Developed Method Research Articles

Finding The Inverse of A Polynomial Modulo in The Ring Z[X] Based on The Method of Undetermined Coefficients

This paper presents the theoretical foundations of finding the inverse of a polynomial modulo in the ring Z[x] based on the method of undetermined coefficients. The use of the latter makes it possible to significantly reduce the time complexity of calculations avoiding the operation of finding the greatest common divisor. An example of calculating the inverse of a polynomial modulo in the ring Z[x] based on the proposed approach is given. Analytical expressions of the time complexities of the developed and classical methods depending on the degrees of polynomials are built. The graphic dependence of the complexity of performing the operation of finding the inverse of a polynomial in the ring Z[x] is presented, which shows the advantages of the method based on undetermined coefficients. It is found that the efficiency of the developed method increases logarithmically with an increase in the degrees of polynomials.

A Comprehensive Analysis of Fel Ursi and Its Common Adulterants Based on UHPLC-QTOF-MSE and Chemometrics.

As one of the four most valuable animal medicines, Fel Ursi, named Xiong Dan (XD) in China, has the effect of clearing heat, calming the liver, and brightening the eyes. However, due to the special source of XD and its high price, other animals' bile is often sold as XD or mixed with XD on the market, seriously affecting its clinical efficacy and consumers' rights and interests. In order to realize identification and adulteration analysis of XD, UHPLC-QTOF-MSE and multivariate statistical analysis were used to explore the differences in XD and six other animals' bile. XD, pig gall (Zhu Dan, ZD), cow gall (Niu Dan, ND), rabbit gallbladder (Tu Dan, TD), duck gall (Yan Dan, YD), sheep gall (Yang Dan, YND), and chicken gall (Ji Dan, JD) were analyzed by UHPLC-QTOF-MSE, and the MS data, combined with multivariate analysis methods, were used to distinguish between them. Meanwhile, the potential chemical composition markers that contribute to their differences were further explored. The results showed that XD and six other animals' bile can be distinguished from each other obviously, with 27 ions with VIP > 1.0. We preliminarily identified 10 different bile acid-like components in XD and the other animals' bile with significant differences (p < 0.01) and VIP > 1.0, such as tauroursodeoxycholic acid, Glycohyodeoxycholic acid, and Glycodeoxycholic acid. The developed method was efficient and rapid in accurately distinguishing between XD and six other animals' bile. Based on the obtained chemical composition markers, it is beneficial to strengthen quality control for bile medicines.

Fast Determination of Fat-soluble Vitamins in Pharmaceutical Preparations by High-Performance Liquid Chromatography

Background: Vitamins are needed for the healthy functioning of the body. When these vitamins are not in sufficient amounts in the body, they are usually taken externally with pharmaceutical preparations. Taking vitamins into the body in the right amounts is possible by analyzing the amounts in pharmaceutical preparations with validated methods. Methods: In this study, a fast, simple, easily applicable, and selective normal-phase HPLC method was developed for the simultaneous determination of fat-soluble A, D3, E, and K1 vitamins in pharmaceutical preparations from syrup and tablets. Separation of the vitamins was carried out on a Zorbax CN column (250 x 4.6 mm, 5 µm) using a mixture of hexane-isopropyl alcohol (98:2, v/v) at 30°C column temperature and 1 ml/min flow rate. The detection wavelength is 280 nm. The developed method has been validated according to ICH Harmonised Tripartite Guideline Validation of Analytical Procedures: Text and Methodology Q2(R1) rules. Results: Calibration graphs are linear over the range of 10-1000 µg ml-1 , 1-50 µg ml-1 , 10-2000 µg ml-1 , 0.5-20 µg ml-1, and the limit of detection values were found to be 1.496, 0.280, 1.388 and 0.040 µg ml-1 for A, D3, E and K1 vitamins, respectively. Relative standard deviation values, which express within-day and between-day repeatability, were found below 2.54%. Average recovery values were also found at about 100.28, 101.46, 100.65, and 100.29% for A, D3, E, and K1 vitamins, respectively Conclusion: The developed and validated method was successfully applied to the simultaneous analysis of fat-soluble vitamins A, D3, E, and K1 in pharmaceutical preparations in syrup and tablet form.

Understanding thermal transport in magnesium solid solutions through first-principles approaches and machine learning feature screening

The solid solution phases have a large influence on the thermal conductivity of alloys, but the physics behind this effect is complicated. Existing works mainly utilize experimental methods to study the thermal conductivity of alloys. However, due to the coexistence of multi-phase and insufficient understanding of the microscopic property variations in different alloy systems, it remains unclear how different solute atoms can affect the thermal transport of solid solutions. In this work, we employ first-principles simulations based on the Korringa–Kohn–Rostoker coherent potential approximation method and the Boltzmann transport equation to calculate the thermal conductivity of 38 binary magnesium solid solutions with dilute solute atom concentration. Solute atoms can greatly reduce the thermal conductivity of magnesium. Phonon contribution is found to be less than 10 %. The machine learning feature screening methods are further applied to identify the key properties that influence their thermal conductivity the most. Different from the commonly used Linde's law, which states that the resistivity is proportional to the square of valence difference, the machine learning screening indicates that thermal conductivity is predominantly influenced by six features in total. Among them, the variance of the density of states of s + p, d + f orbitals at Fermi level is highly correlated to the electronic thermal conductivity of magnesium alloys. These correlations underscore the role of virtual bond states formed in magnesium alloys due to the presence of solute atoms. The developed method and uncovered physical mechanism can potentially be applied to other solid solution systems, which is an important step to achieve predictive design of high thermal conductivity metallic alloy.

Automated design of embedded digital signal processing systems on SOC platform

The object of the study is the procedures for automated design and analysis of digital signal processing algorithms on the SoC technology platform. The subject of the study is models, methods and procedures for designing and optimal selection of SoC components for the implementation of digital signal processing algorithms for audio spectrum. The aim of the study is to develop models and procedures for determining the possibilities of a compromise distribution of signal processing algorithm computations in the cycle of computer-aided design on the SoC technology platform in terms of performance and the feasibility of using hardware and software algorithms realization. The article solves the following tasks: consideration of the procedures for interacting the processor core with programmable logic as part of system-on-chip systems; development of procedures for computer-aided design and analysis of signal processing systems using programming languages and hardware description languages for the implementation of embedded systems. The following methods are being used: implementation of digital signal processing algorithms in the C programming language and high-level synthesis tools for realizing IP blocks, diagnostic experiment by generating test signal patterns, and analysis of the processing results at the system output. The results achieved. Based on the analysis of the procedures for the interaction of the processor core and programmable logic on the selected SoC platform, a model of the audio spectrum signal processing system is designed. The practical implementation was performed based on the Vivado/Vitis/Vitis HLS CAD tool stack. The proposed model was verified using a programmable test signal generator and analyzing the obtained characteristics of digital filters at the system output. Conclusions. The article analyzes the principles of designing embedded information processing systems implemented in system-on-chip. The principles of building and analyzing digital signal processing systems based on system-on-chip containing programmable logic and processor parts are considered. The developed methods have been tested on the algorithms of CIC and FIR filters on the technological platform of SoC FPGA of the ZYNQ-7000 family of Xilinx company.

Development of interactive digital teaching materials based on 21st century skills in special purpose arabic language courses at STAI Attanwir Bojonegoro

Special Purpose Arabic Language refers to the teaching or learning of Arabic language tailored to specific needs or objectives. This means that Arabic language lessons are designed with a focus on its usage context in specific fields or activities, as opposed to a general approach to teaching Arabic. Special Purpose Arabic Language courses at the university level are tailored to specific needs and objectives in a professional context, producing graduates ready to face global challenges. The objectives of this research are (1) to analyze the process of developing interactive digital teaching materials based on 21st-century skills in Special Purpose Arabic Language courses at STAI Attanwir Bojonegoro, (2) to analyze the feasibility of interactive digital teaching materials based on 21st-century skills in Special Purpose Arabic Language courses at STAI Attanwir Bojonegoro, and (3) to analyze the effectiveness of interactive digital teaching materials based on 21st-century skills in Special Purpose Arabic Language courses at STAI Attanwir Bojonegoro. This research uses the Research and Development (R&amp;D) method using the ADDIE model. Data collection techniques in this study use expert validation questionnaires, expert validation materials, student responses, and tests. The results of this research and development are as follows: (1) The development process consists of five steps: analysis, development, design, implementation, and evaluation, resulting in the production of interactive digital teaching materials based on 21st-century skills. (2) Based on validation results by experts, an average score of 90% was obtained. According to the Likert scale, the value of 90% falls into the category of very feasible because it is within the range of &gt;61%. Meanwhile, the average percentage of student responses obtained an overall score of 88.5%, falling into the category of very feasible. (3) The results of the effectiveness test of teaching materials using a paired sample T-test showed a significant difference between pre-test and post-test scores with a significant value (2-tailed) of p = 0.000, &lt;0.05. The null hypothesis (H0) in this study was rejected, and the alternative hypothesis (Ha) was accepted, indicating a significant difference between the two tests. Based on the data above, the developed teaching materials are effective in Special Purpose Arabic Language courses.

Identification of oil contamination in process water using fluorescence excitation emission matrix (FEEM) and parallel factor analysis (PARAFAC)

ABSTRACT Fuel oil is widely used within Eskom, a power generation company in South Africa. Eskom's coal-fired power stations use up to 30,000 L of fuel oil per hour during a cold start-up, a consequence of which results in oil leaks to the dams. Oil contamination in water treatment plants causes irreversible membrane fouling, requiring costly replacement. This research work focused on the development of a rapid method for the identification of low concentrations of the water-soluble oil component fraction of crude fuel oil. For the developed method, known volumes of the water-soluble fraction of crude oil were spiked into various matrices of process water. FEEMs were collected using the patented HORIBA Aqualog spectrometer and data were modelled with PARAFAC. The results were well described with a four-component model, which included an oil component and three natural organic matter components, with a split-half validation match of 90%. The oil component was verified using linear regression of the PARAFAC component scores yielding an R2 value of 0.98. From the scores, a qualitative pass/fail test was developed such that process water can be analysed and subjected to the model to indicate the presence of oil contamination beyond a damaging threshold.

A modified method of self-recovery of distributed software in heterogeneous computer systems

The object of research is the distributed computing process in heterogeneous computer systems. The subject of the research is methods of self-healing for distributed software on heterogeneous computer systems. The goal is to increase the efficiency of distributed data processing systems with support for the functional stability of the computing process by developing a modified method of self-healing of distributed software. Tasks: to investigate the existing methods of restoring the distributed computing process, to draw conclusions about their advantages and disadvantages; on the basis of mathematical models of tasks, computing resources and existing methods of resource allocation, develop a modification of the method of self-recovery of distributed software taking into account management strategies, finding the best solution for the selected criteria, reducing energy consumption during the execution of tasks; conduct a number of experiments comparing the developed method with existing ones. Research methods are based on the use of set theory, general systems theory, and simulation modeling theory. The results of the experiments obtained during the simulation of the allocation of software tasks to computing resources in a simulated simulation environment and the simulation of the computing process during self-recovery in case of resource failures confirm the effectiveness of the proposed method. Conclusion: the application of the method in distributed computing control systems does not increase the time the system spends on performing the task in the absence of failures, at the same time, in the presence of failures, it allows to restore the functionality of the software task faster and reduces the execution time by 8–17%, and energy consumption by 7–12%. There is also an increase in efficiency with an increase in the size of the tasks and the probability of failures. The development of technologies for automated or automatic use of methods of resource allocation and self-recovery can be indicated as areas for future research.

Optimization of Green Sample Preparation for the Determination of Hydroxycinnamic Acids in Multi-Floral Honey Using Response Surface Methodology

Hydroxycinnamic acids are an essential phenolic group in honey that are related with its diverse health effects. Furthermore, they can be considered as potential biomarkers for botanical and geographical origin. The extraction of hydroxycinnamic acids from honey requires complicated extraction techniques due to their low contents and matrix particularity. The goal of the present work was to develop a green sample preparation method for the solubilization of hydroxycinnamic acids in honey samples. Thus, a Box–Behnken design has been used to investigate the effect of four factors: (i) percentage of ethanol (60–90%, v/v), (ii) temperature (30–60 °C), (iii) solvent-honey ratio (10–30 mL g−1), and (iv) sonication time (10–40 min) on the contents of caffeic, chlorogenic, and ferulic acids. Based on the desirability index, the ultrasound-assisted mixing of honey with 60.0% (v/v) ethanol at a solvent-honey ratio of 10 mL g−1 for a period of 17.8 min at a temperature of 54.6 °C resulted in the maximum solubilization of hydroxycinnamates. Subsequently, the greenness of developed method was assessed and applied successfully on the analysis of honeys. The present study reports for first time the hydroxycinnamic acid fingerprint of multi-floral honey produced in Cyprus.

Values Spiral Development Method in the Implementation of Digitalization Projects in Syncretic Methodology

The article is devoted to the formulation of the method of spiral development of values in the implementation of digitalization projects of self-managed organizations, which was developed within the syncretic methodology of project management. The application of the proposed method is considered in the field of infrastructure restoration projects of Ukraine. A scientific problem regarding the availability of a project management methodology that meets modern challenges has been formulated. The gap between the practical needs of project-oriented organizations in a new unique methodology and the availability of established standards for solving typical project management tasks is revealed. A review of literary sources was carried out, modern project management trends were highlighted, including: increasing complexity of modern corporate project management methodologies, application of value-oriented management approaches, models of self-managed teams. The principles of value-oriented management for infrastructure restoration projects implemented by self-managed organizations within the syncretic methodology have been formulated. The method of values spiral development of a project-oriented organization, which uses models of self-management, through the implementation of digitalization projects within the syncretic methodology, is proposed. Within the scope of the method: a value model for digitalization projects of self-managed organizations is proposed; the concept of "stellarator project" is introduced, the definition of such a project is given. The results of the approbation of the method in a project-oriented organization working in the field of infrastructure restoration of Ukraine are presented and analyzed. Areas of improvement of the project-oriented activities of the specified organization have been determined. A SWOT analysis of the proposed method was carried out. Conclusions based on the research are formulated, prospects for further research in the chosen direction are outlined.

Development of a fluorescent nano-sensing probe for atomoxetine analysis: Additional clinical pharmacokinetic study

Atomoxetine is a psychostimulant drug used for the treatment of attention-deficit/hyperactivity disorder (ADHD) symptoms in people with autism. Herein, eco-friendly fluorescent carbon quantum dots (CQDs) were synthesized using black-eyed pea beans and characterized for the purpose of quantifying atomoxetine in pharmaceutical capsules and human plasma. The selectivity of these CQDs towards atomoxetine was improved by functionalizing their surface with an atomoxetine-tetraphenylborate ion complex. The quantification of atomoxetine is based on measuring the fluorescence quenching of the functionalized CQDs in response to varying concentrations of atomoxetine. The Stern-Volmer plot was employed to investigate the mechanism through which atomoxetine quenches the fluorescence intensity of the CQDs. The outcomes indicated a dynamic quenching mechanism. The applied method was optimized and validated in compliance with ICH requirements, resulting in excellent linearity across the concentration range of 50–800 ng/mL. The developed method was successfully used to quantify atomoxetine in pharmaceutical dosage form and human plasma with acceptable accuracy and precision outcomes. In addition, the method was applied for clinical pharmacokinetic study of atomoxetine in the plasma of children diagnosed with both autism and ADHD. Atomoxetine was rapidly absorbed after a single oral dose of 10 mg, reaching maximum concentration within two hours and having a half-life (t1/2) of 3.11 h. Moreover, the method demonstrates a notable degree of eco-friendliness, as evidenced by two greenness evaluation metrics; Green Analytical Procedure Index (GAPI) and Analytical GREEnness (AGREE).

On-Line Preconcentration and Determination of Nuciferine and O-Nornuciferine in Lotus Leaves by Cation-Selective Exhaustive Injection (CSEI)-Sweeping-Micellar Electrokinetic Chromatography (MEKC)

On-line preconcentration incorporating cation-selective exhaustive injection (CSEI) and sweeping followed by micellar electrokinetic chromatography (MEKC) was developed for the simultaneous determination of the bioactive alkaloids nuciferine and O-nornuciferine. The parameters affecting the analytical performance were systematically investigated. Under the optimal conditions, the enrichment factor was significantly improved by 7000 to 13000-fold compared with traditional MEKC. The analytes were well separated within 15 min. The limits of detection for nuciferine and O-nornuciferine were 4.00 and 2.00 ng∙mL−1, and the limits of quantification were 8.00 and 10.00 ng∙mL−1, respectively. The relative standard deviations for intra-day and inter-day precision were less than 3.0%. The recoveries of the analytes were from 98.9% to 102%. Furthermore, the developed method was demonstrated to be suitable for the analysis of nuciferine and O-nornuciferine in lotus leaves, offering high performance without the loss of resolution. CSEI-sweeping-MEKC provides a simple, environmental-friendly option for preconcentration and quantification of nuciferine and O-nornuciferine.

Simultaneous deep eutectic solvent based microextraction of Allura Red and Brilliant Blue in violet-purple foodstuffs

A vortex-assisted simultaneous deep eutectic solvent based microextraction and spectrophotometric determination method was established for the first time to simultaneously monitor Allura Red and Brilliant Blue in violet-purple foodstuffs. A ternary deep eutectic solvent was created using benzoic acid, tetra butyl ammonium bromide and benzyl alcohol at 1:1:3mol ratio. The method variables including pH, volume of deep eutectic solvent and vortex time were optimized by Box-Behnken design of response surface methodology. The limits of detection were determined to be 25 and 9µg/L for Allura Red and Brilliant Blue, respectively. The linear dynamic ranges of the method were obtained between 82-12000 and 29-4200µg/L for Allura Red and Brilliant Blue, respectively. Preconcentration factor of the method was obtained as 15. Greenness evaluation was performed using Analytical GREEnness tools. Extraction mechanisms affecting quantitative simultaneous microextraction of the target dyes were explained. The developed method was validated with high-performance liquid chromatography analysis. Analyte addition-recovery tests were also applied to confectionery samples to validate the proposed method and determine the dye contents of foodstuffs. Allura Red and Brilliant Blue contents of violet-purple confectioneries were determined between 3.85-74.59 and 4.02-26.11µg/g concentrations with 94.5-98.6% and 93.0-101.0% recoveries, respectively.

On-Line Preconcentration and Determination of Nuciferine and O-Nornuciferine in Lotus Leaves by Cation-Selective Exhaustive Injection (CSEI)-Sweeping-Micellar Electrokinetic Chromatography (MEKC)

On-line preconcentration incorporating cation-selective exhaustive injection (CSEI) and sweeping followed by micellar electrokinetic chromatography (MEKC) was developed for the simultaneous determination of the bioactive alkaloids nuciferine and O-nornuciferine. The parameters affecting the analytical performance were systematically investigated. Under the optimal conditions, the enrichment factor was significantly improved by 7000 to 13000-fold compared with traditional MEKC. The analytes were well separated within 15 min. The limits of detection for nuciferine and O-nornuciferine were 4.00 and 2.00 ng∙mL−1, and the limits of quantification were 8.00 and 10.00 ng∙mL−1, respectively. The relative standard deviations for intra-day and inter-day precision were less than 3.0%. The recoveries of the analytes were from 98.9% to 102%. Furthermore, the developed method was demonstrated to be suitable for the analysis of nuciferine and O-nornuciferine in lotus leaves, offering high performance without the loss of resolution. CSEI-sweeping-MEKC provides a simple, environmental-friendly option for preconcentration and quantification of nuciferine and O-nornuciferine.

Sampling-rate calibration vs. equilibrium calibration for in vivo solid-phase microextraction: Analysis of neonicotinoids in bananas

In vivo solid-phase microextraction (in vivo SPME) is an emerging fascinating sample pretreatment technique, but its quantitative correction method is different from the traditional correction methods, which has become a bottleneck limiting its development. At present, the sampling-rate calibration and equilibrium calibration are mainly used, however, their characteristics and applicability are not clear. In this study, the sampling-rate calibration and equilibrium calibration were evaluated in the case of the determination of neonicotinoids in bananas by in vivo SPME. The factors that affect the sampling rate (Rs), such as the matrix states, sampling durations, and individual differences were studied, and they all had impacts on Rs. Conversely, the equilibrium distribution coefficient (Kfs) remained constant after extraction equilibrium and the individual differences were smaller. The highest accuracy and precision were achieved by equilibrium calibration, and the relative recoveries were in the range of 83.2 %-104.3 % with the relative standard deviations below 8.1 % compared to a standard QuEChERS-based method. The lower limits of quantification for 4 neonicotinoids in bananas were below 5 ng g−1, lower than the standard method and the maximum residue levels in China and the European Union. This work clarifies the characteristics, rules and performance of the sampling-rate calibration and equilibrium calibration, which is of crucial importance for the development and application of in vivo SPME. The developed method is convenient, sensitive, and accurate for the determination of pesticide residues, which is of great significance to guide the safe use of pesticides in the field and prevent products with excessive pesticide residues from entering the market.

An analytical-atomistic model for elastic behavior of silicon nanowires

Silicon nanowires entail significant potential as sensors in nanoelectromechanical systems. Despite its crucial impact in such applications, inconsistent trends in mechanical behavior reported in computational and experimental studies remain unexplained. Hence, scale effect in even the most fundamental elastic properties requires clarification. This work introduces a multiscale model to bridge the existing gap between atomistic simulations and experimental observations encountered around a critical dimension of 10 nm. The combined approach of this work is based on molecular dynamics and modified core–shell model and captures the scale effect over a substantial size range. The evolution of the modulus of elasticity is thus studied and linked to nanowire critical dimension through the parameterization of surface inhomogeneity. The developed method is also validated through an analysis of native oxide revealing an average modulus of elasticity of 75 GPa. The method’s applicability can be extended to similar one-dimensional structures with unique surface states.

A platform for continuous monitoring of the degradation of aluminum beverage can lids in realistic conditions through electrochemical impedance spectroscopy

The coatings on aluminum beverage can lid interiors can be prone to long-term degradation due to the high impact forces during fabrication and the corrosive nature of beverages. Multi-month tests are required to assess their resistance to this degradation. This study aims to present an innovative can lid coating testing method that incorporates in-situ Electrochemical Impedance Spectroscopy (EIS) monitoring under real-world conditions and with actual beverages. A robust testing chamber was meticulously engineered to house the 3D-shaped lid and maintain the conditions found in a beverage can. Experiments were conducted at stressed and non-stressed conditions, assessing different coatings and different beverages. The developed method has the potential to mimic the multi-month pack tests and offers a quicker, more insightful, and less laborious alternative for the lid coating degradation assessment. Ultimately, this method could help in improving the longevity and quality of aluminum beverage cans.

Development and effectiveness of digital classroom assessment document for form one mathematics in secondary school

Classroom assessment is essential for tracking students’ progress and improving teaching and learning in the classroom. However, the lack of clear documentation to guide teachers in assessing student mastery often hinders effective communication between teachers and stakeholders about the students’ progress. This study aimed to develop and test the digital classroom assessment document (CA-Do) for form one mathematics to improve classroom assessment practices. Design research and development method, based on ADDIE model, was used to create the digital CA-Do, and 55 mathematics teachers from 55 schools were sampled using stratified sampling. The data collected was then analyzed using SPSS version 27. The digital CA-Do received a satisfactory expert validity score of content validity index (1.00), and found all four tested sub-constructs (i.e., usefulness, ease of use, ease of learning, and satisfaction of use) to be of high level. There were significant differences in teachers’ knowledge post-familiarization with the digital CA-Do. The study concludes that the digital CA-Do can aid teachers in recording the intervention and impact of teaching and learning information and consistently assessing pupils’ mastery level. This research provides guidance to educators on how to modify their classroom assessment strategies to enhance teaching outcomes and classroom assessment methods, particularly formative assessment.

Furfural analysis of aqueous and oily foodstuffs using a single modified paper for combined headspace extraction, derivatization and paper spray mass spectrometry

Furfurals, including 2-furaldehyde, 5-methylfurfural and 5-hydroxymethylfurfural, widely exist in carbohydrate-rich daily foods, and may have toxic effects on humans. Here, a new headspace extraction-paper spray mass spectrometry (HSPS-MS/MS) method was established for furfural detection, in which the extraction and derivatization of volatiles with pre-loaded derivatization agent on paper tips is combined with paper spray mass spectrometry for detection. By this simple and cheap approach, interference of non-volatile matrix compounds is prevented, and the derivatization agent improves electrospray-type ionization efficiency, thus increasing selectivity and sensitivity. The approach was optimized, by investigating positioning during extraction, extraction duration, derivatization agent, addition of internal standard for quantification and finally validated. For this, the developed method was benchmarked against HPLC-UV and could obtain detections limits of 0.32–0.40 μg mL−1 for 2-furaldehyde, 5-methylfurfural and 5-hydroxymethylfurfural in olive oil. Moreover, fast screening of free furfurals in soy sauce, coffees and teas was demonstrated with the HSPS-MS/MS method.

Autopilot drone in construction: A proof of concept for handling lightweight instruments and materials

Applications of Unmanned Aerial Vehicles (UAVs) in construction have been increased in recent years mainly for purposes of automatically collecting field data. In the market, there is a growing opportunity for using UAVs in material handling. On the other side, vertical transportation in construction sites is a crucial challenge that leads to a drop in productivity efficiency. This paper presents a proof of concept for automating the lifting procedure of lightweight instruments and materials in construction sites. To do so, a platform is developed that could automatically manage material/instrument handling requests via an autopilot drone. The aircraft position is tracked with an onboard GPS module which is not accurate in urban areas. So inaccurate GPS signals could deviate the drone from the predefined path. To tackle this problem, a machine vision algorithm is utilized to calibrate the real-time position of the aircraft. A self-supervised learning algorithm is integrated into the system to handling collision avoidance during the flight. Finally, the developed methods are tested with an UAV in a real world environment to demonstrate the potentials of hiring autopilot drones in construction.