Search results for: spectroscopy data analysis

Authors: R. Shamsi, F. Sharifi

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In this paper, we obtain the projection of inefficient units in data envelopment analysis (DEA) in the case of stochastic inputs and outputs using the multi-objective programming (MOP) structure. In some problems, the inputs might be stochastic while the outputs are deterministic, and vice versa. In such cases, we propose a multi-objective DEA-R model because in some cases (e.g., when unnecessary and irrational weights by the BCC model reduce the efficiency score), an efficient decision-making unit (DMU) is introduced as inefficient by the BCC model, whereas the DMU is considered efficient by the DEA-R model. In some other cases, only the ratio of stochastic data may be available (e.g., the ratio of stochastic inputs to stochastic outputs). Thus, we provide a multi-objective DEA model without explicit outputs and prove that the input-oriented MOP DEA-R model in the invariable return to scale case can be replaced by the MOP-DEA model without explicit outputs in the variable return to scale and vice versa. Using the interactive methods for solving the proposed model yields a projection corresponding to the viewpoint of the DM and the analyst, which is nearer to reality and more practical. Finally, an application is provided.

Keywords: DEA-R, multi-objective programming, stochastic data, data envelopment analysis

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Authors: Naima Bouslah, Leila Bounabi, Farid Ouazib, Nabila Haddadine

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Conventional release dosage forms are known to provide an immediate release of the drug. Controlling the rate of drug release from polymeric matrices is very important for a number of applications, particularly in the pharmaceutical area. Hydrogels are polymers in three-dimensional network arrangement, which can absorb and retain large amounts of water without dissolution. They have been frequently used to develop controlled released formulations for oral administration because they can extend the duration of drug release and thus reduce dose to be administrated improving patient compliance. Tramadol is an opioid pain medication used to treat moderate to moderately severe pain. When taken as an immediate-release oral formulation, the onset of pain relief usually occurs within about an hour. In the present work, we synthesized pH-responsive hydrogels of (hydroxyl ethyl methacrylate-co-acrylic acid), (HEMA-AA) for control drug delivery of tramadol in the gastro-intestinal tractus. The hydrogels with different acrylic acid content, were synthesized by free radical polymerization and characterized by FTIR spectroscopy, X ray diffraction analysis (XRD), differential scanning calorimetry (DSC) and thermo gravimetric analysis (TGA). FTIR spectroscopy has shown specific hydrogen bonding interactions between the carbonyl groups of the hydrogels and hydroxyl groups of tramadol. Both the XRD and DSC studies revealed that the introduction of tramadol in the hydrogel network induced the amorphization of the drug. The swelling behaviour, absorptive kinetics and the release kinetics of tramadol in simulated gastric fluid (pH 1.2) and in simulated intestinal fluid (pH 7.4) were also investigated. The hydrogels exhibited pH-responsive behavior in the swelling study. The (HEMA-AA) hydrogel swelling was much higher in pH =7.4 medium. The tramadol release was significantly increased when pH of the medium was changed from simulated gastric fluid (pH 1.2) to simulated intestinal fluid (pH 7.4). Using suitable mathematical models, the apparent diffusional coefficients and the corresponding kinetic parameters have been calculated.

Keywords: biopolymres, drug delivery, hydrogels, tramadol

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Authors: Minna Theres James, Nirmal K Sebastian, Shoubhik Mandal, Pramita Mishra, R Ganesan, P S Anil Kumar

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We report the temperature-dependent evolution of Raman spectra of type-II Dirac semimetal (DSM) NiTe2 (001) in the form of bulk single crystal and a nanoflake (200 nm thick) for the first time. A physical model that can quantitatively explain the evolution of out of plane A1g and in-plane E1g Raman modes is used. The non-linear variation of peak positions of the Raman modes with temperature is explained by anharmonic three-phonon and four-phonon processes along with thermal expansion of the lattice. We also observe prominent effect of electron-phonon coupling from the variation of FWHM of the peaks with temperature, indicating the metallicity of the samples. Raman mode E1 1g corresponding to an in plane vibration disappears on decreasing the thickness from bulk to nanoflake.

Keywords: raman spectroscopy, type 2 dirac semimetal, nickel telluride, phonon-phonon coupling, electron phonon coupling, transition metal dichalcogonide

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Authors: Benamar Makhoukhi

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Clay ion-exchange using bismidazolium salts (MBIM) could provide organophilic clays materials that allow effective retention of polluting dyes. The present investigations deal with bentonite (Bt) modification using (ortho, meta and para) bisimidazolium cations and attempts to remove a synthetic textile dyes, such as (Telon-Orange, Telon-Red and Telon-Blue) by adsorption, from aqueous solutions. The surface modification of MBIM–Bt was examined using infrared spectroscopy (FTIR), X-ray diffraction (XRD) and thermogravimetric analysis (TGA). Adsorption tests applied to Telon dyes revealed a significant increase of the maximum adsorption capacity from ca. 21-28 to 88-108 mg.g-1 after intercalation. The highest adsorption level was noticed for Telon-Orange dye on the p-MBIM–Bt, presumably due higher interlayer space and better diffusion. The pseudo-first order rate equation was able to provide the best description of adsorption kinetics data for all three dyestuffs. The Langmuir and Freundlich adsorption models were applied to describe the equilibrium isotherms and the isotherm constants were also determined. The results show that MBIM–Bt could be employed as low-cost material for the removal of Telon dyes from effluents.

Keywords: Bentonite, Organoclay, Bisimidazolium, Dyes, Isotherms, Adsorption

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Authors: Gizem Kodak

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The Strait of Çanakkale, together with the Strait of Istanbul and the Sea of Marmara, form the Turkish Straits System. In other words, the Strait of Çanakkale is the southern gate of the system that connects the Black Sea countries with the other countries of the world. Due to the heavy maritime traffic, it is important to scientifically examine the accident characteristics in the region. In particular, the results indicated by the descriptive statistics are of critical importance in order to strengthen the safety of navigation. At this point, exploratory data analysis offers strategic outputs in terms of defining the problem and knowing the strengths and weaknesses against possible accident risk. The study aims to determine the accident characteristics in the Strait of Çanakkale with temporal and spatial analysis of historical data, using Exploratory Data Analysis (EDA) as the research method. The study's results will reveal the general characteristics of maritime accidents in the region and form the infrastructure for future studies. Therefore, the text provides a clear description of the research goals and methodology, and the study's contributions are well-defined.

Keywords: maritime accidents, EDA, Strait of Çanakkale, navigational safety

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Authors: Anung Style Bukhori, Ani Dijah Rahajoe

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Poverty poses a significant challenge in Indonesia, requiring an effective analytical approach to understand and address this issue. In this research, we applied the Naïve Bayes classification method to examine and classify poverty data in Indonesia. The main focus is on classifying data using RapidMiner, a powerful data analysis platform. The analysis process involves data splitting to train and test the classification model. First, we collected and prepared a poverty dataset that includes various factors such as education, employment, and health..The experimental results indicate that the Naïve Bayes classification model can provide accurate predictions regarding the risk of poverty. The use of RapidMiner in the analysis process offers flexibility and efficiency in evaluating the model's performance. The classification produces several values to serve as the standard for classifying poverty data in Indonesia using Naive Bayes. The accuracy result obtained is 40.26%, with a moderate recall result of 35.94%, a high recall result of 63.16%, and a low recall result of 38.03%. The precision for the moderate class is 58.97%, for the high class is 17.39%, and for the low class is 58.70%. These results can be seen from the graph below.

Keywords: poverty, classification, naïve bayes, Indonesia

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Authors: Ansah Iris Baffour, Dong-Ho Kim, Sung-Gyu Park

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The ongoing COVID-19 pandemic, caused by the SARS-CoV-2 virus and is gradually shifting to an endemic phase which implies the outbreak is far from over and will be difficult to eradicate. Global cooperation has led to unified precautions that aim to suppress epidemiological spread (e.g., through travel restrictions) and reach herd immunity (through vaccinations); however, the primary strategy to restrain the spread of the virus in mass populations relies on screening protocols that enable rapid on-site diagnosis of infections. Herein, we employed surface enhanced Raman spectroscopy (SERS) for the rapid detection of SARS-CoV-2 lysate on an Au-modified Au nanodimple(AuND)electrode. Through in situone-pot Au electrodeposition on the AuND electrode, Au-lysate nanocomposites were synthesized, generating3D internal hotspots for large SERS signal enhancements within 30 s of the deposition. The capture of lysate into newly generated plasmonic nanogaps within the nanocomposite structures enhanced metal-spike protein contact in 3D spaces and served as hotspots for sensitive detection. The limit of detection of SARS-CoV-2 lysate was 5 x 10-2 PFU/mL. Interestingly, ultrasensitive detection of the lysates of influenza A/H1N1 and respiratory syncytial virus (RSV) was possible, but the method showed ultimate selectivity for SARS-CoV-2 in lysate solution mixtures. We investigated the practical application of the approach for rapid on-site diagnosis by detecting SARS-CoV-2 lysate spiked in normal human saliva at ultralow concentrations. The results presented demonstrate the reliability and sensitivity of the assay for rapid diagnosis of COVID-19.

Keywords: label-free detection, nanocomposites, SARS-CoV-2, surface-enhanced raman spectroscopy

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Authors: Tsige Reda

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Essential oil of Thymus vulgaris was extracted by means of hydro-distillation. This study was done to investigate the chemical composition, antibacterial and antioxidant activities. The chemical composition of the essential oils was determined using gas chromatography coupled to mass spectroscopy (GC-MS). Using disc diffusion assay the antibacterial activity was assessed on one Gram-positive bacteria and one Gram-negative bacteria. The percentage oil yield of the essential oil was found to be 0.97 ± 0.08% (w/w) with yellow color. The physicochemical constants of the oil were also noted. The phytochemical screening of the plant extract revealed the presence of tannins, saponins, phenol, flavonoids, terpenoids, steroids and alkaloids. A total of 18 chemical constituents were identified by Gas Chromatography-Mass Spectroscopy analysis representing 100% of the total essential oil of Thymus vulgaris, with thymol (31.977%), o-cymene (29.992%), and carvacrol (14.541%). Previous studies have revealed that the thymol, o-cymen and carvacrol components of Thymus vulgaris are responsible for their biological activities. Thymus vulgaris have been used traditionally to treat a wide variety of infections. Based on the extensive use and lack of scientific evidence, a study was embarked upon to determine its bioactivity. The essential oil of Thymus vulgaris leaves exhibited higher activity towards the Gram-positive bacteria (Staphylococcus aurous) than the Gram-negative bacteria (Escherichia coli) and also has good antioxidant activity, and can be used medicinal and therapeutic applications. This activity may be due to the high amount of thymol, o-cymen and carvacrol.

Keywords: hydro-distillation, Thymus vulgaris, essential oil composition, phytochemical screening, physicochemical constants, antioxidant activity, antibacterial activity

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Authors: Dale Dzemydiene, Aurelija Burinskiene, Arunas Miliauskas, Kristina Ciziuniene

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Data flow and the purpose of reporting the data are different and dependent on business needs. Different parameters are reported and transferred regularly during freight delivery. This business practices form the dataset constructed for each time point and contain all required information for freight moving decisions. As a significant amount of these data is used for various purposes, an integrating methodological approach must be developed to respond to the indicated problem. The proposed methodology contains several steps: (1) collecting context data sets and data validation; (2) multi-objective analysis for optimizing freight transfer services. For data validation, the study involves Grubbs outliers analysis, particularly for data cleaning and the identification of statistical significance of data reporting event cases. The Grubbs test is often used as it measures one external value at a time exceeding the boundaries of standard normal distribution. In the study area, the test was not widely applied by authors, except when the Grubbs test for outlier detection was used to identify outsiders in fuel consumption data. In the study, the authors applied the method with a confidence level of 99%. For the multi-objective analysis, the authors would like to select the forms of construction of the genetic algorithms, which have more possibilities to extract the best solution. For freight delivery management, the schemas of genetic algorithms' structure are used as a more effective technique. Due to that, the adaptable genetic algorithm is applied for the description of choosing process of the effective transportation corridor. In this study, the multi-objective genetic algorithm methods are used to optimize the data evaluation and select the appropriate transport corridor. The authors suggest a methodology for the multi-objective analysis, which evaluates collected context data sets and uses this evaluation to determine a delivery corridor for freight transfer service in the multi-modal transportation network. In the multi-objective analysis, authors include safety components, the number of accidents a year, and freight delivery time in the multi-modal transportation network. The proposed methodology has practical value in the management of multi-modal transportation processes.

Keywords: multi-objective, analysis, data flow, freight delivery, methodology

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Authors: Seyong Jeong, Jinmo Park, Jinhyoun Park, Boram Kim, Kyoungsoo Ahn

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Energy management in the maritime industry is being required by economics and in conformity with new legislative actions taken by the International Maritime Organization (IMO) and the European Union (EU). In response, the various performance monitoring methodologies and data collection practices have been examined by different stakeholders. While many assorted advancements in operation and technology are applicable, their adoption in the shipping industry stays small. This slow uptake can be considered due to many different barriers such as data analysis problems, misreported data, and feedback problems, etc. This study presents a conceptual design of an energy management system (EMS) and proposes the methodology to resolve the limitations (e.g., data normalization using naval architectural evaluation, management of misrepresented data, and feedback from shore to ship through management of performance analysis history). We expect this system to make even short-term charterers assess the ship performance properly and implement sustainable fleet control.

Keywords: data normalization, energy management system, naval architectural evaluation, ship performance analysis

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Authors: X. Gumara Rigol, I. Martínez de Apellaniz Anzuola, A. Garcia Serrano, A. Franzi Cros, O. Vidal Calbet, A. Al Maruf

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Traditional federated architectures for data warehousing work well when corporations have existing regional data warehouses and there is a need to aggregate data at a global level. Schibsted Media Group has been maturing from a decentralised organisation into a more globalised one and needed to build both some of the regional data warehouses for some brands at the same time as the global one. In this paper, we present the architectural alternatives studied and why a custom federated approach was the notable recommendation to go further with the implementation. Although the data warehouses are logically federated, the implementation uses a single database system which presented many advantages like: cost reduction and improved data access to global users allowing consumers of the data to have a common data model for detailed analysis across different geographies and a flexible layer for local specific needs in the same place.

Keywords: data integration, data warehousing, federated architecture, Online Analytical Processing (OLAP)

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Authors: M. A. Hasan, M. R. Islam, R. A. Tarefder

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This study investigates how the site specific traffic data differs from the Mechanistic Empirical Pavement Design Software default values. Two Weigh-in-Motion (WIM) stations were installed in Interstate-40 (I-40) and Interstate-25 (I-25) to developed site specific data. A computer program named WIM Data Analysis Software (WIMDAS) was developed using Microsoft C-Sharp (.Net) for quality checking and processing of raw WIM data. A complete year data from November 2013 to October 2014 was analyzed using the developed WIM Data Analysis Program. After that, the vehicle class distribution, directional distribution, lane distribution, monthly adjustment factor, hourly distribution, axle load spectra, average number of axle per vehicle, axle spacing, lateral wander distribution, and wheelbase distribution were calculated. Then a comparative study was done between measured data and AASHTOWare default values. It was found that the measured general traffic inputs for I-40 and I-25 significantly differ from the default values.

Keywords: AASHTOWare, traffic, weigh-in-motion, axle load distribution

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Authors: Kwame Sarkodie, William Cheung, Andrew R. Fergursson

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The characterization of multiphase flow has gained enormous attention for most petroleum and chemical industrial processes. In order to fully characterize fluid phases in a stream or containment, there needs to be a profound knowledge of the existing composition of fluids present. This introduces a problem for real-time monitoring of fluid dynamics such as fluid distributions, and phase fractions. This work presents a simple technique of correlating absorbance spectrums of water, oil and air bubble present in containment. These spectra absorption outputs are derived by using an Fourier Infrared spectrometer. During the testing, air bubbles were introduced into static water column and oil containment and with light absorbed in the infrared regions of specific wavelength ranges. Attenuation coefficients are derived for various combinations of water, gas and oil which reveal the presence of each phase in the samples. The results from this work are preliminary and viewed as a build up to the design of a multiphase flow rig which has an infrared sensor pair to be used for multiphase flow characterization.

Keywords: attenuation, infrared, multiphase, spectroscopy

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Authors: Kanchan Mondal, Dasharath Koulage, Dattatray Manerikar, Asmita Ghate

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This paper presents an additive reliability model using warranty data and Finite Element Analysis (FEA) data. Warranty data for any product gives insight to its underlying issues. This is often used by Reliability Engineers to build prediction model to forecast failure rate of parts. But there is one major limitation in using warranty data for prediction. Warranty periods constitute only a small fraction of total lifetime of a product, most of the time it covers only the infant mortality and useful life zone of a bathtub curve. Predicting with warranty data alone in these cases is not generally provide results with desired accuracy. Failure rate of a mechanical part is driven by random issues initially and wear-out or usage related issues at later stages of the lifetime. For better predictability of failure rate, one need to explore the failure rate behavior at wear out zone of a bathtub curve. Due to cost and time constraints, it is not always possible to test samples till failure, but FEA-Fatigue analysis can provide the failure rate behavior of a part much beyond warranty period in a quicker time and at lesser cost. In this work, the authors proposed an Additive Weibull Model, which make use of both warranty and FEA fatigue analysis data for predicting failure rates. It involves modeling of two data sets of a part, one with existing warranty claims and other with fatigue life data. Hazard rate base Weibull estimation has been used for the modeling the warranty data whereas S-N curved based Weibull parameter estimation is used for FEA data. Two separate Weibull models’ parameters are estimated and combined to form the proposed Additive Weibull Model for prediction.

Keywords: bathtub curve, fatigue, FEA, reliability, warranty, Weibull

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Authors: José M. Liñeira Del Río, Ramón Rial, Khodor Nasser, María J.G. Guimarey

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The need to develop new lubricants that offer better anti-friction and anti-wear performance in internal combustion vehicles is one of the great challenges of lubrication in the automotive field. The addition of nanoparticles has emerged as a possible solution and, combined with the lubricating power of ionic liquids, may become one of the alternatives to reduce friction losses and wear of the contact surfaces in the conditions to which tribo-pairs are subjected, especially in the contact of the piston rings and the cylinder liner surface. In this study, the improvement in SAE 10W-40 engine oil tribological performance after the addition of magnesium oxide (MgO) nanoadditives and two different phosphonium-based ionic liquids (ILs) was investigated. The nanoparticle characterization was performed by means of transmission electron microscopy (TEM), Fourier-transform infrared spectroscopy (FTIR), Raman spectroscopy, X-ray diffraction (XRD), and scanning electron microscopy (SEM). The tribological properties, friction coefficients and wear parameters of the formulated oil modified with 0.01 wt.% MgO and 1 wt.% ILs compared with the neat 10W-40 oil were performed and analyzed using a ball-on-three-pins tribometer and a 3D optical profilometer, respectively. Further analysis on the worn surface was carried out by Raman spectroscopy and SEM microscopy, illustrating the formation of the protective IL and MgO tribo-films as hybrid additives. In friction tests with sliding steel-steel tribo-pairs, IL3-based hybrid nanolubricant decreased the friction coefficient and wear volume by 7% and 59%, respectively, in comparison with the neat SAE 10W-40, while the one based on IL1 only achieved a reduction of these parameters by 6% and 39%, respectively. Thus, the tribological characterization also revealed that the MgO and IL3 addition has a positive synergy over the commercial lubricant, adequately meeting the requirements for their use in internal combustion engines. In summary, this study has shown that the addition of ionic liquids to MgO nanoparticles can improve the stability and lubrication behavior of MgO nanolubricant and encourages more investigations on using nanoparticle additives with green solvents such as ionic liquids to protect the environment as well as prolong the lifetime of machinery. The improvement in the lubricant properties was attributed to the following wear mechanisms: the formation of a protective tribo-film and the ability of nanoparticles to fill out valleys between asperities, thereby effectively smoothing out the shearing surfaces.

Keywords: lubricant, nanoparticles, phosphonium-based ionic liquids, tribology

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Authors: Irlana C. do Mar, Thayna A. Ferreira, Dayane S. Rezende, Bruno A. M. Figueira, José M. R. Mercury

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This work presents a low-cost Mn starting material to synthesis manganese oxide octahedral molecular sieve with Mg²⁺ in the tunnel (Mg-OMS-1), based on the Mn residues from Carajás Mineral Province (Amazon, Brazil). After hydrothermal and cation exchange procedures, the Mn residues transformed to a single phase, Mg-OMS-1. The raw material and the synthesis processes were analyzed by means of X-ray diffraction (XRD), Scanning electron microscopy (SEM) and Infrared spectroscopy (FTIR). The tunnel structure was synthesized hydrothermally at 180 °C for three days without impurities. According to the XRD analysis, the formation of crystalline Mg-OMS-1 was identified through reflections at 9.8º, 12º and 18º (2θ), as well as a thermal stability around 300 ºC. The SEM analysis indicated that the final product presents good crystallinity with a homogeneous size. In addition, an intense and diagnostic FTIR band was identified at 515 cm⁻¹ related to the MnO₆ octahedral stretching vibrations.

Keywords: Mn residues , Octahedral Molecular Sieve, Synthesis, Characterization

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Authors: Md. Hafezur Rahaman, Md. Sagor Hosen, Md. Abdul Gafur, Rasel Habib

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This research is a systematic study of effects of poly(D-lactic acid) (PDLA) on the properties of poly(L-lactic acid)(PLLA)/microcrystalline cellulose (MCC)/PDLA blends by stereo complex crystallization. Blends were prepared with constant percentage of (3 percent) MCC and different percentage of PDLA by solution casting methods. These blends were characterized by Fourier Transform Infrared Spectroscopy (FTIR) for the confirmation of blends compatibility, Wide-Angle X-ray Scattering (WAXS) and scanning electron microscope (SEM) for the analysis of morphology, thermo-gravimetric analysis (TGA) and differential thermal analysis (DTA) for thermal properties measurement. FTIR Analysis results confirm no new characteristic absorption peaks appeared in the spectrum instead shifting of peaks due to hydrogen bonding help to have compatibility of blends component. Development of three new peaks from XRD analysis indicates strongly the formation of stereo complex crystallinity in the PLLA structure with the addition of PDLA. TGA and DTG results indicate that PDLA can improve the heat resistivity of the PLLA/MCC blends by increasing its degradation temperature. Comparison of DTA peaks also ensure developed thermal properties. Image of SEM shows the improvement of surface morphology.

Keywords: microcrystalline cellulose, poly(l-lactic acid), stereocomplex crystallization, thermal stability

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Authors: Kamel Taıbı, Abdelmadjid Rais

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Nickel–Aluminium ferrites with the general formula Ni Alx Fe2-x O4 (0 ≤ x ≤ 1) were studied using X-ray diffraction, Infra Red and Raman spectroscopy. XRD diffraction patterns and their Reitveld refinements show that all samples have a pure single-phase cubic spinel structure. From these patterns, the lattice parameters of these samples have been calculated and compared with those predicted theoretically. Most of the values were found to decrease with increasing Al content. Infra Red spectra showed two significant absorption bands. The high band corresponds to tetrahedral (A) sites and the lower band to octahedral [B] sites, thus confirming the single phase spinel structure. For all compositions, Raman spectra show the five active modes A1g + E1g + 3 T2g of the motion of O2- ions and both the A-site and B-site ions. The Raman frequencies trend with aluminium concentration show a blue shift for all modes consistent with the replacement of Fe3+ by lower mass Al3+. Composition dependence of the Raman frequency modes is discussed in relationship with the cations distribution among the A-sites and B-sites.

Keywords: Ni-Al ferrites, spinel structure, XRD, Raman spectroscopy

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Authors: Kanyarat Bussaban, Kunyanuth Kularbphettong

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This research aims to create a model for analysis of student behavior using Library resources based on data mining technique in case of Suan Sunandha Rajabhat University. The model was created under association rules, apriori algorithm. The results were found 14 rules and the rules were tested with testing data set and it showed that the ability of classify data was 79.24 percent and the MSE was 22.91. The results showed that the user’s behavior model by using association rule technique can use to manage the library resources.

Keywords: behavior, data mining technique, a priori algorithm, knowledge discovery

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Authors: Handie Pramana Putra, Ani Dijah Rahajoe

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The proliferation of smart devices and advancements in mobile communication technologies have permeated various facets of life with the widespread influence of e-commerce. Detecting abnormal transactions holds paramount significance in this realm due to the potential for substantial financial losses. Moreover, the fusion of data flow and control flow assumes a critical role in the exploration of process modeling and data analysis, contributing significantly to the accuracy and security of business processes. This paper introduces an alternative approach to identify abnormal transactions through a model that integrates both data and control flows. Referred to as the Extended Data Petri net (DPNE), our model encapsulates the entire process, encompassing user login to the e-commerce platform and concluding with the payment stage, including the mobile transaction process. We scrutinize the model's structure, formulate an algorithm for detecting anomalies in pertinent data, and elucidate the rationale and efficacy of the comprehensive system model. A case study validates the responsive performance of each system component, demonstrating the system's adeptness in evaluating every activity within mobile transactions. Ultimately, the results of anomaly detection are derived through a thorough and comprehensive analysis.

Keywords: database, data analysis, DPNE, extended data flow, e-commerce

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Authors: Mohit Kumar, Mayur Betharia

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Healthcare domain, with the emergence of Electronic Medical Record (EMR), collects a lot of data which have been attracting Data Mining expert’s interest. In the past, doctors have relied on their intuition while making critical clinical decisions. This paper presents the means to analyze the Medical workflows to get business insights out of huge dumped medical databases. Market Basket Analysis (MBA) which is a special data mining technique, has been widely used in marketing and e-commerce field to discover the association between products bought together by customers. It helps businesses in increasing their sales by analyzing the purchasing behavior of customers and pitching the right customer with the right product. This paper is an attempt to demonstrate Market Basket Analysis applications in healthcare. In particular, it discusses the Market Basket Analysis Algorithm ‘Apriori’ applications within healthcare in major areas such as analyzing the workflow of diagnostic procedures, Up-selling and Cross-selling of Healthcare Systems, designing healthcare systems more user-friendly. In the paper, we have demonstrated the MBA applications using Angiography Systems, but can be extrapolated to other modalities as well.

Keywords: data mining, market basket analysis, healthcare applications, knowledge discovery in healthcare databases, customer relationship management, healthcare systems

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Authors: Elias K. Maragos, Petros E. Maravelakis

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In Dynamic Data Envelopment Analysis (DDEA), which is a subfield of Data Envelopment Analysis (DEA), the productivity of Decision Making Units (DMUs) is considered in relation to time. In this case, as it is accepted by the most of the researchers, there are outputs, which are produced by a DMU to be used as inputs in a future time. Those outputs are known as intermediates. The common models, in DDEA, do not take into account the shape of the distribution of those inputs, outputs or intermediates data, assuming that the distribution of the virtual value of them does not deviate from linearity. This weakness causes the limitation of the accuracy of the analytical power of the traditional DDEA models. In this paper, the authors, using the concept of piecewise linear inputs and outputs, propose an extended DDEA model. The proposed model increases the flexibility of the traditional DDEA models and improves the measurement of the dynamic performance of DMUs.

Keywords: Dynamic Data Envelopment Analysis, DDEA, piecewise linear inputs, piecewise linear outputs

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Authors: M. N. Akhtar, J. N. Akhtar

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The present study evaluates the properties of class F fly ash as a replacement of natural materials in civil engineering construction industry. The low-lime flash similar to class F is the prime variety generated in India, although it has significantly smaller volumes of high-lime fly ash as compared to class C. The chemical and physical characterization of the sample is carried out with the number of experimental approaches in order to investigate all relevant features present in the samples. For chemical analysis, elementary quantitative results from point analysis and scanning electron microscopy (SEM)/dispersive spectroscopy (EDS) techniques were used to identify the element images of different fractions. The physical properties found very close to the range of common soils. Furthermore, the fly ash-based bricks were prepared by the same sample of class F fly ash and the results of compressive strength similar to that of Standard Clay Brick Grade 1 available in the local market of India.

Keywords: fly ash, class F, class C, chemical, physical, SEM, EDS

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Authors: Siva Prasad Peddi

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Silver nanoparticles were successfully synthesized from silver nitrate through a rapid green synthesis method using Eclipta prostrata leaf extract as a reducing cum stabilizing agent. The experimental procedure was readily conducted at room temperature and pressure, and could be easily scaled up. The silver nanoparticles thus obtained were characterized using UV-Visible Spectroscopy (UV-VIS) which yielded an absorption peak at 416 nm. The biomolecules responsible for capping of the bio-reduced silver nanoparticles synthesized using plant extract were successfully identified through FTIR analysis. It was evinced through Scanning Electron Microscope (SEM), and X-ray diffraction (XRD) analysis that the silver nanoparticles were crystalline in nature and spherical in shape. The average size of the particles obtained using Scherrer’s formula was 27.4 nm. The adopted technique for silver nanoparticle synthesis is suitable for large-scale production.

Keywords: silver nanoparticles, green synthesis, characterization, Eclipta prostrata

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Authors: Amal A. Al-Kahlawy, Heba H. El-Maghrabi

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Due to the increasing need to environment protection in real time need to energize new materials are under extensive investigations. Between others, TiO2 nanotubes (TNTs) nanocomposite with iron oxide and silver carbonate, are promising alternatives as high-efficiency visible light photocatalyst due to their unique properties and their superior charge transport properties. Our efforts in this domain aim the construction of novel nanocomposite of TiO2NT/Fe2O3@Ag2CO3. The structure, surface morphology, chemical composition and optical properties were characterized by X-ray diffraction (XRD), Raman, Fourier-transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM), energy dispersive X-ray spectrometer (EDS), transmission electron microscopy (TEM), selected area electron diffraction (SAED) and UV–vis diffuse reflectance spectroscopy (DRS). XRD results confirm the interaction of TiO2-NT with iron oxide. This novel nanocomposite shows remarkably enhanced performance for phenol compounds photodegradation. The experimental data shows a promising photocatalytic activity. In particular, a maximum value of 450 mg/g was removed within 60 min at solar light irradiation with degradation efficiency of 99.5%. The high photocatalytic activity of the nanocomposite is found to be related to the increased adsorption toward chemical species, enhanced light absorption and efficient charge separation and transfer. Finally, the designed TiO2NT/Fe2O3@Ag2CO3 nanocomposite has a great degree of sustainability and could has a potential application for the industrial treatment of wastewater containing toxic organic materials.

Keywords: nanocomposite, photocatalyst, solar energy, titanium dioxide nanotubes

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Authors: Pawel Albrycht, Monika Ksiezopolska-Gocalska, Robert Holyst

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Surface Enhanced Raman Spectroscopy (SERS) is a technique of growing importance not only in purely scientific research related to analytical chemistry. It finds more and more applications in broadly understood testing - medical, forensic, pharmaceutical, food - and everywhere works perfectly, on one condition that SERS substrates used for testing give adequate enhancement, repeatability, and homogeneity of SERS signal. This is a problem that has existed since the invention of this technique. Some laboratories use as SERS amplifiers colloids with silver or gold nanoparticles, others form rough silver or gold surfaces, but results are generally either weak or unrepeatable. Furthermore, these structures are very often highly specific - they amplify the signal only of a small group of compounds. It means that they work with some kinds of analytes but only with those which were used at a developer’s laboratory. When it comes to research on different compounds, completely new SERS 'substrates' are required. That underlay our decision to develop universal substrates for the SERS spectroscopy. Generally, each compound has different affinity for both silver and gold, which have the best SERS properties, and that's what depends on what signal we get in the SERS spectrum. Our task was to create the platform that gives a characteristic 'fingerprint' of the largest number of compounds with very high repeatability - even at the expense of the intensity of the enhancement factor (EF) (possibility to repeat research results is of the uttermost importance). As specified above SERS substrates are offered by SERSitive company. Applied method is based on cyclic potentiodynamic electrodeposition of silver or silver-gold nanoparticles on the conductive surface of ITO-coated glass at controlled temperature of the reaction solution. Silver nanoparticles are supplied in the form of silver nitrate (AgNO₃, 10 mM), gold nanoparticles are derived from tetrachloroauric acid (10 mM) while sodium sulfite (Na₂O₃, 5 mM) is used as a reductor. To limit and standardize the size of the SERS surface on which nanoparticles are deposited, photolithography is used. We secure the desired ITO-coated glass surface, and then etch the unprotected ITO layer which prevents nanoparticles from settling at these sites. On the prepared surface, we carry out the process described above, obtaining SERS surface with nanoparticles of sizes 50-400 nm. The SERSitive platforms present highly sensitivity (EF = 10⁵-10⁶), homogeneity and repeatability (70-80%).

Keywords: electrodeposition, nanoparticles, Raman spectroscopy, SERS, SERSitive, SERS platforms, SERS substrates

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Authors: Monika Rani, Claudio Marchesi, Stefania Federici, Laura E. Depero

Abstract:

Degradation of the aquatic environment by plastic litter, especially microplastics (MPs), i.e., any water-insoluble solid plastic particle with the longest dimension in the range 1µm and 1000 µm (=1 mm) size, is an unfortunate indication of the advancement of the Anthropocene age on Earth. Microplastics formed due to natural weathering processes are termed as secondary microplastics, while when these are synthesized in industries, they are called primary microplastics. Their presence from the highest peaks to the deepest points in oceans explored and their resistance to biological and chemical decay has adversely affected the environment, especially marine life. Even though the presence of MPs in the marine environment is well-reported, a legitimate and authentic analytical technique to sample, analyze, and quantify the MPs is still under progress and testing stages. Among the characterization techniques, vibrational spectroscopic techniques are largely adopted in the field of polymers. And the ongoing miniaturization of these methods is on the way to revolutionize the plastic recycling industry. In this scenario, the capability and the feasibility of a miniaturized near-infrared (MicroNIR) spectroscopy combined with chemometrics tools for qualitative and quantitative analysis of urban plastic waste collected from a recycling plant and microplastic mixture fragmented in the lab were investigated. Based on the Resin Identification Code, 250 plastic samples were used for macroplastic analysis and to set up a library of polymers. Subsequently, MicroNIR spectra were analysed through the application of multivariate modelling. Principal Components Analysis (PCA) was used as an unsupervised tool to find trends within the data. After the exploratory PCA analysis, a supervised classification tool was applied in order to distinguish the different plastic classes, and a database containing the NIR spectra of polymers was made. For the microplastic analysis, the three most abundant polymers in the plastic litter, PE, PP, PS, were mechanically fragmented in the laboratory to micron size. The distinctive arrangement of blends of these three microplastics was prepared in line with a designed ternary composition plot. After the PCA exploratory analysis, a quantitative model Partial Least Squares Regression (PLSR) allowed to predict the percentage of microplastics in the mixtures. With a complete dataset of 63 compositions, PLS was calibrated with 42 data-points. The model was used to predict the composition of 21 unknown mixtures of the test set. The advantage of the consolidated NIR Chemometric approach lies in the quick evaluation of whether the sample is macro or micro, contaminated, coloured or not, and with no sample pre-treatment. The technique can be utilized with bigger example volumes and even considers an on-site evaluation and in this manner satisfies the need for a high-throughput strategy.

Keywords: chemometrics, microNIR, microplastics, urban plastic waste

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Authors: J. Suneetha, Vijayalaxmi

Abstract:

Sequential Pattern Mining involves applying data mining methods to large data repositories to extract usage patterns. Sequential pattern mining methodologies used to analyze the data and identify patterns. The patterns have been used to implement efficient systems can recommend on previously observed patterns, in making predictions, improve usability of systems, detecting events, and in general help in making strategic product decisions. In this paper, identified performance of approximate sequential pattern mining defines as identifying patterns approximately shared with many sequences. Approximate sequential patterns can effectively summarize and represent the databases by identifying the underlying trends in the data. Conducting an extensive and systematic performance over synthetic and real data. The results demonstrate that ApproxMAP effective and scalable in mining large sequences databases with long patterns.

Keywords: multiple data, performance analysis, sequential pattern, sequence database scalability

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Authors: F. Chigondo, G. Chitabati

Abstract:

Hexavalent chromium is toxic and is widely used in many industries hence efficient and economical methods must be explored to remove the chromium(VI) from the environment. The removal of Cr (VI) from aqueous solutions onto polyaniline coated maize tassel was studied in batch mode at varying initial metal concentrations, adsorbent doses, pH and contact times. The residual Cr (VI) concentrations before and after adsorption were analyzed by Ultraviolet–visible spectroscopy. FTIR analysis of the polyaniline coated maize tassel showed the presence of C=C, C=N, C-H, C-N and N-H groups. Adsorption conditions were deduced to be pH of 2, adsorbent dosage 1g/L, Cr(VI) initial concentration of 40mg/L contact time of 150 minutes and agitation speed of 140rpm. Data obtained fitted best to the Langmuir isotherm (R2 = 0.972) compared to the Freundlich isotherm (R2 0.671. The maximum adsorption capacity was found to be 125mg/L. Correlation coefficients for pseudo first order and pseudo second order were 0.952 and 0.971 respectively. The adsorption process followed the pseudo-second order kinetic model. The studied polyaniline coated maize tassel can therefore be used as a promising adsorbent for the removal of Cr (VI) ion from aqueous solution.

Keywords: polyaniline-coated, maize tassels, adsorption, hexavalent chromium

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Authors: Ouafek Nora, Keghouche Nassira, Dehdouh Heider, Untidt Carlos

Abstract:

A lot of knowledge has been accumulated on the metal clusters supported on oxide surfaces because of their multiple applications in microelectronics, heterogeneous catalysis, and magnetic devices. In this work, the surface state of Ni / MgO has been studied by XPS (X-ray Photoemission Spectroscopy). The samples were prepared by impregnation with ion exchange Ni²⁺ / MgO, followed by either a thermal treatment in air (T = 100 -350 ° C) or a gamma irradiation (dose 100 kGy, 25 kGy dose rate h -1). The obtained samples are named after impregnation NMI, NMR after irradiation, and finally NMC(T) after calcination at the temperature T (T = 100-600 °C). A structural study by XRD and HRTEM reveals the presence of nanoscaled Ni-Mg intermetallic phases (Mg₂Ni, MgNi₂, and Mg₆Ni) and magnesium hydroxide. Mg(OH)₂ in nanometric range (2- 4 nm). Mg-Ni compounds are of great interest in energy fields (hydrogen storage…). XPS spectra show two Ni2p peaks at energies of about 856.1 and 861.9 eV, indicating that the nickel is primarily in an oxidized state on the surface. The shift of the main peak relative to the pure NiO (856.1 instead of 854.0 eV) suggests that in addition to oxygen, nickel is engaged in another link with magnesium. This is in agreement with the O1s spectra which present an overlap of peaks corresponds to NiO and MgO, at a calcination temperature T ≤ 300 °C.

Keywords: XPS, XRD, nanoparticules, Ni-MgO

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