International Journal of Advances in Scientific Research and Engineering (IJASRE), ISSN:2454-8006, DOI: 10.31695/IJASRE
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Determination of the Optimal Marketing Strategy for Iced Tea Beverages Product Using Mixed Strategy Game Theory
Get PDFIn Indonesia, iced tea is a popular drink enjoyed by people of all ages. This has led to the emergence of various brands and flavors of iced tea beverages. The growing number of these businesses makes competition fiercer and forces businesspeople to develop marketing strategies.
The goal of this study is to determine the optimal marketing strategy for two brands of iced tea. The marketing strategies for these brands include product quality, price, service, promotion, packaging, and location. Mixed strategy game theory is used to determine the optimal marketing strategy.
Based on the results of the competitive analysis using game theory, the optimal strategy for Brand A is price, promotion, and location. Brand A's probability values are 0.5 for price, 0.333 for promotion, and 0.167 for location. The optimal strategy for Brand B includes promotion and location. The probability values for promotion and location are 0.667 and 0.333, respectively. The game value is 5.67
Integrating Lean Canvas and SOS Validation for Early Validation of FTTH Design Automation
Get PDFThis research evaluates the effectiveness of an early product validation framework that integrates Lean Canvas with State-of-the-Solution (SOS) Validation. The focus is on the development of Integrated High Level Design (iHLD), a Fiber to the Home (FTTH) network design automation product. The main objective of this study was to test critical assumptions related to the problem, solution, and value proposition among internal technical users. The research methodology adopted a descriptive-qualitative approach. Initial assumptions were mapped using Lean Canvas, then validated through customer discovery interviews adapted from SOS Validation principles. These interviews involved 23 internal users of the Survey Design Inventory (SDI). The collected data was analyzed descriptively and thematically.
The analysis showed that the assumptions regarding the main problem, i.e. the inefficiency and length of the manual network design process, were strongly validated by internal user responses. Similarly, assumptions regarding iHLD's solution (design automation) and value proposition (operational efficiency and ease of use) were also strongly validated. Quantitatively, the implementation of iHLD proved to drastically reduce design time. The average manual design time, which was previously 30 minutes per design, was successfully cut down to about 1.35 minutes per design, indicating a substantial increase in productivity. This positive impact also contributed to increased user satisfaction and reduced workload.
However, the study also identified that assumptions related to potential revenue streams and cost structures were hypothetical and had not been empirically confirmed at this early validation stage. The main conclusion of this study is that the problem-solution fit has been internally confirmed. However, further validation covering the technical aspects of the algorithm comparatively, external market acceptance, and overall business model viability, is absolutely necessary before the iHLD product can enter the scale-up or market expansion phase
Electronic Signature Policy through the Singo Application at the Secretariat of the DPRD of Malang City
Get PDFThis study aims to analyze the application of the Singo application as well as the obstacles and efforts in its implementation based on the Minister of Home Affairs Regulation Number 1 of 2023. The research was conducted at the Secretariat of the Regional People's Representative Council (DPRD) of Malang City. The data analysis technique in this study used qualitative descriptive analysis. The research findings show that implementing Minister of Home Affairs Regulation No. 1 of 2023 through the Singo Application at the Secretariat of the Malang City DPRD is running quite well based on four Edward III policy indicators: communication, resources, disposition, and bureaucratic structure. The socialization conducted has helped internalize the use of the application, although there is still a need for increased training and technical guidance to reduce concerns of TTE misuse. Infrastructure support, such as computers and mobile phones, is adequate, but application maintenance has not been optimized, so manual signatures are still used when disruptions occur. The disposition of implementers shows a supportive attitude, but high workload constraints hinder the effectiveness of the process. Coordination between implementers is good, but human resource capacity building and more effective supervision are needed. It is expected that the secretariat of the Malang City DPRD will conduct periodic socialization, provide online technical guidance, provide additional supervisory personnel, and maintain the Singo application to improve the effectiveness of electronic signature implementation
Biosynthesis of Silver Nanoparticles and Its Effects on the Establishment in vitro of Cassava (Manihot esculenta)
Get PDFCassava (Manihot esculenta) is a staple crop in Belize, yet efficient in vitro propagation remains challenged by microbial contamination and inconsistent explant development. Silver nanoparticles (AgNPs) offer antimicrobial and growth-modulating benefits. This study compared green-synthesized versus commercial AgNPs on the establishment in vitro of cassava var. “white”. Green AgNPs were biosynthesized using Moringa oleifera extract with AgNO₃ and characterized by UV–Vis and FTIR; commercial AgNPs (XFNANO) served as a reference. Nodal explants were cultured on Murashige and Skoog medium with 1 mg/L 6-benzylaminopurine, 1 mg/L α-naphthaleneacetic acid, and AgNPs at 0, 5, 10, and 15 mg/L. After five weeks, shoot and root lengths were recorded. Contamination percentages were also evaluated. Data were analyzed by one-way ANOVA with Tukey’s HSD for parametric cases and Kruskal–Wallis with Dunn’s post-hoc when assumptions failed. Commercial silver nanoparticles significantly enhanced shoot elongation in a dose-dependent manner, with the 15 mg/L treatment producing a mean shoot length of 1.82 ± 3.27 cm compared to 0.12 ± 0.41 cm in the control group (p < .001). Root growth was also stimulated, reaching 0.44 ± 0.90 cm versus 0 cm in controls (p = 0.0003). In contrast, green-synthesized AgNPs inhibited shoot elongation at 5 mg/L, reducing mean shoot length to 0.38 ± 1.19 cm from 2.20 ± 3.70 cm (p < .001), while root length fell to 0.07 ± 0.26 cm compared to 0.76 ± 1.57 cm in untreated plants (p = 0.0002). Nonparametric tests confirmed these trends under non-normal data distributions. The variance ranged from medium to large, indicating robust treatment effects. Commercial AgNPs can promote initial explant growth, while plant-extract–derived AgNPs at tested doses exert phytotoxicity. These contrasting outcomes underscore that nanoparticle source and concentration must be optimized to balance antimicrobial control with plant growth. 
Design and Development of a Smart Citizen Engagement Platform for a Smart City
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The project aims to design and develop a Smart Citizen Engagement Platform for a Smart City. The concept of Smart Cities revolves around enhancing the quality of life for urban inhabitants through innovative technologies and sustainable practices. The key strategy of this transformation is citizen engagement, which ensures that residents actively participate in shaping their city’s future. However, the design faces challenges of hesitation from Citizens to get involved. In the context of smart cities, citizens must actively engage with planners and architects to collaboratively shape the urban environment. The aim of the study was to create a place where information technology is combined with infrastructure, architecture, everyday objects and our own bodies to address social, economic and environmental problems’ (Townsend 2013, 15).
The study used a mixed method design, employing a Causal research design and focused group discussions across 3 selected Districts in Urban, Peri-Urban and Rural areas in Lusaka Province of Zambia. The interviewees were grouped into two groups aged (18-35) and (36 and above) registered in online platforms/peer groups that included Facebook, WhatsApp and Zoom meeting platforms. Quantitative data was collected using Google forms. A total of 450 interviews were conducted.
The findings of the study indicated that only 82% of the Population were ready to get involved in creating smart city, with 6% adopting a wait and see approach to what happens from the study of creation of smart city and 12% totally unwilling to get involved all together. The determinants of these behavior intentions included: the perceived adverse effects of digital-driven interactions between citizens and planners, inadequate information about the smart city creation, conflicting information about how difficulty creating a smart city is from the social media.
Hesitancy in joining smart city creation remains high among the population but the causes of it are modifiable and communication systems need to have evidence based engagements with the population to reduce hesitancy.
I’m Michael Kanyanta Kabwe, a Student studying Information and Communications Technology at Information and Communications University. Away from Class, I work as an Information and Communications Technology Technician, looking forward to becoming a respectable Information and Communications Technology Engineer so that I can help out in fostering technology in both Information and Communications which is my dream work.
Participant’s biography, Mr Jones Chiguta, Zambia National Service, a Software Engineer with expertise in developing interactive Information and Communications Technology Platforms.
Misclassification-Aware Hybrid Model for Binary Rainfall Prediction
Get PDFHybrid framework for rainfall classification that integrates machine learning (ML) and deep neural network (DNN) applied on meteorological data. The primary DNN serves as robust baseline trained with normalized meteorological features from different sites in the target area after simple preprocessing such as dropping unnecessary features, using MinMaxScaler for feature scaling. To further reduce misclassification samples, a correction mechanism was applied using secondary Light Gradient Boosting Machine (LightGBM) model, which was trained only on misclassified samples by the DNN model.
ROC curve (AUC = 0.98), confusion matrix and precision recall curve proved the model differentiation ability. Furthermore, KMeans clustering highlighted the class strong separation for rain / no-rain classes. Learning curves suggested stable training optimization with consistent generation.
This hybrid method achieved overall accuracy of 98%, while both precision and F1-score were 98% with 96% recall.
As the results proves that using DNN and second ML model specifically for the misclassified samples can boost the rainfall prediction model
Physicochemical characteristics of septic tank sludge treated with calcium oxide in Kinshasa, Democratic Republic of Congo
Get PDFVarious chemicals are used to disinfect septic tank sludge. Their influence on sludge quality is the main focus of this study. This research focuses on manual septic tank cleaners who typically use a hole dug in the ground as a disposal site for sludge. The study is conducted on a laboratory scale on the characteristics of this sewage sludge when treated with calcium oxide (quicklime). Sewage sludge from on-site sanitation systems is contaminated with pathogenic microorganisms; it is possible to modify their biotic characteristics to an acceptable level by treating them with calcium oxide. Several parameters considered to be indicators of pollution are targeted and analyzed in samples of fresh sewage sludge or sludge treated at three levels: 10%, 15%, and 20% CaO; These include total bacteria, fecal coliforms, total streptococci, fecal streptococci, staphylococci, and helminth eggs. The reduction rate for each parameter was used to evaluate the effectiveness of the treatment. The 20% treatment produced interesting results, with a reduction rate ranging from 98.00% to 100% for the bacteriological parameters. The quantities of sewage sludge and lime, their physical state, temperature, pH, contact time, and inhibitors are parameters that influence the speed of this reaction. The results show that chemical treatment with calcium oxide reduces the risk of biological contamination. Sewage sludge from septic tanks treated in this way can be used to improve agricultural soils
An Optimization Ensemble Model for the Detection of Fake News
Get PDFThe rising problem of misrepresentation and misinformation has taken center stage in the contemporary world as a consequence of the digitization of information. The rapid circulation of false information aggravates social and civic conflicts, erodes social trust, and stalls responsible public policy and governance. Therefore, distinguishing fraudulent information from real information has never been more critical. This research proposes a new integrated approach to the problem of fake news in considering the limitations posed by the machine learning approach. This research proposes an enhanced integrated model by making use of the distinctive advantages of several classifiers. For this purpose, the Firefly Algorithm is adopted to assign the optimal feature set and optimally distribute weights to the three base models: XGBoost, SVM, and LR integrated in the optimization ensemble model. The experimental results showed significant optimization ensemble performance improvement with an accuracy of 99.97%, a 99.96% F1-score, 99.94% precision, and 99.97% recall. The performance was comparable to, or slightly better than, that of the top individual model, XGBoost, demonstrating increased ensemble strength and robustness. These results endorse the approach of ensemble learning combined with ensemble learnin
Physicochemical characterization of peat in the Mpama bog in the Congo Basin in northwestern DR Congo
Get PDFThis study is a monitoring of peatlands that aims to determine their natural state in order to obtain scientific information on their physical and chemical properties. It contributes to the characterization of natural capital by evaluating the physical and chemical parameters of peat in the peatlands of the Congo Basin, specifically that of Mpama, with a view to the sustainable management of this ecosystem. The following parameters were determined: temperature (T), hydrogen potential (pH), electrical conductivity (EC), total dissolved solids (TDS), oxidation-reduction potential (ORP), dissolved oxygen (O2), total organic carbon (TOC), moisture (H), density (D), cellulose (CEL), lignin (LIGN), and ash content (TC). The results obtained show variation in the physicochemical parameters analyzed from one sampling point to another. Overall, Mpama peat is acidic, rich in organic matter, very wet, and low in minerals; it has high carbon storage potential, and its low density and high moisture content confirm that it is still actively decomposing
Innovative Use of Agro-Waste Reinforcing Epoxy Composites with Bamboo, Pineapple, and Agarbatti Powder
Get PDFA composite material is made from two or more constituent materials, providing better properties compared to its parent materials. These composites are stronger, lighter, and more economical than traditional materials. In recent years, composites have gained significant attention for advanced engineering structures. This research explores mechanical properties like tensile, flexural, and impact strength of epoxy composites reinforced with natural fibers. Variations of bamboo and pineapple fibers are analyzed, with agarbatti powder hybridization using the hand layup technique. The composites were fabricated and tested as per ASTM standards, demonstrating enhanced mechanical properties. This study aims to identify the optimal composite configuration based on strength parameters.
Key Words: Reinforcement, epoxy resin, bamboo fiber, pineapple fiber, agarbatti powder, composite