Miracle-dz/UniFAR-FTUs huggingface dataset:
Truthful Feedback for Sanctioning Reputation Mechanisms

For product rating environments, similar to that of Amazon Reviews, it has been shown that the truthful elicitation of feedback is possible through mechanisms which pay buyer reports contingent on the reports of other buyers. We study whether similar mechanisms can be designed for reputation mechanisms at online auction sites where the buyers' experiences are partially determined by a strategic seller. We show that this is impossible for the basic setting. However, introducing a small prior belief that the seller is a cooperative commitment player leads to a payment scheme with a truthful perfect Bayesian equilibrium.
A new clustering method for collaborative filtering

Collaborative filtering, which predicts unknown ratings by analyzing the known ratings, is regarded as one of the most successful recommender systems within the last decade. In the process of collaborative filtering, clustering methods can recognize similar users and items. Then different methods can be applied to process different clusters. By these means, the accuracy and scalability of algorithms can be improved. Though the clustering methods for collaborative filtering have plenty of applications, they have long been neglected. The similarity measure for clustering was confused with the similarity measure for collaborative filtering. In this paper, we propose a new similarity measure for clustering and its application. Firstly, we use a basic similarity function to discover neighbor vectors of items. Secondly, we calculate the cosine similarity of the neighbor vectors for clustering. Thirdly, we finish the clustering process by using adjusted DBSCAN. For those users having many known ratings, we adjust the prediction function by adding a parameter which is the function of the item cluster size. The experiments on the grouplens dataset show that our method outperforms the previous methods and has been proved in many clustering applications in the field of collaborative filtering. For those users having many known ratings, our application method of clustering improves the prediction accuracy.
Retrieval of Effective Leaf Area Index in Heterogeneous Forests With Terrestrial Laser Scanning

Terrestrial laser scanner (TLS)-based leaf area index (LAI) retrieval is an appealing concept, due to the ability to capture structural information of canopies as 3-D point cloud data (PCD). TLS-based LAI estimation methods promise a nondestructive tool for spatially explicit calibration of LAI estimated by aerial or satellite remote sensing techniques. These methods also overcome the sky condition restrictions of on-ground optical instruments such as hemispherical photography frequently used for LAI estimation. This paper presents a new method for estimating the effective LAI (LAIe) directly from PCD generated by TLS in heterogeneous forests. We converted the 3-D PCD into 2-D raster images, similar to hemispherical photographs, using two geometrical projection techniques in order to estimate gap fraction and LAIe using a linear least squares method. Our results indicated that the TLS-based algorithm was able to capture the variability in LAIe of forest stands with a range of densities. The TLS-based LAIe estimation method explained 89.1% (rmse = 0.01 ; p <; 0.001) of the variation in results from digital hemispherical photographs taken of the same stands and used for validation. The Breusch-Pagan test score confirmed that the stereographic-projection-based TLS LAIe model was more robust compared to the Lambert azimuthal equal-area projection TLS LAIe model. Finally, we explore and show significant relationships between airborne-laser-scanner (ALS)-based and TLS-based LAIe estimates, showing promise for further exploration of utilizing TLS as a calibration tool for ALS.
An agent-based structure for mobile robots using vision and ultrasonic sensors

Object recognition is an important task associated with mobile robot navigation. Upon detecting any obstacle, the recognition system must be able to say which obstacle is in the robot's trajectory, so that the control system is able to plan a new trajectory for the robot, deviating from the detected obstacle or following it, depending on the obstacle. It is normally necessary to recognize a few obstacles that are commonly present in the robot operating environment. In this paper, a system is proposed to perform the task of recognizing the objects present in the trajectory of a mobile robot. This system is based on information coming from ultrasonic sensors and a digital monochromatic camera. The operation of this system is addressed and an example of object detection and recognition is presented.
Medical case-driven classification of microblogs: characteristics and annotation

In this paper, we study the use of microblogs as source of information for medical intelligence gathering. The huge amount of irrelevant data available in microblogs requires sophisticated filtering methods in order to identify only relevant postings. Microblogs are characteristically sparse and noisy. This requires additional considerations for selection of features for automatic classification for relevance with respect to medical intelligence gathering. In this paper, we will analyze which features are well suited. The objective of this work is three-fold: 1) Specifying annotation guidelines for creating a dataset for microblog classification, 2) Studying the characteristics of tweets for deciding on a well suited feature set, and 3) making use of that feature set in an automatic classification system for relevance filtering of microblogs. The quality of the classifier is assessed in experiments with various feature sets. The evaluation shows that despite the challenging characteristics of mircoblogs, good accuracy values of up to 89% can be achieved by the classifier. One main outcome of this work is a data set of annotated twitter data which can be used as a "gold standard" benchmark for further research in this domain.
Optimisation of Parameters Affecting the Performance of Single Compartment CEDI Unit

The present work describes the production of the ultrapure water using Continuous Electro-deionization (CEDI) method. The CEDI unit consist of ion exchange membranes, Mixed Bed-12 (MB-12) ion exchange resin and electrodes to remove ion impurities from feed water. The product water from the RO unit is supplied to the CEDI unit. The Quality of the ultra-pure water is determined by the amount of ions present in the water. Higher quality of Ultra-pure water is obtained when the maximum number of ions is transferred through the membranes. The Parameters affecting the performance of the CEDI unit are identified and optimized for maximum ions exchange. In order to reduce the number of experiments Taguchi method was used for optimisation of operating parameters. An orthogonal L array (three factor and three level) was employed to evaluate the effect of feed concentration (35,40and 45 ppm), Flow rate (8, 9 and 10 LPH) and voltage (22, 23, 24 volts). Thus it was observed that increasing the applied voltage anddecreasing the waterflow rateincreases the number of ions transfers through the membrane. However, decreasing water flow rate has certain limits as it decreases the production capacity of the unit. Also it is observed that decreasing the ions in the feed water decreases the overall transfer of ions.
Diagnosing and Changing Organizational Culture: Based on the Competing Values Framework

Preface. Acknowledgments. The Authors. 1. An Introduction to Changing Organizational Culture. The Need to Manage Organizational Culture. The Need for Culture Change. The Power of Culture Change. The Meaning of Organizational Culture. Caveats. 2. The Organizational Culture Assessment Instrument. Instructions for Diagnosing Organizational Culture. Scoring the OCAI. 3. The Competing Values Framework. The Value of Frameworks. Development of the Competing Values Framework. The Four Major Culture Types. Applicability of the Competing Values Model. Total Quality Management. Human Resource Management Roles. Culture Change over Time. Culture Change in a Mature Organization. Summary. 4. Constructing an Organizational Culture Profile. Plotting a Profile. Interpreting the Culture Profiles. Summary. 5. Using the Framework to Diagnose and Change Organizational Culture. Planning for Culture Change: An Example. Steps for Designing an Organizational Culture Change Process. Supplementing the OCAI Methodology. 6. Individual Change as a Key to Culture Change. Critical Management Skills. Personal Management Skills Profile. Personal Improvement Agendas. 7. A Condensed Formula for Organizational Culture Change. Appendix A: Organizational Culture Assessment Instrument (OCAI): Definition, Dimensions, Reliability, and Validity. Appendix B: Psychometric Analyses of the Management Skills Assessment Instrument (MSAI). Appendix C: Hints for Initiating Organizational Culture Change in Each Quadrant. Appendix D: Suggestions for Improving Personal Management Competencies. Appendix E: Forms for Plotting Profiles. References and Suggested Reading. Index.
Therapeutic gene transfer to the nervous system using viral vectors

The past few years have been marked by substantial progress in preclinical studies of therapeutic gene transfer for neurologic disease using viral-based vectors. In this article, the authors review the data regarding (1) treatment of focal neuronal degeneration, exemplified by Parkinson disease, ischemia, and trauma models; (2) treatment of global neurologic dysfunction, exemplified by the mucopolysaccharidoses and other storage diseases; (3) peripheral nervous system diseases including motor neuron disease and sensory neuropathies; and (4) the use of vectors expressing neurotransmitters to modulate functional neural activity in the treatment of pain. The results suggest that a number of different viral vectors may be appropriate for gene transfer to the central nervous system for specific disease processes, and that for the peripheral nervous system herpes simplex virus-based vectors appear to have special utility. The results of the first human gene therapy trials for neurologic disease, which are just now beginning, will be crucial in defining the next step in the development of this therapy.
Global Planning for Dexterous Reorientation of Rigid Objects: Finger Tracking with Rolling and Sliding

We address global motion planning for quasi-static reorientation of convex objects (polyhedral and smooth objects) with a four-fingertip grasp. We make use of a simple humanlike manipulation strategy in which a single finger is moved at each instant while the other three are maintained fixed (with regard to the palm)—an extended version of the original finger-tracking scheme of Rus. This new version es sentially incorporates frictional rolling and sliding at the fingertips and deals with the related contact kinematics and quasi-static mo tion/force prediction issues. Our contribution is twofold. First, we describe an analysis showing that this extended scheme is suitable for reducing the space of the object motions, thereby making motion planning easier and operating on a search space of low dimension. Our second contribution is a planner that exploits such a search space reduction and applies the extended finger tracking at the core of a multilevel hierarchical framework to search for global reorien tation trajectories. The planner has been implemented and used for achieving several nontrivial frictional reorientation tasks that show the capabilities and the promise of our approach.
Research on pedestrian detection algorithms based on video

On the basic of the video traffic surveillance system, the pedestrian detection is a crucial part. A study on vehicle and pedestrian recognition based on back propagation (BP) neural network is presented in this paper, and the author puts forward an effective algorithm for pedestrian detection. First, extract the moving objects from the image sequence using background subtraction. Second, select part of the objects for further detected. Most of the moving objects, which can be determined as vehicles would be excluded in the pretreatment. Third, extract several significant eigenvalues from the rest objects, which can indicate the differences of contour between pedestrian and vehicle. Finally, eigenvector is formed and used as the input of the back propagation neural network, the output of which is the detecting result. The BP neural network is trained and used to identify pedestrian, experiment results of which are analyzed. It has been proved that the algorithms proposed in this paper have satisfactory real-time performance and accuracy.
Restricted Low-Rank Approximation via ADMM

The matrix low-rank approximation problem with additional convex constraints can find many applications and has been extensively studied before. However, this problem is shown to be nonconvex and NP-hard; most of the existing solutions are heuristic and application-dependent. In this paper, we show that, other than tons of application in current literature, this problem can be used to recover a feasible solution for SDP relaxation. By some sophisticated tricks, it can be equivalently posed in an appropriate form for the Alternating Direction Method of Multipliers (ADMM) to solve. The two updates of ADMM include the basic matrix low-rank approximation and projection onto a convex set. Different from the general non-convex problems, the sub-problems in each step of ADMM can be solved exactly and efficiently in spite of their non-convexity. Moreover, the algorithm will converge exponentially under proper conditions. The simulation results confirm its superiority over existing solutions. We believe that the results in this paper provide a useful tool for this important problem and will help to extend the application of ADMM to the non-convex regime.
Familiarity affects the same event-related brain potential components in note readers and non-note readers

Musical expertise can lead to neural plasticity in specific cognitive domains (e.g., in auditory music perception). However, not much is known about whether the visual perception of simple musical symbols (e.g., notes) already differs between musicians and non-musicians. This was the aim of the present study. Therefore, the Familiarity Effect (FE) – an effect which occurs quite early during visual processing and which is based on prior knowledge or expertise – was investigated. The FE describes the phenomenon that it is easier to find an unfamiliar element (e.g., a mirrored eighth note) in familiar elements (e.g., normally oriented eighth notes) than to find a familiar element in a background of unfamiliar elements. It was examined whether the strength of the FE for eighth notes differs between note readers and non-note readers. Furthermore, it was investigated at which component of the event-related brain potential (ERP) the FE occurs. Stimuli that consisted of either eighth notes or vertically mirrored eighth notes were presented to the participants (28 note readers, 19 non-note readers). A target element was embedded in half of the trials. Reaction times, sensitivity, and three ERP components (the N1, N2p, and P3) were recorded. For both the note readers and the non-note readers, strong FEs were found in the behavioral data. However, no differences in the strength of the FE between groups were found. Furthermore, for both groups, the FE was found for the same ERP components (target-absent trials – N1 latency; target-present trials – N2p latency, N2p amplitude, P3 amplitude). It is concluded that the early visual perception of eighth note symbols does not differ between note readers and non-note readers. However, future research is needed to verify this for more complex musical stimuli and for professional musicians.
Human Behavior Analysis Using Multiple 2D Features and Multicategory Support Vector Machine

In this study, a human behavior analysis system using multiple 2D (two-dimensional) features and a multicategory support vector machine is proposed. In the proposed system, three kinds of features, namely, human star skeleton, angles of six sticks in the star skeleton, and object motion vectors, are employed to train the human posture classifier and recognize human postures. Based on the recognized human postures, a backward search strategy is proposed to recognize human actions. Based on the experimental results obtained in this study, in terms of recall and precision rates, the proposed system has good performance and is superior to the comparison system.
Semistructured merge: rethinking merge in revision control systems

An ongoing problem in revision control systems is how to resolve conflicts in a merge of independently developed revisions. Unstructured revision control systems are purely text-based and solve conflicts based on textual similarity. Structured revision control systems are tailored to specific languages and use language-specific knowledge for conflict resolution. We propose semistructured revision control systems that inherit the strengths of both: the generality of unstructured systems and the expressiveness of structured systems. The idea is to provide structural information of the underlying software artifacts --- declaratively, in the form of annotated grammars. This way, a wide variety of languages can be supported and the information provided can assist in the automatic resolution of two classes of conflicts: ordering conflicts and semantic conflicts. The former can be resolved independently of the language and the latter using specific conflict handlers. We have been developing a tool that supports semistructured merge and conducted an empirical study on 24 software projects developed in Java, C#, and Python comprising 180 merge scenarios. We found that semistructured merge reduces the number of conflicts in 60% of the sample merge scenarios by, on average, 34%, compared to unstructured merge. We found also that renaming is challenging in that it can increase the number of conflicts during semistructured merge, and that a combination of unstructured and semistructured merge is a pragmatic way to go.
A model for real-time sound synthesis of guitar on a floating-point signal processor

Algorithms that can be used to synthesize guitar sounds on a floating-point signal processor are presented. A finite impulse response (FIR) Lagrange interpolator is introduced to implement the efficient and precise fractional delay approximation that is needed to achieve arbitrary and varying-length strings. This kind of interpolation is especially good in avoiding distortion and undesirable extra effects when the string length is changing continuously during the synthesis of a sound. The interpolator can also be used in other cases, e.g. in transmission-line modeling of acoustic tube resonators in wind instruments and for vocal tract models in speech synthesis. In addition to the interpolation principle, the implementation of the guitar string model on the TMS320C30 floating-point signal processor is described. <<ETX>>
4 Multiple Antenna Techniques

Recent developed information theory results have demonstrated the enormous potential to increase system capacity by exploiting multiple antennas. Combining multiple antennas with orthogonal frequency division multiplexing (OFDM) is regarded as a very attractive solution for the next-generation wireless communications to effectively enhance service quality over multipath fading channels at affordable transceiver complexity. In this regard, multiple antennas, or called multiple-input multiple-output (MIMO) systems, have emerged as an essential technique for the next-generation wireless communications. In general, an MIMO system has capability to offer three types of antenna gains: diversity gains, multiplexing gains and beamforming gains. A wide variety of multiple antennas schemes have been investigated to achieve these gains, while some combo schemes can make tradeoffs among these three types of gains. In this chapter, an overview of multiple antenna techniques developed in the past decade, as well as their transceiver architecture designs, is introduced. The first part of this chapter covers three kinds of diversity schemes: maximum ratio combining (MRC), space-time coding (STC), and maximum ratio transmission (MRT), which are commonly used to combat channel fading and to improve signal quality with or without channel knowledge at the transmitter or receiver. The second part concentrates on spatial multiplexing to increase data rate by simultaneously transmitting multiple data streams without additional bandwidth or power expenditure. Several basic receiver architectures for handling inter-antenna interference, including zero-forcing (ZF), minimum mean square error (MMSE), interference cancellation, etc., are then introduced. The third part of this chapter introduces antenna beamforming techniques to increase signal-tointerference plus noise ratio (SINR) by coherently combining signals with different phase and amplitude at the transmitter or receiver, also known as transmit beamforming or receive beamforming. Another benefit of adopting beamforming is to facilitate multiuser accesses in spatial domain and effectively control multiuser interference. The optimal designs of these beamforming schemes are also presented in this chapter.
Collaborative Design of a Doctoral Nursing Program Online Orientation

AbstractThis article describes the collaborative development of an online orientation for students entering a doctoral nursing education program. Faculty and staff from the school of nursing, university library, and other academic support services worked together to design the orientation course materials, learning activities, and assessments, resulting in a cohesive, active-learning experience for students. As a result, returning adult learners were better prepared to begin their online doctoral studies.
Quinolone-resistant Campylobacter Infections: Risk Factors and Clinical Consequences

We integrated data on quinolone and macrolide susceptibility patterns with epidemiologic and typing data from Campylobacter jejuni and C. coli infections in two Danish counties. The mean duration of illness was longer for 86 patients with quinolone-resistant C. jejuni infections (median 13.2 days) than for 381 patients with quinolone-sensitive C. jejuni infections (median 10.3 days, p = 0.001). Foreign travel, eating fresh poultry other than chicken and turkey, and swimming were associated with increased risk for quinolone-resistant C. jejuni infection. Eating fresh chicken (of presumably Danish origin) was associated with a decreased risk. Typing data showed an association between strains from retail food products and broiler chickens and quinolone-sensitive domestically acquired C. jejuni infections. An association between treatment with a fluoroquinolone before stool-specimen collection and having a quinolone-resistant C. jejuni infection was not observed.