Miracle-dz/UniFAR-FTUs huggingface dataset:
An Application of Neural Networks to Group Technology

ormance of this compressed algorithm is compared to that of the regular algorithm on real engineering designs anda significant savings in memory storage as well as a speed up in execution is observed. In addition, we will describe a"neural database" system under development. This system demonstrates the feasibility of training an ART-i networkto first cluster designs into families, and then to recall the family when presented a similar design. This application isoflarge practical value to industry, making it possible to avoid duplication of design efforts.
The Multi-frequency Imaging Microwave Radiometer: Applications To Land Surface Parameter Retrieval

The Multi-frequency Imaging Microwave Radiometer (MIMR) which is planned for the NASA EOS platform will be a very significant contribution in the field of land / vegetation monitoring on a global scale. With its relatively large number of frequencies and good spatial resolution it should provide much improved data sets than the SMMR. The presentation will describe the different the key parameters of the MIMR together with their impacts on the different fields of application for lanuvegetation (i.e. soil moisture, vegetation biomass etc. .). The presentation will also describe the synergisms with other EOS sensors. Finally the expected products will be described as well as the related possible inversion algorithms.
Coordinated Multi-Point under a Constrained Backhaul and Imperfect Channel Knowledge

Mobile communication has become an essential part of today’s information society. Especially the demand for ubiquitous mobile Internet access has signiﬁcantly increased in the past years, creating a severe challenge for mobile operators to respond to the demand for mobile data rates, while at the same time strongly reducing cost per bit. This challenge can only be successfully addressed if the spectral eﬃciency and fairness of mobile communications are continuously increased. In today’s cellular systems, both aspects are more and more limited through the interference between cells, especially in dense urban deployments. From theory it is known that this inter-cell-interference can be canceled or even exploited if base stations cooperatively process signals connected to multiple terminals, a concept commonly referred to as Coordinated Multi-Point (CoMP). As these schemes promise signiﬁcant improvements of spectral eﬃciency and a more homogeneous throughput distribution, they are seen as a key technology of future mobile systems. Beside many implementation challenges, such as the synchronization of the cooperating entities and an accurate estimation of the involved wireless links, a main issue connected to CoMP is the additional infrastructure required for data exchange between cooperating base stations, usually referred to as backhaul . This work provides an information theoretical analysis of the trade-oﬀ between capacity gains and required backhaul achievable with various CoMP concepts, also taking into consideration the major impact of imperfect channel knowledge at base station and terminal side. A key ﬁnding is that the relative beneﬁt of CoMP in fact increases in certain scenarios under less accurate channel knowledge. Also, major throughput gains are already possible through ﬂexible user assignment and decoding concepts, without requiring any backhaul. For the cellular uplink, two cooperation strategies are identiﬁed that should ideally be used adaptively, depending on the current interference situation. One can be used for a very backhaul-eﬃcient, low complexity, decentralized cancelation of weak interference, where the base stations exchange decoded data. In the other, centralized, scheme, the base stations exchange received signals, providing larger gains under stronger interference conditions, but requiring more back-haul. For the downlink, a ﬂexible scheme of moderate complexity is identiﬁed that provides a good throughput
An Algorithm for Detecting Cycles in Undirected Graphs using CUDA Technology

Cycles count in a graph is an NP-complete problem. This work minimizes the execution time to solve the problem compared to the other traditional serial, CPU based one. It reduces the hardware resources needed to a single commodity GPU. We developed an algorithm to approximate counting the number of cycles in an undirected graph, by utilizing a modern parallel computing paradigm called CUDA (Compute Unified Device Architecture) from nVIDIA, using the capabilities of the massively parallel multi-threaded specialized processor called Graphics Processing Unit (GPU). The algorithm views the graph from combinatorial perspective rather than the traditional adjacency matrix/list view. The design philosophy of the algorithm shows that each thread will perform simple computation procedures in finite loop iterations to be executed in polynomial time. The algorithm is divided into two stages, the first stage is to extract a unique number of vertices combinations for a given cycle length using combinatorial formulas, and then examine whether given combination can for a cycle or not. The second stage is to approximate the number of exchanges (swaps) between vertices for each thread to check the possibility of cycle existence. An experiment was conducted to compare the results between the proposed algorithm and another distributed serial based algorithm based on the Donald Johnson backtracking algorithm.
Comparison of Uncalibrated Model-Free Visual Servoing Methods for Small-Amplitude Movements: A Simulation Study

The paper compares the performance of several methods used for the estimation of an image Jacobian matrix in uncalibrated model-free visual servoing. This was achieved for an eye-in-hand configuration with small-amplitude movements with several sets of system parameters. The tested methods included the Broyden algorithm, Kalman and particle filters as well as the recently proposed population-based algorithm. The algorithms were tested in a simulation environment (Peter Corke's Robotic Toolbox for MATLAB) on a PUMA 560 robot. Several application scenarios were considered, including static point and dynamic trajectory tracking, with several characteristic shapes and three different speeds. Based on the obtained results, conclusions were drawn about the strengths and weaknesses of each method both for a particular setup and in general. Algorithm-switching was introduced and explored, since it might be expected to improve overall robot tracking performance with respect to the desired trajectory. Finally, possible future research directions are suggested.
Genetic algorithms with adaptive probabilities of operator selection

In this paper we propose a new method of tuning the probabilities of the genetic operators. We assume that every member of the optimized population conducts his own ranking of genetic operator qualities. This ranking becomes a base to compute the probabilities of appearance and execution of genetic operators. This set of probabilities is a base of experience of every individual and according to this it chooses the operator in every iteration of the algorithm. Due to this experience one can maximize the chance of offspring survival.
Stem Cell Therapy Combined with Myocardial Revascularization: A Pilot Study using the Harvest Technique

Background: To assess the usefulness of intra-myocardial autologous stem cell injection as a hybrid procedure with coronary artery bypass grafting (CABG) compared to conventional CABG only in the patients with ischemic heart disease with non-viable or non-graftable myocardial segments. Methods: After approval of Local Ethics Committee and obtaining written informed consent, a prospective, comparative randomized study was conducted on 30 ischemic heart patients with non-viable or non-graftable segments. They were divided into two groups. Group A (15 patients): where intra myocardial injection of autologous bone marrow mononuclear cells (ABM-MNCs) was done in conjunction with CABG. Group B (15 patients): where CABG was performed only. Resting and stress echocardiography follow up was done for 6 months. Results: There was no mortality in either group. No complications were noted at a mean of 6 months after surgery. Group A showed a significant improvement (mean of 7.25% and P<0.001) in left ventricular ejection fraction (LVEF). Both end- diastolic (LVEDD) and end-systolic (LVESD) diameters showed significant decrease compared to pre- operative values. LVEDD decreased by a mean of 5.23 (P <0.001) while LVESD by a mean of4.21 (P<0.001). Conclusion: Stem cell therapy combined with CABG improves cardiac function compared with revascularization alone. In the same time, it is safe, feasible, and reproducible and doesn’t increase the risk of major adverse events or mortality.
Taboo niche optimization based on intelligent engineering and its application in water ecology

Intelligent Engineering is kind of method incorporating artificial intelligence Neuron Network and fuzzy system and is of superiority in solving complex system concerning multiple factors. Niche Taboo optimization algorithm is good at solving non-linear optimization problem. In the paper, Intelligent Engineering is used for description of system states and providing a framework for complex problem solving while Taboo Niche optimization algorithm is used for optimization path search in the state-space of intelligent space. The paper details the main idea of Intelligent Engineering and the algorithm of Niche Taboo optimization. Finally a simple case study for water ecology developmental strategy is given to show the feasibility of the method proposed.
Performance of Neural Networks in Managerial Forecasting

This paper investigates the effectiveness of a multi-layered neural network as a tool for forecasting in a managerial time-series setting. To handle noisy data of limited length we adopted two different neural network approaches. First, the neural network is used as a pattern classifier to automate the ARMA model-identification process. We tested the performance of multi-layered neural networks with two statistical feature extractors: ACF/PACF and ESACF. We found that ESACF provides better performance, although the noise in ESACF patterns still caused the classification performance to deteriorate. Therefore we adopted the noise-filtering network as a preprocessor to the pattern-classification network, and were able to achieve an average of about 89% classification accuracy. Second, the neural network is used as a tool for function approximation and prediction. To alleviate the overfitting problem we adopted the structure of minimal networks and recurrent networks. The experiment with three real-world time series showed that the prediction by Elman's recurrent network outperformed those by the ARMA model and other structures of multi-layered neural networks, especially when the time series contained significant noise.
Indirect current control scheme in PWM voltage-sourced converter

An indirect current control scheme for a PWM voltage source converter is proposed in this paper. The main advantages of this proposed system are that the sinusoidal line current waveforms with near unity power factor and the ripple-free DC output voltage waveform are achieved without any current sensors. The mathematical model based on the space vector is derived and the principle of the indirect current control is described. From the comparison of the simulation and experimental results between the direct current control scheme and the indirect current control scheme, the validity of this proposed indirect current control is verified.
2D to 3D Conversion in 3DTV Using Depth Map Generation and Virtual View Synthesis

Abstr act. 2D to 3D conversion is an important task in 3DTV due to the lack of 3D contents. In this paper, we propose a novel framework of the 2D to 3D video conversion. The proposed framework consists of two main stages: depth map generation and virtual view synthesis. In the depth map generation, motion and relative-height cues are effectively used to generate depth maps. In the virtual view synthesis, depth-image-based-rendering (DIBR) is adopted to generate the left and right virtual views from the depth maps. Experimental results demonstrate that the proposed 2D to 3D conversion is very effective in generating depth maps and providing realistic 3D effects.
Role of Carotid Intima-Media Thickness in the Detección of Subclinical Atherosclerosis

In addition, in order to study the efficacy of pharmacological interventions in clinical trials, drug-induced regression or slow progression in carotid IMT in the follow-up period are being used as an alternative, or surrogate clinical end point for cardiovascular morbidity and mortality [1]. Serum biomarkers have been widely utilized to assess the risk of developing atherosclerosis. Despite their benefits and their usefulness in this context, carotid IMT has the additional theoretical advantage of directly visualizing the final consequence of the disease itself, namely atherosclerosis in the vessel wall. The current widespread application of the ultrasound values of carotid IMT measurements has been based on the validity, standardization, and reproducibility of the technique, and the evidence that an increased carotid IMT can be regarded as a marker of atherosclerosis and of increased cardiovascular risk [10-16]. This harmless ultrasound procedure has several advantages due to the lack of invasiveness and its usefulness of repeatability which makes carotid IMT measurement an attractive biomarker, potentially useful as a therapeutic target in those at increased cardiovascular risk [17].
Cybernetics and social science : theories and research in sociocybernetics

In studying the relationship between Cybernetics and Social Science, theories and research in Sociocyber‐netics are examined. The focus is on researchers who apply Cybernetics to the study of society and its social systems and processes. References are backed by a new 300‐item bibliography of the relevant system literature, compiled for the article.
Semi-Supervised Classification for Hyperspectral Image Based on Tri-Training

Hyperspectral image classification is difficult due to the high dimensional features but limited training samples. Tri-training learning is a widely used semi-supervised classification method that addresses the problem of lacking of labeled examples. In this paper, a novel semi-supervised learning algorithm based on tri-training method is proposed. The proposed algorithm combines margin sampling (MS) technique and differential evolution (DE) algorithm to select the most informative samples and perturb them randomly. Then the samples we obtained, which can fulfill the labeled data distribution and introduce diversity to multiple classifiers, are added to training set to train base classifiers for tri-training. The proposed algorithm is experimentally validated using real hyperspectral data sets, indicating that the combination of MS and DE can significantly reduce the need of labeled samples while achieving high accuracy compared with state-of-the-art algorithms.
Performance of M-algorithm MLSE equalizers in frequency-selective fading mobile radio channels

The performance loss of an adaptive M-algorithm maximum likelihood sequence estimation (MLSE) equalizer system is presented for frequency-selective fading mobile ratio channels, assuming a two-ray and a six-ray multipath fading model. The use of a computer simulation of a time division multiple access (TDMA) digital mobile radio link demonstrates that the M-algorithm can be substituted for the optimum Viterbi algorithm in adaptive MLSE equalizers for frequency-selective fading mobile radio channels. For a two-ray channel model, the degradation due to the use of the M-algorithm is less than 1 dB if the number M of evolved paths is 2 or larger. For channels with a heavy multipath propagation, such as the six-ray channel, the M-algorithm MLSE equalizer suffers from a considerable degradation. <<ETX>>
Skills for Instructional Design Professionals

Competent instructional designers must have specific skills to successfully facilitate learning and to improve the performance of individuals and organizations. While some authors and professional organizations have identified the capabilities required for effective instructional designers, only a few have validated these skills by collecting data from actual practitioners. The purpose of this article is to discuss the results of a research study we conducted to identify and empirically validate competencies for instructional design professionals.
The Electronic Magazine of Original Peer-Reviewed Survey Articles

The need for real-time services support over the Internet drives research efforts toward the provisioning of quality of service (QoS) guarantees in IP networks. Among the various aspects of QoS provisioning, QoS state establishment and main- tenance in intermediate routers is a major factor, responsible for dynamic resource allocation. The dynamic manipulation of QoS state is possible through the utilization of appropriate QoS signaling that triggers the respective resource allocation in QoS-capable network elements. At first, protocol design assumed a homogeneous underlying network and resulted in end-to-end QoS protocols that applied a specific QoS configuration in all routers along the path. However, the need for accommodat- ing network heterogeneity and flexibility led to a two-tier resource management model that utilizes separate signaling for intra- and inter-domain reservations and requires different signaling processing in domain interior and border routers. This article gives an overview of the QoS signaling protocols designed for the Internet and describes their characteristics. Moreover, the identified protocols are classified depending on their applicability for intra- or inter-domain usage. A comparison of the various protocols based on some common signaling elements is also provided, and future trends in the Internet QoS signaling area are identified.
A monolithic image sensor for a reading aid for the blind

A compact optical-tactile reading aid that allows a blind person immediate access to virtually all printed reading material used by sighted people has been developed. A singular feature of this instrument is a silicon monolithic image-sensing array that serves as the "retina" of the reading aid: signals from the retina are used to control an array of piezoelectric stimulators that form tactile images of printed characters. The image sensor consists of a 24×6 matrix of bipolar phototransistors integrated on a chip approximately 3×5 mm in size, and is designed on the basis of electrical, optical, psychological, and psychophysical considerations. The column-isolated structure incorporates a 2 to 1 aspect ratio to provide sufficient resolution and field of view for unambiguous letter-by-letter detection using a minimum number of sensor elements. A one-dimensional scanning technique minimizes fixed pattern noise and reduces the complexity of the total system. The individual 150×300 µm photosensing elements are optimized for maximum responsivity, uniformity, and dynamic range. The doping profile, featuring a 2 µm base depth and 12 µm epitaxial thickness, is based on spectral response and on a detailed electrical analysis of array operation. Output nonuniformity is minimized, and electrical crosstalk is virtually eliminated by designing for h FE ≥ 200 and C TC /C TE ≥ 5. Array performance correlates well with the predicted characteristics and has led to improved reading speeds greater than 50 words per minute.
GTTI 2008: sessione Trasmissione Numerica Non-binary LDPC codes with good performance on channels afiected by bursty noise

Non-binary Reed-Solomon (RS) codes represent a typical way to counteract the efiects of error bursts in hard-disk drives (HDD). Recently, it has been demonstrated how q-ary low-density paritycheck (LDPC) codes can outperform RS codes through a proper construction of the parity check (PC) matrix. In this work, two matrix design schemes, based on the main deflnitions of erasure burst proposed in literature, are presented. The performance of generated codes are evaluated on bursty noise channels, in order to highlight the main constraint that has to be taken into account for designing LDPC codes with a good burst error correction capability. The proposed schemes have been evaluated on both AWGN and magnetic recording channels in presence of erasure bursts, comparing their coding gain against those obtained by using non-binary RS codes.
Mobile Robot Path Planning and Research in the Improved Artificial Immune Algorithm

Aim at local optimal problem in the path planning of mobile robot by artificial immune algorithm, it is proposed that the improved artificial immune algorithm of mobile robot path planning. Based on artificial immunity algorithm, the potential function method of an artificial potential field is used in this algorithm, improving randomness of the initial population of the artificial immune algorithm, then the algorithm make initial population turn to evolutionary operation through crossover, variance and selection operator to get optimum antibody. The simulation results showed that this algorithm is easy to get the optimal path, at the same time, increasing the speed of the path planning, and the length of the optimal path planning is less 28.5% compare with the traditional immune algorithm.
Compact multidimensional broadband wireless: the convergence of wireless mobile and access

Broadband wireless communications have gained increased interest during the last few years. This has been fuelled by a large demand on high-frequency utilization as well as a large number of users requiring simultaneous high-data-rate access for the applications of wireless mobile Internet and e-commerce. The convergence of wireless mobile and access will be the next storm in wireless communications, which will use a new network architecture to deliver broadband services in a more generic configuration to wireless customers, and support value-added services and emerging interactive multimedia communications. Large bandwidth, guaranteed quality of service, and ease of deployment coupled with the great advancements in semiconductor technologies make this converged wireless system a very attractive solution for broadband service delivery.
Mobile Student Information System

Purpose – A mobile student information system (MSIS) based on mobile computing and context‐aware application concepts can provide more user‐centric information services to students. The purpose of this paper is to describe a system for providing relevent information to students on a mobile platform.Design/methodology/approach – The research followed a design science approach, including surveys to argue for the relevance of the system and evaluation of different versions of the system using a mobile system acceptance model (MSAM). Findings – It was found that the intention to use such services is high, in particular relative to services providing information based on localization and the personal schedule and interests of the student.Originality/value – Several mobile systems exist that provide generic campus information for students and this paper describes one of the few systems of this sort of personalization which have been evaluated.