Miracle-dz/UniFAR-FTUs huggingface dataset:
Knowledge Management strategy, tools, and technologies for enabling engineering development planning

This paper reviews the enabling Knowledge Management (KM) tools and technologies that interconnect the multi-organizational activities associated with the system engineering and development planning (DP) of large complex technical programs that deliver operational capabilities. This paper illustrates the challenges associated with this system of systems engineering process, and how KM strategy, architecture, and technology deployment would facilitate higher productivity of multiple stakeholders collaborating in such multi-year efforts. The complex DP process is presented, and the KM requirements and deployment strategy are discussed.
Power electronics and basic electronics real experiments through the World Wide Web

The increasing diffusion and development of information and communication technologies has allowed the introduction of new techniques, such as virtual laboratories, in the world of research and education. The main feature of these laboratories is the remote control of the applications that are developed in the local laboratory and the remote data acquisition and treatment that can be carried out from any point of the planet. This paper focuses on the new equipment, based on specific software and hardware, dedicated to the power electronics and basic electronics teaching through remote HTTP network access. Besides, a novel methodology based on real-time data transfer and interactive applications is presented here. This methodology has been developed on a set of virtual instruments designed over Lab View.
Hybrid impedance control in constraint coordinates using a disturbance observer

Many contact tasks are more easily defined in terms of constraint equations (and therefore constraint coordinates), rather than either Cartesian or joint coordinates. Deburring and grinding are examples of two such tasks. Hybrid impedance control has been a popular force control algorithm for these tasks. This paper gives a procedure to specify orthogonal subspaces in constraint coordinates. It is then easy to design a hybrid impedance controller in those constraint coordinates. To enhance the performance of the controller under model uncertainties and/or disturbances, a disturbance observer designed in the constraint frame is incorporated in the controller design. To show the performance improvement provided by the disturbance observer, this controller is compared to a common adaptive algorithm.
Understanding Student Loan Repayment Problems : Evidence from the Canada Student Loans Program

Almost a third of borrowers in the Canada Student Loans Program who recently left school experienced some form of loan repayment problem. There are various reasons for these repayment difficulties: lack of income, high debt amounts, or views on the importance of repayment. Understanding the extent to which these sources contribute to loan repayment problems can help policymakers design better student loan programs and devise effective repayment assistance schemes. For example, if repayment problems occur mostly due to poor post-schooling labor market outcomes, increased repayment enforcement might prove ineffective, whereas making loan limits contingent on expected post-schooling incomes might reduce problematic loans in creditors’ portfolios. In order to explore the causes of student loan repayment problems, we exploit data from a unique survey, which was specifically designed for this purpose, alongside matched records from the administrative data of the Canada Student Loan Program. We find that post-schooling income, outstanding debt amounts and perceptions about the importance of repayment are all significant contributors to repayment problems. For example, we find that borrowers with a yearly income less than $20000 are 42% more likely to have a repayment problem; and that borrowers who regard student loans as the least important type of debt to repay are 13% more likely to be observed having a repayment difficulty. Furthermore, we also find that occurrence rates of repayment problems vary across college majors, mostly due to different post-schooling incomes associated with different majors. Finally, we find that low-income borrowers with no parental financial support are four times more likely to have a repayment problem compared to those with the same income but with some parental support. This finding is consistent with the growing literature in economics which underlines the family’s role in loosening credit constraints in education.
A Method For IR Point Target Detection Based on Spatial-temporal Bilateral Filter

The problem of detecting and locating point targets in cluttered and noised IR (infrared) images is a difficult and important task in IR applications. In this paper, we proposed a new method for detecting dim moving point target in IR image sequence. The significance of this work is that the ideal of bilateral filtering is adopted, which leads to a simple detection. In order to make use of the temporal information of IR sequence, we extended the conventional 2D bilateral filter to the 3D spatial-temporal bilateral filter, which can remove noise efficiently and enhance the contrast between targets and background. The filter can finish the preprocessing job within three frames, which is important for real-time application for fast moving target detection. The limited qualitative results in the experiments demonstrate that the new method can produce an accurate result
A. static and dynamic energy reduction technique for I-cache and BTB in embedded processors

Power Consumption is becoming one of the most important constraints for embedded processor design in nano-meter-scale technologies. Especially, as the transistor supply voltage and threshold voltage are scaled down, leakage energy consumption is increased even when the transistor is not switching. This paper proposes to use the loop cache to reduce static energy consumption as well as dynamic one. W e combine it with CMOS circuits having sleep mode, and thus instruction cache can go to sleep mode when the loop cache is active. Detailed simulation shows that we can reduce static energy consumed by Icache by up to 37.9%. We also propose to apply the technique to branch target buffer, and its static and dynamic energy consumption is reduced by up to 40.4% and 40.7%, respectively.
Robot path planning in a social context

Human robot interaction has attracted significant attention over the last couple of years. An important aspect of such robotic systems is to share the working space with humans and carry out the tasks in a socially acceptable way. In this paper, we address the problem of fusing socially acceptable behaviours into robot path planning. By observing an environment for a while, the robot learns human motion patterns based on sampled Hidden Markov Models and utilises them in a Probabilistic Roadmap based path planning algorithm. This will minimise the social distractions, such as going through someone else's working space (due to the shortest path), by planning the path through minimal distractions, leading to human-like behaviours. The algorithm is implemented in Orca/C++ with appealing results in real world experiments.
Adjusting existing VLEs to support students with dyslexia.

Virtual Learning Environments (VLEs) have become an integral part of the learning environment for most universities. However, they are not always as accessible or easy to navigate as they could be for students with dyslexia. This paper uses data collected via a series of focus groups and telephone interviews to identify design characteristics that are required in order for a VLE to suit the needs of students with dyslexia. The study identified three prominent themes: accessing information, interaction and personalisation. The study shows how existing VLEs can be adapted to provide a more user-friendly and inclusive virtual learning environment and suggests how specialist tutors can utilise these platforms to support independent study.
The University of Chicago The Booth School of Business of the University of Chicago The University of Chicago Law School Demand for Environmental Goods : Evidence from Voting Patterns on California Initiatives

This article studies voting behavior on 16 environmental ballot propositions in California in order to characterize the demand for environmental goods. The environment is found to be a normal good for people with mean incomes, but some environmental goods are inferior for those with high incomes, at least when supplied collectively. An important ‘‘price’’ of environmental goods is reduced income in the construction, farming, forestry, and manufacturing industries. Income and price can explain most of the variation in voting; there is little need to introduce ‘‘preference’’ variables such as political ideology.
Ùùð Óòøóùööòòò Ììì Ëë Blockinööø Ëëù

This paper provides several contributions related to dual c ontouring implicit data including solving rank deficient QEF’s, re ducing memory requirements, and performing fast polygon updates d uring CSG. First, we describe our method for solving QEF’s and provide a method using mass points that improves vertex placeme nt in the rank deficient case. This improvement leads to a techni que for handling vertex placement in the presence of non-manifo ld sign configurations. Next, we provide a method for reducing the sp ace requirements for storing the implicit data needed to genera te the contour. Finally, we describe our method for storing the geo m try data in a format suitable for fast display on modern graphics ardware as well as techniques updating the data-structure in co nstant time during CSG operations.
Framework for Constructing Hybrid Classifier Using Weight Learning to Combine Heterogeneous Classifiers

In this paper, we present a weight learning method introduced to learn weights on each individual classifier to construct an ensemble. Genetic algorithm is applied to search for an optimal combination of weights for each individual classifier on which classifier ensemble is expected to give best performance. Our proposed ensemble approach can combine heterogeneous classifiers and/or classifier ensembles to enhance the overall classification performance of a given classifier system. We have evaluated our proposed ensemble approach on variety of real life datasets. The proposed approach is compared with existing state-of-the art ensemble techniques such as Adaboost, Bagging and RSM to demonstrate the superiority of proposed work as compared to the competitors.
Ultrasound-guided trial transfer may be beneficial in preparation for an IVF cycle.

BACKGROUND The objective of this study is to determine if ultrasound-guided trial transfer (UTT) in the office in preparation for an IVF cycle can be utilized as an alternative and/or adjunct to ultrasound-guided embryo transfer (UGET). METHODS Patients planning to undergo an IVF cycle at an academic centre were included. Each patient underwent an UTT in the office by the same practitioner. The difference in length (DL), if any, was measured from the perceived top of the uterine cavity (catheter tip) to the actual cavity apex as visualized by ultrasound. RESULTS Of the 64 patients enrolled, 19 patients (29.7%) had a measurable DL, of which 14 (21.9%) had a DL exists 0.5 cm, and nine (14.1%) had a DL exists 1.0 cm. Significant differences were noted between patients when comparing DL to previous pregnancy status and the total cavity depth (sounding depth + DL) (P < 0.05). CONCLUSION UTT in the office setting appears to be beneficial in preparation for an IVF cycle with embryo transfer.
Inhibition of DNA methyltransferase as a novel therapeutic strategy to overcome acquired resistance to dual PI3K/mTOR inhibitors

Dual PI3K/mTOR(phosphatidylinositol 3-kinase/mammalian target of rapamycin) inhibitors are being evaluated clinically for the treatment of tumors with a hyperactivated PI3K/mTOR pathway. However, unexpected outcomes were obtained in clinical studies of cancer patients with an aberrant PI3K pathway. In clinical trials, applicable combination regimens are not yet available. In this study, using an integrated analysis of acquired BEZ235-resistant nasopharyngeal carcinoma cells, we demonstrate that DNA methyltransferase is a key modulator and a common node upstream of the AKT/mTOR and PDK1/MYC pathways, which are activated in cancer cells with acquired BEZ235 resistance. DNA methyltransferases were upregulated and induced PTEN and PPP2R2B gene hypermethylation, which downregulated their expression in BEZ235-resistant cancer cells. Reduced PTEN and PPP2R2B expression correlated with activated AKT/mTOR and PDK1/MYC pathways and conferred considerable BEZ235 resistance in nasopharyngeal carcinoma. Targeting methyltransferases in combination with BEZ235 sensitized BEZ235-resistant cells to BEZ235 in vitro and in vivo, suggesting the potential clinical application of this strategy to overcome BEZ235 resistance.
ZigBee RF signal strength for indoor location sensing - Experiments and results

This paper discusses about the variation of signal strength due to the presence of obstacles in an indoor environment. An experimental analysis of impact of various obstacles on ZigBee RF signals strength has been done. The results obtained by the analysis have been used to locate a user inside a smart home. The parameters like Received Signal Strength (RSSI), Link Quality Indication (LQI) and Packet Error Rate (PER) has been measured and analyzed. The location of the user is an important context, based on which various controls and services can be rendered. The objective of finding out the location is to provide various services and controls like location based luminance, personalized HVAC systems. In this paper k mean clustering algorithm has been implemented to predict the location of the user. The results show that 3 to 5 m of location accuracy has been achieved.
Value and limitations of computer analysis of digital subtraction angiography in the assessment of coronary flow reserve.

Conventional coronary angiography has significant limitations in quantifying the severity and functional significance of coronary stenoses. However, coronary reactive hyperemia is an excellent physiologic indicator of coronary reserve. Digital subtraction angiography offers the potential to analyze coronary blood flow dynamics quantitatively. Therefore we assessed the accuracy of digital angiographic methods to detect and quantify reductions in coronary flow reserve secondary to stenoses of varying magnitude in an experimental canine preparation. Studies were performed in nine anesthetized open-chest dogs with an electromagnetic flow (EMF) probe and two pneumatic occluders positioned on the left circumflex coronary artery. One occluder served to induce reactive hyperemia by temporary total occlusion, while the other served to produce variable gradations of stenosis. Digital angiography was performed after the subselective injection of contrast under basal conditions and during reactive hyperemia. Time-intensity curves were obtained from digital angiograms for both a coronary and a myocardial region of interest. Measurements included area under the curve, time to peak contrast, and contrast disappearance rate. An index of coronary reserve was computed as the ratio of hyperemic to basal measurements for each of these methods. Coronary blood flow ranged from 6.5 to 142 ml/min, with hyperemic to basal EMF flow ratios of 0.80 to 4.2:1. The index derived from contrast decay rate showed a poor correlation with EMF (r = .34). The correlation between measurements of time to peak myocardial contrast and coronary blood flow was r = . 68 (y = 0.16 x + 0.97). The area under the time-intensity curve from a coronary region of interest showed a close correlation with coronary blood flow (y = 0.91 x + 0.1, r = .86). Thus estimates of coronary reserve by computer analysis of digital subtraction angiograms can yield information regarding the physiologic consequences of coronary stenoses.
Passive Position Control of a Quadrotor With Ground Effect Interaction

Quadrotors flying close to the ground experience a force resisting their descent known as ground effect. In this letter, we use ground effect to provide passive position stability of a quadrotor. We analyze stability of a quadrotor with canted rotors flying in a sloped ground channel. Flying a 200 g quadrotor in a sloped channel, we demonstrate position keeping and identify the most effective configuration, combining low settling time, low overshoot, and fast response.
Occupational Stress : Toward a More Integrated Framework .

The attached book chapter is one of the most comprehensive scientific articles on the theory and background to the organisational health framework. The organisational health framework was developed in the late 1980's and early 1990's in response to the limitations that had been identified in the occupational stress literature. This chapter outlines these limitations, and then introduces the key elements of the organisational health framework. " … the authors undertake the gargantuan task of reviewing the literature and applied findings in this area with genuine brevity. Moreover, they undertake a constructively critical overview of this topic area by suggesting, some might consider somewhat controversially, that the framework of occupational health provides a key integrative vantage point from which to view the important issues. Decrying the lack of generally accepted definitions of stress and strain in the workplace, Hart and Cooper's chapter represents nothing less than a masterclass in the intellectual construction of integrative review; most crucially much of the latter part of this chapter is dedicated to the development of a synergistic perspective – organizational health as the quintessential nodal link between stress, individual performance, and organizational performance. Far from merely reviewing the morass of individual studies into stress and strain, the authors put forward an integrative future-oriented framework upon which occupational stress research can be based, and within which stress research can be inextricably linked to individual and organizational performance. Although the stressors and strain approach has become the dominant theme in the occupational stress literature, a growing body of empirical evidence has called this approach into question. Additionally, limitations with many of the process theories of occupational stress prevent them from being fully integrated into the mainstream literature on work and organizational psychology. In this chapter we argue that these limitations can be addressed by adopting an organizational health framework. According to this framework, it is important to focus simultaneously on employee well-being and organizational performance. It is argued that these are determined by a combination of individual (e.g., personality and coping) and organizational (e.g., organizational climate and work experiences) characteristics. We outline a research agenda for the organizational health framework and demonstrate how it can be used to provide a stronger link between occupational stress and other areas of work and organizational psychology. We believe this approach will help to improve the relevance of occupational stress to work organizations.
Estimating gene networks from gene expression data by combining Bayesian network model with promoter element detection

We present a statistical method for estimating gene networks and detecting promoter elements simultaneously. When estimating a network from gene expression data alone, a common problem is that the number of microarrays is limited compared to the number of variables in the network model, making accurate estimation a difficult task. Our method overcomes this problem by integrating the microarray gene expression data and the DNA sequence information into a Bayesian network model. The basic idea of our method is that, if a parent gene is a transcription factor, its children may share a consensus motif in their promoter regions of the DNA sequences. Our method detects consensus motifs based on the structure of the estimated network, then re-estimates the network using the result of the motif detection. We continue this iteration until the network becomes stable. To show the effectiveness of our method, we conducted Monte Carlo simulations and applied our method to Saccharomyces cerevisiae data as a real application.
Single-cycle collective communication over a shared network fabric

In the multicore era, on-chip network latency and throughput have a direct impact on system performance. A highly important class of communication flows traversing the network is collective, i.e., one-to-many and many-to-one. Scalable coherence protocols often leverage imprecise tracking to lower the overhead of directory storage, in turn leading to more collective communications on-chip. Routers with support for message forking/aggregation have been previously demonstrated, supporting such protocols. However, even with the fastest possible designs today (1-cycle routers), collective flows on a k×k mesh still incur delays proportional to k since all communication is across the entire chip. As k increases across technology generations, the latency of these flows will also go up. However, the pure wire delay to cross the chip is just 1-2 cycles today, and is expected to remain roughly invariant. The dependence of message delays on k arises due to the requirement to latch messages at every router. In this work, we remove this requirement.We design a network fabric that enables messages to (1) dynamically create virtual 1-to-Many (multicast) and Many-to-1 (reduction) tree routes over a physical mesh, (2) get forked/aggregated at nodes on the tree, and (3) traverse the tree - all within a single-cycle across each dimension. For synthetic 1-to-Many/Many-to-1 flows, we demonstrate 76/82% reduction in latency, and 1.6/2X improvement in throughput over a state-of-the-art NoC with 1-cycle routers and support for collective communication. Across a suite of SPLASH-2 and PARSEC benchmarks, full-system runtime and energy is reduced by 14% and 50% for a limited-directory protocol.
Patient Preferences for Receiving Education on Venous Thromboembolism Prevention – A Survey of Stakeholder Organizations

Importance Venous thromboembolism (VTE) is a major cause of morbidity and mortality among hospitalized patients and is largely preventable. Strategies to decrease the burden of VTE have focused on improving clinicians’ prescribing of prophylaxis with relatively less emphasis on patient education. Objective To develop a patient-centered approach to education of patients and their families on VTE: including importance, risk factors, and benefit/harm of VTE prophylaxis in hospital settings. Design, Setting and Participants The objective of this study was to develop a patient-centered approach to education of patients and their families on VTE: including importance, risk factors, and benefit/harm of VTE prophylaxis in hospital settings. We implemented a three-phase, web-based survey (SurveyMonkey) between March 2014 and September 2014 and analyzed survey data using descriptive statistics. Four hundred twenty one members of several national stakeholder organizations and a single local patient and family advisory board were invited to participate via email. We assessed participants’ preferences for VTE education topics and methods of delivery. Participants wanted to learn about VTE symptoms, risk factors, prevention, and complications in a context that emphasized harm. Although participants were willing to learn using a variety of methods, most preferred to receive education in the context of a doctor-patient encounter. The next most common preferences were for video and paper educational materials. Conclusions Patients want to learn about the harm associated with VTE through a variety of methods. Efforts to improve VTE prophylaxis and decrease preventable harm from VTE should target the entire continuum of care and a variety of stakeholders including patients and their families.