Miracle-dz/UniFAR-FTUs huggingface dataset:
Performance Indicators and their Relationship with Organizational Strategy - A Study in Brazilian Companies

The institutional mission declared by an organization can be taken as baseline for management as well as a mechanism for communicating its objectives and organizational strategies. In a complementary fashion, performance indicators support the evaluation of the processes aimed to execute companies specific strategies. Thus, the present study sought, through an empirical quantitative approach, test the hypothesis of the performance indicators used by a company is associated with the content of the mission it declares. A sample of 85 Brazilian companies listed in BM&FBovespa’s IbrX Index was used. Data has been extracted from the mandatory reference reports issued annually by companies and from its institutional sites. For examination of the data, the technique of content analysis was used in order to identify the characteristics present in the missions reported by the companies studied. Further, the logistic regression was used to test the association between the variables studied. In the context analyzed, no evidence of association between the characteristics of the missions reported by the companies and the performance indicators used by them was observed in the results. The results found contradict, in part, the logic and theory of organizations management control, especially regarding the congruence amongst the objectives that must be pursued, including the alignment of what an organization declared as being relevant in its mission with the indicators it uses to evaluate its performance. Finally, Business Process Management (BPM) is discussed as a fundamental support for the definition of performance indicators in order to guarantee the alignment to the organization’s strategic objectives.
Robust linear anti‐windup synthesis for recovery of unconstrained performance

Fixed order anti‐windup augmentation is addressed by considering the dynamics of the mismatch between the constrained and unconstrained responses. The method utilizes LMIs, and the result parallels other recent LMI‐based anti‐windup synthesis methods. Robustness is directly addressed—which is not done in previous LMI work on anti‐windup. An optimal LMI‐based synthesis procedure is provided for static and plant‐order linear anti‐windup augmentation and the performance of the resulting design strategy is shown via a simulation example. Copyright © 2004 John Wiley & Sons, Ltd.
A preliminary analysis of loss synchronisation between concurrent TCP flows

This paper introduces a preliminary study of synchronisation between packet loss events across concurrent TCP flows. Loss synchronisation is explored over four routing paths – one inside Australia and three international paths (Australia to Asia, Europe and North America respectively). We confirm that loss synchronisation does exist but the level varies from path to path. We outline further work that is required to improve our understanding of loss synchronisation.
Automatic Detection of Social Tag Spams Using a Text Mining Approach

Social tags are annotations for Web pages collaboratively added by users. It will be much easier to understand the meaning of Web pages and classify them according to their tags. The precision in retrieving Web pages may also increase using such tags. Nowadays social tags are mostly annotated manually by users via social bookmarking Web sites. Such manual annotation process may produce diverse, redundant, and inconsistent tags. Besides, many tags which are inconsistent with their annotated Web pages exist and deteriorate the feasibility of social tags. In this work we will develop an automatic scheme to discover the associations between Web pages and social tags and apply such associations on applications of social tag spam detection. We applied a text mining approach based on self-organizing maps to find the relationships between Web pages and social tags. The disadvantages of manual annotation will be remedied through such relationships. The discovered associations were then used to identify social tag spams. Preliminary experiments show that the quality and usability of social tags were improved through this method.
Age Shall Not Weary Us: Deleterious Effects of Self-Regulation Depletion Are Specific to Younger Adults

Self-regulation depletion (SRD), or ego-depletion, refers to decrements in self-regulation performance immediately following a different self-regulation-demanding activity. There are now over a hundred studies reporting SRD across a broad range of tasks and conditions. However, most studies have used young student samples. Because prefrontal brain regions thought to subserve self-regulation do not fully mature until 25 years of age, it is possible that SRD effects are confined to younger populations and are attenuated or disappear in older samples. We investigated this using the Stroop color task as an SRD induction and an autobiographical memory task as the outcome measure. We found that younger participants (<25 years) were susceptible to depletion effects, but found no support for such effects in an older group (40–65 years). This suggests that the widely-reported phenomenon of SRD has important developmental boundary conditions casting doubt on claims that it represents a general feature of human cognition.
Chemistry in disks. I. Deep search for N2H+ in the protoplanetary disks around LkCa 15, MWC 480, and DM Tauri

Aims.To constrain the ionization fraction in protoplanetary disks, we present new high-sensitivity interferometric observations of N2H+ in three disks surrounding DM Tau, LkCa 15, and MWC 480. Methods: We used the IRAM PdBI array to observe the N2H+ J=1-0 line and applied a ? ^2-minimization technique to estimate corresponding column densities. These values are compared, together with HCO+ column densities, to results of a steady-state disk model with a vertical temperature gradient coupled to gas-grain chemistry. Results: We report two N2H+ detections for LkCa 15 and DM Tau at the 5 ? level and an upper limit for MWC 480. The column density derived from the data for LkCa 15 is much lower than previously reported. The [ N2H^+/HCO^+] ratio is on the order of 0.02-0.03. So far, HCO+ remains the most abundant observed molecular ion in disks. Conclusions: . All the observed values generally agree with the modelled column densities of disks at an evolutionary stage of a few million years (within the uncertainty limits), but the radial distribution of the molecules is not reproduced well. The low inferred concentration of N2H+ in three disks around low-mass and intermediate-mass young stars implies that this ion is not a sensitive tracer of the overall disk ionization fraction. Based on observations carried out with the IRAM Plateau de Bure Interferometer. IRAM is supported by INSU/CNRS (France), MPG (Germany) and IGN (Spain). Research partially supported by PCMI, the French national program for the Physics and Chemistry of the Interstellar Medium.
Action classification of humanoid soccer robots using machine learning

This paper presents an alternative approach on humanoid soccer robots action classification in order to seize the ball control and better ball possession using machine learning and data mining classification algorithms. Categorizing proper actions regarding to positional and environmental features is a prerequisite for proper acting in robotics. In this paper we present an approach to gather information and extracting useful features out of that information from SimSpark simulation server logs. These gathered data will generate a meaningful multi-class dataset, afterwards data processing and running appropriate data mining algorithms on the dataset and evaluating our experiments are the most important issues in this paper. In order to achieve a model for classifying our multi-class dataset, we applied two well-known applications from the domain of data mining: TANAGRA and WEKA and finally we have visualized our experimental results as far as possible.
A new conceptual model for business ecosystem visualization and analysis

This study has the objective of plotting the effects of network externalities and superstar software for the visualization and analysis of industry ecosystems. The output is made possible by gathering sales from a tracking website, associating each sale to a single consumer and by using a network visualization software. The result is a graph that shows strategic positioning of publishers and platforms, serving as a strategic tool for both academics and professionals. The approach is scalable to other industries and can be used to support analysis on mergers, acquisitions and alliances.
Narrating experience: the advantage of using mixed expressive media to bring autistic voices to the fore in discourse around their support requirements

This study explores methods of shifting the power imbalance within autism research by acknowledging the autistic voice as the expert ‘insider’. This is critical, since statistics relating to access to services demonstrate social barriers to inclusion and a negative impact on wellbeing. With communication as a central challenge between autistic and non-autistic individuals, I explore methods to access the views of autistic adults regarding their experiences, support requirements and provision of appropriate services. In order to do this, my main research question concerns the deeper exploration of data informing an evaluation of a support service to understand how some autistic individuals conceptualise their experiences. My research design, informed by autistic people, focused on context and power issues through method flexibility. I used collage and narrative diary methods to gather written and visual data, which is presented and analysed as three individual case studies and also as a meta analysis providing a broad picture of themes. My key contribution to autism research blends IPA, narrative analysis and discourse with distinct sites of analysis (narrative process, images of autism, audiencing, turning points and discourse). In addition, I employ a flexible methodology to embrace diverse communication preferences of autistic individuals. My findings demonstrate the importance of contextualisation in making sense of autistic individuals’ experiences and understanding how the ‘outsider’ location of power can negatively impact on the autistic agenda. To address this, autistic people need to be seen as the expert of their lives, and this study demonstrates how autistic and non-autistic individuals can work together.
Improving the Computing Efficiency of HPC Systems Using a Combination of Proactive and Preventive Checkpointing

As the failure frequency is increasing with the components count in modern and future supercomputers, resilience is becoming critical for extreme scale systems. The association of failure prediction with proactive checkpointing seeks to reduce the effect of failures in the execution time of parallel applications. Unfortunately, proactive checkpointing does not systematically avoid restarting from scratch. To mitigate this issue, failure prediction and proactive checkpointing can be coupled with periodic checkpointing. However, blind use of these techniques does not always improves system efficiency, because everyone of them comes with a mix of overheads and benefits. In order to study and understand the combination of these techniques and their improvement in the system's efficiency, we developed: (i) a prototype combining state of the art failure prediction, fast proactive checkpointing and preventive checkpointing; (ii) a mathematical model that reflects the expected computing efficiency of the combination and computes the optimal checkpointing interval in this context; (iii) a discrete event simulator to evaluate the computing efficiency of the combination for system parameters corresponding to the current and projected large scale HPC systems. We evaluate our proposed technique on a large supercomputer (i.e. TSUBAME2) with production-level HPC applications and we show that failure prediction, proactive and preventive checkpointing can be coupled successfully, imposing only about 2% to 6% of overhead in comparison with preventive checkpointing only. Moreover, our model-based simulations show that the optimal solution improves the computing efficiency up to 30% in comparison with classic periodic checkpointing. We show that the prediction recall has a much higher impact on execution efficiency than the prediction precision. This result suggests that researchers on failure prediction algorithms should focus on improving the recall. We also show that the combination of these techniques can significantly improve (by a factor 2, for a particular configuration) the mean time between failures (MTBF) perceived by the application.
Social Issues in Management as a Distinct Field: Corporate Social Responsibility and Performance

This article focuses on the question of whether Social Issues in Management (SIM) is a “field” and, if so, what kind, emphasizing specifically the recent literature on corporate social responsibility and performance (CSR/CSP). Fields are defined in part by coherent bodies of knowledge that serve as guideposts for current research, and so the authors construct a simple model of CSR/CSP scholarship, illustrating the relevant categories with representative publications. The authors conclude that SIM is a “low-paradigm” field but is not recognized or accepted as a field by many scholars who write about CSR/CSP from “outside” the field. This analysis points to the need for SIM scholars to continue to integrate useful ideas from other fields, and also to critique the work of scholars who address “failings” or “gaps” in SIM research without appropriately dealing with the existing SIM literature. The article concludes with some ideas for sustaining the institutional legitimacy of SIM and for challenging those who would “reinvent” a field with a long and fruitful history, including paying careful attention to journal review processes and the content of publications in prominent journals.
Session Segmentation Based on Document Metadata

It has been shown that the search personalization can greatly benefit from exploiting user’s short-term context – his immediate needs and focus. But to achieve that, we need to be able to tell when the context changes; we need to be able to divide the user’s activity into segments, where each segment captures user’s single goal and focus. Many different approaches exist, but their major weakness is that they build inaccurate models that do not include user’s implicit feedback. We present a method for segmenting queries into search sessions which is based on document metadata and incorporates implicit feedback and as such is able to build more accurate context model.
THEIR REMOVAL USING INPAINTING

In this paper, we propose an algorithm that automatically detects and removes moving logos in video. The proposed algorithm consists of logo detection, tracking and extraction, and removal. In the logo detection step, we automatically detect moving logos using the saliency map and the scale invariant feature transform. In the logo tracking and extraction step, an improved mean shift tracking method and backward tracking technique are used in which only logo regions are extracted by using color information. Finally, in the logo removal step, the detected logo region is filled with the region of neighborhood using an exemplar-based inpainting that can fill a large detected region without artifacts. These steps are effectively interconnected using control flags. Experimental results with various test sequences show that the proposed algorithm is effective to detect, track, and remove moving logos in video.
DCU 250 Arabic Dependency Bank: An LFG Gold Standard Resource for the Arabic Penn Treebank

This paper describes the construction of a dependency bank gold standard for Arabic, DCU 250 Arabic Dependency Bank (DCU 250), based on the Arabic Penn Treebank Corpus (ATB) (Bies and Maamouri, 2003; Maamouri and Bies, 2004) within the theoretical framework of Lexical Functional Grammar (LFG). For parsing and automatically extracting grammatical and lexical resources from treebanks, it is necessary to evaluate against established gold standard resources. Gold standards for various languages have been developed, but to our knowledge, such a resource has not yet been constructed for Arabic. The construction of the DCU 250 marks the first step towards the creation of an automatic LFG f-structure annotation algorithm for the ATB, and for the extraction of Arabic grammatical and lexical resources.
The CloudProxy Tao for Trusted Computing

Applications running in a cloud data center face several challenges, including secure deployment, insider attacks, and cryptographic key management. Previous research shows how to securely start and run individual programs using the Trusted Platform Module or other secure co-processors, but none of that work solves the end-to-end problem of deploying and gaining assurance in distributed applications running on third-party hardware. And key management in existing systems often requires trust in potentially untrustworthy certificate authorities. CloudProxy is a new framework that provides secure deployment of applications to the cloud, defends against insider attacks, and provides protocols for automatic key management. Data managed by CloudProxy is never stored or transmitted in unencrypted form, and cryptographic keys are provisioned in a way that defends against malicious operators or other data-center insiders. Protocols are provided for remote or local clients to authenticate the executable and execution environment of a server and for a server to authenticate the executable and execution environment of its clients. Three prototype applications were implemented to evaluate the utility of CloudProxy: FileProxy, a file service; AuthProxy, an authentication service for remote third parties; and BidProxy, an auction service. Performance measurements show that CloudProxy is a practical way to support secure, distributed applications.
The higher the pitch the larger its crossmodal influence on visuospatial processing

High-pitched sounds generate larger neural responses than low-pitched sounds. We investigated whether this neural difference has implications, at cognitive level, for the “vertical” representation of pitch. Participants performed a speeded detection of visual targets that could appear at one of four different spatial positions. Rising or falling frequency sweeps were randomly presented before the visual target. Faster reaction times to visual targets appearing above (but not below) a central fixation point were observed after the presentation of rising frequencies. No significant effects were found for falling frequency sweeps and visual targets presented below fixation point. These results suggest that the difference in the level of arousal between rising and falling frequencies influences their capacity for generating spatial representations. The fact that no difference was found, in terms of crossmodal effects, between the two upper positions may indicate that this “spatial representation of pitch” is not specific for any particular spatial location but rather has a widespread influence over stimuli appearing in the upper visual field. The present findings are relevant for the study of music performance, the design of musical instruments, and research in areas where visual and auditory stimuli with certain complexity are combined (music in advertisements, movies, etc.).
Haptic shared control improves tele-operated task performance towards performance in direct control

In tele-operation, haptic feedback from the remote environment to the human is often limited, which has been shown to negatively influence the performance and required time of tasks. The conventional research focus is on improving the quality of the haptic feedback (transparency), which may have led to significant improvement, but is still imperfect, with many unresolved issues. The present study presents an alternative approach to improve tele-operated tasks: by offering haptic shared control in which both operator and support system apply the required forces at the input (master) device. It is hypothesized that virtual forces from well-designed shared control will improve required time and accuracy, with less control effort, and that these benefits exist for perfect transparency but even more so for imperfect transparency. In an experimental study haptic shared control was designed to aid operators (n=9) with performing a simple bolt-spanner task using a planar (2D, 3DOF) tele-operator setup. The experimental results provided evidence for the hypotheses, showing that the tested tele-manipulation task benefits from haptic shared control, for three different levels of transparency. Essentially, the presence of haptic shared control allows for a worse transparency without compromising required time, and can even improve required time during perfect transparency.
Tension optimization for the dynamic model of cable-driven humanoid arm

A human upper-limb endoskeleton has 7 degrees of freedom to achieve various tasks dexterously. Therefore, the biological structures of human arm are attractive to researchers, and in this paper, a 7-DOF (degree of freedom) humanoid arm with cable-driven is presented. For CDHA inheriting the human arm's natural features, it is expected to possess the remarkable advantages of a human arm. Then a critical issue, i.e., the dynamic modeling of the CDHA is conducted based on Lagrangian formulation. For more effective tension control, the optimization method of cable tension distribution is addressed with some restrictions, that is, limiting torque constraints of actuators, tension constraints, controllable workspace and motion performance. At last, several simulations in MATLAB of the dynamic model and tension optimization algorithm are illustrated.
Joint modelling of repeated measurement and time-to-event data: an introductory tutorial.

BACKGOUND The term 'joint modelling' is used in the statistical literature to refer to methods for simultaneously analysing longitudinal measurement outcomes, also called repeated measurement data, and time-to-event outcomes, also called survival data. A typical example from nephrology is a study in which the data from each participant consist of repeated estimated glomerular filtration rate (eGFR) measurements and time to initiation of renal replacement therapy (RRT). Joint models typically combine linear mixed effects models for repeated measurements and Cox models for censored survival outcomes. Our aim in this paper is to present an introductory tutorial on joint modelling methods, with a case study in nephrology. METHODS We describe the development of the joint modelling framework and compare the results with those obtained by the more widely used approaches of conducting separate analyses of the repeated measurements and survival times based on a linear mixed effects model and a Cox model, respectively. Our case study concerns a data set from the Chronic Renal Insufficiency Standards Implementation Study (CRISIS). We also provide details of our open-source software implementation to allow others to replicate and/or modify our analysis. RESULTS The results for the conventional linear mixed effects model and the longitudinal component of the joint models were found to be similar. However, there were considerable differences between the results for the Cox model with time-varying covariate and the time-to-event component of the joint model. For example, the relationship between kidney function as measured by eGFR and the hazard for initiation of RRT was significantly underestimated by the Cox model that treats eGFR as a time-varying covariate, because the Cox model does not take measurement error in eGFR into account. CONCLUSIONS Joint models should be preferred for simultaneous analyses of repeated measurement and survival data, especially when the former is measured with error and the association between the underlying error-free measurement process and the hazard for survival is of scientific interest.