Developed Method Research Articles

An attempt to open up a new path of rural development? rural transformational development under the characteristic town strategy in China

ABSTRACT The global decline in rural areas has made rural transformational development a subject of significant interest. The Characteristic Town (CT) strategy, a prominent aspect of China’s recent urbanization efforts, focuses on innovative development methods to promote coordinated urban-rural growth and enhance capacity and quality. However, the mechanisms through which this strategy facilitates potential rural transformational development have not yet been investigated. This study addresses this gap by employing a case study approach, using desk research, participatory observation, semi-structured interviews, and questionnaires. The findings indicate that environmental transformation, achieved through targeted planning, design, and construction, is a prerequisite for the CT strategy to stimulate rural transformational development. Subsequently, economic transformation is a crucial step, which includes establishing a sustainable and systematic economic industrial system, local marketing and promotion, and facilitating private sector participation. The strategy also generates social effects, such as a modest improvement in living standards, a lack of public participation, changes in residents’ self-identity, and potential social estrangement between residents and newcomers. The rural transformational development driven by the CT strategy represents a process of creative destruction that progresses quickly, necessitating the consideration of various countermeasures.

Combination of online hollow fiber liquid phase microextraction with smartphone-based sensing for in situ formaldehyde assay in fabric and wastewater samples.

A miniaturized analytical methodology was introduced based on the combination of a direct and online hollow fiber microextraction method with smartphone color detection. The method was used for the determination of formaldehyde (target analyte) in fabric and wastewater samples. In this regard, two reagents including ammonium acetate buffer and acetylacetone were added to the formaldehyde samples to create a colored compound. The colored compound was extracted from the sample by using the hollow fiber liquid-phase microextraction method, the extracted phase was not taken out of the extraction box and was directly transferred into a specially designed detection cell, and a smartphone was applied forin-situ color sensing and data readout. This combination gathered the advantages of both state-of-the-art microextraction techniques and smartphone sensing. Formaldehyde, as a carcinogenic compound widely used in paint and clothing industries, was selected as a model test. Factors affecting extraction efficiency were investigated and optimized, including the type of organic solvents, reagent concentration, salt, pH, stirring speed, reaction temperature, and extraction time. The linear region of the method under optimal conditions was 40-1500µg L-1 for wastewater samples and 0.3-11.2mg kg-1 for fabrics. The limit of detection and limit of qualification were 13 and 40µg L-1, respectively. The relative standard deviations for concentrations of 100 and 1000µg L-1 were 6% and 4%, respectively. To evaluate the application of the method for real samples, types of fabric and two samples of oil refinery wastewater were selected. The relative recovery in real samples was 84-98%. The results of the analytical parameters of the method show that the developed method can be used as an efficient method to determine formaldehyde in real samples.

Accelerated Gradient Approach For Deep Neural Network-Based Adaptive Control of Unknown Nonlinear Systems.

Recent connections in the adaptive control literature to continuous-time analogs of Nesterov's accelerated gradient method have led to the development of new real-time adaptation laws based on accelerated gradient methods. However, previous results assume that the system's uncertainties are linear-in-the-parameters (LIP). To compensate for non-LIP uncertainties, our preliminary results developed a neural network (NN)-based accelerated gradient adaptive controller to achieve trajectory tracking for nonlinear systems; however, the development and analysis only considered single-hidden-layer NNs. In this article, a generalized deep NN (DNN) architecture with an arbitrary number of hidden layers is considered, and a new DNN-based accelerated gradient adaptation scheme is developed to generate estimates of all the DNN weights in real-time. A nonsmooth Lyapunov-based analysis is used to guarantee the developed accelerated gradient-based DNN adaptation design achieves global asymptotic tracking error convergence for general nonlinear control affine systems subject to unknown (non-LIP) drift dynamics and exogenous disturbances. A comprehensive set of simulation studies are conducted on a two-state nonlinear system, a robotic manipulator, and a complex 20-D nonlinear system to demonstrate the improved performance of the developed method. Our simulation studies demonstrate enhanced tracking and function approximation performance from both DNN architectures and accelerated gradient adaptation.

Quantitative analysis of therapeutic peptides by CZE using multiple sample injection in hydrodynamically closed separation system.

Therapeutic peptides have emerged as an innovative and promising class of therapeutic compounds in modern medicine. Synthetic peptide analogs triptorelin and lanreotide are known for their pronounced clinical versatility and potency. In this study, we present the development and validation of novel methods based on capillary zone electrophoresis performed in hydrodynamically closed system (HCS) and paired with ultraviolet detection and repeated injection sample introduction. To the best of our knowledge, we developed the first capillary electrophoresis-based method for the determination of lanreotide, and concurrently, the first HCS method for the determination of triptorelin. Maximal separation efficiency and signal intensity were achieved using background electrolytes composed of 50mM formic acid with the addition of 0.05% (v/v) methyl-hydroxyethyl cellulose. The proposed methods exhibit favorable performance characteristics, namely, calibration curve (r2 exceeding 0.99), low limits of detection (0.25µg/mL in a water matrix and 0.5µg/mL in synthetic urine), acceptable precision (relative standard deviation ranging from 2.2% to 9.6% for intraday repeatability and between 5.2% and 14.9% for interday reproducibility), and accuracy (relative errors falling within the 91.1%-107.8% range). The method for triptorelin determination was then used for its quantification in a commercially available drug dosage form (powder for injection) and in spiked synthetic urine samples. The developed methods were also evaluated according to the novel blue applicability grade index, revealing their superior applicability. The results collectively point out the potential of the proposed methods for both quality control and clinical investigations.

The Experiences of Practical Nurse Students in Promoting the Rehabilitation of the Elderly Through Nursing Care and Its Education – A Secondary Publication

The significance of rehabilitation-promoting nursing care is emphasized in aging Finland. According to studies, rehabilitation-promoting nursing care enhances the functional capacity of the elderly. The Elderly Services Act obliges municipalities to create a plan to support the elderly population, emphasizing living at home and rehabilitative measures. A large portion of graduated practical nurses will be working with the elderly, so the education of practical nurses must meet the needs of the workforce. The study aimed to produce new information on the implementation of rehabilitation-promoting nursing care in the elderly services system and on the education of rehabilitation-promoting nursing care for the elderly in vocational institutions. The research data was collected in the fall of 2020 through individual theme interviews with practical nurse students (n = 8). The data was analyzed using inductive content analysis. The experiences of practical nurse students regarding rehabilitation-promoting nursing care for the elderly were related to nurses’ time management, organizational practices, nurses’ competence, nurses’ attitudes, nurses’ methods of operation, organizational development, implementation and development of practical teaching, factors affecting the use of aids, and the technology of aids in the future. In conclusion, it can be stated that the content of education and practical work life do not align. It is essential to increase competence in rehabilitation-promoting nursing care and develop organizational practices.

Visual Perception and Multimodal Control: A Novel Approach to Designing an Intelligent Badminton Serving Device

Addressing the current issue of limited control methods for badminton serving devices, this paper proposes a vision-based multimodal control system and method for badminton serving. The system integrates computer vision recognition technology with traditional control methods for badminton serving devices. By installing vision capture devices on the serving device, the system identifies various human body postures. Based on the content of posture information, corresponding control signals are sent to adjust parameters such as launch angle and speed, enabling multiple modes of serving. Firstly, the hardware design for the badminton serving device is presented, including the design of the actuator module through 3D modeling. Simultaneously, an embedded development board circuit is designed to meet the requirements of multimodal control. Secondly, in the aspect of visual perception for human body recognition, an improved BlazePose candidate region posture recognition algorithm is proposed based on existing posture recognition algorithms. Furthermore, mappings between posture information and hand information are established to facilitate parameter conversion for the serving device under different postures. Finally, extensive experiments validate the feasibility and stability of the developed system and method.

DESIGN AND DEVELOPMENT OF CAMPUS ROOM USE MONITORING APPLICATION BASED ON ANDORID WITH MAGNETIC DOOR LOCK IN THE DEPARTMENT OF INFORMATICS AND COMPUTER ENGINEERING UNM

The condition of campus room doors that are often open has the potential for misuse of campus rooms that do not comply with the schedule set in the room and affect the security of the room facilities. This research aims to produce an Android-based campus room usage monitoring application using magnetic door locks at JTIK FT UNM as well as knowing the results of functional testing and performance testing or system performance. This research uses the Research and Development method with the Rapid Application Development Development model with stages: needs analysis, system design, system building, validation, testing, and final product. The final product of this research is a system developed in an Android-based room usage monitoring application that is integrated with a magnetic door lock using the QR Code feature. In this case, the system utilizes the ESP32 microcontroller as a chip that receives and provides signals according to the program in the system. The test results obtained validation of the Android-based campus room usage monitoring application using magnetic door locks can be said to be valid and suitable for use.

Canadian Association of Radiologists Cardiovascular Imaging Referral Guideline.

The Canadian Association of Radiologists (CAR) Cardiovascular Expert Panel is made up of physicians from the disciplines of radiology, cardiology, and emergency medicine, a patient advisor, and an epidemiologist/guideline methodologist. After developing a list of 30 clinical/diagnostic scenarios, a rapid scoping review was undertaken to identify systematically produced referral guidelines that provide recommendations for one or more of these clinical/diagnostic scenarios. Recommendations from 48 guidelines and contextualization criteria in the Grading of Recommendations, Assessment, Development, and Evaluations (GRADE) for guidelines framework were used to develop 125 recommendation statements across the 30 scenarios (27 unique scenarios as 2 scenarios point to the CAR Thoracic Diagnostic Imaging Referral Guideline and the acute pericarditis subscenario is included under 2 main scenarios). This guideline presents the methods of development and the referral recommendations for acute chest pain syndromes, chronic chest pain, cardiovascular screening and risk stratification, pericardial syndromes, intracardiac/pericardial mass, suspected valvular disease cardiomyopathy, aorta, venous thrombosis, and peripheral vascular disease.

H-mrk-means: Enhanced Heuristic mrk-means for Linear Time Clustering of Big Data Using Hybrid Meta-heuristic Algorithm

Big data is generally derived with a large volume and combined categories of attributes like categorical and numerical. Among them, [Formula: see text]-prototypes have been adopted into MapReduce structure, and thus, it provides a better solution for the huge range of data. However, [Formula: see text]-prototypes need to compute all distances among every data point and cluster centres. Moreover, the computations of distances are redundant as data points are often present in similar clusters after fewer iterations. Nowadays, to cluster huge-scale datasets, one of the efficient solutions is [Formula: see text]-means. However, [Formula: see text]-means is not intrinsically appropriate to execute in MapReduce due to the iterative nature of this technique. Moreover, for every iteration, [Formula: see text]-means should perform an independent MapReduce job but, it leads to higher Input/Output (I/O) overhead at every iteration. This research paper presents a novel enhanced linear time clustering for handling big data called Heuristic mrk-means (H-mrk-means) using optimized [Formula: see text]-means on the MapReduce model. In order to manage big data that is time series in nature, the sampling and MapReduce framework are adopted, which utilize different machines for processing data. Before initiating the main clustering process, a sampling process is adopted to get the noteworthy information. The two main phases of the developed method are the map phase (divide and conquer) and the reduce phase (final clustering). In the map phase, the data are divided into diverse chunks that should be stored in assigned machines. In the reduce phase, data clustering is performed. Here, the cluster centroid of data is tuned with the help of hybrid Tunicate-Deer Hunting Optimization (T-DHO) algorithm by attaining a newly derived objective function. This type of optimal tuning of solution enhances the efficiency of clustering when compared over normal iterative [Formula: see text]-means and mrk-means clustering. The experimental evaluation on varied counts of chunks using the proposed H-mrk-means has attained higher quality of clustering results and faster execution times evaluated with other clustering approaches.

New maize inbred development method I: Inter‐heterotic group composite and tester choice

AbstractCurrent maize (Zea mays L.) breeding methods and the limited germplasm infusion and mixing may slow the rate of genetic gain in the future. Using inter‐heterotic group composites for maize inbred development has been questioned because of the issue of choosing appropriate testers. However, three observations can be revisited to facilitate the exploration of alternative methods. First, since the adoption of single‐cross hybrids and the establishment of heterotic groups, the amount of heterosis has only been increasing slightly. Second, genomic analysis indicated the frequencies of the favorable alleles had significantly increased after a century's breeding. Third, the divergence of maize heterotic groups was preceded by the merging of landraces and diverse inbreds, after which three major heterotic groups were established. The objective of this study was to design different scenarios to generate inter‐heterotic group composites and evaluate their usefulness in the commercial breeding program. We investigated two methods: the inter‐heterotic group composite method (termed as super population [SupPop]) and the modified SupPop method (ModiSP, that is, backcrossing SupPop lines with elite inbreds). The results showed that the best scenario for the SupPop method was to use the SupPop inbreds to cross with a tester from the B14 group. When all four heterotic groups were mixed, the favored tester was from stiff stalk. However, ModiSP showed a higher chance of producing the best yield performance. These empirical results suggest that solutions can be proposed to identify the testers so that using inter‐heterotic group composites for inbred development can be considered.

Attaining superhydrophobic and superoleophilic bronze surface by picosecond laser texturing and post-heat treatment

As a bearing material, bronze has high strength and hardness but is poor in anti-adhesion property. In this study, we propose a method to prepare a superhydrophobic and superoleophilic bronze surface by combining laser surface texturing and post-heat treatment. A picosecond laser was employed to produce pore arrays with varying spacings and depths on the bronze surface, which exhibited micro-nano hierarchical structures. A further post-heat treatment of the laser-textured sample at 150 °C in the ambient led to the formation of a superhydrophobic surface with a maximum water contact angle of 158° and with superoleophilicity. It was found that pore spacings played a significant role in forming the surface hierarchical structures, which were covered with the laser-ablated micro-nano particles. The pore depth, however, showed little influence on the surface wettability. Analysis of the surface chemical compositions by X-ray photoelectron spectroscopy (XPS) indicates that the C element mainly exists in the form of the C–C(H) group, which reduces the surface energy and leads to superhydrophobicity. It was also verified that the wettability transition of the bronze surface before and after heating was independent of the oxide transition. Rubbing tests were conducted to evaluate the durability of the surface hierarchical structure. Anti-icing and self-cleaning functions were demonstrated showing the potential of the developed method for preparing a superhydrophobic and superoleophilic surface.

Ion chromatography‐based determination of lithium in human urine for monitoring medication compliance

AbstractContinuous Li monitoring is vital in ensuring the safety and treatment efficacy of probationers with psychotic disorders, such as bipolar disorder, depression, and mania. This study introduced a validated quantitative analysis method using ion chromatography (IC) to monitor Li+ concentration in urine. The methodology involved centrifuging the urine sample, diluting the supernatant with deionized water, and subsequent IC analysis using guard and analytical columns for precise Li+ concentration measurement. The method quantified Li+ within the range of 2–400 ng/mL, demonstrating its excellent linearity (r2 = 0.9983) with a weighting factor of 1/x. Precision levels below 12.8% were observed for both intraday and interday measurements with an accuracy of −5.9% to 15.2%. The detection limit was identified as 0.12 ng/mL. The method conformed to analytical standards in terms of selectivity, matrix effect, process efficiency, dilution integrity, and stability. Moreover, the method distinctly quantified Li+ while effectively eliminating interference from Na+, which had a similar retention time as Li+ with higher concentrations. Further, the developed method was successfully applied to analyze forensic urine samples of Li users, demonstrating its applicability for medication compliance monitoring using urine samples of mentally disordered probationers.

Elite Multi-Criteria Decision Making—Pareto Front Optimization in Multi-Objective Optimization

Optimization is a process of minimizing or maximizing a given objective function under specified constraints. In multi-objective optimization (MOO), multiple conflicting functions are optimized within defined criteria. Numerous MOO techniques have been developed utilizing various meta-heuristic methods such as Evolutionary Algorithms (EAs), Genetic Algorithms (GAs), and other biologically inspired processes. In a cooperative environment, a Pareto front is generated, and an MOO technique is applied to solve for the solution set. On other hand, Multi-Criteria Decision Making (MCDM) is often used to select a single best solution from a set of provided solution candidates. The Multi-Criteria Decision Making–Pareto Front (M-PF) optimizer combines both of these techniques to find a quality set of heuristic solutions. This paper provides an improved version of the M-PF optimizer, which is called the elite Multi-Criteria Decision Making–Pareto Front (eMPF) optimizer. The eMPF method uses an evolutionary algorithm for the meta-heuristic process and then generates a Pareto front and applies MCDM to the Pareto front to rank the solutions in the set. The main objective of the new optimizer is to exploit the Pareto front while also exploring the solution area. The performance of the developed method is tested against M-PF, Non-Dominated Sorting Genetic Algorithm-II (NSGA-II), and Non-Dominated Sorting Genetic Algorithm-III (NSGA-III). The test results demonstrate the performance of the new eMPF optimizer over M-PF, NSGA-II, and NSGA-III. eMPF was not only able to exploit the search domain but also was able to find better heuristic solutions for most of the test functions used.

Scalable decarboxylative trifluoromethylation by ion-shielding heterogeneous photoelectrocatalysis

Electrochemistry offers a sustainable synthesis route to value-added fine chemicals but is often constrained by competing electron transfer between the electrode and redox-sensitive functionalities distinct from the target site. Here, we describe an ion-shielding heterogeneous photoelectrocatalysis strategy to impose mass-transfer limitations that invert the thermodynamically determined order of electron transfer. This strategy is showcased to enable decarboxylative trifluoromethylation of sensitive (hetero)arenes by using trifluoroacetate, an inexpensive yet relatively inert trifluoromethyl group (CF 3 ) source. An ion-shielding layer, formed by trifluoroacetate anions electrostatically adsorbed on a positive molybdenum-doped tungsten trioxide (WO 3 ) photoanode, prevents undesired electron transfer between substrates and photogenerated holes. The practicality of the developed method was demonstrated with robust photoanode stability (approximately 380 hours), a good substrate scope, and scaling capability to achieve 100-gram synthesis by using photoelectrochemical flow cells.

A novel perspective on the selection of an effective approach to reduce road traffic accidents under Fermatean fuzzy settings.

Road traffic accidents (RTAs) pose a significant hazard to the security of the general public, especially in developing nations. A daily average of more than three thousand fatalities is recorded worldwide, rating it as the second most prevalent cause of death among people aged 5-29. Precise and reliable decisionmaking techniques are essential for identifying the most effective approach to mitigate road traffic incidents. This research endeavors to investigate this specific concern. The Fermatean fuzzy set (FFS) is a strong and efficient method for addressing ambiguity, particularly when the concept of Pythagorean fuzzy set fails to provide a solution. This research presents two innovative aggregation operators: the Fermatean fuzzy ordered weighted averaging (FFOWA) operator and the Fermatean fuzzy dynamic ordered weighted geometric (FFOWG) operator. The salient characteristics of these operators are discussed and important exceptional scenarios are thoroughly delineated. Furthermore, by implementing the suggested operators, we develop a systematic approach to handle multiple attribute decisionmaking (MADM) scenarios that involve Fermatean fuzzy (FF) data. In order to show the viability of the developed method, we provide a numerical illustration encompassing the determination of the most effective approach to alleviate road traffic accidents. Lastly, we conduct a comparative evaluation of the proposed approach in relation to a number of established methodologies.

Rancang Bangun Computer Based Test (CBT) Berbasis Web

Examinations are an evaluation method in the teaching and learning process in schools. Generally, exams in schools are still carried out conventionally using paper and stationery, and exam assessments are carried out directly by the teacher. However. The process of creating exam questions, duplicating questions, evaluating and filling in answers is still manual using paper and stationery, causing various obstacles such as high costs and long correction times. To solve the problem above, the researcher used the Agile system development method with the Extreme Programming model which involves four stages: planning, designing, coding and testing. The research results show the success of the CBT application that was built. The application was tested using the black box testing method. Test results show that the correction process is faster by 0.9 seconds and more accurate. Apart from that, in terms of costs, using this application is also cheaper. This shows that the CBT application has a positive impact in increasing the efficiency, accuracy and effectiveness of testing and reducing the costs of administering the exam.

Implementasi Google Cloud Pub/Sub menggunakan Metode Subscription Pull dalam Pengiriman Data Promosi Toko di PT XYZ

As a company adopts a distributed business model, scalability issues often arise in the distribution of data from server to client. PT XYZ, as one of the companies facing this challenge, frequently encounters delays and request blocking when using synchronous communication models such as RESTful API. Additionally, there is resource and time wastage on the server side as it has to handle store requests one by one, resulting in losses for the store due to delayed access to required data for business processes. This research proposes a solution to address these issues by implementing a publish/subscribe communication model. Through the implementation of this architecture, clients and servers are separated by a broker, namely Google Cloud. Pub/sub technology is implemented using the Python programming language with the Waterfall development method. The results of this research include the design of a client-side application capable of receiving data from a previously deployed broker. Test results demonstrate that the client can receive data at any time without disrupting the data fetching process for other clients.

THE IMPACT OF USING INTERNAL CONTROL UNDER THE ELECTRONIC OPERATING SYSTEM

Internal control tools constitute one of the modern frameworks approved by the Committee of Sponsoring Organizations (COSO). "And the one which takes into account setting the objectives first, then estimating the possibility of those objectives being exposed to threats, then internal control procedures are designed that reduce the risks, and at the same time provide reasonable guarantees for achieving the organization's objectives and introducing all modern developments into the system. The contemporary trend of internal control focuses on the integration between managing the risks to which the organization is exposed and the internal control frameworks (Enterprise Risk Management- Integrated Framework) and its abbreviation (ERM), which provides the organization Management in conditions of uncertainty related to risks and their probabilities to be able to create and preserve value. The continuous developments in internal control systems, on the one hand, and competition between economic units, on the other hand, have led to many challenges through the use of modern technology and the innovation of new methods of development, which required the development of all sub-systems of control, including internal control systems, and then review the internal control structure and the extent of its acceptance of this computer-based technology and the effectiveness of its devices in providing information that supports the system's ability to adopt it. Based on this, the research topic was divided into five sections. The first section dealt with the research methodology, the second section dealt with the theoretical framework of the internal control system, and the third section dealt with the problems and limits of using electronic computers. The fourth section was devoted to studying the impact of using computers. The electronic section focuses on the components of the internal control system, while the fifth section is dedicated to stating the most important conclusions and recommendations.

Estimation of the Shear Viscosity of Mixed-Polymer Materials for Screw Extrusion-Based Recycling Process Modeling

The scope of this work is the development of a method to estimate the temperature and shear rate-dependent viscosity of mixtures composed of two polymers. The viscosity curve of polymer mixtures is crucial for the modeling and optimization of extrusion-based recycling, which is the most efficient way to recycle polymeric materials. The modeling and simulation of screw extruders requires detailed knowledge of the properties of the processed material, such as the thermodynamic properties, the density, and the rheological behavior. These properties are widely known for pure materials; however, the incorporation of impurities, like other polymers in recycled materials, alters the properties. In this work, miscible, immiscible, and compatibilized immiscible polymer mixtures are considered. A new method based on shear stress is proposed and compared to the shear rate-based method. Several mixing rules are evaluated for their accuracy in predicting mixture viscosity. The developed methods allow the prediction of the viscosity of a compatibilized immiscible mixture with deviations below 5% and that of miscible polymer mixtures with deviations below 3.5%.

Digital Drawing Innovation of Ornaments through Ibis Paint Application

The learning process of ornaments drawing in the Junior High School of Boyolali during the emergency period of the spread of Covid-19 was conducted online. This study follows Bord and Gall’s research and development (R&D) method (1983). Data collection methods were carried out by participatory observation, in-depth interviews, closed questionnaires, and documentation, and data analysis was carried out with a qualitative and quantitative approach. The purpose of this study is to provide a foundation for students to appreciate art and use their imaginations as a trigger for their creativity. That is achievable, though, if educators provide learning in a captivating manner. One way to achieve this aim is by innovating learning media based on Android smartphones with tools like ornaments digital drawing using Ibis Paint application, which can be used by students online and offline to make them understand the subject easily. Learning media innovations can be conducted by exploring video tutorials, text, and images that are presented on a website for online and offline learning processes. The results of the test showed that the data of the material expert test are 99%, the media expert test are 98%, and the website expert test are 98%. These results conclude that innovation in learning media with material ornaments digital drawing is appropriate, relevant, and needed by students for their art appreciation and imagination expression in online and offline learning processes. The role of media in achieving learning objectives has been proven effective because students showed active behavior. Innovation in learning media simplifies the understanding of concepts through visualizations, graphics, animations, and other multimedia presentations. This helps students have a better comprehension of complex concepts. Keywords: learning media, digital drawing, ornaments