Characterizing and Modeling Control-Plane Traffic for Mobile Core Network

In this paper, we first carry out to our knowledge the first in-depth characterization of control-plane traffic, using a real-world control-plane trace for 37,325 UEs sampled at a real-world LTE Mobile Core Network (MCN). Our analysis shows that control events exhibit significant diversity in device types and time-of-day among UEs. Second, we study whether traditional probability distributions that have been widely adopted for modeling Internet traffic can model the control-plane traffic originated from individual UEs. Our analysis shows that the inter-arrival time of the control events as well as the sojourn time in the UE states of EMM and ECM for the cellular network cannot be modeled as Poisson processes or other traditional probability distributions. We further show that the reasons that these models fail to capture the control-plane traffic are due to its higher burstiness and longer tails in the cumulative distribution than the traditional models. Third, we propose a two-level hierarchical state-machine-based traffic model for UE clusters derived from our adaptive clustering scheme based on the Semi-Markov Model to capture key characteristics of mobile network control-plane traffic -- in particular, the dependence among events generated by each UE, and the diversity in device types and time-of-day among UEs. Finally, we show how our model can be easily adjusted from LTE to 5G to support modeling 5G control-plane traffic, when the sizable control-plane trace for 5G UEs becomes available to train the adjusted model. The developed control-plane traffic generator for LTE/5G networks is open-sourced to the research community to support high-performance MCN architecture design R&D

Regularized reconstruction in quantitative SPECT using CT side information from hybrid imaging

A penalized-likelihood (PL) SPECT reconstruction method using a modified regularizer that accounts for anatomical boundary side information was implemented to achieve accurate estimates of both the total target activity and the activity distribution within targets. In both simulations and experimental I-131 phantom studies, reconstructions from (1) penalized likelihood employing CT-side information-based regularization (PL-CT), (2) penalized likelihood with edge preserving regularization (no CT) and (3) penalized likelihood with conventional spatially invariant quadratic regularization (no CT) were compared with (4) ordered subset expectation maximization (OSEM), which is the iterative algorithm conventionally used in clinics for quantitative SPECT. Evaluations included phantom studies with perfect and imperfect side information and studies with uniform and non-uniform activity distributions in the target. For targets with uniform activity, the PL-CT images and profiles were closest to the 'truth', avoided the edge offshoots evident with OSEM and minimized the blurring across boundaries evident with regularization without CT information. Apart from visual comparison, reconstruction accuracy was evaluated using the bias and standard deviation (STD) of the total target activity estimate and the root mean square error (RMSE) of the activity distribution within the target. PL-CT reconstruction reduced both bias and RMSE compared with regularization without side information. When compared with unregularized OSEM, PL-CT reduced RMSE and STD while bias was comparable. For targets with non-uniform activity, these improvements with PL-CT were observed only when the change in activity was matched by a change in the anatomical image and the corresponding inner boundary was also used to control the regularization. In summary, the present work demonstrates the potential of using CT side information to obtain improved estimates of the activity distribution in targets without sacrificing the accuracy of total target activity estimation. The method is best suited for data acquired on hybrid systems where SPECT-CT misregistration is minimized. To demonstrate clinical application, the PL reconstruction with CT-based regularization was applied to data from a patient who underwent SPECT/CT imaging for tumor dosimetry following I-131 radioimmunotherapy.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/85409/1/pmb10_9_007.pd

Quantitative autoradiographic evaluation of the influence of protein dose on monoclonal antibody distribution in human ovarian adenocarcinoma xenografts

We studied the effect of monoclonal antibody protein dose on the uniformity of radioiodinated antibody distribution within tumor masses using quantitative autoradiography. Groups ( n = 11–13/group) of athymic nude mice with subcutaneous HTB77 human ovarian carcinoma xenografts were injected intraperitoneally with an 125 I-labeled anticarcinoma-associated antigen murine monoclonal antibody, 5G6.4, using a high or a low protein dose (500 µg or 5 µg). At 6 days post-injection the macroscopic and microscopic intratumoral biodistribution of radiolabeled antibody was determined. The degree of heterogeneity of the labeled antibody distribution within each tumor was quantified and expressed as the coefficient of variation (CV) of the activity levels in serial histological sections. Tumors from mice given the 500-µg protein doses had substantially lower CV values, 0.327±0.027, than did tumors from animals given 5-µg protein doses, 0.458±0.041, ( P = 0.0078), indicating that the higher protein dose resulted in more homogeneous distribution of radioactivity in tumors than did the lower dose. While the percentage of the injected dose reaching the tumor was comparable between groups, injecting the higher dose of protein resulted in significantly lower tumor to non-tumor uptake ratios than those obtained for the lower protein dose. These data indicate, in this system, that to achieve more uniform intratumoral antibody (and radiation for radioimmunotherapy) delivery, a relatively high protein dose must be administered. However, to obtain this increased uniformity, a substantial drop in tumor/background uptake ratios was seen. Quantitative autoradiographic evaluation of human tumor xenografts is a useful method to assess the intratumoral distribution of antibodies.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/46859/1/262_2005_Article_BF01789014.pd

Fatty acid profile and proximate composition of Pacific mullet (Mugil so-iuy) caught in the Black Sea

This study demonstrates proximate composition and fatty acid profile of Pacific mullet caught in Turkey. The highest moisture and protein contents were observed with muscle tissues as 83.74 and 10.52%, while the highest fat and ash contents were attributed to female gonads as 11.80 and 0.94%, respectively, with a significant variation amongst months (P < 0.05). Significant variation (P < 0.05) usually occurred amongst months within the same sex for total saturated fatty acids (?SFA), monosaturated fatty acids (?MUFA), polyunsaturated fatty acids (?PUFA), eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) in muscle, although overall mean values between sexes were not found significant. Except for EPA, no variation observed for gonads while significant changes occurred (P < 0.05) with liver samples amongst months. Overall total values of ?SFA, ?MUFA, ?PUFA, DHA and EPA in muscle samples were 29.59, 29.26, 18.06 and 4.48%, respectively, while in gonads ranged as 30.26-33.23%, 35.17-37.47%, 11.87-14.88%, 4.38-5.34% and 3.02-5.02%. These FAs were 21.57-33.11%, 32.89-50.96%, 14.78-20.08%, 0.89-9.94% and 5.85-9.54% for liver, respectively. The results of this study showed that muscle and gonads of Pacific mullet were rich in n-3 PUFA, especially, EPA, DHA, increasing the value of this species for human consumption. © 2010 The Authors. Journal compilation © 2010 Institute of Food Science and Technology

Accuracy of 131I tumor quantification in radioimmunotherapy using SPECT imaging with an ultra-high-energy collimator: Monte Carlo study

Accuracy of 131I tumor quantification after radioimmunotherapy (RIT) was investigated for SPECT imaging with an ultra-high-energy (UHE) collimator designed for imaging 511-keV photons. METHODS: First, measurements and Monte Carlo simulations were carried out to compare the UHE collimator with a conventionally used, high-energy collimator. On the basis of this comparison, the UHE collimator was selected for this investigation, which was carried out by simulation of spherical tumors in a phantom. Reconstruction was by an expectation-maximization algorithm that included scatter and attenuation correction. Keeping the tumor activity constant, simulations were carried out to assess how volume-of-interest (VOI) counts vary with background activity, radius of rotation (ROR), tumor location, and size. The constant calibration factor for quantification was determined from VOI counts corresponding to a 3.63-cm-radius sphere of known activity. Tight VOIs corresponding to the physical size of the spheres or tumors were used. RESULTS: Use of the UHE collimator resulted in a large reduction in 131I penetration, which is especially significant in RIT where background uptake is high. With the UHE collimator, typical patient images showed an improvement in contrast. Considering the desired geometric events, sensitivity was reduced, but only by a factor of 1.6. Simulation results for a 3.63-cm-radius tumor showed that VOI counts vary with background, location, and ROR by less than 3.2%, 3%, and 5.3%, respectively. The variation with tumor size was more significant and was a function of the background. Good quantification accuracy (<6.5% error) was achieved when tumor size was the same as the sphere size used in the calibration, irrespective of the other parameters. For smaller tumors, activities were underestimated by up to -15% for the 2.88-cm-radius sphere, -23% for the 2.29-cm-radius sphere, and -47% for the 1.68-cm-radius sphere. CONCLUSION: Reasonable accuracy can be achieved for VOI quantification of 131I using SPECT with an UHE collimator and a constant calibration factor. Difference in tumor size relative to the size of the calibration sphere had the biggest effect on accuracy, and recovery coefficients are needed to improve quantification of small tumors

Characterization of scatter and penetration using Monte Carlo simulation in 131I imaging

In 131I SPECT, image quality and quantification accuracy are degraded by object scatter as well as scatter and penetration in the collimator. The characterization of energy and spatial distributions of scatter and penetration performed in this study by Monte Carlo simulation will be useful for the development and evaluation of techniques that compensate for such events in 131I imaging. METHODS: First, to test the accuracy of the Monte Carlo model, simulated and measured data were compared for both a point source and a phantom. Next, simulations to investigate scatter and penetration were performed for four geometries: point source in air, point source in a water-filled cylinder, hot sphere in a cylinder filled with nonradioactive water, and hot sphere in a cylinder filled with radioactive water. Energy spectra were separated according to order of scatter, type of interaction, and gamma-ray emission energy. A preliminary evaluation of the triple-energy window (TEW) scatter correction method was performed. RESULTS: The accuracy of the Monte Carlo model was verified by the good agreement between measured and simulated energy spectra and radial point spread functions. For a point source in air, simulations show that 73% of events in the photopeak window had either scattered in or penetrated the collimator, indicating the significance of collimator interactions. For a point source in a water-filled phantom, the separated energy spectra showed that a 20% photopeak window can be used to eliminate events that scatter more than two times in the phantom. For the hot sphere phantoms, it was shown that in the photopeak region the spectrum shape of penetration events is very similar to that of primary (no scatter and no penetration) events. For the hot sphere regions of interest, the percentage difference between true scatter counts and the TEW estimate of scatter counts was <12%. CONCLUSION: In 131I SPECT, object scatter as well as collimator scatter and penetration are significant. The TEW method provides a reasonable correction for scatter, but the similarity between the 364-keV primary and penetration energy spectra makes it difficult to compensate for these penetration events using techniques that are based on spectral analysis

Fatty acid profile and proximate composition of Pacific mullet (Mugil so-iuy) caught in the Black Sea

This study demonstrates proximate composition and fatty acid profile of Pacific mullet caught in Turkey. The highest moisture and protein contents were observed with muscle tissues as 83.74 and 10.52%, while the highest fat and ash contents were attributed to female gonads as 11.80 and 0.94%, respectively, with a significant variation amongst months (P < 0.05). Significant variation (P < 0.05) usually occurred amongst months within the same sex for total saturated fatty acids (?SFA), monosaturated fatty acids (?MUFA), polyunsaturated fatty acids (?PUFA), eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) in muscle, although overall mean values between sexes were not found significant. Except for EPA, no variation observed for gonads while significant changes occurred (P < 0.05) with liver samples amongst months. Overall total values of ?SFA, ?MUFA, ?PUFA, DHA and EPA in muscle samples were 29.59, 29.26, 18.06 and 4.48%, respectively, while in gonads ranged as 30.26-33.23%, 35.17-37.47%, 11.87-14.88%, 4.38-5.34% and 3.02-5.02%. These FAs were 21.57-33.11%, 32.89-50.96%, 14.78-20.08%, 0.89-9.94% and 5.85-9.54% for liver, respectively. The results of this study showed that muscle and gonads of Pacific mullet were rich in n-3 PUFA, especially, EPA, DHA, increasing the value of this species for human consumption. © 2010 The Authors. Journal compilation © 2010 Institute of Food Science and Technology

SNAP: Stateful network-wide abstractions for packet processing

Early programming languages for software-defined networking (SDN) were built on top of the simple match-action paradigm offered by OpenFlow 1.0. However, emerging hardware and software switches offer much more sophisticated support for persistent state in the data plane, without involving a central controller. Nevertheless, managing stateful, distributed systems efficiently and correctly is known to be one of the most challenging programming problems. To simplify this new SDN problem, we introduce SNAP. SNAP offers a simpler "centralized" stateful programming model, by allowing programmers to develop programs on top of one big switch rather than many. These programs may contain reads and writes to global, persistent arrays, and as a result, programmers can implement a broad range of applications, from stateful firewalls to fine-grained traffic monitoring. The SNAP compiler relieves programmers of having to worry about how to distribute, place, and optimize access to these stateful arrays by doing it all for them. More specifically, the compiler discovers read/write dependencies between arrays and translates one-big-switch programs into an efficient internal representation based on a novel variant of binary decision diagrams. This internal representation is used to construct a mixed-integer linear program, which jointly optimizes the placement of state and the routing of traffic across the underlying physical topology. We have implemented a prototype compiler and applied it to about 20 SNAP programs over various topologies to demonstrate our techniques' scalability