Miracle-dz/UniFAR-FTUs huggingface dataset:
Efficient Image Transmission over WVSNs Using Two-Measurement Matrix Based CS with Enhanced OMP

WVSN is a collective network of motes containing visual sensors. The nodes in the network are capable of acquiring, compressing, and transmitting successive images to the sink. To increase the lifetime of such network, it is essential to reduce the amount of dataflow across the network without losing the integrity. This paper proposes a CS-based image transmission system to reduce the number of measurements required to represent the image. It utilizes a two-measurement matrix-based CS. TMM with CS leads to 2.8% to 6.7% and 0.67% to 7.9% reduction in the number of measurements compared to one MM-based CS while using DCT and binary DCT, respectively. Similarly, TMM with NUS CS leads to 5% to 40% (DCT) and 1.4% to 20% (binDCT) reduction in the number of measurements than one-measurement matrix-based NUS CS. An Enhanced Orthogonal Matching Pursuit algorithm is also proposed, which produces nearly 2% to 26% better recovery rate with the same number of measurements than the conventional OMP algorithm. Reduced measurements and better recovery rate achieved will enhance the lifetime of the WVSN, with considerable image quality. Rate distortion analysis of the proposed methodology is also done.
Recognition of hand gestures on the video stream based on a statistical algorithm with pre-treatment

The goal of this work is human hand detection and gesture recognition. This is a tremendously difficult task as hands can be very varied in shape and viewpoint, they can de open or closed, they can have different finger articulations. It is proposed a combined method of hand gesture recognition based on a statistical image processing algorithm. As a pre-processing algorithm it was applied Lucas-Kanade method and background subtraction algorithm. Object recognition was performed with using of Haar classifiers. The possibility of using gestures for remote control of various devices with different hands position from the camera location was shown.
Disambiguation of User Queries in Search Engines

 Abstract —With the increasing number of user queries to search engine. it has become necessary to study the area of Information Retrieval. User always expects to get the most appropriate and relevant results to the query. But when there is a ambiguity user usually do not get what he/she actually wants. This paper deals with ambiguity of the query and helps providing user with relevant results. Also to validate the work we have used evaluation measure Mean Average Precision.
Detection of TCP attacks using SOM with fast nearest-neighbor search

A new approach of anomaly intrusion detection (AID) is proposed in this paper. The Self-Organizing Map (SOM) is used to construct the normal usage profiles of network traffic, and in the training phase and detection phase, the Vector Elimination Nearest-Neighbor Search (VENNS) algorithm is designed and implemented. The design procedure optimizes the performance of AID by jointly accounting for accurate usage profile modeling by SOM codebook and fast vector similarity measure using the fast Nearest-Neighbor search. In data processing, according to the characters of TCP attacks, a novel feature extraction approach of TCP flow state is implemented. Using the DARPA Intrusion Detection Evaluation Data Set, we implement the performance evaluation and comparison analysis. It is shown that the performance and efficiency of anomaly intrusion detection are improved greatly: the training time cost can be shortened about by four times and seven times for detection time cost.
Update on B̄ ( s ) → D ∗ ( s ) ` ν̄ form factor at zero-recoil using the Oktay-Kronfeld action

We present an update on the calculation of B̄→D∗`ν̄ semileptonic form factor at zero recoil using the Oktay-Kronfeld bottom and charm quarks on N f = 2+1+1 flavor HISQ ensembles generated by the MILC collaboration. Preliminary results are given for two ensembles with a ≈ 0.12 and 0.09 fm and Mπ ≈ 310 MeV. Calculations have been done with a number of valence quark masses, and the dependence of the form factor on them is investigated on the a≈ 0.12 fm ensemble. The excited state is controlled by using multistate fits to the three-point correlators measured at 4–6 source-sink separations.
One hundred years of forgetting: A quantitative description of retention

A sample of 210 published data sets were assembled that (a) plotted amount remembered versus time, (b) had 5 or more points, and (cj were smooth enough to fit at least 1 of the functions tested with a correlation coefficient of .90 or greater. Each was fit to 105 different 2-parameter functions. The best fits were to the logarithmic function, the power function, the exponential in the square root of time, and the hyperbola in the square root of time. It is difficult to distinguish among these 4 functions with the available data, but the same set of 4 functions fit most data sets, with autobiographical memory being the exception. Theoretical motivations for the best fitting functions are offered. The methodological problems of evaluating functions and the advantages of searching existing data for regularities before formulating theories are considered. At the simplest level, this article is a search for regularities. We ask whether there is one retention function that can describe all of memory, or perhaps a different function for each of a small number of different kinds of memory. At a more abstract level, it is about the role of theory and data in psychological research. Can we most rapidly advance psychology as a science by developing theories at the level that commonly fills psychological journals such as this one, or should we first try to describe phenomena that could constrain theories by establishing robust, preferably quantitative, regularities (Rubin, 1985, 1989, 1995)? A balance between these alternatives is needed, and here we argue that to obtain such a balance more description is needed. Retention offers the ideal topic to make this abstract, philo
Database Selection by Patrons Using CD-ROM

Examen des bases de donnees (bibliographiques) sur CSROM selectionnees par un echantillon d'utilisateurs de la Bibliotheque universitaire de l'Illinois (VIVC) et donnees statistiques sur la justesse de selection d'une base pour un sujet donne
Formal Specifications are Mathematical Models : An Example from Robotics'

Modelling and simulation are two co- herent activities whose unified framework becomes an inherent part of problem analysis and decision making in several engineering and scientific appli- cations. In multifacet ted application domains such as robotic systems, it is necessary to model in- dividual subsystems separately and then combine them with proper interfaces. In this paper, we use a formal approach for modelling and illustrate the expressive power of the three techniques algebraic, VDM and CCS for modelling several subsystems of a robotic system.
Musical Forces and Melodic Expectations: Comparing Computer Models and Experimental Results

Recent work on “musical forces” asserts that experienced listeners of tonal music not only talk about music in terms used to describe physical motion, but actually experience musical motion as if it were shaped by quantifiable analogues of physical gravity, magnetism, and inertia. This article presents a theory of melodic expectation based on that assertion, describes two computer models of aspects of that theory, and finds strong support for that theory in comparisons of the behavior of those models with the behavior of participants in several experiments. The following summary statement of the theory is explained and illustrated in the article: Experienced listeners of tonal music expect completions in which the musical forces of gravity, magnetism, and inertia control operations on alphabets in hierarchies of embellishment whose stepwise displacements of auralized traces create simple closed shapes. A “single-level” computer program models the operation of these musical forces on a single level of musical structure. Given a melodic beginning in a certain key, the model not only produces almost the same responses as experimental participants, but it also rates them in a similar way; the computer model gives higher ratings to responses that participants sing more often. In fact, the completions generated by this model match note-for-note the entire completions sung by participants in several psychological studies as often as the completions of any one of those participants matches those of the other participants. A “multilevel” computer program models the operation of these musical forces on multiple hierarchical levels. When the multilevel model is given a melodic beginning and a hierarchical description of its embellishment structure (i.e., a Schenkerian analysis of it), the model produces responses that reflect the operation of musical forces on all the levels of that hierarchical structure. Statistical analyses of the results of a number of experiments test hypotheses arising from the computer models’ algorithm (S. Larson, 1993a) for the interaction of musical forces as well as from F. Lerdahl’s similar (1996) algorithm. Further statistical analysis contrasts the explanatory power of the theory of musical forces with that of E. Narmour’s (1990, 1992) implication-realization model.
ENHANCEMENT OF NMR SENSITIVITY IN NANOLITER SAMPLES BY DYNAMIC NUCLEAR POLARIZATION AND MICROCOILS FABRICATED ON CAPILLARIES BY SHADOW MASK LITHOGRAPHY

Modern dynamic nuclear polarization (DNP) systems produce a high nuclear magnetic resonance (NMR) signal enhancement but distort the static magnetic field in an NMR system. As a result the obtained spectrum has a resolution not suitable for most NMR applications. Localizing the detection region only to the part of the resonator where the magnetic field component of microwave (MW) is the highest and highest static magnetic field homogeneity should increase the resolution without compromising enhancement. Here we present a novel method of manufacturing a microcoil on a capillary, enabling localized in-situ NMR detection inside a MW cavity.
From ternary relationship to relational tables: a case against common beliefs

The transformation from n-ary relationships to a relational database schema has never been really fully analyzed. This paper presents one of the several ternary cases ignored by the ER-to-RM literature. The case shows that the following common belief is wrong: Given a set of FDs over a table resulting in a non-3NF situation, it is always possible to obtain a fully equivalent set of 3NF tables, without adding other restrictions than candidate keys and elementary inclusion dependencies.
A Locality-Aware Write Filter Cache for Energy Reduction of STTRAM-Based L1 Data Cache

Thanks to superior leakage energy efficiency compared to SRAM cells, STTRAM cells are considered as a promising alternative for a memory element in on-chip caches. However, the main disadvantage of STTRAM cells is high write energy and latency. In this paper, we propose a lowcost write filter (WF) cache which resides between the load/store queue and STTRAM-based L1 data cache. To maximize efficiency of the WF cache, the line allocation and access policies are optimized for reducing energy consumption of STTRAM-based L1 data cache. By efficiently filtering the write operations in the STTRAM-based L1 data cache, our proposed WF cache reduces energy consumption of the STTRAM-based L1 data cache by up to 43.0% compared to the case without the WF cache. In addition, thanks to the fast hit latency of the WF cache, it slightly improves performance by 0.2%.
Acquiring Negative Polarity Items

Negative Polarity Items (NPIs) are words or expressions that exhibit a restricted distribution to certain negative contexts only. For example, yet is an NPI and must appear in the scope of a negation: Mary has *(not) finished yet. The existence of NPIs such as yet gives rise to a learnability problem for language-acquiring children. How do children know that the appearance of yet, for instance, is ungrammatical without a negation based on language input only? Are children able to detect NPIs’ restricted distribution? And do they make overgeneralization errors? By investigating the acquisition of three NPIs of different strengths and categories in both corpus and experimental studies (i.e. Dutch hoeven ‘need’, English any and Mandarin Chinese shenme ‘a/some’), these questions are addressed in this book. Results of this cross-linguistic investigation show that children employ a conservative widening learning strategy to acquire NPIs, which enables them to detect NPIs’ limited distributional patterns and also prevents them from making overgeneralization errors. The exploration to the learnability of the three NPIs moreover provides answers to the question as to why NPIs are restricted to different types of negative contexts. Since different learning paths are attested for the three investigated NPIs, this book concludes that NPIs of different strengths are NPIs due to different reasons, and do not form a homogeneous class. In particular, the Dutch NPI hoeven ‘need’ bears a lexical dependency with an abstract negation neg; English any must be obligatory exhaustified; and Mandarin shenme ‘a/some’ is referentially deficient.
A formal model of trust for calculating the quality of X.509 certificate

The growing number of Public Key Infrastructure (PKI) and the increasing number of situations where partners of a transaction may carry certificates signed by different certification authority (CA) points out the problematic of trust between the different CAs. Several trust models, like the hierarchy model, cross-certification model, and bridge CA model were proposed in order to establish and extend the domain of trust of relying parties (RP). However, each model has disadvantages and especially the scalability in large open networks like Internet. In this paper, we provide users with quantitative information of the confidence a relying party can have about a certificate. We call this information quality of certificate (QoCER). QoCER depends on two parameters which are the quality of procedures announced in the certificate policy (CP) and the quality of CA (QoCA) that represents the evaluation of the CA commitment to its policy. QoCA is calculated based on the recommendation of different actors (audit agency, RP, etc.). QoCER is balanced by another information that represents the confidence on QoCA calculation. We present a formal model of trust to calculate these values. Copyright © 2010 John Wiley & Sons, Ltd.
A spatial approach to perception identification in editorials enhanced with anaphora resolution

A method is proposed to annotate editorials and news articles for sentences that most accurately represent the opinion of the speaker towards the issue. The speaker's point of view or level of discernment of the issue is whittled out. A list of informative and related keywords is extracted from the document based on their frequency of occurrence. Subsequently, pronominal anaphora is resolved at the document level based on minimum distance measures. Normalized Google Distance (NGD) is employed to resolve appositive instances. The Vector Space Model is then applied to the anaphora resolved document. Based on distance measures in high dimensional space, the cohesion between target word pairs is observed. Strongly cohesive word clusters qualify as opinion words. Results from a pilot collection of short opinion editorials and critical reviews from newspapers and manual annotation of perspective of up to 710 such sentences indicate an agreement of 76% in opinion annotation.
Flight control application of eigenstructure assignment with optimization of robustness to structured state space uncertainty

The authors propose a robust eigenstructure assignment design method which optimizes the sufficient condition for robust stability while constraining the dominant eigenvalues to lie within chosen regions in the complex plane. This constrained optimization problem is solved by using the sequential unconstrained minimization technique with a quadratic extended interior penalty function. Also introduced is a similarity transformation on the uncertain plant which can reduce the conservation of the sufficient condition. The design of a robust eigenstructure assignment controller for a pitch pointing/vertical translation maneuver of the AFTI F-16 aircraft is presented as an example. <<ETX>>
A Dynamic Multi-criteria Aid for Process Driving Using Case-based Reasoning

The evolution that knew the driving since the nineties concludes on the necessity to consider the driving as a system of multi-criteria decision aid. It is not an easy task for process decision-makers to acquire, to integrate and to understand all the increasing amount of data obtained from a process and to get meaningful knowledge from it. Thus, it is necessary to use automatic knowledge acquisition to build consistent and robust decisions taken in a process. Case-based reasoning (CBR) is a technique to solve new problems based on previous experience. This paper introduces a new multi-criteria decision aid model for process driving like an answer to the intervening changes in the enterprise and its environment. The objective of this model is to help the decision-maker to adopt the best action facing a new situation. The application of the proposed model has been done in the operational process of the Packing Techniques in Cardboard Mayr-Melnhof Packaging society.
Analysis and Optimization of Connecting Rod With Different Materials

 Abstract — Selection of connecting rod for good performance of engine is very difficult. The material used in the connecting rod should be chosen wisely because during manufacturing process it has to undergo various production processes and subsequent heat treatment process, which is very much important for strength and stiffness. Based on which the High Strength Carbon Fiber connecting rod will be compared with connecting rod made up of Stainless Steel and Aluminum Alloy. The results can be used for optimization for weight reduction and for design modification of the connecting rod. Analyses are carried out in ANSYS software .
Comparing feature bias and feature selection strategies for many-attribute machine learning

We describe the concept of feature bias (FB) strategies and compare such strategies with traditional feature selection (FS) for predictive machine learning on a collection of datasets. FS is a common step in many classification and regression tasks. It is necessary because machine learning tools often cannot cope when the data has thousands of attributes. However, the strategy used by FS techniques is essentially binary. It is hoped that most “irrelevant” features are removed prior to the application of machine learning, and that the subsequent machine learning stage will be much faster (since there are fewer features to process) and also more successful (since many features will be removed by FS that seem unimportant for the classification task at hand). However, FS methods typically rely on standard statistical ideas and are unable to guarantee that all and only relevant features remain. A feature bias strategy, on the other hand, is an alternative approach in which we never entirely remove any feature from consideration. Experimental results reveal that FB can greatly improve upon FS for prediction tasks, particularly on poorly correlated datasets. We propose a tentative guideline for choosing an FS or FB strategy based on simply calculated inherent correlation of the dataset.
Chapter V Querying Web Accessibility Knowledge from Web Graphs

Web Accessibility is a hot topic today. Striving for social inclusion has resulted in the requirement of providing accessible content to all users. However, since each user is unique, and the Web evolves in a decentralized way, little or none is known about the shape of the Web’s accessibility on its own at a large scale, as well as from the point-of-view of each user. In this chapter the authors present the Web Accessibility Knowledge Framework as the foundation for specifying the relevant information about the accessibility of a Web page. This framework leverages Semantic Web technologies, side by side with audience modeling and accessibility metrics, as a way to study the Web as an entity with unique accessibility properties dependent from each user’s point of view. Through this framework, the authors envision a set of queries that can help harnessing and inferring this kind of knowledge from Web graphs.
A shifting bottleneck heuristic for minimizing the total weighted tardiness in a job shop

We present a shifting bottleneck heuristic for minimizing the total weighted tardi- ness in a job shop. The method decomposes the job shop into a number of single-machine subproblems that are solved one after another. Each machine is scheduled according to the solution of its corresponding subproblem. The order in which the single machine subproblems are solved has a significant impact on the quality of the overall solution and on the time required to obtain this solution. We therefore test a number of different orders for solving the subprob- lems. Computational results on 66 instances with ten jobs and ten machines show that our heuristic yields solutions that are close to optimal, and it clearly outperforms a well-known dispatching rule enhanced with backtracking mechanisms. © 1999 John Wiley & Sons, Inc. Naval
Building Croatian WordNet

This paper reports on the prototype Croatian WordNet (CroWN). The resource has been collected by translating BCS1 and 2 from English, but also by usage of machine readable dictionary of Croatian language which was used for automatical extraction of semantic relations and their inclusion into CroWN. The paper presents the results obtained, discusses some problems encountered along the way and points out some possibilities of automated acquisition and populating synsets and their refinement in the future. In the second part the paper discusses the lexical particularities of Croatian, which are also shared between other Slavic languages (verbal aspect and derivation patterns), and points out the possible problems during the process of their inclusion in CroWN.
Multi-threshold Image Segmentation Using Improved Pulse Coupled Neural Networks Based on Mutual Information

In order to process multi-threshold image segmentation automatically,the traditional pulse coupled neural networks model is improved.A new algorithm of multi-threshold image segmentation using improved PCNN based on the maximization of mutual information is put forward according to the relationship between original image and segmented image,which is based on the optimization object of maximal of mutual information and a new measurement criterion for determining the number of clusters in an image called difference of mutual information.Theoretical analysis and simulation results indicate that the new method can automatically determine the optimal cyclic iterative times and the optimal number of gray-scale clusters,has a favorable capability to carve up characteristics and maintain the edges,texture and details of images,has higher precision in different image segmentation and can be more adaptability.