Search results for: Suranga Nanayakkara

Authors: Priyashri Kamlesh Sridhar, Suranga Nanayakkara

Abstract:

Current frameworks in assessment follow lesson delivery and rely heavily on test performance or teacher’s observations. This, however, neglects the underlying cognitive load during the learning process. Identifying the pivotal points when the load occurs helps design effective pedagogies and tools that respond to learners’ cognitive state. There has been limited research on quantifying cognitive load in preschoolers, real-time. In this study, we recorded electrodermal activity and heart rate variability (HRV) from 10 kindergarteners performing executive function tasks and Johnson Woodcock test of cognitive abilities. Preliminary findings suggest that there are indeed sensitive task-dependent markers in skin conductance (number of SCRs and average amplitude of SCRs) and HRV (mean heart rate and low frequency component) captured during the learning process.

Keywords: early childhood, learning, methodologies, pedagogies

Procedia PDF Downloads 294

Authors: Sasini U. G. Nanayakkara, Nishala E. Wedamulla, W. A. J. P. Wijesinghe

Abstract:

Lovi (Flacourtia inermis) is an underutilized fruit crop grown in Sri Lanka with promising antioxidant properties; thus, exhibits the great potential to use as a natural antioxidant. With the concern of synthetic antioxidants, there is a growing trend towards the addition of a natural antioxidant to retard the rancidity of edible oils. Hence, in this backdrop, extract obtained from the peel of F. inermis fruit was used to retard the rancidity of selected edible oils. Free fatty acid (FFA) content and peroxide value (PV) of sunflower oil (SO) and virgin coconut oil (VCO) were measured at 3-day intervals for 21 days at 65 ± 5°C after addition of extract at 500, 1000, 2000 ppm levels and α-tocopherol at 500 ppm level was used as positive control. SO and VCO without added extract was used as the control. The extract was prepared with 70% ethanol using ultrasound-assisted extraction, and antioxidant efficacy and total phenolic content (TPC) of the extract were measured using 2,2-diphenyl-1-picrylhydrazyl (DPPH) radical scavenging capacity and Folin-Ciocalteu method respectively. Antioxidant activity (IC50) and TPC of the extract were 227.14 ± 4.12 µgmL⁻¹ and 4.87 ± 0.01 mg GAE per gram, respectively. During the storage period, FFA content and PV of both oils were increased with time. However, SO showed comparatively high PV than that of VCO and thereby indicate the progression of lipid oxidation as PV is a good indicator of the extent of primary oxidative products formed in oils. The most effective extract concentration was 2000 ppm. After 21 days of storage, VCO (control) sample exhibited significantly (p < 0.05) high FFA (0.36%) and PV (1.93 meq kg⁻¹) than that of VCO with 1000 ppm (FFA: 0.35%; PV: 1.72 meq kg⁻¹) and 2000 ppm (FFA: 0.28%; PV: 1.19 meq kg-1) levels of extract. Thus, demonstrates the efficacy of lovi peel extract in retardation of lipid oxidation of edible oils during storage at higher concentrations of the extract addition. Moreover, FFA and PV of SO (FFA: 0.10%; PV: 12.38 meq kg⁻¹) and VCO (FFA: 0.28%; PV: 1.19 meq kg⁻¹) at 2000 ppm level of extract were significantly (p < 0.05) lower than that of positive control: SO with α-tocopherol (FFA: 0.22%, PV: 17.94 meq kg⁻¹) and VCO with α-tocopherol (FFA: 0.29%, PV: 1.39 meq kg⁻¹) after 21 days. Accordingly, lovi peel extract at 2000 ppm level was more effective than α-tocopherol in retardation of lipid oxidation of edible oils. In conclusion, lovi peel extract has strong antioxidant properties and can be used as a natural antioxidant to inhibit deteriorative oxidation of edible oils.

Keywords: antioxidant, Flacourtia inermis, peroxide value, virgin coconut oil

Procedia PDF Downloads 98

Authors: Dona Shaini Abhilasha Nanayakkara, Kurugamage Jude Pravinda Gregory Perera

Abstract:

E-commerce platforms have revolutionized the shopping experience, offering convenient ways for consumers to make purchases. To improve interactions with customers and optimize marketing strategies, it is essential for businesses to understand user behavior, preferences, and needs on these platforms. This paper focuses on recommending businesses to customize interactions with users based on their behavioral patterns, leveraging data-driven analysis and machine learning techniques. Businesses can improve engagement and boost the adoption of e-commerce platforms by aligning behavioral patterns with user goals of usability and satisfaction. We propose TheAnalyzer, a clustering-based system designed to enhance business productivity by analyzing user-profiles and improving human-computer interaction. The Analyzer seamlessly integrates with business applications, collecting relevant data points based on users' natural interactions without additional burdens such as questionnaires or surveys. It defines five key user analytics as features for its dataset, which are easily captured through users' interactions with e-commerce platforms. This research presents a study demonstrating the successful distinction of users into specific groups based on the five key analytics considered by TheAnalyzer. With the assistance of domain experts, customized business rules can be attached to each group, enabling The Analyzer to influence business applications and provide an enhanced personalized user experience. The outcomes are evaluated quantitatively and qualitatively, demonstrating that utilizing TheAnalyzer’s capabilities can optimize business outcomes, enhance customer satisfaction, and drive sustainable growth. The findings of this research contribute to the advancement of personalized interactions in e-commerce platforms. By leveraging user behavioral patterns and analyzing both new and existing users, businesses can effectively tailor their interactions to improve customer satisfaction, loyalty and ultimately drive sales.

Keywords: data clustering, data standardization, dimensionality reduction, human computer interaction, user profiling

Procedia PDF Downloads 34