Miracle-dz/UniFAR-FTUs huggingface dataset:
Segmentation of 4D cardiac computer tomography images using active shape models

This paper describes a segmentation method for time series of 3D cardiac images based on deformable models. The goal of this work is to extend active shape models (ASM) of tree-dimensional objects to the problem of 4D (3D + time) cardiac CT image modeling. The segmentation is achieved by constructing a point distribution model (PDM) that encodes the spatio-temporal variability of a training set, i.e., the principal modes of variation of the temporal shapes are computed using some statistical parameters. An active search is used in the segmentation process where an initial approximation of the spatio-temporal shape is given and the gray level information in the neighborhood of the landmarks is analyzed. The starting shape is able to deform so as to better fit the data, but in the range allowed by the point distribution model. Several time series consisting of eleven 3D images of cardiac CT are employed for the method validation. Results are compared with manual segmentation made by an expert. The proposed application can be used for clinical evaluation of the left ventricle mechanical function. Likewise, the results can be taken as the first step of processing for optic flow estimation algorithms.
Novel Filtering Power Divider with External Isolation Resistors

In this paper, a novel filtering power divider with external isolation resistors is presented. The proposed power divider can be considered as an integration of a bandpass filter and a Gysel power divider. Based on the circuit topology, a high‐order filtering power divider can be easily realized. Odd‐ and even‐mode models are employed to analyze the filtering and power splitting functions. For demonstration, a third‐order filtering power divider operating at 1.5 GHz is designed and implemented. The measured results exhibit an isolation between the output ports that is better than 20 dB at around the center frequency.
Shoot Growth, Gamma-Terpinene and Essential Oil Content of Satureja hortensis L. in Response to Foliar Application of FeSO4 and Citric Acid

Background: Summer savory (Satureja hortensis L.) is one of the most important medicinal and spice plants cultivated in many parts of the world. Objective: A greenhouse experiment was conducted to study the effects of FeSO4 and citric acid application on the morphological traits and essential oil content and its component, gammaterpinene in S. hortensis. Methods: FeSO4 in four levels (0, 3, 4 and 5 g L -1 ) and citric acid in four levels (0, 4, 6 and 8 mM) through foliar application were considered as two studied factors in this factorial experiment. Results: The results showed that the treatments of FeSO4, and interaction of FeSO4 and citric acid had a significant effect (p<0.01) on the all studied traits, whereas citric acid treatments only had significant effect on the essential oil content (p<0.01) and plant height (p<0.05). FeSO4 and its interaction with citric acid significantly increased these traits. The optimum level of FeSO4 fertilizer on this plant was 3 and 4 g L -1 and for citric acid was 6 and 8 mM which increased the essential oil content and its component, gamma-terpinene compared to control plants. Conclusion: Foliar application of citric acid plus FeSO4 had the capability to alter the relative percentages of the essential oil content. In general, foliar application of FeSO4 with citric acid had synergistic effect on essential oil content, its component gamma-terpinene and agromorphological traits of S. hortensis.
Research Advancements in Humanoid Compression Garments in Sports

The utilization of sport-related compression garments has attracted a great deal of attention from among Sports Science scholars. The function of the garments, such as to maintain muscle functions, reduce sports injuries and improve athletic performance, has been an issue of debate since the beginning of the new century. In this study, a number of methods including a literature review, logical analysis and mathematical statistics, are used to analyse earlier compression garments research, which can be found by searching hardcopy journals and online databases. Among the existing studies, most have tested and confirmed the functions of the garments; however, only a few have mentioned the underlying mechanism. Thus, by using more advanced and appropriate compression materials, future studies into compression garments will be focused on the vibration characteristics of muscles (soft tissues), and especially on their proprioceptive sensation, neuromuscular control, injury prevention and performance enhancement.
Real-time multimedia tagging and content-based retrieval for CCTV surveillance systems

As the number of installed surveillance cameras increases, and the cost of storing the compressed digital multimedia decreases, the CCTV industry is facing the prospect of large multimedia archives where it may be very difficult to locate specific content. To be able to get the full benefit of this wealth of multimedia data, we need to be able to automatically highlight events of interest to the operator in real-time. We also need to make it possible to quickly identify and retrieve content which meets particular criteria. We show how advances in the Internet and multimedia systems can be used to effectively analyze, tag, store, search and retrieve multimedia content in surveillance systems. IP cameras are utilized for multimedia compression and delivery over the Internet or intranet. The recorded multimedia is analyzed in real-time, and metadata descriptors are automatically generated to describe the multimedia content. The emerging ISO MPEG-7 standard is used to define application-specific multimedia descriptors and description schemes, and to enforce a standard Description Definition Language (DDL) for multimedia management. Finally, a graphical multimedia retrieval application is used to provide content-based searching, browsing, retrieval and playback over the Internet or intranet.
Testing Artificial Neural Network (ANN) for Spatial Interpolation

The aim of this research is to test Artificial Neural Network (ANN) package in GRASS 6.4 software for spatial interpolation and to compare it with common interpolation techniques IDW and ordinary kriging. This package was also compared with neural networks packages nnet and neuralnet available in software R Project. The entire packages uses multi-layer perceptron (MLP) model trained with the back propagation algorithm. Evaluation methods were based mainly on RMSE. All the tests were done on artificial data created in R Project software; which simulated three surfaces with different characteristics. In order to find the best configuration for the multilayer perceptron many different settings of network were tested (test-and-trial method). The number of neurons in hidden layers was the main tested parameter. Results indicate that MLP model in the ANN module implemented in GRASS can be used for spatial interpolation purposes. However the resulting RMSE was higher than RMSE from IDW and ordinary kriging method and time consuming. When compared neural network packages in GRASS GIS and R Project; it is better to use the packages in R Project. Training of MLP was faster in this case and results were the same or slightly better.
Product Images Classification with Mul-tiple Features Combination

Visual-based automatic product image classification is a great need and challenge work for e-commerce field. Previous work tested few number product categories with one or two descriptors. For the task of product classification over large number categories, we employed kernel-based SVM classifier combining multiple features, including one global descriptor and three complimentary local descriptors. Furthermore, we investigate four ways to combine discriminative features for SVM classifier. Experiments on the product image dataset (PI 100) showed the performance improved significantly by features fusion.
Optimum design of single-sided linear induction motor using the neural networks and finite element method

A new method for the optimal design of a single-sided linear induction motor (SLIM) is presented. The method utilizes the neural network and finite element method for optimizing the design parameters of SLIM. The finite element analysis is used to produce a variety of neural network training data and the neural network is used for optimizing the design parameters by sequential unconstrained minimization technique. As a result, it is shown that the novel method is very efficient and accurate as an optimization technique.
[Prevalence and Correlates of Substance Use in 5,688 Vocational School Students].

OBJECTIVE The aim of this study was to investigate the prevalence of substance use of German apprentices in vocational schools, considering socio-demographic characteristics and vocational field. METHODS Cross-sectional study of 5,688 first year apprentices. These were 5,001 apprentices from 34 schools of the "Dual System" and 687 students from 15 vocational schools of the social and health sector. Sociodemographic characteristics and prevalence of tobacco, alcohol, cannabis, other illegal drugs, and pharmaceuticals were assessed. There was also a screening for problematic alcohol and cannabis use. The paper-pencil survey was conducted by trained research staff in 7 German federal states from September to December 2012. RESULTS Half of the apprentices (49.9%) used tobacco in the 30 days prior to questioning, 40.7% reported daily smoking. Alcohol use in the past 30 days was reported by 68.9%, 45.0% of the sample had a positive screening result for problematic alcohol use. Prevalence rates for the use of cannabis and other illegal drugs in the last 30 days were 7.5% and 2.6%, taking pharmaceuticals was reported by 20.7%. Significant correlates of substance use were gender and socio-economic status. Differences between vocational clusters were also found, with higher average rates in service-based and commercial-technical professions. However, these differences could mostly be explained by sociodemographic differences in the composition of the vocational clusters. CONCLUSIONS Use of psychotropic substances is a widespread activity in German apprentices. Prevalence rates are higher than in the same age total population. The highest proportion of variance was explained by differences in gender and socio-economic status.
Study on Heuristic Search in Information Retrieval Using Bayesian Networks

This paper proposes a Bayesian networks technique and a heuristic search method for retrieving the most relevant documents, by combining the user profiles with the document details in matching the given query words. This proposed technique helps users to retrieve the documents in the descending order relevant to their needs, as the users can specify their requirements through a set of query words of interests along with heuristic information regarding the required documents. This technique stores heuristic information in both document profiles and user profiles. Then Bayesian networks are used to order documents in the descending order of users' relevancy. We have completed the experiment with 850 document records in the faculty library. Experimental results show that there are two factors that might have some effects on the results. The first factor is the sampling of the documents by the system itself and the second factor is the document number relevant to the users' needs.
Live Random Concepts and Sight-Reading Players: The Role of the Computer in the Era of Digested Digitalism

The author's three compositions discussed here create live performances comprised of sound events of determined, foreseeable variability with the aid of a computer. Performers have laptops in front of them; their predominant role is score synthesis, not sound production. What the monitor shows must be sight-read and realised musically ad hoc on stage. A fixed, overarching time grid within the software generates the piece's formal structure by determining section lengths as well as the total duration of the performance. Different renderings of the same piece share recognizable features, but details within this general framework are created afresh in real-time by the computer. These changes create a situation in which the musician is sight-reading live and result in a performance that lies somewhere between a traditional composition and improvisation.
Overview of three-dimensional shape measurement using optical methods

We first provide an overview of 3-D shape measurement us- ing various optical methods. Then we focus on structured light tech- niques where various optical configurations, image acquisition tech- niques, data postprocessing and analysis methods and advantages and limitations are presented. Several industrial application examples are presented. Important areas requiring further R&D are discussed. Finally, a comprehensive bibliography on 3-D shape measurement is included, although it is not intended to be exhaustive. © 2000 Society of Photo-Optical Instrumentation Engineers. (S0091-3286(00)00101-X)
Design of 3D Space Following Positioning System Based on ZigBee

The research on positioning system and spatial alignment is a big topic. In this paper, we proposed a design (that) studies two issues. One is the study of range positioning algorithm based on ZigBee communication system. The other one is spatial alignment platform which is controlled with two servos. Hardware and software control system was realized, which also consists of two parts, ZigBee network positioning system and automatic orientation platform.
Channel Ranking Based Joint Symbols Detection for MQRD-PCM/MIMO-OFDM

MIMO-OFDM is considered a key technology in emerging high-data rate systems. With MIMO techniques, the transmission quality deteriorates due to co-channel interference (CCI). Several signal detection schemes have been proposed to mitigate this problem. However, it is impractical to use the conventional methods without reducing theirs computational complexity. Previously, we have proposed a parallel detection algorithm using multiple QR decompositions with permuted channel matrix (MQRD-PCM) for MIMO-OFDM to reduce the system complexity. This method achieves a good BER performance with low system complexity. However, since MQRD-PCM is a kind of parallel detection method, the wrong detection probability is increased due to the bad channel SINR of the transmitted signals. As a result, the average BER performance is influenced by the wrong detection probability of the bad channel SINR. To overcome this problem, in this paper, we propose the channel ranking based joint symbols detection for MQRD-PCM/MIMO-OFDM.
Estimation of contact position between a grasped object and the environment based on sensor fusion of vision and force

Robots require various techniques of sensor fusion to achieve effectively manipulation tasks. This paper presents a sensor fusion method of vision and force information to estimate contact position between a grasped object and the other objects in the environment. The technique will be useful especially for assembly tasks since manipulation of an object by using visual information only often falls into difficulties because of the occlusions caused by the grasped object, surrounding objects, and the manipulator itself. In such situations, force sensor information helps to estimate the contact position even when the exact contact position is invisible. Consequently, sensor fusion of vision and force permits to improve adaptability of robot systems to changing situations in the task. Experiments using a robot system demonstrate usefulness of the proposed method. In addition, we address problems of sensor planning to automatically select sensor information taking the fusion of vision and force into account.
Model selection and multimodel inference : a practical information-theoretic approach

The second edition of this book is unique in that it focuses on methods for making formal statistical inference from all the models in an a priori set (Multi-Model Inference). A philosophy is presented for model-based data analysis and a general strategy outlined for the analysis of empirical data. The book invites increased attention on a priori science hypotheses and modeling. Kullback-Leibler Information represents a fundamental quantity in science and is Hirotugu Akaike's basis for model selection. The maximized log-likelihood function can be bias-corrected as an estimator of expected, relative Kullback-Leibler information. This leads to Akaike's Information Criterion (AIC) and various extensions. These methods are relatively simple and easy to use in practice, but based on deep statistical theory. The information theoretic approaches provide a unified and rigorous theory, an extension of likelihood theory, an important application of information theory, and are objective and practical to employ across a very wide class of empirical problems. The book presents several new ways to incorporate model selection uncertainty into parameter estimates and estimates of precision. An array of challenging examples is given to illustrate various technical issues. This is an applied book written primarily for biologists and statisticians wanting to make inferences from multiple models and is suitable as a graduate text or as a reference for professional analysts.
Diode and transistor equivalent circuits for transient operation

Solid-state devices have complex energy storage effects that complicate their transient operation. A frequently used method of analysis is that of charge control. This method relies upon quasi-static equilibrium and may have significant errors for high-speed operation. The method proposed uses a series approximation to a convolution integral solution. The first term of the series is equivalent to charge-control operation and higher order terms provide improved accuracy in terms of lumped elements of an equivalent circuit, but the real merit of the series form is its ready adaptability to computer- programmed node-branch circuits analysis.
IDAC: an interactive design tool for analog CMOS circuits

A design system has been developed which is able to design transconductance amplifiers, operational amplifiers, low-noise BIMOS amplifiers, voltage and current references, quartz oscillators, comparators, and oversampled A/D converters including their digital decimation filter starting from building-block and technology specifications. This design system, called Interactive Design for Analog Circuits (IDAC), is able to size a library of analog schematics (actually more than 40) as a function of technology (p-well and n-well CMOS) and desired building-block specifications. IDAC also generates a complete data sheet, an input file for SPICE2, and an input file for the analog layout program ILAC.
Control of Grid-Connected Quasi-Z Source Inverter Based on Three-States Constant Frequency Hysteresis Current Control

This paper proposes a hysteresis current control method for the grid-connected quasi Z source inverter with three states and constant frequency. The hysteresis band of the inverter is analyzed in detail, and the shoot-through is inserted into the zero state without affecting the grid-connected control. Moreover, the operating states of the switches are discussed. Finally, the feasibility of the proposed topology is verified by simulations and experiments results.
On the Capacities of Spectrum-Sharing Systems with Transmit Diversity

Motivated by recent works on spectrum-sharing systems, this paper investigates the effects of transmit diversity on the peak interference power limited cognitive radio(CR) networks. In particular, we derive the ergodic and outage capacities of a spectrum-sharing system with multiple transmit-antennas. To derive the capacities, peak interference power constraint is imposed to protect the primary receiver. In a CR transmitter and receiver pair with multiple antennas at the transmitter side, the allowable transmit power is distributed over the transmit-antennas to achieve transmit diversity at the receiver. We investigate the effect of this power distribution when a peak interference power constraint is imposed to protect the primary receiver. We show that the transmit diversity does not improve the ergodic capacity compared to the single-antenna system. On the other hand, the transmit diversity significantly improves the outage capacity. For example, two transmit-antennas improve the outage capacity 10 times compared to the singleantenna with a 0 ㏈ interference constraint.
Biologically inspired Metaheuristic Algorithm for solving symmetric TSP

This paper introduces with basic concepts of ant colony optimization and its approach for solving complex optimization problems and a metahueristic algorithm for solving TSP.ACO is inspired from the real ant behavior which use stigmergic communication based on pheromone trails. Ants cooperate using an indirect form of communication mediated by pheromone they deposit on the edges of the TSP graph while building solutions. In this paper we focus on construction of artificial ants, some considerations with experiments. Artificial ants act as agent of solving NP hard problems. In this paper we have considered ACS for solving TSP: Consisting of State Transition rule, local pheromone updating and global pheromone updating and characteristics of ACS. The results show that ACS out performs other nature-inspired algorithms such as simulated annealing and evolutionary computation.
Marketing image categorization using hybrid human-machine combinations

Marketing instruments with nested, short-form, symbol loaded content need to be studied differently. Image classification in the Web2.0 world can dynamically use a configurable amount of internal and external data as well as varying levels of crowd-sourcing. Our work is one such examination of how to construct a hybrid technique involving learning and crowd-sourcing. Through a parameter called turkmix and a multitude of crowd-sourcing techniques available we show that we can control the trend of metrics such as precision and recall on the hybrid categorizer.
Collaborating with computers

The main body of the article explores three questions concerning the collaborative use of computers in classrooms. The first looks at the opinions of the powerful as evidenced by the recent spate of publications concerning the National Curriculum; the second explores the extent to which there exists research evidence to support the position the curriculum makers have taken up; the third reviews the literature for indications as to how teachers are likely to react to their proposals. A fourth question niggles: how does the ‘subjective’ computer fit into the classroom? The article ends in speculationperhaps we need to take a fresh look as to why exactly many teachers remain uneasy in the presence of computers?