A Review of Swarm-Based 1D/2D Signal Processing

While swarming behavior, widely encountered in nature, has recently sparked numerous models and interest in domains as optimization, data clustering, and control, their application to signal processing remains sporadic. In this paper I provide a unitary treatment and a review of former results obtained in signal filtering and enhancement using swarms. General equations are presented for these procedures and stability issues are considered, with examples. The paper overviews several swarming model I introduced in previous papers and provides new evidence of the applicability of these models in signal processing. In all the models for 1D signal processing, the key idea is that the swarm hunts a prey that impersonates the filtered signal. In the 2D models, the signal (image) represents the “landscape” over which the swarm moves at a distance, while the swarm interacts with the signal (landscape). I provide and discuss details of the underlying theory of the models for processing time-domain signals and images. While this paper partly follows and summarizes previous papers, it nevertheless includes supplementary theoretical and algorithmic considerations and new results for both 1D and 2D signal processing. Although following either biological models or physical models in swarm algorithms is not generally accepted for technical applications, we prefer to emphasize the analogies established by our biomimetic approach with these two groups of models

Approach to the Adult Acute Lymphoblastic Leukemia Patient

During recent decades, understanding of the molecular mechanisms of acute lymphoblastic leukemia (ALL) has improved considerably, resulting in better risk stratification of patients and increased survival rates. Age, white blood cell count (WBC), and specific genetic abnormalities are the most important factors that define risk groups for ALL. State-of-the-art diagnosis of ALL requires cytological and cytogenetical analyses, as well as flow cytometry and high-throughput sequencing assays. An important aspect in the diagnostic characterization of patients with ALL is the identification of the Philadelphia (Ph) chromosome, which warrants the addition of tyrosine kinase inhibitors (TKI) to the chemotherapy backbone. Data that support the benefit of hematopoietic stem cell transplantation (HSCT) in high risk patient subsets or in late relapse patients are still questioned and have yet to be determined conclusive. This article presents the newly published data in ALL workup and treatment, putting it into perspective for the attending physician in hematology and oncology