This PDF file contains the front matter associated with SPIE Proceedings Volume 12936, including the Title Page, Copyright information, Table of Contents, and Conference Committee information.

This study aims to determine the influence of website platform quality on purchasing decisions within a website. The study was conducted using quantitative regression analysis and simple random sampling methods. The results showed that the quality of the website platform had a positive effect on purchasing decisions within a website. This indicates that the better the quality of the website platform, the greater the likelihood of consumers making purchases through that website. Therefore, improving the quality of the website platform is necessary to increase purchasing decisions within a website. The result study hopefully can contribute to the development of marketing strategies through websites and increase the sales.

The environmental polymers were created using bio-based plant material as the substrate and powdered mango nuts derived from agricultural residues of mango nuts as the fillers. Cellulose was decomposed in an ecologically acceptable solvent of 8 wt % potassium hydroxide and 12 wt.% urea precooled to 15 °C. TNP was added to the cellulosic liquids in amounts ranging from 10% to 20% by weight. Each solution was equally distributed on glass pieces, and moist aggregates were created utilizing the healing process and an ethanolic clotting solution. The entire wet film is then cured in room-temperature air. The cured composites were subjected to X-ray diffraction, differential thermal, and tensile testing. The composite's ultimate tensile strength and % elongation during break were higher than the matrix's and improved with filler concentration. The substrate had a mechanical property of 123.8 MPa, whereas the biocomposite hybrid with 20 wt. % TNP had a mechanical property of 126.36 MPa (a 12% increase). Although the melting temperature of a combination was lower than that of the cellulosic substrate, all of the hybrids remained stable at 375 °C.

Failure Modes and Effects Analysis (FMEA) is a software application that mitigates environmental hazards during the design stage. Even though many companies use the current FMEA approach, it has several limitations and drawbacks. Risk is quantified using the Risk Priority Number (RPN), a function of incidence, severity, and detection difficulties. Measuring the intensity and complexity of identification is very personal; there is no standard scale. RPN is similarly a product of ordinal; hence, it is useless as a measure. This study discusses the drawbacks of the manual and FMEA approaches to machinability’s, such as inner diameter over and undersize, collar thickness, and depth oversize, which assesses risk based on cost and time. Life Expense PFMEA helps assess and select design choices to minimise a system's life cycle expense. The cost-based FMEA accounts for uncertainty in the following areas: detecting duration, repair moment, frequency, delay, unplanned downtime, and modelling complicated situations. A case study of a large-scale particle collider demonstrates the advantages of a proposed technique in projecting product lifecycle breakdown cost, quantifying risk, and scheduling preventative, planned maintenance, all to increase up-time.

Vaccine hesitancy has become one of the biggest challenges in the pandemic management efforts of the Philippine government, even with a decreasing trend in recorded cases in the past couple of months. A number of studies and surveys have revealed that vaccine hesitancy could even go as high as fifty-eight percent (58%) in some regions. Using the method of network analysis, this study analyzed the relationship between the factors affecting vaccine hesitancy among Filipinos. Specifically, it used the COVID-19 Vaccine Survey data that was previously collected by the Philippine’s Department of Health (DOH). Results revealed varying popular and influential factors when the networks are broken down by demographic variables. It also showed that negative news circulating about certain brands of vaccine and unaddressed concerns about its side effects are the most common reasons for refusing COVID-19 vaccines. Both factors also tend to have the highest betweenness and closeness centrality across different demographics.

tube heat exchanger used a delta airfoil array of turbulators in line configuration to investigate increased heat transmission and flow characteristics. The turbulence test was carried out. Numerous variables, such as pitching proportions, durations, and assault orientations, were tested in this experiment, but its influence on thermophysical properties was noted. The findings suggest that PR considerably affected both F and NU. In all cases where PR = 1.7, VGs had the highest f and Nu. At Re = 7000, tensor flow with L12 B45 PR4.9 achieved the highest TPE of 1.39. Assault direction B considerably influenced thermal efficiency, with a TPE of 2.45 at reduced Res. Fluid film flow or smoky movement visualization was used to locate vortices and explain flowing mechanisms. The lubricant film flow visualization with smoky movement tracked transverse swirl and generated swirl, which caused impact flow and a recirculating region, resulting in significantly enhanced heat transfer.

One of the biggest causes of mortality globally is heart disease (HD). The Support Vector Machine (SVM) method was employed in this work to forecast heart disease cases using data on heart disease. The chosen target group served as the basis for categorization. The primary goal of this forecast is to offer an accurate diagnosis and sufficient lead time to avoid a tragic outcome. Initially, this classification was constructed using a hybrid method, that is, the use of SVM and KNN techniques. Hybrid methods provide a much more accurate prediction than simple methods. The results from the study were satisfactory, and the experimental findings showed how well the system worked for precise predictions. The area under the curve score was 0.86. The proposed system easily identifies and classifies healthy versus unhealthy individuals. The execution time of the algorithm is acceptable, and at the same time, increasing the performance using classification reduces, on average, the execution time and memory usage by 98.75%. The use of SVM and kNN can help doctors diagnose sick patients promptly with satisfactory efficacy.

Mechanical properties are crucial in the creation of bone biomaterials. This research has developed and characterized new PLLA-HA-YSZ hybrid scaffolds with varying compositions. The effect of HA and YSZ quantity on the mechanical behavior of nanocomposites was investigated. The SEM micrograph further revealed that the YSZ dust is in granular form and is breakdowns in diameter. SEM demonstrated that all scaffolds used to have a densely connected porosity architecture. At the same time, the X-ray diffractometer (XRD) showed some molecules among PLA, HA, and YSZ throughout the mixtures. The findings show that adding YSZ to the composites significantly increases compressive strength, elasticity, and urban growth stress. Furthermore, YSZ nanoparticles were introduced into scaffolding, and their structural and modulus properties were evaluated. It must be highlighted that PLA-20%HA-20%YSZ has the maximum strength for compressive and flexural purposes, but it does not show the right strain compared to specific other scaffolding. As a result of its suitable quality and stress, PLA-15%HA-15%YSZ has been identified as the best choice. In addition, a more significant number of YSZ particles increased the energy uptake in nanomaterials. It was discovered that the potency of specimens decreased after already being immersed in SBF.

The present investigation examine the worldwide progression of Cyber Security as a subject of research and detects a recent decline in published research subsequent to a noteworthy surge in 2017. The findings of the study indicate that there is a need for scholars to undertake more extensive research on cybersecurity and leverage bibliometric data to obtain more profound understandings of Cyber Security. The concept of cybersecurity encompasses a range of strategies and techniques that are employed to protect sensitive data from unauthorised access, theft, or damage. These measures typically involve proactive measures to prevent attacks, as well as reactive measures to detect and respond to security breaches. The present investigation undertook an extensive review of the literature utilizing bibliometric analysis to examine the scholarly works pertaining to Cyber Security.

Respiratory diseases such as pneumonia, lung cancer, and tuberculosis are examples of chronic respiratory diseases which are considered as the leading causes of non-communicable disease deaths worldwide. A decision support system for doctors could help make the proper diagnosis, thereby reducing diagnostic errors. One promising field that could help in doing this is by using deep learning methods with image processing, specifically Convolutional Neural Networks (CNN). CNN has been proven effective in classifying chest x-ray images in previous studies. However, most of these mainly focused on classifying two classes or diseases only. This study aimed to use CNN’s to detect multiple respiratory diseases, specifically healthy or normal, lung cancer, tuberculosis, and pneumonia, from chest x-rays. The study was limited to these four classes and only used CNN architecture to detect the aforementioned types. Moreover, image preprocessing methods such as gray level transformation, histogram equalization, and data augmentation were used to improve the dataset's quality and quantity. After applying preprocessing techniques, the images were fed to CNNs through transfer learning, wherein three different models were used, namely, EfficientNetV2, NasNet Large, and ResNet50-V2. Using convolutional neural networks through transfer learning proved effective, with all models obtaining an accuracy of greater than 95%. Convolutional Neural Networks effectively and accurately classified the four types of chest x-ray images. Additionally, the results of this study aid hospitals and doctors in making immediate diagnoses while also being accurate, which is a need, especially at a time when hospitals could be overloaded.

In this research, the Penalized Least Squares method (PLS) is presented to estimate the parameters of kink regression model in the presence of the High dimensional problem using by adopting different penalty functions, including the LASSO penalty function, the SCAD penalty function, Minimax Concave Penalty (MCP) function and Elastic-net penalty function which was suggested use. By using simulation, the PLS estimators were compared with different functions for kink regression parameters and it showed the preference PLS (SCAD)and PLS (MCP)for different sample sizes, and the performance of PLS (LASS0) fluctuated, while the performance of PLS ( Elastic Net ) improved and approached the performance of the PLS (SCAD) and PLS (MCP) at a sample size of 30, depending on the correct choice measure and the percentage of correctness. Real data related to the market value and the variables affecting it (which is accounting data) for the Baghdad Soft Drinks Company, which includes 48 explanatory variables for the period 2012-2019 is applied and PLS (Elastic Net) showed its preference in selecting the important variables because it has the minimum MSE value based on the note of the improvement of PLS (Elastic Net) performance with the increase of the sample size.

A linear quadratic differential game on an infinite time horizon with two types of an information structure is analysed and the equilibrium point is computed via stabilizing solution. The Newton solver for computing the stabilizing solution of the associated Nash-Riccati equations has been established. Here, a convergent linearized iterative method depending on a negative constant is introduced for each information structure: the open loop design and feedback design. The linearized iteration has a linear convergence rate, however there are cases where the iteration is faster than Newton's method. Numerical experiments are implemented to explain the computational advantages of the introduced solvers.

Integrity is fundamental in enforcement agencies including the Royal Malaysia Police (RMP) to ensure accountability in accordance with the law, without misconduct or corruption. Lately, there has been frustration among the people about the increase of misconduct among police officers which is quite alarming with several high-profile cases in the country. Therefore, this study tries to reveal the extent of public trust on the integrity of RMP. This study used qualitative methods through thematic analysis to look more deeply at the views of the people and practitioners. The results of the study are as expected, which is that the people are quite disappointed and worried about the increasing number of misconduct cases among police officers. However, there are also a few of informants who indicate that the level of integrity in RMP is still under control and only a small number of misconduct cases in Malaysia. Nevertheless, the results of this study can be a benchmark for RMP to be more transparent and fairer in carrying out the task of investigating members in inquiry. Measures to strengthen human resource management such as self-reinforcement training, a more appropriate salary system and the addition of sufficient personnel can avoid cases of misconduct in RMP and increase the level of public trust. Future studies can be further expanded by researchers with the use of diverse methods and the involvement of informants in various enforcement agencies in Malaysia.

The purpose of this research was to construct the network model of cooperation from community practice model sufficiency economy to learning for sustainable development. The developing a model for a network of cooperation from the community's practice model of sufficiency economy to learning for sustainable development. The model development process has been defined, consisting of 1) studying documents about the concept of community operation model sufficiency economy in order to define the outline of the components of the model; The present work of the sufficiency economy model community educational philosophy Theoretical concepts that promote networking in community development under the philosophy of sufficiency economy and sustainable development. 3) Synthesize and link various elements to form a cooperation network model from community practices of sufficiency economy model to learning for sustainable development. 4) Generate documents and 5) examine the quality of the model and improve the cooperation network model from the model community's practice of sufficiency economy. Sufficiency to Learning for Sustainable Development By 5 experts, Index of item – objective congruence (IOC) = 0.86. Statistics used in the research were descriptive essays and variable relationships. An analysis of the current situation of the sufficiency economy model community philosophy of sufficiency economy Reformist Philosophy, DFID, Pentagon Model, and Targeting Theory to define as an implementation step of the cooperation network model from community practice model sufficiency economy to learning for sustainable development. The form of cooperation network from community practice model of sufficiency economy to learning for sustainable development is divided into 3 levels: (1) Coordinating the primary network (2) Coordinating the intermediate network (3) high level network coordination At each level, operations are classified into 2 parts: (1) overall operations (2) cooperation networks.

This research aims to find out the influences of information technology development on the concept of share ownership transfer in scripless trading and how this scripless trading looks like in the Indonesian and Malaysian Stock Exchange. This research employed a normative research method, statutory and conceptual approach, with also primary, secondary, and tertiary legal materials to support the research data, all of which were analyzed based on the descriptive-qualitative analysis technique. To study and compare the legal positions in Indonesia and Malaysia concerning scripless trading, a legal comparative analysis is conducted in this. This study aims to offer useful insights into the similarities and contrasts that exist in these two jurisdictions’ unique legal systems by analysing their legal frameworks and guiding principles. The research results came to the following conclusions: (1) the development of information technology manages to transform the relevant jurisprudence into law, especially regarding the concept of transfer of rights of a moveable and intangible object which is more like in the transfer of shares ownership in scripless trading, (2) in the execution of scripless trading, the stock exchange offices serve as the front office fully supported by several institutions backing up transactions such as the Securities Clearing Agency (LKP) executed by PT Kliring Penjamin Efek Indonesia (KPEI), and Depository and Settlement Agency (LPP) executed by PT Kustodian Sentral Efek Indonesia (KSEI) as well as Bursa Malaysia Depository Berhad which assist in scripless trading in a stock exchange, and (3) the adoption of information technology in share transfer mechanisms in public companies has increased the efficiency and economic growth in both countries.

Influenza virus is the most common disease in both children and adults. People can be infected with this disease several times a year. It is a viral infection of the respiratory tract, including the nose, throat and lungs. Age structure influence on the spread of influenza disease. In this research, we apply the dynamical model to describe the transmission of Influenza virus. We consider the age group of patients. We divided into 2 age groups. The first group (children) is the group of people’s age less than 15 years old. The second group (adult) is the group of people’s age greater than 15 years old. We separate the population into children and adult. The conditions for local and global stable are found. The basic reproduction number of the disease is found. The way for reducing this disease is introduced.

In the digital era, SQL injection (SQLi) attacks on web applications pose significant threats to data integrity and security. While traditional methods such as signature-based and anomaly-based detections have some limitations, this research explores the application of neural networks in countering these attacks. Specifically, this research evaluates the performance of three primary neural network architectures: Artificial Neural Networks (ANNs), Convolutional Neural Networks (CNNs), and Recurrent Neural Networks (RNNs) for SQLi attack detection. The research methodology involves converting text-based SQL queries into numeric values suitable and compatible with the neural networks, using Term Frequency-Inverse Document Frequency (TF-IDF), tokenization, and padding. Results show that the CNN outperforms in almost all metrics, with RNNs following closely and ANNs achieving the lower results.

The effects of various gasolines on spraying properties were studied using Lagrange particle monitoring and huge simulations. Spraying velocity drives the gas component into such a strong, multistage jet near the nozzles in a parallel, connected simulation situation. The quasi-Diesel Engine Networking Spray was used to evaluate the influence of fuel properties on liquid spray production. As the benchmark example shows, a base state is selected. An approved spraying a scenario was changed by substituting gasoline, formaldehyde, solvents, or methane for n-dodecane at 140 MPa injection timing. Both the properties and performance of the simulation for petroleum products inside the unresolved, relatively close area are addressed. The following are the report's main results. We show how, in addition to the traditional liquid penetrating (Lliq) and vapour penetrating (Lvap) length dimensions, our model multiphase jet has a novel length dimension Lcore, which corresponds to a hypothetical core part shared by single stage jet. Lcore is shown to connect smoothly with Lliq as well as Lvap for any and all energies, which is a central component of the present method. A secondary sensitive experiment on the diffusion coefficient revealed that fluid height had a negligible effect in Lliq. There was a significant interaction among the oxygen levels of gasoline and the dispersion of the equivalency ratio.

The current work describes the production and characterization of bamboo sheets supplemented with tapioca and utilizing ammonia zirconia (IV) bicarbonate as a compatibilizer. Introducing starches and a coupling agent increases the shredding strength, elastic modulus, and mechanical characteristics of the bamboo sheets by up to 4% and 2%, respectively. The level of condensation reactions is 88% in the optimized formulations. XRD and morphological investigations demonstrate that chemical interaction between hemp fibre and tapioca enhances the efficiency of bamboo papers. The elastic modulus and rip resistance of the produced hemp sheets increased by 129% and 147%, respectively, using only 4% cassava flour and 2% ammonia zirconia bicarbonate. According to the outcome of the research on the level of condensation reactions, hemp, viscose fiber, and tapioca had the maximum contact (87%) when combined.

This paper emphasizes that pre-service Teaching Chinese as a Foreign Language (TCFL) teachers must be professionally trained since researchers reported a shortage of qualified TCFL teachers in different countries. This study aims to analyze the instrument for measuring pre-service TCFL teachers ’ competency using the Rasch Measurement Model regarding validity and reliability. It measures five domains: pedagogical knowledge, teaching skills, self-esteem, working attitude, and job motivation. This paper applies a quantitative research design. The researcher distributed the instrument with 70 items to 80 pre-service TCFL teachers. The Rasch Measurement Model is applied to analyzing and examining the psychometric properties by Winsteps version 3.70.0. The reliability based on Cronbach Alpha is 0.92, according to the results of the psychometric characteristics analysis. Positive Point Measure Correlation (PMC) value, infit, and outfit MNSQ value between 0.5 and 1.5, and ZSTD value range from -2.0 to 2.0 are used to assess the instrument’s construct validity. The person and item dependability are, respectively, 0.90 and 1.00. The item separation index has a value of 19.62, and the person separation index has a value of 2.97, both of which are regarded as excellent separation. The conditions for unidimensionality are met by the raw variance explained by measure, 86.7%, and unexplained variance in the first construct, 2.4%. The results demonstrate that the instrument is valid and reliable for future analysis, and the instrument is understandable by the respondents without any major problems. This study could increase public understanding and attention to the value and importance of teacher competency. In addition, a psychometrically teacher competency measuring instrument can examine the level of teacher competency of pre-service TCFL teachers and provide a result of what kind of academic and psychological components they need to improve in the future.

The purposes of this research were to A model for disseminating a network of cooperation from community practice model sufficiency economy to learning for sustainable development and result of using that model. Mixed method of qualitative-quantitative research. The sample group consisted of 100 people in communities year of 2023 selected by purposive sampling method. For analyzing data, the percentage (%), mean (μ) and standard deviation ( σ). The results of the research were findings: The development of innovative learning media for sustainable development according to the sufficiency economy principle under the cooperation network model through digital media design with the ADDIE Model consists of 1) content analysis of 10 communities of sufficiency economy model 2) media learning innovation The content is divided into 4 aspects: 2.1) Community Context 2.2) Community Leaders 2.3) Community Management Strategies and 2.4) Community Product 3) Efficiency Examination, namely 3.1) Degree Rotation for Animation 3.2) Pixel 3.3) light & Sound 3.4) Definition 3.5) Eye plot diagram and 4) Digital media integrity improvement.

Several new classes of the algebraic problems are investigated, such as permutation d/d-edge/d-transitive-algebras, permutation d/d#-ideals and permutation d-subalgebras are discussed and looked into. We show that the product for any member in permutation d-algebra from the right with constant is equal the same member. Also, any permutation d-algebra is a permutation d-transitive algebra if and only if its extended edge permutation d-algebra is permutation d-transitive algebra. Additionally, permutation d*-algebra, permutation d-morphism, equivalence relation, congruence class and quotient permutation d-algebras were defined with specific results relating to these new notions are examined.

It is widely believed that in a reference frame where the body is moving, the body’s relativistic energy obeys the formula E = mc². In this work, however, we demonstrate form the generalization of Newtonian physics using Einstein relativistic mass that in a reference frame where the body is moving, the body’s effective relativistic energy obeys the formula E = m₀c² + E_k rather than E = mc²; and we will show that no definite value for rest-mass energy m₀c² can be confirmed from E²=(E_k+ m₀c²)²=(pc)² + m₀c²)².

MSMEs going up class means that their business can grow and of course be accompanied by increased productivity. It's not enough that they also have to have increasing competitiveness so that they have the potential to reach higher levels. If initially it was only a micro business and then it grew into a small business, then it increased to a medium business and finally it could become a big business. This study aims to study the influence of company reputation and risk management on company value with creativity and innovation of interneming variables in companies belonging to small and medium enterprises (MSMEs) that have the potential to become international-scale companies, where the company is CV Gammara Jaya Mondial. The research method used is descriptive analytic survey method with the number of samples as company stakeholders as respondents. The measured characteristics of each respondent are entrepreneurial creativity, entrepreneurial innovation, and firm value. The type of data collected from primary data. The results of the study found that company reputation and risk management had a significant effect on firm value, creativity had a significant effect on firm value, innovation had a significant effect on firm value, creativity and innovation had a significant effect on firm value directly or indirectly, for that it is necessary to do further research based on more varied sampling and longer duration, so that generalizable results are obtained.

The Forensic DNA Databank of Malaysia (FDDM) was formally established in December 2015 in solving crimes and upholding justice. Although the awareness among the people is increasing with government efforts, the public still has some misconceptions and concerns about collection, storage, and utilization of DNA samples and data. Hence, the study tries to assess the awareness and acceptance on the benefits and risks of profile storage in forensic DNA data banks. A few informants under qualitative method were selected public, the practitioners from Royal Malaysia Police (RMP), Department of Chemistry and Deputy Public Prosecutor. This study uses the thematic analysis method, and the results of the study are quite surprising. Focus Group Discussion (FGD) shows that the informant's understanding is still low regarding the benefits and risks of storing DNA profiles in forensic DNA data banks. It certainly raises the question of how the Malaysian forensic DNA data bank is sustainable in the eyes of the people if the practitioners themselves in the relevant agencies have a low level of understanding. Thus, the government can have the collaboration with all crucial government agencies, including the department of chemistry, the attorney general's office, the police, and the courts. In future studies, it is hoped that studies related to perspectives on the benefits and risks of storing DNA profiles in forensic DNA data banks will be expanded among other related public authorities and using mixed methodological methods in data collection to see a broader perspective.

The accurate classification depends on identifying the important attributes and removing those with lower weights. The selection of attributes helps reduce noise and increases classification accuracy Using a dataset on thyroid disorders, this study compares and contrasts three alternative feature-selection techniques. The objective is to choose an ideal subset with pertinent properties that provide maximum accuracy. To select the features, a genetic algorithm, practical swarm optimization, and ant colony optimization were considered. Simultaneously, the performance of each algorithm is evaluated. The ranking is based on the accuracy provided by each algorithm. The findings indicate that ACO gives a significantly high accuracy which captures the value of 99.5% followed by PSO with 93% accuracy, while the genetic algorithm came out lower for binary data after capturing the result with 92% accuracy for future selection.

As a popular social media today, Twitter has a huge number of users and extensive social influence. Its news is rich in content, high in participation, and highly interactive. Therefore, it is an important communication platform for news media in various countries. Xinhua News Agency is a very important foreign communication media in China. It has a global news information collection network and can quickly and in real-time publish the latest Chinese developments and news internationally. This paper analyzes and studies the coverage of COVID-19 in China on Xinhua News Agency Twitter in 2021. The research results show that the Xinhua News Agency's Twitter account shows a periodic change in the number of reports on China's COVID-19, and the focus of each stage of the report also has its own focus, the information presentation method is flexible, and the dissemination effect is good. It is an important platform for Chinese news media to report internationally.

This paper presents the design of a refund module for the Student's Financial Information System (SFIS) using Model- View-Control (MVC) approach for system development. The design of the refund module is based on the use of a class diagram, use case diagram, and User-Interface (UI) diagram. The class diagram and UI diagram are modelled using the MVC approach, which separates between model, view, and controller objects. The user interfaces are effectively visualized by using storyboards. The system verification is improved with quality assurance whilst the system validation is perfected via User Acceptance Test (UAT) and Final Acceptance Test (FAT).

Controversial advertising has the potential to significantly impact consumer purchase intention, both positively and negatively. On one hand, controversial ads can generate attention, interest, and curiosity among consumers, leading to an increased likelihood of purchasing the advertised product. On the other hand, controversial ads may also offend or alienate some consumers, leading to decreased purchase intention and even brand boycotts. The impact of controversial advertising on purchase intention is complex and influenced by a range of factors, including the nature of the controversy, the target audience, and the overall marketing strategy of the brand. Ultimately, it is important for brands to approach controversial advertising with thoughtfulness and sensitivity, carefully considering the potential impacts on brand reputation and customer loyalty.

According to the most recent global cancer statistics from WHO, cancer is considered one of the most severe diseases and is becoming one of the main reasons for human deaths globally. Skin cancer is the greater popular kind in view of prolonged exposure to the sun's harmful ultraviolet (UV) radiation. In order to minimize the severity of this disease, since it is more curable in the early stages, initial detection is ideal. Given the importance of this challenge, recently, using artificial intelligence techniques, researchers have developed various methods for early skin cancer lesions, which have been effectively used in the detection, classification, and treatment of various classes of skin diseases, and helping dermatologists in early diagnosis, and thus increasing the patient’s chance of recovery quickly. We present in this paper the latest research article’s details for detecting and classifying skin cancer using AI methods. In this context, we examined more than 100 publications from the last five years and we discussed and analyzed the advancements in AI solutions that exist to aid dermatologists and improve their capacity to detect skin cancer. Additionally, we give a summary of the most popular (deep and machine) learning models and datasets used for training. In this work, we concentrated on doing a comprehensive comparison of different works related to the utilization of AI techniques for skin cancer identification and categorizing is provided.

We introduce an alternative method to solve cooperative investment in a dynamic approach for mean-variance utility function by setting up time consistent mean-variance model based on compound independent axioms. an explicit formula to approximate the certainty equivalent for each investor corresponding to the mean-variance utility function based on the exponential utility function over the normal distribution is derived. Moreover, we establish the way of using alternative theories for decision-makers such as prospect theory to solve cooperative investment schemes. The numerical solutions and applied the method in Saudi Market are also shown.

As an important resource for a company, an ERP system can consolidate company transactions and information into a common database, making information accessible to different departments, thereby improving the ability of management accountants to fulfill their duties of providing real-time data, especially data. operations that support management control and decision making. Operations that support management control and decision making. In Indonesia, ERP has been widely used in companies with a high level of sophistication. One of the industrial fields in Indonesia that is quite constantly practicing ERP is the manufacturing company. Because, manufacturing is a very complex factory compared to other factories. Therefore, the presence of ERP is able to support the increase in the usability and efficiency of a company. Most companies around the world have implemented ERP, but businesses do not really contribute from ERP systems. This research focuses on the use of ERP in logistics.

This study has two main purpose. The first one is to improve Listening Test of College English Test- Band Four (CET-4) in China, because the item type of the existing one is simplex and cannot accurately test college students’ English listening ability. The second aim of the study is to make an appropriate profile of undergraduate students’ English listening ability with newly developed English Listening Quality Test (ELQT). Thus, this study employed IRT Rasch Model to check content validity, unidimensionality, item polarity, reliability and separation, item fit, and item bias of ELQT. This measuring method can systematically and comprehensively test the quality of ELQT, which make contribution to innovate the existing CET-4 Listening Test. The sampling strategy of used in this study is stratified sampling, which can insure the representativeness of samples. Listening material is one of the original listening test of CET-4 and the item type of ELQT refers to IELTS. There were 286 students in colleges and universities in Hebei China involved in this study. The result shows that the developed ELQT can well test college students’ English listening ability, which can be a good supplementation of existing CET-4 Listening Test. Improvement should be done in the sampling size aspect. Larger sample size may better show the results.

Abstract fractional integral equations are investigated with respect to functions and with time delays. Closed operators with strongly continuous semigroups in Banach space are considered. Existence and unique solutions of the considered integral equations are studied. Some smoothness properties with respect to the parameters of these delay fractional integral equations are given.

This work aims to examine the mechanical, biochemical, and thermodynamic conductivity of recycled plastic with altered organo-nanoclay with varied weights to add to many areas of usage and research. In this research, nanocomposites, whose function is in PET, a form of polymer material, and whose function is in altered inorganic materials with various proportions, were created using in-situ polymerization. XRD spectrometry was used to determine the chemical compositions of the produced nanomaterials. The scanning electron microscope was used to analyze the surface characteristics of these nanomaterials. Scanning electron microscopy and thermogravimetric analysis were utilized to examine their thermal behavior. Based on the findings, altered nano clay blends' temperature stability and durability outperformed PET. Furthermore, as the percentage of sand inside the laced PET grew, so did its instability. Whenever the percentage of contributions increased, a large quantity of clay was produced simultaneously. The surface contact of thermoplastic decreased due to the constructed agglomerations preventing the polymer structure from entering the stratum of mud.

To minimize imperfections and debonding issues in the machining operations of bio-composites, it is critical to understand the impacts of machinability and cutting force kinetics. To use a multiple, independent design, the impacts of machinability just on the workpiece level of access—surface and debonding component—all through the milling of coir, jute, and rice bran-augmented epoxy composites were investigated in this work. Different zones in the silica concentrations and hard values of the various natural fabrics were observed, which altered the interface quality of the final fiber-reinforced concrete. Coir/epoxy composites had the least debonding damage and the best surface polish, probably related to the coir's fiber characteristics and morphology. In contrast, RH/epoxy materials were the least difficult to machine. A quantitative examination of the findings shows that travel speed has a greater effect on finished surface integrity than feed rate when milling NFRCs, with such a contribution being at least nearly twice as great.

This study presents a promising approach for carbon dioxide (CO2) capture through fabrication, testing, and simulation of a hollow fiber membrane contactor. The contactor is constructed using a thermal induced phase separation technique, and its effectiveness was assessed using a gas-liquid absorption system. The results indicated that the membrane contactor exhibited a remarkable CO₂ absorption capacity and a rapid mass transfer rate. In addition, computational fluid dynamics (CFD) simulations are used to demonstrate membrane contactor performance, and to investigate the flow behavior and CO₂ concentration profile within a membrane unit setup. The simulation results closely aligned with the experimental data, affirming the accuracy of the CFD model. Collectively, this study highlights the potential of the hollow fiber membrane contactor as an efficient and economical solution for CO₂ capture. Various solvents were investigated based on their ability to absorb CO₂. Results revealed the potassium glycinate is an encouraging solvent.

Natural fibres promise to serve as a high-performance, abrasion-free reinforcement fibre alternative. This research investigated the mechanical properties of polyethylene composites containing various natural materials, including old newspaper, kraft cellulose, and kenaf. The influence of a lighter-weight terephthalate-form pairing consultant on the material properties of such organic fibres Composite material too was probed, with the results indicating that something like this can serve as a new interface descriptor for enhancing the shear strength of a PP-filled polymer composite, with the ideal amount of a compatibilizer being about 2-3 percent by weight of a specimen. Simultaneously, steel fibers, kraft paper, and kenaf fibre materials outperformed glass fiber-reinforced compounds in terms of tension, bending, and un-notched impact resistance. The material properties of a hybrid layer of 10% fiberglass and 30% kenaf fibre improved only marginally.

Software Quality Assurance (SQA) is a way to verify quality in the software. It is the set of activities which make certain processes, procedures as well as standards fit for the project and implemented appropriately. SQA is a process which works parallel to the development of software. It concentrates on improving the software development process so problems can be avoided. SQA is an activity that is applied throughout the software process, which will bring value to the project by saving money and time, implementing stable, competitive, and safe product, building constant process, helping to meet client expectations, and will create good developer’s reputation among the users. SQA can give significant impact to the software project in an academic environment with high defect removal efficiency which decreases the cost of software development and satisfy the users and target customers with respective to their expectations. Based on the implementation of SQA in International Student Module (ISM), the result showed that the error could be minimized beside reduced time effort in developing the software.

Many coal-fired power generators use moderate exhaust gas systems or components to eliminate hydrogen sulphide from exhaust gases. The SO2 is eliminated by potassium adsorbent in a responsive dryer in mid FGD devices; however, the amount of dehydrogenation is smaller than that in wet FGD structures. The impacts of eight chemicals in exhaust gas dehydrogenation are studied in this study: mg, NaOH, potassium nitrate, ammonia solution, ammonium salts, hypochlorite, acetic acid, as well as nitrogen. Drilling fluids containing 2 and 8 wt% of addition with magnesium carbonate levels of 10 and 20 wt% were utilized to remove sulphur dioxide. Ammonium-containing additives accelerated sulphur dioxide elimination as well as boosted feedback and comments. Whenever a solution comprising 4% anhydrous ammonia and 12% CaO was applied to the exhaust gases, this same carbon dioxide level was decreased by 69.8%. Compared to the most significant win achieved with ca (OH)2 slurry with no addition, this solution boosted sulphur dioxide reduction by about 18.5%.

To increase the mechanical performance of polyethylene (PP) polymers in automobile parts, bagasse ash fibres were used before using sulfuric acid solutions. As a compatibilizer, hydride glued polyethylene was employed. Filament chemical structure was also assessed. Using a thermogenetic mixer type MH-50H, PP was blended with fibres in 5%-15% (wt/wt) amounts. Tensile specimens were also made for tension tests to evaluate mechanical behaviour. Other elements of bagasse might be removed using pre-treatment fibres. This foliar spray changed the surfaces of fibres by reducing some of their crystalline constituents. The addition of which was previously and compatible fibres to a matrix phase increased the tension elastic properties. With up to 15% of the fibres, a much stiffer and far less flexible fabric might be obtained. Nevertheless, the application of the binding ingredient produced results that were greater than those obtained with other hybrids.

Currently, there are many online loans in Indonesia because they are very helpful in economic difficulties and are easy to do, especially for the millennial generation. But in the other hand, with the rise of online loans, there are also many individuals who take advantage of the situation by making illegal loan services. This research was conducted to find how financial technology, financial literacy, and income relate to online loans for the millennial generation in Indonesia. The purpose of this research is to determine the effect of how financial technology, financial literacy, and income relate to online loans for the millennial generation in Indonesia in partially and simultaneously. This study uses a quantitative method with a descriptive research type. The sample collection used the nonprobability sampling method and the number of respondents was 400 millennials aged 24-39 years old who used online loans. The analysis technique used is descriptive analysis and multiple linear regression. The result showed that in the descriptive analysis of financial technology 77,71% was included in the good category, 77,7% financial literacy was included in the good category, 82,9% income was included in the good category, and for the online loans 78,72% included in the good category. Partially, financial technology financial literacy, and income have significant effect on online loans for the millennial generation in Indonesia. Simultaneously, there is a significant influence of the financial technology, financial literacy, and income variables on online loans for the millennial generation in Indonesia.

In Indonesia, tourism in rural or village settings is growing as a kind of tourist development that supports regional culture and history. These communities support the economic development of rural regions while providing tourists with a comprehensive rural experience. Low pay and unpleasant working conditions are obstacles, though. This study measures the local communities' preparedness for the creation of a tourism town and rates its efficacy. The study investigates the trends and clusters in village tourism research using bibliometric analysis. The results provide stakeholders in Indonesia information to support national growth and alleviate regional inequities.

The purpose of this research was to the confirmatory Factor Analysis of Components of the Success of the Sufficiency Economy Model Community for Sustainable Quality of Life Development. Research population Specify a model community of sufficiency economy to be used as a sample in the study. By considering the criteria for considering the sufficiency economy community for sustainable development of the Office of the Special Committee for Coordinating Royal Projects, consisting of 9 communities, namely Pho Si Village Ban Nong Sarai, Ban Wang Nok Khai, Ban Hua Ao, Ban Sala Din, Ban Sakae Rai, Ban Suk Duean Ha, Ban Nong Den, and Ban Wang Chik, totaling 270 people in the year 2023. The statistics used in the research were advanced statistics for the analysis of social science. The results indicated that the adjusted model was consistent with empirical data. Goodness of fit measures were found to be: x²= 107.81, df = 39, p-value = 0.00000, GFI = 0.84, RMSEA = 0.048. The variables in adjusted model accounted for 85 percent of the variance in The Components of the Success of the Sufficiency Economy Model Community for Sustainable Quality of Life Development. the Components of the Success of the Sufficiency Economy Model Community for Sustainable Quality of Life Development consists of 4 components: 1) psychological and social aspects, 2) economic aspects, 3) learning aspects, and 4) natural resources and environment aspects. In addition, problems, obstacles, and ways to solve problems and sustainable development were found. which leads to a model community of self-reliance happily.

Urban crime is a worrying problem in Malaysia, especially in densely populated areas and large cities. Although Malaysia generally has a relatively low crime rate compared to some other countries, urban street crime still occurs, and it is important for residents and visitors to take precautions to prevent crime and to ensure their safety. The city of Ipoh is the oldest and one of the largest cities in Malaysia. Activities that are dense with social and economic activities encourage street crime to occur and increase after the economy reopens after April 2022. Therefore, the objective of this study is to unearth urban street crime that occurs in Bandar Ipoh and efforts that can be improved by Royal Malaysian Police (RMP) and local authorities to keep the public and the city safe to live in. The results of the study show that all informants among the public and police officers agree that the level of street crime is still under control despite the increase after the pandemic. Despite experiencing a not serious increase, the government's efforts through RMP and other authorities such as monitoring and patrolling need to be improved. Local authority needs to add facilities such as CCTV and improve Geographic Information System (GIS) will increase the level of security in the city. Future studies can be expanded in scope by involving studies in other cities in Malaysia with the use of diverse methods in data collection to increase the depth of the study results.

In this article, we compute the diameter and Wiener index of circulant graphs. We derive a formula for the Wiener index of these graphs, which is given by two forms, depending on the integer l. Furthermore, we explore the diameter of these circulant graphs and prove that diameter is equal 2. Additionally, we establish that the circulant graph exhibits Eulerian properties when the integer l is an odd number. Our finding contribute to the understanding of the structural characteristics and metrics of circulant graphs, providing valuable insights for graph theory and related fields.

Dengue disease has four serotypes such as DEN1, DEN2, DEN3 and DEN4. The transmission of dengue disease is occurred by the biting of infected Aedes mosquitoes. The person who has been dengue infected will have lifelong immunity to that serotype. They will have immunity to other serotypes in the short term, about 3 – 12 months. In this research, we describe the transmission of dengue disease by formulating the differential equations considering the serotypes of this disease. The populations are separated into human and mosquitoes. Human population are divided into susceptible, Infectious, and recovered. Mosquitoes are divided into susceptible and infectious population. We analyze our differential equations by standard dynamical modeling method. The numerical solutions are shown to confirm our analytical methods. The way for reducing dengue patients is showed.

The physical characteristics of hemp fibre were examined in terms of heat treatments and chemical treatments. Hemp fibres with hydrochloric acid and glyoxal for 2 hours. The effects of alkaline as well as formaldehyde therapy on elongation and tensile force at breaking were thoroughly investigated. Hemp's tensile modulus increased for the first five days of ageing at 50 °C before dropping. Heat complexation of the viscose in the fibre may have increased tensile properties, but pyrolysis due to glucose crosslinks decreased tensile. Tensile strength increased and break elongation decreased in nutrient specimens. Contaminants like paraffin as well as fat residue were removed from coconut fibre by interacting with the strongly basic solutions, which increased the fiber's strength. The cross linkage of viscose to fumaric acid in the fibre reduces flexibility while in use. Experiments were used to investigate the changes in morphology due to chemical treatments. Because of structural rigidity, NaOH and glyoxal can be successfully used to change hemp fibre with outstanding physical properties.

FMEA (Failure Mode Effect Analysis) has been used for several decades and has proven effective in assisting organisations in assessing the risks associated with breakdowns. FMEA risk rating numbers are employed to rank failure mechanisms that may happen in a system. The research has specific criteria for assigning a value to FMEA parts known as intensity, frequency, and recognition. Rather than relying solely on the analyst's expertise, this paper proposes a method for assigning the value for occurrence in a more realistic manner that represents the system's condition under investigation. The primary goal of this study is to build on and fill the research gap between manual and systematic approaches to document maintenance. The risk priority number was computed using trends in body machining data. This study thoroughly discloses the risk based on several characteristics, such as workstations, process inspection, quality checking, and sales returns. All four chosen factors exhibited a correlation coefficient of 0.3, indicating a weak relationship between the number of occurrences exceeding FMEA goal values and the number of Corrective Action Reports created.

The importance of entrepreneurship for economic development makes the interest of people who will be entrepreneurial an indispensable first step. However, interest alone may not be enough to start their own business because in entrepreneurship, entrepreneurs must dare to take risks in optimizing all existing opportunities and opportunities by applying various existing strategies to create something new. This research focuses on entrepreneurship education, motivation and self-efficacy on entrepreneurial intention.

Human activity recognition has received greater attention since last decade as datasets started showing up in literature. Some of these datasets have been developed in controlled laboratory environments or with practical considerations but with limited activities. There is still a need to generalize this effort to accommodate more human activities in practical environment either inside or outside. In this research, different components of human activity like feature extraction and classification of accelerometer data are addressed. We address feature extraction through filtering process and then classify these extracted features through machine learning tools. We show that tool like support vector machine is good enough for classification, but there is a need to improve feature extraction process using modern techniques like deep learning to automate feature extraction process. Experimental results are presented to compare experiments with expected optimum results.

The current work attempts to produce as well as analyse organic fibre materials (coir/epoxy, kenaf/epoxy, jute/epoxy) as well as polymer composites (coir/kenaf/epoxy, kenaf/jute/epoxy, and coir/kenaf/jute/epoxy) using a manual approach. These polymers were mechanically tested (tension, bending, shock, and fracture toughness). Among the three hybrids (coir/epoxy, kenaf/epoxy, and jute/epoxy), jute/epoxy composites have the highest hardness (99 Shore-D) but also the highest tensile strength (43 MPa). In contrast, kenaf/epoxy (9.36 MPa) and coir/epoxy (8.47 kJ/m²) hybrids have higher bending and impact resistance. The analysis indicates that bio-composites have improved mechanical behavior. The tensile modulus, stiffness, and impact resistance of the coir/kenaf/jute/epoxy-reinforced hybrid were 7.32 MPa, 2.9 GPa, and 8.67 kJ/m², respectively. The greatest elastic modulus of a coir/kenaf/epoxy reinforced composite was 84 MPa.

Financial problems are common problems felt by many people, ranging from difficulties in finding money, expenses that are greater than income, increased debt, to declining income. However, low financial literacy is one of the factors that trigger these financial problems. Financial literacy itself refers to the ability of individuals to understand and manage personal finances well. In that context, this thesis aims to examine the influence of family socioeconomic status (X), education level (W), and gender (Z) on the financial literacy (Y) of the community in Tanah Datar Regency. This study used quantitative methods using questionnaires as data collection instruments. Data obtained from 200 respondents in Tanah Datar District were analyzed using the Hayes Process Models regression analysis technique to examine the relationship between independent variables (family socioeconomic status) and moderator variables (education level and gender) with dependent variables (financial literacy). The effect of income, employment, asset ownership, education level, and gender on people's financial literacy levels was examined separately and together. The results showed that simultaneously, socioeconomic status and education level had a positive and significant effect on financial literacy. However, there was no significant effect of gender factors on financial literacy. Therefore, it can be concluded that family socioeconomic status and education level have a positive and significant relationship with the financial literacy of the people in Tanah Datar Regency. These factors can be used as guidelines in designing educational programs and policies that aim to improve financial literacy in the community. In addition, it is important to realize that gender differences do not have a significant impact on financial literacy, so efforts to improve financial literacy must involve all members of society regardless of gender. Therefore, an inclusive approach is needed in an effort to improve financial literacy, so that all people can understand and manage their personal finances well. That way, it is hoped that people can overcome the financial problems they face, and ultimately have a better financial condition.

This study aimed to determine the influence of recruitment and selection on employee performance, particularly in the Big Data Analytics division. Human resources are a crucial asset for a company to achieve success, and employees must perform at a high level according to the company’s targets or quality standards. The study used descriptive quantitative methods, with a population of all employees in the Big Data Analytics division, consisting of 35 employees, using the probability sampling technique. Data collection techniques included field studies and literature studies, and data analysis was carried out using path analysis, hypothesis testing, and coefficient of determination. The results showed that the Recruitment variable (X1) had no significant effect on Employee Performance (Y), while the Selection variable (X2) had a significant effect on Employee Performance (Y). Recruitment and Selection variables had a significant effect, with Recruitment having a direct effect on Performance of 70% and an indirect effect of 12.9%.

Access to knowledge has been widely broadened and made easy via various new technologies compared to how it was 30 years ago. This includes various sources that provide online access to thousands of research publications. As convenient as it may, dealing with large numbers of these reference materials can be quite a hassle while managing them can be even more so. Even though a combination of utility tools and reference management tools can be used to tackle this issue, it involves an unnecessary amount of manual work and time. The main goal of this project is to take a smarter approach of creating a web application that can be used to provide an interface for researchers to identify the material relevance of a research publication without having to read through the entire thing while also providing a centralized way for managing reference materials via the application itself. This eliminates a very common practice of using different applications such as MS. Word, Excel, and Reference management tools. “Documon” differs from existing solutions including available Reference management tools given its simplicity, automated workflows, “Research on The Go” features as well as the overall application utilizing Natural Language Processing, Web scraping, content suggestions and Information extraction using document patterns in PDFs.

Addressing the urgent global need for sustainable energy solutions, this pioneering study carves a transformative path for Indonesian Energy Corporations, with a spotlight on PARAMEL, a leading B2B downstream fuel company. By employing an innovative combination of the Analytical Hierarchy Process (AHP) and Systems Thinking, this research tackles the energy trilemma—security, affordability, and sustainability—through a mixed-methods approach integrating content analysis, AHP, and Causal Loop Diagram (CLD) methodologies to provide actionable insights for organizational change. The study identifies three crucial clusters for sustainable transition: Organizational Strategy and Alignment (OSA), Stakeholder Relations and Engagement (SRE), and Innovation, Culture, and Financial Performance (ICF). By understanding the hierarchical relationships between these factors, organizations can design targeted strategies for sustainability. The research advocates for PARAMEL's adoption of the Visionary Sustainability Pathway (VSP), emphasizing a comprehensive sustainability strategy supported by leadership commitment and effective communication. By leveraging innovative solutions and technologies, PARAMEL can enhance environmental performance and resource efficiency. Additionally, the study introduces PARENT, a business ecosystem shifting from traditional energy trading to solutions addressing the energy trilemma. The CANVAS+ Model of PARENT is presented, along with challenges of measuring organizational sustainability progress. By examining the Sustainable Corporate Story for PARENT, the extended KPIs that covered Environmental and Social aspect, Key Value Indicators (KVIs), and Key Decision-Making Indicators (KDIs) can be developed to guide organizations. In conclusion, this paper offers a blueprint for Indonesian Energy Corporations to adopt sustainable practices, exemplified by PARAMEL. The proposed mixed-methods approach identifies key factors driving sustainable change, and by pursuing the VSP and innovative solutions, corporations can enhance their environmental performance, resource efficiency, and commitment to sustainability.

The purpose of this research was to the Concept of Cooperative Network Development from Community Practice Model Sufficiency Economy to Learning for Sustainable Development. The study population was chosen from community leaders. Specific according to the criteria for considering the Sufficiency Economy Community for Sustainable Development of the Office of the Special Committee for Coordinating Royal Projects Personal characteristics of 106 respondents in the year 2023, consisting of community leaders, village committees Village chiefs/village headmen, members of SAO/sub-district municipalities, volunteer groups, housewives groups, community enterprise groups savings group. The elderly group and others, including monks, government employees classified by gender, age, education level Career and roles in the community. Study, analyze and synthesize the operation to achieve success of sufficiency economy model communities according to the sufficiency economy philosophy of sufficiency economy model communities, totaling 9 communities in 4 dimensions, consisting of (1) mental and spiritual dimensions; society (2) Economic Dimension (3) Learning dimension and (4) dimensions of resources and environment. by collecting data with a questionnaire The results of the study were analyzed and synthesized from questioning opinions of members of the sufficiency economy model community about the operational factors leading to the success of the sufficiency economy model community. Get information that can be analyzed and synthesized in this section. It was derived from answering questionnaires on the opinions of members of the sufficiency economy model community operation. The Concept of Cooperative Network Development from Community Practice Model Sufficiency Economy to Learning for Sustainable Development that classified into 4 sections, which were: 1) Data on personal characteristics of the respondents 2) Operational factors leading to success of the sufficiency economy model community consisting of 2.1) Mental and social operating factors 2.2) Economic operating factors 2.3) Activities 2.4) Operational factors related to natural resources and the environment, 2.5) Problems and community development approaches as a model of sufficiency economy, and 2.6) Partnership development networks.

In this paper, we look at how measurement error affects the statistical performance of the s chart. The linear covariate error model is used to evaluate the efficiency of the s chart with measurement error. The influence of input factors on the performance of the s chart is explored using the linear covariate error model. Shorter out-of-control average run lengths of the s chart are seen to be connected to smaller measurement error ratios, higher coefficient B values, and more repeated measurements of each item in each sample. To illustrate how to use the s chart when there is measurement error, an example is given.

In this paper, the notion of an entirely novel type of BP-algebras was introduced. Moreover, their fundamental characteristics were examined. Also, we thought about and talked about and talked about some novel ideas in permutation BP-algebras, such as {1}-commutative permutation BP-algebras, and some relationships with permutation BH- algebras and permutation B-algebras.

The honeycomb model serves as a comprehensive framework for understanding social media engagement. It encompasses seven dimensions, including identity, conversations, sharing, presence, relationships, reputation and groups. This study utilised a bibliometric analysis to examine keywords related to the honeycomb model, revealing distinct clusters that highlight practical aspects, theoretical frameworks, mathematical and computational aspects as well as a broad range of topics. The analysis showcased the multidimensional nature of the honeycomb model's research landscape and its significance across diverse sectors. The findings provided valuable insights for businesses and researchers seeking to enhance social media engagement and develop effective marketing strategies.

Bitcoin as a digital form of stock is widely researched to forecast its short-term and long-term value. Several studies have been conducted with the aim of predicting Bitcoin prices, however, data transformation techniques for better forecast in machine learning models have yet to be tackled in details. This research aims to generate a 7-day forecast of future Bitcoin prices from time-series data, using a 21-day historical data through Recurrent Neural Network (RNN) with applied Singular Value Decomposition. The methodology covered three models including a control model in which the number of singular values for SVD differ from one another while the rest of the model parameters were held constant. The study revealed that SVD transformation can reduce memory usage by 60% to 75%. However, in terms of predictive accuracy, the results indicate that there are no significant improvements on models with applied SVD over the control model. Despite this downside, this study can be useful in understanding dimensionality reduction with SVD, at the same time can serve as a steppingstone to create better predictive models from low density inputs, and this would serve as a guide for other researchers to understand Bitcoin and its economic nature.

Utilizing microbial cotton nanotubes, a photovoltaic enclosing membrane based on polyethylene adipate monomer (EVA) was developed. EVA was pre-treated with a butyric acid alkaline solution before being combined in a dual extruder. The effect of fibre on the tensile, thermal, and photonic properties of EVA composite films, as well as their blocking characteristics, has been investigated. Once altered BC signalling was utilised, the mechanical and repellent characteristics of the EVA coatings improved. The findings are attributed to the various pharmacological functional groups of the filament, as confirmed by XRD spectra. Demethylation of the EVA was postponed, and the light source opacity of the EVA sheets was maintained at or greater than 80%. Ultimately, our investigation demonstrated that only by employing an appropriate kind and amount of cellulosic was it feasible to increase the barrier qualities of EVA film with compromising significant clarity.

The article intended to study the influence of chemical reactions on Magneto hydrodynamic (MHD) fluid flow over a permeable extending sheet in the presence of a magnetic field with variable viscosity. The non-dimensional governing laws for this examination are resolved by utilizing the MATLAB BVP4C package. The impact of distinct non-dimensional governing equations on velocity, temperature, and concentration profiles have been discoursed qualitatively and exhibited graphically, as well the skin friction, rate of heat transfer, and rate of mass transfer values are analyzed, also displayed in tabular form.

The main purpose of this research work is to apply the theory of "interval graphs" to a specific viral genome, reconstruct the sequence from the unknown-ordered fragments for possible combinations for further studies. We use the restriction digestion method to cut the chromosome into many segments with several restriction enzymes. These cut segments can be separated by agarose gel electrophoresis according to their molecular size and are not in order of the original sequence. Besides, the segments cut out by each enzyme are different, so there will be intersections (sub-segments). The method of interval graph, suggested by14, attempts to use the information at the intersection to reorganize the original sequence. We selected our own patented insect viral gene sequence and conducted research on the above-mentioned interval graph method. More specifically, the isolated recombinant baculovirus, tentatively named ABM, and the widelyused prototype of baculovirus species, which is Autographa californica multiple nucleopolyhedrovirus (AcMNPV), were used as the model system. Although the length of the insect viral genome sequence we used is relatively short as compared with the genome of organisms, this study failed to achieve the purpose of sorting by the method of interval graph. The two main reasons can be summarized as follows: First, the enzyme experiment detected multiple short segments that did not intersect with other segments, and the interval graph method could not determine their positions in the original sequence. Secondly, any "graph” is made up of vertices and edges. Representing gene sequences with interval graphs means translating segments and intersecting segments with vertices and edges. Even if the improved method was adopted, the number of vertices and edges that can be loaded by the existing hardware makes this research unable to complete all the steps of the basic interval graph construction. This paper illustrates the experimental methods, mathematical procedures, relevant data and details, and provides experiences and references for scholars who are interested in researching this topic to seek breakthroughs in key steps.

Machine learning has become a vital part of marker genes selection. Complex machine learning models have been used to select genes that can possibly lead to different types of cancer, e.g. leukemia. Deep learning models have been used to provide deep and sophisticated research of potential gene mutations. Yet, the output from machine learning and deep learning models can be difficult to interpret. They can also be time-consuming. The aim of this research is to propose a fast way to pre-screen large datasets of genes and identify the ones whose mutations have the greatest possibility of causing leukemia. Unlike existing research, the proposed approach is easy to understand and provides insights into the importance of each gene, allowing medical researchers to have prior knowledge when setting up gene combinations for research. The proposed algorithm uses ANOVA ranking to calculate the importance of each gene and then a bootstrapped classification model to check if a selected combination of the genes generates high accuracy. This algorithm can be used as a fast way to select genes for medical tests.

Entrepreneurship is the process of identifying opportunities, taking risks, and creating and managing business ventures. With the continued development of business in Indonesia, it will encourage economic growth in Indonesia and is expected to reduce the number of unemployed. Therefore, it is very important for every educational institution to continue to encourage students to increase their interest in entrepreneurship. The purpose of this study was to determine the direct effect of entrepreneurship education, entrepreneurial mindset, and creativity on entrepreneurial intentions with an indirect role in entrepreneurial self-efficacy. This research study takes a quantitative approach, in which the data obtained from the survey is statistically evaluated using SmartPLS. Researchers took a sample of 105 samples from students throughout Indonesia who had participated in entrepreneurship learning or training as research objects using a purposive sampling method. The results of this study indicate that there is a positive and significant direct relationship between entrepreneurship education and entrepreneurial intention, entrepreneurial mindset and entrepreneurial intention, creativity and entrepreneurial intention, entrepreneurship education and entrepreneurial self- efficacy, entrepreneurial mindset and entrepreneurial self- efficacy, creativity and efficacy entrepreneurial self, as well as entrepreneurial selfefficacy and entrepreneurial intention. In addition, the results of the study show that entrepreneurial self-efficacy partially mediates the relationship between the variables of entrepreneurship education, entrepreneurial mindset, and creativity on entrepreneurial intentions.

In this research, the method of selecting explanatory variables in the linear regression model was presented in the presence of the two problems of high dimensions and outliers. The new selection method for variables was obtained by pooling or combining the Weighted Bootstrap with Probability method with the Robust LARS (RLARS) method called WBP-RLARS (Weighted Bootstrap probability - Robust Least Angle Regression method). It has been compared with some methods of selecting variables, namely B-LARS and B-RLARS Which depends on pooling or combining the pairs Bootstrap Approach in order to know the effect of employing some Bootstrap Approach (pairs Bootstrap and Weighted Bootstrap with probability) on the performance of the LARS method and the RLARS method in selecting variables in the HDRM model in the presence of outliers. The comparison was made using simulations, which were applied to different sample sizes (20, 26,70,90,104) and correlation coefficient (0.95) as well as data pollution ratios (0.05,0.10,0.15). Real data were analysed and the results of the analysis showed the preference of the WBP-RLARS method in the case of n < p and in the case of n>p the performance of the B-RLARS and WBP-RLARS method.

This article discusses the steady MHD Casson fluid past a vertical porous surface incorporating the effects of radiation, chemical reaction. Using similarity analysis the nonlinear system of PDEs are transformed to ODEs and then calculated by applying 4th and 5th order Runge-Kutta method. The graphs plotted illuminates the characteristics of heat and mass transfer flow, and their dependency upon the several parameters. Hear falling of velocity observed in Casson fluid parameter. Mathematical values of skin friction, rate of heat and mass transfer coefficients are examined in a tabular form.