Miracle-dz/UniFAR-FTUs huggingface dataset:
Image compression and transmission using wavelets and vector quantization

To compact a large amount of multimedia data, and route it through a busy network like the Internet, or a low bandwidth one like the telephone network at interactive rates has emerged as a significant contemporary technological challenge. In this dissertation we take a unified “systems view” approach to developing real-time image and video compression/transmission systems. The objective is to produce systems with variable rate/distortion encoding at the source that can flexibly adapt to available channel bandwidth. There are three aspects to the overall impact of this research in the area of image and video coding. First, our new wavelet coding algorithm is a fundamental contribution in wavelet based compression. It can be used by all wavelet coding methods, and has been demonstrated to improve the performance of the most successful ones in existence. It also led to the first known wavelet coding algorithm with flexible data granularity. Such algorithms can be used in compression/transmission systems that are faster and more reliable than existing ones based on wavelet coding. Second, we have developed the first known compression algorithms that can automatically adapt to fluctuating available bandwidth, while maintaining joint rate distortion optimality. These algorithms are very suitable for use in current compression/transmission systems that use the Internet. Third, we develop a new video coding algorithm, in which we introduce the concept of a re-trainable motion transform. This method is faster and more accurate than older ones like MPEG-1, and of wider applicability than newer ones based on 3-D object modeling. This algorithm may be incorporated into the flexible current MPEG-4 standard for video coding.
One-shot multi-user cancellation receiver for wireless CDMA communication systems

This paper deals with a multiuser cancellation detection scheme for direct sequence code division multiple access (DS/CDMA) communication systems where the BPSK modulation technique is used in transmission. Asynchronous users and multipath fading phenomena are considered. The proposed receiver, named the one-shot detector is supposed to be used at the end of an uplink terrestrial channel. The one-shot receiver basic assumption is to divide signals into reliable and unreliable ones. The reliable signals are directly detected and cancelled from the whole received signal so as to improve the decision on unreliable signals. A suitable analytical approach is proposed in order to evaluate error probability (P/sub e/) of the receiver under consideration. Simulation results are also presented to validate obtained analytical predictions. The results shown here clearly demonstrate that the proposed receiver exhibits better performance and lowers the computational complexity and processing delay in comparison with previously proposed alternatives.
Arduino Sketches: Tools and Techniques for Programming Wizardry

Master programming Arduino with this hands-on guide Arduino Sketches is a practical guide to programming the increasingly popular microcontroller that brings gadgets to life. Accessible to tech-lovers at any level, this book provides expert instruction on Arduino programming and hands-on practice to test your skills. You'll find coverage of the various Arduino boards, detailed explanations of each standard library, and guidance on creating libraries from scratch plus practical examples that demonstrate the everyday use of the skills you're learning. Work on increasingly advanced programming projects, and gain more control as you learn about hardware-specific libraries and how to build your own. Take full advantage of the Arduino API, and learn the tips and tricks that will broaden your skillset. The Arduino development board comes with an embedded processor and sockets that allow you to quickly attach peripherals without tools or solders. It's easy to build, easy to program, and requires no specialized hardware. For the hobbyist, it's a dream come true especially as the popularity of this open-source project inspires even the major tech companies to develop compatible products. Arduino Sketches is a practical, comprehensive guide to getting the most out of your Arduino setup. You'll learn to: Communicate through Ethernet, WiFi, USB, Firmata, and Xbee Find, import, and update user libraries, and learn to create your own Master the Arduino Due, Esplora, Yun, and Robot boards for enhanced communication, signal-sending, and peripherals Play audio files, send keystrokes to a computer, control LED and cursor movement, and more This book presents the Arduino fundamentals in a way that helps you apply future additions to the Arduino language, providing a great foundation in this rapidly-growing project. If you're looking to explore Arduino programming, Arduino Sketches is the toolbox you need to get started.
Mapping the topographic epitopes of a model antigen

The thesis describes the development of a method for determining the antigenicity of different regions of the surface of a protein. The method involved the construction of a set of mutant antigens in which cysteine residues had been introduced at different points in the surface of the antigen. Each mutant protein was tethered through the surface cysteine residue and a bifunctional chemical cross-linker to solid phase, allowing the creation of an array of mutant antigens, each oriented so as to expose or to mask different topological regions of the antigen surface. Indeed, as expected, binding of a set of monoclonal antibodies proved sensitive to the orientation of the antigen. By use of this array of oriented antigen it became possible to compare the different regions of the antigen surface for binding to rabbit antiserum, and thereby to create a topological map of the antibody response. When the immunisations were undertaken with use of Freund's adjuvant, the antibody response to β-lactamase was mainly directed against a region centered on a flexible loop. Furthermore it comprised antibodies cross-reactive to both native and denatured protein. By contrast, in the absence of Freund's adjuvant, the antibody response was more evenly distributed, and with few cross reactive antibodies. This suggested that Freund's adjuvant denatures β-lactamase (as was confirmed experimentally), and that the appearance of dominant epitopes may follow the presentation of denatured protein to the immune system. These observations have implications for understanding the basis for dominance of B-cell epitopes, and also for design of vaccines.
Using an Object-Oriented Approach to Develop a Software Application

This paper describes a software development project completed using an object-oriented approach. Because Visual Basic . NET was used to build the Windows-based application, application design patterns were identified that would be beneficial in this development environment. A discussion of which design patterns were selected and how they were implemented using Visual Basic . NET is included, along with descriptions of object-oriented design documents and their role in the project. The paper also provides details about how the project has and will be used to provide teaching examples in software development courses. Object-Oriented Development 7 Table of
An Agent Based Method to Predict the Subsequent Concept in Concept Shifting Data Streams

The advent of new application areas leads to intensive research on data streams. Due to concept shifts in the underlying data, maintaining a timely updated model has become one of the most challenging tasks. The data streams originate from the events of the real world so we think the associations among these events should exist among the concepts of the originated data stream too. Extraction of hidden associations among the concepts can be useful for prediction of subsequent concept in data stream. In this paper we present an agent-based method for classification of data streams with concept shifts. The agent creates a history from the concept changes and uses this history to have an intelligent behavior. The results of conducted experiments showed that the agent is proper for classification of concept shifting data streams.
BORIS: a free, versatile open‐source event‐logging software for video/audio coding and live observations

Quantitative aspects of the study of animal and human behaviour are increasingly relevant to test hypotheses and find empirical support for them. At the same time, photo and video cameras can store a large number of video recordings and are often used to monitor the subjects remotely. Researchers frequently face the need to code considerable quantities of video recordings with relatively flexible software, often constrained by species‐specific options or exact settings. BORIS is a free, open‐source and multiplatform standalone program that allows a user‐specific coding environment to be set for a computer‐based review of previously recorded videos or live observations. Being open to user‐specific settings, the program allows a project‐based ethogram to be defined that can then be shared with collaborators, or can be imported or modified. Projects created in BORIS can include a list of observations, and each observation may include one or two videos (e.g. simultaneous screening of visual stimuli and the subject being tested; recordings from different sides of an aquarium). Once the user has set an ethogram, including state or point events or both, coding can be performed using previously assigned keys on the computer keyboard. BORIS allows definition of an unlimited number of events (states/point events) and subjects. Once the coding process is completed, the program can extract a time‐budget or single or grouped observations automatically and present an at‐a‐glance summary of the main behavioural features. The observation data and time‐budget analysis can be exported in many common formats (TSV, CSV, ODF, XLS, SQL and JSON). The observed events can be plotted and exported in various graphic formats (SVG, PNG, JPG, TIFF, EPS and PDF).
Resource and Energy Efficient Virtual Machine Migration in Cloud Data Centers

Cloud computing service has been on the rise over the past few decades, which has led to an increase in the number of data centers, thus consuming more amount of energy for their operation. Moreover, the energy consumption in the cloud is proportional to the resource utilization. Thus consolidation schemes for the cloud model need to be devised to minimize energy by decreasing the operating costs. The consolidation problem is NP-complete, which requires heuristic techniques to get a sub-optimal solution. The authors have proposed a new consolidation scheme for the virtual machines (VMs) by improving the host overload detection phase. The resulting scheme is effective in reducing the energy and the level of Service Level Agreement (SLA) violations both, to a considerable extent. For testing the performance of implementation, a simulation environment is needed that can provide an environment of the actual cloud computing components. The authors have used CloudSim 3.0. 3 simulation toolkit that allows testing and analyzing Allocation and Selection algorithms.
How do I choose the right NoSQL solution? A comprehensive theoretical and experimental survey

With the advent of the Internet of Things (IoT) and cloud computing,the need for data stores that would be able to store and process big data inan ecient and cost-e ective manner has increased dramatically. Traditionaldata stores seem to have numerous limitations in addressing such requirements.NoSQL data stores have been designed and implemented to address the shortcomingsof relational databases by compromising on ACID and transactionalproperties to achieve high scalability and availability. These systems are designedto scale to thousands or millions of users performing updates, as wellas reads, in contrast to traditional RDBMSs and data warehouses. Althoughthere is a plethora of potential NoSQL implementations, there is no one-size- t-all solution to satisfy even main requirements. In this paper, we explorepopular and commonly used NoSQL technologies and elaborate on their documentation,existing literature and performance evaluation. More speci cally,we will describe the background, characteristics, classi cation, data model andevaluation of NoSQL solutions that aim to provide the capabilities for big dataanalytics. This work is intended to help users, individuals or organizations,to obtain a clear view of the strengths and weaknesses of well-known NoSQLdata stores and select the right technology for their applications and use cases.To do so, we rst present a systematic approach to narrow down the properNoSQL candidates and then adopt an experimental methodology that can berepeated by anyone to nd the best among short listed candidates consideringtheir speci c requirements.
Automatic Segmentation for Textured Object Images

In this paper, we proposed an automatic segmentation method of object color images with irregular texture. Recently segmentation often used for the image retrieval and in the application. It is more important to approximate the regions than to decide precise region boundary. A color image is divided into blocks, and edge strength for each block is computed by using the modified color histogram intersection method that has been developed to differentiate object boundaries from irregular texture boundaries effectively. The edge strength is defined to have high values at the object boundaries, while it is designed to have relatively low values at the texture boundaries or in the interior of a region. The proposed method works based on small-size blocks, the color histogram of each of which is computed preliminarily once. Thus it works fast but provides rough segmentation. A hybrid color quantization method is used to select a small number of appropriately quantized colors quickly. The proposed method can be applicable for the segmentation in object based image retrieval.
HTSPN: An Experience in Formal Modeling of Multimedia Applications Coded in MHEG or Java

Multimedia authoring involves people not familiar with formal design techniques, but eager to check documents against synchronization, scheduling and resource allocation errors. Visual modeling with Petri Nets answers that need with a graphic syntax and a formal semantics that makes models executable. A Petri Net defines a bipartite graph where summits are divided into places associated with data processing functions and transitions which represent synchronization points. The chapter discusses an experiment with Hierarchical Time Stream Petri Nets, a timed extension of Petri Nets which was designed with distributed multimedia systems in mind. HTSPNs define a unified framework to structure complex and interactive documents. Dynamic synchronization strategies based on temporal intervals composition make it possible to take the asynchronous nature of distributed systems into account. Last but not least, a HTSPN remains an open model, which can be extended with implementation details regarding, e
3 Architectonic Mapping of the Human Cerebral Cortex

The classical cytoand myeloarchitectonic maps of the human cerebral cortex considerably influenced the concept of localization of function. Presently, these maps serve as anatomical references in functional imaging studies. However, the classical maps suffer from drawbacks such as the highly observer-dependent definition of areal borders; the fact that they present only a single aspect of architectonic organization of the cortex (e.g. only cytoarchitecture), and the lack of information on intersubject variability of location and size of a cortical area in a spatial reference system. Recent methodological progress in computerized image analysis of histological specimens, the introduction of markers which reflect various architectonic aspects of cortical organization (e.g. receptor autoradiography), and the development of warping techniques to compensate for intersubject variability of brain structure in 3D made it possible to overcome these drawbacks. We propose a new concept of architectonic mapping which is based on: (i) a definition of areal borders by using multivariate statistical analysis, and not by highly subjective judgements; (ii) a quantitative analysis of similarity and dissimilarity in architecture between cortical areas; and (iii) a multimodal characterization of cortical organization based on cyto-, myeloand receptor-architectonic mapping. The comparison of architectonic maps with functional imaging data in a common standard reference space allows, for the first time, a direct analysis of correlations between structure and function in the living human brain, and provides new insights into the architecture of the cerebral cortex.
Incremental maintenance of discovered spatial association rules

Executing spatial association rule mining repeatedly is often necessary to get interesting and effective rules.Though incremental maintenance algorithms can be introduced to improve the efficiency of association rule mining, currently there exists no such algorithm that can use spatial datasets directly. To solve this problem, the update strategy of the discovered rules was discussed. Both threshold changes and spatial datasets updates were taken into consideration, and an incremental mining algorithm called Incremental Spatial Apriori( ISA) was suggested. ISA algorithm aimed to update frequent predicate sets and association rules after the minimum support threshold decreased or new spatial layers added. This algorithm did not rely on the creation and update of spatial transaction tables; it directly used spatial layers as input data. In experiments with real-world data, the mining result extracted by ISA and Apriori-like algorithms are identical, but ISA can save 20. 0% to71. 0% time comparatively. Besides, 1 372 722 rules were successfully updated with the filtering method, costing less than0. 1 seconds. These results indicate the incremental update strategy and algorithm for spatial association rules suggested in this paper are correct, efficient and applicable.
Bayesian inference application to burglary detection

ii ACKNOWLEDGEMENTS I am grateful to my advisor Dr. Supratik Mukhopadhyay for supporting and guiding me throughout this thesis, and giving me the opportunity to work on the surveillance project. His guidance , advise, discussions were invaluable to me. I am grateful to Dr. to be part of my thesis committee and sparing their precious time.
Facial expression recognition based on improved LBP and LDP

Put forward a combined with improved LBP(Local Binary Mode)and the LDP(Local Directional Pattern)face expression method of feature extraction.The dimension of improved LBP has decreased significantly,more considered the space structure information.The method of LDP has the very strong antinoise ability,and better edge information extraction.Based on the two methods can be complementary advantages,the image block branch area with improved LBP for first feature extraction.Subspace of face use LDP area feature extraction.Finally the features of the improved LBP extraction and extraction of the LDP extraction characteristics connected as the general features.JAFFE database of experiment proves the proposed method has more effectively improving the face expression recognition.
Secure bits with quantum pseudo-telepathy

Motivated by the concept of quantum pseudo-telepathy games as well as by quantum key distribution protocols such as [1], the security of which is based on the non-signaling principle, we try to answer the question wheather it is possible to generate a perfectly secure, shared bit between two parties by a single usage of quantum correlations and a performance of local operations on the input and output. We provide both parties with some prior shared entanglement and the possibility of postselection, e.g. discard of inputs and outputs, aiming to prevent any eavesdropper bound by the non-signaling condition from successfully performing an attack. After, in a first step, defining the framework and setting up the requirements we are going to see that quantum mechanics does not allow for a physical simulation of such correlations. For the case of binary output we will even see that, in order to make perfectly correlated bits perfectly secure, we would need maximal nonlocal correlations which also prohibits a quantum physical representation.
Network traffic orediction model of wavelet combined neural network

Based on the multi-time scale and the nonlinear character of the network traffic time series,a new network traffic prediction model which combines the wavelet transform and neural network is presented.The suggested model has advantage with its absorbing some merits of wavelet transform and artificial neural network.First,the traffic time series are decomposed to the scaling coefficient series and wavelet coefficient series.Then,RBF neural network and Elman neural network are used respectively to make prediction. Finally,the two predictions are combined into the final result through BP neural network.The simulation results on real network traffic show the new model has better predictive precision.
Image Retrieval Method Based on Salient Region and pLSA

Because image retrieval method using global features is largely affected by background,presented a novel image retrieval method based on salient region and pLSA.In this approach,salient regions are first detected through spectral residual and multi-resolution analysis,then color and texture features of those salient regions are quantized into a dictionary of visual words by K-mean clustering,after that each image is represented by a bag of visual words.Finally,by exploiting probabilistic latent semantic analysis,achieve the latent semantic feature,which can be used to construct a SVM model to fulfill the image retrieval.Compare the method proposed with the global-based image retrieval method,the experimental results show that the accuracy of image retrieval method based on salient region is higher than the other one.
Reducing bias in supervised learning

Nonparametric statistical supervised learning methods often suffer from bias caused by non-uniformity of the probability distribution of training samples. This problem is discussed in this paper and a new nonparametric neighborhood method for classification and estimation that significantly reduces the bias is proposed. Simulations exemplify the advantages, and theoretical results are noted.
Computer and

: The objective of this system is to present an automated system for human face recognition for an organization or institute to mark the attendance of their students or employees. This paper introduces face detection method using the Voila and Jones algorithm and recognition using correlation technique. The system will record the attendance of the students in class room environment. The above system is fully automated and easily deployable. User gets an authentication to upload the image containing file and also to view the attendance.
A review of Technologies on Tracking Tibetan Public Opinion Topics

The target of technologies on tracking Tibetan-based network public opinion topics is to track the development of some known topics. By tracking these topics could help people to grasp the trend of public opinion. This research area becomes more and more important on Natural Language Processing domain and how to apply these state-of-the-art computer science technologies on the study of national language has drawn lots of awareness to related researchers. This article will introduce some features about Tibetan language and its grammar. Some technologies about categorizing Tibetan text and tracking Tibetan-based network public opinion will also be talked about.