Miracle-dz/UniFAR-FTUs huggingface dataset:
A Robust Vision Module for Humanoid Robotic Ping-Pong Game

Developing a vision module for a humanoid ping-pong game is challenging due to the spin and the non-linear rebound of the ping-pong ball. In this paper, we present a robust predictive vision module to overcome these problems. The hardware of the vision module is composed of two stereo camera pairs with each pair detecting the 3D positions of the ball on one half of the ping-pong table. The software of the vision module divides the trajectory of the ball into four parts and uses the perceived trajectory in the first part to predict the other parts. In particular, the software of the vision module uses an aerodynamic model to predict the trajectories of the ball in the air and uses a novel non-linear rebound model to predict the change of the ball's motion during rebound. The average prediction error of our vision module at the ball returning point is less than 50 mm - a value small enough for standard sized ping-pong rackets. Its average processing speed is 120fps. The precision and efficiency of our vision module enables two humanoid robots to play ping-pong continuously for more than 200 rounds.
A model of routine lifetime optimization with linguistic knowledge in wireless ad-hoc networks

Ad-hoc On-Demand Distance Vector (AODV) routing protocol has been and continues to be a very active and fruitful research protocol since its introduction in the wireless ad-hoc networks. AODV uses a static value for its route lifetime parameter called Active Route Timeout (ART) which indicates the time that the route can stay active in the routing table. Route lifetime may be more accurately determined dynamically via measurement, instead of static value. To accomplish this, the fuzzy logic system is used to obtain adaptive values for ART depending on the situation of the transmitter and intermediate nodes. To study the effect of various parameters on ART, three design methods for fuzzy ART are proposed here, namely: fuzzy-SKP, fuzzy- Power, and fuzzy-Comb. Analysis shows that the proposed design methods are quite efficient and superior to the conventional design method with respect to routing overhead (25%) and average end-to-end delay (41%). Hence, the proposed fuzzy system is able to optimize ART efficiently.
Low-delay embedded 3D wavelet color video coding with SPIHT

In this paper, a modification of the 3D SPIHT, which is the 3D extension to image sequence of 2D SPIHT still image coding, is presented in order to allow more flexibility in choosing the number of frames to be processed at one time by introducing unbalanced tree structure. Simulation shows that 3D SPIHT with reduced coding latency still achieves coding result comparable to MPEG-2, and exhibits more uniform PSNR fluctuations. In additional extension to color video coding is accomplished without explicit rate-allocation, and can be used to any color-plane representation.
A Novel Approach for Route Determining by Integrating Three Routing Techniques

Mobile Ad Hoc Networks (MANET) is an autonomous collection of mobile users that communicate over relatively bandwidth constrained wireless links. Since the nodes are mobile, the network topology may change rapidly and unpredictably over time. The network is decentralized, where all network activity including discovering the topology and delivering messages must be executed by the nodes themselves, i.e., routing functionality will be incorporated into mobile nodes. The routing algorithms can be classified into Reactive and Proactive. A Hybrid algorithm combines the basic properties of reactive and proactive into one. The proposed approach is a novel and hybrid (integrated) approach, integrates three different algorithms together and helps to get optimum routes for a particular radio range. The approaches used here are Ant Colony Optimization (ACO), Multi Agent System (MAS) and Position based routing approach. The proposed integrated approach has a relatively short route establishment time while using a small number of control messages which makes it a scalable routing approach. The overhead of this routing approach is inexpensive and also enables to have an alternate route during route failure.
An Optimization Method for Constraint Web Service Composition Based on Fuzzy Petri Net

With the development of Web service theories and technologies, it has been an effective approach to satisfy users’ requirements by service composition. For independent global constraints Web services composition problem, the paper presents an optimization method of Web service composition with constraint using fuzzy Petri net(FPN), which can transforms solving the optimal service composition problem into locating the largest trust value of legal firing sequences in the FPN model. Then we use the cooperative algorithm including simulated annealing and genetic algorithm (SAGA) to find the optimal legal sequences. The experimental results show that the method can not only reduce the time cost, but also find more feasible solutions.
Fully decentralised algorithm for multisensor Kalman filtering

An algorithm that achieves complete decentralisation of the Kalman filter algorithm amongst the sensing nodes of a multisensor system is preserved. This algorithm does not require any form of central processing facility or centralised communications medium. Each sensing node implements its own local Kalman filter to arrive at a partial decision which it then broadcasts to every other node. Each node then assimilates this received information to arrive at its own local estimate of the system state. The algorithm guarantees that each local estimate thus obtained is identical to the estimate that would be obtained if a conventional, completely centralised, Kalman filter were used. Because there is no single central processing node the algorithm is highly resilient to loss of one or more sensing nodes. The fully decentralised nature ensures that it is ideal for implementation on a parallel processing array, such as a transputer network. The algorithm has been tested using a simulated multiperson pursuitevasion game to check the viability. The algorithm has also been implemented on a transputer based array of cameras to perform tracking of an object moving around a room.
Developing Algorithmic Thinking by Inventing and Playing Algorithms

In many cases at school and at universities most of the learners consider the topic of algorithms as hard and not very attractive. Very often the focus of traditional courses is on learning specific algorithms that are considered as important in education or in practice. Often these algorithms are sequential algorithms. We show in contrast to these courses a way of learning principles and concepts of algorithms that is much easier to comprehend by the learners and makes them more fun. The idea is that we do involve as many students as possible in playing algorithms that are moreover usually proposed by them. The task of the teacher is to give proper problem statements and to ask proper questions to keep the students thinking to create working algorithms that solve these problems. The teacher also motivates the students to improve their algorithms to find more efficient solutions. Compared to a theatre play the students have the roles of the actors and the idea deliverers and the teacher has the role of the stage manager.
Placing Text and Icon Labels Simultaneously: A Real-Time Method

This paper presents a method of combining text and icon label placement in a real-time computing environment. The method computes label configurations based on placement properties, cartographic disturbance, and label overlap. The process is divided into four phases. In the first phase, candidate positions of the text labels are chosen. In the second phase, the same is done for the icon labels. The choice of candidate positions is based on cartographic preference and cartographic disturbance. The removal of overlap between labels is solved, in the third phase, by means of a combinatorial optimization technique (simulated annealing). When there are label pairs in conflict that could not be resolved, the fourth and final step is executed to remove one label in the pair. The success of the proposed method lies in the ability to effectively reduce the search space for the combinatorial optimization. A number of strategies for reducing search space have been evaluated in a case study. The results show that a good search-space-reduction strategy will lead to acceptable solutions for text and icon labeling within a limited processing time.
Mobile imagery systems using commercial technology

Considerable improvement in satellite channel capacity utilization is achievable through application of compression technology to military communications, especially secondary imagery systems. Standards activities are producing uniform and powerful compression algorithms. In addition, the NITFS standardizes the format of digital imagery and imagery related data. NITFS incorporates JPEG and will incorporate other compression algorithms in the future. <<ETX>>
COLD STANDBY REDUNDANCY ALLOCATION IN A MULTI-LEVEL SERIES SYSTEM BY MEMETIC ALGORITHM

Reliability improvement problems have much importance in various engineering systems. Real-world engineering systems contain multiple levels. So, a redundancy allocation problem (RAP) is an efficient method to improve the reliability. Different from existing approaches that consider either hot or cold standby redundancy for a component, our approach considers a multi-level cold standby redundancy allocation problem (MLCSRAP). In other words, MLCSRAP is considered for the module and component levels, simultaneously. The units are duplicated by cold standby redundant units. An optimization solution methodology based on a customized memetic algorithm (MA) is presented for obtaining the optimal reliability of configuration multi-level series. The optimal multi-level redundancy allocation provides the improved reliability and lower life cycle cost. The proposed multi-level cold standby redundancy is compared with a multi-level active redundancy. Also, we allocate the cold standby redundancy at all levels using hierarchical genetic algorithm and compare two algorithms together. Finally, the numerical example illustrates how the theoretical results obtained in this paper can be applied.
Building and Solving Macroeconomic Models using WinSolve: Introduction to WinSolve

WinSolve (Pierse 2000) is a computer package for solving and simulating (nonlinear) models. It is a 32 bit Windows program that runs under all Windows platforms. To start the program, click on the WinSolve icon on your computer desktop. A banner screen is displayed briey. Then the main window opens (Figure 1). This is the WinSolve desktop in which you work. At the top of the screen is the menu bar from which commands can be selected, either by clicking with the mouse on the appropriate menu name, or by pressing the key of the rst letter of the menu name while holding down the the Alt key. Below the menu bar is the tool bar. This contains icons that are shortcuts to some of the more popular commands on the menu bar; double clicking on the icon is equivalent to selecting the corresponding command from the menu bar. When an icon is greyed, then that command cannot be selected. On rst startingWinSolve, only two icons are ungreyed.
Fuzzy-metaheuristic methods to solve a hybrid flow shop scheduling problem with pre-assignment

This paper deals with a particular version of the hybrid flow shop scheduling problem inspired from a real application in the automotive industry. Specific constraints such as pre-assigned jobs, non-identical parallel machines and non-compatibility between certain jobs and machines are considered in order to minimise the total tardiness time. A mixed-integer programming model that incorporates these aspects is developed and solved using ILOG Cplex software. Thus, because of the computation time constraint, we propose approximate resolution methods based on genetic and particle swarm optimisation algorithms coupled or not with fuzzy logic control. The effectiveness of these methods is investigated via computational experiments based on theoretical and real case instances. The obtained results show that fuzzy logic control improves the performances of both genetic and particle swarm optimisation algorithms significantly.
Integrating natural language constraints into HMM-based speech recognition

An approach to implementing spoken language systems is discussed. This approach takes full advantage of syntactic and semantic constraints provided by a natural language processing component in the speed understanding task and provides a tractable search space. The results indicate that the approach is a promising one for large-vocabulary spoken language systems. Parse times within a factor of 20 of real time are achieved for high-perplexity syntactic grammars with resulting hidden Markov model recognition computational requirements (2500 active words/frame) that are well within the capability of high-speed multiprocessor computers or special-purpose speech recognition hardware. <<ETX>>
Complications in body contouring stratified according to weight loss method

Background Body contouring procedures following massive weight loss have become increasingly common and, unfortunately, continue to be associated with a high complication rate. Objective To evaluate how weight loss method affects complications following abdominally based body contouring procedures. Methods Patients undergoing abdominally based contouring procedures were retrospectively evaluated over an 11-year period and stratified into two groups based on method of weight loss: diet and exercise; or bariatric surgery. Complications, including seroma, wound dehiscence, skin necrosis, infection, hematoma and venous thromboembolism, were included if they required intervention. An adjusted logistic model was used to examine the effect of weight loss method on aggregate complication rates. Results A total of 307 patients were included: 77 (25%) lost weight through diet and exercise; and 230 (75%) through bariatric surgery. Results from the logistic model showed no difference in complication rates between weight loss methods (OR 1.01 [95% CI 0.51 to 2.02]). However, there was a strong correlation between body mass index at the time of surgery and complication rates (OR 1.05 [95% CI 1.02 to 1.08]; P<0.01). Conclusions The findings reveal no difference in complication rates following abdominal body contouring procedures attributable to method of weight loss. Rather, there was a proportional rise in complication rates in patients with a higher body mass index at the time of surgery. Surgeons and patients should be aware of this trend, and it should be part of any discussion of abdominal body contouring procedures and informing patients of their risk profile.
Real-time dynamic image-source implementation for auralisation

This paper describes a software package for auralisation in inter- active virtual reality environments. Its purpose is to reproduce, in real time, the 3D soundfield within a virtual room where listener and sound sources can be moved freely. Output sound is presented binaurally using headphones. Auralisation is based on geometric acoustic models combined with head-related transfer functions (HRTFs): the direct sound and reflections from each source are computed dynamically by the image-source method. Directional cues are obtained by filtering these incoming sounds by the HRTFs corresponding to their propagation directions relative to the listener, computed on the basis of the information provided by a head-tracking device. Two interactive real-time applications were developed to demonstrate the operation of this software package. Both provide a visual representation of listener (position and head orientation) and sources (including image sources). One focusses on the auralisation-visualisation synchrony and the other on the dynamic calculation of reflection paths. Computational performance results of the auralisation system are presented.
Application of fuzzy neural network to ECG diagnosis

In automated diagnosis of electrocardiographic (EGG) signals, the conventional approach requires a human expert to formulate the rules and has not the ability of learning. A neural network is capable of learning, but it needs large training sets, and its training speed is too slow. In addition, we can not understand thoroughly the knowledge that follows the changes of hidden neurons. All these limits hamper the practical application of neural network to ECG diagnosis. In this study, a fuzzy neural network (FNN) is designed to translate directly the expert knowledge into the neural network structure by using a fuzzy model. Thus, it can be applied to a diagnostic system without training process, and learn from the responding data in the running to improve the accuracy of the system. Thus, it possible to use FNN to interpret the knowledge that hides in the neural network.
Improved digital elevation models via multi-baseline interferometric SAR

This paper presents an extension to interferometric SAR (InSAR), known as multi-baseline InSAR. The technique is based on the use of N>2 SAR imaging flight paths to synthesise an aperture in the normal-to-slant-range (nsr) direction. This leads to the generation of digital elevation models with improved ground-range resolution and elevation accuracy as well as the ability to resolve scatterers in the nsr direction.
Providing Adequate Interactions in Online Discussion Forums Using Few Teaching Assistants

In order to encourage students to participate in online learning forums, prompt responses to their questions are essential. To answer students’ online questions, teaching assistants are assigned to manage discussions and answer questions in online learning forums. To minimize the response time, many teaching assistants may be needed to interact with learners. We investigated the trade-off between the request-response time and the cost of labor for handling the requests since this has become a challenging and important issue for education managers. In this study, a queuing-based model is proposed to construct the relationship between response time and the human resource requirement in a learning forum. In addition, an experiment using students in a Computer Science
Study on Word Alignment for Reordering of Web-mined OOV Translation Candidates

Web information retrieval technology has been widespread concerned by researchers. Web-based search of the OOV Translation Mining has also become hot spots. In this paper, the re-ordering of OOV translation candidates is studied, which is the result of web mining. Automatic word alignment technology is used to calculate the weighted points for each candidate then sort the results, with the closely right candidate to be top ranking. The approach can make good performance in such aspects like equal frequency or low frequency circumstances. We take some OOV phrases in different fields as test corpora for web mining, and evaluate out the method on it, and the result is encouraging.
A statistical analysis of the power control error in fast Rayleigh fading

The effect of fast multipath fading on power control is analysed for a mobile telephone system. A new statistical model for the single path, Rayleigh faded channel is presented. From this model the probability for the relative change in signal amplitude at different time delays and mobile speeds is determined. The maximum time delay allowed for a desired accuracy in the loop may then be found.
Scalable partitioning-driven algorithms for solving complex and emerging problems in vlsi physical design automation

This dissertation presents a number of extensions and applications of multilevel hypergraph-partitioning algorithms for solving some of the emerging, as well as the existing complex problems in the physical-design-automation phase of electronic circuit fabrication. The technology used in electronic circuit fabrication evolves very rapidly, and as a result, it presents a number of challenges in automating the tasks involved. The key challenges are in (i) devising scalable algorithms to handle exponentially increasing design sizes, (ii) devising new algorithms to effectively counter undesirable but inevitable effects associated with the shrinking geometries of electronic circuit manufacturing technologies, and (iii) devising algorithms to solve new problems that arise because of the evolving architectures of pre-fabricated chips, such as FPGAs. This dissertation advocates the use of multilevel hypergraph-partitioning algorithms, as the underlying tools to accommodate scalability requirements because of their availability, near-linear scalability and other desirable properties, such as cut quality of the solutions generated and run time. This dissertation identifies two new partitioning problems; minimizing maximum subdomain degree and cut of k-way partitioning and multi-resource aware partitioning, and proposes effective algorithms for solving them. In addition, this dissertation enhances the primary application of partitioning—placement—by proposing two inventions, namely “bounding box aware terminal propagation” and “perimeter-degree”. These are used for improving the accuracy of the objective minimized in partitioning-driven placement methods and for identifying congestion prone clusters in multilevel placement algorithms, respectively.
Synchronous multi-user multi-carrier CDMA communication system with decorrelating interference canceler

Multi-carrier (MC) multi-user CDMA is a new transmission method in which every user bit is sent simultaneously over multiple subcarriers (or multiple tones), each of which has a time-constant 0 or /spl pi/ phase offset. The offsets corresponding to each user form a unique code signature sequence, orthogonal to those of any other user, or pseudo orthogonal as with Gold codes or Kessami code sequences. We address a moderately dispersive channel in which each user-subcarrier channel has a different random amplitude and phase. We estimate the performance of a receiver matched to such a multicarrier, multi-user scheme. Then we implement a decorrelating interference canceler at the output and examine its effect on performance.
Blind Detection with Deterministic Arrange and Scale to Underwater Acoustic Source

t is a valid anti-interference method that blindly separates the contaminated radiant acoustic source object from interferences, but the separated radiant acoustic source object with arrange and scale ambiguity makes the likelihood ratio detection impossible. This paper solves the ambiguity problems by utilizing the correlation and energy consistency of the same source in the same overlapped frame data; Known delay distance, data sum length and signal to noise ratio (SNR), the paper analyzes algorithms performance and draws the receiver operating characteristic (ROC) curve in different distance, which offers an accord to design detector parameters in different false alarm probability and detection probability.
A Low Memory Cost Fast Retrieval Method Based on Bucket Map Chain

To reduce the high memory cost of fast retireval method, we present a fast retrieval method based on bucket map chain on the basis of Exact Euclidean Locality Sensitive Hashing (E2LSH). The bucket map chain contains all the points projected from feature space in multiple buckets, which store the nearby points. When conducting query, it searches the chain by the bucket index of query point and locates the position of related buckets, then reads the related points in related buckets and measurs the similarity of these points with query point. The experiments show that this method can efficiently decrease the memory cost of retrieval. It is very important for increasing the feasibility of large scale information retrieval especially image retrieval.