Iterative algorithms are simple yet efficient in solving large-scale optimization problems in practice. With a surge in the amount of data in past decades, these methods have become increasingly important in many application areas including matrix/tensor recovery, deep learning, data mining, and reinforcement learning. To optimize or improve iterative algorithms,...
Unlike the North and the South where abundance of freshwater, the marine capture fisheries is underdeveloped, the Central Coast, especially South Central Coast with little freshwater fisheries resources, but high amount of shrimps, fishes at sea, thus local fishermen have exploited this resource for living early. Together with this living...
The global demand for food is expected to double by 2050, presenting a need that is complicated by the many interrelated of pressures on the world’s natural resources from climate change, growing urban populations, and increasing development. As one of the fastest growing food production sectors, aquaculture is poised to...
Reconciling conservation and livelihoods is a concern wherever forests are important in local people’s lives. We plead for engaging these people in survey activities to clarify what is important to them, as a first step in conservation planning. This will help to address their priorities and gain their guidance and...
The Discrete Cosine Transform is used in many image and video compression
standards. Many methods have been developed for efficiently computing the Discrete
Cosine Transform including flowgraph algorithms, distributed arithmetic and
two-dimensional decompositions.
A new architecture based on distributed arithmetic is presented for computing
the Discrete Cosine Transform and it's...
Soil nitrogen exists largely as organic matter, including plant liter, dead animal matter, and microbial necromass. About 90% of soil organic nitrogen is proteinaceous material that is too large for plants and microorganisms to assimilate directly. Protein depolymerization therefore plays a critical role in mobilizing this organic source of nitrogen,...
Efficient time-series analysis can impact multiple application domains such as motif discovery in gene analysis or music data, extracting spectro-temporal patterns in acoustic scene analysis, or annotating and classifying electrical bio-signals (such as ECG, EEG, and EMG) for medical applications.
Time-series analysis involves a variety of tasks.
To predict future...
In weak supervision learning, label information can be provided at different levels of granularity. For example, in multi-instance multi-label learning, samples are organized into bags and labels for each class are provided at the bag level. For small datasets, this approach offers means of reducing the labeling efforts. However, in...