Miracle-dz/UniFAR-FTUs huggingface dataset:
A multi-level abstraction model for competitive learning neural networks

Competitive learning neural networks are powerful analytical tools for data clustering and topology-preserving visualization. However, they are limited in the sense of being unable to achieve more than one task on the same network. When applied to clustering tasks, every neuron unit is supposed to represent one of the inherent data clusters, while learning topology requires much more neuron units. The aim of this work is to figure out how connections between neurons -- specially those inserted by a competitive Hebbian learning -- can be exploited to construct higher abstraction levels of a topology-preserving neural network. The idea is to devote the basic level of the network to detailed description of the data while taking advantage of higher abstraction levels to facilitate quantitative analysis and structural overview of the network. The abstraction is done in two different fashions: macro and micro abstractions. In macro abstraction, the objective is to cluster the first-level neuron units into their principal groups corresponding to the clusters inherent in the data. In contrast, micro abstraction is designed to capture underlying clusters according to a given granularity degree. The abstraction-level units are also connected to reflect a simplified structure of the data distribution. At the end, the basic level of the network can be hierarchically organized with one or more abstraction levels, permitting both qualitative and quantitative analysis of the data. Simulations on many synthetic data shown the relevance of proposed model.
A Goal-Oriented, Sequential, Inverse Design Method for the Horizontal Integration of a Multistage Hot Rod Rolling System

The steel manufacturing process is characterized by the requirement of expeditious development of high quality products at low cost through the effective use of available resources. Identifying solutions that meet the conflicting commercially imperative goals of such process chains is hard using traditional search techniques. The complexity in such a problem increases due to the presence of a large number of design variables, constraints and bounds, conflicting goals and the complex sequential relationships of the different stages of manufacturing. A classic example of such a manufacturing problem is the design of a rolling system for manufacturing a steel rod. This is a sequential process in which information flows from first rolling stage/pass to the last rolling pass and the decisions made at first pass influence the decisions that are made at the later passes. In this context, we define horizontal integration as the facilitation of information flow from one stage to another thereby establishing the integration of manufacturing stages to realize the end product. In this paper, we present an inverse design method based on wellestablished empirical models and response surface models developed through simulation experiments (finite-element based) along with the compromise decision support problem (cDSP) construct to support integrated information flow across different stages of a multistage hot rod rolling system. The method is goal-oriented because the design decisions are first made based on the end requirements identified for the process at the last rolling pass and these decisions are then passed to the preceding rolling passes following the sequential order in an inverse manner to design the entire rolling process chain to achieve the horizontal integration of stages. We illustrate the efficacy of the method by carrying out the design of a multistage rolling system. We formulate the cDSP for the second and fourth pass of a four pass rolling chain. The stages are designed by sequentially passing the design information obtained after exercising the cDSP for the last pass for different scenarios and identifying the best combination of design variables that satisfies the conflicting goals. The cDSP for the second pass helps in integrated information flow from fourth to first pass and in meeting specified goals imposed by the fourth and third passes. The end goals identified for this problem for the fourth pass are minimization of ovality (quality) of rod, maximization of throughput (productivity), and minimization of rolling load (performance and cost). The method can be instantiated for other multistage manufacturing processes such as the steel making process chain having several unit operations. [DOI: 10.1115/1.4035555]
Evaluation of the combination mode and features of p38 MAPK inhibitors: construction of different pharmacophore models and molecular docking

ABSTRACT Abnormal expression of tumour necrosis factor-α (TNF-α) can lead to various pathological reactions, such as arthritis, psoriasis, krone disease, etc. p38 mitogen-activated protein kinase (p38 MAPK) is an important signal transduction enzyme that plays important roles in influencing the release of intracellular TNF-α factor. It is very meaningful to study the targeting kinase with specific inhibitors in the treatment of related diseases. In order to achieve a deeper insight, it is necessary to analyse the structural characteristics and the action mode of the p38 MAPK inhibitors in the active site. In the study, a ligand-based common feature pharmacophore model and the receptor structure-based pharmacophore model were constructed, respectively. Their common chemical features consisted of the hydrophobic groups (H) and the hydrogen bond acceptors (A), and kept the consistency of spatial structure distribution. Then, the molecular docking and molecular dynamics simulation were performed with the eight training set compounds. The binding characteristics of molecules binding were described in the topological region of the active site. Finally, the structure–activity relationship (SAR) was obtained by analysing docking results with the different pharmacophore models. This research leads to the proposal of an interaction model in the p38 MAPK active site and provides guidance for the screening and design of more potent and selective p38 MAPK inhibitors.
Silicon Nanowires for Photovoltaic Solar Energy Conversion

Semiconductor nanowires are attracting intense interest as a promising material for solar energy conversion for the new‐generation photovoltaic (PV) technology. In particular, silicon nanowires (SiNWs) are under active investigation for PV applications because they offer novel approaches for solar‐to‐electric energy conversion leading to high‐efficiency devices via simple manufacturing. This article reviews the recent developments in the utilization of SiNWs for PV applications, the relationship between SiNW‐based PV device structure and performance, and the challenges to obtaining high‐performance cost‐effective solar cells.
Coverage optimization strategy based on co-evolution bee colony algorithm

To improve the monitoring of the regional network coverage,the locations of mobile nodes are optimized in wireless sensor networks with mobile nodes.Traditional bee colony algorithm exists the phenomenon of prematurely mature and late slow convergence.To overcome this shortcoming,the co-evolution mechanism is introduced colony algorithm to increase the diversity of solutions and accelerate the convergence process.A co-evolutionary artificial bee colony based coverage optimization strategy is proposed.What′s more,for the nodes in the process of moving the path detour phenomenon,based on greedy method,a motion path optimization strategy is proposed.Simulation show that coverage optimization results by co-evolution bee colony algorithm is better than particle swarm optimization and artificial bee colony.Mobile path optimization strategies can effectively reduce the moving distance of nodes.
Research on the Single Source Shortest Path Algorithm Using MapReduce

Via the analysis to implementation process of mapreduce, aimming at the problem that single source shortest path algorithm is hard to be used with the appearance and development of cloud computing and the problem of searching efficiency,a parallel single source shortest path algorithm based on mapreduce framework is designed and implemented . research and experiment are done based on hadoop platform.As shown by the experimental results,the proposed algorithm can search the single source shortest path efficiently in the whole graphic structure,and its good performance is testified.
The Scent of a Newsgroup: Providing Personalized Access to Usenet Sites through Web Mining

We investigate Web mining techniques focusing on a speciﬁc application scenario: the problem of providing personalized access to Usenet sites accessible through a Web server. We analyze the data available from a Web-based Usenet server, and describe how traditional techniques for pattern discovery on the Web can be adapted to solve the problem of restructuring the access to news articles. In our framework, a personalized access tailored to the needs of each single user, can be devised according to both the content and the structure of the available data, and the past usage experience over such data.
Automatic Analysis Of Landmarks In Cephalograms

Landmarks on the cephalograms are those representing the actual anatomic structures of the skull. These points are used by orthodontists for diagnosis and treatment planning. In this study, a microcomputer system with a desk-top scanner was employed for locating the landmarks of X-ray cephalogram automatidy. Fustly, the digitized image of cephalogram is processed to define a reference point for analysis, and divided into several rectangular subimages (such as frontal, orbit, mda, mandible,.). These regions containing all the useful landmarks are then enhanced in the preprocessing stage. The pyramid method is used to reduce the resolution of image, and the edges are detected by the appropriate edge detectors or the best orientation edge detector. The curve. of each edge is corrected elastically with the pre-stored models. Finally, positions of landmarks could be located immediately and the associated paremeters could also be computed for diagnosis.
Generator Bearing Fault Diagnosis Based on Analytic Hierarchy Process and Binary-tree Support Vector Machine

Binary-tree support vector machine (SVM) has such advantages as small repeated operation workload, fast classification speed and dead zone inexistence, but the structural design can influence the classification accuracy thereof. In order to rationally design the structure of the binary-tress SVM, a multi-classification algorithm (AHP-BSVM) combining analytic hierarchy process (AHP) and binary-tree SVM is proposed in this paper. Firstly, the analytic hierarchy process is adopted to establish the evaluation system model so as to comprehensively evaluate multiple influencing factors for determining the weight values of various faults; then, the faults are ordered by the weight values and the structure of the binary-tree SVM is determined according to the fault sequence; finally, the proposed algorithm is adopted for fault diagnosis and analysis. The simulation experiment shows: compared with other algorithms, the proposed algorithm has higher recognition accuracy and higher classification accuracy, and is applicable to multi-classification, thus having good promotion prospect.
OMNI-DIRECTIONAL OBSTACLE AVOIDANCE MECHANISM

Considering the special requirements for wall climbing cleaning robot, a new type of omni directional mechanism which can avoid obstacles was developed. This omni directional mechanism can make the wall climbing robot not only run towards all directions in line without changing its posture or rotate along definite angle at its original position, but also avoid the obstacles such as the window frame in its routine.
Authoring augmented reality as situated multimedia

Augmented reality (AR) is an enabling technology for presenting information in relation to real objects or real environments. AR is situated multimedia or information that is positioned in authentic physical contexts. In this paper, we discuss how we address issues in creating AR content for educational settings. From the learning theory perspective, we explain that AR is a logical extension of multimedia learning theory. From the development perspective, we demonstrate how AR content can be created through our in situ authoring tool and our platform for handheld AR.
Computer-aided design of experiments

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Audio networks for speech enhancement and indexing

viii Acknowledgements x Published work xi Abbreviations xi Notations xiii 0.1 Specific variables and functions . xiv 0.2 Indexing or counting variables . xvii 0.3 Constant . xvii
A Comparative Analysis of Three Layers Feature Extraction, Categorization and Classification of Malicious Tweets in Social Networks

Social networks are most popular networks through which information or ideas of human or people are exchanged throughout the world. Twitter, facebook, pinterest many more are some popular social networks. In twitter short messages are exchanged called as tweets of length 140 characters which contain text as well as URLs.But along with some useful information. Some fake and irrelevant data are also wide spreading on the network which known as spam. Spam can be categorized in terms of text, UPLs and unauthorized users. It is featured on the basis of profile name, user id, location, number of repetitions, etc and various techniques are there which are used to distinguish spam and non-spam. In some previous papers individual and some combination of existing techniques are used to detect spam. So in this paper an attempt has been made to discuss all the existing techniques to detect and distinguish spam by comparative analysis. For comparative analysis precision, Recall and F-measures matrices are used.
Software Defect Prediction

Software defect prediction has been one of the active parts of software engineering since it was developed in 1970's.It plays a very important role in the analysis of software quality and balance of software cost. This paper investigates and discusses the motivation,evolvement,solutions and challenges of software defect prediction technologies,and it also categorizes,analyzes and compares the representatives of these prediction technologies.Some case studies for software defect distribution models are given to help understanding.
Milkweed scaffold: A new candidate for bone cell growth

Abstract This study aims to evaluate the potential of milkweed as potential candidate to construct biodegradable scaffold for bone regeneration. A mat made of milkweed, polyethylene, and polypropylene was treated with an atmospheric pressure plasma to functionalize the surface of the polymer assembly with carboxylic acid groups, which enable to conjugate bioactive molecules, while accelerating the degradation of milkweed. Degradation tests demonstrated substantial decrease of the weight of the treated polymer mat as compared to untreated one. Biological assays revealed that the polymer assembly promoted preosteoblast MC3T3 cells recruitment with a significant enhancement observed on the RGD-grafted polymer mat. Graphical Abstract
Lignin as Sustainable Antimicrobial Fillers to Develop PET Multifilaments by Melting Process

Nowadays, textiles functionalization is developing increasingly, fabrics are not only defined by the intrinsic properties of the fiber but some properties are also brought to provide them added value. Among the desired properties, antibacterial activity is targeted to improve the comfort and durability of textiles but many commercial products use chemical substances which are harmful for the environment (regulation 528/2012). The goal of this study was to use bio-based biocide which can be incorporated in the polyethylene terephthalate (PET) by melt spinning for the development of functional PET. This biocide had to resist to the PET processing temperature up to 264°C which was the maximum temperature of implementation. Two kinds of Kraft lignin and titanium dioxide as reference were added by melting way. The antimicrobial activity was characterized at low concentration (1 and 2 wt.%), to avoid a significant decrease in mechanical strength for the multifilaments and to maintain optimal rheological properties of the polymer for the melt spinning process. Filled PET pellets were obtained by twin screw extrusion step and the multifilaments by melt spinning step. Finally, knitting structures were developed for the evaluation of the antibacterial activity. The mechanical (tensile test) and thermal (DSC and TGA) properties of the filaments were characterized.
Enhancing Semantic Web Data Access

The Semantic Web was invented by Tim Berners-Lee in 1998 as a web of data for machine consumption. Its applicability in supporting real world applications on the World Wide Web, however, remains unclear to this day because most existing works treat the Semantic Web as one universal RDF graph and ignore the Web aspect. In fact, the Semantic Web is distributed on the Web as a web of belief: each piece of Semantic Web data is independently published on the Web as a certain agent's belief instead of the universal truth. Therefore, we enhance the current conceptual model of the Semantic Web to characterize both the content and the context of Semantic Web data. A significant sample dataset is harvested to demonstrate the non-trivial presence and the global properties of the Semantic Web on the Web. Based on the enhanced conceptual model, we introduce a novel search and navigation model for the unique behaviors in Web-scale Semantic Web data access, and develop an enabling tool -- the Swoogle Semantic Web search engine. To evaluate the data quality of Semantic Web data, we also (i) develop an explainable ranking schema that orders the popularity of Semantic Web documents and terms, and (ii) introduce a new level of granularity of Semantic Web data-- RDF molecule that supports lossless RDF graph decomposition and effective provenance tracking. This dissertation systematically investigates the Web aspect of the Semantic Web. Its primary contributions are the enhanced conceptual model of the Semantic Web, the novel Semantic Web search and navigation model, and the Swoogle Semantic Web search engine.
Usability Evaluation in Virtual Environments: Classification and Comparison of Methods

Virtual environments (VEs) are a relatively new type of human-computer interface in which users perceive and act in a three-dimensional world. The designers of such systems cannot rely solely on design guidelines for traditional two-dimensional interfaces, so usability evaluation is crucial for VEs. We present an overview of VE usability evaluation. First, we discuss some of the issues that differentiate VE usability evaluation from evaluation of traditional user interfaces such as GUIs. We also present a review of VE evaluation methods currently in use, and discuss a simple classification space for VE usability evaluation methods. This classification space provides a structured means for comparing evaluation methods according to three key characteristics: involvement of representative users, context of evaluation, and types of results produced. To illustrate these concepts, we compare two existing evaluation approaches: testbed evaluation [Bowman, Johnson, & Hodges, 1999], and sequential evaluation [Gabbard, Hix, & Swan, 1999]. We conclude by presenting novel ways to effectively link these two approaches to VE usability evaluation.
An Algorithm for License Plate Locating Based on Mathematical Morphology and Edge Characteristics

Vehicle license plate locating is of vital importance in automatic LPR(license plate recognition) system. With the license plate feature, first, image preprocessing is adopted , which is then followed by mathematical morphology operations. Next, a simple license plate searching algorithm is designed to get coarse location. In the end , an exact location is obtained according to the characteristics of character edge. The results of the experiment show that the algorithm possesses advantages of fast locating speed and high percentage accuracy.
Standard Model for Live Actor and Entity Representation in Mixed and Augmented Reality

/012345#2367458 9(:67&; 45#67458=? @A&BCB.  45 DE ? "#$(LAE: live actor and entity)63D 67F :=>"GHIJ%K3LMN, OP3D QRS, 3D 67$TUV WHX 6Y=B. Z [  ? LAE83D 67F "GHIJ=\, ] ]7^A_3*+&%) `(B. `(*+&/aM]LAES:7^A 3 K3LB.AbstractMixed and augmented reality technique deals with mixing content between real world and virtual world containing augmented reality and augmented virtuality excluding of pure real and pure virtual world. In mixed and augmented reality, if a live actor and entity moving in real world can be embedded more naturally in 3D virtual world, various advanced applications such 3D tele-presence, 3D virtual experience education and etc can be serviced. Therefore, in this paper, we propose a standard model which is supporting to embed the live actor and entity into 3D virtual space, and to interact with each other. And also the natural embedding and interaction of live actor and entity can be performed based on the proposed model. Keyword : Mixed and augmented reality, live actor and entity, spatial mapping, event mapping
Smoothing Text Representation Models Based on Rough Set

Text representation is the prerequisite of various document processing tasks, such as information retrieval, text classification, text clustering, etc. It has been studied intensively for the past few years, and many excellent models have been designed as well. However, the performance of these models is affected by the problem of data sparseness. Existing smoothing techniques usually make use of statistic theory or linguistic information to assign a uniform distribution to absent words. They do not concern the real word distribution or distinguish between words. In this chapter, a method based on a kind of soft computing theory, Tolerance Rough Set theory, which makes use of upper approximation and lower approximation theory in Rough Set to assign different values for absent words in different approximation regions, is proposed. Theoretically, our algorithms can estimate smoothing value for absent words according to their relation with respect to existing words. Text classification experiments by using Vector Space Model (VSM) and Latent Dirichlet Allocation (LDA) model on public corpora have shown that our algorithms greatly improve the performance of text representation model, especially for the performance of unbalanced corpus.
A Based Vision Location System for Autonomous Robots

An autonomous location tracking ability is a major performance for locating sensor systems to navigate an autonomous mobile robot. This paper presents a vision based omnidirectional location sensor system we have developed in our lab. It is composed of active landmarks, a vision sensor, an image and data processing device. The whole sensor system can be mounted on a mobile robot. Meanwhile, the relative calculation methods and function software were developed that used to obtain the absolute position and orientation of the sensor system and vehicles in their working places. The experiments showed this system could get its pose online and suitable position accuracy for track guidance of mobile robots as well.