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This study aimed to develop a novel, sustainable, highly efficient, and affordable salt processing technology tailored to local salt producers. Novel technology converts raw solar sea salt into the finest dried salt, which is widely accepted by various industries. Experiments were conducted at a drying temperature of 80°C, with an air velocity of 30 m/s, and a feed rate of 125 kg per hour to evaluate the proposed novel salt processing technology. Performance evaluation was based on product quality parameters (e.g. wet moisture content, sodium chloride (NaCl) percentage, and whiteness) and specific energy consumption. The economic assessment relied on financial analysis and payback period parameters. The results indicated a reduction in salt sample moisture content from 10.37% ± 0.4% to 0.47% ± 0.02%, with NaCl percentage and whiteness of the salt produced at 98.5% ± 0.3% and 81 ± 0.7, respectively. The specific energy consumption for the novel salt processing technology was 0.119 ± 0.07 kWh/kg of the final salt product. Initial investment requirements totalled IDR 275,435,000, with a payback period of 1.66 years. This proposed novel salt processing technology has the potential to generate high-quality dried salt with a production efficiency of 89.5%. Consequently, it could enhance local producer’s businesses, seize opportunities in the national salt market, support rural industrialisation, and be best configured for Indonesia’s local salt producers. [ABSTRACT FROM AUTHOR]

VANETs (Vehicular Ad-hoc Networks) are a kind of Mobile Ad-hoc Networks (MANETs) with increased mobility as well as occasional geographic changes. Clustering is used in VANETs to divide networks into groups of adaptable vehicles to optimize routing, information gathering, as well as routing. As large data block transmission contains several stages and inside those, one of the important stages such as optimal model selection was these selections of quintessential features helps in a further stage called data transmission much more effective. This stage will also bring energy optimization and also improves the effectiveness of the optimal path for data transmission. This paper brings a comparative analysis of this optimal relay node selection. Here, we use Linear Scaling based Red Colobuses Monkey technique and are contrasted with other state-of-the-art models over various measures. Analysis proves that the proposed optimal relay node selection technique boosts the data transmission model. [ABSTRACT FROM AUTHOR]

The aim of this paper is to investigate agricultural sustainability as a collective issue involving multiple rather than individual farms. Through the utilization of energy consumption as a proxy, we propose a novel methodology that evaluates the impact of farm consolidations on agricultural sustainability while accounting for resource preferences. Our approach incorporates the ordered weighted averaging (OWA) operator within an inverse data envelopment analysis (IDEA) model to identify post-merger farms that meet preset efficiency targets. We employ a DEA cross-efficiency (DEA-CE) procedure to select merger plans that maximize agricultural sustainability for each preference scenario. By analysing a case study of 43 tomato greenhouse farms in Biskra, northern Algeria, our findings demonstrate that mergers can significantly enhance agricultural sustainability, surpassing the potential of individual farms by a factor of over 15. Additionally, the adoption of the most sustainable merger plan can lead to energy savings of more than 69%. Irrespective of the preference scenario, substantial energy savings in machinery, fertilizers, diesel, and electricity ranging from 22.92% to 73.73% were observed. These results emphasize the strategic role of merger processes in promoting agricultural sustainability and optimizing resource utilization. [ABSTRACT FROM AUTHOR]