Agroecological producers shortening food chains during Covid-19: opportunities and challenges in Costa Rica

Addressing Internet of Things security by enhanced sine cosine metaheuristics tuned hybrid machine learning model and results interpretation based on SHAP approach

An ever increasing number of electronic devices integrated into the Internet of Things (IoT) generates vast amounts of data, which gets transported via network and stored for further analysis. However, besides the undisputed advantages of this technology, it also brings risks of unauthorized access and data compromise, situations where machine learning (ML) and artificial intelligence (AI) can help with detection of potential threats, intrusions and automation of the diagnostic process. The effectiveness of the applied algorithms largely depends on the previously performed optimization, i.e., predetermined values of hyperparameters and training conducted to achieve the desired result. Therefore, to address very important issue of IoT security, this article proposes an AI framework based on the simple convolutional neural network (CNN) and extreme machine learning machine (ELM) tuned by modified sine cosine algorithm (SCA). Not withstanding that many methods for addressing security issues have been developed, there is always a possibility for further improvements and proposed research tried to fill in this gap. The introduced framework was evaluated on two ToN IoT intrusion detection datasets, that consist of the network traffic data generated in Windows 7 and Windows 10 environments. The analysis of the results suggests that the proposed model achieved superior level of classification performance for the observed datasets. Additionally, besides conducting rigid statistical tests, best derived model is interpreted by SHapley Additive exPlanations (SHAP) analysis and results findings can be used by security experts to further enhance security of IoT systems.

Consumer Behaviour and Attitude towards the Purchase of Organic Products in Riobamba, Ecuador

The development of organic agriculture has been promoted worldwide to improve the nutritional health of families, and Ecuador is no exception. The aim of this research was to identify the behaviour and attitudes of consumers toward the commercialization of organic products in the city of Riobamba. This will help us to understand in what situations the consumers access these foods, the producer position in relation to the market, and to know their attitude towards these products. The study used a quantitative approach, and is descriptive, incorporating the deductive method and a non-experimental design. The techniques used were a survey as a source of data collection, with a sample including 195 consumers. Linear regression was applied to test the hypotheses; this made it possible to identify those demographic and cultural factors that determine, to a lesser extent, consumer purchase behaviour in regard to organic products. The study determined that motivation, emotions, and feelings are significantly related to the consumer’s attitude and purchase of organic products.

Food Supply Impacts and Solutions Associated with the COVID-19 Pandemic: A Regional Australian Case Study

This study aimed to explore how food supply chains were impacted by COVID-19 and identify how the region could be better prepared for future crises. An online survey was completed by 107 consumers. In-depth interviews were conducted with 27 food supply stakeholders working in food production, distribution, retail, hospitality, institutions (i.e., childcare), logistics/freight and local government. Pre-COVID-19, farmer-direct distribution options and hospitality businesses comprised a substantial proportion of local food producer businesses. During the COVID-19 pandemic, consumers favoured local food supply options, farmers collaborated, and produce usually destined for export was redirected into local markets. Critical food supply actions included keeping borders open to food freight, enhancing social capital through real-time business communication, and business flexibility. Solutions included business adaptation, for example, farmers selling produce boxes and hospitality businesses selling excess stock, COVID-safe delivery, and collaboration through digital networks. To better prepare the region for future crises, actions to support communities could include a community approach to agriculture, increasing food supply diversity, facilitating transport to aid food distribution and purchasing, and more effective messaging to discourage panic buying. Actions to support retailers could include increasing access to wholesalers through online platforms. Actions to support producers could include improving infrastructure, such as more regional distribution facilities.