Miracle-dz/UniFAR-FTUs huggingface dataset:
Dynamic Modeling and Control of a 6-DOF Parallel-kinematic-mechanism-based Reconfigurable Meso-milling Machine Tool

In this thesis, a methodology for rigid body dynamic modeling and control design is presented for a 6 degree-of-freedom (DOF) parallel-kinematic-mechanism-based reconfigurable meso-milling machine tool (RmMT) with submicron tracking accuracy requirement. The dynamic modeling of the parallel kinematic mechanism (PKM) is formulated using the Lagrangian method with the application of principle of energy equivalence and coordinate transformations to separate the mechanism into serial sub-systems. The rigid body gyroscopic force is also modeled using this approach and its effect as a disturbance is analyzed and compensated. The contour errors for both position and orientation are formulated to increase machining accuracy. The dynamic model of the system is linearized through feedback linearization and the contour error based feedback control law is formulated using the convex combination design approach to satisfy a set of design specifications simultaneously. The dynamic model and its control methodology are simulated and verified within the MATLAB Simulink environment.
A Simple Strategy of Controlling a Balanced Voltage Capacitor in Single Phase Five-Level Inverter

The five-level inverter has been used for many applications in renewable energy systems. Even though its harmonic distortion was lower than the conventional two-level inverter. The five-level converter has some disadvantages such as increasing power semiconductor, complex pulse width modulation control methods, and problem with the voltage balancing of the capacitor. This paper aims to propose a modified five-level inverter based on sinusoidal pulse width modulation using phase shifted carrier to enhancing the capacitor voltage balancing. This modified five-level inverter reduces the overall cost and the complexity of the pulse width modulator. Thus making the proposed control system highly simple. The performance and its controller were validated by means of standard laboratory equipments. The analysis, simulation and implementation result showed better performance of five-level inverter.
Infrared image compression using subband coding in the wavelet domain

Infrared (IR) imaging has become one of the most important image sources and is used now in many different applications. Thus, the compression of IR images is very important for the transmission and storage purposes. The application of the subband coding in the wavelet domain (SCWD) to IR images is shown to be a good tool to reduce the image redundancy. In this paper, the SCWD is applied to IR images with one and two levels of decomposition and the results are compared with a standard image. The application of the SCWD to IR images gives a bit rate of 1.25 bpp with very high PSNR and excellent perceptual quality. Also, a bit rate of 0.312 bpp is obtained with high PSNR and very good perceptual quality of the reconstructed image.
Real-Time Stress Detection by Means of Physiological Signals

the recent years, a number of recognition and authentication systems based on biometric measurements have been proposed. Algorithms and sensors have been developed to acquire and process many different biometric traits. Moreover, the biometric technology is being used in novel ways, with potential commercial and practical implications to our daily activities. The key objective of the book is to provide a collection of comprehensive references on some recent theoretical development as well as novel applications in biometrics. The topics covered in this book reflect well both aspects of development. They include biometric sample quality, privacy preserving and cancellable biometrics, contactless biometrics, novel and unconventional biometrics, and the technical challenges in implementing the technology in portable devices. The book consists of 15 chapters. It is divided into four sections, namely, biometric applications on mobile platforms, cancelable biometrics, biometric encryption, and other applications. The book was reviewed by editors Dr. Jucheng Yang and Dr. Norman Poh. We deeply appreciate the efforts of our guest editors: Dr. Girija Chetty, Dr. Loris Nanni, Dr. Jianjiang Feng, Dr. Dongsun Park and Dr. Sook Yoon, as well as a number of anonymous reviewers.
FPGA-based Internet protocol firewall chip

We present the design of a firewall for IP networks using a field-programmable gate array (FPGA). The FPGA implements, in hardware, the accept or deny rules of the firewall. A hardware-based firewall offers the advantages of speed over a software firewall, in addition to direct interfacing with network devices, such as an Ethernet or a serial line transceiver. This paper shows how the rules are translated to VHDL and then implemented in hardware, and how the hardware is utilized to filter network traffic in a packet-by-packet fashion, or based on connection information, with a speed of more than 500,000 packets per second.
The dynamics of invariant object and action recognition in the human visual system

Humans can quickly and effortlessly recognize objects, and people and their actions from complex visual inputs. Despite the ease with which the human brain solves this problem, the underlying computational steps have remained enigmatic. What makes object and action recognition challenging are identity-preserving transformations that alter the visual appearance of objects and actions, such as changes in scale, position, and viewpoint. The majority of visual neuroscience studies examining visual recognition either use physiology recordings, which provide high spatiotemporal resolution data with limited brain coverage, or functional MRI, which provides high spatial resolution data from across the brain with limited temporal resolution. High temporal resolution data from across the brain is needed to break down and understand the computational steps underlying invariant visual recognition. In this thesis I use magenetoencephalography, machine learning, and computational modeling to study invariant visual recognition. I show that a temporal association learning rule for learning invariance in hierarchical visual systems is very robust to manipulations and visual disputations that happen during development (Chapter 2). I next show that object recognition occurs very quickly, with invariance to size and position developing in stages beginning around 100ms after stimulus onset (Chapter 3), and that action recognition occurs on a similarly fast time scale, 200 ms after video onset, with this early representation being invariant to changes in actor and viewpoint (Chapter 4). Finally, I show that the same hierarchical feedforward model can explain both the object and action recognition timing results, putting this timing data in the broader context of computer vision systems and models of the brain. This work sheds light on the computational mechanisms underlying invariant object and action recognition in the brain and demonstrates the importance of using high temporal resolution data to understand neural computations.
LVDS I/O buffers with a controlled reference circuit

A controlled reference circuit maintains the output voltage levels and current values of an LVDS output buffer constant over (PVT) processing, voltage supply, and temperature variations. The reference circuit requires one external resistor and generates two DC control voltages which are applied to all output buffers. An on-chip resistance is described which maintains a tightly controlled impedance of approximately 100 /spl Omega/ over the common mode range of 0 to 2.4 V. A measured waveform at 1.244 Gb/s is given.
Biorobotics: Methods and Applications

Animal-like robots are playing an increasingly important role as a link between the worlds of biology and engineering. The new, multidisciplinary field of biorobotics provides tools for biologists studying animal behavior and testbeds for the study and evaluation of biological algorithms for potential engineering applications. This book focuses on the role of robots as tools for biologists. An animal is profoundly affected by the many subtle and complex signals within its environment, and because the animal invariably disturbs its environment, it constantly creates a new set of stimuli. Biorobots are now enabling biologists to understand these complex animal-environment relationships. This book unites scientists from diverse disciplines who are using biorobots to probe animal behavior and brain function. The first section describes the sensory systems of biorobotic crickets, lobsters, and ants and the visual system of flies. The second section discusses robots with cockroach motor systems and the intriguing question of how the evolution of complex motor abilities could lead to the development of cognitive functions. The final section discusses higher brain function and neural modeling in mammalian and humanoid robots.
Determinants of relative weight and body fat distribution in an international perspective

textabstractOverweight can be defined as excess storage of body fat in an individual. In adult men with a "normal" weight, the percentage of body fat is about 15-20%. In women this percentage is higher, about 25-30%. In spite of the fact that differences in weight between individuals are only partly due to variation in body fat, indices based on relative weight (such as body mass index (EM! ), defined as weight (kg) divided by the square of height (m'» are most often used to measure the degree of overweigh! It has been shown that there is a very good correlation between BMI and the percentage of body fat in large populations I, and therefore the use of BMI to measure the degree of overweight in popUlations is justified. Overweight is generally defined as BMI equal to or higher than 25 kg/m', and obesity as BMI equal to or higher than 30 kg/m'. These cut-off points have been recently incorporated in the WHO Expert Committee recommendation for the classification of overweight '. The WHO report names the first as grade I overweight and the laller as grade 2 overweight, but these terms have not spread to a wider use. In the following, the term overweight will be used to refer both to overweight and obesity when not referring to obesity alone.
Power efficient MAC protocol for multihop radio networks

In this paper we develop a new multi-access protocol for multi-hop radio networks. The unique feature of our protocol is that it is energy conserving. Radios that are not actively transmitting or receiving a packet power themselves off. The manner in which nodes power themselves off does not influence the delay or throughput characteristics of our protocol. Simulation results indicate that power savings of between 10% and 70% are attainable in most systems.
Combining negative selection with immune K-means algorithm for improving the support vector machines method

This paper presents a novel method of using the ideas from Artificial Immune Systems for improving the performance of the Support Vector Machines. By means of Immune K-Means algorithm a set of artificial data is generated based on the original training data. The artificial data describes the most important information from the classifiers learning point of view the information about the boundaries among the classes remain in the artificial data. Combining the Immune K-Means algorithm with Negative Selection methods allows for further improvements of the artificial data set. The proposed approach allows to speed up the learning process of SVM when the training data set is large by extracting the most important information first. The proposed method can also be used as a data compression, especially suited when the information about boundaries among classes is an important issue. The artificial data can be created once and then used for parameters tuning of different classification methods, speeding up the learning process.
A rule warehouse system for knowledge sharing and business collaboration

In collaborative e-business, the business rules of different business partners need to be shared electronically and be used to solve business problems collaboratively. To achieve this, a neutral knowledge representation is needed to translate heterogeneous rules into the neutral representation so that: (1) Pair wise translations between rule representations can be avoided. (2) The collection of rules can be verified to identify inconsistencies, redundancies, and non-termination conditions. In this dissertation, we describe the design and implementation of a Rule Warehouse System (RWS), which allows heterogeneous business rules to be imported and transformed into the neutral knowledge representation, verified to eliminate rule anomalies, and exported for use by some existing rule systems to support collaborative e-business applications. An Active Object Model is used as the neutral knowledge representation for different types of rules commonly recognized in the literature, and several algorithms are developed and implemented for the detection of rule anomalies. The verification process first converts all types of rules into an event-and-action-oriented representation. An algorithm is then applied on the set of transformed rules to detect non-termination conditions. Next, the same set of rules is partitioned based on their associated events before applying algorithms on each partitioned subset to detect inconsistencies and redundancies. These algorithms take into consideration the side effects of methods can be called in rules. An important benefit of an RWS is to integrate the knowledge acquired from different sources to solve problems that cannot be solved by using the knowledge and the rule engine of an individual source. In this dissertation, we describe our work on the integration of a deductive rule engine with an event-and-action-oriented rule engine to demonstrate collaborative problem-solving by using both constraint-oriented and event and-action-oriented rules.
Researching Language and Social Media: A Student Guide

Social Media is fast becoming a key area of linguistic research. This highly accessible guidebook leads students through the process of undertaking research in order to explore the language that people use when they communicate on social media sites. This textbook provides: An introduction to the linguistic frameworks currently used to analyse language found in social media contexts An outline of the practical steps and ethical guidelines entailed when gathering linguistic data from social media sites and platforms A range of illustrative case studies, which cover different approaches, linguistic topics, digital platforms, and national contexts Each chapter begins with a clear summary of the topics covered and also suggests sources for further reading to supplement the initial discussion and case studies. Written with an international outlook, Researching Language and Social Media is an essential book for undergraduate and postgraduate students of Linguistics, Media Studies and Communication Studies.
Why are we so sure we know what a word is

We all know what a word is. Yet describing and defining the word is far from easy. So, what is the source of our intuition? Is the word a universal concept across human languages? Is it a cognitive necessity, enabling us to express our ideas using small recombinable units? Or are our intuitions more superficial, reflecting only the convention of where spaces are placed in writing? This chapter argues that the concept of the word looks vague because it is inherently so, and that our intuition is fooled into seeing greater definition by the twin influences of orthography and the noun as a strong prototype. With only some conventional word classes rendering truly independent units, writing imposes word breaks that don’t always have much psychological reality. The consequence for linguistic theory is significant: a major difference between what the language learner knows and what corpora of texts can capture.
A model-based active-adaptive controller for thermoacoustic instability

Active control of thermoacoustic instabilities in continuous combustion processes is desirable for operating at conditions of low NOx, high performance, and high efficiency. We have previously developed a model-based approach for active control design by taking into account underlying acoustics and heat release dynamics. While this model captures a number of the dominant dynamic features of a premixed laminar combustor, there are a number of uncertainties associated with it as well. In this paper, we study the sensitivity of this model with respect to parametric uncertainties, and the efficacy of a fixed control design for suppressing pressure oscillations. We show that under certain conditions, the fixed controller is inadequate and present a self-tuning controller which is capable of delivering the desired performance in the presence of these uncertainties. The controller proposed is based on a rigorous analytical foundation, and is shown through simulation results to lead to better performance than corresponding fixed controllers.
Unconscious advertising effects

Most traditional advertising effect models are based on the premise that advertising is attended to and processed consciously. However, recent neuroscientific research shows that most information is unconsciously attended to, processed, and stored in memory. The concept of unconscious processing is very interesting for an advertising landscape that is challenged by a growing amount of messages being sent and the declining consumer attention rates.
Vowel recognition and (adaptive) speaker normalization

In automatic and human speech recognition alike, there is the unsolved problem of non-uniqueness in speech production because of many sources of more or less systematic variability (global and local context, speakers, style, communication channel, etc.) versus the supposed fixed distributional variance in template-based recognition. This paper concentrates on acoustic vowel recognition (neglecting language modeling) and various ways of extrinsic and intrinsic adaptive speaker normalization. We used such methods as discriminant analysis, Procrustes transform, feedforward neural nets and adaptive resonance theory networks. One of the problems is to optimize fast learning, adapting and generalizing on the basis of small amounts of new information, versus not forgetting acquired knowledge too quickly. For training and testing we used Dutch databases of vowels spoken by men, women and children, plus the vowel segments from the American-English TIMIT database with 438 male and 192 female speakers.
An error-correcting line code for a HEP rad-hard multi-gigaBit optical link

This paper presents a line encoding scheme designed for the GBT ASIC, a transceiver under development for a multigigabit optical link upgrade of the TTC system. A general overview of issues related to optical links placed in radiation environments is given, and the required properties of the line code discussed. A scheme that preserves the DC-balance of the line and allows forward error correction is proposed. It is implemented through the concatenation of scrambling, a Reed-Solomon error-correction scheme and the addition of an error-tolerant DC-balanced header. The properties of the code are verified for two different interleaving options, which achieve different error correction capability at different implementation costs. One of the two options was implemented in a fully digital ASIC fabricated in a 0.13 μm CMOS technology, and ASIC implementation details and test results are reported.
Intelligent Techniques of User-Oriented Recognition of Objects from the Web Informational Resources

The idea of applying Semantic Web intelligent techniques to the recognition of information objects has resulted in a number of recent research activities and initiatives. The ontologies can be used to represent personalized, user-oriented and problem-oriented knowledge about structure of intelligent information objects in distributed Web-based applications. This article proposes the methods of ontology use for recognition of information about information objects with complex structure that are relevant to user needs
Effects of Auditory Cues for Linear and Differential Magnification Methods on Visual Inspection Performance

The unfavorable consequence of biased attention to peripheral objects was reported with the use of a newly proposed differential magnification method by the authors. Given the favorable influence of auditory cueing on attention orientation, this study investigated the effectiveness of auditory cues in directing participants’ attention from the peripheral to foveal areas of the differential magnifying lens for improving inspection performance. Thirty‐nine Chinese undergraduates performed a simulated inspection task using a particular magnification method (between‐participant factor). Three within‐participant factors of auditory cue interval, target difficulty, and magnification power were tested. Objective performance measures of speed and accuracy and subjective evaluation using NASA task load index were collected and analyzed. The results showed that positive effects of auditory cues were found for the differential magnification methods but not for the traditional linear magnification method. Significant effects of target difficulty and magnification power were also found. It was concluded that the aid of auditory cues, which did not share the same attentional resource with the visual inspection task, proved to be an appropriate reminder for the differential magnification methods to improve participants’ visual inspection performance. Attention should also be paid to selecting an appropriate auditory cue interval for search tasks of different target difficulties. The findings of this study have implications for the design of video magnifiers in the context of multimodal human–machine interfaces.
A System Area Network Characterization In A Commercial Cluster

and have found that it is complete and satisfactory in all respects, and that any and all revisions required by the final examining committee have been made. Abstract Commercial computer clusters have become an essential element in information system centers around the world. Cluster installations are now pervasive in the commercial marketplace. Clusters are deployed to provide both continuous availability and horizontal growth. Continuous availability is essential in mission critical applications where twenty-four hours a day, seven days a week availability is required for business survival. Horizontal growth provides both incremental expansion and increases in maximum capacity and performance. In order to continue to meet the customer cluster needs into the future, reductions in inter-system communication latencies are required. This thesis presents measured data collected from a client/server test environment using a commercially available IBM AS/400 computer. This measured data is then analyzed to identify inter-system communication latency bottlenecks. Finally, a System Area Network is proposed that reduces the inter-system communication latency. The proposed System Area Network provides increases in link bandwidth and reductions in transmission backpressure. This System Area Network provides a key component which will assist in improving the benefits of commercial clusters well into the next decade.
An exposure guided background subtraction for smart camera

An exposure guided background subtraction (EGBS) model is proposed for smart cameras to handle illumination change due to auto-exposure in visual surveillance. To reduce false foreground pixels caused by auto-exposure, EGBS compensates background illumination directly utilizing the information generated by auto-exposure module without extra illumination change estimation. Hence, it is very preferable for smart camera without any extra hardware resources. Experimental results indicate the proposed model efficiently reduces false foreground pixels caused by auto-exposure.