Miracle-dz/UniFAR-FTUs huggingface dataset:
Investigating the Interplay Between Searchers' Privacy Concerns and Their Search Behavior

Privacy concerns are becoming a dominant focus in search applications, thus there is a growing need to understand implications of efforts to address these concerns. Our research investigates a search system with privacy warning labels, an approach inspired by decision making research on food nutrition labels. This approach is designed to alert users to potential privacy threats in their search for information as one possible avenue to address privacy concerns. Our primary goal is to understand the extent to which attitudes towards privacy are linked to behaviors that protect privacy. In the present study, participants were given a set of fact-based decision tasks from the domain of health search. Participants were rotated through variations of search engine results pages (SERPs) including a SERP with a privacy warning light system. Lastly, participants completed a survey to capture attitudes towards privacy, behaviors to protect privacy, and other demographic information. In addition to the comparison of interactive search behaviors of a privacy warning SERP with a control SERP, we compared self-report privacy measures with interactive search behaviors. Participants reported strong concerns around privacy of health information while simultaneously placing high importance on the correctness of this information. Analysis of our interactive experiment and self-report privacy measures indicate that 1) choice of privacy-protective browsers has a significant link to privacy attitudes and privacy-protective behaviors in a SERP and 2) there are no significant links between reported concerns towards privacy and recorded behavior in an information retrieval system with warnings that enable users to protect their privacy.
Eigenstructure Assignment For Control System Design

Thank you very much for downloading eigenstructure assignment for control system design. Maybe you have knowledge that, people have search numerous times for their favorite novels like this eigenstructure assignment for control system design, but end up in malicious downloads. Rather than reading a good book with a cup of tea in the afternoon, instead they are facing with some infectious bugs inside their computer.
Efficient Memory Virtualization

Two important trends in computing are evident. First, computing is becoming more data centric, where low-latency access to a very large amount of data is critical. Second, virtual machines are playing an increasing critical role in server consolidation, security and fault tolerance as substantial amounts of computing migrate to shared resources in cloud services. Since the software stack accesses data using virtual addresses, fast address translation is a prerequisite for efficient data-centric computation and for providing the benefits of virtualization to a wide range of applications. Unfortunately, the growth in physical memory sizes is exceeding the capabilities of the most widely used virtual memory abstraction—paging—that has worked for decades. This thesis addresses the above challenge in a comprehensive manner proposing a hardware/software co-design for fast address translation in both virtualized and native systems to address the needs of a wide variety of big-memory workloads. This dissertation aims to achieve near-zero overheads for virtual memory for both native and virtualized systems. First, we observe that the overheads of page-based virtual memory can increase drastically with virtual machines. We previously proposed direct segments, which use a form of contiguous allocation in memory along with paging to largely eliminate virtual memory overhead for big-memory workloads on unvirtualized hardware. However, direct segments
Mobile Applications for Extension

Mobile computing devices (smart phones, tablets, etc.) are rapidly becoming the dominant means of communication worldwide and are increasingly being used for scientific investigation. This technology can further our Extension mission by increasing our power for data collection, information dissemination, and informed decision-making. Mobile computing applications (apps) with relevance for Extension can be divided loosely into three categories—information delivery, collaborative research/participatory sensing, and self-assessment. Examples can be found in all Extension fields of inquiry, from agricultural production, pest management, natural resources management to youth science literacy and managing nutrition and fitness.
Mobile robot self-localization in unstructured environments based on observation localizability estimation with low-cost laser range-finder and RGB-D sensors

When service robots work in human environments, unexpected and unknown moving people may deteriorate the convergence of robot localization or even cause failure localization if the environment is crowded. In this article, a multisensor observation localizability estimation method is proposed and implemented for supporting reliable robot localization in unstructured environments with low-cost sensors. The contribution of the approach is a strategy that combines noisy laser range-finder data and RGB-D data for estimating the dynamic localizability matrix in a probabilistic framework. By aligning two sensor frames, the unreliable part of the laser readings that hits unexpected moving people is fast extracted according to the output of a RGB-D-based human detector, so that the influence of unexpected moving people on laser observations can be explicitly factored out. The method is easy for implementation and is highly desirable to ensure robustness and real-time performance for long-term operation in populated environments. Comparative experiments are conducted and the results confirm the effectiveness and reliability of the proposed method in improving the localization accuracy and reliability in dynamic environments.
A relational thesaurus : Modeling semantic relationships using frames

The study investigated the argument structure of mid- to high-frequency English verbs, grouped semantically, to establish a basic inventory of relational structures, represented as frames. Based on this investigation, 28 general relational structures were identified. These relationship types are, in turn, related to each other through specialization (based on the hierarchy relationship) and composition (based on the part-whole relationship). Relational structures are also interrelated through the background knowledge inherent in their use.
GroupRight : collaborative group management system

GroupRight is a comprehensive group decision-making platform for simplifying the organization of event scheduling, task management, and mass communication. Consisting of a website, iOS application and an Android application, GroupRight provides convenient tools for groups of all sizes to improve productivity. Users can quickly create and manage dynamic groups so that each member of the group can contribute to the overall system. Likewise, updates from individuals using GroupRight’s core tools are provided to the entire group to increase each member’s situational awareness.
A Refinement Calculus for Circus - Mini-thesis

Most software developments do not use any of the existing theories and formalisms. This leads to a loss of precision and correctness on the resulting softwares. Two different approaches to formal techniques have been raised in the past decades: one focus on data aspects, and the other focus on the behavioural aspects of the system. Some combined languages have already been proposed to bring these two schools together. However, as far as we know, none of them has a related refinement calculus. Using Circus as the specification language, we can describe both data and control behaviour. The objective of this work is to formalise a refinement calculus for Circus. A refinement strategy for Circus, new refinement laws and their proofs are presented. The proofs are based on an extension of the existing Circus semantics, which is based on the unifying theory of programming. This extension, and its mechanisation, and the proof of the laws on ProofPower are also part of this work. We intend to provide a tool that supports the Circus refinement calculus. Furthermore, as an extension of the existing refinement strategy for Circus, we present a translation strategy for Circus programs. This translation strategy can be used as a guideline in the translation of Circus programs to Java. Furthermore, the mechanisation of this translation is also feasible. We present a case study, a safety-critical fire protection system, that, as far as we know, is the largest case study on the Circus refinement calculus. We present the refinement of its abstract centralised specification to a concrete distributed one. Finally, the translation of the concrete specification of the system to Java, using our translation strategy, is also presented. Throughout this mini-thesis, some sections, and even chapters are not written. They have not been removed from the mini-thesis on purpose. Our intention is to give an idea of the scope and the structure of our final thesis, which is discussed in details in the final chapter of this document.
Temporal perception in vision : an examination of bottleneck models

The present work is an exami nati on of the mechani sms underl yi ng temporal processi ng in vision. Recent studi es have shown that when observers are asked to identify two obj ects presented in rapid successi on, identification of the first obj ect is quite accurate, while identification of the second obj ect is poor when it folows the first at very brief inter-target intervals (i.e. 200-500 ms). This second-target deficit is known as the atentional blink. Accordi ng to botl eneck model s, the atentional blink occurs because processi ng of the first target prevents the second target from gai ni ng access to high-level processi ng. A strong prediction of this account is that if processi ng ti me for the first target is increased, the magni tude of the atentional blink shoul d al so increase. This prediction is confi rmed in five experi ments. It is argued that these results strongl y support botl eneck model s as an account of the atentional blink in particular and of temporal processi ng more generaly.
Performance Guarantees In Communication Networks

performance guarantees in communication networks is available in our book collection an online access to it is set as public so you can download it instantly. Our books collection spans in multiple countries, allowing you to get the most less latency time to download any of our books like this one. Merely said, the performance guarantees in communication networks is universally compatible with any devices to read.
Inverse kinematics for the variable geometry truss manipulator via a Lagrangian dual method

This article studies the inverse kinematics problem of the variable geometry truss manipulator. The problem is cast as an optimization process which can be divided into two steps. Firstly, according to the information about the location of the end effector and fixed base, an optimal center curve and the corresponding distribution of the intermediate platforms along this center line are generated. This procedure is implemented by solving a non-convex optimization problem that has a quadratic objective function subject to quadratic constraints. Then, in accordance with the distribution of the intermediate platforms along the optimal center curve, all lengths of the actuators are calculated via the inverse kinematics of each variable geometry truss module. Hence, the approach that we present is an optimization procedure that attempts to generate the optimal intermediate platform distribution along the optimal central curve, while the performance index and kinematic constraints are satisfied. By using the Lagrangian duality theory, a closed-form optimal solution of the original optimization is given. The numerical simulation substantiates the effectiveness of the introduced approach.
Parallel processing in the mammalian olfactory bulb

Splitting sensory information into parallel pathways is a common strategy in sensory systems. Yet, it is not well understood how circuits in these parallel pathways are composed to maintain or even enhance the encoding of specific stimulus features. In this dissertation, we investigate the parallel pathways formed by mitral and tufted cells (MCs and TCs) of the olfactory system and characterize the emergence of feature selectivity in these cell types via distinct patterns of connectivity to local inhibitory interneurons. Chapter 2 explores differences in feedforward circuitry onto MCs and TCs. We find that MCs display longer latency spiking that is more strongly dependent on stimulus intensity than TCs. Longer latency spiking in MCs is a consequence of weaker excitatory and stronger inhibitory currents, mediated by periglomerular cells, onto MCs compared to TCs. Chapter 3 describes the causes and consequences of lateral inhibition differences between MCs and TCs. We find that MCs are affected by lateral inhibition at intermediate firing rates, while TCs are affected at lower firing rates. These differences arise, in part, due to differential recruitment of morphologically distinct classes of granule cells by MCs and TCs. Using simulations, we show that these differences in lateral inhibition allow TCs and MCs to perform odor discriminations best in separate concentration ranges. Together, the experiments described here suggest that differences in odor-evoked responses between MCs and TCs are a consequence of distinct patterns of connectivity to multiple populations of inhibitory interneurons.
RDIT - Race Detection from Incomplete Traces

In a precise race-detector, a race is detected only if the trace exhibits a real race. In such tools, every memory access from each thread is typically checked for conflicting accesses. We show that there are many redundant memory access checks present in real world program execution traces. Removing these redundant checks during the online run-time instrumentation stage can significantly speed up execution time. All the while, removing these redundant checks does not affect its race-detection capability.
A machine learning approach for Biomedical Named Entity Recognition

This paper aims to develop a Named Entity Recognition (NER) that creates new tags that facilitate fast query processing, information retrieval and data preprocessing of Biomedical Domain. We have used a machine learning approach that uses domain specific knowledge to train the data and label the entities with appropriate tags. Conditional Random Fields (CRF) is implemented and used to train the input domain specific data that yields good performance. Experimental and evaluation result shows that the learned model yields a Biomedical domain specific NER recall of 82%, precision of 85%, accuracy of 82% and Fmeasure of 83%. Thus learned CRF model builds a domain specific NER for Biomedical Domain and tags the domain keywords with appropriate tags.
ADVANCED STUDY OF FUTURE GENERATION ANTENNA FOR WIRE-FREE APPLICATIONS

channel equalization is a process of compensating the disruptive effects caused mainly by inter symbol interference in a band-limited channel and plays a vital role for enabling higher data rate in digital communication. The development of new training algorithms, structures and the selection of the design parameters for equalizers are active fields of research which are exploiting the benefits of different signal processing techniques. Here in our paper work for equalization we use the various adaptive algorithms like least mean square (lms), recursive least square (rls), and constant modules algorithms (cma) with 16-ary quadrature amplitude modulation (qam) and 16-ary phase shift keying (psk) modulation technique and then compare the mean square error of all these combinations of adaptive algorithms and modulation techniques. The simulation work has been done on matlab -2008 software.
Analysis, Modeling and Simulation of State Feedback Control for Positive Output Super Lift Luo Converter

This article studies a design and implementation of state-feedback control problem for dc-dc Positive Output Super Lift Luo (POSLL) converter by considering the line and load disturbances for needing desired power source for various portable electronic equipments like battery charger, hard disk drives, medical device, LED TV etc. The POSLL’s dynamic performance becomes non-linear in nature; the designed controller able to get superior dynamic performance given by load estimation is done by using an observer and by combining the state-feedback control with the load estimator, a controller which is explicitly developed with strong robustness using separation principle. An effectual stability analysis is exemplified to prove that by carefully selecting the state feedback control and observer gain matrix, the output voltage of the dc-dc POSLL converter tracks the desired value irrespective of the uncertainties. Extensive simulation is carried out using MATLAB/Simulink model. The result based on time domain analysis is done by using the controllers for various disturbances given to the converter.
Formalizing and Comparing Software Architectures of Federated Database Management Systems

Constructing a formal specification requires some effort that should be justified. A motivation for formalizing software architectures is to enable a precise analysis and comparison of specific architectures for evaluating and selecting appropriate architectural variations. This contribution discusses a detailed investigation of schema architectures, which are central components in the software architecture of federated database management systems. It is shown how specific architectures can be compared to the reference architecture and to each other. To achieve this, we combine the semi-formal object-oriented modeling language UML with the formal object-oriented specification language Object-Z.
Asymmetric Two-Handed Input for Mode Selection on Touchscreens

vii List of Abbreviations and Symbols Used . viii Acknowledgements . ix Chapter
Big Data Analytics: A Field of Opportunities for Information Systems and Technology Researchers

ABSTRACT In recent years, the information systems research community has been experiencing an exciting time discovering and coming to grips with many unexplored or untapped opportunities for research that lie at the intersection of the disciplines of information systems and technology, big data, analytics, and data science. In this article, some of the critical aspects of the big data problem are discussed, and their importance as well as relevance to information systems research is shown. Also proposed are a number of research problems in this area that interested information systems scholars can address to delve more deeply into the field as well as to generate further active interest of the subject within the information systems community.
DNIDS: A dependable network intrusion detection system using the CSI-KNN algorithm

The dependability of an Intrusion Detection System (IDS) relies on two factors: ability to detect intrusions and survivability in hostile environments. Machine learningbased anomaly detection approaches are gaining increasing attention in the network intrusion detection community because of their intrinsic ability to discover novel attacks. This ability has become critical since the number of new attacks has kept growing in recent years. However, most of today’s anomaly-based IDSs generate high false positive rates and miss many attacks because of a deficiency in their ability to discriminate attacks from legitimate behaviors. These unreliable results damage the dependability of IDSs. In addition, even if the detection method is sound and effective, the IDS might still be unable to deliver detection service when under attack. With the increasing importance of the IDS, some attackers attempt to disable the IDS before they launch a thorough attack. In this thesis, we propose a Dependable Network Intrusion Detection System (DNIDS) based on the Combined Strangeness and Isolation measure K-Nearest Neighbor (CSI-KNN) algorithm. The DNIDS can effectively detect network intrusions while providing continued service even under attacks. The intrusion detection algorithm analyzes different characteristics of network data by employing two measures:
New bit-rate control models for image and video transmission

This paper presents two new schemes of bit rate control: a linear significant coefficient percentage model and a mixed power function model of step-size. Based on the rate-distortion characteristics of wavelet images, the relationship between the percentage of significant coefficients and the output bit-rate is examined, and a linear model is developed. Next, a mixed power function model is introduced as the regression of experimental results. Both bit rate control algorithms have been implemented for the X-tree wavelet coder. Simulation results have verified the effectiveness of the new bit-rate control models.
An evaluation on CT image acquisition method for medical VR applications

Recent medical virtual reality (VR) applications to minimize re-operations are being studied for improvements in surgical efficiency and reduction of operation error. The CT image acquisition method considering three-dimensional (3D) modeling for medical VR applications is important, because the realistic model is required for the actual human organ. However, the research for medical VR applications has focused on 3D modeling techniques and utilized 3D models. In addition, research on a CT image acquisition method considering 3D modeling has never been reported. The conventional CT image acquisition method involves scanning a limited area of the lesion for the diagnosis of doctors once or twice. However, the medical VR application is required to acquire the CT image considering patients’ various postures and a wider area than the lesion. A wider area than the lesion is required because of the necessary process of comparing bilateral sides for dyskinesia diagnosis of the shoulder, pelvis, and leg. Moreover, patients’ various postures are required due to the different effects on the musculoskeletal system. Therefore, in this paper, we perform a comparative experiment on the acquired CT images considering image area (unilateral/bilateral) and patients’ postures (neutral/abducted). CT images are acquired from 10 patients for the experiments, and the acquired CT images are evaluated based on the length per pixel and the morphological deviation. Finally, by comparing the experiment results, we evaluate the CT image acquisition method for medical VR applications.
A service-oriented grid computing platform and its framework

The Open Grid Services Architecture (OGSA) represents an evolution towards a Grid system architecture based on Web ser-vices concepts and technologies. It provides a service-oriented view of Grid architectures. This paper proposes a service-oriented Gridcomputing platform that complies with the OGSA infrastructure. This Grid computing platform aims to support the execution of appli-cations in a Grid environment. The platform is a multi-layer architecture which integrates Grid portal layer, Web server layer and Gridservices layer. The fundamental components of this architecture are a pool of Grid services that conform to the OGSI (Open Grid Ser-vices Infrastructure) specifications. Each Grid service provides a set of interfaces and operations which characterizes the functionalityit offers, and all these Grid services work cooperatively to manage different stages of the execution of Grid applications. As higher-lever services, the Grid services are constructed by the composition of the Globus Toolkit core services. The implementation, commu-nication and deployment of these Grid services are based on Web services technologies and protocols