μblog: engineering from the trenches

I am going to the BioMEMS Gordon Research Conference for a week, then moving up to State College, so I will be writing even less useful posts in the next two weeks. In other news, I pretty much finished packing my house and as well as the lab.

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Sometime in the 1950’s, the term Receiver Operating Characteristic curve was coined. The original purpose for this mathematical device was to determine how effective a receiver was in identifying symbols in a transmission stream, however, in recent decades the popularity of this device has grown beyond the radio communication field. In any kind of situation where there is data analysis to be performed and a binary result to be computed, the ROC curve can be used to determine both the efficiency of the detection algorithm as well as parameter optimization. Looking at the graph above, we can replace sensitivity with true positive detection rate and 1 – specificity as the false positive detection rate. It is clear that the green line represents a random guess detector, where the probability of picking a true positive and a false positive is the same. The blue line is then the curve of some detection algorithm, since the area under the green curve is greater than ½, we can say that the algorithm generally performs better than a random guess algorithm. To generate such a curve with variable detector parameters, we vary the parameters and re-run the detection on some gold-standard data set to get each point on the curve, where each point on the curve is the statistical information generated from a certain set of detector parameters. With this information, we can not only determine the general performance of the algorithm, but also find the point on the curve that gives us the highest sensitivity and the highest specificity, that is, the point that is geometrically closest to the top left corner of the curve. With this point in hand, we can extract the parameters used to generate this point and use them as the optimal detector settings.

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When we are faced with the problem of system identification, it is convenient to determine the transfer function, or impulse response, of a system in order to generate a working model. Since at this stage of analysis, the system is almost a black-box, we cannot make too many assumptions about the transfer function beyond what can be determined from the input and output time series. All hope is not lost, however, since there exist formidable methods of transfer function estimation. (more…)

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My advisor is working on a grant renewal, so I wrote a little piece to fit in somewhere. Not much, but might be interesting to read.

( instrumentation-amp-comparison.pdf )

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With so many magnetic cards in our wallets/money clips/purses, some times we wonder what information is exactly stored there. The first step is to determine which card standard needs to be decoded. The popular formats are ISO1, ISO2 and ISO3 which are the magnetic stripes 5.5mm, 9mm and 12.5mm from the card edge respectively. Next, a card reader must be obtained. It is possible to construct your own reader by using cassette tape heads, however, card readers are readily on both Ebay and Digikey for reasonable prices ($5-$40). Most cards have either ISO1 or ISO2 data which features some padding that determines the scan direction. Having said that, readers are available that support multiple ISO formats on the same device. With These devices generally offer three control lines (per track): card present, data, and clock. The card present is good for interrupt control and the other two are for standard data retrieval. With this information and a reader, the information can be readily extracted and processed, however, there also exist expensive magnetic particles suspended in liquid solvent that will allow visual inspection of the magnetic data without the need for a reader.

( DG60A166 _ZU-M1242S1_.pdf )

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If you have an Nvidia Personal Cinema (NvRemote?) or ATI all-in-wonder RF to usb remote control, or any other similar RF remote control based on the X10 RF to usb transciever, they are all made with a similar chipset and therefore are mostly supported by the same driver. Since the transciever is USB based, it is often helpful to use them on machines separate from the cards they are bundled with, but its hard to find the driver. After long searching, I have finally found a generic driver that will support most of the functionality of most of these remotes (mine is the NvRemote from an eVGA Nvidia Personal Cinema). The company is Niveus and the remote homepage is here.

( Niveus_PC_Remote_Software.zip )

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When having the responsibility of monitoring a network and periodically auditing it to look for places of improvement, there are two major kinds of unauthorized network access that make your job harder: pirated data transfers and infected/zombie machines. In this small segment, I will focus only on part of the pirated data transfers category. Most university networks have some amount of background bittorrent traffic which can be somewhat managed due to the requirement of an open port for optimal efficiency. The bigger problem arises when a staff member or student with privileged network access decides to run a large dumpsite on your edu/Internet2 connection. With many network-intensive research applications running, it is sometimes hard to tell what is legitimate traffic and what is illegal transit. Furthermore, many dumpsite/topsite operators have gotten clever and implemented encryption and command channel bounces on their ftp servers along with access lists and so forth, which has all made it more difficult for the network admin to distinguish legitimate network access from pirated traffic. What I propose is a method of using mathematical analysis to give an indication of dumpsite/topsite presence by sniffing encrypted traffic. (more…)

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Finally, the new edition of the field controller has been put to use. I have been working with J. Ziburkus to try to modulate neural activity by polarizing pyramidal neurons (in slices) with electric fields as specified in the papers by B. Gluckman (see below). The basic idea is that these neurons in the hippocampus are shaped like elongated pyramids, where most of the cells are oriented in the same direction. This means that with an applied electric field, the distribution of ions inside the cell can be changed by a function of electric field, cell morphology and orientation. Since it is commonly believed that the part of the cell that determines if an action potential is to be fired is the axon hillock, located between the axon and the cell body, changes in ion gradients in that area will make the cell more or less excitable. Because of the favorable cell orientation in this part of the hippocampus, we can cause the same change in excitation levels in many cells at the same time, and thereby study the effects of various channel altering drugs at different excitation levels.

Some relevant Gluckman papers:

A model of the effects of applied electric fields on neuronal synchronization. J Comput Neurosci. 2005 Aug;19(1):53-70.

Sensitivity of neurons to weak electric fields. J Neurosci. 2003 Aug 13;23(19):7255-61.

Adaptive electric field control of epileptic seizures. J Neurosci. 2001 Jan 15;21(2):590-600.

(If you are interested in these papers but cannot access them, email me and we can work it out.)

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