Monitoring-Based Commissioning: Tracking the Evolution and Adoption of a Paradigm-Shifting Approach to Retro-Commissioning

Proceedings of the 2012 ACEEE Summer Study (Panel 4, Paper 1130). Monitoring-based commissioning (MBCx) emphasizes permanent energy performance metering and trending—for diagnosis of energy waste, for savings accounting, and to enable persistence of savings. Emphasis on monitoring represents a paradigm shift for the retro-commissioning (RCx) industry, which has traditionally relied upon test protocols and modeled savings estimates. Since 2004, a major monitoring-based commissioning program at twenty-five California university campuses has evolved to meet the changing needs of university and utility partners. More recently the monitoring-based approach has been adopted by third-party programs in California. We present information on the progression of program design and results for the multiple phases of the original program, along with a look at third-party and other programs adopting similar program features

Cross Layer Aware Adaptive MAC based on Knowledge Based Reasoning for Cognitive Radio Computer Networks

In this paper we are proposing a new concept in MAC layer protocol design for Cognitive radio by combining information held by physical layer and MAC layer with analytical engine based on knowledge based reasoning approach. In the proposed system a cross layer information regarding signal to interference and noise ratio (SINR) and received power are analyzed with help of knowledge based reasoning system to determine minimum power to transmit and size of contention window, to minimize backoff, collision, save power and drop packets. The performance analysis of the proposed protocol indicates improvement in power saving, lowering backoff and significant decrease in number of drop packets. The simulation environment was implement using OMNET++ discrete simulation tool with Mobilty framework and MiXiM simulation library.Comment: 8 page

Measuring Use of Resourcefulness Skills: Psychometric Testing of a New Scale

Highly resourceful individuals have been found better able to meet life\u27s challenges and to experience more positive health outcomes. Although psychometrically sound measures of resourcefulness exist and resourcefulness training trials show that the intervention increases adaptive functioning and enhances quality of life, there is no direct measure of intervention fidelity. This study examined the reliability and validity of an 8-item Resourcefulness Skills Scale (RSS), which measures the frequency with which intervention recipients use specific resourcefulness skills. The RSS was found to have acceptable internal consistency (� = .78), criterion-related validity (�\u27s = .50 and .52 with other resourcefulness scales), and construct validity (�\u27s =.38 and .53 with theoretically-related constructs). Factor analysis revealed two factors reflecting personal and social resourcefulness. Because the RSS queries respondents on their use of skills taught during resourcefulness training, it has potential usefulness as a measure for evaluating how well the training is translated into use of the skills in daily life

Southern California fisheries monitoring summary for 1993 and 1994

The southern California Monitoring and Management Units collectively gathered 803 discrete samples of 7,329 marine finfishes and invertebrates from local commercial fish markets or authorized fish transporters in 1993. Nineteen different species were sampled and biological information recorded for future summarization and use in formulating fisheries management strategies and decisions. Increased sampling efforts in 1994 resulted in 801 samples of 14,566 marine finfish and invertebrates representing 44 different species. Fisheries trends and threats to local fishing opportunities were identified. Results of Marine Recreational Fishery Statistics Survey interviews were also incorporated for a more complete overview of species targeted by both the sport and commercial industries. (26pp.

Randomized Benchmarking of Multi-Qubit Gates

As experimental platforms for quantum information processing continue to mature, characterization of the quality of unitary gates that can be applied to their quantum bits (qubits) becomes essential. Eventually, the quality must be sufficiently high to support arbitrarily long quantum computations. Randomized benchmarking already provides a platform-independent method for assessing the quality of one-qubit rotations. Here we describe an extension of this method to multi-qubit gates. We provide a platform-independent protocol for evaluating the performance of experimental Clifford unitaries, which form the basis of fault-tolerant quantum computing. We implemented the benchmarking protocol with trapped-ion two-qubit phase gates and one-qubit gates and found an error per random two-qubit Clifford unitary of $0.162 \pm 0.008$, thus setting the first benchmark for such unitaries. By implementing a second set of sequences with an extra two-qubit phase gate at each step, we extracted an error per phase gate of $0.069 \pm 0.017$. We conducted these experiments with movable, sympathetically cooled ions in a multi-zone Paul trap - a system that can in principle be scaled to larger numbers of ions.Comment: Corrected description of parallel single-qubit benchmark experiment. Results unchange

Principles in Patterns (PiP) : Heuristic Evaluation of Course and Class Approval Online Pilot (C-CAP)

The PiP Evaluation Plan documents four distinct evaluative strands, the first of which entails an evaluation of the PiP system pilot (WP7:37). Phase 1 of this evaluative strand focuses on the heuristic evaluation of the PiP Course and Class Approval Online Pilot system (C-CAP). Heuristic evaluation is an established usability inspection and testing technique and is most commonly deployed in Human-Computer Interaction (HCI) research, e.g. to test user interface designs, technology systems testing, etc. The success of heuristic evaluation in detecting 'major' and 'minor' usability problems is well documented, but its principal limitation is its inability to capture data on all possible usability problems. For this reason heuristic evaluation is often used as a precursor to user testing, e.g. so that user testing focuses on deeper system issues rather than on those that can easily be debugged. Heuristic evaluation nevertheless remains an important usability inspection technique and research continues to demonstrate its success in detecting usability problems which would otherwise evade detection in user testing sessions. For this reason experts maintain that heuristic evaluation should be used to complement user testing. This is reflected in the PiP Evaluation Plan, which proposes protocol analysis, stimulated recall and pre- and post-test questionnaire instruments to comprise user testing (see WP7:37 phases 2, 3 and 4 of PiP Evaluation Plan). This brief report summarises the methodology deployed, presents the results of the heuristic evaluation and proposes solutions or recommendations to address the heuristic violations that were found to exist in the C-CAP system. It is anticipated that some solutions will be implemented within the lifetime of the project. This is consistent with the incremental systems design methodology that PiP has adopted

A database model for object dynamics.

Object-oriented database systems, Dynamic object re-classification, Object role model, Dynamic class hierarchy, Object migration

Deep Learning-based Prescription of Cardiac MRI Planes.

PurposeTo develop and evaluate a system to prescribe imaging planes for cardiac MRI based on deep learning (DL)-based localization of key anatomic landmarks.Materials and methodsAnnotated landmarks on 892 long-axis (LAX) and 493 short-axis (SAX) cine steady-state free precession series from cardiac MR images were retrospectively collected between February 2012 and June 2017. U-Net-based heatmap regression was used for localization of cardiac landmarks, which were used to compute cardiac MRI planes. Performance was evaluated by comparing localization distances and plane angle differences between DL predictions and ground truth. The plane angulations from DL were compared with those prescribed by the technologist at the original time of acquisition. Data were split into 80% for training and 20% for testing, and results confirmed with fivefold cross-validation.ResultsOn LAX images, DL localized the apex within mean 12.56 mm ± 19.11 (standard deviation) and the mitral valve (MV) within 7.68 mm ± 6.91. On SAX images, DL localized the aortic valve within 5.78 mm ± 5.68, MV within 5.90 mm ± 5.24, pulmonary valve within 6.55 mm ± 6.39, and tricuspid valve within 6.39 mm ± 5.89. On the basis of these localizations, average angle bias and mean error of DL-predicted imaging planes relative to ground truth annotations were as follows: SAX, -1.27° ± 6.81 and 4.93° ± 4.86; four chambers, 0.38° ± 6.45 and 5.16° ± 3.80; three chambers, 0.13° ± 12.70 and 9.02° ± 8.83; and two chamber, 0.25° ± 9.08 and 6.53° ± 6.28, respectively.ConclusionDL-based anatomic localization is a feasible strategy for planning cardiac MRI planes. This approach can produce imaging planes comparable to those defined by ground truth landmarks.© RSNA, 2019 Supplemental material is available for this article