Linear Techniques Research Articles

Pengaruh Digital Marketing dan Promosi Penjualan terhadap Keputusan Pembelian pada TWN Second Store Tasikmalaya

This study aims to determine: (1) the influence of digital marketing on purchasing decisions at TWN Second Store Tasikmalaya, (2) The influence of sales promotion on purchasing decisions at TWN Second Store Tasikmalaya. The type of research used is quantitative research. The population in this study were consumers of TWN Second Store Tasikmalaya totaling 900 people. The sampling technique used purposive sampling with a sample size of 90 people. This data collection technique uses a questionnaire that has been tested for validity and reliability. The analysis technique used in testing the hypothesis is the multiple linear regression analysis technique. The results of the study show that: (1) Digital marketing has a positive effect on purchasing decisions at the TWN Second Store Tasikmalaya of 82.6% and is proven by a sign value of 0.000<0.05, and the regression coefficient has a positive value of 0.448. (2) Sales promotion has a positive effect on purchasing decisions at the TWN Second Store Tasikmalaya of 74,0% and is proven by a sign value of 0.001<0.05, and the regression coefficient has a positive value of 0.279. (3) Digital marketing and sales promotions have a positive value and have a simultaneous influence on purchasing decisions at TWN Second Store of 84.4% and are proven by a sign value of 0.000<0.05.

The "4.3," A New Filler Lips Technique.

The "4.3" technique is a hybrid lip augmentation approach that combines the aesthetic benefits of the vertical-lip technique with the fewer entry points of the retrograde linear technique. This method aims to create natural-looking, harmonious, and defined lips using hyaluronic acid (HA)-based fillers, to enhance volume and contour. The objective of this study is to evaluate the effectiveness, safety, and reproducibility of the "4.3" technique in achieving natural lip augmentation with minimal filler volume and reduced injections. This technique is applied to improve the shape and volume of the lips while minimizing the risk of complications. The technique was applied to male and female patients with standard anatomical features who desired subtle enhancements in lip contour, projection, and volume. The procedure involved four injections in the upper lip and three in the lower lip, using a combination of retrograde linear and vertical techniques. A total of 0.7 mL of HA filler were used for each patient. The "4.3" technique achieved consistent and aesthetically pleasing results across all patients, with improvements in lip volume, shape, and definition. The reduced number of injections minimized discomfort and risk of vascular complications. The use of Tri-Hyal technology contributed to smooth, plump lips with harmonious proportions. The "4.3" technique is a standardized, intuitive, and reproducible method suitable for most patients, regardless of sex. It allows for natural-looking lip augmentation using a reduced volume of filler and fewer injections, making it a safe and effective option for enhancing lip aesthetics.

Examining the relationship between social well-being levels of health personnel and their perception of gender roles: a university hospital example

ABSTRACT The purpose of this research is to examine the relationship between the social well-being of healthcare professionals and their perception of gender roles. The correlational screening model was used in the research. The study group consisted of 247 healthcare professionals working in a university hospital. As a data collection tool in the research, the Social Well-Being Scale-Healthcare Professionals Version, Gender Roles Attitude Scale, and Demographic Data Form were used. Unrelated Samples t-test, One-Way Analysis of Variance, Pearson Product Moment Correlation Coefficient, and Multiple Linear Regression Analysis techniques were used to analyze the data. It was determined that the social well-being average of healthcare workers was 121.43 ± 24.46 and the gender role average was 99.48 ± 9.70. It was observed that the average social well-being of healthcare professionals differed at a statistically significant level according to family structure, length of service in the current institution, alcohol use, gender roles, gender, and profession (p < .05). As a result of the research, it was determined that there is a positive relationship between social well-being and gender roles. It was determined that gender roles, gender, length of service in the current institution and alcohol use status significantly predict social well-being.

Profit Quality, Islamic Corporate Social Responsibility And Company Values: Islamic Corporate Governance As Moderation

This study aims to analyze the effect of profit quality and Islamic corporate social responsibility (ICSR) on firm value moderated by Islamic corporate governance (ICG). This study uses a quantitative approach. The population used is all Islamic Commercial Banks (ICB) registered with the Financial Services Authority (FSA) in 2018-2023. The sampling technique used purposive sampling and obtained 11 ICB samples. The data source used is secondary data in the form of documentation of each BUS's financial statements. This study uses multiple linear regression analysis techniques. The results of this study indicate that profit quality negatively affects firm value. ICSR positively affects firm value. ICG is unable to moderate the relationship between profit quality and firm value. ICG is unable to moderate the relationship between ICSR and firm value. This study can complement existing theories and be a reference for future research. This study can also be a reference for ICB in increasing ICB value, especially regarding profit quality and ICSR.

Data-driven collaborative healthcare resource allocation in pandemics

Severe shortages of healthcare resources are major challenges in pandemics, especially in their early stages. To improve emergency management efficiency, this paper proposes a novel rolling predict-then-optimize framework that includes three interactive modules, i.e., data-driven demand prediction, healthcare resource allocation, and parameter rolling update. Such a framework uses historical data to dynamically update the control parameters of the proposed Net-SEIHRD model, which predicts the healthcare needs of each region by jointly considering government interventions and cross-regional travel behaviors. Based on the forecasted healthcare resource demand in real-time, an optimization model is then formulated to realize coordinated resource allocation across multiple regions by minimizing the total generalized cost. To facilitate model solving, the proposed mixed integer nonlinear programming model is converted into an equivalent mixed integer linear model by using some linearization techniques. Finally, the proposed method is applied to the SARS-CoV-2 emergency response and collaborative allocation of healthcare resources in Shanghai, China. The results show that the proposed prediction model can effectively predict the peak and scale of the spread of the virus. Compared with the traditional LM and SEIHR models, the prediction accuracy of the Net-SEIHRD model is improved by 10.76% and 24.11%, respectively. Moreover, coordinated relief activities across regions, such as patient transfer and drug-sharing can improve the efficiency of pandemic control and save social costs.

A uniqueness theory on determining the nonlinear energy potential in phase-field system

Abstract The phase-field system is a nonlinear model that has significant applications in material sciences. In this paper, we are concerned with the uniqueness of determining the nonlinear energy potential in a phase-field system consisted of Cahn-Hilliard and Allen-Cahn equations. This system finds widespread applications in the development of alloys engineered to withstand extreme temperatures and pressures. The goal is to reconstruct the nonlinear energy potential through the measurements of concentration fields. We establish the local well-posedness of the phase-field system based on the implicit function theorem in Banach spaces. Both of the uniqueness results for recovering time-independent and time-dependent energy potential functions are provided through the higher order linearization technique.

Data-Driven Prescribed Performance Platooning Control Under Aperiodic Denial-of- Service Attacks

This article studies a data-driven prescribed performance platooning control method for nonlinear connected automated vehicle systems (CAVs) under aperiodic denial-of-service (DoS) attacks. Firstly, the dynamic linearization technique is employed to transform the nonlinear CAV system into an equivalent linearized data model. Secondly, to improve the system’s transient performance, a prescribed performance transformation (PPT) scheme is proposed to transform the constrained output into the unconstrained one. In addition, an attack compensation mechanism is designed to reduce the adverse impact. Combining the PPT scheme and the attack compensation mechanism, the data-driven adaptive platooning control scheme is proposed to achieve the vehicular tracking control task. Lastly, the merits of the developed control method are illustrated by an actual simulation.

Analysis of the Influence of Brand Image and Product Variety on Purchasing Decisions for Wizzmie in Sidoarjo Regency

The goal of this study is to explore at how brand image and product diversity effect consumer purchasing decisions for Wizzmie in Sidoarjo Regency. A quantitative research approach, including a survey procedure, was employed. Wizzmie clients were requested to fill out surveys in order to collect primary data. The data was analysed using multiple linear regression techniques. The study's findings imply that brand image has a favourable and significant influence on client buying decisions. Product diversity has a substantial positive impact on buying decisions. As a result, both brand image and product variety impact Wizzmie consumers' purchase decisions in Sidoarjo Regency. This research implies that companies should pay attention to and enhance their brand image and product variety to improve consumer purchasing decisions. It is hoped that this will help companies in designing more effective marketing strategies.

The Influence Of Motivation, Work Environment, And Competency On Asn Performance In The Public Works, Spatial Planning, Housing And Settlement Area (Putrpkp) Enviroment Of Takalar District

The Influence of Motivation, Work Environment, and Competence on the Performance of Civil Servants in the Public Works, Spatial Planning, Housing and Settlement Areas Office (PUTRPKP) of Takalar Regency, guided by Andi Mappatompo Badawi and Dg. Maklassa. This study aims to analyze and explain the Influence of Work Motivation, Work Environment, and Competence on the Performance of Civil Servants in the Public Works, Spatial Planning, Housing and Settlement Areas Office (PUTRPKP) of Takalar Regency. This type of research is quantitative research, which is research based on data that can be calculated to produce a solid assessment using SPSS. This study used 68 respondents using multiple linear analysis techniques. The results of this study show that work motivation has a significant positive influence on ASN performance with P = 0.007 &lt; 0.05 with a coefficient value of 0.380. The work environment has a positive and insignificant influence on ASN performance with P = 0.502 &gt; 0.05 with a coefficient value of 0.118. Competence has a significant positive influence on ASN performance with P = 0.024 &lt; 0.05 with a coefficient value of 0.280. The Work Motivation variable is the most dominant variable that affects ASN Performance.

Performance Optimization with LPV Synthesis for Disturbance Attenuation in Planar Motors

Optimizing the performance of motion control systems with variations in nonlinear parameters is not an easy task. To accomplish this task, it is important to design the controller using the linear system approach. In this study, a linear parameter varying (LPV) control method is proposed in which nonlinearities are treated as parameter variations for planar motors. The proposed control method consists of the force and torque modulation with the commutation scheme and the nonlinear current controller with H∞ state feedback control in the form of LPV synthesis to improve the position-tracking performance. An interpolated gain-scheduling controller based on LPV synthesis is determined by applying H∞ control to a linear matrix inequality technique. An interpolated gain-scheduling controller can attenuate disturbance without disturbance estimation. The effectiveness of the proposed control method is evaluated using simulation results and compared with the conventional proportional–integral–derivative control to verify both improved position-tracking performance and disturbance attenuation.

Flourishing Pada Mahasiswa Yang Mengikuti Organisasi Kemahasiswaan Ditinjau Dari Spiritualitas Dan Dukungan Sosial

Flourishing is an important construct for students to have, because it has a positive impact or influence on them. These impacts include the good influence of flourishing on academic achievement and improving student performance. This research aims to determine the relationship between spirituality and social support and the flourishing of students who join student organizations. This research uses a correlational quantitative approach with 92 students as respondents who are currently actively participating in student organizations. The instruments used in this research were the flourishing scale (α = 0.832), the spirituality scale (α = 0.936) and the social support scale (α = 0.900). The data collection technique uses non-probability sampling techniques, especially purposive sampling techniques. In analyzing the data, researchers used multiple linear regression test techniques. The research results show that there is a relationship between spirituality and social support and the flourishing of students who join student organizations.

Order dispatch problem of the inter-city or inter-district ridesplitting service

This study formulates the order dispatch problem of the inter-city/inter-district ridesplitting service as an integer linear programming, and a solution framework that combines Lagrangian relaxation (LR) and alternating direction methods of multipliers is constructed. Specifically, LR problem is constructed by relaxing coupling constraints; based on this, the augmented Lagrangian relaxation (ALR) problem is constructed by adding a quadratic penalty term. Then, the ALR problem can be decomposed into a series of interdependent vehicle route subproblems by using linearisation technique and block coordinate descent method. The upper bound of the model is generated by ALR and a heuristic, and the solution quality can be evaluated by the lower bound provided by LR. Finally, numerous experiments are conducted to verify the effectiveness of proposed algorithms. The results show that the proposed algorithm could achieve an average cost saving of 10% and an average detour reduction of over 20% than the existing algorithm.

Sibling Discrimination Using Linear Fusion on Deep Learning Face Recognition Models

Facial recognition technology has revolutionised human identification, providing a non-invasive alternative to traditional biometric methods like signatures and voice recognition. The integration of deep learning has significantly enhanced the accuracy and adaptability of these systems, now widely used in criminal identification, access control, and security. Initial research focused on recognising full-frontal facial features, but recent advancements have tackled the challenge of identifying partially visible faces, a scenario that often reduces recognition accuracy. This study aims to identify siblings based on facial features, particularly in cases where only partial features like eyes, nose, or mouth are visible. Utilising advanced deep learning models such as VGG19, VGG16, VGGFace, and FaceNet, the research introduces a framework to differentiate between sibling images effectively. To boost discrimination accuracy, the framework employs a linear fusion technique that merges insights from all the models used. The methodology involves preprocessing image pairs, extracting embeddings with pre-trained models, and integrating information through linear fusion. Evaluation metrics, including confusion matrix analysis, assess the framework's robustness and precision. Custom datasets of cropped sibling facial areas form the experimental basis, testing the models under various conditions like different facial poses and cropped regions. Model selection emphasises accuracy and extensive training on large datasets to ensure reliable performance in distinguishing subtle facial differences. Experimental results show that combining multiple models' outputs using linear fusion improves the accuracy and realism of sibling discrimination based on facial features. Findings indicate a minimum accuracy of 96% across different facial regions. Although this is slightly lower than the accuracy achieved by a single model like VGG16 with full-frontal poses, the fusion approach provides a more realistic outcome by incorporating insights from all four models. This underscores the potential of advanced deep learning techniques in enhancing facial recognition systems for practical applications.

Modeling the Dynamics of Prosthetic Fingers for the Development of Predictive Control Algorithms

In the field of biomechanical modeling, the development of a prosthetic hand with dexterity comparable to the human hand is a multidisciplinary challenge involving complex mechatronic systems, intuitive control schemes, and effective body interfaces. Most current commercial prostheses offer limited functionality, typically only one or two degrees of freedom (DoF), resulting in reduced user adoption due to discomfort and lack of functionality. This research aims to design a computationally efficient low-level control algorithm for prosthetic hand fingers to be able to (a) accurately manage finger positions, (b) anticipate future information, and (c) minimize power consumption. The methodology employed is known as model-based predictive control (MBPC) and starts with the application of linear identification techniques to model the system dynamics. Then, the identified model is used to implement a generalized predictive control (GPC) algorithm, which optimizes the control effort and system performance. A test bench is used for experimental validation, and the results demonstrate that the proposed control scheme significantly improves the prosthesis’ dexterity and energy efficiency, enhancing its potential for daily use by people with hand loss.

Calculation of Distribution Network PV Hosting Capacity Considering Source–Load Uncertainty and Active Management

The access of a high proportion of photovoltaic (PV) will change the energy structure of the distribution network (DN), resulting in a series of safety operation risks. This paper proposes a two-stage PV hosting capacity (PVHC) calculation model to assess the maximum PVHC, considering the uncertainty and active management (AM). Firstly, we employ a robust optimization model to characterize the uncertainty of sources and loads in DN with PV and analyze the worst-case scenarios for PVHC. Subsequently, we construct a PVHC calculation model that takes into account AM, and convert the model into a mixed-integer second-order cone (MISOC) model using linearization techniques. Finally, we apply “heuristic optimization + CPLEX solver” to solve the model and introduce overvoltage and overcurrent indices to analyze the safety of the DN under PV limit access. Case studies are carried out on the IEEE 33-bus system and a practical case. Results show that (1) only the uncertainty that reduces the load or increases the output efficiency will affect PVHC; (2) for DN limited by overvoltage, AM can better improve PVHC; however, for DN limited by maximum transmission power, the effect of AM is low; (3) for most DN, SVC can improve PVHC, but the effect is modest. And network reconfiguration can significantly increase PVHC on the system with poor branch network, even reaching 150% of the original PVHC.

The Affect of Firm Size, Debt Policy, Profitability on Stock Returns: Moderating Role Dividend Policy

This research aims to examine the influence of Firm Size, Debt Policy and Profitability on Stock Returns with Dividend Policy as a moderating variable in non-financial Firms included in the LQ45 stock index on the Indonesia Stock Exchange (BEI) for the 2017-2022 period. The sampling technique in this research is the purposive sampling technique. This research uses secondary data, namely the firm's annual financial report (annual report) obtained from the official website of the Indonesian Stock Exchange (IDX). The analytical method used is multiple linear regression techniques and moderated regression analysis (MRA) with testing using the SPSS version 29.0 application. The research results show that Firm size has a positive and significant effect on stock returns. Debt policy and profitability have a negative and insignificant effect on stock returns. Dividend policy can moderate Firm size on stock returns. However, dividend policy does not moderate debt policy and profitability on stock returns; however, dividend policy can moderate the influence of Firm size, debt policy, and profitability simultaneously on stock returns. The managerial implications of this research show that Firm size, debt policy, and profitability have a significant influence on stock returns, while dividend policy can moderate this relationship.

Fractional order slide mode droop control for simultaneous voltage and frequency regulation of AC microgrid

AbstractThis research proposes the application of fractional‐order sliding mode control (FOSMC) at the primary controller level to improve the stability of an islanded microgrid by adjusting its voltage and frequency. The control strategies used in the microgrid are performed in two levels (primary and secondary) in the islanded mode. Practically, most previous studies have worked to improve the primary controller. Droop control is one of the most commonly used methods at the primary level and is adopted in this study as well. The sliding mode control (SMC) strategy is normally used to control linear equations. Thus, the non‐linear microgrid equations were transformed into some linear ones using the input‐output feedback linearization technique. Further, a fractional sliding surface was acquainted. The sliding surface and FOSMC were designed to reject system uncertainties and organize the voltage and frequency. Design parameters were chosen using the Lyapunov stability theorem. The validation of the proposed method using Simulink‐MATLAB confirms its effectiveness in enhancing level power sharing, regulating frequency, and maintaining voltage stability across the system.

The Influence Of Total Production, NTP And Grdp On Labor Absorption In The Coconut Plantation Subsector In Riau Province

This research aims to determine the effect of total production, Farmer Exchange Rate (NTP) and Gross Regional Domestic Product (GRDP) on labor absorption in the smallholder coconut plantation subsector in Riau Province in 2012-2023. In this research, multiple linear regression techniques were used using the Ordinary Least Square (OLS) method. The research results show that the simultaneous test (F test) shows that total production, NTP and GRDP together have a significant influence on labor absorption in the coconut plantation subsector in Riau Province in 2012-2023. Meanwhile, the partial regression test (t test) shows that total production has a positive and significant effect on labor absorption, NTP has a positive and significant effect on labor absorption, and GRDP has a negative and insignificant effect on labor absorption. The results of the coefficient of determination (R2) of the independent variable on the dependent variable obtained a value of 0.973238. This means that the contribution of the independent variables (total production, NTP and GRDP) to the dependent variable (demand for employment) is 97.32% and the remaining 2.68% is influenced by other variables outside the regression model in this research.

Reliable Finite‐Time Control for Nonlinear Chaotic Semi‐Markov Jump Systems With Incomplete Transition Rates

ABSTRACTThis article studies the finite‐time control problem for a class of nonlinear chaotic semi‐Markov jump systems with incomplete transition rates described by the T‐S fuzzy model approach. As a means to depict the dynamical properties pertaining to the examined system, parametric uncertainties, faults, external disturbances and input saturation are taken into consideration. The foremost objective of this study is to come up with a composite control mechanism that effectively rejects and attenuates the repercussions of faults and disturbances. In particular, we primarily built a disturbance observer in order to obtain a precise estimation of the external disturbances. After which, the fault diagnosis observer is designated to effectively estimate the faults. Specifically, a composite reliable control mechanism is developed by fusing the output of the constructed observers with the mode‐dependent fuzzy‐rule based state feedback controller. By employing suitable Lyapunov functions in conjunction with the linear matrix inequality technique, a set of mode‐dependent conditions is derived to ensure the finite‐time stochastic boundedness of the underlying closed‐loop and estimation error systems. Following this, the anticipated controller and observer gain matrices are elicited by resolving the established linear matrix inequalities. Thereafter, intending to ascertain the efficacy and usefulness of accrued theoretical findings, simulation results performed on Chua's circuit system is endowed.

The Effect of Sharia Financial Inclusion on Creative Industry Financing (KSPPS BMT-NU Lenteng Branch, Sumenep)

This study aims to analyze the effect of Islamic financial inclusion on creative industry financing in KSPPS BMT-NU Sumenep. Multiple linear regression analysis technique was applied to identify the influence of independent variables.The research design used in this study is a questionnaire to customers of BMT-NU EAST JAVA Lenteng Branch Office who are willing to be respondents and fill out a questionnaire, the purpose of which is to find out how much influence the independent variables, namely, Profile (X1), Income (X2), Accessibility (X3), and Product (X4) on financing the creative industry in Sumenep Regency. The results of the research obtained through multiple Linear Regression dummy variables are profile variables and products that have a significant positive effect on financing the creative industry of BMT-NU Lenteng Branch Sumenep customers. While the accessibility variable has a significant negative effect on financing the creative industry of BMT-NU Lenteng Sumenep Branch customers. While the income variable has a positive, but insignificant effect on financing the creative idustry of BMT-NU Lenteng Sumenep Branch customers.