Miracle-dz/UniFAR-FTUs huggingface dataset:
Extracting -of- Rules from Trained Neural Networks

An effective algorithm for extracting -of- rules from trained feedforward neural networks is proposed. Two com- ponents of the algorithm distinguish our method from previously proposed algorithms which extract symbolic rules from neural net- works. First, we train a network where each input of the data can only have one of the two possible values, 1 or one. Second, we apply the hyperbolic tangent function to each connection from the input layer to the hidden layer of the network. By applying this squashing function, the activation values at the hidden units are ef- fectively computed as the hyperbolic tangent (or the sigmoid) of the weighted inputs, where the weights have magnitudes that are equal one. By restricting the inputs and the weights to binary values ei- ther 1 or one, the extraction of -of- rules from the networks becomes trivial. We demonstrate the effectiveness of the proposed algorithm on several widely tested datasets. For datasets consisting of thousands of patterns with many attributes, the rules extracted by the algorithm are surprisingly simple and accurate. Index Terms—DNF rules, feedforward neural networks, -of- rules, network pruning, rule extraction.
Packet scheduling in SDMA based wireless networks

This paper deals with packet scheduling in SDMA based wireless cellular networks. Depending on the terminal's positions and the capabilities of the antenna and signal processing system it is possible for more than one mobile terminal to receive or to transmit simultaneously. We discuss the two-dimensional scheduling problem and address the spatial as well as the temporal domain. Based on the framework of batch Markovian arrival processes we develop an analytical model for the air interface and present some results for uplink capacity request transmissions.
Calculation of node-pair reliability in large networks with unreliable nodes

A new efficient method that compensates for unreliable nodes in network reliability computations is presented. This method can be embedded in the modified Dotson algorithm or any algorithm that generates a symbolic reliability expression for networks with perfect nodes. Its cost increases linearly with the number of links, and the effect of unreliable nodes can be directly computed. This method supplants the Aggarwal method and other methods of compensating for unreliable nodes in the calculation of node-pair reliability. When combined with the modified Dotson algorithm, this method provides accurate reliability estimates for networks so large that the Theologou-Carlier algorithm cannot complete its computations in a reasonable amount of time. For such networks, the new method can be embedded in the modified Dotson algorithm to estimate both the node-pair reliability and the error in this estimate even if the algorithm is terminated before completion. >
Defining User Interactions without Programming Knowledge

Programming has always been predominantly performed based on formal textual input languages. Thus, people who want to automate sequences of events on a computer usually have to learn a programming language, with all the difficulties concerning syntax, execution context and concepts of general-purpose programming languages. We take a look at alternative approaches like Scratch (http://scratch.mit.edu), which uses graphical modelling for the definition of actions. We then focus on a single system, the mGBL (http://www.mg-bl.com) platform for mobile game-based learning, which tried to overcome the difficulties of conventional programming with two antipodal approaches: one of them based on graphical modelling and structured persistence, the other more conventionally based on a textual programming language. Experience gained with these two methods allows us to compare their strengths and weaknesses and can also be valuable for other projects facing similar requirements and circumstances.
Prague Czech-English Dependency Treebank 2.0

Texts The Prague Czech-English Dependency Treebank 2.0 (PCEDT 2.0) is a major update of the Prague Czech-English Dependency Treebank 1.0 (LDC2004T25). It is a manually parsed Czech-English parallel corpus sized over 1.2 million running words in almost 50,000 sentences for each part. Data The English part contains the entire Penn Treebank - Wall Street Journal Section (LDC99T42). The Czech part consists of Czech translations of all of the Penn Treebank-WSJ texts. The corpus is 1:1 sentence-aligned. An additional automatic alignment on the node level (different for each annotation layer) is part of this release, too. The original Penn Treebank-like file structure (25 sections, each containing up to one hundred files) has been preserved. Only those PTB documents which have both POS and structural annotation (total of 2312 documents) have been translated to Czech and made part of this release. Each language part is enhanced with a comprehensive manual linguistic annotation in the PDT 2.0 style (LDC2006T01, Prague Dependency Treebank 2.0). The main features of this annotation style are: dependency structure of the content words and coordinating and similar structures (function words are attached as their attribute values) semantic labeling of content words and types of coordinating structures argument structure, including an argument structure ("valency") lexicon for both languages ellipsis and anaphora resolution. This annotation style is called tectogrammatical annotation and it constitutes the tectogrammatical layer in the corpus. For more details see below and documentation. Annotation of the Czech part Sentences of the Czech translation were automatically morphologically annotated and parsed into surface-syntax dependency trees in the PDT 2.0 annotation style. This annotation style is sometimes called analytical annotation; it constitutes the analytical layer of the corpus. The manual tectogrammatical (deep-syntax) annotation was built as a separate layer above the automatic analytical (surface-syntax) parse. A sample of 2,000 sentences was manually annotated on the analytical layer. Annotation of the English part The resulting manual tectogrammatical annotation was built above an automatic transformation of the original phrase-structure annotation of the Penn Treebank into surface dependency (analytical) representations, using the following additional linguistic information from other sources: PropBank (LDC2004T14) VerbNet NomBank (LDC2008T23) flat noun phrase structures (by courtesy of D. Vadas and J.R. Curran) For each sentence, the original Penn Treebank phrase structure trees are preserved in this corpus together with their links to the analytical and tectogrammatical annotation.
An implementation of support vector machine on sentiment classification of movie reviews

With technological advances, all information about movie is available on the internet. If the information is processed properly, it will get the quality of the information. This research proposes to the classify sentiments on movie review documents. This research uses Support Vector Machine (SVM) method because it can classify high dimensional data in accordance with the data used in this research in the form of text. Support Vector Machine is a popular machine learning technique for text classification because it can classify by learning from a collection of documents that have been classified previously and can provide good result. Based on number of datasets, the 90-10 composition has the best result that is 85.6%. Based on SVM kernel, kernel linear with constant 1 has the best result that is 84.9%
Embedded nonvolatile memories

The embedded nonvolatile memories (NVM) offer in-system reprogrammability along with low power, noise reduction. more reliable, and reduced system cost while maintain high speed, high density system performance over other NVM including stand-alone flash memory. The extent of market opportunity is driven by product cost. For most applications, manufacturability is the primary concern for embedded NVM, not cell size. The design simplicity is a key factor when choosing cell design. Another area of concern for cell design is the integration compatibility of the logic core process to the additional NVM flow. In this paper we review different NVM concepts from ROM to flash, and to FeRAM, and their applications in support of the diverse and emerging consumer market.
Reliability Analysis of Ten Unit Bridge Network Connected in Series with Critical and Non-critical Human Errors

This paper represents about a complex system can produce a non –series parallel structure. The most simple non-series parallel structure is a bridge configuration. In this paper, we discuss the Reliability analysis of ten unit’s Bridge network with critical& non-critical human errors. People will always make mistakes when interacting with system design and development processes. Fortunately, human errors can be anticipated, and protective measures taken against their occurrence. This requires the
Output feedback stabilization using variable structure control

Considers the stabilization of a class of multivariable nonlinear systems, about an equilibrium point at the origin, using variable structure output feedback control. In particular, the system can be transformed into a normal form with no zero dynamics. A robust high-gain observer is used to estimate the state variables while rejecting error disturbances. A globally bounded discontinuous variable structure controller is designed to compensate for modeling error. The authors show that the controller can stabilize the closed-loop system and does not suffer from the peaking phenomenon which exists in previous designs. <<ETX>>
A fast parallel multiplier-accumulator using the modified Booth algorithm

This paper presents a dependence graph (DG) to visualize and describe a merged multiply-accumulate (MAC) hardware that is based on the modified Booth algorithm (MBA). The carry-save technique is used in the Booth encoder, the Booth multiplier, and the accumulator sections to ensure the fastest possible implementation. The DG applies to any MAC data word size and allows designing multiplier structures that are regular and have minimal delay, sign-bit extensions, and datapath width. Using the DG, a fast pipelined implementation is proposed, in which an accurate delay model for deep submicron CMOS technology is used. The delay model describes multi-level gate delays, taking into account input ramp and output loading. Based on the delay model, the proposed pipelined parallel MAC design is three times faster than other parallel MAC schemes that are based on the MBA. The speedup resulted from merging the accumulate and the multiply operations and the wide use of carry-save techniques.
Trex : taxonomy-based robot-control expert-system

This work presents the basis for an expert system design for robot control. The system is based on a new taxonomy for robot control. This taxonomy identifies the main issues in the design and selection of robot controllers and categorizes and relates these issues. A clear distinction is drawn between the selection of robot control architectures and the controller algorithms that are utilized within these architectures. In both cases a wide variety of approaches are examined and evaluated based on characteristics such as disturbance rejection, effective stiffness, allowable planing task error, dynamic motion characteristics, sensor information, hardware requirements and model accuracy. Based on these characteristics the controller architectures and controller algorithms are categorized and evaluated using these major criteria: reliability, complexity and robustness. This review and categorization gives rise to a taxonomy based on desired task, imposed criteria, and the distinctive characteristics of various controller architectures and controllers described in the taxonomy. Based on this taxonomy an open expert system for selecting suitable control architectures and algorithms is developed. The appropriateness of the rules embedded in expert system's inference engine as well as the correctness of the decisions made by the expert system is verified via simulations and experiments. Simulation results are obtained by
Why that expression has this type, and how it got it

Strongly-typed languages present programmers with compile-time feedback about the type correctness of programs. Errors during polymorphic type checking most often take the form of a unification failure for two types. Finding the source of the type error in the code is possibly very difficult because the error may occur far from the spot where the inconsistency is detected. As functional languages utilize more and more complex type systems, the difficulty of interpreting and locating these errors will increase. To locate the source of type errors the programmer must unravel the long chain of deductions and type instantiations made during type reconstruction. This paper describes an approach that maintains the deductive steps of type inference and the reasons for type instantiations. We describe two functions that, given an expression and some type obtained by type reconstruction, answer the question why that expression has this type and how it got it.
Water Removal from Protective Glass

Today’s network outdoor surveillance cameras face problems when water drops stick to the protective glass in front of the camera lens, thus significantly disturbing the image. This problem mainly occurs during heavy rain weather or when the camera is being cleaned with a hose. Solving this problem would greatly improve the performance and versatility of outdoor surveillance cameras. The way this problem is solved today is by using wind shield wipers. The drawback with this solution is that the screen will get scratched over time, especially if the wipers accidentally operate on a dry protective glass. To solve this problem, a systematic approach was used. After generating a wide spectrum of concepts, they were systematically tested and evaluated. Our mission was to find a solution that is reliable, energy efficient and implementable into existing products. The final result of this project was a vibrating solution to the problem. By vibrating the protective glass at a specific frequency and amplitude, the water drops could successfully be removed. A prototype of the final solution was implemented into an already existing product which proves that the concept might be possible to include in future products. The result of this project will be an attractive feature for network surveillance cameras. The results of this project have only been tested in camera applications, but have the potential of being implemented into other fields, such as car or home windows. (Less)
From climatological to small-scale applications: simulating water isotopologues with ICON-ART-Iso (version 2.3)

Abstract. We present the new isotope-enabled model ICON-ART-Iso. The physics package of the global ICOsahedral Nonhydrostatic (ICON) modeling framework has been extended to simulate passive moisture tracers and the stable isotopologues HDO and H218O. The extension builds on the infrastructure provided by ICON-ART, which allows for high flexibility with respect to the number of related water tracers that are simulated. The physics of isotopologue fractionation follow the model COSMOiso. We first present a detailed description of the physics of fractionation that have been implemented in the model. The model is then evaluated on a range of temporal scales by comparing with measurements of precipitation and vapor. A multi-annual simulation is compared to observations of the isotopologues in precipitation taken from the station network GNIP (Global Network for Isotopes in Precipitation). ICON-ART-Iso is able to simulate the main features of the seasonal cycles in δD and δ18O as observed at the GNIP stations. In a comparison with IASI satellite retrievals, the seasonal and daily cycles in the isotopologue content of vapor are examined for different regions in the free troposphere. On a small spatial and temporal scale, ICON-ART-Iso is used to simulate the period of two flights of the IAGOS-CARIBIC aircraft in September 2010, which sampled air in the tropopause region influenced by Hurricane Igor. The general features of this sample as well as those of all tropical data available from IAGOS-CARIBIC are captured by the model. The study demonstrates that ICON-ART-Iso is a flexible tool to analyze the water cycle of ICON. It is capable of simulating tagged water as well as the isotopologues HDO and H218O.
Dynamic Analysis of Hammer Buffer System Using Pseudo-Bond Graph Simulation Method

The buffer device of hydraulic piling hammer is a power source coupling the thermodynamic , mechanical and hydraulic domains. Traditional modeling techniques usually focus on the single-domain systems. Equations of multi-energy domains must be connected by the intermediate variables , but the complexity o f thermodynamic dynamics restricts this modeling method. In th is paper, bond graph model of the buffer system including multi-energy domains was developed in a unified way, the dynamic simulation was studied and the experimental results validate the modeling method.
Elements for Parallel Array Computations

Parallel high performance array programming in functional languages is usually performed with a fixed set of carefully chosen high-level combinators. Problems that fall outside the design scope for the combinators usually result in programs that are too slow and programmers resort to implementing them in low-level imperative languages without safety guarantees. We present element sets that allow us to keep the safety of functional high-level combinators but relaxes the specification order for array elements. The cost of the flexibility is two proof obligations for the compiler or library writer and the return is safety guarantees with zero performance overhead for all programs. We implemented element sets in a compiler and measured to see that that scalability and performance remained competitive with our solution.
Fake currency detection using image processing

The advancement of color printing technology has increased the rate of fake currency note printing and duplicating the notes on a very large scale. Few years back, the printing could be done in a print house, but now anyone can print a currency note with maximum accuracy using a simple laser printer. As a result the issue of fake notes instead of the genuine ones has been increased very largely. India has been unfortunately cursed with the problems like corruption and black money. And counterfeit of currency notes is also a big problem to it. This leads to design of a system that detects the fake currency note in a less time and in a more efficient manner. The proposed system gives an approach to verify the Indian currency notes. Verification of currency note is done by the concepts of image processing. This article describes extraction of various features of Indian currency notes. MATLAB software is used to extract the features of the note. The proposed system has got advantages like simplicity and high performance speed. The result will predict whether the currency note is fake or not.
Efficient Low-Overhead Channel Estimation for 5G Lens Based Millimeter-Wave Massive MIMO Systems

Beamspace MIMO performs beam-selection which can substantially reduce the number of power-consuming radio frequency (RF) chains without perceptible performance deterioration. However, for capacity-approaching performance, accurate information of the beamspace-channel of large-size is required for beam-selection, which is contesting in case of little number of RF-chains. To overcome such problem, I proposed an efficient support-detection (SD) algorithm for channel-estimation with low pilot-overhead and short number of RF chains. The key idea of SD-algorithm is to divide the whole issue of beamspace channel-estimation into a series of sub-issues, where each of them considers only one sparse channel-component. The support of each channel component is detected reliably by deploying the sparse structure attributes of the beamspace-channel. The effect of this channel-component is eliminated from the whole channel-estimation issue. Thus, the sparse beamspace-channel can be estimated with low pilot-overhead. Simulation Results shows that the proposed schemes perform much better than the conventional compressed-sensing (CS) schemes.
Propagation of modeling uncertainty through structural dynamic models

PROPAGATION OF MODELING UNCERTAINTY THROUGH STRUCTURAL DYNAMIC MODELS Timothy K. Hasselman* and Jon D. Chrostowski ACTA, Inc. and Timothy J. Ross University of New Mexico An earlier paper [I] presented results from a two and a half year NASA SBIR project to develop methods for evaluating the predictive accuracy of structural dynamic models. The present paper describes how modeling uncertainties derived from comparisons of prior modal analysis and test data are propagated through the equations of motion to predict response uncertainties, andlor to infer design parameter uncertainties. Three alternative methods for uncertainty propagation are presented. They provide measures of response uncertainty in terms of possibility intervals, probability intervals and probability distributions.
Iris Recognition Based on Improved Compressive Sensing Algorithm

The traditional iris recognition algorithm exists some shortcomings, such as the higher iris feature dimension, and which caused low efficiency of algorithm execution. A quick iris recognition method based on improved Compressive Sensing (CS) algorithm is proposed in this paper. The conventional construction process of redundant atom library is just based on image gray information. It converts two-dimensional image into a one-dimensional column vector, ignoring the image texture informations. There is a high dimension of the shortcomings of one-dimensional vector. In this paper, a redundant atom library construction algorithm is proposed. It is based on Gabor + PCA (GPCA) to retain the image texture features, greatly reduces the dimension of the image at the same time. Orthogonal Matching Pursuit (OMP) algorithm is used to achieve the sparse coefficient, and then identify the image. The experimental results show that: the iris recognition algorithms based on GPCA and CS can reduce the dimension of the image features greatly, and execution speed and recognition accuracy is high.
Image Tagging by Semantic Neighbor Learning Using User-Contributed Social Image Datasets

The explosive increase in the number of images on the Internet has brought with it the great challenge of how to effectively index, retrieve, and organize these resources. Assigning proper tags to the visual content is key to the success of many applications such as image retrieval and content mining. Although recent years have witnessed many advances in image tagging, these methods have limitations when applied to high-quality and large-scale training data that are expensive to obtain. In this paper, we propose a novel semantic neighbor learning method based on user-contributed social image datasets that can be acquired from the Web’s inexhaustible social image content. In contrast to existing image tagging approaches that rely on high-quality image-tag supervision, we acquire weak supervision of our neighbor learning method by progressive neighborhood retrieval from noisy and diverse user-contributed image collections. The retrieved neighbor images are not only visually alike and partially correlated but also semantically related. We offer a step-by-step and easy-to-use implementation for the proposed method. Extensive experimentation on several datasets demonstrates that the performance of the proposed method significantly outperforms others.