Miracle-dz/UniFAR-FTUs huggingface dataset:
A New Positioning Scheme Exploiting RSS Difference of Arrival in Indoor Environments

Three basic properties of radio signal, such as received signal strength (RSS), time of flight, and angle of arrival, are commonly used in estimation of distance for positioning of a target. Among them, the positioning technique based on RSS attracts much more interests of researchers due to its high feasibility in realization. However, the performance of the conventional positioning scheme based on RSS is significantly degraded than that of TOA or fingerprinting scheme because of error components from multipath and shadowing effects. In this paper, the RSS-based positioning scheme, which defines RSS difference of arrival (RDOA) likewise time difference of arrival (TDOA) to mitigate error components, is proposed and its performance of position estimation is experimentally analyzed in indoor environments. The performance of the proposed RDOA scheme is compared with that of conventional scheme likewise TOA scheme with respect to the fixed AP selection case, the base AP changing case, and the adaptive AP selection case, respectively. According to the experiment results, it is shown that a high accuracy in position estimation also can be achieved with the RDOA scheme compared to the conventional scheme likewise TOA, while the RDOA scheme can provide less standard deviation than the conventional scheme.
Evaluating Eucalyptus Virtual Machine Instance Types: a Study Considering Distinct Workload Demand

Cloud computing paradigm provides virtualized computing resources as a service on demand. This paradigm allows companies focus on their business issues rather than conceiving and managing complex infrastructures. As a consequence, performance evaluation of cloud computing infrastructures has been receiving considerable attention by service providers as a prominent activity for improving service quality infrastructure planning, and selection of software platforms (e.g., Eucalyptus). This paper presents the performance evaluation of virtual machines on Eucalyptus platform considering different workloads. This study provides insights about Eucalyptus system infrastructure suitability for applications with high processing and storage performance requirements. This work provided the evaluation of virtual machine instances types from a private cloud, which was configured with Eucalyptus platform. Keywords-cloud computing; eucalyptus platform; performance evaluation.
Investigation and application of ant colony clustering algorithms

Clustering is widely used in some fields as a part of important data mining.Ant colony algorithms are novel algorithms in re-cently years.These methods have several virtues such as distributed parallel computing,positive feedback mechanism and combination with certain heuristics.Some kinds of basic and popular ant colony clustering algorithms are introduced,the differences of them are analyzed and the direction for study of ant colony algorithms based on application and improving modality in clustering.
Automatic design of algorithms for the traveling salesman problem

Abstract The automatic generation of procedures for combinatorial optimization problems is emerging as a new alternative to address the hardest problems of this class. One of these problems still offering great computational difficulty is the traveling salesman problem. Its simple presentation masks the great difficulty that exists when solving it numerically. The results obtained so far for this problem are based on the hybridization of known heuristics. However, there is still a need for an experimental breakthrough in the study of all of the possible combinations of heuristics, which represents a huge search space. In this paper, we explore this space using evolutionary computing to automatically design new algorithms for the problem. We carried out a computational experiment to produce the algorithms that not only are competitive with some of the existing heuristics but that also contain several novel structures that directly influence performance.
Cognitive Human Emotion Detection withVocal Output

Face recognition process pertains to recognizing meaningful expressions of emotion by a human, involving angry, happy, fear, sad, disgust and anger. It is of utmost importance in designing an intelligent and efficient human computer interface. The face is a rich source of information about human behaviour. The proposed method will recognize the facial expression from a well captured image. The approach for Facial Expression Recognition System is based on Neural Network. For any Facial Expression Recognition, it is necessary to extract the features of face that can be possibly used to detect the expression. For Feature Extraction the Support Vector Machines will be used. After extracting the features the eigenvectors will be generated. This will be further fed into the Neural Network for Emotion Recognition. The paper briefly describes the schemes for selecting the image and then processing the image to recognize the expressions.
An Improved Short Text Classification Algorithm Based on Bayesian Network

Due to the fact that inadequate features of short text makes unsatisfactory classification,an improved algorithm for text classification based on Bayesian network is presented.The improvement lies in the steps of Bayesian network structure learning phase for finding parent node.The algorithm takes into account the connection strength of the factors,thus,a decrease of interference errors between two nodes that are unrelated to the father and son nodes is achieved.It enables each node to find more accurate father node,and improves the classification accuracy of text.
The optical design of intraocular lens implants.

Abstract Intraocular lens implants have been around for more than 25 years. On the verge of a major breakthrough to ever widening popularity, there is, however, a general lack of understanding of the pertinent optical principles. A critical comparison is made between this new method and conventional methods of correcting aphakia. From this it appears that the visual needs of the patient are a decisive factor in the selection of the method of correction. Moreover, the full potential of intraocular lens implants can only be realized by appropriate selection of the power of the implant in each situation. To this end, ultrasonic measurement of the ocular axial length is indispensable. The use of standard power lens implants is inadequate. Formulas are presented to make an eye emmetropic or to give it any refractive error. Guidelines are given for the use of these formulas. Two methods for obtaining equal image size in unilateral antiphakia are described.
polySegratioMM: An R library for Bayesian mixture models for marker dosage in autopolyploids

It is well known that the dosage level of markers in autopolyploids and allopolyploids can be characterised by their observed segregation ratios. The related package polySegratio provides functions to allocate dosage by standard approaches and to simulate marker data sets for differing ploidies and levels of overdispersion. Note that these methods could equally well be applied to allopolyploids with specified expected segregation ratios. For details see polySegratio. A Bayesian approach was proposed by Baker et al. (2010) where marker dosage estimation was obtained by fitting a finite mixture distribution. This library calls the JAGS software for Bayesian calculation. JAGS 1.0 or higher must be installed following instructions from http://www-fis.iarc. fr/ ~martyn/software/jags/. The JAGS executable must be in your path. Currently, no checking is carried out to ascertain whether or not JAGS is set up appropriately. To use the library, you need to attach it with
Study on key technologies of intelligent Gobang playgame

Based on studying and discussing the key technologies of intelligent Gobang playgame,such as the methods of the game state data structure of Gobang,the design of evaluation function,selecting of search depth,usage of background time and the using methods of opening book and endgame database,the archetype system of intelligent Gobang was developed by Visual C+ +6.0 in Windows XP,which included that the game state data structure of Gobang was showed by three-D array,that the state was evaluated by weighted estimating method,that α-β lopping search was used as basis searching algorithms and hewristic rule was used to select search depth.The implementation and result discussion indicate that compared with the other Gobang programs,the speed of our program is increased by reducing the searching space.
Formal Verification Methods

On June 1, 2009, Air France Flight 447 from Rio de Janeiro to Paris crashed into the Atlantic Ocean, killing all 216 passengers and 12 crew members. Prior to the disappearance of the A330 aircraft, the automatic reporting system sent messages indicating disagreement in the airspeed readings, which led investigators to believe that the pilot probe sensors did not “accurately” measure airspeed and the autopilot may have automatically disengaged. Like the above probes, many systems are increasingly being used in safety-critical domains, such as medicine, transportation systems, chemical plants, etc. There is hence a dire need to ensure the accuracy of such systems as a system bug, or error, may endanger human life or lead to a significant financial loss. In order to ensure error-free systems, the system design process is usually accompanied by a rigorous system analysis to check if the designed system would exhibit the desired behavior. The core of system analysis is based on mathematics and the fundamental idea is to create a mathematical model of the system and then use logical or mathematical reasoning to verify that the desired properties hold for this model. Traditionally, system analysis is done by paper-and-pencil proof methods. However, considering the complexity of present age systems, such kind of analysis is notoriously difficult, if not impossible, and is quite error prone due to the human error factor. Moreover, it is quite often the case that mathematicians forget to pen down all the assumptions that are required for the validity of their analysis. This fact may also result in designing erroneous systems. With the advent of computers, many computer based software tools based on the principle of testing or simulation have been introduced for system verification. Due to the reliable and efficient bookkeeping characteristic of computers, large systems can be analyzed and thus one of the limitations of paper-and-pencil proof methods can be overcome. However, the main problem with such kind of analysis is its completeness as the system is checked only for a subset of possible inputs since exhaustive testing is not possible for any system with a significant number of inputs due to the exponential growth of the test patterns. In Dijkstra’s words “Program testing can be a very effective way to show the presence of bugs, but it is hopelessly inadequate for showing their absence. ” Moreover, testing or simulation cannot be used to precisely verify properties about continuous systems due to the usage of computer arithmetic, like floating-point or fixed-point representations of real numbers. The above mentioned inaccuracy limitations of commonly used system analysis techniques can be held responsible for many unfortunate incidents that happened due to an erroneous system deployed in a safety-critical domain For example, the Therac-25 software bug and the Intel Pentium’s floating-point division unit error).
Title Synchronous, DS-CDMA/FDMA PHY Proposal for IEEE 802.16.3 Date Submitted

This document outlines a PHY proposal for IEEE 802.16. 3 using a combined synchronous DS- CDMA (S-CDMA) and FDMA scheme. The proposed PHY features adaptive QAM modulation, high-rate trellis and/or turbo coding, linear equalization along with power and timing control. Purpose To provide a description of a proposed physical layer specification for consideration by the IEEE 802.16. 3 Task Group. Notice This document has been prepared to assist IEEE 802.16. It is offered as a basis for discussion and is not binding on the contributing individual(s) or organization(s). The material in this document is subject to change in form and content after further study. The contributor(s) reserve(s) the right to add, amend or withdraw material contained herein. Release The contributor grants a free, irrevocable license to the IEEE to incorporate text contained in this contribution, and any modifications thereof, in the creation of an IEEE Standards publication; to copyright in the IEEE's name any IEEE Standards publication even though it may include portions of this contribution; and at the IEEE's sole discretion to permit others to reproduce in whole or in part the resulting IEEE Standards publication. The contributor also acknowledges and accepts that this contribution may be made public by IEEE 802.16.
Tecnología e informática musical: Unidad didáctica para abordar las competencias digitales

La relacion entre la musica y las TIC ha estado ligada a los medios existentes en cada epoca para organizar el sonido de un modo aceptable esteticamente. A la hora de planificar los objetivos curriculares de la materia, se deben combinar las competencias propias del area de musica con las digitales. Pero, ? que conocimientos tecnologicos poseen alumnado y profesorado? Necesitamos ampliar nuestra formacion?
Formal Verication of a Framework for Microkernel Programmers

This thesis presents the formal verification of a framework for microkernel programmers called CVM (communicating virtual machines) [41]. CVM is a computational model for concurrent user processes interacting with a generic microkernel and devices. It is implemented in C0A, a restricted C-dialect with support of inline assembly, as a framework featuring virtual memory, demand paging, memory management, and low-level inter-process and devices communications. The framework can be linked on the source code level with an abstract kernel, an interface to users, in order to obtain a concrete kernel, a program that can be translated and run on a target machine. We use a formally verified microprocessor VAMP [20] as a platform to run the concrete kernel. The main result of this work is a mechanically checked formal proof that concurrent executions of user processes interacting with a kernel are simulated by executions of the VAMP instruction set architecture model interleaved with devices. In order to obtain this result a number of attendant formal theories have been developed, most notably, a theory of inline assembly verification. This work is a part of the Verisoft project [111], a large scale effort bringing together industrial and academic partners to push the state-of-the-art in formal verification for realistic computer systems comprising hardand software.
Implementation of PCA for Recognition of Hand Gesture Representing Alphabets

Establishment of communication between two peers plays a crucial role in knowledge exchange. It can be done either using linguistic features or gestures. The development of procedure for realizing gestures into meaningful information plays a pivotal role in instances where linguistic feature cannot be used. In such situations gestures can be used as the alternative for conveying the same. This paper basically aims at discussing implementation of Principal Component Analysis (PCA) for recognizing hand gesture that represents alphabets. PCA is a useful statistical technique that has found application in field such as image recognition, dimension reduction. It identifies pattern by reducing the dimension of data with minimum loss of information.
Evaluating Innovative Measures in University Mathematics – The Case of Affective Outcomes in a Lecture focused on Problem-Solving

The transition from high school to university mathematics has proven to be difficult for many students but especially for pre-service secondary teachers. To support these students at mastering this transition, various universities have introduced support measures of various kinds. The WiGeMath project developed a taxonomy that makes it possible to describe and compare these measures concerning their goals as well as their frame characteristics. We will exemplify the use of the taxonomy in the description of one specific innovative measure that was part of the WiGeMath evaluations. Moreover, we will present first results concerning the goal-fulfilment of this measure concerning affective characteristics of the student cohort and their predominant beliefs.
A Best Clustering Scheme Based on Simulated Annealing Algorithm in Wireless Sensor Networks

Through the thorough study of existing clustering algorithms,with the problem of typical combinatorial optimization and the idea of simulated annealing algorithm,a best clustering scheme of the wireless sensor network was proposed based on simulated annealing algorithm.The assembled cluster head nodes were assembied and Abstracted to a referenced model,objective cluster head collection was obtained through certain perturbation factors from continuous iteration.The idea of simulated annealing algorithm was used to the choosing process of the best number of clusters.This paper introduces the realization of the whole process in detail.The best number of clusters,persistent time,iterative times are studied and analyzed through established mathematics model and simulated experiments.
A Method for Estimating User’s Preference about Shopping Items Based on User’s Behaviors on Smartphone

Nowadays, with the wide spread of smart phone, many users turn to use their smart phones frequently on online shopping instead of immovable devices such as desktop PCs. For providing high quality service, the user’s evaluations on shopping items are useful for recommendation and search of items that the user would prefer to. However, it is not easy to obtain user’s manual evaluations on items. It is not convenient for user to make evaluations manually on each item. In this paper, we propose a simple and effective idea to estimate user’s preference on online shopping items that the user has already browsed without manual evaluation, based on the user’s browsing behaviors. This is performed under the hypothesis that the user’s preference of browsed items is reflected by the operation behavior on the smart phone. This hypothesis is verified by experiment, using our original application. The experimental results show the correlation between browsing behaviors and evaluation of product items by using statistical analysis. In addition, by using machinelearning techniques, the results show that the user’s preference of browsed item can be estimated effectively based on the user’s browsing behaviors.
Designing a Methodology for Semantic Type Tagging of Argument Positions

A verb argument position can be described by the semantic type that characterizes the words ﬁlling that position. We investigate a number of linguistic issues underlying the tagging of an Italian corpus with the semantic types provided by the T-PAS (Typed Predicate-Argument Structure) resource. Our main interest is to evaluate whether our annotation methodology can be employed effectively for the extension of the annotation of the corpus associated with the resource. In order to achieve this goal we compare quantitative data about the tagging and qualitative data derived from the Inter-Annotator Agreement.
Dynamic Tensor Product Regression

In this work, we initiate the study of \emph{Dynamic Tensor Product Regression}. One has matrices $A_1\in \mathbb{R}^{n_1\times d_1},\ldots,A_q\in \mathbb{R}^{n_q\times d_q}$ and a label vector $b\in \mathbb{R}^{n_1\ldots n_q}$, and the goal is to solve the regression problem with the design matrix $A$ being the tensor product of the matrices $A_1, A_2, \dots, A_q$ i.e. $\min_{x\in \mathbb{R}^{d_1\ldots d_q}}~\|(A_1\otimes \ldots\otimes A_q)x-b\|_2$. At each time step, one matrix $A_i$ receives a sparse change, and the goal is to maintain a sketch of the tensor product $A_1\otimes\ldots \otimes A_q$ so that the regression solution can be updated quickly. Recomputing the solution from scratch for each round is very slow and so it is important to develop algorithms which can quickly update the solution with the new design matrix. Our main result is a dynamic tree data structure where any update to a single matrix can be propagated quickly throughout the tree. We show that our data structure can be used to solve dynamic versions of not only Tensor Product Regression, but also Tensor Product Spline regression (which is a generalization of ridge regression) and for maintaining Low Rank Approximations for the tensor product.
Single-View Semantic Mesh Refinement

While 3D reconstruction is a well-established and widely explored research topic, semantic 3D reconstruction has only recently witnessed an increasing share of attention from the Computer Vision community. Semantic annotations allow in fact to enforce strong class-dependent priors, as planarity for ground and walls, which can be exploited to refine the reconstruction often resulting in non-trivial performance improvements. State-of-the art methods propose volumetric approaches to fuse RGB image data with semantic labels; even if successful, they do not scale well and fail to output high resolution meshes. In this paper we propose a novel method to refine both the geometry and the semantic labeling of a given mesh. We refine the mesh geometry by applying a variational method that optimizes a composite energy made of a state-of-the-art pairwise photo-metric term and a single-view term that models the semantic consistency between the labels of the 3D mesh and those of the segmented images. We also update the semantic labeling through a novel Markov Random Field (MRF) formulation that, together with the classical data and smoothness terms, takes into account class-specific priors estimated directly from the annotated mesh. This is in contrast to state-ofthe-art methods that are typically based on handcrafted or learned priors. We are the first, jointly with the very recent and seminal work of [3], to propose the use of semantics inside a mesh refinement framework. Differently from [3], which adopts a more classical pairwise comparison to estimate the flow of the mesh, we apply a single-view comparison between the semantically annotated image and the current 3D mesh labels; this improves the robustness in case of noisy segmentations.
Critical Path Analysis for Structure Optimization of Workflow

To meet the requirement of evaluation and optimization of the workflow model, an extended critical path method was proposed to support two extra structures (optional, loop) that traditional critical path methods do not considered. This method converts the workflow control blocks in the form of tree and establishes their corresponding reduction rules. A weighted critical path algorithm was provided to calculate the expectation value of the workflow's duration, record the process of reduction, and identify the time-oriented critical path. As a result, the critical activities and their distribution of time are included in the path, which is a good preparation for the further optimization of workflow.
An adaptive video-watermarking detection algorithm

An adaptive video watermarking detection algorithm in the spatial domain is proposed. The side information obtained in the process of video decoding is utilized for calculating the confidence factor of each pixel in the reconstructed images, according to the loss of watermark information. For the same embedding method of video watermarking, this improved algorithm can further increase the precision of watermarking detection compared to the traditional algorithm.