nils-herrmann/clean_scirepeval huggingface dataset:
Influence of Benefits Realization Management on Business Strategies and Project Success in Pakistan's Construction Projects

Benefits realization management (BRM) practices are supposed to be the one of the key promising solution for developing business strategies and for project success. This concept is evaluated in the perspective of Pakistan's construction industry where the project managers keen to develop the business strategies in order to reduce the gap between effective planning and project executions. The objective of the study is to examine the impact of BRM practices on business strategies and project success in the Pakistan's construction industry. The project success measured by the project output, project goals and the project customer, while BRM practices measured by the project planning, project review, project realization and project strategy. The results of Model 1 show the influence of success dimension factors on project success which reveals that, out of four dimension factors, 3 success factors positively associated with the project success, while schedule goals have a negative relationship with the project success. The results of Model 11 show the influence of BRM practices on project success in three different regression paths. In the first regression path, 7 BRM item shows their significant relationship with the project success, out of which 2 of them having a negative relationship with the project success while remaining 5 of them having a positive relationship with the project success. In the second regression path, out of four BRM factors, three have a positive relationship with the project success, while the remaining BRM factor shows a negative association with the project success. Finally, in the third regression path, the aggregated value of BRM practices tends to show the positive relationship with the project success in the Pakistan's construction projects. The results of Model 111 indicate BRM practices have a positive relationship with the business strategy in the construction industry; however, the intensity of BRM practices is comparatively low to influence business strategy as compared to larger influence of BRM practices on project success. The study conclude that BRM practices deem desirable for project success i.e. there is required a strong policy vista to device policies in order to strengthen the capabilities of project managers to fore see the future challenges across the construction industry.
Benefits Realization Management: Strategic Value from Portfolios, Programs, and Projects

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Gemini: A Computation Centric Distributed Graph Processing System
Venue: OSDI

Traditionally distributed graph processing systems have largely focused on scalability through the optimizations of inter node communication and load balance. However, they often deliver unsatisfactory overall processing efficiency compared with shared memory graph computing frameworks. We analyze the behavior of several graph parallel systems and find that the added overhead for achieving scalability becomes a major limiting factor for efficiency, especially with modern multi core processors and high speed interconnection networks. Based on our observations, we present Gemini, a distributed graph processing system that applies multiple optimizations targeting computation performance to build scalability on top of efficiency. Gemini adopts (1) a sparse dense signal slot abstraction to extend the hybrid push pull computation model from shared memory to distributed scenarios, (2) a chunk based partitioning scheme enabling low overhead scaling out designs and locality preserving vertex accesses, (3) a dual representation scheme to compress accesses to vertex indices, (4) NUMA aware sub partitioning for efficient intra node memory accesses, plus (5) locality aware chunking and fine grained work stealing for improving both internode and intra node load balance, respectively. Our evaluation on an 8 node high performance cluster (using five widely used graph applications and five real world graphs) shows that Gemini significantly outperforms all well known existing distributed graph processing systems, delivering up to 39.8x (from 8.91x) improvement over the fastest among them.
LEADERSHIP APPROACH IN RELATION TO LEVEL OF CONSCIOUSNESS: A CORRELATIONAL ANALYSIS

The present empirical study was designed to explore the relationship between the leadership approach of teacher trainees and their level of consciousness. A descriptive survey was conducted on 100 teacher trainees (both male female in the ratio of 1:1) The level of consciousness of teacher trainees was assessed using Consciousness Quotient Inventory (CQ i) by Brazdau (2011) To assess the leadership approach Multifactor Leadership Questionnaire (MLQ 6S) by Bass and Avolio (1992) was used. The relationship between scores on seven leadership factors (comprising three leadership approaches) and the level of consciousness was studied using Pearson's product moment correlation. Results indicate a significant positive correlation to a varying degree between consciousness and three leadership approaches
Dynamic configuration of reverse proxy cache based on multi dimensional time series prediction of visit traffic
Venue: 2016 7th IEEE International Conference on Software Engineering and Service Science (ICSESS)

This paper does research on the Internet visit traffic prediction by using time series and apply it to server configuration. After analyzing the periodicity and regularity of typical periods of time series, we propose the multi dimensional model establishment method, which is both applicable for long term and short term prediction. In addition, for immediate prediction we propose dynamic change rate prediction and adjustment algorithm based on exponential smoothing and moving average. The experiment result show high precision of prediction. By applying the model and algorithm above to the cluster server reverse proxy for dynamic cache configuration, the average response time from server to the user's request is greatly reduced, accurately predict the Internet traffic warning line, and has a guiding significance for cluster resources optimization.
An Extensible Universal Reverse Proxy Architecture
Venue: 2016 International Conference on Network and Information Systems for Computers (ICNISC)

With the rapid development of the computer techniques, researchers develop more and more application layer protocols to realize new functions. However, traditional reverse proxy servers can't support these new protocols very well because of low extensibility. To solve the problem, we propose an extensible universal reverse proxy architecture which makes reverse proxy server more adaptive to new protocols by employing corresponding protocol plugins. When a client request comes, the universal reverse proxy server will analyze the data header by the protocol filter and then call the appropriate protocol plugin thread from the plugin pool, which will handle the client request and perform the reverse proxy work. Experimental results show that this architecture has the advantage of universality, extensibility and efficiency.
On the "naturalness" of buggy code
Venue: ICSE

Real software, the kind working programmers produce by the kLOC to solve real world problems, tends to be "natural" like speech or natural language; it tends to be highly repetitive and predictable. Researchers have captured this naturalness of software through statistical models and used them to good effect in suggestion engines, porting tools, coding standards checkers, and idiom miners. This suggests that code that appears improbable, or surprising, to a good statistical language model is "unnatural" in some sense, and thus possibly suspicious. In this paper, we investigate this hypothesis. We consider a large corpus of bug fix commits (ca. 7,139) from 10 different Java projects, and focus on its language statistics, evaluating the naturalness of buggy code and the corresponding fixes. We find that code with bugs tends to be more entropic (i.e. unnatural) becoming less so as bugs are fixed. Ordering files for inspection by their average entropy yields cost effectiveness scores comparable to popular defect prediction methods. At a finer granularity, focusing on highly entropic lines is similar in cost effectiveness to some well known static bug finders (PMD, FindBugs) and ordering warnings from these bug finders using an entropy measure improves the cost effectiveness of inspecting code implicated in warnings. This suggests that entropy may be a valid, simple way to complement the effectiveness of PMD or FindBugs, and that search based bug fixing methods may benefit from using entropy both for fault localization and searching for fixes.
RL$^2$ Fast Reinforcement Learning via Slow Reinforcement Learning
Venue: ArXiv

Deep reinforcement learning (deep RL) has been successful in learning sophisticated behaviors automatically; however, the learning process requires a huge number of trials. In contrast, animals can learn new tasks in just a few trials, benefiting from their prior knowledge about the world. This paper seeks to bridge this gap. Rather than designing a "fast" reinforcement learning algorithm, we propose to represent it as a recurrent neural network (RNN) and learn it from data. In our proposed method, RL$^2$ the algorithm is encoded in the weights of the RNN, which are learned slowly through a general purpose "slow" RL algorithm. The RNN receives all information a typical RL algorithm would receive, including observations, actions, rewards, and termination flags; and it retains its state across episodes in a given Markov Decision Process (MDP) The activations of the RNN store the state of the "fast" RL algorithm on the current (previously unseen) MDP. We evaluate RL$^2$ experimentally on both small scale and large scale problems. On the small scale side, we train it to solve randomly generated multi arm bandit problems and finite MDPs. After RL$^2$ is trained, its performance on new MDPs is close to human designed algorithms with optimality guarantees. On the large scale side, we test RL$^2$ on a vision based navigation task and show that it scales up to high dimensional problems.
A Review of the Growth of the Fast Food Industry in China and Its Potential Impact on Obesity
Venue: International journal of environmental research and public health

The fast food (FF) industry and obesity rates have rapidly increased in China. This study examined the FF industry growth in China, key factors contributing to the growth, and the association between FF consumption (FFC) and obesity. We collected related data from multiple sources and conducted analysis including linear regression analysis on the increase in FF revenue. It was found that FF industry in China is large, with over two million FF facilities. Its total revenue (in million US$ increased from 10,464 in 1999 to 94,218 in 2013, and by 13% annually since 2008. Increased income, urbanization, busier lifestyle, speedy FF service, assurance of food safety, new brands and foods have stimulated demand for FF. Studies have linked FFC with obesity risk, including a few reporting a positive association between FFC and obesity in China. Rapid expansion of Western style FF restaurants has also stimulated local FF industry growth. Government regulation and public health education need to address the health consequences of rapidly increasing FFC. Lessons learned in China will help other countries.
Joint Action Essays in honour of John Shotter

Essays in honour of John Shotter brings together a cross disciplinary group of fifteen respected international scholars to explain the relevance of John Shotter's work to emerging concerns in twenty first century social science.Shotter's work extends over forty years and continues to challenge conventional scientific thinking across a range of topics. The disciplines and practices that Shotter's work has informed are well established throughout the English speaking world. This is the first publication to examine the importance of his influence in contemporary social sciences and it includes authoritative discussions on topics such as social constructionism, democratic practice, organisational change, the affective turn and human relations. The geographical diversity and disciplinary breadth of scholarly contributions imbues the book with international scope and reach.Joint Action presents a contemporary reflection on Shotter's work that demonstrates its influence across a range of substantive topics and practical endeavours and within disciplines including management studies and philosophy as well as psychology. As such, it will appeal to researchers and postgraduate students of social sciences and related disciplines, as well as to those who have heard of Shotter's work and want to know more about its utility and value in relation to their own research or practice.
SU F T 507: Modeling Cerenkov Emissions From Medical Linear Accelerators: A Monte Carlo Study.
Venue: Medical physics

Cerenkov emissions are a natural byproduct of MV radiotherapy but are typically ignored as inconsequential. However, Cerenkov photons may be useful for activation of drugs such as psoralen. Here, we investigate Cerenkov radiation from common radiotherapy beams using Monte Carlo simulations.  GAMOS, a GEANT4 based framework for Monte Carlo simulations, was used to model 6 and 18MV photon beams from a Varian medical linac. Simulations were run to track Cerenkov production from these beams when irradiating a 50cm radius sphere of water. Electron contamination was neglected. 2 million primary photon histories were run for each energy, and values scored included integral dose and total track length of Cerenkov photons between 100 and 400 nm wavelength. By lowering process energy thresholds, simulations included low energy Bremsstrahlung photons to ensure comprehensive evaluation of UV production in the medium.  For the same number of primary photons, UV Cerenkov production for 18MV was greater than 6MV by a factor of 3.72 as determined by total track length. The total integral dose was a factor of 2.31 greater for the 18MV beam. Bremsstrahlung photons were a negligibly small component of photons in the wavelength range of interest, comprising 0.02% of such photons.  Cerenkov emissions in water are 1.6x greater for 18MV than 6MV for the same integral dose. Future work will expand the analysis to include optical properties of tissues, and to investigate strategies to maximize Cerenkov emission per unit dose for MV radiotherapy.
Venous thromboembolism rates in patients with lower limb immobilization after Achilles tendon injury are unchanged after the introduction of prophylactic aspirin: audit
Venue: Journal of thrombosis and haemostasis JTH

We audited venous thromboembolism (VTE) in Achilles injuries after the use of prophylactic aspirin. We audited 218 patients with Achilles injury requiring lower limb immobilization for 1 week. Fourteen patients (6.4% 95% CI 3.6% to 10.5% developed symptomatic and confirmed VTE. The incidence was similar to the 6.3% identified in the same patient group prior to the use of aspirin.
Abstract 13150: The Economic Implications of Non adherence to Aspirin in Patients With Prior Primary Cardiovascular Events

Adherence to medications for secondary prevention of cardiovascular events has been shown to be poor in both general and high risk populations. Non adherent patients are at higher risk of experiencing another CV event, leading to adverse clinical events and high costs. Few prior studies have explored the economic and consequences of non adherence to aspirin in relation to cardiovascular health.  Improved adherence to aspirin will lead to lower healthcare costs and improved long term survival rates.  We developed a generalizable Markov model to estimate the cost effectiveness of aspirin adherence. The rates of aspirin adherence, events and costs were gathered from published literature. We applied the model separately to a general (low risk) population with no comorbidities and a high risk population with type II diabetes. Outcomes of interest included fatal and nonfatal events, including secondary myocardial infarction (MI) stroke, other clinical CV events including PAD re.
Baseline insulin sensitivity affects response to high amylose maize resistant starch in women: a randomized, controlled trial
Venue: Nutrition Metabolism

BackgroundResistant starch (RS) is a type of dietary fiber that can improve glucose metabolism, but its effects may be modulated by sex or baseline insulin sensitivity. This study was designed to examine the effect of high amylose maize resistant starch (HAM RS2) on insulin sensitivity (SI) in women, and to determine if SI status affects the response to RS.MethodsThis was a randomized, placebo controlled, double blind, cross over study. Participants were 40 healthy, non diabetic women aged 22 67 years in the normal weight to obese BMI range (20.6 47.4 kg/m2) Two doses of HAM RS2 were tested, 15 and 30 g per day, administered in the form of cookies. Participants were randomized to the order in which they received the experimental and placebo product. Each arm was 4 weeks, with a 4 week wash out period in between. SI was assessed at the end of each 4 week arm of product consumption by frequently sampled, insulin modified, intravenous glucose tolerance test and minimal modeling. Participants were categorized as being insulin resistant (IR; SI 7.8) or insulin sensitive (IS; SI 7.8) based on Gaussian analysis. The effect of treatment arm on SI was examined by mixed model analysis within IR and IS sub groups, using all available data. In addition, SI was examined by ANOVA among just those women who completed all three arms of the study with valid SI results.ResultsAmong IR participants, SI was on average ~16 higher after the 30 g arm when compared to the control arm by mixed model analysis (n 40, P 0.05) and tended to be 23 higher by ANOVA among women who completed all arms (n 23, P 0.06) HAM RS2 did not affect SI in IS women.ConclusionConsumption of HAM RS2 at 30 g/day in the form of a snack food item was associated with improved insulin sensitivity in women with insulin resistance.
The Context Dependence of Citizens' Attitudes and Preferences Regarding Privacy and Security

This paper considers the relationship between privacy and security and, in particular, the traditional "trade off" paradigm that argues that citizens might be willing to sacrifice some privacy for more security. Academics have long argued against the trade off paradigm, but these arguments have often fallen on deaf ears. Based on data gathered in a pan European survey we discuss which factors determine citizens' perceptions of concrete security technologies and surveillance practices.
Improving K 12 Online Learning: Information Literacy Skills for Teacher Candidates
Venue: Int. J. Inf. Commun. Technol. Educ.

Research indicates the need for teachers to be able to locate, evaluate, and use Internet resources in their teaching and learning processes. In addition, the Common Core State Standards require that students are able to think critically and know how to search and use alternative views and perspectives in their assignments. These skills are imperative for teachers and teacher candidates. This article reports the results of a study that sought to examine strategies used by teacher candidates when using Internet search engines, their ability to integrate the information they find into their own assignments, and use the acquired skills for future classroom use. The study employed a mixed method approach in the collection and analysis of data gathered from a sample of 45 teacher candidates. Data sources included a survey, class assignments that required documentation of the search process as well as the located sources, and semi structured interviews. Findings from the study revealed the need to teach teacher candidates how to conduct searches effectively, critically evaluate the sources, and integrate the information acquired from the online sources into professional and academic writing that models such behavior for their students. Suggestions for improvement of practice offered in this paper were piloted in one instructional technology course.
Global finite time lag synchronization for a class of chaotic systems with the cubic terms in the presence of time delay
Venue: 2016 35th Chinese Control Conference (CCC)

This paper designs a simple, continuous and dimension reducible controller, named the variable substitution and feedback controller, to deal with the global finite time lag synchronization for a class of chaotic systems with cubic terms in the presence of time delay. Under the new designed controller, the finite time lag synchronization scheme is built up after the description of a class of chaotic systems with cubic terms. Then the finite time stability theory is applied to prove some criteria for the global finite time lag synchronization of this class of chaotic systems and estimate the synchronization time by transforming the global finite time lag synchronization problem to the global finite time stability of the error system, which originates from the established finite time lag synchronization scheme for this class of chaotic systems. Then, the obtained criteria are applied to the modified Chua's circuit system, further attaining a criterion on the global finite time lag synchronization of the Chua's circuit systems. Finally, a numerical example is provided to verify the effectiveness of the newly obtained criterion.
A Combined Adaptive Neural Network and Nonlinear Model Predictive Control for Multirate Networked Industrial Process Control
Venue: IEEE Transactions on Neural Networks and Learning Systems

This paper investigates the multirate networked industrial process control problem in double layer architecture. First, the output tracking problem for sampled data nonlinear plant at device layer with sampling period Td is investigated using adaptive neural network (NN) control, and it is shown that the outputs of subsystems at device layer can track the decomposed setpoints. Then, the outputs and inputs of the device layer subsystems are sampled with sampling period Tu at operation layer to form the index prediction, which is used to predict the overall performance index at lower frequency. Radial basis function NN is utilized as the prediction function due to its approximation ability. Then, considering the dynamics of the overall closed loop system, nonlinear model predictive control method is proposed to guarantee the system stability and compensate the network induced delays and packet dropouts. Finally, a continuous stirred tank reactor system is given in the simulation part to demonstrate the effectiveness of the proposed method.