Miracle-dz/UniFAR-FTUs huggingface dataset:
Inferring room geometries

Determining the geometry of an acoustic enclosure using microphone arrays has become an active area of research. Knowledge gained about the acoustic environment, such as the location of reflectors, can be advantageous for applications such as sound source localization, dereverberation and adaptive echo cancellation by assisting in tracking environment changes and helping the initialization of such algorithms. A methodology to blindly infer the geometry of an acoustic enclosure by estimating the location of reflective surfaces based on acoustic measurements using an arbitrary array geometry is developed and analyzed. The starting point of this work considers a geometric constraint, valid both in two and three-dimensions, that converts time-of-arrival and time-difference-ofarrival information into elliptical constraints about the location of reflectors. Multiple constraints are combined to yield the line or plane parameters of the reflectors by minimizing a specific cost function in the least-squares sense. An iterative constrained least-squares estimator, along with a closedform estimator, that performs optimally in a noise-free scenario, solve the associated common tangent estimation problem that arises from the geometric constraint. Additionally, a Hough transform based data fusion and estimation technique, that considers acquisitions from multiple source positions, refines the reflector localization even in adverse conditions. An extension to the geometric inference framework, that includes the estimation of the actual speed of sound to improve the accuracy under temperature variations, is presented that also reduces the required prior information needed such that only relative microphone positions in the array are required for the localization of acoustic reflectors. Simulated and real-world experiments demonstrate the feasibility of the proposed method.
Implementation of Micro-Controller Based Adaptive Motion Detection for Industrial Monitoring System

Industrial system has become concurrent research focus in most developed counties being an ultimate source of revenue benefited by citizens. This project emphasized on implementation of micro-controller based adaptive motion detection for industrial monitoring system as a factor that determines synergy and sustainability of industrial management. The camera will be interface with PC to detect the presence of object and report production activities through image capture and enable video stream for monitoring. The design is to create interface link between Microcontroller AVR PC, ATMEG16 and camera C3088. The PC will establish bi-directional communication with AVR while using I 2 C communication protocol is used to interface camera and AVR. The industrial feedback process will be control with AVR based on adaptive motion detection from installed camera. The captured image obtain from the camera can be use for surveillance or can be process for image processing purpose in industries and organizations. Keywords : Lighting, LED, economic usage, light energy, detection
Cryptography Based Light-Weight Attribute Encryption Scheme for Internet of Things

For those organization for vast number about IoT devices, progressively vast amounts about information need aid produced, which abandons provision suppliers confronting new tests especially for administration to security. Information security might make attained utilizing cryptographic encryption strategies. Cryptographic keys are needed will unscramble data, Furthermore must a chance to be disseminated to An specific best approach will commissioned information clients that perform dissimilar errands with respect to information. To deal with an extensive amount about units generating trickles for data, an adaptable and fine-grained get control result thought to a chance to be utilized. A guaranteeing approach need as of late rose In view of Attribute-Based encryption (ABE) that gives adaptable What's more fine-grained get control. This framework employments quality based encryption to IOT gadgets. Those different clients previously, an association will oblige to entry different information produced Eventually Tom's perusing diverse sensors. Hence, in this system, best the clients who need aid commissioned will right specific information camwood right it. The way used to scramble that information is itself encrypted Also sent should client. When a commissioned client solicitation those data, as much genuineness is main checked and the qualities of the asked information are sent on as much email. He may be at that point obliged with enters this data. These qualities would use to unscramble those encrypted enter. Those decrypted fact that thus used to unscramble the information
Pass-transistor logic and its sub-Vdd voltage-swing behaviours in low-voltage circuit design

Internal signal propagation with voltage swing less than the supply voltage have been proposed through various architecture or structures. Reduced supply voltage in digital and analog circuits is considered to be one of the best methods for achieving real low power dissipation circuits. In this paper, pass-transistor logic with suppressed internal voltage-swing is investigated and analyzed. A proposal on a reduced swing 14-bit parity generator and carry generation blocks of a parallel full adder are also given. In addition, optimization on propagation delay can be achieved by proper tapering of the dimension of the transistors.
Improvements of a Remote User Password Authentication Scheme using Smart Card

In 2009, Hsiang et al.’s proposed a secure, improved remote user authentication scheme using smart card against the parallel session attack, masquerading attack, and password guess attack. Hsiang et al.’s scheme, however, is still vulnerable to off-line password guess attack if the attacker steals or temporarily accesses the smart card to extract the information stored in it, and does not satisfy the security requirement against the adversary that have to be considered in remote user authentication scheme using password-based smart cards. In this paper, I proposed an efficient mutual authentication scheme that based on the hash function and random number. Accordingly, an improved remote user authentication scheme is proposed that is secure against password guess attack.
A novel hyperspectral image classification approach based on multiresolution segmentation with a few labeled samples

Hyperspectral remote sensing technology becomes more and more popular in recent years which can be applied to satellite, plane, and flying robots. An important application of hyperspectral remote sensing is the classification of ground objects. However, when the number of labeled samples is very small, the classification accuracy of pixelwise classifiers will decline dramatically. In this article, a novel hyperspectral image classification approach is proposed based on multiresolution segmentation with a few labeled samples. The proposed method is motivated by the fact that pixels within a homogenous region are very likely to have the same class label, which can be utilized to increase the number of labeled samples. The proposed method consists of four steps. First, the hyperspectral image was segmented using the multiresolution image segmentation method. Second, the unlabeled neighbor pixels in the same region as the labeled pixels were selected randomly to assign the class labels. Next, one pixelwise classifier, that is, support vector machine, is used to classify the hyperspectral image with the new labeled sample set. Finally, edge-preserving filtering is performed on the classification result to remove the salt-and-pepper noise and preserve edges of ground objects. Experimental results on three real hyperspectral images demonstrate that the proposed method can improve the classification accuracy significantly when the number of labeled samples is relatively small.
Nonword Repetition Task to Evaluate Syllable Stress as a Motor Class

Nonword Repetition Task to Evaluate Syllable Stress as a Motor Class Emily R. Cobun Current speech therapy methods and theories are based on generalized motor program (GMP) theory (Schmidt, 1975). GMP theory states a single GMP, or motor program, directs multiple movements of speech (Maas et al., 2008). Additionally, GMP theory asserts these similar muscle movements are part of the same motor class, which allows a GMP to direct performance on novel, untrained patterns of movements (i.e., what is termed “transfer performance”; Chamberlin & Magill, 1992; Schmidt, 1975). Alternatively, movements outside of a learned motor class will be more difficult to perform because a different GMP is controlling these movements. Currently, syllable stress patterns are theorized as the GMP when planning motor speech tasks. This study aims to help clarify the method through which motor speech movements are learned. Meigh et al. (in press) conducted a study to learn more about speech motor planning. This study found that syllable stress, which was the expected GMP for speech production, did not direct transfer performance on untrained stimuli following training on a speech-like task. Instead, participants encoded speech sound (i.e., phoneme) information during training that influenced transfer results. In Meigh’s study, participants were trained using a speech production task but the testing procedure was not speech-based. Meigh’s results and interpretation may have been impacted by the study design because of the “mismatch” between modes of training and testing in this study. Therefore, the current study replicated and extended Meigh’s experiment using a speech-based training and transfer task. Twenty-four participants (16 females and 3 males) produced nonsense words (i.e., nonwords) using a motor learning design, which included mass amounts of training followed by an evaluation of performance on untrained stimuli. During training, participants produced different syllable stress patterns while repeating a training list of nonwords. Following training, participants repeated a list of both trained and untrained nonwords that varied in similarity to the trained stimuli. All untrained stimuli varied by motor class (i.e., syllable stress pattern), as well as the phonemes (or sounds). Accuracy of nonword productions were evaluated across transfer stimuli sets, and results revealed participants had learned syllable stress and phoneme information during training. These results align with a GMP theory and Meigh (in press) suggesting that more than one GMP memory representation may be encoded during motor learning.
The Chinese Multi-Word Expression Extraction Based on Improved Semi-supervised Algorithm

Failing to identify multi-word expression (MWE) may cause serious problems for many Natural Language Processing (NLP) tasks. Because of lack of Chinese MWE labeled corpus, we used a semi-supervised Co-trade algorithm to extract Chinese MWE, furthermore, a supervised head word expansion method was used to find cluster center in data editing step, which makes that the supervised information was also added to the Co-trade algorithm in order to select correct data. Experiment result shows that the extraction results of Chinese multi-word expression using improved Co-trade algorithm is better than that of original algorithm, which verified that the improved algorithm is effective.
Stable, circulation-preserving, simplicial fluids

Visual quality, low computational cost, and numerical stability are foremost goals in computer animation. An important ingredient in achieving these goals is the conservation of fundamental motion invariants. For example, rigid and deformable body simulation benefits greatly from conservation of linear and angular momenta. In the case of fluids, however, none of the current techniques focuses on conserving invariants, and consequently, they often introduce a visually disturbing numerical diffusion of vorticity. Visually just as important is the resolution of complex simulation domains. Doing so with regular (even if adaptive) grid techniques can be computationally delicate. In this chapter, we propose a novel technique for the simulation of fluid flows. It is designed to respect the defining differential properties, i.e., the conservation of circulation along arbitrary loops as they are transported by the flow. Consequently, our method offers several new and desirable properties: (1) arbitrary simplicial meshes (triangles in 2D, tetrahedra in 3D) can be used to define the fluid domain; (2) the computations are efficient due to discrete operators with small support; (3) the method is stable for arbitrarily large time steps; (4) it preserves discrete circulation avoiding numerical diffusion of vorticity; and (5) its implementation is straightforward.
UNIX Guardians: active user intervention in data protection

The GUARDNIX system is tailored for user participation in the protection of data. The system, an enhanced 4.2 BSD Unix, utilizes a special class of processes called Guardians to change normally passive files into active objects. Multiple processors are used to physically separate normal processes from the main operating system kernel. Data is provided additional protection by using cryptography. The file directory tree is partitioned, with the subtrees attached to Guardians. GUARDNIX reduces the need for roots and does not allow root processes during normal operations. <<ETX>>
Proceedings of the 6th Eurographics Symposium on Sketch-Based Interfaces and Modeling

Welcome to SBIM 2009! These proceedings represent the sixth year of "Sketch-Based Interfaces and Modeling. " Started in 2004, SBIM provides a unique venue for researchers, students and practitioners interested in sketch-based techniques to interact with one another, share lessons learned, show new results and discuss open issues. It continues to be a forum for the HCI community to present their latest work on 2D sketch-based interfaces and recognition technology and for the computer graphics community to present their latest work on sketch-based modeling. Last year, SBIM was held in Annecy, France in conjunction with the Annecy Animation Film Festival. This year, SBIM is in the United States for the second time and is co-located with ACM SIGGRAPH 2009 in New Orleans, Louisiana. This year also marks the first time that SBIM is a symposium instead of a workshop. Co-locating with SIGGRAPH broadens the attendee base and gives people the chance to experience New Orleans culture and cuisine. We had 29 paper submissions this year, which is down from the 36 submissions we had last year, but on par with previous SBIM workshops. Each paper was double blind reviewed by four members of our international program committee and we were able to accept 19 of them for the symposium. As in previous years, the quality of the submitted papers was strong, resulting in a high acceptance rate, a testament to those researchers who work in this field. The papers in these proceedings present a mix of innovative ideas in sketch recognition, 3D modeling, and sketch-based interface usability.
MobileSage - A Prototype Based Case Study for Delivering Context-Aware, Personalized, On-Demand Help Content

—We present the system design decisions for the MobileSage Prototype, a service for the on-demand delivery of multimodal help content to anyone in general and seniors in particular. Findings from user-centered research formed the system requirements, design considerations and decisions. The design of the system also includes availability, relevance, accessibility, conciseness, and comprehensiveness of multimodal content. The prototype has been evaluated in user trials with encouraging results, showing the participants’ high appreciation of the system.
The Generation Z and their Social Media Usage: A Review and a Research Outline

The paper tries to explore the awareness of how the present Generation Z is using the social media as well as to review its repercussion on them as an individual’s, organization and society as a system. The paper demarcates Generation Z from other branches of generation with a systematized differentiation in the behaviour, principles and choices which are constant over the time. It outlines their social media usage and intra-generational difference springing from environmental factors and personal factors. Personal factors are divided into steady and driving factors. The paper brings forward how the futuristic Generation Z’s use of social media influences them as an individual’s, organization and society. It also attempts to bring forward certain managerial repercussions and to them and a research outline. Earlier researches on access of social media by Generation Y as well as Generation Z give rise to certain queries which are yet to be answered. They laid focus mainly on the US & UK, ignoring other regions and countries (including nation like India which comprises of 28% of youths) with huge and rapidly increasing share of Generation Y’s & Z’s populations; and where the determinants of social-media usability would vary considerably; the customer set under these studies are those whose behaviour are inclined to vary as they move on the different phases of their life cycle; they tried to understand Generation Z’s social media use but misses to look at the controllers as well as aftermaths of social-media usage. The theoretical frame of reference brought forward in this paper harvests a thorough set of investigation questions and designs the pathway for considering the predecessors & outcomes of social networking used by Gen Z. It tries to identify certain ignored queries regarding Gen Z’s and their social media usability, along with also sketches practical insights for various decision makers.
K2K near detector laserball calibration : manipulator motivation, design and results

The K 2 K experiment uses a muon neutrino (v^) beam generated at the K E K accelerator facility, aimed at Super-Kamiokande (Super-K) detector 250 k m away, to measure oscillations first seen from atmospheric u's at Super-K. The measurement is done using two detectors. The near detector measures the flux 300 m from the origin of the neutrino beam. The far detector (Super-K) measures the neutrino flux 250 k m downstream. One main source of error in the oscillation measurement is the understanding of the near detector. After some optical calibrations along the vertical axis of the One K i l o Ton (1KT) detector found problems wi th the position reconstruction a manipulation system was built. The goal of this manipulation system was to allow exploration of the entire 1 K T volume wi th a calibration source. The design required the manipulation system to place the calibration source to ~1 cm accuracy in the 1 K T , and to avoid all contact wi th the photomultiplier tubes monitoring the tank volume. This manipulation system was built and tested at T R I U M F (Tri-University Meson Facility) and deployed in the 1 K T detector at K E K . The results of the optical position reconstruction indicate a reconstruction bias of unknown origin at high occupancy.
Are Traditional Journalism Principles Still Alive and Well in Today’s Local TV Newsrooms?

This study surveyed 348 local TV journalists to learn whether—given the demands of the contemporary, conglomerated television news industry—they still adhere to traditional journalistic principles. The findings suggest that, by and large, reporters believe they make a determined effort to uphold good journalism practices despite management pressures to produce increasingly higher volumes of news content more quickly and with fewer resources. Findings suggest further scholarly attention to two journalism principles in particular may be needed: the principle of verifying facts before publication as it pertains to social media adoption in newsrooms and, secondly, changes in newsroom organization related to the principle of watchdog journalism.
Indoor Slope and Edge Detection by Using Two-Dimensional EKF-SLAM with Orthogonal Assumption

In an indoor environment, slope and edge detection is an important problem in simultaneous localization and mapping (SLAM), which is a basic requirement for mobile robot autonomous navigation. Slope detection allows the robot to find areas that are more traversable while the edge detection can prevent robot from falling. Three-dimensional (3D) solutions usually require a large memory and high computational costs. This study proposes an efficient two-dimensional (2D) solution to combine slope and edge detection with a line-segment-based extended Kalman filter SLAM (EKF-SLAM) in a structured indoor area. The robot is designed to use two fixed 2D laser range finders (LRFs) to perform horizontal and vertical scans. With local area orthogonal assumption, the slope and edge are modelled into line segments swiftly from each vertical scan, and then are merged into the EKF-SLAM framework. The EKF-SLAM framework features an optional prediction model that can automatically decide whether the application of iterative closest point (ICP) is necessary to compensate for the dead reckoning error. The experimental results demonstrate that the proposed algorithm is capable of building an accurate 2D map swiftly, which contains crucial information of the edge and slope.
Designing Optimized Pattern RecognitionSystems By Learning Voronoi Vectors UsingGenetic Algorithms

In this work is described a methodology for developing optimized pattern recognition systems by means of genetic machine learning. The idea is to redefine the set of classes that must be learned by the classification system, mapping them into another set which the Voronoi vectors can successfully classify a sample into one of the original classes. The main objective of this approach is to find the minimum number of classification rules (by minimizing the number of classes in the new set) that maximizes the number of correct classifications. To accomplish that, a genetic algorithm was design. In the genetic model, a classical fixed length genotype encodes the vectors positions in such a way that a variable number of vectors is allowed. The objective function is designed so that it rewards the correctness in the classification and penalize high number of vectors. In order to verify the accuracy and robustness of the genetic algorithm in finding the optimum Voronoi vectors set, simple benchmarks, which the expected optima are well known, were used. The success obtained in the tests with benchmarks has motivated the application of the methodology in the design of a nuclear power plant transients diagnosis system. The obtained results reveal the ability of the genetic algorithm in learning optimized classification rules that lead to efficient diagnosis, dealing with the compromise between number of rules and certainty in the classification.