Mixed Programming Research Articles

Assessment of the viability of integrating virtual reality programs in practical tests for the Korean Radiological Technologists Licensing Examination: a survey study

The objective of this study was to assess the feasibility of incorporating virtual reality/augmented reality (VR/AR) programs into practical tests administered as part of the Korean Radiological Technologists Licensing Examination (KRTLE). This evaluation is grounded in a comprehensive survey that targeted enrolled students in departments of radiology across the nation. In total, 682 students from radiology departments across the nation were participants in the survey. An online survey platform was used, and the questionnaire was structured into 5 distinct sections and 27 questions. A frequency analysis for each section of the survey was conducted using IBM SPSS ver. 27.0. Direct or indirect exposure to VR/AR content was reported by 67.7% of all respondents. Furthermore, 55.4% of the respondents expressed that VR/AR could be integrated into their classes, which signified a widespread acknowledgment of VR among the students. With regards to the integration of a VR/AR or mixed reality program into the practical tests for purposes of the KRTLE, a substantial amount of the respondents (57.3%) exhibited a positive inclination and recommended its introduction. The application of VR/AR programs within practical tests of the KRTLE will be used as an alternative for evaluating clinical examination procedures and validating job skills.

Trade-off between optimal design and operation in district cooling networks

Especially in densely populated areas, district cooling represents an opportunity to reduce energy consumption and emissions. Nevertheless, this technology is characterised by large capital costs which impede its diffusion. As a consequence, optimization tools can significantly help to unleash their potential. In this paper, a methodology is proposed to combinedly optimize the design and operation of a district cooling system based on a Mixed Integer Quadratic Programming. The model is compared to the design only optimization, based on a properly tailored heuristic approach. The models, when applied to a case study characterized by seasonal demand, provide similar solutions, which differ by 0.5 % in terms of objective value for a standard scenario. The simultaneous design and operation optimization does not provide sensible savings with respect to optimizing solely the design. A sensitivity analysis is performed to prove the robustness of the results. The results showed that the simultaneous operation and design optimization would be limited to 1 % of total costs in the case of seasonal cooling demand. On the other hand, if the cooling demand persists throughout the year, as in tropical climates, the combined optimization provides significant benefits, since these savings reach 4.7 % of total costs.

Optimizing electric bus charging infrastructure deployment under two charging modes considering seasonal differences

ABSTRACT The innovations of battery and charging technologies facilitate worldwide bus electrification, which can conserve energy and reduce emissions. The emergence of wireless power transfer technology offers the potential to alleviate bus range anxiety. This paper constructs the layout models of static wireless and centralized charging stations based on the seasonal differences associated with battery capacities and passenger flow, which aims to obtain the bus charging station layout scheme of the lowest cost. Then, the heuristic algorithm is utilized to solve the layout models as the mixed linear programming problem. This study results confirm that the combined layout of static wireless and centralized charging stations is more advantageous than a single model. Finally, the required fixed cost of supporting bus system operation is explored for future capital reserves.

Integrating renewable energy sources for optimal demand-side management using decentralized multi-agent control

Demand-side management has garnered significant attention recently as a viable solution for electricity demand management. However, existing control approaches have encountered stability and energy efficiency issues that limit their effectiveness. To address these concerns, this work proposes a multi-agent control technique for optimal Demand-Side Management (DSM) in grid-connected mode. The proposed technique presents a novel multi-level nonlinear heterogeneous consensus control scheme to optimize the utilization of distributed energy sources and renewable energy resources under both fixed and dynamic communication scenarios. It validates the proposed model through extensive simulations and case studies conducted in MATLAB and JADE. Moreover, this work compares the performance of the proposed approach with state-of-the-art classical method, stochastic programming, model predictive control, and mixed linear programming techniques. The results of these techniques are evaluated and observe the superiority of the proposed approach. Decentralized coordination control results in energy savings of 21.4% through coordinated demand response schemes. Additionally, the proposed scheme surpasses other approaches in terms of active power sharing and delivering 14.2% more energy savings by effectively integrating energy storage sources and electric vehicles. Notably, the proposed approach achieve an impressive energy efficiency of 98.2% compared to 2% of other approaches. This remarkable efficiency translates to a 19% increase in energy storage capacity through multi-level coordination. This work further validates the practicality and feasibility of our proposed scheme to integrate distributed energy sources and renewable energy resources for sustainable and scalable energy models.

Reactive power optimization in active distribution systems with soft open points based on deep reinforcement learning

In the context of the increasing penetration level of photovoltaic energy, its intermittence and randomness bring challenges such as voltage over-limit and increased network loss to the distribution network. The paper proposes a real-time two-time-scale voltage regulation method with soft open point (SOP) to solve the reactive power optimization problem. To obtain hourly scheduling strategies for on-load tap changers and switchable capacitor banks, the centralized optimization problem is formulated as a mixed integer second-order cone programming in the first stage. In the second stage, the active distribution system is divided into multiple subsystems according to the proposed partitioning method, and the SOP is regulated to adjust the voltage in real-time through an effective control strategy and local measurement information of the subsystems. The proposed method takes full account of the randomness of photovoltaic, and can conduct distributed real-time voltage regulation in the active distribution system based on the rapid and continuous response of SOP. Compared with traditional methods, this method has lower communication costs, better real-time performance, and does not dependent on an accurate power flow model. Finally, the effectiveness of the proposed method is verified by the IEEE 33-bus and IEEE 123-bus simulation examples.

On transforming hybrid nonlinear control problems with model uncertainty and input disturbance to mixed integer-linear programs

Control of multi-input multi-output (MIMO) hybrid nonlinear dynamic systems which are affine in control inputs is studied in this paper. It is assumed that each control input of the system can be continuous or discrete with a bound constraint. It is also assumed that the controller is discrete-time and updates the control(s) with a constant frequency. Based on these assumptions, a theorem which represents the necessary and sufficient condition for uniform convergence of the sequence of samples of the state vector of system towards the desired point is presented and proved. As a result of this theorem, a (mixed integer-) linear programming for calculation of control(s) is proposed. Two well-known nonlinear hybrid control problems with multiple inputs are solved by using the proposed method and the results are presented.

Optimizing joint technology selection, production planning and pricing decisions under emission tax: A Stackelberg game model and nested genetic algorithm

In practice, manufacturers and their independent retailers in dyadic supply chains jointly make decisions by capitalizing on decision interactions while respecting the carbon emission tax and subsidy determined by local governments. Though studies have been published to address the joint decision-making, they involve only a very few of the important supply chain decisions due to the problem complexities. In this study, we, therefore, investigate a comprehensive joint decision-making of a manufacturer and his independent retailer considering both carbon emission tax and subsidy offered by the local government. The decisions in our study include i) the manufacturer’s technology selection, production quantities, and wholesale price and ii) the retailer’s retail price. Per the decision interactions, we analyze the decision-making problem as a Stackelberg game. The game model developed, by nature, is a bilevel 0–1 mixed nonlinear programming, and cannot be solved analytically. Considering its complexities, we further develop a nested genetic algorithm (NGA) to solve the model. Numerical examples demonstrate the applicability of the Stackelberg game model in facilitating supply chain members to jointly make decisions and the robustness of the NGA. With sensitivity analysis, we shed light on several important managerial implications, such as, manufacturers need to identify “optimal” ranges of emissions released from producing a unit of green (or dirty) product to obtain higher profits; manufacturers need to control well their production processes so that emissions released from producing a unit of product from a green (or dirty) technology fall in “optimal” ranges contributing to higher profits.

Risk-based distributionally robust optimal dispatch for multiple cascading failures in regional integrated energy system using surrogate modeling

Regional integrated energy system (RIES) with the close coupling of multiple energies faces various cascading failure risks in its operation, and formulating the risk-based optimal dispatch scheme is important to ensure the secure and economic operation of the RIES. Considering that the occurrence probability of each subsequent failure path caused by the initial failure in the cascading failure chain varies with the change of dispatch scheme, the cooling/heating and gas pipeline dynamics and the uncertainty of renewable energy, a risk-based distributionally robust optimal dispatch model for multiple cascading failures in a RIES is proposed. A kernel ambiguity set is constructed by using the maximum mean discrepancy between the real and reference probability distributions and the kernel mean embedding technology, which can obtain the more accurate worst-case probability distribution. Moreover, a surrogate modeling method based on piecewise convex quadratic functions is proposed to learn the mapping between the cascading failure risks and the decision variables, and the original large-scale mixed integer nonlinear programming model is transformed into a small-scale mixed integer quadratic constrained programming model for efficient solution. Finally, case study on an actual RIES demonstrates the effectiveness and advantages of the proposed method. Compared to optimal dispatch without considering the cascading failure risks, the proposed method can reduce the total failure risk cost by nearly 60%.

Mixed Training Programs Applied to Young Soccer Players: Effects on Speed-Power Abilities.

We compared the effects of two 4-week strength-power-speed training protocols on physical performance of young soccer players. Twenty-three highly trained under-20 soccer players were randomly allocated to two mixed-training groups: 1) "traditional" (TRAD: n=11), comprising vertically oriented strength-power exercises and linear sprints; or 2) "multidirectional" (MULTI: n=12), combining vertically and horizontally oriented strength-power exercises, linear sprints, and change-of-direction (COD) drills. Squat jump (SJ) and countermovement jump, 2) linear sprint, COD speed, and 3) jump-squat (JS) and hip-thrust (HT) power tests were performed pre- and post-training. Differences were determined using a two-way ANOVA with repeated measures and "target scores" were used to detect real changes in performance. No group-time interactions were found for any of the variables (p>0.05). Significant increases (p<0.05) in 20-m sprint velocity, JS- and HT-power were found in both groups, and in SJ in TRAD. Individual analyses revealed a greater number of meaningful changes in zig-zag velocity in MULTI while most players in TRAD displayed meaningful increases in SJ height. In conclusion, both training protocols resulted in similar adaptations but, at the individual level, it appears that MULTI protocol is superior to improve COD ability while TRAD should be preferred to maximize vertical jumping capabilities during short soccer pre-seasons.

Techno-economic investigation of hybrid peaker plant and hydrogen refuelling station

The power and transport sectors are responsible for significant emissions of greenhouse gases. Therefore, it is imperative that substantial efforts are directed towards the decarbonisation of these industries. This study establishes a combined-solar-wind system's economic and technical practicality for producing hydrogen for an onsite hydrogen refuelling station (HRS) and electricity to meet peak demand. To minimise the levelised cost of electricity and maximise the system's reliability at different commercial locations in South Africa, the dual-objective optimisation sizing is carried out using Mixed Integer Quadratic Constrained Programming (MICQP) model and was executed with an Advanced Multi-dimensional Modelling System (AIMMS) [61], [62]. The levelised costs of electricity and hydrogen at Johannesburg, Pretoria and Cape Town for 2 MW grid export benchmark are 74.2 $/MWh/5.85 $/kg, 76.3 $/MWh/5.97 $/kg and 50 $/MWh/4.45 $/kg respectively. The CO₂ equivalent emissions (tonnes) are 54,000, 55,800, 59,000 and the corresponding carbon taxes ($) avoided for the locations are 432,100, 446,200, and 472,000 for Johannesburg, Pretoria and Cape Town respectively. The results of the framework show that it can be adopted as a viable and fossil-free replacement for conventional peaking generators.

A Decision-Making Model to Determine Dynamic Facility Locations for a Disaster Logistic Planning Problem Using Deep Learning

Disaster logistics management is vital in planning and organizing humanitarian assistance distribution. The planning problem faces challenges, such as coordinating the allocation and distribution of essential resources while considering the severity of the disaster, population density, and accessibility. This study proposes an optimized disaster relief management model, including distribution center placement, demand point prediction, prohibited route mapping, and efficient relief goods distribution. A dynamic model predicts the location of post-disaster distribution centers using the K-Means method based on impacted demand points’ positions. Artificial Neural Networks (ANN) aid in predicting assistance requests around formed distribution centers. The forbidden route model maps permitted and prohibited routes while considering constraints to enhance relief supply distribution efficacy. The objective function aims to minimize both cost and time in post-disaster aid distribution. The model deep location routing problem (DLRP) effectively handles mixed nonlinear multi-objective programming, choosing the best forbidden routes. The combination of these models provides a comprehensive framework for optimizing disaster relief management, resulting in more effective and responsive disaster handling. Numerical examples show the model’s effectiveness in solving complex humanitarian logistics problems with lower computation time, which is crucial for quick decision making during disasters.

Flexible yard space allocation plan for new type of automated container terminal equipped with unilateral-cantilever rail-mounted gantry cranes

In this paper, new automated container terminals equipped with Unilateral-cantilever Rail-Mounted Gantry Cranes (URMGC) are considered as the research object. In the scenario, the automated guided vehicles can go deep among the container blocks arranged perpendicularly to the shoreline, which completely changes the yard’s operation mode and affects its operational efficiency. In addition, considering the shortage of storage space in the yard, a flexible space allocation strategy for these yards is studied, and a mixed integer quadratic programming model is established to minimize the horizontal transportation cost of containers. An improved particle swarm optimization algorithm is designed to compensate for the increased complexity of the proposed model. To accelerate the solution speed, the quantity and priority rules are developed to generate reasonable initial solutions, and two velocity updating strategies are adopted to accelerate convergence. Numerical experiments are conducted to validate effectiveness and efficiency of the proposed method, and comparisons with fixed space allocation strategy are presented. The results show that the strategy and solution adopted in this paper can reduce the driving distance of AGVs in such terminal configurations effectively and potentially increase the handling capacity of the yard.

Optimal AC/DC Distribution Systems Expansion Planning From DSO's Perspective Considering Topological Constraints

As the integration of DC distributed resources increases in recent years, hybrid AC/DC topology emerges as a promising alternative in the planning of distribution systems. This paper presents an AC/DC optimal expansion planning of distribution networks from Distribution System Operator's perspective with a special focus on grid architecture through Integer Programming-based topological constraints. The proposed formulation aims to determine the optimal location and sizing of converters and to select lines type (AC or DC) and state (closed or open). The problem is formulated as a mixed integer second-order conic programming model that guarantees global optimality and verifiable exactness by using off-the-shelf solvers. A multi-scenario approach with a Wasserstein distance-based scenario reduction is applied to deal with resource uncertainty. Case studies based on a 13 bus and IEEE 33 bus distribution networks were used to verify the effectiveness of the model. The results show that a hybrid architecture can improve the efficiency of the grid through optimal active power flow and reduce the total network costs.

START – physical exercise and person-centred cognitive skills training as treatment for adult ADHD: protocol for a randomized controlled trial

BackgroundCore symptoms in attention deficit hyperactivity disorder (ADHD) are inattention, impulsivity and hyperactivity. Many individuals with this disorder also have a sedentary lifestyle, co-morbid mental illness such as depressive and anxiety disorders, and reduced quality of life. People with ADHD often have impaired executive function, which among other things may include difficulty in time management and structuring of everyday life. Pharmacological treatment is often the first-line option, but non-pharmacological treatment is also available and is used in clinical settings. In children and adolescents with ADHD, physical exercise is used as a non-pharmacological treatment. However, the evidence for the effectiveness of exercise in adults is sparse.ObjectiveTo implement the START intervention (START = Stöd i Aktivitet, Rörelse och Träning [Support in activity, movement and exercise]) consisting of a 12-week, structured mixed exercise programme with or without a cognitive intervention, in adults with ADHD, and study whether it has an effect on core symptoms of ADHD as well as physical, cognitive, mental and everyday functioning compared with usual treatment. A secondary aim is to investigate the participants’ experiences of the intervention and its possible benefits, and to evaluate the cost-effectiveness of START compared with usual treatment.MethodsThis is a randomized controlled trial planned to be conducted in 120 adults with ADHD, aged 18–65. The intervention will be given as an add-on to standard care. Participants will be randomized to three groups. Group 1 will be given a physiotherapist-led mixed exercise programme for 12 weeks. Group 2 will receive the same intervention as group 1 with the addition of occupational therapist-led cognitive skills training. Group 3 will be the control group who will receive standard care only. The primary outcome will be reduction of ADHD symptoms measured using the World Health Organization (WHO) Adult ADHD Self-Report Scale (ASRS-v1.1), Clinical Global Impression-Severity scale (CGI-S) and CGI-Improvement scale (CGI-I). The effect will be measured within 1 week after the end of the intervention and 6 and 12 months later.DiscussionData collection began in March 2021. The final 12-month follow-up is anticipated to be completed by autumn 2024.Trial registrationClinicalTrials.gov (Identifier: NCT05049239). Registered on 20 September 2021 (last verified: May 2021).

Public Libraries Can Be Open Science Laboratories for Citizen Science Projects

A Review of: Cigarini, A., Bonhoure, I., Vicens, J., &amp; Perelló, J. (2021). Public libraries embrace citizen science: Strengths and challenges. Library &amp; Information Science Research, 43(2), 101090. https://doi.org/10.1016/j.lisr.2021.101090Objective – The objective of this study was to evaluate the potential of libraries supporting citizen scientist (CS) projects. Design – Mixed methods program evaluation study. Setting – 24 public libraries in Barcelona, Spain. Subjects – Public librarians and library users. Methods – It is a mixed methods and mixed population study done in several phases. The first phase involved training 30 librarians how to conduct a citizen science project. They were given a pre and post survey about their perceptions of citizen science and comfort-level in conducting a project. The second phase involved a project run by the now-trained librarians with library user participation. At this phase a questionnaire was given to the users at the start and end of the project. Finally, a focus group of librarians was asked about their project. The responses were evaluated through thematic analysis. Seven libraries participated in the focus groups. Main Results – During the first phase of the study, the survey found the librarians were pessimistic about user participation in a citizen science project, both at the beginning (75%) and at the end (79%) of the session. Though they felt confident in discussing citizen science (100%) and had high satisfaction in the training (70%), only 42% felt confident to conduct a project on their own. The second phase involved the users, 94% of whom had never participated in a CS project. At the end, 70% of users said the project positively changed their perceptions of the library and 70% were satisfied with the experiment. During the focus groups, librarians said the project brought new users into the library and had the potential to build more relationships among participants and with the community. Major challenges discussed were user commitment to the project and the workload required by librarians, however they all answered positively when asked about continuing with CS projects. Conclusion – This study showed that citizen science projects can be successfully implemented in public libraries. Public libraries are facing challenges caused by societal change, the rise of open science, and more transparent and novel democratic ways of knowledge production. Updating public library infrastructure would be needed to support these projects more fully. This may involve building partnerships and developing new guidelines. There is potential for public libraries to be leaders and innovators in citizen science.

Smart distribution grid management during a worst-case scenario of renewable energy outage

Nowadays, due to the high penetration of renewable energy sources such as wind generation and PV in the distribution network and the possibility of their outage, the optimal operation of the distribution grid has faced challenges. In this paper, a bi-level model based on mixed integer quadratic programming (MIQP) is proposed for the optimal operation of smart distribution networks under the worst case of the outage of renewable energy resources. At the upper-level problem, minimization of the energy losses, energy purchase, and load shedding in the demand side management program is formulated, and at the lower-level problem, the maximization of output and curtailment of renewable energy resources is modeled. At the lower level, the worst-case realization of the renewable outage is derived and at the upper level, optimal operation of the distribution network is done under the worst-case realization of renewable resources. The reformulation method based on Karush–Kuhn–Tucker (KKT) conditions is considered to solve the proposed bi-level model, which is faster and less complicated than similar algorithms. The IEEE 33-bus distribution grid is considered for the analysis of the proposed model and method, which proves the accuracy and optimal performance of the proposed model and method. The findings indicate that, with the implementation of the suggested model, the smart distribution network successfully avoided load-shedding even when various renewable resources were disconnected. Also, the proposed model in operation under normal conditions has caused a 56% reduction in losses and a 53% reduction in energy purchases compared to the outage of 6 renewable units in the distribution network.

Marketing Mix Relationship with Patients' Re-Visit Interest of Out Patient in Internal Polyclinic at Gunungtua Hospital

The marketing mix is ​​a set of marketing tools that a company uses to continuously achieve its marketing objectives which consist of product, price, place and promotion. Interest in revisiting behavior that appears in response to objects that indicate the desire of the customer to make repeat visits. The purpose of this study was to analyze the relationship between marketing and patient re-visit interest in outpatient disease polyclinic at Gunungtua Hospital, Padang Lawas Utara Regency in 2020. This type of quantitative research uses a cross sectional approach. The study sample was 150 people with purposive sampling. Data analysis used the chi square test with a significance level of α = 0.05 (95%). The results of the research were supported by the marketing mix associated with the interest in revising products (p = 0.002 &lt;α 0.05), price (p = 0.001 &lt;α 0.05), place (p = 0.002 &lt;α 0.05), and promotion ( p = 0.002 &lt;α 0.05). The results of this study indicate that the marketing mix in the form of products, places, prices and promotions can increase the interest of outpatient re-visits in internal medicine polyclinics. Gunungtua Hospital can improve the marketing mix program so that the interest in patient re-visits increases.

Substance Use Outcomes Among Sexual and Gender Minority Individuals Living with HIV Following Residential Substance Use Treatment in Washington, DC

ABSTRACT This study explored how sexual or gender minority (SGM) status influenced substance use (SU) treatment outcomes in a predominantly African American and unemployed sample of people with HIV. N = 60 participants were enrolled in an abstinence-focused inpatient SU treatment center, followed by outpatient treatment sessions. At 12-months follow-up, the survival rate (i.e. those who did not reuse substances) was 37.6% (non-SGM group) vs. 4.8% (SGM group). The impact of SGM status on reuse was .54 log odds, p = .11, which translates to a 71.8% increase in the hazard of reusing substances for SGM vs. non-SGM individuals. For both groups, frequency of reuse remained stable and problems associated with SU decreased over time. Results suggest a potentially clinically relevant finding that SGM individuals have possible heightened risk of SU after a mixed inpatient-outpatient program. ClinicalTrials.gov trial registration number: NCT01351454.

Effectiveness of a mixed lifestyle program in couples undergoing assisted reproductive technology: a study protocol

BackgroundThe desire for fertility is the manifestation of yearning for immortality. Infertility and assisted reproductive technology (ART) expose couples to great affective, anxiety, stress, and financial burden. Increasing evidence emphasize the impact of lifestyle on infertility. One of the most crucial factors affecting the fertility process is the nutrition patterns, the amount and quality of physical activities, emotional problems management; modulate stressors, relief from anxiety, and the living conditions of couples. Most ART treatment interventions in Iran are not integrated into lifestyle programs. Therefore, this research will investigate the impact of mixed fertility health-promoting programs in couples who use ARTs.Methodology/DesignThis study entails three steps. The first step includes the systematic review of literature on a health-promoting lifestyle in infertile couples undergoing ARTs, a systematic review of observational studies and interventions in couple’s lifestyle, then, a systematic review of qualitative studies on infertility in couples and their lifestyle, and in the final step couple’s life style literature systematically will evaluate in Iran. In case of failure to obtain the required results from systematic reviews, cross-sectional studies will be carried out to determine the lifestyle of infertile couples receiving ARTs. In the second stage, by holding a panel of experts, an intervention is planned based on the results of the previous stages in order to improve the lifestyle of couples. In the final step, the designed intervention will be administered as a random clinical trial—on ART candidates, in intervention or control groups in one of Iran University of Medical Sciences hospitals. Afterward, the data’s will be evaluated by using standard questionnaires, that include health-promoting lifestyle questionnaire (HPLII), Beck’s depression inventory (BDI), international physical activity questionnaire—short form (IPAQ-SF), and food frequency questionnaire (FFQ). The statistical analysis will be carried out in SPSS software. During the study, subjects meeting the inclusion criteria were randomly selected and randomized into the intervention and control groups. The health-promoting lifestyle training program will be executed for the intervention group while the standard care program is administered to the control group. The content of this program will be obtained from the consensus opinions of the expert panel. The program includes diet recommendations, physical activity, and stress management. Appropriate time, frequency, duration and number of activities will be considered. Communication with subjects will be possible through private meeting special comfort room. Support to the participants will also be through clinical visits social media, SMS and phone calls. Nutritional changes, physical activity amount, anxiety and stress level, abdominal circumference (AC), and body mass index (BMI) will be measured after the completion of the specified time interval. The initial outcome includes examining chemical pregnancy (2 weeks after the transmission) and clinical pregnancy by ultrasound (6 weeks after). The secondary outcome will be live birth rate. Retrieved oocyte and embryo numbers will also be reported.DiscussionHealth-promoting lifestyle programs are essential in assisted reproductive technologies to improve pregnancy results and live birth. These programs in association with in-vitro fertilization (IVF) influence the outcome of fertilization. In addition, enhancing parental health leads to healthy pregnancy outcome. Despite the frequency of lifestyle risk factors, employing proper methods helps reduce anxiety and stress, modify dietary patterns, and perform qualitatively and quantitatively balanced physical activities. In addition, having coping skills and mental health management methods, in nowadays modern world challenges seems crucial and effective in solving fertility problems and reducing them before pregnancy.

Effectiveness of a Mixed Methods-Based Literacy Program in Improving Reading Comprehension, Vocabulary Mastery, and Reading Fluency Skills of Early Grade Students

Many young children still experience reading difficulties when they enter school age. This study aimed to examine the effectiveness of a mixed methods-based reading literacy program (computer-assisted reading, independent tiered reading, and group-based reading teaching) to improve reading comprehension skills, vocabulary mastery, and reading fluency among early grade students. The study used a quantitative approach with experimental research methods. A quasi-experimental design was used to achieve the research objectives by involving 350 elementary school students who were in the fourth to sixth grade range of elementary school. The sample selection in this study involved the purposive sampling technique using several criteria. The teachers involved in this study totaled 150 teachers from 8 schools who acted as program implementers at school. The reading literacy program was implemented for two semesters for five days each week. The research findings show that the mixed methods-based reading literacy program had a significant effect on all competencies (word reading efficiency, reading comprehension ability, and reading fluency) in Grade 3 students, but this increase in ability was not seen in grades 5 and 6 students. More specifically, the effect size of the intervention on oral reading fluency in Grade 3 students was greater than the effect size in Grade 5 students. Furthermore, the effect size in Grade 4 was greater than the effect size in grades 5 and 6. This is because the treatment of reading difficulties in younger students is easier and more effective than in older students. In addition, based on the results of the correlation analysis, the number of words read during reading activities using a computer had a positive relationship with word reading scores and visual word reading efficiency in the post-test phase. Therefore, mixed methods-based literacy programs have a significant impact on reading fluency, and on vocabulary mastery and reading comprehension competence and reading fluency. This research has implications in that improving reading ability in the early grades is better done by using a combination of methods, such as computer-assisted reading, independent tiered reading, and group-based reading teaching. In this way, the improvement of students’ reading skills is more optimal.