Development of a project level performance measurement model for improving collaborative design team work

This research explored a new direction of improving collaborative design by performance measurement. More specifically, a novel 3-dimensional performance measurement model is developed and the purpose of this model is to help project managers improve team collaboration by indicating strengths and weaknesses of team members during the project development process. Considering the complexity of collaborative design work, a multiple criteria model is proposed to reflect the design dynamics, which highlights five performance indicators: efficiency, effectiveness, collaboration, management skills and innovation. These five indicators are mostly influenced by role-based performance measurement criteria (the second dimension). Design and development process (time) is also considered (the third dimension). This 3D model allows all involved design participants to measure work performance at any time during the product development process. In order to develop this model, the role-based task analysis and industrial survey methods were utilized. Three groups of role-based product design and development performance measurement criteria were identified for measuring design performance of the top managers, middle managers and individual designers in a project team. A 3-dimensional performance measurement method was proposed to calculate final performance scores from a performance measurement matrix. The proposed model was evaluated as a tool which can support project managers to reduce potential design and collaboration risks and increase confidence in decision-making process. The model has been discussed on implementing in a web-based application for measuring design performance throughout the product design and development proces

Joint Channel Assignment and Opportunistic Routing for Maximizing Throughput in Cognitive Radio Networks

In this paper, we consider the joint opportunistic routing and channel assignment problem in multi-channel multi-radio (MCMR) cognitive radio networks (CRNs) for improving aggregate throughput of the secondary users. We first present the nonlinear programming optimization model for this joint problem, taking into account the feature of CRNs-channel uncertainty. Then considering the queue state of a node, we propose a new scheme to select proper forwarding candidates for opportunistic routing. Furthermore, a new algorithm for calculating the forwarding probability of any packet at a node is proposed, which is used to calculate how many packets a forwarder should send, so that the duplicate transmission can be reduced compared with MAC-independent opportunistic routing & encoding (MORE) [11]. Our numerical results show that the proposed scheme performs significantly better that traditional routing and opportunistic routing in which channel assignment strategy is employed.Comment: 5 pages, 4 figures, to appear in Proc. of IEEE GlobeCom 201

A smart performance measurement approach for collaborative design in Industry 4.0

Industry 4.0, the fourth industrial revolution, focuses on intelligent and smart manufacturing. This article investigates a smart design performance measurement approach, which can be utilized to support performance measurement implementation during a collaborative design process. First, we develop a smart product design framework with Industry 4.0 enabling technologies to support key design stages in an iterative fashion. Second, based on this framework, we propose a smart design performance measurement approach to potentially support a smart product design project management via its performance management. Third, we adapt our existing design performance measurement, for a traditional design environment into a smart design environment at its early stage to test its feasibility. This approach features integration of a flexible performance measurement setup, a multi-feedback design performance measurement mechanism and a multiple design performance measurement results presentation which allows the design performance measurement approach to produce flexible and customized operations by connecting design performance measurement with the stage-based design objectives, balancing design performance measurement feedbacks through interoperability between collaborative design team members and providing real-time design performance measurement results to guide design activities. An empirical industrial evaluation case study indicates that the proposed design performance measurement approach can support design team members in improving their collaborative design performance

Efficient SGD Neural Network Training via Sublinear Activated Neuron Identification

Deep learning has been widely used in many fields, but the model training process usually consumes massive computational resources and time. Therefore, designing an efficient neural network training method with a provable convergence guarantee is a fundamental and important research question. In this paper, we present a static half-space report data structure that consists of a fully connected two-layer neural network for shifted ReLU activation to enable activated neuron identification in sublinear time via geometric search. We also prove that our algorithm can converge in $O(M^2/\epsilon^2)$ time with network size quadratic in the coefficient norm upper bound $M$ and error term $\epsilon$

Dietary Exposures Contribute to Different Diseases through the Microenvironment

Genetic predispositions play an important role in our health, but these are not absolute; lifestyle choices help determine how long and how well we live. The global pandemic of obesity and related diseases is a good example. Lifestyle can contribute to diseases through altering the microenvironment of important tissues including adipose in obesity. In this dissertation, the consequences of lifestyle components on local and systemic inflammation and hyperinsulinemia were investigated, both of which contribute to risk of diseases such as obesity, insulin resistance, and breast cancer. Using preclinical mouse models, we aimed to uncover mechanisms by which alcohol and obesogenic diet exposures alter the microenvironment in the pathogenesis of adipose and mammary gland dysfunction. We found that binge ethanol exposure followed by burn injury exacerbated the adipose inflammatory response induced by burn alone, with significant elevations in macrophage infiltration and secretion of pro-inflammatory mediators when compared to controls not exposed to binge alcohol intake. It is well established that adipose inflammation contributes to insulin resistance, especially associated with obesity. We discovered that fatty acid transporter 1 (FATP1) predominantly on alternatively activated macrophages contributes to decreased local and systemic inflammation. Macrophage FATP1 overexpression suppressed inflammatory response, while FATP1 knock out exaggerated inflammatory factor expression in vitro. Mice transplanted with Fatp1-/- bone marrow and fed an obesogenic diet gained more weight and greater epididymal white adipose accretion, and became hyperglycemic and glucose intolerant. Obesity is a strong risk factor for an aggressive subtype of breast cancer called basal-like breast cancer (BBC) and reducing adiposity is predicted to lower incidence of BBC in human populations. Thus, we made mice obese in early adulthood and induced weight loss by a diet intervention. Mice, which lost weight following an initial weight gain, reversed obesity-driven tumor aggressiveness and mammary gland hyperplasia and ductal carcinoma in situ through alterations in kinase activation. The obese microenvironment of mammary glands in adulthood therefore can promote early tumor onset. Importantly the composition of the mammary gland can be reprogrammed with weight loss and restored to a lean phenotype associated with significantly reduced tumor aggressiveness.Doctor of Philosoph

Clinical significance of HPV-HC2 in diagnosis and prognosis of cervical lesions: a retrospective study

Background: To evaluate the human papillomavirus HC2 different range detection values and their clinical significance in prediction of CIN lesions grades as well as their role in the follow-up outcome after treatment.Methods: Using the hybrid capture 2 to detect and measure the HPV and the viral load quantity, we enrolled a total of 527 HPV positive women. All patients underwent thin prep liquid-based cytology test (TCT) and only 325 underwent colposcopy guided biopsy due to abnormal cytology results. All cytology and biopsy results were collected and analyzed according to the HPV viral load. Among these patients 108 patients were followed during 2years post-operatives and their prognosis results were collected and analyzed.Results: The proportion and severity of cytological abnormalities was positively correlated with the HPV-HC2 viral load (P0.05).Conclusions: High HPV-HC2 viral load is significantly associated with the severity of cervical lesions (CIN), however it does not predict any further prognosis on follow-up after treatment

CROR: Coding-Aware Opportunistic Routing in Multi-Channel Cognitive Radio Networks

Cognitive radio (CR) is a promising technology to improve spectrum utilization. However, spectrum availability is uncertain which mainly depends on primary user's (PU's) behaviors. This makes it more difficult for most existing CR routing protocols to achieve high throughput in multi-channel cognitive radio networks (CRNs). Inter-session network coding and opportunistic routing can leverage the broadcast nature of the wireless channel to improve the performance for CRNs. In this paper we present a coding aware opportunistic routing protocol for multi-channel CRNs, cognitive radio opportunistic routing (CROR) protocol, which jointly considers the probability of successful spectrum utilization, packet loss rate, and coding opportunities. We evaluate and compare the proposed scheme against three other opportunistic routing protocols with multichannel. It is shown that the CROR, by integrating opportunistic routing with network coding, can obtain much better results, with respect to throughput, the probability of PU-SU packet collision and spectrum utilization efficiency.Comment: 6 pages, 8 figures, to appear in Proc. of IEEE GlobeCom 201

MODEL OF WORKING SHIP CROSSING CHANNEL

An application method for working ship crossing safely is proposed to determine how to make navigation scheme at a certain time. This method makes it possible for decision makers to make reasonable judgments at different times. In this paper, the position relationship between working ship and navigation vessel in waterway is analysed by considering the ship size, hydrological conditions of waterway, ship arrival model and ship navigation trajectory. Using genetic algorithm, the operation scheme of keeping a safe distance between the working ship and the vessel in the channel is solved by taking the speed and direction of the working ship as genetic factors. By analysing the crossing scheme at each starting time in a given time range, the optimal crossing scheme with the farthest distance between the working ship and the vessels in the channel is obtained. According to the measured data, the simulation is carried out with MATLAB to verify the model of working ship crossing channel. The results show that it is safe and reliable to choose the navigation scheme proposed in this paper, which has strong application value