Miracle-dz/UniFAR-FTUs huggingface dataset:
Analysis of Full-Length Metagenomic 16S Genes by SMRT ® Sequencing

Assaying 16S CCS Above: Raw read length distributions for sequencing of full-length 16S (~1500 bp) amplicons. The dotted vertical line denotes the minimum read length for CCS. Left: Mean quality-values for fulllength 16S CCS sequences by raw read length. High-throughput sequencing of the 16S rRNA gene has become a valuable tool for characterizing microbial communities. However, the short read lengths produced by second-generation sequencing introduce bias and cannot provide taxonomic classification below the genus level, limiting biological insight. The best results are therefore obtained with full-length sequences of the 16S gene, however doing so with Sanger sequencing is time-consuming, costly, and low-throughput. SMRT® Sequencing has been used previously to analyze 16S amplicons[1], but to our knowledge no attempts have been made to analyze full-length (~1500 bp) 16S. In this study, we evaluate the PacBio® RS and PacBio® RS II for full-length 16S rRNA gene sequencing and community profiling. We profiled four microbial communities (Cecum, Soil, Water, and a Mock control) for bacterial 16S, archaeal 16S, and fungal ITS using barcoded primers. Sample data was evaluated with rDnaTools[2], a custom pipeline that integrates the widely used Mothur suite[3] with PacBio-specific utilities. Each SMRT Cell of full-length 16S data generated 17-24k CCS reads, of which between 10-16k had >99% predicted concordance to the reference. Community samples were predicted to contain between 2.3-15 times as many species as phyla, with abundance levels as low as 0.05%. SMRT® Sequencing therefore represents a novel platform for community analysis, allowing for high depth and unprecedented sensitivity. 1. Export CCS Sequence Data from Bas.H5 2. Filter Sequences by Quality 3. Group Sequences by Barcode and/or Primer 4. Align Sequences to Reference 5. Filter Partial Alignment Reads (<80%) 6. Identify & Remove Chimeric Sequences 7. Pre-Cluster Sequences 8. Calculate Distance Matrix 9. Cluster Sequences 10.Generate OTU Consensus Sequences 11.Classify Clusters based on the Consensus 12.Summarize OTUs Analysis of 16S CCS sequences was carried out with standard tools from the Mothur package (http://www.mothur.org)[3] where possible. Where existing tools were not well suited for analyzing SMRT sequence data, custom scripts were written using Python. The complete analysis pipeline, and all custom scripts are available for download on GitHub (https://github.com/bnbowman/rDnaTools). Steps highlighted in bold are implemented with custom scripts.
Improved Time Aware Incremental PageRanking Using Personalized Link Structure Analysis

This paper devises time-aware and Link Analysis based improvement pageranking technique. The time-aware techniques exploit temporal information, present in networks like the World Wide Web, to produce rankings reflecting authority with regard to a temporal interest. The link prediction analysis techniques produce rankings based on the relative change with regard to a temporal interest. The time-aware methods extend PageRank and are defined incrementally. The link prediction based methods are defined independently, one extending PageRank and the other based on a comparison of precomputed page rankings. The method proposed in this paper suggests an improvement in time-aware PageRanking method by giving information of temporal interest of a particular user on a specific web page.So,this method is useful for finding time spent by a user on a particular web page which suggests user’s temporal behavior and link prediction for a particular webpage by that user.
Interactive cardiac mapping. II. Data analysis

For pt.I see ibid., p.204-5, 1989. An interactive cardiac mapping system is described which integrates human intelligence and the power of computers. In pt.I the data acquisition hardware and software of this mapping system were described. After acquiring cardiac potential data, the next step is to analyze the data to obtain the activation sequence of the heart and to draw an isochrone map. The corresponding data analysis methods are described. The resulting data analysis software and the previously described data acquisition hardware and software constitute a complete interactive cardiac mapping system for the study of cardiac electrophysiology of the human and animal heart. <<ETX>>
Provide a Model for Web Content Strategy, Using Data Mining Techniques

A B S T R A C T Background: Application of data mining in the process of extracting data from a database and user experience of websites related to ecommerce. Objective: It is usually extracted by using data mining techniques and data server log files or data acquisition is performed using special software. In this paper, clustering methodology is applied to different customer behavior have a website selling software products have been introduced in the field. This classification can be used to profile for each group of customers. Results: In the present study, using unsupervised cluster analysis and observing patterns in the user clicked is exploring. Conclusion: The results obtained will help the team website maintenance through the understanding of users' behavior to improve the quality of your website. Thus, by analyzing data collected from website click streams, the kinds of behavior categories and then offers solutions for website design, better quality is available.
LINGUISTIC INTERFACES IN EARLY ACQUISITION: LEXICAL CLASSES AND GRAMMATICAL SYSTEMS IN HEBREW CHILD LANGUAGE

i TRANSCRIPTION AND GLOSSARY CONVENTIONS. 1 CHAPTER I – INTRODUCTION. 3 1.1 Theories of Language Acquisition. 4 1.2 Domains of Grammatical Analysis. 11 1.2.1 Verb Inflection. 12 1.2.2 Predicate Constituency. 18 1.2.3 Marking of Non-Subject Constituents [NSCs]. 20 1.3 Psycholinguistic Principles. 25 1.3.1 Structural Opacity/Transparency. 25 1.3.2 Usage Productivity. 27 1.3. 3 Developmental Phases. 30 1.4 Linguistic Interfaces in Acquisition. 31 1.5 Goals of Study. 33 CHAPTER II – THE STUDY. 35 2.1 Participants. 36 2.2 Data-Base. 37 2.3 Categories of Analysis. 40 2.3.1 Linguistic Categories. 40 2.3.2 Opacity/Transparency of Grammatical Forms. 43 2.3. 3 Productivity in Use of Grammatical Forms. 46 CHAPTER III – FINDINGS. 48 3.1 Developmental Patterns. 48 3.1.1 Developmental Phases. 48 3.1.2 Verb Inflection across Phases. 49 3.1.3 Prepositional Marking across Developmental Phases. 53 3.2 Inter-Domain Convergences. 56 3.2.1 Verb Inflection and Predicate Constituency. 57 3.2.2 Verb Inflection and Prepositional Marking. 64 CHAPTER IV – DISCUSSION. 68 4.1 Summary of Findings. 68 4.2 Psycholinguistic Facets of Early Grammatical Development. 69 4.2.1 Bridging Categories. 69 4.2.2.1 Non-Finite Verb Usage. 70 4.2.2.2 Non-Marking of Syntactic Relations. 75 4.2.2 Developmental Phases. 78 4.2.3 Individual Differences. 80 4.3 Inter-Domain Convergences. 82 4.3.1 Verb Inflection and Predicate Constituency. 82 4.3.2 Verb Inflection and NSC Marking. 83 4.4 Implications of the Study. 85 4.4.1 Evidence in Acquisitional Research. 86 4.4.2 The Role of Opacity in Developing Grammar. 88 4.4.3 Interfaces in Acquisition. 89 4.5 Directions for Further Research. 90 REFERENCES. 93 APPENDIX. 120 HEBREW ABSTRACT. א
Neural networks in specification level software size estimation

Presents a neural network approach to software size estimation. A multilayer feedforward network is trained using the backpropagation algorithm. The training and testing data consist of randomly generated structured analysis descriptions as input data and corresponding algorithm based size metric values as output data. The size metrics used in the experiments are Albrecht's (1979) function points, Symon's (1988) Mark II function points, and DeMarco's (1982) function bang metric. The experiments indicate that neural networks can learn to calculate software size estimates. In each of the experiments it was found that the results depend on the features of the input data, the metric, and the convergence criteria used. The results also encourage the development of a general input set to represent size-related features of graph-based system descriptions. <<ETX>>
Getting acquainted with social networks and apps: Snapchat and the rise of ephemeral communication

Purpose – The traditional library image that comes to mind upon hearing this word is of vertical files filled with newspaper clippings, photos, brochures, flyers on a popular topic or event. Design/methodology/approach – The modern image of ephemera, however, is now more nuanced and complex, as the increased creation of digital ephemera provides opportunities and challenges for libraries and archives. Findings – There now need to be considerations for dealing with digital materials and artifacts that are short-lived and temporary. These digital ephemera are increasing every day, with a presence in the world that is anything but temporary. Originality/value – The Library of Congress announced that it would be digitally archiving every public tweet since Twitter’s inception in March 2006 (Raymond, 2010). As of 2013, they had archived 170 billion tweets and were receiving nearly a half billion tweets a day (Allen, 2013). However, the magnitude of the project is being grappled with and currently the project a.
Performance of a low complexity CELP speech coder under mobile channel fading conditions

The authors report on the simulation of a voice codec intended for the terrestrial and satellite radio environments. The coder is based on a complexity reduced version of code-excited linear prediction (CELP). The codebook search complexity has been reduced to only 0.5 MFLOPS (million floating point operations per second) while maintaining excellent speech quality. Novel methods to quantize the residual and the long- and short-term model filters are presented. Due to its inherent simplicity, the codec can be easily realized in VLSI form or implemented on a dedicated single-chip digital signal processor. The coder has been tested under simulated channel conditions. Different block coding and convolutional coding techniques have been applied to improve the performance of the coder in the presence of burst errors. <<ETX>>
Hierarchical SOM applied to image compression

The increase of the need for image storage and transmission in computer systems has increased the importance of signal and image compression algorithms. The approach involving vector quantization (VQ) relies on the design of a finite set of codes which will substitute the original signal during transmission with a minimal of distortion, taking advantage of the spatial redundancy of image to compress them. Algorithms such as LBG and SOM work in an unsupervised way toward finding a good codebook for a given training data. However, the number of code vectors (N) needed for VQ increases with the vector dimension, and full-search algorithms such as LBG and SOM can lead to large training and coding times. An alternative for reducing the computational complexity is the use of a tree-structured vector quantization algorithm. This paper presents an application of a hierarchical SOM for image compression which reduces the search complexity from O(N) to O(log N), enabling a faster training and image coding. Results are given for conventional SOM, LBG and HSOM, showing the advantage of the proposed method.
Broadcast disks: Dynamic data scheduling in mobile communication

Recently, lot of work was done on data dissemination for asymmetrical communication environments. However, majority of studies are confined to push based broadcast and that too in single channel data dissemination. Few studies are on multiple channel data dissemination, but again the access frequencies are assumed fixed for a particular period. Since mobile users data access patterns change dynamically, the allocation of broadcast disks (channels) generated separately by push-pull calculations are not optimal after changes in access patterns. This suggests that the number of broadcasting channels and organization of the data items in the broadcast disks should be continuously updated to match changing access patterns. Creating new broadcast disks from scratch is not feasible in terms of time and efforts. A better solution is to adjust the structure of broadcast disks incrementally to accommodate changes in access patterns. This paper proposed Adaptive Data Scheduling Algorithm for generating broadcast program for multiple channels and compared the results with the FLAT and DL algorithms. It is seen that the proposed incremental algorithm is performing better in terms of scalability and reducing the data access times.
DCNP: data communication management system for network node processors in a distributed processing environment

Network node processors (NNPs), which can execute application programs and can cooperate with each other via high-speed LANs, have become essential components for distributed online systems. DCNP is a data communication management system for NNP. DCNP provides unified communication interfaces and high-performance and highly reliable communication services. An addressing technique which unifies program interfaces for node-to-terminal communications and internode communications is presented. Socket interface extensions for improving performance and techniques for highly reliable internode multicast communications on multiple LANs are also presented. DCNP has been implemented with a Unix kernel on fault-tolerant minicomputers and is operating in online systems. <<ETX>>
The PUNDIT natural-language processing system

The authors describe the PUNDIT (Prolog Understanding of Integrated Text) text-understanding system, which is designed to analyze and construct representations of paragraph-length text. PUNDIT is implemented in Quintus Prolog, and consists of distinct lexical, syntactic, semantic, and pragmatic components. Each component draws on one or more sets of data, including a lexicon, a broad-coverage grammar of English, semantic verb decompositions, rules mapping between syntactic and semantic constituents, and a domain model. Modularity, careful separation of declarative and procedural information, and separation of domain-specific and domain-independent information all contribute to a system which is flexible, extensible and portable. Versions of PUNDIT are now running in five domains, including four military and one medical. <<ETX>>
A Novel Algorithm for Cross Level Frequent Pattern Mining in Multidatasets

pattern mining has become one of the most popular data mining approaches for the analysis of purchasing patterns. There are techniques such as Apriori and FP-Growth, which were typically restricted to a single concept level. We extend our research to discover cross - level frequent patterns in multi-level environments. Unfortunately, little research has been paid to this research area. Mining cross - level frequent pattern may lead to the discovery of mining patterns at different levels of hierarchy. In this study a transaction reduction technique with FP-tree based bottom up approach is used for mining cross-level pattern. This method is using the concept of reduced support.
Building an environment map using a sweeping system based on a single ultrasonic sensor

We present an efficient and cheap approach to building a sonar based map for autonomous mobile robots in indoor environments. The system uses one ultrasonic sensor (emitter and receiver are separated) mounted on a motorization constituted by two motors allowing horizontal and vertical scanning. The reading is modelled as probability profiles projected on a two-dimensional map. These readings provide information concerning empty and occupied areas in the sensor cone. The world is modelled as a grid of cells. Using a raster-based approach to computer graphics, we determine the cells of the area occupied by the sensor cone. The map can be used to plan paths and for landmark recognition. Results from actual runs are presented.
The classification of motion in image sequences using 3D recursive adaptive filters to obtain neural network input vectors

A new application of neural networks is described that permits the selective classification of objects on the basis of their motion in digital image sequences. An adaptive 3D recursive linear-trajectory (LT) filter is employed to track a moving object on a smoothly-varying space-time trajectory. The trajectory information produced by the adaptive 3D LT filter is used as the input vector to a conventional multilayer perceptron (MLP) neural network to perform the classification of motion.
Learning SKOS Relations for Terminological Ontologies from Text

The problem of learning concept hierarchies and terminological ontologies can be divided into two subtasks: concept extraction and relation learning. The authors of this chapter describe a novel approach to learn relations automatically from unstructured text corpus based on probabilistic topic models. The authors provide definition (Information Theory Principle for Concept Relationship) and quantitative measure for establishing “broader” (or “narrower”) and “related” relations between concepts. They present a relation learning algorithm to automatically interconnect concepts into concept hierarchies and terminological ontologies with the probabilistic topic models learned. In this experiment, around 7,000 ontology statements expressed in terms of “broader” and “related” relations are generated using different combination of model parameters. The ontology statements are evaluated by domain experts and the results show that the highest precision of the learned ontologies is around 86.6% and structures of learned ontologies remain stable when values of the parameters are changed in the ontology learning algorithm.
Battery Modeling Based on the Co

A new battery model by coupling and computational fluid dynamics (CFD) provides the insight of electrical performan temperature distribution of a battery pac potentially suitable for hybrid electric vehicl vehicle (EV) battery modeling because of the high temperature nature of these applications Hybrid vehicle (HEV) and electric vehi future trend for automotive industry. T intensive research in the related areas and has been one of the hottest topics. Models usually divided in two types: 1) physics thermal management simulation 2) electric for system level simulation. Each type has cons. Computational fluid dynamics (CFD been well known for battery pack thermal [2]. The advantage of CFD is that it can a the temperature distribution based on the h boundary conditions, geometry, material pro drawback is that it does not have a good mechanism. Therefore usually over-simplif are used to carry out CFD analysis. On the o models are suitable for system level simula of the most significant advantages of the that they are very fast in terms of simulatio simply because they are lumped parameter parameters are curve fitted from lab me drawback is that it lacks of temperature di makes it impossible for thermal managem therefore propose a new battery model that c model types, circuit model based on CFD one hand the circuit model provides as a he other hand, realistic battery pack geometry temperature distribution as a function of d material, flow rate, etc. The proposed batter simulated between the circuit model and Within each time step of the co-simu generated by the circuit model is sent to source. CFD model then uses the heat from calculate the temperature distribution, a upling of Electrical Circuit and Computation
Techniques for Wireless Channel Modeling in Harsh Environments

With the rapid growth in the networked environments for different industrial, scientific and defense applications, there is a vital need to assure the user or application a certain level of Quality of Service (QoS). Environments like the industrial environment are particularly harsh with interference from metal structures (as found in the manufacturing sector), interference generated during wireless propagation, and multipath fading of the radio frequency (RF) signal all invite novel mitigation techniques. The challenge of achieving the benefits like improved energy efficiency using wireless is closely coupled with maintaining network QoS requirements. Assessment and management of QoS needs to occur, allowing the network to adapt to changes in the RF, information, and operational environments. The capacity to adapt is paramount to maintaining the required operational performance (throughput, latency, reliability and security). This thesis address the need for accurate radio channel modeling techniques to improve the performance of the wireless communication systems. Multiple different channel modeling techniques are considered including statistical models, ray tracing techniques, finite time-difference technique, transmission line matrix method (TLM), and stochastic differential equation-based (SDE) dynamic channel models. Measurement of ambient RF is performed at several harsh industrial environments to demonstrate the existence of uncertainty in channel behavior. Comparison of various techniques is performed with metrics including accuracy, applicability, and computational efficiency. SDEand TLM-based methods are validated using indoor
Improving Iterative Retinex Algorithm for Dynamic Range Compression

In this paper, the iterative Retinex algorithm is improved to handle dynamic range compression problems. Based on the analysis of the McCann-Sobel algorithm, the iterative smoothing operation can be interpreted as an asymmetric diffusion. In order to characterized the sharp discontinuities in illumination, an edge-stopping function is introduced into the iterative procedure, which is inspired by anisotropic diffusion. Using the improved illumination estimator, dynamic range of images can be arbitrarily manipulated while suppressing undesirable artifacts. Experiments show that the proposed algorithms outperforms several derivatives for dynamic range compression based on the iterative Retinex.
A Novel Method for Parallel Resources Acquisition from Bilingual Web Pages

A new approach is proposed for acquiring parallel resources by expanding seeds (some high-quality parallel sentence pairs) in the same page. Specifically, given a bilingual web page, the method is composed of three challenging tasks: 1) page’s content structure is detected for adaptive viewing on its main data region; 2) some high-quality parallel sentence pairs in the main data region are selected as seeds for the next task; 3) wrappers for mining parallel resources are learnt by expanding the seeds. We identify and extract more parallel resources in the same page using the learnt wrappers. Our method can be applied to web documents written in any markup language and in any human language. The test is based on 500 bilingual web pages randomly selected from 12 popular English learning web sites, which gets a high F-score of 85.68%. The experimental results show that our method is quite promising.
SKOS Simple Knowledge Organization System Primer

SKOS—Simple Knowledge Organization System—provides a model for expressing the basic structure and content of concept schemes such as thesauri, classification schemes, subject heading lists, taxonomies, folksonomies, and other similar types of controlled vocabulary. As an application of the Resource Description Framework (RDF), SKOS allows concepts to be composed and published on the World Wide Web, linked with data on the Web and integrated into other concept schemes. This document is a user guide for those who would like to represent their concept scheme using SKOS. In basic SKOS, conceptual resources (concepts) are identified with URIs, labeled with strings in one or more natural languages, documented with various types of note, semantically related to each other in informal hierarchies and association networks, and aggregated into concept schemes.