Miracle-dz/UniFAR-FTUs huggingface dataset:
\One Weird Trick" for Advertising Outcomes: An Exploration of the Multi-Armed Bandit for Performance-Driven Marketing

In this work, we explore an online reinforcement learning problem called the multi-armed bandit for application to improving outcomes in a web marketing context. Specifically, we aim to produce tools for the efficient experiment design of variations of a website with the goal of increasing some desired behavior such as purchases. We provide a detailed reference, with a statistical lens, of the existing research in variants and associated policies known for the problem, then produce a set of theoretical and empirical analyses of specific application area questions. Concretely, we provide a number of contributions: First, we present a new standardized simulation platform integrating knowledge and techniques from the existing literature for the evaluation of bandit algorithms in a set of pre-defined worlds. To the best of our knowledge, this is the first comprehensive simulation platform for multi-armed bandits capable of arbitrary arms, parameterization, algorithms and repeatable experimentation. Second, we integrate Thompson sampling into linear model techniques and explore a number of implementation questions, finding both that replication of Thompson sampling and adjusting for estimative uncertainty is a plausible mechanism for improving the results. Third, we explore novel techniques for dealing with certain types of structural non-stationarity such as drift and find that the technique of weighted least squares is a strong tool for handling both known and unknown drift. Empirically, in the unspecified case, an exponential decaying weight provides good performance in a large variety of cases; in the specified case, an experimenter can select a weighting strategy to reflect their known drift achieving state-of-the-art results. Fourth, we present the first known oracle-free measure of regret called statistical regret, which utilizes intuitions from the confidence interval to produce a type of interval metric by replaying late-experiment knowledge over prior actions to determine how performant an experimenter can believe their results to be. Fifth, we present preliminary results on a specification-robust and computationally efficient sampling technique called the Simple Optimistic Sampler which shows promising outcomes via a technique which requires no modelling assumptions to implement.
User Behaviour and Security in Opportunistic Networks

This thesis investigates by means of simulation the effects of uncooperative user behaviour in opportunistic dissemination networks, in which a message originator can specify that the message should only be delivered to a trusted subset of the total node population. The nodes in the network are required to disseminate messages only to nodes whose membership in this desired subset they have confirmed, which is determined by a computational trust value that is assigned to each node. It is likely that some nodes in the opportunistic network will ignore this selection requirement, and therefore jeopardise the security of the network from the point of view of the message originator. The investigations show the extent to which uncooperative dissemination behaviour negatively affects computational trust schemes that are applied as a security measure in opportunistic networks. Subsequently, a scheme is devised that helps to detect and exclude uncooperative disseminators from the networks, and conclusions are drawn about its effectivity and the conditions under which such a scheme can work. A second contribution of this work is the creation of a mobility trace that is superior to existing mobility traces in terms of the realistic modelling of human mobility. This trace is used as an input to the opportunistic network simulations, and by being realistic allows to draw authoritative conclusions from these.
Toward a Practical Data Privacy Scheme for a Distributed Implementation of the Smith-Waterman Genome Sequence Comparison Algorithm

Volunteer distributed computations utilize spare processor cycles of personal computers that are connected to the Internet. The resulting platforms provide computational power previously available only through the use of expensive clusters or supercomputers. However, distributed computations running in untrustworthy environments raise a number of security concerns, including computation integrity and data privacy. This paper introduces a strategy for enhancing data privacy in some distributed volunteer computations, providing an important first step toward a general data privacy solution for these computations. The strategy is used to provide enhanced data privacy for the Smith-Waterman local nucleotide sequence comparison algorithm. Our modified Smith-Waterman algorithm provides reasonable performance, identifying most, and in many cases all, sequence pairs that exhibit statistically significant similarity according to the unmodified algorithm, with reasonable levels of false positives. Moreover the modified algorithm achieves a net decrease in execution time, with no increase in memory requirements. Most importantly, our scheme represents an important first step toward providing data privacy for a practical and important real-world algorithm.
PRAW—A PRivAcy model for the Web: Research Articles

Web navigation enables easy access to vast amounts of information and services. However, it also poses a major risk to users' privacy. Various eavesdroppers constantly attempt to violate users' privacy by tracking their navigation activities and inferring their interests and needs (profiles). Users who wish to keep their intentions secret forego useful services to avoid exposure. The computer security community has concentrated on improving users' privacy by concealing their identity on the Web. However, users may want or need to identify themselves over the Net to receive certain services but still retain their interests, needs, and intentions in private. PRAW—a PRivAcy model for the Web suggested in this paper—is aimed at hiding users' navigation tracks to prevent eavesdroppers from inferring their profiles but still allowing them to be identified. PRAW is based on continuous generation of fake transactions in various fields of interests to confuse eavesdroppers' automated programs, thus providing them false data. A privacy measure is defined that reflects the difference between users' actual profile and the profile that eavesdroppers might infer. A prototype system was developed to examine PRAW's feasibility and conduct experiments to test its effectiveness. Encouraging results and their analysis are presented, as well as possible attacks and known limitations. © 2005 Wiley Periodicals, Inc.
Trimming the Wireless Capsule Endoscopic Video by Removing Redundant Frames

Wireless Capsule Endoscopy (WCE) is a new challenging clinical technique for obtaining a detailed video of the small intestine. A major drawback of this technology is that it generates a large volume of video which will take time for visualization. In this paper, we propose a method to reduce the visualization time by removing those redundant video frames. There are two types of redundant frames. The first one is called non-informative frames, which is created by turbid fluids, foods, and faecal materials. The second one is called redundant frames, which is caused by the non-uniform movement of WCE. We first applied Gauss Laguerre Transform (GLT) to detect the bubble-like non-informative frames. The redundant frame was detected by a distance measure based on image edges. We apply Canny operator with a fixed smoothing parameter to detect edges of the image. An asymmetric distance was defined to measure the shift of edges from one image to another. The image whose edge shift to its neighboring image is smaller than a threshold was defined as a redundant frame. Experimental results demonstrate an average of 17% of non-informative frames and 37% of redundant frames for one person, without a loss of useful frames.
A game theoretical study of peering vs transit in the internet

We propose a model for network optimization in a non-cooperative game setting with specific reference to the Internet connectivity. We refer to the general model shown in internal report [1], where Autonomous Systems (AS) decisions on link creation and traffic routing are strategically based on realistic interconnection costs, keeping into account the peering/transit dichotomy. Equilibria existence and convergence results were obtained in [1] only for a specific toy problem, while here we study larger scale scenarios which better fit the complex nature of the Internet. We are able to show that equilibria existence and convergence properties still hold for many possible generalizations, yet not all of them, and provide a specific example for which the system enters in a never-ending oscillation. Thanks to the use of simulations we covered those scenarios for which analytic results could not be obtained, thus analyzing a broad variety of general cases which were not studied in [1]. Simulation shows that the system, in the vast majority of cases, converges to an equilibrium. Very interestingly, even in asymmetric scenarios the equilibrium reached suggests that players tend to be symmetric with respect to the peering exchange points and send their asymmetric traffic quota via the transit service providers.
Stabilization of a compliant humanoid robot using only Inertial Measurement Units with a viscoelastic reaction mass pendulum model

To guarantee its balance, a humanoid robot has to respect some contact force constraints. Therefore, traditional controllers generate motions complying with these constraints, but they usually consider the robot as stiff and the joint position perfectly known. However, several robots contain compliant parts in their structure. This flexibility modifies the forces at contacts and endangers balance. However, most solutions to stabilize the robot rely on force sensors. But several humanoid robots aren't equipped with these sensors. This paper has two aims. The first one is to develop a compliance stabilizer using the center of mass position and upper-body orientation through a viscoelastic reaction mass pendulum model. The second objective is to show the performances of such a stabilizer when relying only on an IMU-based state observer. Experimental results on HRP-2 robot show that the stabilization successfully rejects perturbations with high gains using only these IMU signals. Moreover, the actuation of the upper-body orientation provides redundancy, robustness and finally improved performances to the stabilizer.
Microtubule behavior in the growth cones of living neurons during axon elongation

To understand how microtubules are generated in the growth cone, we have imaged fluorescently tagged microtubules in living frog embryonic neurons. The neurons were labeled by injecting rhodamine-labeled tubulin into the fertilized egg and explanting the neurons from the neural tube. Microtubules extend deep into the growth cone periphery and adopt three characteristic distributions: (a) dispersed and splayed throughout much of the growth cone; (b) looped and apparently contorted by compression; and (c) bundled into tight arrays. These distributions interconvert on a time scale of several minutes and these interconversions are correlated with the behavior of the growth cone. We observed microtubule growth and shrinkage in growth cones, but are unable to determine their contribution to net assembly. However, translocation of polymer form the axon appears to be a major mechanism of generating new polymer in the growth cone, while bundling of microtubules in the growth cone appears to be the critical step in generating new axon. Neurons that were about to turn spontaneously generated microtubules in the future direction of growth, suggesting that orientation of microtubules might be an important early step in neuronal pathfinding.
Proposal of a cloud-based agent for social human-robot interaction that learns from the human experimenters

The field of human-robot interaction usually uses an experimental technique called Wizard of Oz where a human operator (the experimenter or a confederate) remotely controls the behavior of the system. Per contra, if robots are autonomous during the interaction, they have a limited pre-programmed set of behaviors. We propose to use reinforcement learning for adaptation of autonomous robotic behavior during the interaction and to benefit from the advantages that brings the field of cloud computing. The overall goal is to design robotic behaviors less boring and more effective and thus, to prepare robots for a long-term human-robot interaction.
Diffusion LMS for Multitask Problems With Local Linear Equality Constraints

We consider distributed multitask learning problems over a network of agents where each agent is interested in estimating its own parameter vector, also called task, and where the tasks at neighboring agents are related according to a set of linear equality constraints. Each agent possesses its own convex cost function of its parameter vector and a set of linear equality constraints involving its own parameter vector and the parameter vectors of its neighboring agents. We propose an adaptive stochastic algorithm based on the projection gradient method and diffusion strategies in order to allow the network to optimize the individual costs subject to all constraints. Although the derivation is carried out for linear equality constraints, the technique can be applied to other forms of convex constraints. We conduct a detailed mean-square-error analysis of the proposed algorithm and derive closed-form expressions to predict its learning behavior. We provide simulations to illustrate the theoretical findings. Finally, the algorithm is employed for solving two problems in a distributed manner: A minimum-cost flow problem over a network and a space–time varying field reconstruction problem.
Source identification of camera phones using SVD

We present a novel method to extract the sensor pattern noise (SPN) of digital images and associate them with their respective source camera phones. The method first estimates the photo response non-uniformity (PRNU) of each image by means of its energy level and then converts it to an additive noise to facilitate extraction using Singular Value Decomposition (SVD). The latter is a spectral decomposition technique that separates the PRNU from the signal subspace. The camera reference signatures of the individual cameras are computed from a sample of their respective images and compared with a mixture of image signatures from a set of known camera devices. Our studies show that it is possible to determine the source device of digital images from camera phones using such method of signature extraction, with encouraging results.
A comparison of numerical implementations of the Eigenstate expansion method for quantum molecular dynamics simulations

We investigate the ecient computation of a few of the lowest eigenvalues of a symmetric eigenvalue problem occurring in quantum dynamical molecular simulations. The large sparse system of order n 3 is highly structured such that its multiplication with a vector costs O(n 3 logn) oating point operations only. We compare a number of eigensolvers: subspace iteration, two variants of the restarted Lanczos algo- rithm, among them ARPACK, the Jacobi-Davidson algorithm and the classical algorithms from LAPACK for full matrices. Some of them are applied with a shift-and-invert spectral transformation. The arising systems of equations are solved by the preconditioned conjugate gradient method for which new ecient ADI-type preconditioners are proposed and analyzed.
Sparse Subspace Clustering for Incomplete Images

In this paper, we propose a novel approach to cluster incomplete images leveraging sparse subspace structure and total variation regularization. Sparse subspace clustering obtains a sparse representation coefficient matrix for input data points by solving an ℓ1 minimization problem, and then uses the coefficient matrix to construct a sparse similarity graph over which spectral clustering is performed. However, conventional sparse subspace clustering methods are not exclusively designed to deal with incomplete images. To this end, our goal in this paper is to simultaneously recover incomplete images and cluster them into appropriate clusters. A new nonconvex optimization framework is established to achieve this goal, and an efficient first-order exact algorithm is developed to tackle the nonconvex optimization. Extensive experiments carried out on three public datasets show that our approach can restore and cluster incomplete images very well when up to 30% image pixels are missing.
Hypnos: understanding and treating sleep conflicts in smartphones

To maximally conserve the critical resource of battery energy, smartphone OSes implement an aggressive system suspend policy that suspends the whole system after a brief period of user inactivity. This burdens developers with the responsibility of keeping the system on, or waking it up, to execute time-sensitive code. Developer mistakes in using the explicit power management unavoidably give rise to energy bugs, which cause significant, unexpected battery drain. In this paper, we study a new class of energy bugs, called sleep conflicts, which can happen in smartphone device drivers. Sleep conflict happens when a component in a high power state is unable to transition back to the base power state because the system is suspended when the device driver code responsible for driving the transition is supposed to execute. We illustrate the root cause of sleep conflicts, develop a classification of the four types of sleep conflicts, and finally present a runtime system that performs sleep conflict avoidance, along with a simple yet effective pre-deployment testing scheme. We have implemented and evaluated our system on two Android smartphones. Our testing scheme detects several sleep conflicts in WiFi and vibrator drivers, and our runtime avoidance scheme effectively prevents sleep conflicts from draining the battery.
The NETSIM Concept and Global Optimization

Different factors influence the planning and the production flow as well. Generally, these factors can be considered in different ways. Nevertheless, it is not possible to do a correct and complete planning and to consider all different alternatives. Therefore it will be the aim to analyze possible procedures during the planning, to evaluate possible measures and their results and to prepare optima measures. When there should be considered that the task has to consider additional influence factors on the Supply Chain level the complexity of the task increases considerable. Today's planning systems are not fully prepared for these demands because of the relatively fixed nature of their planning data structures (local planning nets) that hardly may be integrated into an overall planning structure. Moreover, these systems rely upon deterministic input parameters and fixed work sequences, which does not correspond to the situation in dynamic environments. On the other hand supply chain management offers a large potential for the enterprises to reduce cost and improve customer service performance Apart from the Supply Chain Management Concept planning systems require much more then in the ERP approach; integration as well as adaptability of the planning systems, especially integration of internet and intranet and multiagent based distributed applications. Beside different technical difficulties for the online data update or the synchronization of planning there are missing modeling approaches which can be integrated in practice. In this research paper we will analyze the possibilities in the area of combinatoric and distributed planning based on distributed databases for the support of the production planning. Further, we will introduce a new web based alternative for modeling, called NETSIM and we will present its applicableness by means of a Prototype. This NETSIM (Network Simulation) concept, fits into the dynamic scenario of dynamic environments as well as it provides substantial enhancements to traditional planning (Deterministic or stochastic basis). A very important aspect for NETSIM is that all scenario parameter can be considered and if its needed can be changed. Additional will be analyzed apart from problems of combinatoric there the applicability of deterministic and stochastic planning. A very important aspect in this contribution is an universal interface description for using with all standard software systems, e.g. SAP, BAAN, Navision and Peoplesoft. Using this universal interface can be used the NETSIM concept with all state-of-the-art (ERP Enterprise Resource Planning) systems.
Stereo image to stereo sound methods for Vision based ETA

Sonification is defined as the use of non-speech audio to convey information. More specifically, sonification is the transformation of data relations into perceived relations in an acoustic signal for the purposes of facilitating communication or interpretation. This paper describes the methods for stereo image processing, sonification and the results to support the vision substitution system for human blinds. The experimental Stereo Vision based Electronic Travel Aid (SVETA) system consists of a kit built-in with computing device, stereo cameras and a stereo headphone. The images captured from the stereo cameras are processed to extract object information such as distance from camera, object location and its size to support navigation. This visual information is conveyed to the blind through a specially designed structured sound. Two methods are proposed for image sonification and each method is tested for its ability in conveying information.
Information Use Environment of Religious Professionals: a Case Study of the Everyday Life Information Seeking Behavior of Catholic Clergy in Northern Nigeria

This study explores the everyday life information seeking (ELIS) behavior of Catholic clergy in Northern Nigeria and describes their information use environment (IUE). It employed a mixed-method case study using survey and episodic interview techniques of data collection. The ELIS of Savolainen, the IUE of Taylor and the small world of Chatman were theoretical frameworks that guided this study. Findings showed that the IUE of these Catholic clergy is shaped by four elements: (1) geographical location and culture, (2) the celibate clergy, (3) their information needs, and (4) the information sources used to resolve these needs. Three types of information needs were identified: essential needs, circumstantial needs and intermittent needs. There was a high interrelatedness between the effects of culture and celibacy on the information seeking of these clergy. They are not likely to cross boundaries of their world to seek particularly essential information about their ministry or private lives. The findings of this study align with Chatman’s proposition that members who live in the round will not cross the boundaries of their world to seek information. The study found problems with access and availability of information, which included lack of familiarity with electronic/online library databases among the clergy, and the lack of archives and documentation of records and historical materials. It recommended the development of an archiving and documentation plan that digitizes paper documents for electronic management, including policies on data curation for the Catholic religious institutions in Nigeria.