Miracle-dz/UniFAR-FTUs huggingface dataset:
Multi-agent decision system for solving dynamic location in manufacturing cells

This study proposes a new approach to multi-criteria decision support systems (MDSS) using an agent-based approach. The dynamic location /distribution problem is formulated as a mixed integer programming model which forms the basis of the MDSS and whose objectives are to minimize total weighted delivery time, purchasing cost, total weighting cost, or total number of vehicles, by using multi-agent negotiation and cooperation The proposed models and methods are applied interactively to determine the weight of each criterion. The multiple objectives are then transformed into a single objective. A prototype system for delivering goods from multiple suppliers to customers is presented. Since the proposed problem is NP-hard, business software does not work well as the number of suppliers or customers becomes a large (over 100). Thus, a heuristic algorithm is developed and adopted. Compared to the lower bound of the optimal solution, the heuristic algorithm performs well and outputs an adequate solution. An agent-based approach is presented to determine favorable alternatives in changing market environments
A fast algorithm for mining association rules in medical image data

This paper presents a fast association rule mining algorithm which is suitable for medical image data sets. In particular, it assesses the feasibility of using association rule algorithms to extract hidden information from medical image data sets. In addition, we provide a flavour of our implementation environment. Finally, we show, with an example, how our proposed algorithm works to assess its suitability.
Augmenting the access grid using augmented reality

The Access Grid (AG) targets an advanced collaboration environment, with which multi-party group of people from remote sites can collaborate over high-performance networks. However, current AG still employs VIC (Video Conferencing Tool) to offer only pure video for remote communication, while most AG users expect to collaboratively refer and manipulate the 3D geometric models of grid services' results in live videos of AG session. Augmented Reality (AR) technique can overcome the deficiencies with its characteristics of combining virtual and real, real-time interaction and 3D registration, so it is necessary for AG to utilize AR to better assist the advanced collaboration environment. This paper introduces an effort to augment the AG by adding support for AR capability, which is encapsulated in the node service infrastructure, named as Augmented Reality Service (ARS). The ARS can merge the 3D geometric models of grid services' results and real video scene of AG into one AR environment, and provide the opportunity for distributed AG users to interactively and collaboratively participate in the AR environment with better experience.
Performance Comparison of AODV, OLSR and OFLSR in Wireless Mesh Networks

Wireless mesh networks are the next step in the evolution of wireless architecture, delivering wireless services for a large variety of applications in personal, local, campus, and metropolitan areas. Unlike WLANs, Mesh networks are self- configuring systems where each Access Point (AP) can relay messages on behalf of others, thus increasing the range and available bandwidth. Despite recent advances in wireless mesh networking, many research challenges remain in all protocol layers. To use existing protocols in wireless mesh network we have to add more features in existing protocols so that they become suitable for use in wireless mesh network. In this paper, We present a detailed simulation study of the performance of the predominant mesh routing protocols being considered in IEEE 802.11s: Ad Hoc On Demand Distance Vector (AODV) and optimized Link State Routing Protocol (OLSR). Moreover, for large-scale wireless mesh networks, we gracefully integrate advantages of OLSR and Fisheye routing protocol (FSR). Results show that OFLSR provides better scalability in terms of traffic load and host mobility than AODV in mesh networks.
How Robust Are Distributed Systems

A distributed system is made up of large numbers of components operating asynchronously from one another and hence with imcomplete and inaccurate views of one another's state. Load fluctuations are common as new tasks arrive and active tasks terminate. Jointly, these aspects make it nearly impossible to arrive at detailed predictions for a system's behavior. It is important to the successful use of distributed systems in situations in which humans cannot provide the sorts of predictable realtime responsiveness of a computer, that the system be robust. The technology of today can too easily be affected by worn programs or by seemingly trivial mechanisms that, for example, can trigger stock market disasters. Inventors of a technology have an obligation to overcome flaws that can exact a human cost. A set of principles for guiding solutions to distributed computing problems is presented.
Study of load control mechanisms for the effective delivery of IN services

We evaluate the performance of two schemes to control the load imposed to the service control point (SCP), namely, call gapping and credit-based control and introduce a two level load-balancing control mechanism to provide better quality of services guarantees to IN services. Our study differs from previous studies as we consider in detail the internal organization of the SCP. Furthermore, we consider the operation of the system when servicing IN services of various levels of complexity. The complexity being measured by the number of visits to the database required to complete the service. We have been particularly interested in evaluating the call response time and system utilization since these are the two performance metrics of concern to the users and service provider, respectively.
Adaptive Operator Scheduling in Evolutionary Algorithms

A growing problem in the field of evolutionary computation is the large amount of genetic operators available for certain problem domains. This tendency is especially pronounced in areas where heuristics are used to create highly specialised operators. Even within the same problem domain, the performance of such operators often depends on the specific problem instance at hand. This results in a tedious and time-consuming process of comparing individual operator performances every time a new problem is to be solved. This paper investigates the use of adaptive operator scheduling to automate the operator selection process. The approach is tested on instances of the Travelling Salesman Problem a problem for which a long list of operators exists. Results show that benefits are twofold: Operator selection is achieved automatically and an overall performance improvement is observed.
Practical implementation of cross-layer design in broadband wireless access networks

The established success of wireless communications in terms of high data rates provision is undoubtedly owed to several combinations of different mechanisms. Such a combination is the well-known forward error correction (FEC) mechanism that combines automatic-repeat-request (ARQ) protocol and error correction capabilities. Furthermore, in the last decade, a cross-layer design provides the combination of different mechanisms across the layers and thus the performance gain is increased in wireless communications over fading channels. In this paper, we present a practical cross-layer design implementation that combines adaptive modulation and coding (AMC) and hybrid ARQ at the physical and data link layer by using different error correction schemes. Our implementation is based on a cross-layer design of AMC and HARQ. We perform simulations with different channel coding and modulation schemes that are implemented in broadband wireless access networks as IEEE 802.16 and 3GPP HSPA and thus the results obtained show the performance achieved by this practical cross-layer implementation in terms of spectral efficiency in two main broadband wireless access networks available into the market.
Design of pipelined memory systems for decoupled architectures

Design of memory systems for decoupled architectures is the theme of this dissertation. The decoupled architecture uses hardware queues to architecturally decouple memory request generation from algorithmic computation. This results in an implementation that has two separate instruction streams that communicate via hardware queues. Thus, performance is improved through parallelism and efficient memory referencing. Techniques for increasing memory bandwidth and algorithms for servicing memory requests are incorporated into the memory system designs within these two constraints: (1) the operands placed in the hardware queue must be in the correct order, and (2) the needed operands are the only operands that can be placed in the hardware queue. Techniques such as pipelining, interleaving, servicing requests out of arrival order, and cache memory are investigated. Two strategies for servicing memory requests are studied: (1) to service requests according to their priorities, and (2) to minimize the total request service time. For the first strategy, the priority of each request type is derived from the characteristics of memory reference and possible bottleneck during decoupled computations. The second strategy results in a request scheduling policy, Free-Module-Request-First, that is proven to be able to minimize the total request service time. A sequence control scheme must be used with the Free-Module-Request-First scheduling policy in order to deliver the memory outputs to the hardware queue in the correct order. This sequence control scheme is also used to track cache hits and misses, so that a data cache can be implemented in the memory system without difficulty. The designed data cache can not only support flexible fetch and replacement cache algorithms, it can also detect memory access hazards and short-circuit the Read-After-Write requests. Therefore, the penalty of memory access hazards can be greatly reduced. The combination of the designed data cache and the pipelined interleaved memory system using Free-Module-Request-First scheduling policy results in a high-performance memory system, that is capable of servicing memory requests nearly no conflict delay under the particular workload defined in the trace files.
Foliar reflectance and fluorescence responses for plants under nitrogen stress determined with active and passive systems

Leaves of corn (Zea mays L.) and soybean (Glycine max L.) plants were examined in a set of four experiments conducted in the summer of 2001 at USDA in Beltsville, MD. Red edge reflectance spectra and red (R) and far-red (FR) fluorescence emissions were acquired for adaxial and abaxial leaf surfaces, in conjunction with foliar chlorophyll content, photosynthetic capacity (Amax), and C/N ratio. A red edge first derivative ratio was strongly related to chlorophyll content, Amax, and C/N ratio. R/FR fluorescence emission ratios also were related to Amax and C/N levels, and enabled species discrimination.
On an M [X] / G /1 queuing system with random breakdowns, server vacations, delay times and a standby server

In this work, we study a batch arrival queue with a Bernoulli schedule vacation where after every service completion the server may take a vacation of random length with probability p or may stay in the system providing service with probability 1 - p . Moreover, we assume that the server may breakdown randomly, and the repair process does not start immediately after a breakdown; consequently, there is a delay time waiting for repairs to start. The main new contribution in this work is that we assume that the system is equipped with a standby server to serve the costumers during the vacation period of the main server. The service times, vacation times, repair times and delay times are assumed to follow different general arbitrary distributions while the service times of the standby server follows an exponential distribution.
The MP-tree: a data structure for spatio-temporal data

The MP-tree (Multi-dimensional Persistent tree), a data structure for managing spatio-temporal data, is proposed. The MP-tree is developed by extending conventional spatial data structures using techniques of Persistent Search Tree. In this paper, the structure and operations of the MP-tree are described and the performance of the MP-tree is compared with three possible methods. Through computer simulations, it is shown performance of the MP-tree is better than the three methods for range searching for current version. For multiversion range searching, the MP-tree is also shown to be better when the length of query time interval is short. <<ETX>>
Efficient filtering of images using binomial sequences

The authors introduce a class of nonrecursive multidimensional filters for frequency-selective image processing without multiply operations. These binomial filters constitute a family of orthogonal filters. The magnitude responses are narrowband and approximately Gaussian-shaped, with center frequencies that can be positioned to yield low-pass, bandpass, or high-pass filtering. It is shown that the binomial algorithms provide a fast, easily implemented, noise-free family of filters for image processing in the spatial domain. A software implementation of the low-pass and high-pass filtering operators is useful for seismic data. A hardware implementation can be realized with only adders and delay elements. Since no coefficient multipliers are needed, reliability is improved, there are no attendant accuracy or roundoff errors, and a substantial savings in cost is achieved. <<ETX>>
Comparison of Verilog-A compact modelling strategies for spintronic devices

Magnetic random access memory based on magnetic tunnel junctions (MTJs) is among the most attractive technologies of emerging non-volatile memories. However, the integration of spin-based devices in integrated circuits is still hindered by a lack of established standard electrical simulator models. Many of such models have been proposed during the past decade which can be classified into two categories: the first ones are based on the physical Landau-Lifshitz-Gilbert (LLG) equation describing real-time MTJ magnetic switching dynamics; the second one uses analytical expressions for switching thresholds derived from the LLG equation. The aim of this reported work was to investigate for the first time the capability of each strategy to fulfil the need of industrial standard electrical simulation tools and pave the path towards a standard industrial model. Multi-simulator compatibility, efficient runtime, accuracy and reliability are the three main assets of a device model. It is shown that using the Cadence® tools suite with the Spectre® simulator, the LLG modelling strategy overcomes the analytical approach in terms of accuracy and speed with a 7× faster runtime. Both models require nearly the same hardware memory resources.
Estimating parameters in stochastic compartmental models using Markov chain methods

Markov chain Monte Carlo methodology is presented for estimating parameters in stochastic compartmental models from incomplete observations of the corresponding Markov process. The methods, which are based on the Metropolis-Hastings algorithm, are developed in the context of epidemic models. Their use is illustrated for the particular case where only susceptible, infective, and removed states are represented using simulated realizations of the process. By comparing estimated likelihoods with theoretical forms, in cases where these can be derived, or with the known model parameters, we show that the methods can be used to provide meaningful estimates of parameters and parameter uncertainty. Potential applications of the techniques are also discussed.
Car License Plate Recognition using Color Features of Persian License Plates

Car license plate recognition is addressed in of intelligent transportation systems, it is absolutely essential to implement a strong license plate recognition system. Efforts were made to put forward a novel reliable method for car license plate recognition in Iran. system comprises three main parts. The first part is the license plate detection stage. The blue color feature of the license plate margin along with Scale Feature Transform (SIFT) algorithm were used for this purp the presented method over the database was approximately second. License plate morphological features were utilized upon character segmentation. Using these features, areas with sizes close to that of the characters of a license plate may be searched probabilistic neural network together with a Support Vector Machine (SVM) was employed at the character recognition stage. For this stage, an accuracy of nearly 97% in 55 milliseconds for each license plate was achieved
Efficient local approximation of perceptual color differences for color inspection

We suggest a local approximation of perceptual color differences in a device dependent color space, e.g. an RGB space. The approximation is efficiently computed from measuring Euclidean color distance in the device dependent color space combined with an associate memory data structure. Established measures of color difference are considered. Results for small perceptual color differences in a color inspection setup are given.
A distributed fair, and efficient protocol for integrated voice/data services on token ring networks

A protocol is proposed which supports integrated services on a token ring network. The key features of the protocol are: (1) both synchronous and asynchronous traffic, such as voice and data, are supported, (2) the control station of the protocol is not assigned to a fixed station, and thus the protocol is more distributedly controlled, (3) all voice stations have a fair chance of accessing the channel, (4) data traffic has a higher chance of accessing the channel without influencing the quality of the synchronous traffic, and (5) expedited data traffic is supported. An analytic model and simulations are included to show that this protocol is robust, efficient, and fair and that it presents small delay for data traffic. <<ETX>>
Analyzing spatial patterns of meteorological drought using standardized precipitation index

Drought is a slow‐onset, creeping natural hazard and a recurrent phenomenon in the arid and semi‐arid regions of Gujarat (India). In Asia, the standardized precipitation index (SPI) has gained wider acceptance in the detection and the estimation of the intensity, magnitude and spatial extent of droughts. The main advantage of the SPI, in comparison with other indices, is that the SPI enables both determination of drought conditions at different time scales and monitoring of different drought types. This index captures the accumulated deficit (SPI < 0) or surplus (SPI > 0) of precipitation over a specified period, and provides a normalized measure (i.e. spatially invariant Z score) of relative precipitation anomalies at multiple time scales. In the present study, monthly time series of rainfall data (1981–2003) from 160 stations were used to derive SPI, particularly at 3‐month time scales. This 3‐month SPI was interpolated to depict spatial patterns of meteorological drought and its severity during typical drought and wet years. Correlation analysis was also done to evaluate usefulness of SPI to quantify effects of drought on food grain productivity. Further, time series of SPI were exploited to assess the drought risk in Gujarat. Copyright © 2007 Royal Meteorological Society
The EOS MOPITT instrument:validation and early results

Launched on the EOS Terra satellite on December 18, 1999, the MOPITT (Measurements of Pollution in the Troposphere) instrument has been observing tropospheric carbon monoxide (CO) and methane (CH/sub 4/) since March, 2000. The instrument is now fully functional, and the retrieval algorithms are now being validated. Because of the pioneering aspect of this instrument, validation is a particularly important phase of operations and is the main emphasis of this paper.
A neural architecture for diagnosis

A neural classifier, well-adapted to the diagnosis problem, is presented in this paper. It is able to learn the non-convex envelop of the classes and so, to allow the rejection of points situated far from high density regions in the space. The basic component of the architecture is a Gaussian cell. The learning algorithm allows the incremental recruitment of the cells. A decision rule is proposed and compared to a classical decision rule. Experimental results are shown in a two and four-dimensional case. <<ETX>>
Polarimetric optimisation applied to permanent scatterers identification

In this work, the potential of full-polarimetric SAR data to enhance the performance of permanent scatterers candidates (PSC) detection is investigated. In particular, the problem of finding the polarisation states that maximise the signal amplitude inverse coefficient of variation (ICV) is analyzed. Under the hypotheses of Rice statistics and high signal to clutter ratio (SCR), the problem can be cast into a form equivalent to the optimisation of the ratio between PS (target) and clutter backscatter. Then, solution can be derived for the optimal transmit and receive polarisation states. In the paper, selected typologies of PS and clutter are investigated. The approach is validated through Monte Carlo simulation of the multitemporal polarimetric response of PS-like SAR pixels. Results indicate that optimal ICV values of polarimetrically complex PSC pixels are higher than in the ERS case of the single VV channel, thus leading to increased stability of the subsequent parameter retrieval. Moreover, simulation of ICV vs. SCR suggest that a higher number of PSC may be detected by using optimal polarisation states than in the conventional VV channel alone.
Computer-assisted Laser Material Processing (CALMP): a PC database and simulation software for laser material processing

The design and implementation of a software system for supporting laser material processing work is presented. The system integrates a database, numerical simulation and various other computer techniques and provides a user friendly environment. The general system structure is described. Research results on some related topics for the system design are also presented in this paper. This includes a neural network analysis on laser surface hardening and cladding, and the implementation of simulation models for cutting and welding of steel. A PC version of the software, named CALMP (Computer Assisted Laser Material Processing), is briefly described.
A study of making clear body‐conducted speech using differential acceleration

An existing problem for speech recognition is that the recognition rate tends to decrease because of the noise. Body‐conducted speech offers a robust signal extraction method to extract speech signals from noisy environments, particularly because body‐conducted speech is a propagated sound and not easily influenced by noise. However, when body‐conducted speech is extracted with an accelerator, the typical frequency component of 2 kHz or more decreases in comparison with normal speech. Therefore, much research has been carried out investigating the techniques for improving the sound quality of body‐conducted speech. Particularly, conventional methods require normal speech to estimate clear speech. Here, we propose a technique that combines differential acceleration and noise reduction to estimate a clear signal using only body‐conducted speech. By comparing spectrogram differences with each method, we found that the Wiener filtering method was suitable for eliminating noise with differential acceleration. Thereafter, improvements in recognition rates were obtained using retrieval signals although the decoder has an acoustic model made by speech parameters. © 2011 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.