Assignment 2: State of CS Research and Variety of Technical Topics

We had a new assignment in CS research. It asked us to find any article/information and examine the state of CS research. Also, discuss the variety of technical topics. So I look for CS research papers and found an article that interest me. It's a study from Stanford University, the article was entitled BioAct!

In compliance of the assignment here is my article regarding the BioAct of Stanford students who won awards: Best Student Paper award at JCDL 2006 and Brian Shackel Award at Interact 2005.

The students of Stanford University conducted a study, BioAct, to help biodiversity researchers for three purposes:

1) To Acquire – to help in acquiring digital materials in the field,

2) To Curate – to help in managing these online holdings, and

3) To Transfer (or disseminate) – to help transfer the knowledge to other researchers, museums, and the public [1].

Due to the increasing diversity of data to be gathered it is a great challenge in identifying and cataloging the data. Therefore, the proponents’ created three sets of tools: (1) Tools for speedy data entry and small-group collaboration in the field, (2) Tools for large scale collaboration in distributed collection curation, and (3) Tools for semi-directed search and browsing of digital biodiversity materials [1].

The study is favorable since the study utilized the technology in gathering and maintaining the collections of the biodiversity documents around the globe, and to educate students and the public about the aspects of natural history.

From what I read and understand about BioAct the variety of technical topics that are discussed are bioinformatics and computational biology which involves the use of techniques including applied mathematics, informatics, statistics, computer science, artificial intelligence, chemistry, and biochemistry to solve biological problems usually on the molecular level [2].

References:

1. BioAct! http://i.stanford.edu/bioact/
2. BioInformatics and Computational biology. http://en.wikipedia.org/wiki/Bioinformatics
3. Video of PhotoSpread. http://www.youtube.com/watch?v=rf7rA-roBlM

Reports: Three Scientific Papers

Haptic Guidance Improves the Visou-Manual Tracking of Trajectories

The proponents of this study found out that “the addition of haptic information, probably encoded in force coordinates, plays a crucial role on the visou-manual tracking of new trajectories” [1].

The achievement in performing new movements is learned through visual demonstrations. The proponents’ evaluated three training techniques of haptic guidance, the HGP (Haptic Guidance in Position), HGF (Haptic Guidance in Force, and NHG (without Haptic Guidance). They conducted an assessment in the dynamic time warping (shape matching), number of velocity peaks, and mean velocity before and after the training session to examine if there is an improvement in the performance.

Using the PHANToM™ Omni device (Sensible Technology) which serves as a pen and a simple flat screen, as a paper they performed their two experiments where experiment 1 consist of two Arabic and two Japanese-inspired letters while experiment 2 consist of ellipses. And thus gave them a result that HGF improves the fluency of the visou-manual tracking of trajectories while there is no significant improvement was found for HGP/NHG.

Citations:
1. http://www.plosone.org/article/info:doi/10.1371/journal.pone.0001775



Antibiotic Innovation May Contribute to Slowing the Dissemination of Multiresistant Streptococcus pneumoniae: The Example of Ketolides

Ketolides, as defined in Wikipedia, are antibiotics belonging to the macrolide group. Ketolides are derived from erythromycin by substituting the cladinose sugar with a keto-group and attaching a cyclic carbamate group in the lactone ring [3]. In addition, it constitutes one of the very few new antibiotic classes active against Streptococcus pneumoniae developed during the last 25 years. Their mechanism of action resembles that of macrolides, but they are unaffected by common resistance mechanisms [2]. Streptococcus pneumoniae bacterium is the most common cause of bacterial pneumonia. It is also called as pneumococcus, which usually causes lobar pneumonia attacking an entire lobe or portion of a lobe of the lung [1].

In this study the proponents’ objective is to assess the potential dissemination of newly emerged resistance and to control the selection of strains that already multiresistant to existing antimicrobials. By taking an account to 3 different classes (P: penicillin, M: macrolides and K: ketolides), and PCV7. In their experiment, the population was divided into groups according to their age, vaccination status, colonization and antibiotic exposure.

The results of the study could foretell that “in a population with widespread use of PCV7 and rational use of antibiotics, antibiotic innovation that are prescribed to all age groups could have an added impact on multiresistance rates. The more the new drug is prescribed, the slower the multiresistance would diffuse however, the more this new drug is used the faster new mutliresistant pneumococcal strains would be selected” [2].

Citations:
1. http://encarta.msn.com/encyclopedia_761576059/Pneumonia.html#p14
2. http://www.plosone.org/article/info:doi/10.1371/journal.pone.0002089
3. http://en.wikipedia.org/wiki/Ketolides



Global Considerations in Hierarchical Clustering Reveal Meaningful Patterns in Data

“Clustering is a common unsupervised machine learning procedure, often used for preprocessing, and usually provides a general overview, especially when dealing with large databases. It is classified as non-hierarchical (partitioning) or hierarchical. Hierarchy is a tree-like relationship and is a natural method of organizing data in various domains” [1].

In this study the proponents’ objective is to examine the advantages of involving global approaches in clustering and demonstrates that they can generate meaningful results near the top of the hierarchy. Using three assessment methods were used to find these advantages; node score, level score, and tree score. The methods used will assess the advantages of different algorithms, TDQC (Top-down Quantum Clustering), BU (Bottom-up), TU (Top-down), and Glocal (Global-local).

The proponents’ find out that “although currently rarely used, global approches, in particular, TD or Glocal algorithms, should be considered in the exploratory process of clustering. In general, applying unsupervised clustering methods can leverage the quality of manually-created mapping proteins families. And that it can also provide insights in erroneous and missed annotations” [1].

Citations:
1. http://www.plosone.org/article/info:doi/10.1371/journal.pone.0002247