Miracle-dz/UniFAR-FTUs huggingface dataset:
Information technology: A luddite analysis

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Linear Clustering Algorithm by Competitive Learning Suitable for Coal Mine in Wireless Sensor Networks

Because of the complex environment of coal mines, there are many accidents like communication link fault caused by mobile equipment and sliding stones. Therefore, fast rebuilding of remaining nodes and dynamic adding of nodes toted by the rescuer are required after the disaster. Furthermore, the sensor nodes used for localization of the miner and his equipment can only be deployed redundantly along the straight laneway to form a linear wireless sensor network, which proposes a new requirement of topology control strategy. Combining with the self-organizing learning theory of the artificial neural networks, LCACL is presented, a linear clustering algorithm by competitive learning, in which sensor nodes are divided into mobile nodes which add or leave the network dynamically and fixed nodes which could act as sleep nodes, followers, cluster-bridges, or cluster-heads self-adaptively. On the comprehensive consideration of the remaining energy of the sensor node and the number of neighboring nodes, the competition vector, the base for competition, and evaluation vector, the evaluation standard, are formed, which correspond to the input vector and weight vector of artificial neural networks respectively. A similarity comparison using the Euclidean distance is made between them after normalization, and the competitive selection of roles and conversion are achieved using the Euclidean distance. Only the winner node will be entitled to make a learning adjustment, and then broadcasts the adjusted competition vector, which is the evaluation vector in the next competition. According to the rule of cluster-head selection from odd hops and cluster-bridge selection from even hops, the network is initialized as that nodes are divided into clusters of scale-uniform and low overlap ratio. The cluster-head initiates the competitive selection of the sleep node if there are too many followers, and its followers compete to sleep. Along with the energy consumption of the node, the cluster-head or cluster-bridge initiates a new election if it detects its energy consumption exceeding a certain threshold, and all the nodes in the cluster participate in competition by means of competitive learning to achieve role conversion. The simulation results show that the network organized by LCACL has balanced energy consumption, stronger ability to resist destruction, better expansibility, and longer lifetime of network, and the ratio of overlap could be 14% if the communication radius is 70 meters.
Statistical physics of macromolecules

Partial Contents: 1. Ideal Polymer Chain. A Freely Jointed Chain. Flexibility of a Polymer Chain. Size of an Ideal Polymer Chain. 2. Polymer Chains with Volume Interactions. Basic Definitions and Methods. Polymer Chain Models of Systems with Volume Interactions. Basic Definitions in the Theory of Volume Interactions in Polymer Systems. Perturbation Theory for Polymer Coils with Volume Interactions. 3. Single Macromolecule with Volume Interactions. Swelling of a Polymer Coil in Good Solvent (excluded volume problem). Renormalization Group and S-expansion Methods Applied to the Excluded Volume Problem. Properties of Polymer Coils with Excluded Volume (the scaling concept and the notion of a blob). 4. Polymer solutions and melts. Basic Preliminary Data and Definitions. Theory of Polymer Solutions and Melts in the Self-Consistent Field Approximation. Appendix. Flory Lattice Theory of Polymer Solutions and Melts. 5. Other Polymer Systems. Polymer Mixtures and Block Copolymers. Liquid- Crystal Polymers. High Elasticity of Polymer Networks. Methods of Polymer Network Synthesis. 6. Dynamic Properties of Polymer Solutions and Melts. The Rouse Model: a Phantom Chain in Immobile Solvent. The
Machine vision: an incremental learning system based on features derived using fast Gabor transforms for the identification of textural objects

This paper proposes a fast, effective and also very adaptable incremental learning system for identifying textures based on features extracted from Gabor space. The Gabor transform is a useful technique for feature extraction since it exhibits properties that are similar to biologically visual sensory systems such as those found in the mammalian visual cortex. Although two-dimensional Gabor filters have been applied successfully to a variety of tasks such as text segmentation, object detection and fingerprint analysis, the work of this paper extends previous work by incorporating incremental learning to facilitate easier training. The proposed system transforms textural images into Gabor space and a non-linear threshold function is then applied to extract feature vectors that bear signatures of the textural images. The mean and variance of each training group is computed followed by a technique that uses the Kohonen network to cluster these features. The centers of these clusters form the basis of an incremental learning paradigm that allows new information to be integrated into the existing knowledge. A number of experiments are conducted for real-time identification or discrimination of textural images.
A Novel Chalcone from Garcinia Nervosa

A novel chalcone 5′-bromo-2′-hydroxy-4,4′,6′-trimethoxy-chalcone, isoliquiritigenin-4,4′-dimethyl ether (2′-hydroxy-4,4′-dimethoxy chalcone) and 2′-hydroxy-3,4,4′,6′-tetramethoxy dihydrochalcone have been isolated from the leaves of Garcinia nervosa. Their structure have been elucidated on the basis of chemical and spectral evidences (1H NMR, 13C NMR, HMQC, NOE, IR, UV and mass spectra).
Identifying features for multi-modality coding

Identifying feature areas in head and shoulder image is an important stage in solving the problems present in current telecommunication systems. For example, in the case of videophone systems, to gain lip synchronisation, it is believed that integrating the speech and image data would help reduce the loss of synchronisation between the voice and the lip movements. To do so, the mouth area should be known/detected and the corresponding speech information analysed. We discuss how the area of the mouth is detected and is used to help create a basic system for gaining lip synchronisation.
Efficient Spatial Query Processing in Geographic Database Systems.

The management of spatial data in geographic information systems (GISs) gained increasing importance during the last decade. Due to the high complexity of objects and queries and also due to extremely large data volumes, geographic database systems impose stringent requirements on their storage and access architecture with respect to efficient spatial query processing. Geographic database systems are used in very different application environments. Therefore, it is not possible to find a compact set of operations fulfilling all requirements of geographic applications. But as described in [BHKS 93], spatial selections are of great importance within the set of spatial queries and operations. They do not only represent an own query class, but also serve as a very important basis for the operations such as the nearest neighbor query and the spatial join. Therefore, an efficient implementation of spatial selections is an important requirement for good overall performance of the complete geographic database system. The two main representatives of spatial selections are the point and the window query (see figure 1): • Point query: Given a query point P and a set of objects M, the point query yields all the objects of M geometrically containing P . • Window query: Given a rectilinear rectangle W and a set of objects M, the window query yields all the objects of M sharing points with W. For the efficient processing of spatial queries, we present a multi-stepprocedure (see figure 5). The main goal of our spatial query processor is to reduce expensive steps by preprocessing operations in the preceding steps which reduce the number of objects investigated in an expensive step. In figure 5 expensive steps are marked with a “$”symbol.
The formal system paradogm for studying failures

One way in which general lessons may be learnt from sets of failures and disasters is by using a common conceptual framework for analysis. Many authors have found the use of individual systems concepts useful in their studies of failure. This paper presents a unified model that draws together those concepts and other related concepts. The model that is described forms part of a systemic methodology which has been used successfully in the understanding of failures. It is suggested that the model could be developed further so as to become a predictive and preventative tool.
Fast Gabor Filterbank and its Application in Fingerprint Texture Analysis

Minutiae-based matching is the main method of fingerprint recognition. Anil K. Jain brought forward a method (FingerCode) which use Gabor filter to extract the texture feature of fingerprint and match it. In order to get a faster algorithm of fingerprint identification, the properties of the real part of Gabor filter are analyzed and the Gabor filter algorithm is accelerated in special conditions and is validated by experiment, which decreases the computational complexity from O(n2) to O(n).
An Improved Genetic Algorithm for Crew Pairing Optimization

Crew pairing is a sequence of flights beginning and ending at the same crewbase. Crew pairing planning is one of the primary processes in airline crew scheduling; it is also the primary cost-determining phase in airline crew scheduling. Optimizing crew pairings in an airline timetable helps minimize operational crew costs and maximize crew utilization. There are numerous restrictions that must be considered and just as many regulations that must be satisfied in crew pairing generation. The most important regulations—and the ones that make crew pairing planning a highly constrained optimization problem—are the the limits of the flight and the duty periods. Keeping these restrictions and regulations in mind, the main goal of the optimization is the generation of low cost sets of valid crew pairings which cover all flights in the airline’s timetable. For this research study, We examined studies about crew pairing optimization and used these previously existing methods of crew pairing to develop a new solution of the crew pairing problem using genetic algorithms. As part of the study we created a new genetic operator—called perturbation operator.Unlike traditional genetic algorithm implementations, this new perturbation operator provides much more stable results, an obvious increase in the convergence rate, and takes into account the existence of multiple crewbases.
Neighbor-Index Method for Continuous Window Queries over Wireless Data Broadcast

A continuous window query is an important class of spatial queries for location-based services. It retrieves spatial objects in a fixed window region of every point on a line segment and indicates the valid segments of them. In this paper, we focus on continuous window queries in wireless data broadcast systems. Since the query result of the continuous window queries has the spatial locality, providing neighbor information of spatial objects can guide clients to efficiently retrieve related objects. Therefore, we propose a neighbor-index method to efficiently support the continuous window queries in wireless data broadcast systems. The proposed method interleaves the neighbor information between spatial objects to guide mobile clients to quickly retrieve the answered objects and save the power consumption of the mobile devices. Experimental results show that our method outperforms the distributed indexing.
An Intelligent Online Vehicle Tyre Pressure Monitoring System

This paper aims at designing an intelligent online tyre pressure monitoring system (TPMS). The objective of this work is to display the tyre pressure of the tyre and also give the indication about the quality. The data corresponding to the tyre pressure is obtained with a high precision MEMS pressure sensor. The output of the MEMS pressure sensor is amplified and transmitted to the processing unit placed on the dash of the vehicle using wireless communication (RF). The processing is carried on using fuzzy logic algorithms on LabVIEW platform. The output pressure is displayed along with the indicator representing the quality. Indicator is green when the tyre pressure is in the desired range specified by the manufacturer. Yellow when the pressure has dropped and need to be inflated. Red indicates tyre pressure is below the safety driving conditions. After testing and validating the entire system using LabVIEW. The entire code is converted to verilog code and dumped on to FPGA chip (Spartan 3E) using FPGA module of LabVIEW with CompactRIO, for implementation of FPGA chip on real time system. DOI: http://dx.doi. org/10.11591/ijece.v2i3. 239
Some Exploratory Uses of Interactive Video in Teacher Education: Designing and Presenting Interactive Video Sequences to Primary Student Teachers

This study examines the potential use of interactive video in promoting Primary students’ thinking about, and their interpretation of, various classroom episodes as a means of making them more aware of the processes of learning how to teach. Implicit in the design of teacher‐education programmes are certain assumptions about the nature and growth of teacher knowledge. Our interactive video programmes are designed to explore the main features of that knowledge using Shulman's distinction between subject‐matter and pedagogical knowledge. Each programme has been designed to represent different aspects of both types of knowledge by using a range of exemplars of typical primary classroom practices. The interactive learning tasks are intended to encourage students to describe, analyse and evaluate various teaching episodes by comparing alternative images of practice, by considering the appropriateness of particular classroom activities and through discussing aspects of their own practice, using a detailed set o.
REACTIONS OF COMPLEXES OF DITHIOCARBAMATE AND RELATED LIGANDS

Review: In einer Ubersicht uber die Redoxreaktionen von Dithiocarbamat-Komplexen werden die Stabilitat der verschiedenen Oxidationszustande, die Geschwindigkeit der Redoxreaktionen, Struktur und Eigenschaften von Cu-Verbindungen mit gemischten Oxidationszustanden sowie der bemerkenswerte Unterschied im Redoxverhalten von Sb diskutiert.
Attack visualisation for cyber-security situation awareness

This paper illustrates how Situation Awareness measurement techniques can be transferred and adopted to a Cloud Computing network environment, specifically concerning the Intrusion Detection field. Bearing in mind the rise of Cloud Infrastructures and the importance of Cyber Security, this topic is critical. In this paper the relationship between Situation Awareness, decision-making and the most known measurements of Situation Awareness is being presented. Moreover, an application of some techniques through an attack-visualisation case study is being provided. This study has the form of an on-line questionnaire and it's consisted of two main parts; the first part is related to general knowledge questions, which provide information that can also help in the categorization of the population. The second part is examining the three levels of Situation Awareness theory and a video/image representation is a key technique. Finally, in this paper the results of the study are being discussed and some key conclusions are being provided.
Analysis of the concurrent model of train station based on Petri net

Petri nets are important instruments for modeling concurrent, distributed, asynchronous, parallel deterministic and non-deterministic systems. In this paper, we propose a concurrency analysis method for railway stations using Petri nets. By employing inter-current control analysis, the rail track flow of the railway station is simulated. This method also has an important function in improving the system's capability and in reducing its implementation difficulty.
Successful Pedagogy with Web Assignments Checker

What is the effect on studies when integrating Web Assignment Checker (WAC) into science teaching? This article examines the change in students' attitudes to this question from the beginning of the course to its end, as compared with the attitudes of the teaching staff. The examiner's questionnaires, incorporating six aspects relating to students' attitudes with six aspects that the students' attitudes relate to, were given in five courses at the start of the semester and at its end. An analysis of the findings identified several members of the teaching staff who had succeeded in reducing the disparity between their attitudes and those of their students by the end of the course. An analysis of the means of operating WAC by these members of the teaching staff point reveals a successful pedagogy that may be implemented in other courses.
Orc-X: Combining Orchestrations and XQuery

In designing a language for distributed computing, the handling of data and distribution can be viewed as largely orthogonal concerns, as long as the data model supports the communication requirements of the distribution model. This view contrasts strongly with approaches based on distributed objects, which typically enforce a tight coupling of state and behavior. We have previously presented Orc, a language that provides simple but powerful constructs to orchestrate distributed computations. Previous versions of Orc included only simple data types, since these were sufficient to demonstrate the concurrency primitives. However, Orc’s communication model is based on web services, which support complex XML documents in addition to simple data types. Thus it is natural to consider XML as an appropriate data model for Orc. We present Orc-X, an extension of the Orc language with an XML data model and XML-specific data management capabilities from XQuery. We demonstrate that Orc-X is well-suited for the application domain of distributed resource management protocols such as the Narada mesh overlay protocol.
Technology developments driving an evolution of cellular phone power amplifiers to integrated RF front-end modules

Millions of cellular phone power amplifiers (PAs) are produced every day worldwide using a great diversity of technologies. This is true both for the active devices, where various silicon as well as GaAs transistors are used, and for the PA architecture, in which MMIC, module, and discrete solutions compete. This paper gives an overview of the various technological and architectural choices and discusses their influence on the PA performance, notably the power efficiency and linearity. It sketches the future of PA development toward more functional integration, which may be obtained by two paths: integration on chip and added functionality in modules.
Analyzing qualitative/categorical data: Log-linear models and latent-structure analysis

In this book, originally published in 1978 by Abt Books, author Leo Goodman presents new methods for causal analyses of qualitative variables, for scaling response patterns, for latent structure analysis, and for analyzing and comparing various kinds of cross-classification tables. Edited by Jay Magidson, this volume includes contributions from James A. Davis and Jay Magidson.
An Adaptive Neural Network Learning-based Solution for the Inverse Kinematics of Humanoid Fingers

This paper presents an adaptive neural network learning-based solution for the inverse kinematics of humanoid fingers. For the purpose, we specify an effective finger model by considering the interphalangeal joint coordination inherent in human fingers. In order to find a proper joint combination for any fingertip trajectory, we propose an adaptive learning scheme by using a multi-layered neural network. It is interesting to use an adaptive learning rate algorithm that leads the neural network to get the inverse kinematic solution quickly. The usefulness of the proposed approach is verified by exemplary simulations for the general motion of humanoid fingers.
C21. Super Resolution Using Dictionary Technique

This paper addresses the problem of generating a super resolution (SR) image from a degraded input image, using a hybrid algorithm called Kernel-Local Learned Dictionary (K-LLD) to form dictionary from low resolution (LR) image to produce high resolution (HR) one, a patch-based, locally adaptive denoising method based on clustering the given degraded image into regions of a like geometric structure. It will show the effectiveness of sparsity as a prior for regularizing, where we utilize as features the local weight functions derived from steering kernel regression, to effectively perform such clustering. Next, we model each region (or cluster) which may not be spatially contiguous by ? learning? a best basis describing the patches within that cluster. This learned basis (or ? dictionary? ) is then employed to optimally estimate the underlying pixel values using a kernel regression framework. In addition, this paper illustrates the overall algorithm capabilities with several examples. Sparse K-SVD algorithm is applied for optimization to speed up sparse coding. Comparison with sparse coding method shows that sparse dictionary is more compact and effective.
Road Boundary Detection Based on Random Forests and Particle Filter

Road detection is a primary problem for autonomous vehicle. There have been many approaches attempting to solve this problem. However, most of the approaches tend to be affected by shadow, occlusion and not always robust. In this paper, we propose a new approach to detect the road boundary, our approach has two parts: firstly, we detect the road boundary by random forests on the pixel level, then we track the road boundary by particle filter with the parameters of vanish point position and road boundary slope. The experiment shows our approach is an effective way to detect road boundary fast and robustly.
Resolution enhancement of images using fractal coding

The code generated by fractal coding of a digital image provides a resolution-independent representation of the image as this code can be decoded to generate a digital image at any resolution. When the image is decoded at a size larger than the original encoded image, image details beyond the resolution of the original image are predicted by assuming local self-similarity in image at different scales. In this paper, we (1) present a formulation of how decoding may be done at a higher resolution, (2) evaluate the accuracy of the predicted details using a frequency analysis of fractally enlarged test images, and (3) propose a method for fractal resolution enhancement without the low-frequency loss of information due to fractal coding.
Application Study of Information Visualization in Digital Library

Information visualization in digital library can solve some problems faced during its development. In formation visualization consists of four parts: determine the object, visualization mapping, space structure and graphics rendering. This article introduces application of information visualization in information resources, information retrieval process, information retrieval results and knowledge domain in digital library. KeywordsInformation visualization; Information retrieval; Digital library; knowledge domain