Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparison of Multilayer Perceptron and Adaptive Neuro-Fuzzy System on Backcalculating the Mechanical Properties of Flexible Pavements

Nondestructive testing (NDT) is the integral part of the performance evaluation of flexible pavements. In all NDT methods, Falling Weight Deflectometer (FWD) is probably the most popular technique. Basically, it measures time-domain deflections from numerous road sections emerging by the applied impulse load. In order to characterize the structural integrity of considered pavement system, it is required to make an inversion for the calculation of mechanical pavement properties using a backcalculation tool covering both a forward pavement response model and an optimization algorithm. On the other hand, backcalculation problem can also be solved by an adaptive system using a supervised learning algorithm. In this manner, multilayer perceptron (MLP) and adaptive neuro-fuzzy system (ANFIS) methodologies, popular universal functional approximating techniques of Artificial Intelligence (AI), are appropriate for pavement backcalculation problem. Therefore, two-phased (forward and backward) structure of traditional backcalculation approaches is reduced into one step with the help of the supervised learning mechanisms of MLP and ANFIS. In this study, these methodologies are both employed to backcalculate mechanical properties of flexible pavements and compared in terms of modeling precision, uncertainty handling, computational expense, and data requirements. Results indicated that, both techniques are valid and have certain advantages over each other and should be preferred with respect to quantity and quality of the data at hand. In addition, AI-based supervised nonlinear mapping techniques not only exhibit precise backcalculation results, but also enable real-time pavement analyzing abilities.
Analytical Results for Design Space Exploration of Many-Core Processors for Sound Synthesis of Guitar

In this paper, we present a design space exploration of optimal many-core processors for the physics-based sound synthesis of guitar by quantitatively evaluating the impact of a sample-per-processing element (SPE) ratio - the amount of sample data directly mapped to each processing element (or varying the number of processing elements for a fixed sample size) on system performance and efficiency using architectural and workload simulation. The effect of the sample to processor ratio is difficult to analyze because it significantly affects both hardware and software design as SPE ratio is varied. Experimental results indicate that a SPE in the range of 2,756 to 11,025 (or the number of PEs between 24 and 96) provides the most efficient operation for synthesizing guitar sounds with 6-note polyphony sampled at 44.1 kHz, yielding the highest task throughput per unit of area or energy. In addition, the synthesized sounds are very similar to the original guitar sounds.
Using Social Signal of Hesitation in Multimedia Content Retrieval

This paper presents the graphical analysis of selection traces in matrix-factorization space of multimedia items. A trace consists of links (lines) between points that present a selected item during interaction between user and video-on-demand (VoD) system. User used gestures to select from among video on screen (VoD service), while additional user-produced social signal (SS) information was used to recommend more suitable new videos in the process of selection. We used a sample of 42 users, equally split into test (SS considered) and control and random (SS not considered) user groups. We assumed, for each user, there are areas of multimedia items in the matrix-factorization space that include preferred user items, called preferred areas. The results showed that user selection traces in the space of multimedia items (matrix-factorization space) better covered the user’s preferred areas of items if the SS of hesitation was considered.
Getting around the task-artifact cycle: how to make claims and design by scenario

We are developing an “action science” approach to human-computer interaction (HCI), seeking to better integrate activities directed at understanding with those directed at design. The approach leverages development practices of current HCI with methods and concepts to support a shift toward using broad and explicit design rationale to reify where we are in a design process, why we are there, and to guide reasoning about where we might go from there. We represent a designed artifact as the set of user scenarios supported by that artifact and more finely by causal schemas detailing the underlying psychological rationale. These schemas, called claims, unpack wherefores and whys of the scenarios. In this paper, we stand back from several empirical projects to clarify our commitments and practices.
A STUDY ON MHD BOUNDARY LAYER FLOW OVER A NONLINEAR STRETCHING SHEET USING IMPLICIT FINITE DIFFERENCE METHOD

The problem of the MHD boundary layer flow of an in compressible viscous fluid over a non-linear stretc hing sheet is discussed. Using similarity transformation governing equations are transformed in to nonlinear ordinary different ial equation. The Implicit finite difference Keller box method is applied to find the numerical solution of nonlinear differential equat ion. Graphical results of fluid velocity have been presented and discussed for the related parameters.
THE IMPACT OF CHILDHOOD FAMILY EXPERIENCE ON PARTNERSHIP PROBLEMS AND BIRTH-RATE IN ADULTHOOD

The causes for the partnership problems and low birth-rate can be looked upon not only through an economical discourse, but also via the thorough exploration of psychological determinants of sustainable family relationships. The skills and abilities for the development of such relationships significantly depend on the characteristics of childhood family experience. Exploring the factors that influence partnership quality and birth-rate in Latvia 221 respondents were surveyed (185 women and 36 men) aged from 20 to 40. Majority of the sample indicated to their negative childhood experience (mostly parents’ conflicts, divorce, neglect, alcohol abuse) and admitted an impact of this experience on their partnership in adulthood. The respondents with negative childhood family experience reported conflicts in their current relationships more often than their counterparts with supportive childhood experience. T he most frequent partnership problems appeared to be emotional violence and computer addiction, at much less rate – alcohol abuse. Though, the statistically significant correlations between the childhood family experience and the partnership problems as well as between the childhood family experience and nymber of childen in family were not found in the given sample. The problem of drug addiction had a statistically significant negative correlation with the number of children in family. Future research could focus on the ways in which positive and adverse childhood experiences interact to influence partnership quality and birth-rate.
Passive Millimeter-wave imaging using a Substrate Integrated Waveguide antenna

A millimeter-wave imaging system for concealed object detection at the frequency of 24 GHz with total power radiometer configuration has been designed and tested. We added to the system a microwave lens to focus the target to the antenna and a nipkow disc to scan the image under surveillance. We also incorporated the substrate integrated waveguide (SIW) technology in the receiver antenna.
Boundary value problems for higher order ordinary differential equations

Let f : [a, b] × R n+1 → R be a Carathéodory's function. Let {t h }, with t h ∈ [a, b], and {x h } be two real sequences. In this paper, the family of boundary value problems´x is considered. It is proved that these boundary value problems admit at least a solution for each k ≥ ν, where ν ≥ n + 1 is a suitable integer. Some particular cases, obtained by specializing the sequence {t h }, are pointed out. Similar results are also proved for the Picard problem.
Overhead reduction of location-aided gateway discovery protocols

Integration of mobile ad-hoc networks (MANETs) into infrastructure-based networks allows mobile users to access other networks. At a network boundary, some node with multiple interfaces plays an important role as a gateway. Gateway discovery mechanism is necessary for mobile nodes to discover nearby gateways but causes message exchange overhead. In order to control the overhead, we present a novel location-aided gateway discovery protocol with directional broadcast algorithm and Solicitation technique. Simulation results show that our proposed protocol can reduce the overhead, as compared to conventional protocols. Moreover, it improves packet delivery ratio, end-to-end delay, and gateway discovery time.
Face Identification by SIFT-based Complete Graph Topology

This paper presents a new face identification system based on graph matching technique on SIFT features extracted from face images. Although SIFT features have been successfully used for general object detection and recognition, only recently they were applied to face recognition. This paper further investigates the performance of identification techniques based on Graph matching topology drawn on SIFT features which are invariant to rotation, scaling and translation. Face projections on images, represented by a graph, can be matched onto new images by maximizing a similarity function taking into account spatial distortions and the similarities of the local features. Two graph based matching techniques have been investigated to deal with false pair assignment and reducing the number of features to find the optimal feature set between database and query face SIFT features. The experimental results, performed on the BANCA database, demonstrate the effectiveness of the proposed system for automatic face identification.
Full Bayesian significance test applied to multivariate normal structure models

The Full Bayesian Signicance Test (FBST) for precise hy- potheses is applied to a Multivariate Normal Structure (MNS) model. In the FBST we compute the evidence against the precise hypothesis. This evi- dence is the probability of the Highest Relative Surprise Set (HRSS) tangent to the sub-manifold (of the parameter space) that denes the null hypothesis. The MNS model we present appears when testing equivalence conditions for genetic expression measurements, using micro-array technology.
A computational algorithm for F0 contour generation in Korean developed with prosodically labeled databases using k-toBI system

This study describes an algorithm for the F0 contour generation system for Korean sentences and its evaluation results. 400 K-ToBI labeled utterances were used which were read by one male and one female announcers. F0 contour generation system uses two classification trees for prediction of K-ToBI labels for input text and 11 regression trees for prediction of F0 values for the labels. Evaluation results of the system showed 77.2% prediction accuracy for prediction of IP boundaries and 72.0% prediction accuracy for AP boundaries. Information of voicing and duration of the segments was not changed for F0 contour generation and its evaluation. Evaluation results showed 23.5Hz RMS error and 0.55 correlation coefficient in F0 generation experiment using labelling information from the original speech data.
Learning about Users from Observation

Many approaches and systems for recommending information, goods, or other kinds of objects have been developed in recent years. In these systems, machine learning methods are often used that need training input to acquire a user interest profile. Such methods typically need positive and negative evidence of the user’s interests. To obtain both kinds of evidence, many systems make users rate relevant objects explicitly. Others merely observe the user’s behavior, which yields positive evidence only; in order to be able to apply the standard learning methods, these systems mostly use heuristics to also find negative evidence in observed behavior. In this paper, we present an approach for learning interest profiles from positive evidence only, as it is contained in observed user behavior. Thus, both the problem of interrupting the user for ratings and the problem of somewhat artificially determining negative evidence are avoided. A methodology for learning explicit user profiles and recommending interesting objects has been developed. It is used in the context of ELFI - a Web-based information system. The evaluation results are briefly described in this paper. Our current efforts revolve around further improvements of the methodology and its implementation for recommending interesting web pages to users of a web browser.
Received Power-Based Channel Estimation for Energy Beamforming in Multiple-Antenna RF Energy Transfer System

In this paper, we propose a channel estimation algorithm based on the received power measurements for the multi-antenna radio frequency (RF) energy transfer system. The energy beamforming is a key technology to resolve a low energy transfer efficiency problem of the RF energy transfer system, which is mainly caused by a free-space path loss. The channel gains between transmit and receive antennas should be estimated to use the energy beamforming technique. We propose a received power-based channel estimation scheme that can be implemented by means of a simple power meter at a receiver. In the proposed scheme, the receiver measures the received power of the RF signal and sends a feedback containing the received power measurements to the transmitter. We formulate a channel estimation problem, which is recast into a linear estimation problem by using complex vectorization. Then, this linear estimation problem is solved by the ordinary least squares method and the Kalman filter-based algorithm. We also propose a method to reduce the dimension of the estimation problem when there are a smaller number of receive antennas than transmit antennas.
Dynamic Window Coupling for multipath congestion control

The traditional problem of end-hosts efficiently and fairly utilizing end-to-end paths becomes significantly harder when the end-hosts are multihomed. Such is the case, for instance, when an end-host has simultaneous connectivity through several service providers, or when a mobile device is simultaneously connected via both a wireless LAN and a cellular network. A multihoming-aware transport protocol, such as MPTCP or SCTP, that sends data over the multiple resulting end-to-end paths must be fair to other flows in the network while being able to maximize its own throughput. In this paper, we present Dynamic Window Coupling (DWC), a multipath congestion control mechanism that seeks to achieve both these goals. DWC uses loss and delay signals to detect shared bottlenecks, explicitly grouping and sharing congestion control across subflows on paths that have a common bottleneck, while separating congestion control for subflows on paths with distinct bottlenecks. DWC detects shifting bottlenecks in the network and responds by dynamically regrouping subflows. Simulations demonstrate that DWC detects shared bottlenecks under most network topologies and conditions that we considered, regroups subflows correctly as bottlenecks shift, aggregates throughput across distinct bottlenecks, and is fair to other TCP flows at all bottlenecks.
Speech enhancement using a robust Kalman filter post-processor in the modulation domain

We propose a speech enhancement algorithm that applies a Kalman filter in the modulation domain to the output of a conventional enhancer operating in the time-frequency domain. The speech model required by the Kalman filter is obtained by performing linear predictive analysis in each frequency bin of the modulation domain signal. We show, however, that the corresponding speech synthesis filter can have a very high gain at low frequencies and may approach instability. To improve the stability of the synthesis filter, we propose two alternative methods of limiting its low frequency gain. We evaluate the performance of the speech enhancement algorithm on the core TIMIT test set and demonstrate that it gives consistent performance improvements over the baseline enhancer.
RMT: A novel algorithm for reducing multicast traffic in HSR protocol networks

The high-availability seamless redundancy (HSR) protocol is one of the most important redundancy IEC standards that has garnered a great deal of attention because it offers a redundancy with zero recovery time, which is a feature that is required by most of the modern substation, smart grid, and industrial field applications. However, the HSR protocol consumes a lot of network bandwidth compared to the Ethernet standard. This is due to the duplication process for every sent frame in the HSR networks. In this paper, a novel algorithm known as the reducing multicast traffic (RMT) is presented to reduce the unnecessary redundant multicast traffic in HSR networks by limiting the spreading of the multicast traffic to only the rings that have members associated with that traffic instead of spreading the traffic into all the network parts, as occurs in the standard HSR protocol. The mathematical and the simulation analyses show that the RMT algorithm offers a traffic reduction percentage with a range of about 60-87% compared to the standard HSR protocol. Consequently, the RMT algorithm will increase the network performance by freeing more bandwidth so as to reduce HSR network congestion and also to minimize any intervention from the network administrator that would be required when using traditional traffic filtering techniques.
A Multicriteria Scheduling with Sequence-Dependent Setup Times

In this paper a multicriteria scheduling problem with sequence-dependent setup times on a single machine is considered. The objective function of the problem is minimization of the weighted sum of total completion time, maximum tardiness and maximum earliness. An integer programming model is developed for the problem which belongs to NP-hard class. Only small size problems with up to 12 jobs can be solved by the proposed integer programming model. Heuristic methods are also used to solve large size problems. These heuristics are four tabu search based heuristics and random search method. According to computational results the tabu search based methods are effective in finding problem solutions with up to 1000 jobs.
Optimization of Culture Conditions (Sucrose, pH, and Photoperiod) for In Vitro Regeneration and Early Detection of Somaclonal Variation in Ginger Lime (Citrus assamensis)

Various explants (stem, leaf, and root) of Citrus assamensis were cultured on MS media supplemented with various combinations and concentrations (0.5–2.0 mgL−1) of NAA and BAP. Optimum shoot and root regeneration were obtained from stem cultures supplemented with 1.5 mgL−1 NAA and 2.0 mgL−1 BAP, respectively. Explant type affects the success of tissue culture of this species, whereby stem explants were observed to be the most responsive. Addition of 30 gL−1 sucrose and pH of 5.8 was most optimum for in vitro regeneration of this species. Photoperiod of 16 hours of light and 8 hours of darkness was most optimum for shoot regeneration, but photoperiod of 24 hours of darkness was beneficial for production of callus. The morphology (macro and micro) and anatomy of in vivo and in vitro/ex vitro Citrus assamensis were also observed to elucidate any irregularities (or somaclonal variation) that may arise due to tissue culture protocols. Several minor micromorphological and anatomical differences were observed, possibly due to stress of tissue culture, but in vitro plantlets are expected to revert back to normal phenotype following full adaptation to the natural environment.
User Interfaces for the Exploration of Hierarchical Multi-dimensional Data

A variety of user interfaces have been developed to support the querying of hierarchical multi-dimensional data in an OLAP setting such as pivot tables and Polaris. They are used to regularly check portions of a dataset and to explore a new dataset for the first time. In this paper, we establish criteria for OLAP user interface capabilities to facilitate comparison. Two criteria are the number of displayed dimensions along which comparisons can be made and the number of dimensions that are viewable at once - visual comparison depth and width. We argue that interfaces with greater visual comparison depth support regular checking of known data by users that know roughly where to look, while interfaces with greater comparison width support exploration of new data by users that have no a priori starting point and need to scan all dimensions. Pivot tables and Polaris are examples of the former. The main contribution of this paper is to introduce a new scalable interface that uses parallel dimension axis which supports the latter, greater visual comparison width. We compare our approach to both table based and parallel coordinate based interfaces. We present an implementation of our interface SGViewer, user scenarios and provide an evaluation that supports the usability of our interface
B-SHOT: A binary feature descriptor for fast and efficient keypoint matching on 3D point clouds

In this paper, we introduce the very first `binary' 3D feature descriptor, B-SHOT, for fast and efficient keypoint matching on 3D point clouds. We propose a binary quantization method that converts a real valued vector to a binary vector. We apply this method on a state-of-the-art 3D feature descriptor, SHOT [1], and create a new binary 3D feature descriptor. B-SHOT requires 32 times lesser memory for its representation while being 6 times faster in feature descriptor matching, when compared to the SHOT feature descriptor. Experimental evaluation shows that B-SHOT offers comparable keypoint matching performance to that of the state-of-the-art 3D feature descriptors on a standard benchmark dataset.
A Programmable Dual-RNA–Guided DNA Endonuclease in Adaptive Bacterial Immunity

Ditching Invading DNA Bacteria and archaea protect themselves from invasive foreign nucleic acids through an RNA-mediated adaptive immune system called CRISPR (clustered regularly interspaced short palindromic repeats)/CRISPR-associated (Cas). Jinek et al. (p. 816, published online 28 June; see the Perspective by Brouns) found that for the type II CRISPR/Cas system, the CRISPR RNA (crRNA) as well as the trans-activating crRNA—which is known to be involved in the pre-crRNA processing—were both required to direct the Cas9 endonuclease to cleave the invading target DNA. Furthermore, engineered RNA molecules were able to program the Cas9 endonuclease to cleave specific DNA sequences to generate double-stranded DNA breaks. A prokaryotic RNA–directed targeting system can be designed to cleave any DNA sequence. Clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated (Cas) systems provide bacteria and archaea with adaptive immunity against viruses and plasmids by using CRISPR RNAs (crRNAs) to guide the silencing of invading nucleic acids. We show here that in a subset of these systems, the mature crRNA that is base-paired to trans-activating crRNA (tracrRNA) forms a two-RNA structure that directs the CRISPR-associated protein Cas9 to introduce double-stranded (ds) breaks in target DNA. At sites complementary to the crRNA-guide sequence, the Cas9 HNH nuclease domain cleaves the complementary strand, whereas the Cas9 RuvC-like domain cleaves the noncomplementary strand. The dual-tracrRNA:crRNA, when engineered as a single RNA chimera, also directs sequence-specific Cas9 dsDNA cleavage. Our study reveals a family of endonucleases that use dual-RNAs for site-specific DNA cleavage and highlights the potential to exploit the system for RNA-programmable genome editing.