Miracle-dz/UniFAR-FTUs huggingface dataset:
Improvements of Temporal Error Concealment Schemes for H.264 Video Streams

Temporal error concealment schemes suggested in the newly composed video coding standard (H.264) are based on macroblocks, and only include spatial neighboring motion vectors in the candidate MV set. A method of subblock-based refined motion compensated concealment with weighting boundary match criteria was proposed. The candidate MV set is adaptively expanded, which improves the accuracy for motion vector recovery. An adaptive spatial/temporal estimation method with low complexity is used to effectively combine temporal and spatial concealment. The promotions are focused on decoder side, without any structure changes on H.264 video encoder and transport technology. They can be widely employed in multiple video devices. The simulation of transmission over 3GPP/3GPP2 mobile IP channels shows that the modified concealment schemes provide improvements in error resilience over those suggested in H.264.
Implementation of peer-to-peer updating system used in distributed heterochronous databases based on web service

To solve this problem of keeping date consistence in the heterochronous environment,the paper puts forward a synchronous updating system model,which applied Web Service to capture,store and then transfer updated things in the homogeneous distributed database system and farther implement the system’s model of data synchronization,In the design of this model,the concurrency control of distributed things and the method of failure inspection are discussed and solved successfully.Then on the basis of this model,the model is implemented by Java.Finally,the system was applied as a tool for DBA into a Student MIS in Computer Center of University,solving the synchronous updating problem successfully.
Issues in intelligent robots for search and rescue

Since the 1995 Oklahoma City bombing and Kobe, Japan, earthquake, robotics researchers have been considering search and rescue as a humanitarian research domain. The recent devastation in Turkey and Taiwan, compounded with the new Robocup Rescue and AAAI Urban Search and Rescue robot competition, may encourage more research. However, roboticists generally go not have access to domain experts: the emergency workers or first providers. This paper shares our understanding of urban search and rescue, based on our active research in this area and training sessions with rescue workers from the Hillsborough County (Florida) Fire Departments. The paper is intended to be a stepping stone for roboticists entering the field.
Broadband wireless data access over microcellular infrastructures

This paper describes a broadband wireless data access system using a microcellular infrastructure. This system can be envisioned as an overlay data system which shares the same network infrastructure as a microcellular voice system, such as the Personal Access Communications System (PACS). Unlike microcellular voice systems, however, the proposed system provides a high peak data rate of 2 Mbps, can operate with a group frequency reuse factor of one, only requires handoffs between the group areas of sixteen radio ports, and can start with a minimum of 1 MHz spectrum in each direction. We quantify the performance of the proposed system under different air interface assumptions, each of which has a different required complexity and achievable performance. The proposed system can provide adequate performance (i.e., 1% packet error rate) with only the use of either half rate channel coding or dynamic time slot assignment, for a 95% target coverage. Further performance improvement is possible with the use of SINR-based feedback power control.
Study and Practice of a Kind of Automatic Summarization System Focusing on News Articles

A kind of automatic summarization system, which could be applied.in the field of news, was presented in this paper. Firstly, the principles of automatic summarization focusing on news articles were introduced. Next, some experiences about constructing the library, in which the rule of subject extraction for news articles was storing, were also introduced. Then, the sample flow of the whole system could be got Lastly, the result of a large-scale black-box test was given and it revealed that the system was good enough for applied in practice.
Determining Services for the Mobile Tourist

The increasing popularity of mobile devices presents an opportunity for developing innovative mobile tourism services for tourism-related organizations. While there is much research on mobile tourism applications and on tourist needs and behavior, there is comparatively less work on studying the types of services they desire. The present study aims to determine mobile services that are important from the tourists' perspective using a factor analytic approach. This was first done via a survey of the literature and confirmed by a focus group. The set of candidate tourism services was then translated into a questionnaire for determining their appropriateness for mobile tourism. Thereafter, exploratory and confirmatory factor analytic procedures were performed. Our findings show that tourists appear to favor basic services such as those providing information about transportation, accommodation and food, while advanced ones such as context-aware services and trip planning were deemed comparatively less desirable. Practical and theoretical implications of our findings are also discussed.
An online real-time path compensation system for industrial robots based on laser tracker

Industrial robots have been widely used in many areas for the properties such as low cost, high flexibility and relatively large working space. The low absolute accuracy and low stiffness, however, limit the application in high precision areas. This article presents an approach for industrial robots that overcomes the inaccuracy of robotic path in offline programming. Robot Sensor Interface of KUKA robot controller makes the error compensation available. First, the compensation performance of the KUKA KR5 arc robot is investigated and the straight-line and circular arc path compensation strategies are proposed. Besides, an error compensation algorithm is proposed to generate the compensation values as well as to deal with the oscillation of real-time compensation. Finally, experimental results using a KUKA KR5 arc robot verify the correctness and accuracy of the approach.
IMAGE RETOUCHING AND IT'S DETECTION - A SURVEY

Image retouching is one more type of image forgery tool which is most commonly used for commercial and aesthetic applications. Retouching operation is carried out mostly to enhance or reduce the image features. Retouching is also done to create a convincing composite of two images which may require rotation, resizing or stretching of one of the image. The paper discusses the state of the art studies organized towards various image authentication techniques and algorithms in digital image Retouching process and its detection. The study also highlights a survey and comparative analysis of various image Retouching mechanisms and some detection methods. Keywords— Digital Image Processing, Image Retouching, image Inpainting, Image Forensics --------------------------------------------------------------------***------------------------------------------------------------------
VIAF (virtual international authority file) : Linking the deutsche nationalbibliothek and library of congress name authority files

The Deutsche Nationalbibliothek, the Library of Congress, and OCLC Online Computer Library Center are jointly developing a virtual international authority file (VIAF) for personal names which links authority records from the world's national bibliographic agencies and will be made freely available on the Web. The goals of the project are to prove the viability of automatically linking authority records from different national authority files and to demonstrate its benefits. The authority and bibliographic files from the Library of Congress and the Deutsche Nationalbibliothek were used to create the initial VIAF which contains over six million names with over a half million links. A key aspect of the project was the development of automated name matching algorithms which use information from both authority records and the corresponding bibliographic records. The practicality of algorithmically linking the personal names between national authority files was demonstrated; seventy percent of the authority records for personal names common to both files were automatically linked with an error rate of less than one percent. The long-term goal of the VIAF project is to combine the authoritative names from many national libraries and other significant sources into a shared global authority service.
Similarity image retrieval system using hierarchical classification: Experimental system on mobile internet with cellular phone

We developed a similarity image retrieval system for database consists of various kinds and large amount of image data. Our system has the following features. (1) The similarity retrieval algorithm selects the most similar group to the visual key step by step as a search space so that the system could achieve less computation and better precision. (2) The system can easily adapt each user's subjective criterion for similarity. (3) The interface is so user friendly that just showing a key image is enough to invoke content-based image retrieval. Based on the features above, we developed and evaluated a similarity retrieval system using cellular phone with digital camera as a multimedia terminal.
On Summarization and Timeline Generation for Evolutionary Tweet Streams

Short-text messages such as tweets are being created and shared at an unprecedented rate. Tweets, in their raw form, while being informative, can also be overwhelming. For both end-users and data analysts, it is a nightmare to plow through millions of tweets which contain enormous amount of noise and redundancy. In this paper, we propose a novel continuous summarization framework called Sumblr to alleviate the problem. In contrast to the traditional document summarization methods which focus on static and small-scale data set, Sumblr is designed to deal with dynamic, fast arriving, and large-scale tweet streams. Our proposed framework consists of three major components. First, we propose an online tweet stream clustering algorithm to cluster tweets and maintain distilled statistics in a data structure called tweet cluster vector (TCV). Second, we develop a TCV-Rank summarization technique for generating online summaries and historical summaries of arbitrary time durations. Third, we design an effective topic evolution detection method, which monitors summary-based/volume-based variations to produce timelines automatically from tweet streams. Our experiments on large-scale real tweets demonstrate the efficiency and effectiveness of our framework.
Troubleshooting with Wireshark: Locate the Source of Performance Problems

Whether you are a Wireshark newbie or an experienced Wireshark user, this book streamlines troubleshooting techniques used by Laura Chappell in her 20+ years of network analysis experience. Learn insider tips and tricks to quickly detect the cause of poor network performance. This book consists of troubleshooting labs to walk you through the process of measuring client/server/network delays, detecting application error responses, catching delayed responses, locating the point of packet loss, spotting TCP receiver congestion, and more. Key topics include: path delays, client delays, server delays, connection refusals, service refusals, receive buffer overload, rate throttling, packet loss, redirections, queueing along a path, resolution failures, small MTU sizes, port number reuse, missing support for TCP SACK/Window Scaling, misbehaving infrastructure devices, weak signals (WLAN), and more. Book supplements: sample trace files, Laura's Wireshark troubleshooting profile, and a troubleshooting checklist.
Digital image compression based on BEMD and PCA

Binary Empirical Mode Decomposition(BEMD) is a kind of adaptive method of data-driven,which is primary function dependent.Principle Component Analysis algorithm has an excellent performance in decorrelation and high compression ratio.Therefore,in this paper,a new method for compressing is proposed,which is implemented by first decomposing the original image through BEMD and then using the PCA algorithm to compress the decomposed subimages.By simulating on the Matlab,the validity and the superiority of this method are proved,and basically achieve the goal of a high signal to noise ratio under a high compression ratio.
Non-invasive blood pressure data acquisition employing pulse transit time detection

Changes in the transit time of arterial blood pulse under an occluding cuff can be used as indicators of blood pressure. In this non-invasive method arterial blood pulse is detected by piezoelectric pick-up placed proximally and distally under the cuff. As the cuff pressure is lowered from the value above presumed systolic pressure a distinct signal is received by the distal pick-up at the moment when the artery opens for the first time. This moment defines systolic blood pressure. With the following decrease in cuff pressure it has been observed that the pulse transit time decreases monotonously. The inflection point in pulse transit time plot, where the reduction in pulse transit time ceases and subsequently will keep constant, is defined as the point of diastolic blood pressure.
A systematic literature review of factors influencing acceptance on Mixed Reality technology

Mixed Reality (MR) is amongst the potential technologies that have attracted attention recently. The MR environment is unique since it combines real and virtual objects, interactive in real time and registered in 3-dimension. Even though proponents of MR put forward many advantages of MR, but there are still lack of studies on the users’ acceptance of the MR technology. Understanding the factors influencing users’ acceptance on the MR technology especially in education helps the developers to produce useful MR applications. The aim of this study is to identify the factors that determine users’ acceptance of MR application. A Systematic Literature Review (SLR) was carried since it uses a more rigorous and well-defined approach to reviewing the research evidence relevant to the study. Initially, 336 papers were retrieved by a manual search in six databases and 26 primary studies were finally included. Consequently, 27 factors were identified and analyzed. The findings have revealed that there are four types of factors that can be used to examine the acceptance of MR: productivity-oriented; entertainment dimensions; users personal background and overall system evaluation.
Designs of Mixed Method Research

Mixed methods research is becoming an increasingly popular approach in the discipline fields of sociology, psychology, education and health sciences. Calls for the integration of quantitative and qualitative research methods have been advanced in these fields. A key feature of mixed methods research is its methodological pluralism, which frequently results in research which provides broader perspectives than those offered by mono-method designs. The central premise of mixed methods is that the use of quantitative and qualitative approaches in combination provides a better understanding of research problems and complex phenomena than either approach alone. The purpose of this chapter is to review designs of mixed methods research. The study surveys the common designs of mixed methods research and examine the main characteristics of each in terms of purposes, strengths, and issues, and posits suggestions on the application of these designs.
Analysis of Financial Transactions using Machine Learning

Many people want to know the socio-ecological impact of the goods they purchase. In this thesis, we describe a system that computes the socio-ecological impact of those goods by analyzing uncategorized financial transactions. The computation is made possible by extending a system that can computate socio-ecological impact from categorized transactions. The extension further includes visualizations on the system’s web GUI using AngularJS and extension of the system’s Node.js API. To compute the socio-ecological impact the report describes a categorization service. To connect the service to the core system a RabbitMQ message queue was used. The service trained supervised machine learning models using Apache Spark’s machine learning library (MLlib) on a dataset containing about 2.4 million categorized transactions. This achieved a categorization accuracy of 82.9%. The main focus for future work is to increase accuracy by using named-entity recognition and splitting up the categorization into two steps using multiple categorizers. (Less)
A Survey of Detecting Regions of Interest in a Static Image

The detection of regions of interest (ROI) introduces visual attention mechanism from the human vision to the image analysis. It is significant to improve the efficiency of the existing image analysis system. In this paper, the current technique for detecting ROI in a static image is surveyed. After the background of ROI detection is introduced, the mechanism of visual attention in human visual system is addressed firstly. And then the main algorithms of ROI detection are classified into two categories including bottom up method and top down method. Each of them is discussed in detail respectively. The primary applications of ROI are described afterward. At the end, several research trends of ROI detection are given.
FIN multicast optimization algorithm in P2P communication

This paper proposed the factors integrated(FIN) multicast tree algorithm by considering the network node communication capability and the communication weights between nodes.The algorithm was based on the multi-link concurrent multicast tree model.By considering the structure characteristics of P2P network,which had tree manager node(TMN),it introduced the maintenance plan of multicast tree to solve the communication efficiency problem of the nodes join and leave on the multicast tree.Experiment result shows that FIN algorithm has better effect in the range of various weights by comparison among the branch first(BFI),joint first(JFI),weight first(WFI) and FIN algorithm.
pythOPT: A problem-solving environment for optimization methods

Optimization is a process of finding the best solutions to problems based on mathematical models. There are numerous methods for solving optimization problems, and there is no method that is superior for all problems. This study focuses on the Particle Swarm Optimization (PSO) family of methods, which is based on the swarm behaviour of biological organisms. These methods are easily adjustable, scalable, and have been proven successful in solving optimization problems. This study examines the performance of nine optimization methods on four sets of problems. The performance analysis of these methods is based on two performance metrics (the win-draw-loss metric and the performance profiles metric) that are used to analyze experimental data. The data are gathered by using each optimization method in multiple configurations to solve four classes of problems. A software package pythOPT was created. It is a problem-solving environment that is comprised of a library, a framework, and a system for benchmarking optimization methods. pythOPT includes code that prepares experiments, executes computations on a distributed system, stores results in a database, analyzes those results, and visualizes analyses. It also includes a framework for building PSO-based methods and a library of benchmark functions used in one of the presented analyses. Using pythOPT, the performance of these nine methods is compared in relation to three parameters: number of available function evaluations, accuracy of solutions, and communication topology. This experiment demonstrates that two methods (SPSO and GCPSO) are superior in finding solutions for the tested classes of problems. Finally, by using pythOPT we can recreate this study and produce similar ones by changing the parameters of an experiment. We can add new methods and evaluate their performances, and this helps in developing new optimization methods.
Novel Strategy of Motion Detection and Object Tracking Based on Robust Statistics

A novel motion detection method based on robust statistics was proposed.It used global motion estimation and hypothesis test to detect the independently moving objects in the video sequence captured by a moving camera.To improve the accuracy of the detection algorithm,occlusion effect was compensated by bi-directional motion estimation.Based on it,a robust active contour model was proposed to track the contours of the moving objects.The model was solved using Level Set method.Experimental results on real-world data show that the proposed algorithm can detect and track the moving objects correctly and reliably.
Robust method for facial features localization

In this paper, a robust hierarchical approach based on AdaBoost algorithm and C-V method was presented for facial features localization. First, four kinds of detectors were trained by AdaBoost algorithm for detecting faces, eyes, noses and mouths. Second, face regions were detected using the face detector combined with a rule of face edge. Third, the eye regions, nose regions and mouth regions were detected using the facial feature detectors, and the feature contours and feature points were extracted from the feature regions by C-V method. The experiments on DTU_IMM face test set resulted in 94.6% accuracy rate on eyes, 95.3% on noses and 98.4% on mouths, and the positions of the extracted feature points were accurate. Results show that the proposed approach is efficient and robust.
Delivering the Incredible Years® Dina Treatment Program in Schools for Early Elementary Students with Self-Regulation Difficulties

ABSTRACT The purpose of this paper is to describe the implementation of an evidence-based treatment, the Incredible Years® (IY) Small Group Dina Dinosaur Treatment program, as delivered in elementary schools to address the needs of children in kindergarten through second grade with self-regulation difficulties. Adaptations for school-based delivery of 17 intervention groups across three cohorts and 11 schools from an ongoing randomized controlled trial are described, and implementation data including qualitative feedback from school stakeholders are presented. Results show that, with implementation supports, this adapted model can be delivered in schools with fidelity comparable to the clinic-based model, although several activities were delivered at lower dosage in the low-income urban schools as compared with low-income rural or better resourced schools. Satisfaction among school counselors, teachers, and parents was consistently high. Implementation challenges include logistics such as space and scheduling, program fit with school practices and policies, use of specific treatment strategies such as time-out within the school context, capacity of school personnel to deliver the program, and selection of students and group composition. Lessons learned can inform adaptation and delivery of other evidence-based clinic treatments in school settings.