Miracle-dz/UniFAR-FTUs huggingface dataset:
Architecting Water Supply System - A Perspective from Value of Flexibility

Water supply system is socially, politically, and financially critical, and long term security of water supply has to be met in spite of the huge uncertainty in its operation decades since the time of design. Everyone concerned with architecting such a system faces a common challenge: how do we design a system to perform well in a constantly evolving and thus risky context? As one of the water-stress countries, Singapore dealt the challenge by architecting its water supply system around several sources to increase its flexibility. Using a real option perspective, this paper examines various water supply resources and examines their flexibility values in actively dealing with the risks. It is found that incorporating alternative water resources increases the flexibility of the water supply system and helps the system from financial cost, political risk, and socioeconomic risk aspects. Through the Singapore water supply system study, this paper presents to decision makers a perspective of flexibility to manage risk with quantitative awareness using a real option approach based on multiple objectives.
From Social Butterfly to Engaged Citizen: Urban Informatics, Social Media, Ubiquitous Computing, and Mobile Technology to Support Citizen Engagement

Web 2.0 tools, including blogs, wikis, and photo sharing and social networking sites, have made possible a more participatory Internet experience. Much of this technology is available for mobile phones, where it can be integrated with such device-specific features as sensors and GPS. From Social Butterfly to Engaged Citizen examines how this increasingly open, collaborative, and personalizable technology is shaping not just our social interactions but new kinds of civic engagement with cities, communities, and spaces. It offers analyses and studies from around the world that explore how the power of social technologies can be harnessed for social engagement in urban areas. Chapters by leading researchers in the emerging field of urban informatics outline the theoretical context of their inquiries, describing a new view of the city as a hybrid that merges digital and physical worlds; examine technology-aided engagement involving issues of food, the environment, and sustainability; explore the creative use of location-based mobile technology in cities from Melbourne, Australia, to Dhaka, Bangladesh; study technological innovations for improving civic engagement; and discuss design research approaches for understanding the development of sentient real-time cities, including interaction portals and robots.
Digital passive geometric telemanipulation

In this paper we present an intrinsically passive telemanipulation scheme over a digital transmission line Internet-like. We present an analysis of the energetic behavior of the communication line both in case of loss of packages and in case of variable delay. The sample data nature of the passive controller is explicitly taken into account following the approach outlined.
Association of Plasma Angiotensin-(1–7) Level and Left Ventricular Function in Patients with Type 2 Diabetes Mellitus

Background We recently found that overexpression of angiotensin (Ang)-converting enzyme 2, which metabolizes Ang-II to Ang-(1–7) and Ang-I to Ang-(1–9), may prevent diabetes-induced left ventricular remodeling and dysfunction in rats. Our objective was to evaluate the association of plasma Ang-(1–7) level and left ventricular function in patients with type 2 diabetes mellitus. Methodology/Principal Findings We measured the left ventricular ejection fraction (EF), ratio of early to late left ventricular filling velocity (E/A) and ratio of early diastolic mitral inflow to annular velocity (E/Ea) by ultrasonography in 110 patients with type 2 diabetes mellitus for more than 5 years. Anthropometric and fasting blood values were obtained from medical records. The plasma Ang-(1-7) level in patients with a poor EF (<50%) was significantly lower than that in patients with EF ≥50%; the level in patients with E/A <1 was significantly lower than that in patients with E/A ≥1; and the level in patients with E/Ea >15 was significantly lower than that in patients with E/Ea ≤15. Ang-(1–7) level was negatively correlated with E/Ea and Log-N-terminal pro-B-type natriuretic peptide and positively with EF and E/A. Stepwise multiple regression analysis revealed that Ang-(1–7), hemoglobin A1c and Ang-II levels as well as duration of diabetes predicted EF; Ang-(1–7) level, fasting blood glucose, low-density lipoprotein cholesterol level and duration of diabetes predicted E/A; and Ang-(1–7) and hemoglobin A1c levels predicted E/Ea. Conclusions/Significance Plasma Ang-(1–7) level is independently associated with left ventricular function in patients with type 2 diabetes mellitus and may be a biomarker for assessing cardiac function in such patients.
Orthogonal Locality Sensitive Discriminant Analysis for Face Recognition

An innovative appearance-based method that called Orthogonal Locality Sensitive Discriminant Analysis is presented for face recognition in this paper. Our algorithm is based on the Locality Sensitive Discriminant Analysis (LSDA) algorithm, which aims at finding a projection by maximizing the margin between data points from different classes at each local area. However, a major disadvantage of LSDA is that LSDA is non- or- thogonal, and this makes it difficult to estimate the intrinsic dimensionality and to recon- struct the face data. Non-orthogonality distorts the local geometrical structure of the data submanifold. In this paper, an Orthogonal LSDA algorithm is proposed to preserve the local geometrical structure by computing the mutually orthogonal basis functions itera- tively. Since it produces orthogonal basis functions and can have more local structure preserving power, it is expected to have more discriminating power than LSDA. Experi- ments based on the ORL and Yale face database show the impressive performance of the proposed method. Results show that our new algorithm outperforms the other popular approaches reported in the literature and achieves a much higher recognition rate.
Automatic generation of fuzzy logic components for enhancing the mechanism of learner's modeling while using educational games

Working memory is the system used by every human for temporarily storing and managing the information required to carry out complex cognitive tasks such as learning, reasoning and comprehension. In particular, working memory capacity plays an important role in learning process, because learner often have to hold information in mind while engaged in a learning activities. Having information about learners' WMC could be helpful to support them during the learning process. Khenissi et al. [1] proposed an approach based on fuzzy logic for learner's modeling while using educational games and/or e-learning system. This paper will detail the description of the mechanism proposed by Khenissi et al. [1]. Furthermore, it will describe how the system architecture will be improved by the automatic generation of the fuzzy logic components. In particular, the machine learning, web services and the model of educational games are adopted for automatically generate the components of the fuzzy logic system. The automatic generation of these components will help the expert in parameterizing them, and thus better estimation of the learner's WMC.
Analysis of thermographic patterns using Open CV case study: A clinker kiln

The core of the cement production process is the clinker kiln. Proper operation of the kiln depends on factors such as the timely monitoring of its thermal behavior under different operation conditions. This work includes a systematization of empirical knowledge of skilled kiln operators, linking it with the analysis of thermography images of the kiln using Open CV. The paper includes an integration of interventions implemented by the operators, in terms of a log described in natural language. The work highlights potential uses of the knowledge of experienced operators, when this is combined with techniques based on image analysis and artificial intelligence.
Protein Kinase C Mediates Basic Fibroblast Growth Factor Protection of Endothelial Cells against Radiation-induced Apoptosis 1

Basic fibroblast growth factor (bFGF) was found to protect bovine aortlc endotheial cells against the lethal effects of ionizing radiation by Inhibiting the programmed cell death (apoptosis) induced in these cells by radiation exposure The involvement ofthe bFGF receptor tyrosine kinase In this function was demonstrated by abrogation of the radioprotective effect of bFGF by a specific Inhibitor of the bFGF receptor tyrosine ldnase, the tyrphostin AG213. The downstream signaling after stimulation of the bFGF receptor tyrosine kinase in bovine aortic endothelial cells involved translocation of the a isotype of cytoplasmic protein kinase C (PKC) into the membrane and Its activation within 30 s after bFGF stimulation. The involvementof PKC in the radioprotective effect con ferred by bFGF was suggested by the demonstration that nonspecific PKC activation by short-term exposure (30 stain) to the phorbol ester, 12-0tetradecaaoylphorbol-13-acetate (TPA; 30 ng/ml) mimicked the radiopro tective effect of bFGF. Furthermore, treatment of the cells with the PKC inhibitor 1-(5-isoquinolinesulfonyl)-2-methylplperazine (2O@iM) abrogated the radioprotective effect of bFGF, as was observed after the depletion of cellular PKC by overnight preincubation with high-dose TPA (200 nsa). Agarose gel electrophoresis of DNA extracted from irradiated bovine aortic endotheial cells showed that both TPA (30 ng/ml; 30 sin) and bFGF (1 ng/ml) inhibited the apoptotic degradation of DNA induced in these cells by radiation exposure (500 cGy). Both the bFGFand the TPA-mediated inhibition of apoptosis could be reversed by the PKC inhibitor 1-(5-isoquinollnesulfonyl)-2-methylpiperazine (20 psa). These data demonstrate the involvement of PKC in the Inhibition of radiation induced apoptosis by bFGF and the rescue of endothellal cells from this mode of radiation-induced cell death.
Simulated loss of foveal vision eliminates visual search advantage in repeated displays

In the contextual cueing paradigm, incidental visual learning of repeated distractor configurations leads to faster search times in repeated compared to new displays. This contextual cueing is closely linked to the visual exploration of the search arrays as indicated by fewer fixations and more efficient scan paths in repeated search arrays. Here, we examined contextual cueing under impaired visual exploration induced by a simulated central scotoma that causes the participant to rely on extrafoveal vision. We let normal-sighted participants search for the target either under unimpaired viewing conditions or with a gaze-contingent central scotoma masking the currently fixated area. Under unimpaired viewing conditions, participants revealed shorter search times and more efficient exploration of the display for repeated compared to novel search arrays and thus exhibited contextual cueing. When visual search was impaired by the central scotoma, search facilitation for repeated displays was eliminated. These results indicate that a loss of foveal sight, as it is commonly observed in maculopathies, e.g., may lead to deficits in high-level visual functions well beyond the immediate consequences of a scotoma.
A New Approach for Handling Null Values in Web Log Using KNN and Tabu Search KNN

When the data mining procedures deals with the extraction of interesting knowledgefrom web logs is known as Web usage mining. The result of any mining issuccessful, only if the dataset under consideration is well preprocessed. One of the important preprocessing steps is handling of null/missing values. Handlings of null values have been a great bit of test for researcher. Various methods are available for estimation of null value such as k-means clustering algorithm, MARE al gorithm and fuzzy logic approach. Although all these process are notalways efficient. We propose an efficient approach for handling null value s in web log. We are using a hybrid tabu search– k nearest neighbor classifier with multiple distance function. Tabu search– KNN classifier perform feature selection of K-NN rules. We are handling null values efficiently by u sing different distance function. It is called Ensemble of function. It gives different set of feature vector. Feature selection is useful for improving the classification accuracy of NN rule. We are using different distance metric with different set of feature, so it reduces the possibility that some error will common.Therefore, proposed method is better for handling null values. The proposed method is using hybrid classifier with different distance metrics and different feature vector . It is evaluated using our MANIT database.Results have indicated that a significant increase in the performance when compared with simple K -NN classifier.
Quantitative Trading: How to Build Your Own Algorithmic Trading Business

Preface. Acknowledgments. Chapter 1: The Whats, Whos, and Whys of Quantitative Trading. Who Can Become A Quantitative Trader? The Business Case for Quantitative Trading. Scalability. Demand on Time. The Nonnecessity of Marketing. The Way Forward. Chapter 2: Fishing for Ideas. How to Identify a Strategy That Suits You. Your Working Hours. Your Programming Skills. Your Trading Capital. Your Goal. A Taste for Plausible Strategies and Their Pitfalls. How Does It Compare with a Benchmark and How Consistent Are Its Returns? How Deep and Long is the Drawdown? How Will Transaction Costs Affect the Strategy? Does the Data Suffer from Survivorship Bias? How Did the Performance of the Strategy Change Over the Years? Does the Strategy Suffer from Data-Snooping Bias? Does the Strategy "Fly under the Radar" of Institutional Money Managers? Summary. Chapter 3: Backtesting. Common Backtesting Platforms. Excel. MATLAB. TradeStation. High-End Backtesting Platforms. Finding and Using Historical Databases. Are the Data Split- and Dividend-Adjusted? Are the Data Survivorship Bias Free? Does Your Strategy Use High and Low Data? Performance Measurement. Common Backtesting Pitfalls to Avoid. Look-Ahead Bias. Data-Snooping Bias. Transaction Costs. Strategy Refinement. Summary. Chapter 4: Setting up Your Business. Business Structure: Retail or Proprietary? Choosing a Brokerage or Proprietary Trading Firm. Physical Infrastructure. Summary. Chapter 5: Execution Systems. What an Automated Trading System Can Do for You. Building a Semiautomated Trading System. Building a Fully Automated Trading System. Minimizing Transaction Costs. Testing Your System by Paper Trading. Why Does Actual Performance Diverge from Expectations? Summary. Chapter 6: Money and Risk Management. Optimal Capital Allocation and Leverage. Risk Management. Psychological Preparedness. Summary. Appendix: A Simple Derivation of the Kelly Formula when Return Distribution is Gaussian. Chapter 7: Special Topics in Quantitative Trading. Mean-Reverting versus Momentum Strategies. Regime Switching. Stationarity and Cointegration. Factor Models. What Is Your Exit Strategy? Seasonal Trading Strategies. High-Frequency Trading Strategies. Is it Better to Have a High-Leverage versus a High-Beta Portfolio? Summary. Chapter 8: Conclusion: Can Independent Traders Succeed? Next Steps. Appendix: A Quick Survey of MATLAB. Bibliography. About the Author. Index.
Were there Anomalies in the Sterling-Franc Exchange Rate Regulation during the Mid-19th Century?

In this paper, we test whether French and British central banks discount rates were an efficient tool for currency stabilisation over the 1850-1870 period. Causality and impulse analysis as well as outlier methodology are carried out in order to test this proposition. We give strong evidence that the discount rate differential between France and England had a crucial corrective influence on the Sterling-Franc spot exchange rate. Regarding this exchange rate regulation hypothesis, we find only one single anomaly which occurred in February 1861. The assessment of the historical context helps to understand this peculiar event. We conclude to the absence of anomalies in the Sterling-Franc exchange rate regulation over the 1850-1870 period.
Strategic Alliances, Equity Stakes, and Entry Deterrence

I study how strategic alliances and their impact on future competitive incentives can motivate interfirm equity sales. In the model, an alliance between an entrepreneurial firm and an established firm improves efficiency for both. However, the requisite knowledge transfer heightens the established firm's incentive to enter one of its partner's markets. I show that equity can eliminate the entry incentive, but accommodation is sometimes chosen to encourage entrepreneurial effort on future growth options. I analyze stake sizes, block pricing, and stock returns. The results have implications for equity alliances, corporate venture capital, and the organization of research activities.
Monitoring human larynx by random forests using questionnaire data

This paper is concerned with noninvasive monitoring of human larynx using subject's questionnaire data. By applying random forests (RF), questionnaire data are categorized into a healthy class and several classes of disorders including: cancerous, noncancerous, diffuse, nodular, paralysis, and an overall pathological class. The most important questionnaire statements are determined using RF variable importance evaluations. To explore multidimensional data, t-Distributed Stochastic Neighbor Embedding (t-SNE) and multidimensional scaling (MDS) are applied to the RF data proximity matrix. When testing the developed tools on a set of data collected from 109 subjects, 100% classification accuracy was obtained on unseen data coming from two — healthy and pathological — classes. The accuracy of 80.7% was achieved when classifying the data into the healthy, cancerous, and noncancerous classes. The t-SNE and MDS mapping techniques facilitate data exploration aimed at identifying subjects belonging to a ”risk group”. It is expected that the developed tools will be of great help in preventive health care in laryngology.
A hybrid framework for modelling and simulation for deshopping behaviour and how companies respond

Deshopping is rapidly turning into a modern day scourge for the retailers due to its prevalence and regularity. The presence of flexible return policies have made retail return management a real challenging issue for both the present and the future. In this paper, we propose a hybrid framework for modelling, simulating and analysing deshopper behavior, company reaction policies, and strategic initiatives for reduce exposure and protect ethical consumer returns. The strengths of the analytic hierarchy process, simulation with animation techniques, expert system approach, intelligent software agent method, and complex adaptive system theory are utilised and combined to deal with the deshopping problem as it occurs in fashion retailers with both online and offline presences. Relevant concepts, theoretical rationale and paradigm are presented and discussed in the paper.
Sentiment Classification for Chinese Netnews Comments Based on Multiple Classifiers Integration

With the development of World Wide Web technologies, more and more netizens express their opinions on society and politics in net news comments. Sentiment classification is one of the most important sub-problems of opinion mining, which can classify net news comments as positive or negative to help government automatically identify the netizens' viewpoints on news event and make right decision or help enterprises find out weather the customers satisfy the products or not. Most of the researches for sentiment classification only use single classifier, such as kNN, Naive Bayes and Support Vector Machine (SVM). In this paper, we use two multiple classifiers integration algorithms, which are Bagging and Boosting, to conduct the sentiment classification. Different feature selection methods are also investigated. The result of experiment shows that AdaBoost approach, a type of Boosting, usually achieve better performance than Bagging and single classifier and feature selection based on statistic is better than POS-based method for sentiment classification of Chinese net news comments.
Intragenerational equity : a new name for international environmental justice

In August 2002 the world converged on South Africa for the purpose of thrashing out a plan to save the environment and its inhabitants. The World Summit was intended to build on the successes of earlier such conferences, namely the Rio Summit on Environment and Development and the Stockholm Conference on the Human Environment. In particular the World Summit was supposed to give effect to the aspirations of the earlier conferences by, for example, setting specific targets for implementation.
Cascaded Movement Strategy for Repairing Coverage Holes in Wireless Sensor Networks

In wireless sensor networks (WSN), in order to move mobile sensors to repair coverage holes caused by sensor nodes who can not work normally due to all kinds of reasons, a cascaded movement is used in this paper. It introduces the cascaded movement by describing how to choose intermediate nodes and right cascaded routes. Using intermediate nodes to participate in moving mobile sensors, it increases the movement distance, but reduces the movement delay and balances the energy of every sensor node. Also, it defines a standard for choosing appropriate cascaded routes, which is the minimum difference between total energy consumption and minimum remaining energy. Compared with moving mobile sensors directly in the proxy-based bidding protocol, the simulation results show that the cascaded movement not only makes full use of the energy in networks, but also extends the network lifetime. Its performances are superior to directly move mobile sensors.
A multi-camera approach to sensor evaluation in video surveillance

In this paper, we provide an objective sensor performance evaluation approach to automatically carry out the sensor evaluation task in a multi-sensor system for video surveillance. That is, given a set of sensors monitoring the same area, the proposed technique estimates the accuracy of each sensor in detecting a given target. This measure depends on the conditions under which the sensor is operating and is computed per sensor and per target at every time instant. In this way, data coming from the different sensors may be weighted accordingly and fused. Promising experimental results are presented on real video sequences.
Political Partisanship and Welfare State Reform in Advanced Industrial Societies

In this article we evaluate two claims made in recent studies of the welfare states of advanced industrial societies: first, that welfare states have remained quite resilient in the face of demands for retrenchment; and second, that partisan politics have ceased to play a decisive role in their evolution. Addressing the first claim, we present analysis from a new data set on unemployment insurance and sickness benefit replacement rates for 18 countries for the years 1975‐99. We find considerably more evidence of welfare retrenchment during the last two decades than do recent cross-national studies. Second, we examine the “end of partisanship” claim by estimating the effects of government partisanship on changes in income replacement rates in sickness and unemployment programs. Our results suggest that, contrary to claims that partisanship has little impact on welfare state commitments, traditional partisanship continues to have a considerable effect on welfare state entitlements in the era of retrenchment.