent molecules of the substance to be detected. generally, the support materials used are TiO2 and SiO2. In the present work, we used zinc oxide (ZnO) known for its interesting physical properties. The synthesis of nano scale ZnO was performed by co-precipitation at low temperature (60 ° C).To our knowledge, the obtaining of this material at this temperature was carried out for the first time. This shows the low cost of this operation. On the other hand, the surface functionalization of ZnO was performed with (3-aminopropyl) triethoxysilane (APTES) by using a specific method using ethanol for the first time. In addition, the duration of this stage is very low compared to literature. The samples obtained were analyzed by XRD, TEM, DLS, FTIR, and TGA shows that XPS that the operation of grafting of APTES on our support was carried out with success.

Keywords: functionalization, nanoparticle, ZnO, APTES, caractérisation

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Authors: A. Esra Pişkin, L. Yusuf Yivlik

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Polyurethane consumption in the world increases every year. Polyetherpolyol, which is the main raw material of polyurethane, is produced from petroleum, and bioresources are needed in polyol production due to the damage it causes to the environment and the consumption of too much energy during the production phase. In this present work, bio polyol was synthesized with castor oil and soybean oil, and its use in rigid polyurethane systems was investigated. Transesterification and ring opening methods were applied for polyol synthesis, and the obtained bio polyols were compared with polyols derived petroleum. The goal of the present study was to synthesize biopolyols and to investigate the mechanical, thermal, and chemical properties of the synthesized polyurethane in terms of bio polyols.

Keywords: polyurethane, polyol, biopolyol, vegetable oil, foam, rigid polyurethane foam, ring opening, transesterification

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Authors: M. I. Youssef, A. E. Emam, M. Abd Elghany

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The performance of wireless communication systems is affected mainly by the environment of its associated channel, which is characterized by dynamic and unpredictable behavior. In this paper, different statistical earth-satellite channel models are studied with emphasize on two main models, first is the Rice-Log normal model, due to its representation for the environment including shadowing and multi-path components that affect the propagated signal along its path, and a three-state model that take into account different fading conditions (clear area, moderate shadow and heavy shadowing). The provided models are based on AWGN, Rician, Rayleigh, and log-normal distributions were their Probability Density Functions (PDFs) are presented. The transmission system Bit Error Rate (BER), Peak-Average-Power Ratio (PAPR), and the channel capacity vs. fading models are measured and analyzed. These simulations are implemented using MATLAB tool, and the results had shown the performance of transmission system over different channel models.

Keywords: fading channels, MIMO communication, RNS scheme, statistical modeling

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Authors: B. M. Patil

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Calcium Zirconate (CaZrO3) has high protonic conductivities at elevated temperature in water or hydrogen atmosphere. Undoped calcium zirconate acts as a p-type semiconductor in air. In this paper, we reported synthesis of CaZrO3 nanoparticles via modified molecular precursor method. The precursor calcium zirconium oxalate (CZO) was synthesized by exchange reaction between freshly generated aqueous solution of sodium zirconyl oxalate and calcium acetate at room temperature. The controlled pyrolysis of CZO in air at 700°C for one hour resulted in the formation nanocrystalline CaZrO3 powder. CaZrO3 obtained by the present method was characterized by Simultaneous thermogravimetry and differential thermogravimetry (TG-DTA), X-ray diffraction (XRD), infra-red spectroscopy and transmission electron microscopy (TEM). The pellets of synthesized CaZrO3 fabricated, sintered at 1000°C for 5 hr and tested as sensors for NO2 and NH3 gases.

Keywords: CaZrO3, CZO, NO2, NH3

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Authors: Debora Gottardello, Mireia Valverde Aparicio, Juan Llopis Taverner

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Globalization has given rise to a great diversity in the composition of people in organizations. Diversity management is therefore key to create growth in today’s competitive global marketplace. This work develops a literature review related to the existing models for managing diversity covering the period from 1980 until 2014. Furthermore, it identifies limitations in previous models. More specifically, the literature review reveals that there is a lack of information about how these models can be adapted from the headquarters to the subsidiaries. Therefore, the contribution of this paper is to suggest how the models should be adapted when they are directed to host countries. Our aim is to highlight the limitations of the developed models with regards to the translation of the diversity management practices to the subsidiaries. Accordingly, a model that will enable MNCs to ensure a global strategy is suggested. Taking advantage of the potential incorporated in a culturally diverse work team should be at the top of every international company’s aims. Executives from headquarters need to use different attitudes when transferring diversity practices towards their subsidiaries. Further studies should reassess local practices of diversity management to find out how this universal management model is translated.

Keywords: culture diversity, diversity management, human resources management, MNCs, subsidiaries, workforce diversity

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Authors: Ana Jurkeviciute, Larisa Grigorieva, Ksenia Moskvinа

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Oil shale alkylresorcinols are formed as a by-product in oil shale processing. They are unique raw material for chemical industry. Polycondensation resins obtaining is one of the worthwhile directions of oil shale alkylresorcinols use. These resins are widely applied in many branches of industry such as wood-working, metallurgic, tire, rubber products, construction etc. Possibility of resins obtaining using overall alkylresorcinols will allow to cheapen finished products on their base and to widen the range of resins offered on the market. Synthesis of polycondensation resins on the basis of alkylresorcinols was conducted by several methods in the process of investigations. In the formulations a part of resorcinol was replaced by fractions of oil shale alkylresorcinols containing different amount of 5-methylresorcinol (40-80 mass %). Some resins were modified by aromatic alkene at the stage of synthesis. Thermal stability and degradation behavior of resins were investigated by thermogravimetric analysis (TGA) method both in an inert nitrogen environment and in an oxidative environment of air. TGA integral curves were obtained and processed in dynamic mode for interval of temperatures from 25 to 830 °C. Rate of temperature rise was 5°C/min, gas flow rate - 50 ml/min. Resins power for carbonization was evaluated by carbon residue. Physical-chemical parameters of the resins were determined. Content of resorcinol and 5-methylresorcinol not reacted in the process of synthesis were determined by gas chromatography method.

Keywords: resorcinol, oil shale alkylresorcinols, aromatic alkene, polycondensation resins, modified resins

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Authors: Kyaw Zin Htut

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In this article, the synthesis of the efficiency of intelligent diagnostic system in the aircraft measuring devices is described. The technology developments of the diagnostic system are considered based on the model errors of the gyro instruments, which are used to measure the parameters of the aircraft. The synthesis of the diagnostic intelligent system is considered on the example of the problem of assessment and forecasting errors of the gyroscope devices on the onboard aircraft. The result of the system is to detect of faults of the aircraft measuring devices as well as the analysis of the measuring equipment to improve the efficiency of its work.

Keywords: diagnostic, dynamic system, errors of gyro instruments, model errors, assessment, prognosis

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Authors: Aldin Justin Sundararaj, Austin Lord Tennyson, Divya Jose, A. N. Subash

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Blast waves are generated due to the explosions of high energy materials. An explosion yielding a blast wave has the potential to cause severe damage to buildings and its personnel. In order to understand the physics of effects of blast pressure on buildings, studies in the shock tube on generic configurations are carried out at various pressures on discrete models. The strength of shock wave is systematically varied by using different driver gases and diaphragm thickness. The basic material of the diaphragm is Aluminum. To simulate the effect of shock waves on discrete models a shock tube was used. Generic models selected for this study are suitably scaled cylinder, cone and cubical blocks. The experiments were carried out with 2mm diaphragm with burst pressure ranging from 28 to 31 bar. Numerical analysis was carried out over these discrete models. A 3D model of shock-tube with different discrete models inside the tube was used for CFD computation. It was found that cone has dissipated most of the shock pressure compared to cylinder and cubical block. The robustness and the accuracy of the numerical model were validation with the analytical and experimental data.

Keywords: shock wave, blast wave, discrete models, shock tube

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Authors: Ayed S. Al-Shihri, Abul Kalam, Abdullah G. Al-Sehemi, Gaohui Du, Tokeer Ahmad, Ahmad Irfan

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We report here the synthesis of nickel oxide (NiO) nanoparticles by microwave-assisted method, using a common precipitating agent followed by calcination in air at 400°C. The effect of the microwave and pH on the crystallite size, morphology, structure, energy band gap and surface area of NiO have been investigated by means of powder X-ray diffraction (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM), high resolution transmission electron microscopy (HRTEM), Fourier transform infrared spectroscopy (FTIR), ultraviolet visible spectroscopy (UV-vis) and BET surface area studies. X-ray diffraction studies showed the formation of monophasic and highly crystalline cubic NiO. TEM analysis led to decrease the average grain size of NiO nanoparticles from 16.5 nm to 14 nm on increasing the amount of NaOH. FTIR studies also confirm the formation of NiO nanoparticles. It was observed that on increasing the volume of NaOH, the optical band gap energy (2.85 eV to 2.95 eV) and specific surface area (33.1 to 39.8 m2/g) increases, however the average particles size decreases (16.5 nm to 14 nm). This method may be extended to large scale synthesis of other metal oxides nanoparticles and the present study could be used for the potential applications in water treatment and many other fields.

Keywords: BET surface area analysis, electron microscopy, optical properties, X-ray techniques

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Authors: Seyoung Kim, Jeongmin Kim, Kwang Ryel Ryu

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A database that records average traffic speeds measured at five-minute intervals for all the links in the traffic network of a metropolitan city. While learning from this data the models that can predict future traffic speed would be beneficial for the applications such as the car navigation system, building predictive models for every link becomes a nontrivial job if the number of links in a given network is huge. An advantage of adopting k-nearest neighbor (k-NN) as predictive models is that it does not require any explicit model building. Instead, k-NN takes a long time to make a prediction because it needs to search for the k-nearest neighbors in the database at prediction time. In this paper, we investigate how much we can speed up k-NN in making traffic speed predictions by reducing the amount of data to be searched for without a significant sacrifice of prediction accuracy. The rationale behind this is that we had a better look at only the recent data because the traffic patterns not only repeat daily or weekly but also change over time. In our experiments, we build several different k-NN models employing different sets of features which are the current and past traffic speeds of the target link and the neighbor links in its up/down-stream. The performances of these models are compared by measuring the average prediction accuracy and the average time taken to make a prediction using various amounts of data.

Keywords: big data, k-NN, machine learning, traffic speed prediction

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Authors: Sakshi Gupta, Anupam Agrawal, Ekta Singla

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An exoskeleton design for rehabilitation purpose encounters many challenges, including ergonomically acceptable wearing technology, architectural design human-motion compatibility, actuation type, human-robot interaction, etc. In this paper, a passive architecture for upper limb exoskeleton is proposed for assisting in rehabilitation tasks. Kinematic modelling is detailed for task-based kinematic synthesis of the wearable exoskeleton for self-feeding tasks. The exoskeleton architecture possesses expansion and torsional springs which are able to store and redistribute energy over the human arm joints. The elastic characteristics of the springs have been optimized to minimize the mechanical work of the human arm joints. The concept of hybrid combination of a 4-bar parallelogram linkage and a serial linkage were chosen, where the 4-bar parallelogram linkage with expansion spring acts as a rigid structure which is used to provide the rotational degree-of-freedom (DOF) required for lowering and raising of the arm. The single linkage with torsional spring allows for the rotational DOF required for elbow movement. The focus of the paper is kinematic modelling, analysis and task-based synthesis framework for the proposed architecture, keeping in considerations the essential tasks of self-feeding and self-exercising during rehabilitation of partially healthy person. Rehabilitation of primary functional movements (activities of daily life, i.e., ADL) is routine activities that people tend to every day such as cleaning, dressing, feeding. We are focusing on the feeding process to make people independent in respect of the feeding tasks. The tasks are focused to post-surgery patients under rehabilitation with less than 40% weakness. The challenges addressed in work are ensuring to emulate the natural movement of the human arm. Human motion data is extracted through motion-sensors for targeted tasks of feeding and specific exercises. Task-based synthesis procedure framework will be discussed for the proposed architecture. The results include the simulation of the architectural concept for tracking the human-arm movements while displaying the kinematic and static study parameters for standard human weight. D-H parameters are used for kinematic modelling of the hybrid-mechanism, and the model is used while performing task-based optimal synthesis utilizing evolutionary algorithm.

Keywords: passive mechanism, task-based synthesis, emulating human-motion, exoskeleton

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Authors: Lin Cheng, Zijiang Yang

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Program synthesis is the task to automatically generate programs based on user specification. In this paper, we present a framework that synthesizes programs from flow charts that serve as accurate and intuitive specification. In order doing so, we propose a deep neural network called GRCNN that recognizes graph structure from its image. GRCNN is trained end-to-end, which can predict edge and node information of the flow chart simultaneously. Experiments show that the accuracy rate to synthesize a program is 66.4%, and the accuracy rates to recognize edge and node are 94.1% and 67.9%, respectively. On average, it takes about 60 milliseconds to synthesize a program.

Keywords: program synthesis, flow chart, specification, graph recognition, CNN

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Authors: Pavan K. Rallabandi, Kailash C. Patidar

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In this paper, we present an optimization technique or a learning algorithm using the hybrid architecture by combining the most popular sequence recognition models such as Recurrent Neural Networks (RNNs) and Hidden Markov models (HMMs). In order to improve the sequence or pattern recognition/ classification performance by applying a hybrid/neural symbolic approach, a gradient descent learning algorithm is developed using the Real Time Recurrent Learning of Recurrent Neural Network for processing the knowledge represented in trained Hidden Markov Models. The developed hybrid algorithm is implemented on automata theory as a sample test beds and the performance of the designed algorithm is demonstrated and evaluated on learning the deterministic finite state automata.

Keywords: hybrid systems, hidden markov models, recurrent neural networks, deterministic finite state automata

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Authors: K. V. Ramanaiah, R. Jagan, N. N. Murthy

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Trinuclear oxo-centered carboxylate-bridged iron complexes, [Fe3(µ3-O)(µ2-O2CR)L¬3]+/0 (where R = alkyl or aryl; L = H2O, ROH, Py, solvent) have attracted tremendous attention because of their interesting structural and magnetic properties, exhibit mixed-valent trapped and de-trapped states, and have bioinorganic relevance. The presence of a trinuclear iron binding center has been implicated in the formation of both bacterial and human iron storage protein, Ft. They are used as precursors for the synthesis of models for the active-site structures of non-heme proteins, hemerythrin (Hr), methane monooxygenase (MMO) and polyiron storage protein, ferritin (Ft). Used as important building blocks for the design and synthesis of supramolecules this can exhibit single molecular magnetism (SMM). Such studies have often employed simple and compact carboxylate ligands and the use of bulky carboxylates is scarce. In the present study, we employed two different type of sterically hindered carboxylates and synthesized a series of novel oxo-centered, carboxylate-bridged triiron complexes of general formula [Fe3(O)(O2CCPh3)6L3]X (L = H2O, 1; py, 2; 4-NMe2py, 3; X = ClO4; L = CH3CN, 4; X = FeCl4) and [Fe3(O)(O2C-anth)6L3]X (L = H2O, 5; X = ClO4; L = CH3OH, 6; X = Cl). Along with complex [Fe(OMe)2(O2CCPh3)]10, 7 was prepared by the self-assemble of anhydrous FeCl3, sodium triphenylacetate and sodium methoxide at ratio of 1:1:2 in CH3OH. The Electronic absorption spectra of these complexes 1-6, in CH2Cl2 display weak bands at near FTIR region (970-1135 nm, ε > 15M-1cm-1). For complex 7, one broad band centered at ~670nm and also an additional intense charge transfer (L→M or O→M) bands between 300 to 550nm observed for all the complexes. Paramagnetic 1H NMR is introduced as a good probe for the characterization of trinuclear oxo - cantered iron compounds in solution when the L ligand coordinated to iron varies as: H2O, py, 4-NMe2py, and CH3OH. The solution state magnetic moment values calculated by using Evans method for all the complexes and also solid state magnetic moment value of complex, 7 was calculated by VSM method, which is comparable with solution state value. These all magnetic moment values indicate there is a spin exchange process through oxo and carboxylate bridges in between two irons (d5). The ESI-mass data complement the data obtained from single crystal X-ray structure. Further purity of the compounds was confirmed by elemental analysis. Finally, structural determination of complexes 1, 3, 4, 5, 6 and 7 were unambiguously conformed by single crystal x-ray studies.

Keywords: decanuclear, paramagnetic NMR, trinuclear, uv-visible

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Authors: Taha Ahmed Özbey, Sedat Nazlıbilek, Alparslan Çağrı Yapıcı

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Combline cavity filters have gained significant attention in recent years due to their exceptional narrowband characteristics, high unloaded Q, remarkable out-of-band rejection, and versatile post-manufacturing tuning capabilities. These filters play a vital role in various wireless communication systems, radar applications, and other advanced technologies where stringent frequency selectivity and superior performance are required. This paper represents combined cavity filter design and implementation by coupling matrix synthesis. Limited filter length, 50 dB out-of-band rejection, and agile design were aimed. To do so, CAD tools and intuitive methods were used.

Keywords: cavity, band pass filter, cavity combline filter, coupling matrix synthesis

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Authors: Farrukh Javed, Krzysztof Podgórski

Abstract:

We propose a new model that accounts for the asymmetric response of volatility to positive ('good news') and negative ('bad news') shocks in economic time series the so-called leverage effect. In the past, asymmetric powers of errors in the conditionally heteroskedastic models have been used to capture this effect. Our model is using the gamma difference representation of the generalized Laplace distributions that efficiently models the asymmetry. It has one additional natural parameter, the shape, that is used instead of power in the asymmetric power models to capture the strength of a long-lasting effect of shocks. Some fundamental properties of the model are provided including the formula for covariances and an explicit form for the conditional distribution of 'bad' and 'good' news processes given the past the property that is important for the statistical fitting of the model. Relevant features of volatility models are illustrated using S&P 500 historical data.

Keywords: heavy tails, volatility clustering, generalized asymmetric laplace distribution, leverage effect, conditional heteroskedasticity, asymmetric power volatility, GARCH models

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Authors: Carolin Anna Joy, Rohith K. R, Rehin Sulay, Parvathy Santhoshkumar, G.Anil Kumar, Vibin Ipe Thomas

Abstract:

Ullmann coupling reactions are gaining great relevance owing to their contribution in the synthesis of biologically and pharmaceutically important compounds. Palladium and many other heavy metals have proven their excellent ability in coupling reaction, but the toxicity matters. The first-row transition metal also possess toxicity, except in the case of iron and manganese. The suitability of manganese as a catalyst is achieving great interest in oxidation, reduction, C-H activation, coupling reaction etc. In this presentation, we discuss the thermo chemistry of ligand free manganese catalyzed C-O coupling reaction between phenol and aryl halide for the synthesis of biaryl ethers using Density functional theory techniques. The mechanism involves an oxidative addition-reductive elimination step. The transition state for both the step had been studied and confirmed using Intrinsic Reaction Coordinate (IRC) calculation. The barrier height for the reaction had also been calculated from the rate determining step. The possibility of other mechanistic way had also been studied. To achieve further insight into the mechanism, substrate having various functional groups is considered in our study to direct their effect on the feasibility of the reaction.

Keywords: Density functional theory, Molecular Modeling, ligand free, biaryl ethers, Ullmann coupling

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Authors: Parvesh Singh, Vipan Kumar, Vishu Mehra

Abstract:

Quinoline-4-ones represent an important class of heterocyclic scaffolds that have attracted significant interest due to their various biological and pharmacological activities. This heterocyclic unit also constitutes an integral component in drugs used for the treatment of neurodegenerative diseases, sleep disorders and in antibiotics viz. norfloxacin and ciprofloxacin. The synthetic accessibility and possibility of fictionalization at varied positions in quinoline-4-ones exemplifies an elegant platform for the designing of combinatorial libraries of functionally enriched scaffolds with a range of pharmacological profles. They are also considered to be attractive precursors for the synthesis of medicinally imperative molecules such as non-steroidal androgen receptor antagonists, antimalarial drug Chloroquine and martinellines with antibacterial activity. 2-Aryl-2,3-dihydroquinolin-4(1H)-ones are present in many natural and non-natural compounds and are considered to be the aza-analogs of favanones. The β-lactam class of antibiotics is generally recognized to be a cornerstone of human health care due to the unparalleled clinical efficacy and safety of this type of antibacterial compound. In addition to their biological relevance as potential antibiotics, β-lactams have also acquired a prominent place in organic chemistry as synthons and provide highly efficient routes to a variety of non-protein amino acids, such as oligopeptides, peptidomimetics, nitrogen-heterocycles, as well as biologically active natural and unnatural products of medicinal interest such as indolizidine alkaloids, paclitaxel, docetaxel, taxoids, cyptophycins, lankacidins, etc. A straight forward route toward the synthesis of quinoline-4-ones via the triflic acid assisted Fries rearrangement of N-aryl-βlactams has been reported by Tepe and co-workers. The ring expansion observed in this case was solely attributed to the inherent ring strain in β-lactam ring because -lactam failed to undergo rearrangement under reaction conditions. Theabovementioned protocol has been recently extended by our group for the synthesis of benzo[b]-azocinon-6-ones via a tandem Michael addition–Fries rearrangement of sorbyl anilides as well as for the single-pot synthesis of 2-aryl-quinolin-4(3H)-ones through the Fries rearrangement of 3-dienyl-βlactams. In continuation with our synthetic endeavours with the β-lactam ring and in view of the lack of convenient approaches for the synthesis of C-3 functionalized quinolin-4(1H)-ones, the present work describes the single-pot synthesis of C-3 functionalized quinolin-4(1H)-ones via the trific acid promoted Fries rearrangement of C-3 vinyl/isopropenyl substituted β-lactams. In addition, DFT calculations and MD simulations were performed to investigate the stability profles of synthetic compounds.

Keywords: dihydroquinoline, fries rearrangement, azetidin-2-ones, quinoline-4-ones

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Authors: Minttu Laukkanen, Janne Huiskonen

Abstract:

This study investigates the sharing economy business models as examples of the sustainable business models. The aim is to contribute to the limited literature on sharing economy in connection with sustainable business models by explaining sharing economy business models value capturing. Specifically, this research answers the following question: How business model choices affect captured sustainable value? A multiple case study approach is applied in this study. Twenty different successful sharing economy business models focusing on consumer business and covering four main areas, accommodation, mobility, food, and consumer goods, are selected for analysis. The secondary data available on companies’ websites, previous research, reports, and other public documents are used. All twenty cases are analyzed through the sharing economy business model framework and sustainable value analysis framework using qualitative data analysis. This study represents general sharing economy business model value attributes and their specifications, i.e. sustainable value propositions for different stakeholders, and further explains the sustainability impacts of different sharing economy business models through captured and uncaptured value. In conclusion, this study represents how business model choices affect sustainable value capturing through eight business model attributes identified in this study. This paper contributes to the research on sustainable business models and sharing economy by examining how business model choices affect captured sustainable value. This study highlights the importance of careful business model and sustainability impacts analyses including the triple bottom line, multiple stakeholders and value captured and uncaptured perspectives as well as sustainability trade-offs. It is not self-evident that sharing economy business models advance sustainability, and business model choices does matter.

Keywords: sharing economy, sustainable business model innovation, sustainable value, value capturing

Procedia PDF Downloads 148