Miracle-dz/UniFAR-FTUs huggingface dataset:
Research on Image Feature Extraction Method Based on Orthogonal Projection Transformation of Multi-Task Learning Technology

When the number of labeled training samples is very small, the sample information we can use would be very little. Because of this, the recognition rates of some traditional image recognition methods are not satisfactory. In order to use some related information that always exist in other databases, which is helpful to feature extraction and can improve the recognition rates, we apply multi-task learning to feature extraction of images. Our researches are based on transferring the projection transformation. Our experiments results on the public AR, FERET and CAS-PEAL databases demonstrate that the proposed approaches are more effective than the general related feature extraction methods in classification performance.
Dynamic-threshold CMOS SRAM cells for fast, portable applications

A novel quad-rail CMOS SRAM cell architecture that doubles cell read current, improves cell static noise margin (SNM) by 70%, increases cell immunity to SER and lowers cell standby power by over an order of magnitude is proposed. These improvements are achieved by implementing a scheme of WL transition triggered pulses on source and substrate terminals of cell inverter transistors that share a common WL.
Training MLPs via the expectation maximization algorithm

Two factors that inhibit the use of multi layer perceptrons (MLP) by the pattern recognition and statistical modelling community are the long training times and a poorly developed theory of network internals. The paper proposes a solution to these problems by introducing a framework in which the hidden nodes of a multi layer perceptron are models of a binary stochastic process governed by the Bernoulli probability density function. Within this framework, we present an expectation maximisation (EM) algorithm for training the network. The algorithm iteratively finds the most probable internal representation given the network inputs and desired outputs. The internal representation forms target values for the hidden nodes so that the desired output of all nodes in the network is specified. This removes the necessity of using back propagation of errors to modify hidden layer weights, and effectively decomposes the MLP into two single layer perceptrons, the parameters of which can be efficiently optimised. We demonstrate the use of our algorithm on a number of binary and multiway classification tasks.
L'hybridation des pratiques de GRH à l'international par le truchement de l'ethnicité en Afrique

Cet article met au jour le fait que les pratiques de GRH a l’international des firmes multinationales (FMN) en Afrique peuvent recevoir un eclairage nouveau si l’on mobilise le concept d’ethnicite. Les investigations ont ete menees dans trois filiales camerounaises de FMN francaises. Les donnees empiriques analysees montrent que les realites culturelles locales influencent fortement l’application des politiques de GRH decidees par le siege. Les resultats demontrent la necessite d’ouvrir des espaces, ou va s’inserer la dimension ethnique dans les pratiques quotidiennes de GRH. L’article propose d’ancrer l’ethnicite dans le debat sur l’hybridation des pratiques GRH a l’international, comme une source d’avantage competitif, en la considerant non pas comme un compromis couteux mais plutot comme un compromis necessaire.
Optimal design of stochastic production lines: a dynamic programming approach

We consider the problem of choosing the number and type of machines for each station in a new production line where the sequence of processes (i.e., manufacturing recipe) has already been established. We formulate a model to minimize cost (investment plus operating) subject to constraints on throughput and cycle time. Using queueing network approximations within a dynamic programming framework, we develop a line design algorithm that works in station-wise fashion. For computational tractability, we must discretize a continuous state space. However, we are able to compute bounds on the error in the cost function as a guide to the appropriate choice of grid size. We conclude by applying our algorithm to an industrial problem that motivated this work.
Actuator saturation avoidance for fault-tolerant robots

Actuator saturation in robotic systems is a problem area that needs attention. This problem occurs more frequently and at the same time becomes more difficult to address when robots operate under faulty conditions. This work investigates two different approaches, the time regulation, and the torque redistribution methods, in an attempt to avoid saturation in fault-tolerant robots. Fault-tolerant robots considered include general architecture, spatial robots with serial or parallel structures. The control algorithm consists of a model reference algorithm and the computed torque method in the feedforward process, and a PID controller in the feedback process. Upon failure, these methods recover the robot from faulty conditions and complete the task avoiding actuator saturations. Initial simulation results indicate that the time regulation method is more suitable for serial robots, and the torque redistribution method for parallel robots. These methods are expected to be applied not only to a case where a joint is fully failed but also so cases where some joints experience partial failure. <<ETX>>
Classifying and resolving ambiguities in sketch-based interaction

Natural interaction approaches, such as the Sketch-based interaction, frequently imply ambiguities in the interpretation by the computer side. This paper focuses only on micro-level ambiguity analysing the interpretation of the abstract geometrical elements point, polyline and polygon. Considering a dynamic perspective, ambiguities can be caused by: inaccuracy in the user's drawing, approximation of the represented reality and user's deletion or retracing of fragments of the sketch. Moreover, this paper discusses methods to solve ambiguities taking into account the spatial and temporal information that characterise the user's drawing, deleting and over-tracing process according to some experimental observations of users' behaviour.
Estimation accuracy of a landing point of a ballistic target

This paper studies the problem of tracking a re-entry ballistic object by means of radar measurements. Practical applications are in the fields of surveillance for defense and for safety against the re-entry of old satellites. In particular, the investigation determines the estimation accuracy of the impact point of a ballistic target by processing radar measurements during the re-entry phase of the target. In practice, the radar measurements are available only for a limited part of the re-entry trajectory; while it is of interest to estimate the target landing point and its accuracy. This problem is tackled via non linear filtering technique and by resorting to the theory of Cramer-Rao lower bound (CRLB) recently developed for such filters.
Analysis of Machine Learning Techniques for Intrusion Detection System: A Review

Security is a key issue to both computer and computer networks. Intrusion detection System (IDS) is one of the major research problems in network security. IDSs are developed to detect both known and unknown attacks. There are many techniques used in IDS for protecting computers and networks from network based and host based attacks. Various Machine learning techniques are used in IDS. This study analyzes machine learning techniques in IDS. It also reviews many related studies done in the period from 2000 to 2012 and it focuses on machine learning techniques. Related studies include single, hybrid, ensemble classifiers, baseline and datasets used.
REDES NEURONALES, PROCESOS COGNOSCITIVOS Y ANÁLISIS DE LA CONDUCTA

Se analiza la importancia de los modelos de redes neuronales para el entendimiento de los procesos cognoscitivos en psicología y especialmente en el análisis de la conducta. En el trabajo se describen las diferencias entre los modelos simbólicos y los modelos conexionistas o de redes para la descripción de los procesos cognoscitivos. Posteriormente se describen los modelos de redes y se detallan los cálculos relacionados con la función de activación y el entrenamiento de la red a partir de las reglas de aprendizaje y la estimación del error. En la última sección se analiza la importancia de integrar los modelos de redes al análisis de la conducta. Se concluye que los modelos de redes pueden servir como un puente para que las explicaciones surgidas del análisis de la conducta se extiendan a la explicación de fenómenos típicos de la psicología cognoscitiva como la representación y la memoria. Un propósito adicional es que este trabajo sirva como una introducción que permita a los psicólogos y analistas de la conducta entender el funcionamiento de las redes neuronales artificiales a partir de ejemplos relativamente simples.
Resource Scheduling of Workflow Multi-instance Migration Based on the Shuffled Leapfrog Algorithm

Purpose: When the workflow changed, resource scheduling optimization in the process of the current running instance migration has become a hot issue in current workflow flexible research; purpose of the article is to investigate the resource scheduling problem of workflow multi-instance migration. Design/methodology/approach: The time and cost relationships between activities and resources in workflow instance migration process are analyzed and a resource scheduling optimization model in the process of workflow instance migration is set up; Research is performed on resource scheduling optimization in workflow multi-instance migration, leapfrog algorithm is adopted to obtain the optimal resource scheduling scheme. An example is given to verify the validity of the model and the algorithm. Findings: under the constraints of resource cost and quantity, an optimal resource scheduling scheme for workflow migration is found, ensuring a minimal running time and optimal cost.
Enhanced information transmission mediated by multiplicative noise (Invited Paper)

We have investigated information transmission in an array of threshold units with multiplicative noise that have a common input signal. We demonstrate a phenomenon similar to stochastic resonance with additive noise, and show that information transmission can be enhanced by a non-zero multiplicative noise level. Given that sensory neurons in the nervous system have multiplicative as well as additive noise sources, and they act approximately like threshold units, our results suggest that multiplicative noise might be an essential part of neural coding.
Research and Implement about Embedded Database System Base-on NAND Flash Memory

Currently, the embedded database technology has become a very active research field, and attracted more and more attention. This paper research how to improve the storage performance of embedded database indexing mechanism using read and write characteristics of NAND flash memory. Based on the reviewed and compared of existing design of NAND flash memory, this article expressed the design and implementation of dynamic index mechanism base on B + Tree. The prototype system combines the advantages of operation of the adapted read operation disk model and write adapted write operation log model, optimal matching and converting for storage model of each node in B + tree model while running which make a variety of devices have better read and write performance.
Efficient feature extraction from wide-area motion imagery by MapReduce in Hadoop

Wide-Area Motion Imagery (WAMI) feature extraction is important for applications such as target tracking, traffic management and accident discovery. With the increasing amount of WAMI collections and feature extraction from the data, a scalable framework is needed to handle the large amount of information. Cloud computing is one of the approaches recently applied in large scale or big data. In this paper, MapReduce in Hadoop is investigated for large scale feature extraction tasks for WAMI. Specifically, a large dataset of WAMI images is divided into several splits. Each split has a small subset of WAMI images. The feature extractions of WAMI images in each split are distributed to slave nodes in the Hadoop system. Feature extraction of each image is performed individually in the assigned slave node. Finally, the feature extraction results are sent to the Hadoop File System (HDFS) to aggregate the feature information over the collected imagery. Experiments of feature extraction with and without MapReduce are conducted to illustrate the effectiveness of our proposed Cloud-Enabled WAMI Exploitation (CAWE) approach.
Developing manufacturer-independent components for ECG viewing and for data exchange with ECG devices: can the SCP-ECG standard help?

In the context of HYGEIAnet, the regional health-telematics network of Crete, the Center for Medical Informatics and Health Telematics Applications (CMI-HTA) has explored the capabilities of several ECG devices and management systems. The focus was placed on the SCP-ECG (Standard Communications Protocol for computer-assisted Electrocardiography) standard, which defines a uniform format for the processing and storage of digital ECG recordings and specifies a means by which ECG devices and systems may exchange information. The development of a multi-manufacturer ECG viewer took more effort than expected. Although the SCP-ECG guidelines are sound and useful as far as they go, the protocol leaves too many degrees of freedom in a number of areas, so that the development of generic SCP-based software is, in practice, a difficult task. Moreover, the manufacturer's degree of compliance with the SCP standard may be unclear, while there is no recognized body or institution that is able to certify the level of conformance.
Fast image foreground object segmentation based on block texture for embedded system implementation

In this paper, a novel block-based foreground object detection method based on block texture is presented. It can significantly reduce the memory usage when constructing the background model in dynamic scenes. The proposed background model and detection algorithm are suitable for implementing on embedded system platforms with resource limitations. The experimental results of processing benchmark videos show that our method has outcomes that are very close to ground truth segmentation. In addition, the proposed method requires approximately 23.97% less memory than the latest algorithms. Finally, the proposed approach is implemented on an embedded system platform. The processing speed can achieve a real-time rate of at least 20 fps, which is an improvement of 17.64% as compared to the latest algorithms.
An IBM second generation RISC processor architecture

A second-generation RISC (reduced-instruction-set computer) architecture designed to support superscalar implementations which can execute multiple instructions every cycle is described. The architecture provides compound function instructions which allow application path lengths to be less than would be required on many complex-instruction-set computers. This second-generation RISC architecture also exploits advances in optimizing compiler and operating system technology. An extension to the original 801 minicomputer virtual memory architecture for hardware support of database storage is described. <<ETX>>
Reference at the commons: a case study

Purpose – This paper aims to examine whether relocating the reference desk closer to the main entrance has factored into increased reference activity at Regent University Library.Design/methodology/approach – Statistics from 1992/1993 through 2007/2008 were examined to see whether gate counts and questions asked went up, down or remained steady.Findings – Technology changes and user expectations have affected reference service at Regent University Library. Even though the number of patrons coming to the library has declined, the number of questions being asked through e‐mail and the telephone has risen slightly. Librarians have also seen an increase in students making appointments for extended assistance.Research limitations/implications – This case study examines the decline in gate counts and reference activity at one academic library during a period of enrollment growth. Changes to the layout and location of the reference desk resulted in an increase of in‐person reference transactions.Practical implic.
A benchmark system for the evaluation of selected phase retrieval methods

In comparison to classical phase measurement methods like interferometry and holography, there are many phase retrieval methods which are able to recover the phase of a complex valued object without the necessity of a reference wave. Due to the large number of different methods, iterative as well as non-iterative ones, it is hard to find the method which is appropriate for a given application or object. We propose a system which is based on different criteria, some of which can be calculated by analyzing the phase retrieval result compared to the original object. Other criteria like the complexity of the optical system are also taken into account. For testing the benchmark system we use a software which is suitable, first, to simulate the acquisition process of the intensity measurements, second, to run the phase retrieval algorithm itself and, third, to calculate the values of the benchmark criteria. Having determined the values of the different criteria we assign points for every criterion which can be weighted by importance and are summed up for getting an overall benchmark score. This final score can be used to compare different phase retrieval methods and by having a closer look at the single criteria it is possible to analyze the strengths and weaknesses of the method. We will show the detailed proceeding of calculating the benchmark value by means of a selected phase retrieval method and a phase only object (USAF target). We have to emphasize that the results strongly depend on the object.
User Simulation for Spoken Dialog System Development

A user simulation is a computer program which simulates human user behaviors. Recently, user simulations have been widely used in two spoken dialog system development tasks. One is to generate large simulated corpora for applying machine learning to learn new dialog strategies, and the other is to replace human users to test dialog system performance. Although previous studies have shown successful examples of applying user simulations in both tasks, it is not clear what type of user simulation is most appropriate for a specific task because few studies compare different user simulations in the same experimental setting. In this research, we investigate how to construct user simulations in a specific task for spoken dialog system development. Since most current user simulations generate user actions based on probabilistic models, we identify two main factors in constructing such user simulations: the choice of user simulation model and the approach to set up user action probabilities. We build different user simulation models which differ in their efforts in simulating realistic user behaviors and exploring more user actions. We also investigate different manual and trained approaches to set up user action probabilities. We introduce both task-dependent and task-independent measures to compare these simulations. We show that a simulated user which mimics realistic user behaviors is not always necessary for the dialog strategy learning task. For the dialog system testing task, a user simulation which simulates user behaviors in a statistical way can generate both objective and subjective measures of dialog system performance similar to human users. Our research examines the strengths and weaknesses of user simulations in spoken dialog system development. Although our results are constrained to our task domain and the resources available, we provide a general framework for comparing user simulations in a task-dependent context. In addition, we summarize and validate a set of evaluation measures that can be used in comparing different simulated users as well as simulated versus human users.
Mobile Devices Strengthen Classroom Management

Research on using Tablet PCs, PDAs and other intelligent mobile devices in education is abundant; how- ever, much of this research emphasizes how these devices can assist students with writing, sketching, drawing, or annotating media using electronic ink and drawing tools. Few studies have focused on how these devices can best accommodate teachers with student assessment. We designed, developed an integrated learner assessment system, which includes user management, login access management, data initialization, data collection rules' management, data collection, data management, motivation rules' manag ement and grading rules' management.
A carrier synchronization technique for OFDM on the frequency-selective fading environment

This paper proposes a new frequency offset correction technique for OFDM (orthogonal frequency division multiplexing) receivers on a frequency-selective fading channel. In order to combat the frequency offset effectively, the proposed technique consists of two steps: acquisition and tracking. In the acquisition process, the frequency offset is reduced to less than half of the intercarrier spacing. In the tracking process, the frequency offset is corrected to zero by employing an automatic frequency detector (AFD). In addition, this paper proposes a pattern matching algorithm for the acquisition and derives an AFD characteristic curve for the tracking. From the results, it is shown that the proposed algorithm can correct a large frequency offset encountered in a severely frequency-selective fading environment.
Technology and school leadership

As the demand for schools to become more effective and efficient learning communities increases, the need for principals to cultivate broad‐based, skilful participation in the work of leadership is essential. It is important for educational leaders to recognise the significance of their role in technology implementation and utilisation. They should be proficient in the use of technology and then provide leadership in the use of technology for administrative, instructional, and learning functions. Relatively few studies have empirically examined the level of computer use by principals, their perceived computer competence and their leadership style. This paper will report on these issues from an initial analysis of baseline data gathered from 30 secondary school principals in Tehran, a large province in Iran. Findings indicate that school principals spent a few times a week working on their computers and they had moderate levels of information technology competency. This paper also suggests that transformational leadership can help school leaders increase successful use of technology in schools. Hence, policy makers must design professional development programmes, such as leadership studies, in order to teach the components of transformational leadership: idealised influence, inspirational motivation, intellectual stimulation and individual consideration to future administrators.