Search results for: constriction factor based particle swarm optimization (CPSO)

Authors: Said Benaissa, David Plets, Emmeric Tanghe, Jens Trogh, Luc Martens, Leen Vandaele, Annelies Van Nuffel, Frank A. M. Tuyttens, Bart Sonck, Wout Joseph

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The herd monitoring and managing - in particular the detection of ‘attention animals’ that require care, treatment or assistance is crucial for effective reproduction status, health, and overall well-being of dairy cows. In large sized farms, traditional methods based on direct observation or analysis of video recordings become labour-intensive and time-consuming. Thus, automatic monitoring systems using sensors have become increasingly important to continuously and accurately track the health status of dairy cows. Wireless sensor networks (WSNs) and internet-of-things (IoT) can be effectively used in health tracking of dairy cows to facilitate herd management and enhance the cow welfare. Since on-cow measuring devices are energy-constrained, a proper characterization of the off-body wireless channel between the on-cow sensor nodes and the back-end base station is required for a power-optimized deployment of these networks in barns. The aim of this study was to characterize the off-body wireless channel in indoor (barns) environment at 868 MHz using LoRa nodes. LoRa is an emerging wireless technology mainly targeted at WSNs and IoT networks. Both large scale fading (i.e., path loss) and temporal fading were investigated. The obtained path loss values as a function of the transmitter-receiver separation were well fitted by a lognormal path loss model. The path loss showed an additional increase of 4 dB when the wireless node was actually worn by the cow. The temporal fading due to movement of other cows was well described by Rician distributions with a K-factor of 8.5 dB. Based on this characterization, network planning and energy consumption optimization of the on-body wireless nodes could be performed, which enables the deployment of reliable dairy cow monitoring systems.

Keywords: channel, channel modelling, cow monitoring, dairy cows, health monitoring, IoT, LoRa, off-body propagation, PLF, propagation

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Authors: Nanhee Cho, Eugene Han, Hanbyul Kim, Hochan Cho

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Pre-diabetes includes impaired fasting glucose (IFG) and impaired glucose tolerance (IGT) and there is a strong probability that pre-diabetes will lead to diabetes mellitus (DM). Serum fibroblast growth factor 21 (FGF-21) is known to be increased as a compensatory response to metabolic imbalance under conditions such as obesity, metabolic syndrome, and DM. This study aims to identify the relationship of serum FGF-21 with pre-diabetes, and with biomarkers of related metabolic diseases. Fifty five Korea adult patients participated in a cohort study from June 2012 to December 2015. The analysis revealed that BMI, FBS levels, and serum FGF-21 levels were significantly higher in the IFG group compared to those in the normal group. A multiple regression analysis was conduted on the correlations of serum FGF-21 levels with BMI, and FBS levels, and the result did not show statistical significance. In conclusion, our results revealed that serum FGF-21 level serve as a marker to predict IFG.

Keywords: cytokine, fibroblast growth factor 21, impaired fasting glucose, prediabetes

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Authors: Krutika K. Sawant, Anil Solanki

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The present study deals with the preparation and optimization of ethyl cellulose-containing disopyramide phosphate loaded microspheres using solvent evaporation technique. A central composite design consisting of a two-level full factorial design superimposed on a star design was employed for optimizing the preparation microspheres. The drug:polymer ratio (X1) and speed of the stirrer (X2) were chosen as the independent variables. The cumulative release of the drug at a different time (2, 6, 10, 14, and 18 hr) was selected as the dependent variable. An optimum polynomial equation was generated for the prediction of the response variable at time 10 hr. Based on the results of multiple linear regression analysis and F statistics, it was concluded that sustained action can be obtained when X1 and X2 are kept at high levels. The X1X2 interaction was found to be statistically significant. The drug release pattern fitted the Higuchi model well. The data of a selected batch were subjected to an optimization study using Box-Behnken design, and an optimal formulation was fabricated. Good agreement was observed between the predicted and the observed dissolution profiles of the optimal formulation.

Keywords: disopyramide phosphate, ethyl cellulose, microspheres, controlled release, Box-Behnken design, factorial design

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Authors: Simon Bard, Martin Demleitner, Florian Schonl, Volker Altstadt

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For an electrically driven aircraft, whose engine is based on semiconductors, alternative materials are needed. The avoid hotspots in the materials thermally conductive polymers are necessary. Nevertheless, the mechanical properties of these materials should remain. Herein, the work of three years in a project with airbus and Siemens is presented. Different strategies have been pursued to achieve conductive fiber-reinforced composites: Metal-coated carbon fibers, pitch-based fibers and particle-loaded matrices have been investigated. In addition, a combination of copper-coated fibers and a conductive matrix has been successfully tested for its conductivity and mechanical properties. First, prepregs have been produced with a laboratory scale prepreg line, which can handle materials with maximum width of 300 mm. These materials have then been processed to fiber-reinforced laminates. For the PAN-fiber reinforced laminates, it could be shown that there is a strong dependency between fiber volume content and thermal conductivity. Laminates with 50 vol% of carbon fiber offer a conductivity of 0.6 W/mK, those with 66 vol% of fiber a thermal conductivity of 1 W/mK. With pitch-based fiber, the conductivity enhances to 1.5 W/mK for 61 vol% of fiber, compared to 0.81 W/mK with the same amount of fibers produced from PAN (+83% in conducitivity). The thermal conductivity of PAN-based composites with 50 vol% of fiber is at 0.6 W/mK, their nickel-coated counterparts with the same fiber volume content offer a conductivity of 1 W/mK, an increase of 66%.

Keywords: carbon, electric aircraft, polymer, thermal conductivity

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Authors: Mahya Naghipoor

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Purpose: Non-small cell lung cancer (NSCLC) is the most common lung cancer type. Epidermal growth factor receptor (EGFR) mutation is the main reason which causes NSCLC. Computed tomography (CT) is used for diagnosis and prognosis of lung cancers because of low price and little invasion. Semantic analyses of qualitative CT features are based on visual evaluation by radiologist. However, the naked eye ability may not assess all image features. On the other hand, radiomics provides the opportunity of quantitative analyses for CT images features. The aim of this review study was comparing accuracy of semantic and radiomics features in prognosis of EGFR mutation in NSCLC. Methods: For this purpose, the keywords including: non-small cell lung cancer, epidermal growth factor receptor mutation, semantic, radiomics, feature, receiver operating characteristics curve (ROC) and area under curve (AUC) were searched in PubMed and Google Scholar. Totally 29 papers were reviewed and the AUC of ROC analyses for semantic and radiomics features were compared. Results: The results showed that the reported AUC amounts for semantic features (ground glass opacity, shape, margins, lesion density and presence or absence of air bronchogram, emphysema and pleural effusion) were %41-%79. For radiomics features (kurtosis, skewness, entropy, texture, standard deviation (SD) and wavelet) the AUC values were found %50-%86. Conclusions: In conclusion, the accuracy of radiomics analysis is a little higher than semantic in prognosis of EGFR mutation in NSCLC.

Keywords: lung cancer, radiomics, computer tomography, mutation

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Authors: Armin Amindari

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Hermetic compressors are used widely for refrigeration, heat pump, and air conditioning applications. With the improvement of energy conservation and environmental protection requirements, inverter compressors that operates at different speeds have become increasingly attractive in the industry. Although speed change capability is more efficient, passing through resonant frequencies may lead to excessive vibrations. In this work, an integrated vibration control approach based on flexible multi-body dynamics theory is used for optimizing the vibration amplitudes of the compressor at different operating speeds. To examine the compressor vibrations, all the forces and moments exerted on the cylinder block were clarified and minimized using balancers attached to the upper and lower ends of the motor rotor and crankshaft. The vibration response of the system was simulated using Motionview™ software. In addition, mass-spring optimization was adopted to shift the resonant frequencies out of the operating speeds. The modal shapes of the system were studied using Optistruct™ solver. Using this approach, the vibrations were reduced up to 56% through dynamic simulations. The results were in high agreement with various experimental test data. In addition, the vibration resonance problem observed at low speeds was solved by shifting the resonant frequencies through optimization studies.

Keywords: vibration, MBD, compressor, hermetic

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Authors: Charizza D. Montarin, Daryl Jae S. Sigue, Gilford Estores

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Philippines was moderately vulnerable to corrosion and to prevent this problem, surface coating should be applied. The main objective of this research was to develop and optimize a bio-based mixture of Pili Resin and Lime as Coating Materials. There are three (3) factors to be considered in choosing the best coating material such as chemical adhesion, friction, and the bearing/shear against the steel bar-concrete interface. Fortunately, both proportions of the Bio-based coating materials (50:50 and 65:35) do not have red rust formation complying with ASTM B117 but failed in terms of ASTM D 3359. Splitting failures of concrete were observed in the Unconfined Reinforced Concrete Samples. All of the steel bars (uncoated and coated) surpassed the Minimum Bond strength (NSCP 2015) about 203% to 285%. The experiments were about 1% to 3% of the results from the ANSYS Simulations with and without Salt Spray Test. Using the bio-based and epoxy coatings, normal splitting strengths were declined. However, there has no significant difference between the results. Thus, the bio-based coating materials can be used as an alternative for the epoxy coating materials and it was highly recommended for Low – Rise Building only.

Keywords: Canarium luzonicum, calcium oxide, corrosion, finite element simulations

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Authors: P. M. Fonseca Alfonso, E. A. Murillo Ruiz, M. Diaz Lagos

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Understanding the physicochemical properties and mineralogy of fly ash from a particular source is essential for to protect the environment and considering its possible applications, specifically, in the production of geopolymeric materials that solidify/stabilize heavy metals ions. The results of the characterization of three fly ash samples are shown in this paper. The samples were produced in the TERMOPAIPA IV thermal power plant in the State of Boyaca, Colombia. The particle size distribution, chemical composition, mineralogy, and molecular structure of three samples were analyzed using laser diffraction, X-ray fluorescence, inductively coupled plasma mass spectrometry, X-ray diffraction, and infrared spectroscopy respectively. The particle size distribution of the three samples probably ranges from 0.128 to 211 μm. Approximately 59 elements have been identified in the three samples. It is noticeable that the ashes are made up of aluminum and silicon compounds. Besides, the iron phase in low content was also found. According to the results found in this study, the fly ash samples type F has a great potential to be used as raw material for the manufacture of geopolymers with potential use in the stabilization/solidification of heavy metals; mainly due to the presence of amorphous aluminosilicates typical of this type of ash, which react effectively with alkali-activator.

Keywords: fly ash, geopolymers, molecular structure, physicochemical properties.

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Authors: Shunsuke Miyoshi, Yasuyuki Nogami, Takuya Kusaka, Nariyoshi Yamai

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Elliptic curve discrete logarithm problem (ECDLP) is one of problems on which the security of pairing-based cryptography is based. This paper considers Pollard's rho method to evaluate the security of ECDLP on Barreto-Naehrig (BN) curve that is an efficient pairing-friendly curve. Some techniques are proposed to make the rho method efficient. Especially, the group structure on BN curve, distinguished point method, and Montgomery trick are well-known techniques. This paper applies these techniques and shows its optimization. According to the experimental results for which a large-scale parallel system with MySQL is applied, 94-bit ECDLP was solved about 28 hours by parallelizing 71 computers.

Keywords: Pollard's rho method, BN curve, Montgomery multiplication

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Authors: Farhat Hajer, Khir Tahar, Cherni Rafik, Dakhli Radhouen, Ammar Ben Brahim

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This paper presents the energy and exergy optimization of a real gas turbine power plant performance of 100 MW of power, installed in the South East of Tunisia. A simulation code is established using the EES (Engineering Equation Solver) software. The parameters considered are those of the actual operating conditions of the gas turbine thermal power station under study. The results show that thermal and exergetic efficiency decreases with the increase of the ambient temperature. Air excess has an important effect on the thermal efficiency. The emission of NOx rises in the summer and decreases in the winter. The obtained rates of NOx are compared with measurements results.

Keywords: efficiency, exergy, gas turbine, temperature

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Authors: Alan Luo, Hunter N. B. Moseley

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Many macromolecular structure entries in the Protein Data Bank (PDB) have a range of regional (localized) quality issues, be it derived from x-ray crystallography, Nuclear Magnetic Resonance (NMR) spectroscopy, or other experimental approaches. However, most PDB entries are judged by global quality metrics like R-factor, R-free, and resolution for x-ray crystallography or backbone phi-psi distribution statistics and average restraint violations for NMR. Regional quality is often ignored when PDB entries are re-used for a variety of structurally based analyses. The binding of ligands, especially ligands involved in energy metabolism, is of particular interest in many structurally focused protein studies. Using a regional quality metric that provides chemically interpretable information from electron density maps, a significant number of outliers in regional structural quality was detected across x-ray crystallographic PDB entries for proteins bound to biochemically critical ligands. In this study, a series of analyses was performed to evaluate both specific and general potential factors that could promote these outliers. In particular, these potential factors were the minimum distance to a metal ion, the minimum distance to a crystal contact, and the isotropic atomic b-factor. To evaluate these potential factors, Fisher’s exact tests were performed, using regional quality criteria of outlier (top 1%, 2.5%, 5%, or 10%) versus non-outlier compared to a potential factor metric above versus below a certain outlier cutoff. The results revealed a consistent general effect from region-specific normalized b-factors but no specific effect from metal ion contact distances and only a very weak effect from crystal contact distance as compared to the b-factor results. These findings indicate that no single specific potential factor explains a majority of the outlier ligand-bound regions, implying that human error is likely as important as these other factors. Thus, all factors, including human error, should be considered when regions of low structural quality are detected. Also, the downstream re-use of protein structures for studying ligand-bound conformations should screen the regional quality of the binding sites. Doing so prevents misinterpretation due to the presence of structural uncertainty or flaws in regions of interest.

Keywords: biomacromolecular structure, coenzyme, electron density discrepancy analysis, x-ray crystallography

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Authors: Jacob Schwartz, Maxim Durach, Aniruddha Mitra, Abbas Rashidi, Glen Sage, Atin Adhikari

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NIOSH (National Institute for Occupational Safety and Health) approved N95 respirators are commonly used by workers in construction sites where there is a large amount of dust being produced from sawing, grinding, blasting, welding, etc., both electrostatically charged and not. A significant portion of airborne particles in construction sites could be nanoparticles created beside coarse particles. The penetration of the particles through the masks may differ depending on the size and charge of the individual particle. In field experiments relevant to this current study, we found that nanoparticles of medium size ranges are penetrating more frequently than nanoparticles of smaller and larger sizes. For example, penetration percentages of nanoparticles of 11.5 – 27.4 nm into a sealed N95 respirator on a manikin head ranged from 0.59 to 6.59%, whereas nanoparticles of 36.5 – 86.6 nm ranged from 7.34 to 16.04%. The possible causes behind this increased penetration of mid-size nanoparticles through mask filters are not yet explored. The objective of this study is to identify causes behind this unusual behavior of mid-size nanoparticles. We have considered such physical factors as Boltzmann distribution of the particles in thermal equilibrium with the air, kinetic energy of the particles at impact on the mask, Stoke’s drag force, and electrostatic forces in the mask stopping the particles. When the particles collide with the mask, only the particles that have enough kinetic energy to overcome the energy loss due to the electrostatic forces and the Stokes’ drag in the mask can pass through the mask. To understand this process, the following assumptions were made: (1) the effect of Stoke’s drag depends on the particles’ velocity at entry into the mask; (2) the electrostatic force is proportional to the charge on the particles, which in turn is proportional to the surface area of the particles; (3) the general dependence on electrostatic charge and thickness means that for stronger electrostatic resistance in the masks and thicker the masks’ fiber layers the penetration of particles is reduced, which is a sensible conclusion. In sampling situations where one mask was soaked in alcohol eliminating electrostatic interaction the penetration was much larger in the mid-range than the same mask with electrostatic interaction. The smaller nanoparticles showed almost zero penetration most likely because of the small kinetic energy, while the larger sized nanoparticles showed almost negligible penetration most likely due to the interaction of the particle with its own drag force. If there is no electrostatic force the fraction for larger particles grows. But if the electrostatic force is added the fraction for larger particles goes down, so diminished penetration for larger particles should be due to increased electrostatic repulsion, may be due to increased surface area and therefore larger charge on average. We have also explored the effect of ambient temperature on nanoparticle penetrations and determined that the dependence of the penetration of particles on the temperature is weak in the range of temperatures in the measurements 37-42°C, since the factor changes in the range from 3.17 10-3K-1 to 3.22 10-3K-1.

Keywords: respiratory protection, industrial hygiene, aerosol, electrostatic force

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Authors: Rui Mao, Heming Ji, Xiaoyu Wang

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Keystroke dynamics are widely used in identity recognition. It has the advantage that the individual typing rhythm is difficult to imitate. It also supports continuous authentication through the keyboard without extra devices. The existing keystroke dynamics authentication methods based on machine learning have a drawback in supporting relatively complex scenarios with massive data. There are drawbacks to both feature extraction and model optimization in these methods. To overcome the above weakness, an authentication model of keystroke dynamics based on deep learning is proposed. The model uses feature vectors formed by keystroke content and keystroke time. It ensures efficient continuous authentication by cooperating attention mechanisms with the combination of CNN and Bi-LSTM. The model has been tested with Open Data Buffalo dataset, and the result shows that the FRR is 3.09%, FAR is 3.03%, and EER is 4.23%. This proves that the model is efficient and accurate on continuous authentication.

Keywords: keystroke dynamics, identity authentication, deep learning, CNN, LSTM

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Authors: A. E. Kurtoglu, A. Cevik, M. Bilgehan

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In this parametric study, effect of soil and material characteristics on safety of structures is investigated. The soil parameters such as shear strength, unit weight; geometrical parameters of the structure such as foundation depth and height of building; and material properties such as weight of concrete were selected as input parameters. A real accelerogram of 1989 El-Centro earthquake recorded by the USGS in Imperial Valley is used for this study. It is contained in the standard Strong Motion CD-ROM (SMC) format, which can be recognized and interpreted by FEM software used. The soil-structure interaction model subjected to above-mentioned earthquake was analyzed for 729 cases. Effect of input parameters on safety factor of the soil-structure system was then investigated and the interaction between the input and output parameters is presented in graphical form. Findings showed that all input parameters have significant effects on factor of safety results.

Keywords: factor of safety, finite element method, safety of structures, soil structure interaction

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Authors: Héctor Rivera-Gómez, Eva Selene Hernández-Gress, Oscar Montaño-Arango, Jose Ramon Corona-Armenta

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This research studies the joint production, maintenance and subcontracting control policy for an unreliable deteriorating manufacturing system. Production activities are controlled by a derivation of the Hedging Point Policy, and given that the system is subject to deterioration, it reduces progressively its capacity to satisfy product demand. Multiple deterioration effects are considered, reflected mainly in the quality of the parts produced and the reliability of the machine. Subcontracting is available as support to satisfy product demand; also overhaul maintenance can be conducted to reduce the effects of deterioration. The main objective of the research is to determine simultaneously the production, maintenance and subcontracting rate which minimize the total incurred cost. A stochastic dynamic programming model is developed and solved through a simulation-based approach composed of statistical analysis and optimization with the response surface methodology. The obtained results highlight the strong interactions between production, deterioration and quality which justify the development of an integrated model. A numerical example and a sensitivity analysis are presented to validate our results.

Keywords: subcontracting, optimal control, deterioration, simulation, production planning

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Authors: Yefrem Yefremov

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In Kazakhstan, there are approximately 100,000 ethnic Koreans with the ethnonym "Koryo Saram". They are part of the global Korean diaspora around the world, deported to Kazakhstan by Stalin’s decree in 1937. Koryo Saram's diasporic identity is a composite of numerous identities based on a shared cultural heritage of the USSR and independent Kazakhstan and has mosaic character. The author has conducted a sociological survey to find out the main features of the identity of the Koryo Saram diaspora. The purpose of this paper is to depict the degree of ethnic, cultural, and diasporic identity of Koryo Saram and which effect on the preserving Korean diaspora in Kazakhstna do they have. The following elements impacting the above-mentioned identities were investigated in the survey: criteria by which Koryo Saram perceive themselves to be Korean, attitude of Koryo Saram to their ethnicity, degree of feeling of ethnocultural similarity between Koreans of Kazakhstan and Koreans of the Republic of Korea, degree of association of Koreans of Kazakhstan with other Koreans living in other CIS countries, degree of practicing Korean traditions Koryo Saram's attitudes towards interethnic marriages. The primary factor in defining the identity among the respondents is the factor of ethnic origin. Nationality is the second most significant component in establishing Koryo Saram’s identity. The maintenance of "Koreanness" of Koryo Sarams in the context of a multiethnic community, particularly in Kazakhstan, is based on genetic elements as well as the preservation of the culture. In conclusion, the high level of preserving Korean identity is being observed in the Korean Diaspora of Kazakhstan.

Keywords: diasporic identity, diaspora, ethnic identity, identity markers, korean diaspora, koreans of kazakhstan, koryo saram, multiethnicity

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Authors: Surendra Agrawal, Pravina Gurjar, Supriya Bhide, Ram Gaud

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Levamisole hydrochloride is a prominent anticancer drug in the treatment of colon cancer but resulted in toxic effects due poor bioavailability and poor cellular uptake by tumor cells. Levamisole is an unstable drug. Incorporation of this molecule in solid lipids may minimize their exposure to the aqueous environment and partly immobilize the drug molecules within the lipid matrix-both of which may protect the encapsulated drugs against degradation. The objectives of the study were to enhance bioavailability by sustaining drug release and to reduce the toxicities associated with the therapy. Solubility of the drug was determined in different lipids to select the components of Solid Lipid Nanoparticles (SLN). Pseudoternary phase diagrams were created using aqueous titration method. Formulations were subjected to particle size and stability evaluation to select the final test formulations which were characterized for average particle size, zeta potential, and in-vitro drug release and percentage transmittance to optimize the final formulation. SLN of Levamisole hydrochloride was prepared by Nanoprecipitation method. Glyceryl behenate (Compritol 888 ATO) was used as core comprising of Tween 80 as surfactant and Lecithin as co-surfactant in (1:1) ratio. Entrapment efficiency (EE) was found to be 45.89%. Particle size was found in the range of 100-600 nm. Zeta potential of the formulation was -17.0 mV revealing the stability of the product. In-vitro release study showed that 66 % drug released in 24 hours in pH 7.2 which represent that formulation can give controlled action at the intestinal environment. In pH 5.0 it showed 64% release indicating that it can even release drug in acidic environment of tumor cells. In conclusion, results revealed SLN to be a promising approach to sustain the drug release so as to increase bioavailability and cellular uptake of the drug with reduction in toxic effects as dose has been reduced with controlled delivery.

Keywords: SLN, nanoparticulate delivery of levamisole, pharmacy, pharmaceutical sciences

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Authors: Yonas Shuke Kitawa

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Background: Although malaria incidence has substantially fallen sharply over the past few years, the rate of decline varies by district, time, and malaria type. Despite this turn-down, malaria remains a major public health threat in various districts of Ethiopia. Consequently, the present study is aimed at developing a predictive model that helps to identify the spatio-temporal variation in malaria risk by multiple plasmodium species. Methods: We propose a multivariate spatio-temporal Bayesian model to obtain a more coherent picture of the temporally varying spatial variation in disease risk. The spatial autocorrelation in such a data set is typically modeled by a set of random effects that assign a conditional autoregressive prior distribution. However, the autocorrelation considered in such cases depends on a binary neighborhood matrix specified through the border-sharing rule. Over here, we propose a graph-based optimization algorithm for estimating the neighborhood matrix that merely represents the spatial correlation by exploring the areal units as the vertices of a graph and the neighbor relations as the series of edges. Furthermore, we used aggregated malaria count in southern Ethiopia from August 2013 to May 2019. Results: We recognized that precipitation, temperature, and humidity are positively associated with the malaria threat in the area. On the other hand, enhanced vegetation index, nighttime light (NTL), and distance from coastal areas are negatively associated. Moreover, nonlinear relationships were observed between malaria incidence and precipitation, temperature, and NTL. Additionally, lagged effects of temperature and humidity have a significant effect on malaria risk by either species. More elevated risk of P. falciparum was observed following the rainy season, and unstable transmission of P. vivax was observed in the area. Finally, P. vivax risks are less sensitive to environmental factors than those of P. falciparum. Conclusion: The improved inference was gained by employing the proposed approach in comparison to the commonly used border-sharing rule. Additionally, different covariates are identified, including delayed effects, and elevated risks of either of the cases were observed in districts found in the central and western regions. As malaria transmission operates in a spatially continuous manner, a spatially continuous model should be employed when it is computationally feasible.

Keywords: disease mapping, MSTCAR, graph-based optimization algorithm, P. falciparum, P. vivax, waiting matrix

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Authors: Sarra Arbaoui, Taoufik Bettaieb

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Contaminated soils and problems related to them have increasingly become a matter of concern. The most common the contaminants generated by industrial urban emissions and agricultural practices are trace metals). Remediation of trace metals which pollute soils can be carried out using physico-chemical processes. Nevertheless, these techniques damage the soil’s biological activity and require expensive equipment. Phytoremediation is a relatively low-cost technology based on the use of selected plants to remove, degrades or contains pollutants. The potential of kenaf for phytoremediation on Cd-contaminated soil was investigated. kenaf plants have been grown in pots containing different concentrations of cadmium. The observations made were for biomass production and cadmium content in different organs determinate by atomic emission spectrometry. Cadmium transfer from a contaminated soil to plants and into plant tissues are discussed in terms of the Bioconcentration Factor (BCF) and the Transfer Factor (TF). Results showed that Cd was found in kenaf plants at different levels. Tolerance and accumulation potential and biomass productivity indicated that kenaf could be used in phytoremediation.

Keywords: kenaf, cadmium, phytoremediation, contaminated soil

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Authors: Umme Hani, Mohammed Rahmatulla, Mohammed Ghazwani, Ali Alqahtani, Yahya Alhamhoom

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Background and introduction: Neratinib is a potent anticancer drug used for the treatment of breast cancer. It is poorly soluble at higher pH, which tends to minimize the therapeutic effects in the lower gastrointestinal tract (GIT) leading to poor bioavailability. An attempt has been made to prepare and develop a gastro-retentive system of Neratinib to improve the drug bioavailability in the GIT by enhancing the gastric retention time. Materials and methods: In the present study a three-factor at two-level (23) factorial design based optimization was used to inspect the effects of three independent variables (factors) such as sodium alginate (A), sodium bicarbonate (B) and sodium citrate (C) on the dependent variables like in vitro gelation, in vitro floating, water uptake and percentage drug release. Results: All the formulations showed pH in the range 6.7 ±0.25 to 7.4 ±0.24, percentage drug content was observed to be 96.3±0.27 to 99.5 ±0.28%, in vitro gelation observed as gelation immediate remains for an extended period. Percentage of water uptake was in the range between 9.01±0.15 to 31.01±0.25%, floating lag time was estimated form 7±0.39 to 57±0.36 sec. F4 and F5 showed floating even after 12hrs. All formulations showed a release of around 90% drug release within 12hr. It was observed that the selected independent variables affect the dependent variables. Conclusion: The developed system may be a promising and alternative approach to augment gastric retention of drugs and enhances the therapeutic efficacy of the drug.

Keywords: neratinib, 2³ factorial design, sodium alginate, floating, in situ gelling system

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Authors: Aniket Ganvir, Ritarani Sahu, Suchismita Chinara

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The rapid digitization of various aspects of life is leading to the creation of smart IoT ecosystems, where interconnected devices generate significant amounts of valuable data. However, these IoT devices face constraints such as limited computational resources and bandwidth. Cloud computing emerges as a solution by offering ample resources for offloading tasks efficiently despite introducing latency issues, especially for time-sensitive applications like fog computing. Fog computing (FC) addresses latency concerns by bringing computation and storage closer to the network edge, minimizing data travel distance, and enhancing efficiency. Offloading tasks to fog nodes or the cloud can conserve energy and extend IoT device lifespan. The offloading process is intricate, with tasks categorized as full or partial, and its optimization presents an NP-hard problem. Traditional greedy search methods struggle to address the complexity of task offloading efficiently. To overcome this, the efficient crow search algorithm (ECSA) has been proposed as a meta-heuristic optimization algorithm. ECSA aims to effectively optimize computation offloading, providing solutions to this challenging problem.

Keywords: IoT, fog computing, task offloading, efficient crow search algorithm

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Authors: Muhammad Naeem, Amina Zubari, Abdus Salam, Summera Yasmeen, Syed Ali Ayub Bukhari, Abir Ishtiaq

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In the present study, eighty three wild Oreochromis aureus of different body size ranging 5.3-14.6 cm in total length were collected from the River Chenab, District Muzzafer Garh, Pakistan to investigate the parameters of length –weight, length-length relationships and condition factor in relation to size. Each fish was measured and weighed on arrival at laboratory. Log transformed regressions were used to test the allometric growth. Length-weight relationship was found highly significant (r = 0.964; P < 0.01). The values of exponent “ b” in Length–weight regression (W=aLb), deviated from 3, showing isometric growth (b = 2.75). Results for LLRs indicated that these are highly correlated (P< 0.001). Condition factor (K) found constant with increasing body weight, however, showed negative influence with increasing total length.

Keywords: Oreochromis aureus, weight-length relationship, condition factor, predictive equations

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Authors: Balwinder Singh

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Castings are produced by using aluminum alloy ADC 10 through the process of Ceramic Shell Investment Casting. Experiments are conducted as per the Taguchi L9 orthogonal array. In order to evaluate the effect of process parameters such as mould preheat temperature, preheat time, firing temperature and pouring temperature on surface roughness of ceramic shell investment castings, the Taguchi parameter design and optimization approach is used. Plots of means of significant factors and S/N ratios have been used to determine the best relationship between the responses and model parameters. It is found that the pouring temperature is the most significant factor. The best tensile strength of aluminum alloy ADC 10 is given by 150 ºC shell preheat temperature, 45 minutes preheat time, 900 ºC firing temperature, 650 ºC pouring temperature.

Keywords: investment casting, shell preheat temperature, firing temperature, Taguchi method

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Authors: Siri Marthe Arbo, Afaf Saai, Sture Sørli, Mette Nedreberg

Abstract:

This work aims to establish a reliable approach for optimizing a Laser Metal Deposition (LMD) process for a critical maritime component, based on the material properties and structural performance required by the maritime industry. The component of interest is a water jet impeller, for which specific requirements for material properties are defined. The developed approach is based on the assessment of the effects of LMD process parameters on microstructure and material performance of standard AM 2205 duplex stainless steel powder. Duplex stainless steel offers attractive properties for maritime applications, combining high strength, enhanced ductility and excellent corrosion resistance due to the specific amounts of ferrite and austenite. These properties are strongly affected by the microstructural characteristics in addition to microstructural defects such as porosity and welding defects, all strongly influenced by the chosen LMD process parameters. In this study, the influence of deposition speed and heat input was evaluated. First, the influences of deposition speed and heat input on the microstructure characteristics, including ferrite/austenite fraction, amount of porosity and welding defects, were evaluated. Then, the achieved mechanical properties were evaluated by standard testing methods, measuring the hardness, tensile strength and elongation, bending force and impact energy. The measured properties were compared to the requirements of the water jet impeller. The results show that the required amounts of ferrite and austenite can be achieved directly by the LMD process without post-weld heat treatments. No intermetallic phases were observed in the material produced by the investigated process parameters. A high deposition speed was found to reduce the ductility due to the formation of welding defects. An increased heat input was associated with reduced strength due to the coarsening of the ferrite/austenite microstructure. The microstructure characterizations and measured mechanical performance demonstrate the great potential of the LMD process and generate a valuable database for the optimization of the LMD process for duplex stainless steels.

Keywords: duplex stainless steel, laser metal deposition, process optimization, microstructure, mechanical properties

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Authors: Peng Li, Luan Wang, Haifeng Fei, Renhong Xie, Yibin Rui, Shanhong Guo

Abstract:

The applications of satellite-based automatic identification system (S-AIS) pave the road for wide-range maritime traffic monitoring and management. But the coverage of satellite’s view includes multiple AIS self-organizing networks, which leads to the collision of AIS signals from different cells. The contribution of this work is to propose an improved multi-channel blind source separation algorithm based on Artificial Bee Colony (ABC) and advanced stochastic optimization to perform separation of the mixed AIS signals. The proposed approach adopts modified ABC algorithm to get an optimized initial separating matrix, which can expedite the initialization bias correction, and utilizes the Adaptive Moment Estimation (Adam) to update the separating matrix by adjusting the learning rate for each parameter dynamically. Simulation results show that the algorithm can speed up convergence and lead to better performance in separation accuracy.

Keywords: satellite-based automatic identification system, blind source separation, artificial bee colony, adaptive moment estimation

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Authors: Galal H. Senussi, Muamar Benisa, Sanja Vasin

Abstract:

In our business field today, one of the most important issues for any enterprises is cost minimization and profit maximization. Second issue is how to develop a strong and capable model that is able to give us desired forecasting of these two issues. Many researches deal with these issues using different methods. In this study, we developed a model for multi-criteria production program optimization, integrated with Artificial Neural Network. The prediction of the production cost and profit per unit of a product, dealing with two obverse functions at same time can be extremely difficult, especially if there is a great amount of conflict information about production parameters. Feed-Forward Neural Networks are suitable for generalization, which means that the network will generate a proper output as a result to input it has never seen. Therefore, with small set of examples the network will adjust its weight coefficients so the input will generate a proper output. This essential characteristic is of the most important abilities enabling this network to be used in variety of problems spreading from engineering to finance etc. From our results as we will see later, Feed-Forward Neural Networks has a strong ability and capability to map inputs into desired outputs.

Keywords: project profitability, multi-objective optimization, genetic algorithm, Pareto set, neural networks

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Authors: Yuguang Gao, Qiang Yang, Yanpeng Zhang, Mingtao Deng

Abstract:

To enhance the safety, quality and efficiency of healthcare services provided by surgical doctors, we propose a comprehensive approach to the performance evaluation of individual doctors by incorporating insights from performance data as well as views of different stakeholders in the hospital. Exploratory factor analysis was first performed on collective multidimensional performance data of surgical doctors, where key factors were extracted that encompass assessment of professional experience and service performance. A two-level indicator system was then constructed, for which we developed a weighted interval-valued spherical fuzzy analytic hierarchy process to analyze the relative importance of the indicators while handling subjectivity and disparity in the decision-making of multiple parties involved. Our analytical results reveal that, for the key factors identified as instrumental for evaluating surgical doctors’ performance, the overall importance of clinical workload and complexity of service are valued more than capacity of service and professional experience, while the efficiency of resource consumption ranks comparatively the lowest in importance. We also provide a retrospective case study to illustrate the effectiveness and robustness of our quantitative evaluation model by assigning meaningful performance ratings to individual doctors based on the weights developed through our approach.

Keywords: analytic hierarchy processes, factor analysis, fuzzy logic, performance evaluation

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Authors: Amir Moslehi, Gholamreza Raisali

Abstract:

Microdosimetric detectors based on multiple-thick gas electron multiplier (multiple-THGEM) configurations are being used in various fields of radiation protection and dosimetry. In the present work, microdosimetric response of these detectors to fast neutrons has been investigated by Monte Carlo method. Three similar microdosimeters made of A-150 and rexolite as the wall materials are designed; the first based on single-THGEM, the second based on double-THGEM and the third is based on triple-THGEM. Sensitive volume of the three microdosimeters is a right cylinder of 5 mm height and diameter which is filled with the propane-based tissue-equivalent (TE) gas. The TE gas with 0.11 atm pressure at the room temperature simulates 1 µm of tissue. Lineal energy distributions for several neutron energies from 10 keV to 14 MeV including 241Am-Be neutrons are calculated by the Geant4 simulation toolkit. Also, mean quality factor and dose-equivalent value for any neutron energy has been determined by these distributions. Obtained data derived from the three microdosimeters are in agreement. Therefore, we conclude that the multiple-THGEM structures present similar microdosimetric responses to fast neutrons.

Keywords: fast neutrons, geant4, multiple-thick gas electron multiplier, microdosimeter

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Authors: Ravi Patel, Krishna K. Krishnan

Abstract:

In global supply chains, appropriate and sustainable suppliers play a vital role in supply chain development and feasibility. In a larger organization with huge number of suppliers, it is necessary to divide suppliers based on their past history of quality and delivery of each product category. Since performance of any organization widely depends on their suppliers, well evaluated selection criteria and decision-making models lead to improved supplier assessment and development. In this paper, SCOR® performance evaluation approach and ISO standards are used to determine selection criteria for better utilization of supplier assessment by using hybrid model of Analytic Hierchchy Problem (AHP) and Fuzzy Techniques for Order Preference by Similarity to Ideal Solution (FTOPSIS). AHP is used to determine the global weightage of criteria which helps TOPSIS to get supplier score by using triangular fuzzy set theory. Both qualitative and quantitative criteria are taken into consideration for the proposed model. In addition, a multi-product and multi-time period model is selected for order allocation. The optimization model integrates multi-objective integer linear programming (MOILP) for order allocation and a hybrid approach for supplier selection. The proposed MOILP model optimizes order allocation based on manufacturing process and product tolerances as per manufacturer’s requirement for quality product. The integrated model and solution approach are tested to find optimized solutions for different scenario. The detailed analysis shows the superiority of proposed model over other solutions which considered individual decision making models.

Keywords: AHP, fuzzy set theory, multi-criteria decision making, multi-objective integer linear programming, TOPSIS

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Authors: Otman Jai, Otman Elhajjaji, Jaouad Tajmouati

Abstract:

Several neutronic calculation codes must be used to solve the equation for different levels of discretization which all necessitate a specific modelisation. This chain of such models, known as a calculation scheme, leads to the knowledge of the neutron flux in a reactor from its own geometry, its isotopic compositions and a cross-section library. Being small in size, the 'Slowpoke-2' reactor is difficult to model due to the importance of the leaking neutrons. In the paper, the simulation model is presented (geometry, cross section library, assumption, etc.), and the results obtained by DRAGON4/DONJON4 codes were compared to the calculations performed with Monte Carlo code MCNP using detailed geometrical model of the reactor and the experimental data. Criticality calculations have been performed to verify and validate the model. Since created model properly describes the reactor core, it can be used for calculations of reactor core parameters and for optimization of research reactor application.

Keywords: transport equation, Dragon4, Donjon4, neutron flux, effective multiplication factor

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