USING PROBABILISTIC GRAPHICAL MODELS TO DRAW INFERENCES IN SENSOR NETWORKS WITH TRACKING APPLICATIONS

Sensor networks have been an active research area in the past decade due to the variety of their applications. Many research studies have been conducted to solve the problems underlying the middleware services of sensor networks, such as self-deployment, self-localization, and synchronization. With the provided middleware services, sensor networks have grown into a mature technology to be used as a detection and surveillance paradigm for many real-world applications. The individual sensors are small in size. Thus, they can be deployed in areas with limited space to make unobstructed measurements in locations where the traditional centralized systems would have trouble to reach. However, there are a few physical limitations to sensor networks, which can prevent sensors from performing at their maximum potential. Individual sensors have limited power supply, the wireless band can get very cluttered when multiple sensors try to transmit at the same time. Furthermore, the individual sensors have limited communication range, so the network may not have a 1-hop communication topology and routing can be a problem in many cases. Carefully designed algorithms can alleviate the physical limitations of sensor networks, and allow them to be utilized to their full potential. Graphical models are an intuitive choice for designing sensor network algorithms. This thesis focuses on a classic application in sensor networks, detecting and tracking of targets. It develops feasible inference techniques for sensor networks using statistical graphical model inference, binary sensor detection, events isolation and dynamic clustering. The main strategy is to use only binary data for rough global inferences, and then dynamically form small scale clusters around the target for detailed computations. This framework is then extended to network topology manipulation, so that the framework developed can be applied to tracking in different network topology settings. Finally the system was tested in both simulation and real-world environments. The simulations were performed on various network topologies, from regularly distributed networks to randomly distributed networks. The results show that the algorithm performs well in randomly distributed networks, and hence requires minimum deployment effort. The experiments were carried out in both corridor and open space settings. A in-home falling detection system was simulated with real-world settings, it was setup with 30 bumblebee radars and 30 ultrasonic sensors driven by TI EZ430-RF2500 boards scanning a typical 800 sqft apartment. Bumblebee radars are calibrated to detect the falling of human body, and the two-tier tracking algorithm is used on the ultrasonic sensors to track the location of the elderly people.

Effects of a 6-Week Jump Training Program Combined with Two Lifting Programs

We evaluated the effects of a 6-week jump training program on 12 college basketball players using strength training programs. The Leg Press (LP) group participated in a strength program using the leg press, and the Power Clean group (PC) used the power clean exercise instead of the leg press. Both groups participated in a 6-week jump training program. Pre-program measurements recorded jump scores for one-foot take off and two-foot take offs. The LP group had an average pre-program vertical of 72.60 and 88.05 cm for the 2-foot and 1-foot take-off for an increase of about 1.7 cm. The PC group had an average post-program vertical of 76.2 cm for the 2-foot take-off for an increase of 3.6 cm, and 90.81 cm for the 1-foot take-off for an increase of about 2.75 cm. The comparison of average increases between the LP and PC groups was not significant for either the 2-foot or 1-foot take off.

BETASCAN: probable beta-amyloids identified by pairwise probabilistic analysis

Amyloids and prion proteins are clinically and biologically important beta-structures, whose supersecondary structures are difficult to determine by standard experimental or computational means. In addition, significant conformational heterogeneity is known or suspected to exist in many amyloid fibrils. Recent work has indicated the utility of pairwise probabilistic statistics in beta-structure prediction. We develop here a new strategy for beta-structure prediction, emphasizing the determination of beta-strands and pairs of beta-strands as fundamental units of beta-structure. Our program, BETASCAN, calculates likelihood scores for potential beta-strands and strand-pairs based on correlations observed in parallel beta-sheets. The program then determines the strands and pairs with the greatest local likelihood for all of the sequence's potential beta-structures. BETASCAN suggests multiple alternate folding patterns and assigns relative a priori probabilities based solely on amino acid sequence, probability tables, and pre-chosen parameters. The algorithm compares favorably with the results of previous algorithms (BETAPRO, PASTA, SALSA, TANGO, and Zyggregator) in beta-structure prediction and amyloid propensity prediction. Accurate prediction is demonstrated for experimentally determined amyloid beta-structures, for a set of known beta-aggregates, and for the parallel beta-strands of beta-helices, amyloid-like globular proteins. BETASCAN is able both to detect beta-strands with higher sensitivity and to detect the edges of beta-strands in a richly beta-like sequence. For two proteins (Abeta and Het-s), there exist multiple sets of experimental data implying contradictory structures; BETASCAN is able to detect each competing structure as a potential structure variant. The ability to correlate multiple alternate beta-structures to experiment opens the possibility of computational investigation of prion strains and structural heterogeneity of amyloid. BETASCAN is publicly accessible on the Web at http://betascan.csail.mit.edu.

Tuberculosis in antiretroviral treatment programs in lower income countries: availability and use of diagnostics and screening

OBJECTIVES In resource-constrained settings, tuberculosis (TB) is a common opportunistic infection and cause of death in HIV-infected persons. TB may be present at the start of antiretroviral therapy (ART), but it is often under-diagnosed. We describe approaches to TB diagnosis and screening of TB in ART programs in low- and middle-income countries. METHODS AND FINDINGS We surveyed ART programs treating HIV-infected adults in sub-Saharan Africa, Asia and Latin America in 2012 using online questionnaires to collect program-level and patient-level data. Forty-seven sites from 26 countries participated. Patient-level data were collected on 987 adult TB patients from 40 sites (median age 34.7 years; 54% female). Sputum smear microscopy and chest radiograph were available in 47 (100%) sites, TB culture in 44 (94%), and Xpert MTB/RIF in 23 (49%). Xpert MTB/RIF was rarely available in Central Africa and South America. In sites with access to these diagnostics, microscopy was used in 745 (76%) patients diagnosed with TB, culture in 220 (24%), and chest X-ray in 688 (70%) patients. When free of charge culture was done in 27% of patients, compared to 21% when there was a fee (p = 0.033). Corresponding percentages for Xpert MTB/RIF were 26% and 15% of patients (p = 0.001). Screening practices for active disease before starting ART included symptom screening (46 sites, 98%), chest X-ray (38, 81%), sputum microscopy (37, 79%), culture (16, 34%), and Xpert MTB/RIF (5, 11%). CONCLUSIONS Mycobacterial culture was infrequently used despite its availability at most sites, while Xpert MTB/RIF was not generally available. Use of available diagnostics was higher when offered free of charge.

NodePM: A Remote Monitoring Alert System for Energy Consumption Using Probabilistic Techniques

In this paper, we propose an intelligent method, named the Novelty Detection Power Meter (NodePM), to detect novelties in electronic equipment monitored by a smart grid. Considering the entropy of each device monitored, which is calculated based on a Markov chain model, the proposed method identifies novelties through a machine learning algorithm. To this end, the NodePM is integrated into a platform for the remote monitoring of energy consumption, which consists of a wireless sensors network (WSN). It thus should be stressed that the experiments were conducted in real environments different from many related works, which are evaluated in simulated environments. In this sense, the results show that the NodePM reduces by 13.7% the power consumption of the equipment we monitored. In addition, the NodePM provides better efficiency to detect novelties when compared to an approach from the literature, surpassing it in different scenarios in all evaluations that were carried out.

The Effect on Meat Quality of Integrating Pasturing Systems into Cattle Finishing Programs

The effect on meat quality of integrating pasturing systems into cattle finishing programs was observed over a two-year period. Year one consisted of 84 fall born calves and 28 spring born calves and year two consisted of 116 fall born calves. The effect of using Rumensinâ for cattle on bromegrass pasture was incorporated into year one. In year two cattle on pasture received bromegrass pasture, and one treatment group received switchgrass during the warm season. In both years there was a control group of calves that went directly to the feedlot with the remaining calves going to pasture for varying periods of time before being finished in drylot. At the conclusion of the feeding trial, cattle were processed into beef, and a ribeye steak was removed from each carcass for sensory evaluation. In year one cattle that were on pasture the longest had the lowest (P<0.05) average quality grades. In year two this trend was reversed, and cattle placed directly into drylot had the lowest (P<0.05) average quality grades. In both years cattle carcasses in all treatments averaged yield grade 2. Warner Bratzler shear force values were not affected by treatments. Sensory panel evaluations indicated tenderness was unaffected by treatments, and in year two flavor and flavor intensity were unaffected by treatments. In year one flavor intensity was lowest (P<0.05) for steaks derived from cattle that were on pasture the longest and received Rumensinâ. Inclusion of Rumensinâ for cattle on pasture did not influence yield and quality grades or affect tenderness, juiciness, and flavor. Results of this study indicate that steer calves placed on cool and warm season pastures prior to being finished in drylot, can produce carcasses with acceptable yield and quality grades and that the meat eating qualities will be largely unaffected by the inclusion of pasture.

Integration of Pasturing Systems for Cattle Finishing Programs

A 3-year study, using 84 fall-born and 28 spring-born calves of similar genotypes, was conducted to integrate pasturing systems with drylot feeding systems. Calves were started on test following weaning in May and October. Seven treatments were imposed: 1) fall-born calves directly into feedlot; 2 and 3) fall-born calves put on pasture with or without ionophore and moved to the feedlot at the end of July; 4 and 5) fall-born calves put on pasture with or without ionophore and moved to the feedlot at the end of October; 6 and 7) spring-born calves put on pasture with or without ionophore and moved to the feedlot at the end of October. A bromegrass pasture consisting of 16 paddocks, each 1.7 acre in size, was available. Each treatment group had access to 1 paddock at a time and was rotated at approximately 3-day intervals. In the feedlot, steers were provided an 82% concentrate diet containing whole-shelled corn, ground alfalfa hay, and a protein, vitamin and mineral supplement containing ionophore and molasses. As pens of cattle reached about 1150 lb. average live weight, they were processed and carcass traits were evaluated. Pasture daily gains were highest for cattle on pasture for the longest duration (P < .03), and overall daily gains were highest for drylot cattle (P < .01) and decreased with increased time spent on pasture. Although differences among treatments existed in numerical scores for yield and quality grades (P < .05 and P < .03, respectively), all treatments provided average yield grade scores of 2 and quality grades of low Choice or higher. Use of four production costs and pricing scenarios revealed that fall-born calves placed on pasture for varying lengths of time were the most profitable (P < .04) among the treatments. Furthermore, employing a 5% price sensitivity analysis, indicated that fed-cattle selling price had great impact on profit potential and was followed in importance by feeder purchase price and corn grain price. Overall, these findings should provide significant production alternatives for some segments of the cattle feeding industry and also lend substantial credence to the concept of sustainable agriculture.

Integration of Pasturing Systems for Cattle Finishing Programs: A Progress Report

A three-year study was conducted to integrate pasturing systems with drylot feeding systems. Each year 84 fall-born and 28 spring-born calves of similar genotypes were used. Fall-born calves were started on test in May, and spring-born calves were started in October. Seven treatments were imposed: 1) fall-born calves directly into the feedlot (28 steers); 2 and 3) fall-born calves put on pasture with or without an ionophore and moved to the feedlot at the end of July (14 steers in each treatment); 4 and 5) fall-born calves put on pasture with or without an ionophore and moved to the feedlot at the end of October (14 steers in each treatment); and 6 and 7) spring-born calves put on pasture with or without an ionophore and moved to the feedlot at the end of October (14 steers in each treatment). Cattle on pasture receiving an ionophore gained faster (P=.009), but lost this advantage in drylot (P>.10). Overall, cattle started directly in the feedlot had higher gains (P<.001). Cattle receiving an ionophore on pasture had lower KPH than those that did not receive an ionophore (P<.01). Treatment influenced yield grade (P<0.001), although all treatments were YG 2. The percentage of cattle grading Prime and Choice was 75 % or higher for all treatment groups. The results show that using an ionophore improved pasture gains and that pasture treatments did not adversely influence yield and quality grades.