Miracle-dz/UniFAR-FTUs huggingface dataset:
Feature Selection of Sudden Failure Based on Affinity Propagation Clustering

When diagnosing sudden mechanical failure, in order to make the result of classification more accurate, in this article we describe an affinity propagation clustering algorithm for feature selection of sudden machinery failure diagnosis. General methods of feature selection select features by reducing dimension of the features, at the same time changing the data in the feature space, which would result in incorrect answer to the diagnosis. While affinity propagation method is based on measuring similarity between features whereby redundancy therein is removed, and selecting the exemplar subset of features, while doesn't change the data in the feature space. After testing on clustering and taking the result of PCA and affinity propagation clustering as input of a same SVM classifier, we get the conclusion that the latter has lower error than the former.
On development of supporting tool for Folksonomy Mining based on Formal Concept Analysis

Folksonomy is a user-generated taxonomy to organize information by which a user assigns tags to resources published on the web. Triadic datas that indicate relations of between users, tags, and resources, are created by collaborative tagging from many users in folksonomy-based system. Such the folksonomy data has been utilized in the field of the semantic web and web2.0 as metadata about web resources. In this paper, we propose FCA-based folksonomy data mining approach in order to extract the useful information from folksonomy data with various points of view. And we developed tool for supporting our approach. In order to verify the usefulness of our proposed approach and FMT, we have done some experiments for data of del.icio. us, which is a popular folksonomy-based bookmarking system. And we report about result of our experiments.
Integrated approach for fault tolerance and digital signature in RSA

Data security and fault tolerance are two important issues in modern communications. In most cases, they are studied and implemented separately. The author proposes an integrated approach for both fault tolerance and digital signature in the RSA implementation. It shares the same computations required by the Hash function, which is the major part of the digital signature and error detections and corrections. Therefore the total overheads are minimised. The proposed approach is able to detect and correct up to three errors occurring in the computation processes, including encryption, decryption and Hash function evaluation in the data transmission process. The principle of the proposed approach may also be used for other public key cryptography schemes.
The hybrid feature selection k-means method for Arabic webpage classification

The high-dimensional data features found in the enormous amount of Arabic text available on the Internet is an important research problem in Web information retrieval. It reduces the accuracy of the clustering algorithms and maximizes the processing time. Selecting the relevant features is the best solution. Therefore, in this paper, we propose a feature selection model that incorporates three different feature selection methods (CHI-squared, mutual information, and term frequency-inverse document frequency) to build a hybrid feature selection model (Hybrid-FS) for k -means clustering. This model represents text data in a high structure (consisting of three types of objects, namely, the terms, documents and categories). We evaluate the model on a set of common Arabic online newspapers. We assess the effect of using the Hybrid-FS with standard k -means clustering. The experimental results show that the proposed method increases purity by 28% and lowers the runtime by 80% compared to the standard k -means algorithm. We conclude that the proposed hybrid feature selection model enhances the accuracy of the k -means algorithm and successfully produces coherent-compact clusters that are well-separated when applied to high-dimensional datasets.
Spatiotemporal analysis of meteorological drought variability in the Indian region using standardized precipitation index

Grid (1° latitude × 1° longitude) level daily rainfall data over India from June to September for the years 1951–2007, generated by the India Meteorological Department, were analysed to build monthly time series of Standardized Precipitation Index (SPI). Analysis of SPI was done to study the spatial and temporal patterns of drought occurrence in the country. Geographic spread of SPI‐derived Area under Dryness (AUD) in different years revealed the uniqueness of the 2002 drought, with widespread dryness in July. Mann–Kendall trend analysis and moving average based trends performed on the AUD indicated an increasing trend in July. The area under moderate drought frequency has increased in the most recent decade. Ranking of years based on Drought Persistency Score (DPS) indicated that 1987 was the most severe drought year in the country. The results of the study have revealed various aspects of drought climatology in India. A similar analysis with the SPI of finer spatial resolution and relating it to crop production would be useful in quantifying the impact of drought in economic terms. Copyright © 2011 Royal Meteorological Society
Initially Cognitive Computation with Self-Organization Strategy for Securely Humanized Human-Machine Interactions

This brief paper addresses the issue of human machine interaction with consideration of security and humanization both. Initially Cognitive Computation (ICC) has been proposed and described with an illustration combining with a surveillance ICC framework with its application scene and process. Considering its diversity of devices and application involved with cloud computing with sophisticated configuration for networking in pervasive computational networked system, we further consider the autonomy and security of the systematic materialization that is in need of flexible configuration and proposed a self-organization strategy with security authentication in duration of trustworthy connection establishment. keywords: human-machine interactions, initially cognitive computation, humanization, security, self-organization, cloud
Constructing a Depth Map from Images

Abstract : This paper describes two methods for constructing a depth map from images. Each Method has two stages. First, one or more needle maps are determined using a pair of images. This process employs either the Marr-Poggio-Grimson stereo and shape from shading, or, instead, photometric stereo. Secondly, a depth map is constructed from the needle map or needle maps computed by the first stage. Both methods make use of an iterative relaxation method to obtain the final depth map. (Author)
Getting Chipped: To Ban or Not to Ban

Abstract Human Radio Frequency Identification (RFID) implants are currently being marketed as a way to limit access to secure areas or as anti-kidnapping devices, as well as means to track and quickly identify in emergency situations individuals with serious medical conditions or mental disabilities or to serve as cashless payment devices with a wave of the hand. While in certain instances, such as in some medical applications, this technology can have positive and benign effects there are also serious privacy implications. Although at present, technological and financial challenges prevent the wide take-up of these highly controversial devices, privacy advocates fear the technology might be abused by governments and big corporations and used to constantly locate and profile people. A detailed critique of the complex privacy, security, ethical and health implications in the light of this emerging technology is still lacking and this article attempts to contribute to this process.
Deprecating the Observer Pattern with Scala.React

Programming interactive systems by means of the observer pattern is hard and error-prone yet is still the implementation standard in many production environments. We show how to integrate different reactive programming abstractions into a single framework that help migrate from observer-based event handling logic to more declarative implementations. Our central API layer embeds an extensible higher-order data-flow DSL into our host language. This embedding is enabled by a continuation passing style transformation.
Robust and Accurate Multiple-Camera Pose Estimation toward Robotic Applications

Pose estimation methods in robotics applications frequently suffer from inaccuracy due to a lack of correspondence and real-time constraints, and instability from a wide range of viewpoints, etc. In this paper, we present a novel approach for estimating the poses of all the cameras in a multi-camera system in which each camera is placed rigidly using only a few coplanar points simultaneously. Instead of solving the orientation and translation for the multi-camera system from the overlapping point correspondences among all the cameras directly, we employ homography, which can map image points with 3D coplanar-referenced points. In our method, we first establish the corresponding relations between each camera by their Euclidean geometries and optimize the homographies of the cameras; then, we solve the orientation and translation for the optimal homographies. The results from simulations and real case experiments show that our approach is accurate and robust for implementation in robotics applications. Finally, a practical implementation in a ping-pong robot is described in order to confirm the validity of our approach.
Access Control Based on a Distributed Fingerprint Recognition System

This paper presents an implemented solution for controlling the access of the users to restricted areas and resources (including machines and robots), based on fingerprint recognition. The proposed distributed system is composed of a number of fingerprint scanning mobile terminals connected to a server net (one or more server instances used for identity confirmation). The proposed server architectures itself was designed to be loosely coupled in order to be able to achieve a highly scalable system.
Multi-hop Routing Protocol based on Neighbor Conditions in Multichannel Ad-hoc Cognitive Radio Networks

During the routing process between nodes on the CR(Cognitive Radio) network conducting for efficient use of limited frequency resources, spectrum handover process due to the appearance of the PU occupies most of the routing latency, and also decreases the reliability of the path. In this paper, a cooperative routing protocol in a multi-channel environment is proposed. The source node broadcasts a message with available channel lists and probability of PU appearance during its route guidance. The intermediate nodes re-transmit the message, received from the source node, and update and maintain the information, status table of the path. The destination node determines the optimal path and sends a reply message to the selected path after it receives the messages from the intermediate nodes. The average probability of the PU appearance and the average time of the PU appearance are updated while transferring data. During data transmission the channel with the lowest probability of appearance of the PU is selected dynamically and if a PU appears on the current channel partial repairment is performed. It is examined that reliability of the selected path considerably is improved and the routing cost is reduced significantly compared to traditional routing methods.
Superscalar Huffman decoder hardware design

Huffman coding is one of the most common forms of lossless data compression. Many lossy image compression standards, for example the MPEG and JPEG, use Huffman coding as the back end entropy compressor because of its relatively good compression performance and simple hardware implementation. However, the decoding speed is limited by a feedback loop. For applications that require high speed decoding, such as High Definition Television at about 100 Mbyte/s, this feedback loop can be prohibitively slow. The highest speed conventional `parallel' Huffman decoders decode one complete codeword per look-up table memory cycle. This paper describes three different hardware designs that break through this limit. All three depend on probabilistic modeling of the coded data stream to predict, or speculate, on the values of adjacent codewords. One design uses a single fully specified memory with enough width for two, or more, output tokens. The other two designs use multiple memories each fed by a different portion of the code stream. This superscalar approach leads to average decode rates twice, or more, that of a conventional `parallel' decoder for a simulation of JPEG Huffman token data. The relative performance versus hardware cost is described for each design.
A portable digital DLL for high-speed CMOS interface circuits

A digital delay-locked loop (DLL) that achieves infinite phase range and 40-ps worst case phase resolution at 400 MHz was developed in a 3.3-V, 0.4-/spl mu/m standard CMOS process. The DLL uses dual delay lines with an end-of-cycle detector, phase blenders, and duty cycle correcting multiplexers. This more easily process portable DLL achieves jitter performance comparable to a more complex analog DLL when placed into identical high-speed interface circuits fabricated on the same test-chip die. At 400 MHz, the digital DLL provides <250 ps peak-to-peak long-term jitter at 3.3 V and operates down to 1.7 V, where it dissipates 60 mW. The DLL occupies 0.96 mm/sup 2/.
Seamless Routing and Cooperative Localization of Multiple Mobile Robots for Search and Rescue Application

In particular, for a practical mobile robot team to perform such a task as that of carrying out a search and rescue mission in a disaster area, the network connectivity and localization have to be guaranteed even in an environment where the network infrastructure is destroyed or a Global Positioning System is unavailable. This paper proposes the new collective intelligence network management architecture of multiple mobile robots supporting seamless network connectivity and cooperative localization. The proposed architecture includes a resource manager that makes the robots move around and not disconnect from the network link by considering the strength of the network signal and link quality. The location manager in the architecture supports localizing robots seamlessly by finding the relative locations of the robots as they move from a global outdoor environment to a local indoor position. The proposed schemes assuring network connectivity and localization were validated through numerical simulations and applied to a search and rescue robot team.
Direct Phase Detection Utilizing Phase Contrast Imaging

A mathematical approach to describe phase contrast imaging is presented by means of Taylor expansion. The contrast of image of phase object is discussed by changing the absorption and phase-retarding of spatial filters at Fourier plane. A new filtering method is proposed to enhance the image contrast. Based on this approach, a phase-to-intensity image of phase object with higher contrast is got at its imaging plane. Through the image the phase can be detected directly without interferogram processes or phase unwrapping. From the mathematical approach, simulation in MATLAB programming is executed to prove the feasibility of small phase detection. The quick detection of phase may be used for applications such as studying living cells, high throughput microscopy or automated microscopy.
Image following using the feature-based optical flow approach

Visual servo can be achieved by extracting motion information from the optical flow, defined as the apparent motion of brightness patterns of an image. Since the optical-flow-based approach does not require knowledge of targets in advance, it is suitable for versatile tracking and positioning purposes. For most robotic tasks, steady position of the end-effector with respect to its working environment is essential to successful and efficient operations. In this paper, application of the optical flow technique to following of a moving image is presented. In addition, more accurate values of the optical flow are usually observed along image features. In order to achieve better estimation of the optical flow, feature-based optical flow computation approaches are also proposed. Image following tasks are demonstrated by 3D tracking experiments driven by stepping motors.
Robotic analyses of output force distribution developed by human limbs

We propose an introduction of a muscle coordinate system consisting of the bi-articular muscles as well as the mono-articular muscles instead of a conventional joint coordinate system consisting of only the mono-articular muscles without the bi-articular muscles to discuss an interface between man and machine. The output force distribution developed at the wrist joint of the human arm under isometric and maximal effort conditions demonstrates a hexagonal shape. Since complex muscle arrangements of the human arm could be simplified into one antagonistic pair of the bi-articular muscles and two antagonistic pairs of the mono-articular muscles (functionally effective muscular strengths), a robot arm provided with three pairs of muscles was built. The robot arm operated with the muscle coordinate system demonstrated hexagonal shape output force distributions. Whereas, the robot arm operated with the joint coordinate system showed quadrangular output force distributions. A characteristic of the hexagonal force distribution made it possible to evaluate individual functionally effective muscular strengths from the human arm output force distribution. The results obtained here will lead a new virtual human model to be more realistic than the conventional model operated with the joint coordinate system. The idea will also be useful for a human-friendly robot.
Controlled Purification of Single-Walled Carbon Nanotube Films by Use of Selective Oxidation and Near-IR Spectroscopy

Electric-arc produced as-prepared single-walled carbon nanotube (AP-SWNT) films have been purified by a selective oxidation process. The purification is monitored by near-infrared (NIR) spectroscopy, which gives a quantitative estimate of relative purities. This technique also gives an estimate of the change in relative amounts of SWNTs and amorphous carbon impurities after each purification step, thereby providing accurate and selective control over the oxidation process. Oxidation was carried out by reaction in flowing oxygen at different temperatures and for different durations of time; the purity was evaluated after each oxidation step and compared to the starting as-prepared film. The purities and amounts of SWNTs and carbonaceous impurities were monitored as a function of oxidation temperature and time. Optimization of the process allowed a 3-fold improvement in the AP-SWNT purity with almost quantitative retention of the SWNT portion of the sample. A purification efficiency is defined, which is exp.
CONVERGÊNCIA E DIVERGÊNCIA NOS NÍVEIS DE RENDA PER CAPITA: UMA CRÍTICA À APLICABILIDADE DOS MODELOS NEOCLÁSSICOS DE CRESCIMENTO ECONÔMICO

O artigo pretende analisar em que medida os modelos neoclassicos de crescimento economico  mais especificamente, o modelo de Solow (1956, 1957), o modelo de Mankiw, Romer e Weill (1992) e o modelo de Romer (1990)  sao capazes de explicar a divergencia global nos niveis de renda per capita nos ultimos dois seculos e a convergencia nos niveis de renda per capita e o catch-up ocorridos entre Europa e Estados Unidos no periodo do Pos Segunda Guerra Mundial. Com efeito, trata-se de uma confrontacao entre teoria e pratica, de modo a analisar de que forma tais modelos explicam (ou nao) os fatos supramencionados. No trabalho, demonstra-se que a ocorrencia dos fatos anteriormente mencionados deveu-se fundamentalmente as diferencas do progresso tecnico existente entre as economias (no caso da divergencia) e a reducao de tais disparidades entre os Estados Unidos e a Europa no periodo de tempo imediatamente apos a 2.a Guerra Mundial (no caso da convergencia e do catch-up). Na verdade, tenta-se demonstrar que os modelos apresentados nao conseguem explicar satisfatoriamente os fatos ocorridos, sendo validos apenas em casos especificos. O que o artigo se propoe a expor e que a realidade do crescimento economico mundial e bastante diferente das conclusoes dos modelos neoclassicos considerados. Abstract This work intends to analyze in which way the neoclassical growth models  more specifically, Solow (1956, 1957), Mankiw, Romer and Weill (1992) and Romer (1990)  are capable to explain the global divergence on the levels of per capita income over the last two centuries and the convergence on the levels of per capita income and the catch-up occurred between Europe and the United States after World War II. In fact, it is a confrontation between theory and practice, in order to view in which way these models explain (or not) the above-mentioned facts. During the present work, we demonstrate that the occurrence of these facts were mainly caused by differences on technological progress between economies (case of divergence) and the reduction of such disparities between the United States and Europe on the period of time immediately after World War II (case of convergence and catch-up). In fact, we try to demonstrate that these models are incapable to give a satisfactory explanation to the occurred facts, being only valid on specific cases. The work tries to propose that the reality of global economic growth differs considerably from the conclusions of the considered neoclassical growth models.
Rex Programmer's Manual

Abstract : This manual describes Rex, a programming language for specifying machines by dedara tively describing their behavior. The Rex language consists of a set of LISP functions that define primitive Rex machines and provides methods for building complex machines out of simpler components. A Rex machine is a synchronous abstract device that has inputs, local state, and outputs, all of which are storage locations. Storage locations may be thought of as wires that can be set to certain values and whose values can be read by Rex machines. The value of a storage location is determined by its constraint, some function of the values of a set (possibly empty) of storage locations. A Rex machine operates by repeatedly computing a mapping from its inputs and current state into its outputs and next state. By hierarchically dividing a large state into small components and specifying their state transitions, we can "make the combinatorial explosion work for us" [3]. The size of the smallest component may vary from implementation to implementation; it could be a bit, an integer, or a small enumerated type. The state transitions are described by functions that map tuples of elements of the primitive data types into other tuples. The new value of any given component could, in principle, depend on all of the inputs and the entire current state of the machine, but, in practices, the dependencies are usually local.
Study on the Trajectory Planning of Hybrid-Driven Planar 3-RRR Mechanism

Hybrid-driven mechanism synthesis the constant speed motor and the servo motor as the power source through a multi degree of freedom mechanism. The text study on the trajectory planning of hybrid-driven planar 3-RRR mechanism. Firstly, based on compatible link combinations, all possible basic configurations of planar 3-dof kinematics chains were derived. Based on the requirements of hybrid-driven mode, the kinematics chains were selected one by one Planar 3-RRR mechanism was determined to be the research object finally. Then, based on the conclusions of inverse kinematics analysis, using the cubic spline function on point to point path planning, the servo motor rotation laws were presented. Comparing the different speed situation of constant motor, the influence trends on planning results were analyzed.