Miracle-dz/UniFAR-FTUs huggingface dataset:
Avoiding Load Issues in Wireless Sensor Networks by Adopting Data Aggregation Methods

We investigate the following fundamental question - how fast can information be collected from a wireless sensor network organized as tree? To address this, we explore and evaluate a number of different techniques using realistic simulation models under the many-to-one communication paradigm known as convergecast. We first consider time scheduling on a single frequency channel with the aim of minimizing the number of time slots required (schedule length) to complete a convergecast. Next, we combine scheduling with transmission power control to mitigate the effects of interference, and show that while power control helps in reducing the schedule length under a single frequency, scheduling transmissions using multiple frequencies is more efficient. We give lower bounds on the schedule length when interference is completely eliminated, and propose algorithms that achieve these bounds. We also evaluate the performance of various channel assignment methods and find empirically that for moderate size networks of about 100 nodes, the use of multi-frequency scheduling can suffice to eliminate most of the interference. Then, the data collection rate no longer remains limited by interference but by the topology of the routing tree. To this end, we construct degree-constrained spanning trees and capacitated minimal spanning trees, and show significant improvement in scheduling performance over different deployment densities. Lastly, we evaluate the impact of different interference and channel models on the schedule length.
Live Programming in Scientific Simulation

We demonstrate that a live-programming environment can be used to harness and add run-time interactivity to scientific simulation codes. Through a set of examples using a Particle-In-Cell PIC simulation framework we show how the real-time, human-in-the-loop interactivity of live programming can be incorporated into a traditional, "offline", development workflow. We discuss how live programming tools and techniques can be productively integrated into the existing HPC landscape to increase productivity and enhance exploration and discovery.
Anomalous Trajectory Detection in Surveillance Systems Using Pedestrian and Surrounding Information

Concurrently detected and annotated abnormal events can have a significant impact on surveillance systems. By considering the specific domain of pedestrian trajectories, this paper presents two main contributions. First, as introduced in much of the work on trajectory-based anomaly detection in the literature, only information about pedestrian paths, such as direction and speed, is considered. Differing from previous work, this paper proposes a framework that deals with additional types of trajectory-based anomalies. These abnormal events take places when a person enters prohibited areas. Those restricted regions are constructed by an online learning algorithm that uses surrounding information, including detected pedestrians and background scenes. Second, a simple data-boosting technique is introduced to overcome a lack of training data; such a problem particularly challenges all previous work, owing to the significantly low frequency of abnormal events. This technique only requires normal trajectories and fundamental information about scenes to increase the amount of training data for both normal and abnormal trajectories. With the increased amount of training data, the conventional abnormal trajectory classifier is able to achieve better prediction accuracy without falling into the over-fitting problem caused by complex learning models. Finally, the proposed framework (which annotates tracks that enter prohibited areas) and a conventional abnormal trajectory detector (using the data-boosting technique) are integrated to form a united detector. Such a detector deals with different types of anomalous trajectories in a hierarchical order. The experimental results show that all proposed detectors can effectively detect anomalous trajectories in the test phase.
Practical Human Biology

Thank you for reading practical human biology. As you may know, people have search numerous times for their favorite books like this practical human biology, but end up in infectious downloads. Rather than reading a good book with a cup of tea in the afternoon, instead they juggled with some harmful virus inside their laptop. practical human biology is available in our book collection an online access to it is set as public so you can get it instantly. Our digital library saves in multiple countries, allowing you to get the most less latency time to download any of our books like this one. Merely said, the practical human biology is universally compatible with any devices to read.
A Theory-Based Integrated Design Process for Development and Evaluation of Web-Based Supplemental Learning Environments

As an increasingly powerful, interactive, and dynamic medium for sharing information, the World Wide Web (Web) has found many educational applications. Because of educational benefits for both learners and educators, Web-based courses and programs have increasingly been developed and implemented by many academic institutions, organizations, and companies worldwide (Aggarwal & Brento, 2000). This study, however, asserts that many of the developmental approaches lack three important considerations to be used for implementing learning applications based on the Web: (1) integration of the human-computer interface design with instructional design, (2) development of the evaluation framework to improve the overall quality of Web-based learning support environments, and (3) development of an individualistic approach to the Web hosting of courses. This study explored the three Web-based learning environment weaknesses while developing a user-centered, Web-based learning support environment for Global Positioning System (GPS) education: Web-based distance and distributed learning (WDL) environment. Research goals of the study were all concerned with the improvement of the design process and usability of the WDL environment based on a theory-based Integrated Design Process (IDP) proposed in the study. Results indicated that the proposed IDP was effective in that the study showed (1) the WDL environment’s equivalence to traditional supplemental learning, especially as a Web-based supplemental learning program and (2) users’ positive perceptions of WDL environment resources. The study also confirmed that for an e-learning environment to be successful, various aspects of the learning environment as a Web-based supplemental learning program should be considered such as application domain knowledge (i.e., target subject field), conceptual learning theory, instructional design, human-computer interface design, and evaluation about the overall quality of the learning environment.
Multivariate Calculation Use Of The Continuous Groups

Thank you very much for downloading multivariate calculation use of the continuous groups. Maybe you have knowledge that, people have look hundreds times for their favorite novels like this multivariate calculation use of the continuous groups, but end up in infectious downloads. Rather than enjoying a good book with a cup of coffee in the afternoon, instead they juggled with some malicious bugs inside their desktop computer.
On Trajectory Generation for Robots

A fundamental problem in robotics is the generation of motion for a task. How to translate a task to a set of movements is a non-trivial problem. The complexity of the task, the capabilities of the robot, and the desired performance, affect all aspects of the trajectory; the sequence of movements, the path, and the course of motion as a function of time.This thesis is about trajectory generation and advances the state of the art in several directions. Special attention to trajectories in constrained situations when interaction forces are involved is paid. We bring a control perspective to trajectory generation and propose novel solutions for online trajectory generation with a rapid response to sensor inputs. We formulate and find optimal trajectories for various problems, closing the gap between path planning and trajectory generation. The inverse problem of finding the control signal corresponding to a desired trajectory is investigated and we extend the applicability of an existing algorithm to a broader class of problems.To collect human-generated trajectories involving force interactions, we propose a method to join two robotic manipulators to form a haptic interface for task demonstration. Furthermore, fast algorithms for fixed-time point-to-point trajectory generation are investigated. More importantly, two optimal closed-loop trajectory generation methods are proposed. We derive an optimal controller for the fixed-time trajectory-generation problem with a minimum-jerk cost functional. The other method is based on Model Predictive Control, which allows a more generic form of system dynamics and constraints. In addition, a ball-and-finger system is modeled for studying trajectory generation where interaction plays an important role. Efficient movements for rotating the ball are numerically computed and simulated.Iterative Learning Control (ILC) finds a proper control signal for obtaining a desired trajectory. We derive frequency-domain criteria for the convergence of linear ILC on finite-time intervals that are less restrictive than existing ones in the literature. (Less)
Particle adhesion and removal mechanisms during brush scrubber cleaning in post-CMP processes

Brush scrubbers are among the most commonly used instruments for wafer-cleaning applications nowadays. However, the removal mechanisms of nanosized particles are far from clear, especially because no direct experimental data are available to backup theoretical models in the literature. This study combines a theoretical approach based on a force analysis with an experimental study of the removal of nanosized slurry particles. In the theoretical part, all forces affecting the adhesion and the removal of particles are evaluated to determine which are dominant in two extreme removal mechanisms: lifting and rolling. In the experimental part, the removal efficiency of 34nm SiO2 particles is investigated by using the haze approach. Based on a study of the aging of contaminated wafers, conditions are selected where no chemical bonds are formed between a particle and a substrate. Force analysis and experimental observations both show that nanosized particles cannot be lifted directly by a brush. Instead, rolling s.
A Content Delivery Model for Online Video

Online video accounts for a large and growing portion of all Internet traffic. In order to cut bandwidth costs, it is necessary to use the available bandwidth of users to offload video downloads. Assuming that users can only keep and distribute one video at any given time, it is necessary to determine the global user cache distribution with the goal of achieving maximum peer traffic. The system model contains three different parties: viewers, idlers and servers. Viewers are those peers who are currently viewing a video. Idlers are those peers who are currently not viewing a video but are available to upload to others. Finally, servers can upload any video to any user and has infinite capacity. Every video maintains a first-in-first-out viewer queue which contains all the viewers for that video. Each viewer downloads from the peer that arrived before it, with the earliest arriving peer downloading from the server. Thus, the server must upload to one peer whenever the viewer queue is not empty. The aim of the idlers is to act as a server for a particular video, thereby eliminating all server traffic for that video. By using the popularity of videos, the number of idlers and some assumptions on the viewer arrival process, the optimal global video distribution in the user caches can be determined.
Construction of Two‐Dimensional MoS2/CdS p‐n Nanohybrids for Highly Efficient Photocatalytic Hydrogen Evolution.

Two-Dimensional MoS2/CdS nanohybrids with a sandwich-like p-n junction heterostructure, large specific surface area, and decreased band gap are solvothermally prepared from a DMSO suspension of well-dispersed MoS2 nanosheets (obtained from a mixture of LiBH4 and bulk MoS2 in the molar ratio of 2.5:1 at 350 °C for 3 d) and Cd(OAc)2 (ultrasound, autoclave, 220 °C, 18 h).
Suite2p: beyond 10,000 neurons with standard two-photon microscopy

Two-photon microscopy of calcium-dependent sensors has enabled unprecedented recordings from vast populations of neurons. While the sensors and microscopes have matured over several generations of development, computational methods to process the resulting movies remain inefficient and can give results that are hard to interpret. Here we introduce Suite2p: a fast, accurate and complete pipeline that registers raw movies, detects active cells, extracts their calcium traces and infers their spike times. Suite2p runs on standard workstations, operates faster than real time, and recovers ~2 times more cells than the previous state-of-the-art method. Its low computational load allows routine detection of ~10,000 cells simultaneously with standard two-photon resonant-scanning microscopes. Recordings at this scale promise to reveal the fine structure of activity in large populations of neurons or large populations of subcellular structures such as synaptic boutons.
Wireless and Mobile Network Security

This book provides a thorough examination and analysis of cutting-edge research and security solutions in wireless and mobile networks. It begins with coverage of the basic security concepts and fundamentals which underpin and provide the knowledge necessary for understanding and evaluating security issues, challenges, and solutions. This material will be of invaluable use to all those working in the network security field, and especially to the many people entering the field. The next area of focus is on the security issues and available solutions associated with off-the-shelf wireless and mobile technologies such as Bluetooth, WiFi, WiMax, 2G, and 3G. There is coverage of the security techniques used to protect applications downloaded by mobile terminals through mobile cellular networks, and finally the book addresses security issues and solutions in emerging wireless and mobile technologies such as ad hoc and sensor networks, cellular 4G and IMS networks.
Neural Network-Based Techniques for Damage Identification of Bridges: A Review of Recent Advances

A modern approach for the design of bridges should be able to assess the structural health and performance during their entire life-cycle. From this perspective, effective structural monitoring assumes a primary role for detecting the circumstances that may eventually lead to damage and unsafe operations in a timely manner, so that costly replacements can be avoided or delayed by effective preventive maintenance. The extraction of useful information from the large amount of measurement data, that are often time series of the accelerations, is still considered a challenge and suitable techniques are needed for assessing the health of the bridge from such data. Various methods for structural assessment and identification of damage, based on the use of neural networks, have been proposed in the past few decades and shown to be effective. In the first part of this work, a review of some case studies, focusing in more detail on those methods proposed in the last five years, is carried out. This analysis shows that most of the applications are still based on the use of traditional neural network models, where the internal architecture is assigned on the basis of rules of thumb or regularization procedures. In the second part of the work, the neural network model is re-examined from the Bayesian probability logic viewpoint. Using this approach, it is shown that the conventional learning approach can be derived as a particular approximation of the Bayesian framework, and it is schematically recalled how Bayesian inference can be applied to neural networks in order to optimize the architecture of the models and determine the relative importance of different inputs. In the last part, these Bayesian neural networks are applied for processing the data coming from the long term monitoring of the Tianjin Yonghe Bridge. The dataset was provided by the Asian-Pacific Network of Centers for Research in Smart Structure Technology (ANCRiSST) that made the monitoring data available to the researchers as a benchmark problem.
Facial Expression Recognition Based on Improved United Model

On the basis of the idea of unifying Active Appearance Model(AAM) and Active Shape Model(ASM), this paper mines the relation of peg points fully and proposes a method to construct local vein model. It modifies the matching algorithm to improve location precision and matching speed of feature point. Facial expression feature obtained by this algorithm is input to the nearest neighbor classifier. Classification results indicate the high recognition rate of the algorithm.
Word Sense Disambiguation for Indian Languages: A brief Survey

In this paper, we made a survey on Word Sense Disambiguation (WSD) using some of the Indian languages. A research in WSD has been conducted upto different extents. In this paper, we have gone through a survey regarding the different approaches adopted in different research works, the State of the Art in the performance in this domain, recent works in different Indian languages such as Bengali, Hindi, Punjabi language. We have made a survey on different competitions in this field and built a comparison according to results, obtained from those competitions.
An Effective Eye Location Method for Drowsy Driving Detection

For a driver fatigue monitoring system,one of the most important problems to solve is eye location.Present an improved approach to achieve fast and effective eye location.Firstly,horizontal and vertical integral projection is used to detect eye area.Then,dynamic threshold of binary-conversion of convolution template and morphological operations is used comprehensively to locate black area of eyes.After checking its validity,eye center can be located accurately.Experiment pictures conducted on CAS-PEAL and ORL faces show that this algorithm is time-saving and robust to a lot of complicated situation such as head rotation with a certain degree and face with glasses.This method can be used in occasions like driver fatigue monitoring system or any other occasions that need fast eye location.
Providing Automated Feedback on Software Design for Novice Designers

In this paper we describe the design and implementation of a pedagogical feedback agent, designed to provide on-demand feedback on software design. The implemented feedback agent was integrated with an online UML editor, and novice designers can design UML class diagrams within this environment and request formative feedback from the feedback agent. Tool evaluations were conducted with the purpose of improving the system and as way to observe how users respond to the provided feedback. Results from this research are encouraging and most of the evaluation participants found the automated feedback on design to be helpful.
Novel Approaches for Regional Multifocus Image Fusion

Image fusion is a research topic about combining information from multiple images into one fused image. Although a large number of methods have been proposed, many challenges remain in obtaining clearer resulting images with higher quality. This chapter addresses the multifocus image fusion problem about extending the depth of field by fusing several images of the same scene with different focuses. Existing research in multifocus image fusion tends to emphasis on the pixel-level image fusion using transform domain methods. The region-level image fusion methods, especially the ones using new coding techniques, are still limited. In this chapter, we provide an overview of regional multi-focus image fusion, and two different orthogonal matching pursuitbased sparse representation methods are adopted for regional multi-focus image fusion. Experiment results show that the regional image fusion using sparse representation can achieve a comparable even better performance for multifocus image fusion problems.
Recent Application of Polymer Supported Metal Nanoparticles in Heck, Suzuki and Sonogashira Coupling Reactions

Carbon-carbon coupling reactions via transition-metal-catalyzed processes have been intensively developed for their important synthetic applications. However, due to both economical and environmental concern, development of novel polymer supported catalysts is of great deal of attention in recent years. The use of these catalysts offers several ad- vantages such as easy workup of the products and recovery of the catalysts. In this paper, recent developments in the Heck, Suzuki and Sonogashira reactions with this type of catalyst are reviewed.
3D interactive system based on vision computing of direct‐flective cameras

A bare‐finger 3D interactive technology for portable devices was developed. Using directive‐flective cameras to reform the field of viewing, a blind working range close to the camera is eliminated. Moreover, the algorithm of vision computing, different from skin color detection, is presented to determine the positions of fingertips. The interactive range is workable from 1.5 to 50 cm above the entire surface of the display. The mean position error of less than 1 cm is achieved. This accuracy realizes a camera‐based 3D interactive system allowing for near‐distance functionality. Therefore, floating 3D images can be touched and interacted with, potentially creating more application and intuitive user‐machine interface.
Composition and Dynamics of Stress Granules

Stress granules are non-membranous assemblies of RNA and protein that form during conditions in which translation initiation is limited. Stress granules are of interest due to their potential role in the regulation of gene expression and their relation to other cytoplasmic RNP granules, such as p-bodies, germ granules, and neuronal granules. Additionally, stress granules are related to pathological aggregates observed in neurodegenerative diseases since (1) they share many protein components with these aggregates and (2) mutations that promote stress granule assembly or inhibit their clearance are causative in neurodegenerative disease. The goals of this thesis are (1) to understand the dynamics of stress granule assembly and disassembly, (2) to elucidate the RNA composition of stress granules, and (3) to understand how RNAs are targeted to stress granules. Herein we make several important observations about the composition and dynamics of stress granules. i) Stress granules assemble through a multistep process in which stable substructures, termed cores, form first and coalesce into larger stress granules. ii) Stress granules are a composite of many mRNAs and lncRNAs, and transcripts vary in their degree of recruitment from <1% to >95% enriched in stress granules. iii) RNAs partition to stress
Building multi-view real-time video face detection system based on Adaboost algorithm

In order to fast detect the multi-view face in Real-time video,the classifier which can effectively detect a wide range gesture and rotation face by using the extended Haar-like features,is trained.With using the classifier,a multi-view real-time video face detection system is built.The system includes two sub-systems,training system and detecting system.Training system uses a large number of images containing both positive and negative examples for training the classifier.In detection system,DirectShow is used to get real-time images from the USB camera,then images are detected by using the classifier.Experiments show that the system can quickly and accurately detected multi-view face in a real-time video,which makes it more practicable.