With big data analytics comes big insights into profitability Big data is big business. But having the data and the computational power to process it isn't nearly enough to produce meaningful ...results. Big Data, Data Mining, and Machine Learning: Value Creation for Business Leaders and Practitioners is a complete resource for technology and marketing executives looking to cut through the hype and produce real results that hit the bottom line. Providing an engaging, thorough overview of the current state of big data analytics and the growing trend toward high performance computing architectures, the book is a detail-driven look into how big data analytics can be leveraged to foster positive change and drive efficiency. With continued exponential growth in data and ever more competitive markets, businesses must adapt quickly to gain every competitive advantage available. Big data analytics can serve as the linchpin for initiatives that drive business, but only if the underlying technology and analysis is fully understood and appreciated by engaged stakeholders. This book provides a view into the topic that executives, managers, and practitioners require, and includes: * A complete overview of big data and its notable characteristics * Details on high performance computing architectures for analytics, massively parallel processing (MPP), and in-memory databases * Comprehensive coverage of data mining, text analytics, and machine learning algorithms * A discussion of explanatory and predictive modeling, and how they can be applied to decision-making processes Big Data, Data Mining, and Machine Learning provides technology and marketing executives with the complete resource that has been notably absent from the veritable libraries of published books on the topic. Take control of your organization's big data analytics to produce real results with a resource that is comprehensive in scope and light on hyperbole.
Fully automated decoding of human activities and intentions from direct neural recordings is a tantalizing challenge in brain-computer interfacing. Implementing Brain Computer Interfaces (BCIs) ...outside carefully controlled experiments in laboratory settings requires adaptive and scalable strategies with minimal supervision. Here we describe an unsupervised approach to decoding neural states from naturalistic human brain recordings. We analyzed continuous, long-term electrocorticography (ECoG) data recorded over many days from the brain of subjects in a hospital room, with simultaneous audio and video recordings. We discovered coherent clusters in high-dimensional ECoG recordings using hierarchical clustering and automatically annotated them using speech and movement labels extracted from audio and video. To our knowledge, this represents the first time techniques from computer vision and speech processing have been used for natural ECoG decoding. Interpretable behaviors were decoded from ECoG data, including moving, speaking and resting; the results were assessed by comparison with manual annotation. Discovered clusters were projected back onto the brain revealing features consistent with known functional areas, opening the door to automated functional brain mapping in natural settings.
The adaptive immune system generates a remarkable range of antigen-specific T-cell receptors (TCRs), allowing the recognition of a diverse set of antigens. Most of this diversity is encoded in the ...complementarity determining region 3 (CDR3) of the β chain of the αβ TCR, which is generated by somatic recombination of noncontiguous variable (V), diversity (D), and joining (J) gene segments. Deletion and non-templated insertion of nucleotides at the D-J and V-DJ junctions further increases diversity. Many of these gene segments are annotated as non-functional owing to defects in their primary sequence, the absence of motifs necessary for rearrangement, or chromosomal locations outside the TCR locus.
We sought to utilize a novel method, based on high-throughput sequencing of rearranged TCR genes in a large cohort of individuals, to evaluate the use of functional and non-functional alleles. We amplified and sequenced genomic DNA from the peripheral blood of 587 healthy volunteers using a multiplexed polymerase chain reaction assay that targets the variable region of the rearranged TCRβ locus, and we determined the presence and the proportion of productive rearrangements for each TCRβ V gene segment in each individual. We then used this information to annotate the functional status of TCRβ V gene segments in this cohort.
For most TCRβ V gene segments, our method agrees with previously reported functional annotations. However, we identified novel non-functional alleles for several gene segments, some of which were used exclusively in our cohort to the detriment of reported functional alleles. We also saw that some gene segments reported to have both functional and non-functional alleles consistently behaved in our cohort as either functional or non-functional, suggesting that some reported alleles were not present in the population studied.
In this proof-of-principle study, we used high-throughput sequencing of the TCRβ locus of a large cohort of healthy volunteers to evaluate the use of functional and non-functional alleles of individual TCRβ V gene segments. With some modifications, our method has the potential to be extended to gene segments in the α, γ, and δ TCR loci, as well as the genes encoding for B-cell receptor chains.
The purpose of this mixed methods study was to understand how adjunct nursing faculty integrate their pedagogical professional development (PD) experiences to develop identity salience as an ...educator, and understand how PD affects their perceptions of commitment, satisfaction, and time spent in the adjunct role. Administrators of nursing programs can use the results as evidence of the importance of providing PD to their adjunct faculty. Ten adjunct nursing faculty who participated in PD were interviewed using phenomenological qualitative methods comprised of interviewing and gathering field notes. The themes emerging from the interview revealed that ongoing PD fosters a teaching identity, reduces adjunct isolation, and leads to higher satisfaction through peer mentoring. The results also showed that a lack of PD lead to a reduced commitment to the adjunct role. In addition, quantitative data were gathered through the distribution of the Adjunct Faculty Identity Salience Survey (AFISS). The AFISS required the participants to answer 68 questions related to how PD affects their role as an adjunct. The data were analyzed using descriptive statistics, crosstabs, correlations, and exploratory factor analysis (EFA). The results generated from the AFISS supported the qualitative findings that pedagogical PD does contribute to salience as an educator. The EFA revealed the extent of the relationship that PD had on the independent variables. A positive, statistically significant relationship was revealed between PD and identity salience, commitment, time spent in the adjunct role, and satisfaction. Professional development had a stronger relationship with identity salience (r = .560), commitment (r = .535) and time spent in the adjunct role (r = .665) than it did on satisfaction (r = .123). The results can be incorporated by nursing programs utilizing adjunct nursing faculty as evidence to support that pedagogical PD does lead to salience as an educator and higher levels of adjunct commitment, satisfaction, and time spend in the role as an adjunct.
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