385 research outputs found
AI technologies for enhancing recycling processes
No full textAI technologies revolutionize recycling processes by offering innovative solutions to the challenges of waste management and resource recovery. By utilizing advanced algorithms, machine learning, and computer vision, organizations may enhance sorting accuracy, optimize logistics, and improve the efficiency of recycling systems. Robotics can identify and separate recyclable materials more effectively than traditional methods, reducing contamination and increasing recovery rates. Predictive analytics can streamline operations by anticipating demand and adjusting processing capabilities. Further exploration into the integration of AI in recycling may increase operational performance while supporting current environmental goals and a circular economy. AI Technologies for Enhancing Recycling Processes explores the influential role technologies play in transforming waste management practices and propelling us towards sustainability. It examines the pressing international issue of waste accumulation and critiques the inadequacies inherent in conventional disposal methods, revealing how advancements such as automation, robotics, and state-of-the-art processing methods can revolutionize our approach. This book covers topics such as environmental science, nanotechnology, and sustainability, and is a useful resource for computer engineers, material scientists, environmentalists, business owners, economists, academicians, and researchers
Exploring sentence level query expansion in language modeling based information retrieval
No full textWe introduce two novel methods for query expansion in information retrieval (IR). The basis of these methods is to add the most similar sentences extracted from
pseudo-relevant documents to the original query. The first method adds a fixed number of sentences to the original query, the second a progressively decreasing number of sentences. We evaluate these methods on the English and Bengali test collections from the FIRE workshops. The major
findings of this study are that: i) performance is similar for both English and Bengali; ii) employing a smaller context (similar sentences) yields a considerably higher
mean average precision (MAP) compared to extracting terms from full documents (up to 5.9% improvemnent in MAP for
English and 10.7% for Bengali compared to standard Blind Relevance Feedback (BRF); iii) using a variable number of sentences for query expansion performs better and shows less variance in the best MAP for different parameter settings; iv) query expansion based on sentences can
improve performance even for topics with low initial retrieval precision where standard BRF fails
Interaction between Plants and Growth-Promoting Rhizobacteria (PGPR) for Sustainable Development
No full textThe relationship between plants and microorganisms is of paramount importance in maintaining the delicate balance of life on Earth, as evidenced by their interconnectedness in the intricate tapestry of nature [...
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Report on the Nineteenth International FLAIRS Conference
No full textThe Nineteenth International FLAIRS Conference (FLAIRS-19) was held 11-13 May 2006 at the Crowne Plaza Melbourne Oceanfront Hotel in Melbourne Beach, FL. The general cochairs were Philip Chan and Debasis Mitra, from the Florida Institute of Technology. The program cochairs were Geoff Sutcliffe, from the University of Miami, and Randy Goebel, from the University of Alberta. The special tracks chair was Barry O'Sullivan, from University College Cork. The conference was attended by almost 200 AI researchers from around the world
Microbial Solutions in Agriculture: Enhancing Soil Health and Resilience Through Bio-Inoculants and Bioremediation
No full textSoil microbes are important for maintaining agricultural ecosystems by promoting nutrient cycling, plant growth, and soil resilience. Microbial-based inoculants, such as bio-inoculants and bioremediation agents, have been identified as suitable means to promote soil health, reduce environmental deterioration, and achieve sustainable agriculture. Bio-inoculants, such as biofertilizers and biopesticides, promote nutrient availability, plant growth, and chemical input dependency reduction. Diverse microbial populations, especially plant growth-promoting bacteria (PGPB), enhance resistance by promoting a symbiotic association with plants and inducing natural resistance against insects. Bioremediation, the second significant microbial intervention, is the use of microorganisms for detoxifying and rehabilitating polluted soils. Methods effectively degrade organic pollutants, immobilize heavy metals, and mitigate the toxic effects of industrial and agricultural pollutants. Recent advances in microbial ecology and biotechnology, such as metagenomics, have transformed the knowledge of microbial soil communities, and tailor-made microbial formulations and monitoring equipment may be developed to maximize their activity. Though promising, environmental heterogeneity, scalability, and lack of field-based evidence constrain their widespread application. Multidimensional applications of microbial solutions in agroecology are explored in this review, with a focus on their potential in maintaining soil health, crop production, and environmental sustainability. It also addresses the application of bioremediation and microbial inoculants in agroecosystems and technological innovations with future research objectives. Microbial innovation to shape the soil microbiome offers a valid tool for addressing global challenges in agriculture, food security, and ecological resilience in the context of climate change
Stochastic traffic engineering for demand uncertainty and risk-aware network revenue management
No full textStochastic traffic engineering for demand uncertainty and risk-aware network revenue management
No full textJoint pricing-network design and stochastic traffic engineering to manage demand uncertainty
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