Analysing Citizens’ Inputs in Public Online Open Innovation Platforms

Online open innovation platforms are being used widely in the public sector of many countries. Citizens are the main users of these types of platforms which allow citizens to share and post their ideas online. The citizens’ values that can be derived from the content of public open innovation platforms are not clear in the literature as previous studies were limited to studying open innovation platforms in the private sector. This study will explore the content of two public online open innovation platforms, specifically citizens’ interests which are called “values”. The ideas of around 2580 citizens from open innovation platforms in Saudi Arabia and Australia will be analysed. By using thematic analysis and a non-linear coding process, themes will be generated. These themes are categories of citizens’ values. Finally, citizens’ values will be represented as a framework of the content of citizen inputs in public online open innovation platforms

Harnessing the Power of Design Thinking for Open Innovation

University of Technology Sydney. Faculty of Engineering and Information Technology.Open innovation is a concept through which an organisation taps on the knowledge of external sources and acquires creative ideas for value creation. Open innovation has received high interest from the private sector compared to the public sector. The lack of awareness of conducting open innovation in the public sector has been considered a barrier to applying open innovation in the public sector. To enhance understanding and provide evidence on using open innovation in the public sector drawing from a comprehensive literature review and aspects of the Double Diamond design thinking model, this study proposed an initial conceptual framework that depicts steps, activities and tools applied in the public sector's open innovation process. The conceptual framework was validated through a multi-case study design and interviews with open innovation responsible in different countries and analysis of the content of five open innovation platforms. The research findings reveal details of the first stage which was missing in the literature that should be added to the open innovation process in the public sector which is problem determination. Moreover, the research findings elucidate that the five cases use design thinking to some extent, however only one case has used design thinking in the whole process and as a result overcome the challenges of the open innovation process compared to other cases which have some limitations regarding delivering the final solution to community, in addition to a lack of collaboration and coordination to implement the solution. Therefore, the best practice of design thinking enhances the practice of the open innovation process. This study has theoretical and practical contributions by providing insights from the lived experience of those involved in conducting open innovation and content available in open innovation platforms in the public sector. This study enhances organisations’ awareness of open innovation in the public sector and guides them on how to benefit from embedding the concepts of the design thinking approach to address the barriers to applying open innovation in the public sector

The Laplace Residual Power Series Method for Solving Fractional Fifth-Order Korteweg–de Vries Equations

This study explores a modern analytical approach for solving the fractional fifth-order Korteweg–de Vries (KdV) equations, which describe intricate wave phenomena influenced by nonlinearity, dispersion, and memory effects. Specifically, the Laplace residual power series method (LRPSM) is utilized to obtain accurate approximate analytical solutions for three fundamental fractional equations: the fractional Sawada–Kotera (SK) equation, the fractional Caudrey–Dodd–Gibbon (CDG) equation, and the fractional Kaup–Kuperschmidt (KK) equation. These equations represent special cases of the broader fractional fifth-order KdV equation. The novelty of this study lies in the application of LRPSM, which addresses the limitations of traditional methods by combining analytical precision with computational efficiency. The method successfully captures fractional dynamics, including soliton-like behaviors and memory effects, demonstrating its capability to model wave attenuation and smoothness influenced by fractional orders. The numerical results demonstrate that this method achieves minimal error margins, validating its robustness and precision in solving nonlinear fractional systems. Numerical examples validate the efficiency and robustness of this method, achieving high accuracy in solving nonlinear fractional systems. The results establish LRPSM as a versatile and reliable tool for solving fractional differential equations, paving the way for advancements in modern wave theory and applications across disciplines such as plasma physics, fluid mechanics, and nonlinear optics.OPEN ACCESS Received: 12/10/2024 Accepted: 21/01/2025 Published: 14/07/202

Enhancing quality characteristics and controlling gray mold disease caused by Botrytis cinerea in strawberries fruits using various edible abiotic coatings

The study aimed to evaluate the efficiency of chitosan, potassium silicate, and calcium chloride as edible abiotic coatings in controlling the postharvest gray mold disease of strawberries caused by Botrytis cinerea, reducing the use of chemical fungicides and managing fruit decay. Two pure isolates of B. cinerea were extracted from strawberry fruits of cv. ‘Festival’, identified based on morphological features, and their rDNA sequences were sequenced using BLAST and phylogenetic analysis, showing 98.9-100% equivalence. The ITS sequences have been deposited in Gene Bank and assigned accession numbers MT708074 and MT704983. In vitro, all treatments inhibited linear growth of both isolates, with chitosan and potassium silicate were the most effective against the two isolates. In vivo test showed a significant decrease in gray mold incidence and severity. The study revealed that potassium silicate significantly reduced disease incidence in strawberry fruit cultivars ‘Fortuna’ and ‘Festival’ from Qalyubia governorate, while chitosan achieved the greatest reduction in disease severity in samples from Beheira governorate. Both treatments increased the total phenolic and peroxidase activity. The study found that application of potassium silicate and chitosan to strawberry fruit in ‘Fortuna’ and ‘Festival’, resulted in higher sugar and ascorbic acid content, increased fruit firmness, and decreased respiration rate, suggesting that these treatments could potentially reduce postharvest decay and enhance fresh strawberry fruit quality

Deep Belief Networks (DBN) with IoT-Based Alzheimer’s Disease Detection and Classification

Dementias that develop in older people test the limits of modern medicine. As far as dementia in older people goes, Alzheimer’s disease (AD) is by far the most prevalent form. For over fifty years, medical and exclusion criteria were used to diagnose AD, with an accuracy of only 85 per cent. This did not allow for a correct diagnosis, which could be validated only through postmortem examination. Diagnosis of AD can be sped up, and the course of the disease can be predicted by applying machine learning (ML) techniques to Magnetic Resonance Imaging (MRI) techniques. Dementia in specific seniors could be predicted using data from AD screenings and ML classifiers. Classifier performance for AD subjects can be enhanced by including demographic information from the MRI and the patient’s preexisting conditions. In this article, we have used the Alzheimer’s Disease Neuroimaging Initiative (ADNI) dataset. In addition, we proposed a framework for the AD/non-AD classification of dementia patients using longitudinal brain MRI features and Deep Belief Network (DBN) trained with the Mayfly Optimization Algorithm (MOA). An IoT-enabled portable MR imaging device is used to capture real-time patient MR images and identify anomalies in MRI scans to detect and classify AD. Our experiments validate that the predictive power of all models is greatly enhanced by including early information about comorbidities and medication characteristics. The random forest model outclasses other models in terms of precision. This research is the first to examine how AD forecasting can benefit from using multimodal time-series data. The ability to distinguish between healthy and diseased patients is demonstrated by the DBN-MOA accuracy of 97.456%, f-Score of 93.187 %, recall of 95.789 % and precision of 94.621% achieved by the proposed technique. The experimental results of this research demonstrate the efficacy, superiority, and applicability of the DBN-MOA algorithm developed for the purpose of AD diagnosis

A nationwide survey of public COPD knowledge and awareness in Saudi Arabia: A population-based survey of 15,000 adults

BACKGROUND: There is a concerning lack of representative data on chronic obstructive pulmonary disease (COPD) awareness in Saudi Arabia, and a significant proportion of the population is vulnerable to developing a smoking habit, which is a major risk factor for the disease. METHODS: Population-Based Survey of 15,000 people was conducted to assess the public knowledge and awareness of COPD across Saudi Arabia from October 2022 to March 2023. RESULTS: A total of 15002 responders completed the survey, with a completion rate of 82%. The majority 10314 (69%) were 18–30 year and 6112 (41%) had high school education. The most common comorbidities among the responders were depression (7.67%); hypertension (6%); diabetes (5.77%) and Chronic Lung Disease (4.12%). The most common symptoms were dyspnea (17.80%); chest tightness (14.09%) and sputum (11.19%). Among those who complains of any symptoms, only 16.44% had consulted their doctor. Around 14.16% were diagnosed with a respiratory disease and only 15.56% had performed pulmonary function test (PFT). The prevalence of smoking history was 15.16%, in which current smokers were 9.09%. About 48% of smokers used cigarette, 25% used waterpipe and around 27% were E-cigarette users. About 77% of the total sample have never heard about COPD. Majority of current smokers (73.5%; 1002), ex-smokers (68%; 619), and non-smokers (77.9%; 9911) are unaware of COPD, p value <0.001. Seventy five percent (1028) of the current smokers and 70% (633) of the ex-smokers have never performed PFT, p value <0.001. Male, younger age (18–30 years), higher education, family history of respiratory diseases, previous diagnosis of respiratory disease, previous PFT, and being an ex-smokers increases the odds of COPD awareness, p-value <0.05. CONCLUSION: There is a significantly low awareness about COPD in Saudi Arabia, especially among smokers. A nationwide approach must include targeted public awareness campaigns, continued healthcare professional education, community-based activities encouraging diagnosis and early detection, advice on smoking cessation and lifestyle changes, as well as coordinated national COPD screening programs

Mathematical Model for the Control of Red Palm Weevil

The red palm weevil (Rhynchophorus ferrugineus) is a highly destructive pest, causing severe damage to palm trees and significantly reducing their productivity. This paper aims to develop and analyze a mathematical model that captures the interactions between palm trees, Rhynchophorus ferrugineus, and entomopathogenic nematodes as a means of integrated control. We identify the equilibrium points of the system and perform a stability analysis to assess the system&rsquo;s behavior. Additionally, we design a linear quadratic regulator (LQR) to limit the spread of the red palm weevil within a locally linearized framework. The feedback control law, which is both straightforward and immediately implementable, is employed to avoid the need for complex cost calculations, thus simplifying the solution to the optimal control problem. Numerical simulations demonstrate that the proposed control strategy is effective in reducing the number of infected palm trees. The results indicate that increasing the population of entomopathogenic nematodes can significantly decrease the red palm weevil population, offering a promising approach to mitigating this pest&rsquo;s impact

Asymptotic and Oscillatory Analysis of Second-Order Differential Equations with Distributed Deviating Arguments

This paper focuses on studying the oscillatory properties of a distinctive class of second-order advanced differential equations with distributed deviating arguments in a noncanonical case. Utilizing the Riccati method and the comparison method with first-order equations, in addition to other analytical methods, we have established criteria to test whether the solutions of the studied equation exhibit oscillatory behavior. To verify the validity of the results we obtained and determine their applicability, we present some examples to confirm the strength and accuracy of our proposed criteria

Oscillatory Properties of Second-Order Differential Equations with Advanced Arguments in the Noncanonical Case

This paper focuses on studying certain oscillatory properties of a new class of half-linear second-order differential equations with an advanced argument in a non-canonical case. By employing some new relations between the solution and its higher derivatives and taking into account the symmetry of positive and negative solutions, we have introduced new criteria to test whether all solutions of the studied equation exhibit oscillatory behavior. Our study aims to expand and enhance previous results, helping to understand these properties in the specified context. The results obtained are confirmed and clarified through an example involving Euler-type equations