Miracle-dz/UniFAR-FTUs huggingface dataset:
LAFTER: lips and face real time tracker

This paper describes an active-camera real-time system for tracking, shape description, and classification of the human face and mouth using only an SGI Indy computer. The system is based on use of 2-D blob features, which are spatially-compact clusters of pixels that are similar in terms of low-level image properties. Patterns of behavior (e.g., facial expressions and head movements) can be classified in real-time using Hidden Markov Model (HMM) methods. The system has been tested on hundreds of users and has demonstrated extremely reliable and accurate performance. Typical classification accuracies are near 100%.
Laterally coupled hexagonal micropillar resonator add-drop filters in silicon nitride

We report the first laterally coupled hexagonal micropillar resonator add-drop filters in silicon nitride. Our experiment reveals waveguide-coupled resonances of six-bounce ray orbits in the hexagonal microcavity. By tuning the submicrometer waveguide width, we demonstrate simultaneous optimization of the coupling efficiency and the resonance Q value. We attribute the optimum waveguide width to the near k-vector matching between the input- and output-coupled waveguide fundamental mode and the cavity six-bounce modes that are coherently coupled along the resonator flat sidewalls.
GO-function: deriving biologically relevant functions from statistically significant functions

In high-throughput studies of diseases, terms enriched with disease-related genes based on Gene Ontology (GO) are routinely found. However, most current algorithms used to find significant GO terms cannot handle the redundancy that results from the dependencies of GO terms. Simply based on some numerical considerations, current algorithms developed for reducing this redundancy may produce results that do not account for biologically interesting cases. In this article, we present several rules used to design a tool called GO-function for extracting biologically relevant terms from statistically significant GO terms for a disease. Using one gene expression profile for colorectal cancer, we compared GO-function with four algorithms designed to treat redundancy. Then, we validated results obtained in this data set by GO-function using another data set for colorectal cancer. Our analysis showed that GO-function can identify disease-related terms that are more statistically and biologically meaningful than those found by the other four algorithms.
Applications of Near-infrared Spectroscopy in Food Safety Evaluation and Control: A Review of Recent Research Advances

Food safety is a critical public concern, and has drawn great attention in society. Consequently, developments of rapid, robust, and accurate methods and techniques for food safety evaluation and control are required. As a nondestructive and convenient tool, near-infrared spectroscopy (NIRS) has been widely shown to be a promising technique for food safety inspection and control due to its huge advantages of speed, noninvasive measurement, ease of use, and minimal sample preparation requirement. This review presents the fundamentals of NIRS and focuses on recent advances in its applications, during the last 10 years of food safety control, in meat, fish and fishery products, edible oils, milk and dairy products, grains and grain products, fruits and vegetables, and others. Based upon these applications, it can be demonstrated that NIRS, combined with chemometric methods, is a powerful tool for food safety surveillance and for the elimination of the occurrence of food safety problems. Some disadvantages that need to be solved or investigated with regard to the further development of NIRS are also discussed.
R-trees Have Grown Everywhere

Spatial data management has been an active area of intensive research for more than two decades. In order to support spatial objects in a database system several issues should be taken into consideration such as: spatial data models, indexing mechanisms, efficient query processing, cost models. One of the most influential access methods in the area is the R-tree structure proposed by Guttman in 1984 as an effective and efficient solution to index rectangular objects in VLSI design applications. Since then, several variations of the original structure have been proposed towards: providing more efficient access, handling objects in high-dimensional spaces, supporting concurrent accesses, supporting I/O and CPU parallelism, efficient bulk-loading. It seems that due to the modern demanding applications and after the academia has paved the way, recently the industry recognized the use and necessity of R-trees. The simplicity of the structure and its resemblance to the B-tree, allowed developers to easily incorporate the structure into existing database management systems in order to support spatial query processing. In this paper we provide an extensive survey of the R-tree evolution, studying the applicability of the structure and its variations to efficient query processing, accurate proposed cost models, and implementation issues like concurrency control and parallelism. Based on the observation that ‘space is everywhere’, we anticipate that we are in the beginning of the era of the ‘ubiquitous R-tree’ in an analogous manner as B-trees were considered 25 years ago.
Virtual Reality as an Adjunct Home Therapy in Chronic Pain Management: An Exploratory Study

Background Virtual reality (VR) therapy has been successfully used as an adjunct therapy for the management of acute pain in adults and children, and evidence of potential efficacy in other health applications is growing. However, minimal research exists on the value of VR as an intervention for chronic pain. Objective This case series examined the value of VR to be used as an adjunctive therapy for chronic pain patients in their own homes. Methods An exploratory approach using a case series and personal interviews was used. Ten chronic pain patients received VR therapy for 30 min on alternate days for 1 month. Pre- and postexposure (immediately afterwards, 3 h, and at 24 h) pain assessment was recorded using the Numerical Rating Scale (NRS), and weekly using the Brief Pain Inventory (BPI) and Self-completed Leeds Assessment of Neuropathic Symptoms and Signs pain scale (S-LANSS). Terminal semistructured personal interviews with the patients were also undertaken. Results Of the 8 patients who completed the study, 5 of them reported that pain was reduced during the VR experience but no overall treatment difference in pain scores postexposure was observed. VR was not associated with any serious adverse events, although 60% of patients reported some cybersickness during some of the experiences. Conclusions Of note is that the majority of these study participants reported a reduction in pain while using the VR but with highly individualized responses. One patient also reported some short-term improved mobility following VR use. Some evidence was found for the short-term efficacy of VR in chronic pain but no evidence for persistent benefits.
Garbage Collection Algorithms for NAND Flash Memory Devices -- An Overview

This paper highlights the necessary garbage collection algorithms which is needed in flash translation layer (FTL) for NAND Flash memory devices such as SATA SSD's (Solid State Devices). Garbage collection is the process of freeing up partially filled blocks to make room for more data and the Garbage collection (GC) algorithms recommended here plays a key role in maintaining SSD's Performance and structuring the Flash memory's long term problems related to Reliability and early wearing out of cells due to repeated overwrites beyond the threshold program limit (P/E cycles). NAND Flash Memories require Garbage Collection (GC) and Wear Leveling (WL) operations to be carried out by Flash Translation Layers (FTLs) that oversee flash management. These Algorithms were implemented to reduce the number of read/write, erase cycles on the pages so that Wear Leveling, Write Amplification and Wear out of the Flash Pages can be reduced.
United Kingdom back pain exercise and manipulation (UK BEAM) randomised trial: cost effectiveness of physical treatments for back pain in primary care

Abstract Objective To assess the cost effectiveness of adding spinal manipulation, exercise classes, or manipulation followed by exercise (“combined treatment”) to “best care” in general practice for patients consulting with low back pain. Design Stochastic cost utility analysis alongside pragmatic randomised trial with factorial design. Setting 181 general practices and 63 community settings for physical treatments around 14 centres across the United Kingdom. Participants 1287 (96%) of 1334 trial participants. Main outcome measures Healthcare costs, quality adjusted life years (QALYs), and cost per QALY over 12 months. Results Over one year, mean treatment costs relative to “best care” were £195 ($360; €279; 95% credibility interval £85 to £308) for manipulation, £140 (£3 to £278) for exercise, and £125 (£21 to £228) for combined treatment. All three active treatments increased participants' average QALYs compared with best care alone. Each extra QALY that combined treatment yielded relative to best care cost £3800; in economic terms it had an “incremental cost effectiveness ratio” of £3800. Manipulation alone had a ratio of £8700 relative to combined treatment. If the NHS was prepared to pay at least £10 000 for each extra QALY (lower than previous recommendations in the United Kingdom), manipulation alone would probably be the best strategy. If manipulation was not available, exercise would have an incremental cost effectiveness ratio of £8300 relative to best care. Conclusions Spinal manipulation is a cost effective addition to “best care” for back pain in general practice. Manipulation alone probably gives better value for money than manipulation followed by exercise.
Routing multiple services in Optical Transport Network environment using mixed line rates

International Telecommunication Union (ITU-T) has laid down broad principles for the convergence of packet and optical platforms through a series of Optical Transport Network (OTN) protocols. Convergence of multiple services in order to use a common transport layer has emerged as an attractive solution to bring down the capital expenditure and operational costs. In this paper an Integer Linear Programming (ILP) model based on OTN protocol is presented to provide end to end converged optical transport network while dealing with Synchronous Digital Hierarchy (SDH) network, 10 Gigabit Ethernet (10GE), 40 Gigabit Ethernet (40GE) and 100 Gigabit Ethernet (100GE) traffic at the same time. Objective function is defined in terms of the cost of the links on which the traffic was routed, and further these links support mixed line rates. The algorithm has also been studied for evaluating the effect of data grooming and inverse multiplexing at a node. The port size of packet optical transport platform used at each node is approximated in terms of the optimal amount of each type of traffic moving through a node. To reduce the running times, the ILP model has also been evaluated for a greedy routine, what we call Highest Rate First (HRF) ordering, through which the ILP took considerably less time to converge.
Enhanced robotic body extension with modular units

The adaptation of robots to changing tasks has been explored in modular self-reconfigurable robot research, where the robot structure is altered by adapting the connectivity of its constituent modules. As these modules are generally complex and large, an upper bound is imposed on the resolution of the built structures. Inspired by growth of plants or animals, robotic body extension (RBE) based on hot melt adhesives allows a robot to additively fabricate and assemble tools, and integrate them into its own body. This enables the robot to achieve tasks which it could not achieve otherwise. The RBE tools are constructed from hot melt adhesives and therefore generally small and only passive. In this paper, we seek to show physical extension of a robotic system in the order of magnitude of the robot, with actuation of integrated body parts, while maintaining the ability of RBE to construct parts with high resolution. Therefore, we present an enhancement of RBE based on hot melt adhesives with modular units, combining the flexibility of RBE with the advantages of simple modular units. We explain the concept of this new approach and demonstrate with two simple unit types, one fully passive and the other containing a single motor, how the physical range of a robot arm can be extended and additional actuation can be added to the robot body.
A Derivation of the Steady-State MSE of RLS: Stationary and Nonstationary Cases

In this report we combine the approach of Yousef and Sayed [1] with that of Rupp and Sayed [2] to derive the steady-state mean-squared error (MSE) of the recursive least squares (RLS) algorithm in both stationary and non-stationary environments. Comparisons with the steady-state MSE of LMS are included.
Aim of the Study: Dynamic Develop- Ment of Research on Pain Has Resulted the Effect of Pre-emptive Analgesia on the Level of Postoperative Pain in Women Undergoing Surgery for Breast Neoplasm

in the formulation of the concept of pre-emptive analgesia, which involves administration of analgesics before the first pain-producing stimulus appears. It is meant to prevent increased sensitivity to pain in the postoperative period. The aim of this study was to assess the possibilities of modifying the intensity of postoperative pain evaluated with the visual analogue scale (VAS) in patients after surgical treatment for breast neoplasm offered by pre-emptive analgesia. Material and methods: The intensity of postoperative pain was measured immediately after the surgery as well as 6, 12, 18, and 24 hours later in 100 women who had undergone surgery for breast tumour. The correlation between experienced pain and the type of analgesic administered pre-emp-tively, including metamizole, tramadol, ketoprofen, and placebo was examined. The effect of other correlates such as the extensiveness of surgery, systolic and diastolic blood pressure, and heart rate on the level of experienced pain as well as the usefulness of physiological parameters for its assessment were also analysed. Results: The conducted study demonstrated the effectiveness of tramadol (p = 0.004) and ketoprofen (p = 0.039) administered half an hour before the beginning of surgery, but there was no similar effect in the case of metam-izole (p = 1.0). A positive correlation was observed between the level of experienced pain and blood pressure values (p < 0.001). Heart rate does not seem to be significantly linked with the intensity of experienced pain (p = 0.157).
Dynamical Control in Large-Scale Material Handling Systems through Agent Technology

Delayed arrivals, missing tag codes, flight changes, break-downs, etc. are some of the factors, which make the environment of airport baggage handling systems (BHS) extremely dynamic. Pre-scheduling and optimization is not an option, as identity, destination, and the order of items are unknown until they enter the system, which raises the requirement of dynamic control. The DECIDE project focuses on using multi-agent technologies as generic software components to replace traditional system-specific, centralized control software of production systems. This paper presents an application of multi-agent technologies to be used in large-scale material handling systems, such as BHS. To increase understanding and flexibility, standardized interaction patterns from the FIPA organization are used in combination with ontologies, which defines a vocabulary that enables meta-level communication. A mix of coordinating shop floor agents and mediator agents establish an agent platform capable of coping with the challenges. The investigated BHS problem is part of a larger research project, DECIDE, applying multi-agent controls in production systems.
Characterization of a Novel Low-Power SRAM Bit-Cell Structure at Deep Sub-Micron CMOS Technology for Multimedia Applications

To meet the increasing demands for higher performance and low-power consumption in present and future Systems-on-Chips (SoCs) require a large amount of on-die/embedded memory. In Deep-Sub-Micron (DSM) technology, it is coming as challenges, e.g., leakage power, performance, data retentation, and stability issues. In this work, we have proposed a novel low-stress SRAM cell, called as IP3 SRAM bit-cell, as an integrated cell. It has a separate write sub-cell and read sub-cell, where the write sub-cell has dual role of data write and data hold. The data read sub-cell is proposed as a pMOS gated ground scheme to further reduce the read power by lowering the gate and subthreshold leakage currents. The drowsy voltage is applied to the cell when the memory is in the standby mode. Further, it utilizes the full-supply body biasing scheme while the memory is in the standby mode, to further reduce the subthreshold leakage current to reduce the overall standby power. To the best of our knowledge, this low-stress memory cell has been proposed for the first time. The proposed IP3 SRAM Cell has a significant write and read power reduction as compared to the conventional 6 T and PP SRAM cells and overall improved read stability and write ability performances. The proposed design is being simulated at VDD = 0.8 V and 0.7 V and an analysis is presented here for 0.8 V to adhere previously reported works. The other design parameters are taken from the CMOS technology available on 45 nm with tOX = 2.4 nm, Vthn = 0.224 V, and Vthp = 0.24 V at T = 27? C.
Attitude of the rural population in Senegal to oral health

Attitude of the rural population in Senegal to oral health Faye Daouda, Kanouté Aïda, Lo Cheikh Moukhamadou Mbacké , Sembène Ndèye Mbogne 1 Associate Lecturer in Public Health, Head of Public Health Department of Dentistry, Faculty of Medicine, Pharmacy and Dentistry, University of Dakar 2 Assistant, Public Health Department of Dentistry, Faculty of Medicine, Pharmacy and Dentistry, University of Dakar
p190-RhoGAP as an integral component of the Tiam1/Rac1-induced downregulation of Rho

Abstract The Rho family of small GTPases plays a central role in intracellular signal transduction, particularly in reorganization of the actin cytoskeleton. Rho activity induces cell contractility, whereas Rac promotes cellular protrusion, which counteracts Rho signaling. In this regard, the reciprocal balance between these GTPases determines cell morphology and migratory behavior. Here we demonstrate that Tiam1/Rac1 signaling is able to antagonize Rho activity directly at the GTPase level in COS-7 cells. p190-RhoGAP plays a central regulatory role in this signaling pathway. Interfering with its activation by Src-kinase-dependent tyrosine phosphorylation or its recruitment to the membrane through interaction with the SH2 domains of p120-RasGAP blocks the Tiam1-mediated rapid downregulation of Rho. This process is mediated by Rac1, but not by Rac2 or Rac3 isoforms. Our data provide evidence for a biochemical pathway of the reciprocal regulation of two related small GTPases, which are key elements in cell migration.
Questioning Hu's Invariants - Bad or Good Enough?

Despite Hu’s invariants were proven not to be independent nor complete long time ago, their use in computer vision applications is still broad, mainly because of their diffusion among common CV libraries and ease of use by inexperienced users. In this paper I want to investigate whether, given their mathematical flaws, they are nevertheless good enough to justify such a wide diffusion, also considering that more sophisticated tools have been developed over the years. In order to do this, I am going to test the robustness of Hu’s invariants in a comparative way against the more modern wavelet invariants, in a hand gesture recognition application. Finally, I am going to discuss, basing my considerations on the experimental data, whether Hu’s invariants are still a viable option for small scale, amateurish applications, or if the time has come to abandon them for more effective solutions.
Development of a fuel-powered compact SMA (Shape Memory Alloy) actuator system

Development of a Fuel-Powered Compact SMA (Shape Memory Alloy) Actuator System. (December 2003) Hyoung Yoll Jun, B.S., Inha University; M.S., Inha University, Inchun, Korea Co-Chairs of Advisory Committee: Dr. Othon K. Rediniotis Dr. Dimitiris C. Lagoudas The work presents investigations into the development of a fuel-powered compact SMA actuator system. For the final SMA actuator, the K-alloy SMA strip (0.9 mm x 2.5 mm), actuated by a forced convection heat transfer mechanism, was embedded in a rectangular channel. In this channel, a rectangular piston, with a slot to accommodate the SMA strip, ran along the strip and was utilized to prevent mixing between the hot and the cold fluid in order to increase the energy density of the system. The fuel, such as propane, was utilized as main energy source in order to achieve high energy and power densities of the SMA actuator system. Numerical analysis was carried out to determine optimal channel geometry and to estimate maximum available force, strain and actuation frequency. Multi-channel combustor/heat exchanger and micro-tube heat exchanger were designed and tested to achieve high heat transfer rate and high compactness. The final SMA actuator system was composed of pumps, valves, bellows, multi-channel combustor/heat exchanger, micro-tube heat exchanger and control unit. The experimental tests of the final system resulted in 250 N force with 2 mm
Semantic Web Mining using RDF Data

Information on the web is increasing every minute. Redundancy in information is growing rapidly. Data mining is the technique used to extract this data as per the user’s query. Technically data mining analyzing and summarizing it into useful information. Keyword search is an important tool for exploring and searching large data corpuses whose structure is either unknown, or constantly changing. So, keyword search has already been studied in the context of relational databases XML documents and more recently over graphs and RDF data. Semantic web mining aims to combine semantic web and web mining. Semantic web mining is the need of today’s redundant data. In this paper major focus is on minimizing extraction of number of pages by ranking technique. Due to which the extraction of information is done exact as query fired and the top ranked pages are shown to user. Here for this three main areas are going to use such as semantic web, ontology and RDF data.
State‐Based Prognostics with State Duration Information

Failure prediction (i.e. prognostics) is critical for effective maintenance because it greatly impacts the competitiveness of organizations through its direct connection with operating and support costs, system availability, and operational safety. In recent years, research has focused on state‐based prognostics that forecast future progression by first identifying the current state. The duration spent in a state is a factor that influences the expected time to be spent in that state in the future; however, previous works on state‐based prognostics have ignored the effect of duration. Hidden Markov Models are the most famous state‐based prognostics methods in the literature with practicality problems such as computational complexity, requirement of excessive data, and dependency on initialization. This paper presents a new, simple and easy to implement state‐based prognostic method using state duration information. The presented method is applied to two real systems (railway turnout systems and drill bits), and the results are compared with the existing methods presented in the literature. The results show that the presented method outperforms the existing methods. Copyright © 2012 John Wiley & Sons, Ltd.