Miracle-dz/UniFAR-FTUs huggingface dataset:
Semi Blind Source Separation for Application in Machine Learning

Unsupervised learning is a class of problems in machine learning which seeks to determine how the data are organized. Unsupervised learning encompasses many other techniques that seek to summarize and explain key features of the data. One form of unsupervised learning is blind source separation (BSS). BSS is a class of computational data analysis techniques for revealing hidden factors that underlie sets of measurements or signals. BSS assumes a statistical model whereby the observed multivariate data, typically given as a large database of samples, are assumed to be linear or nonlinear mixtures of some unknown latent variables. The mixing coefficients are also unknown. Sometimes more prior information about the sources is available or is induced into the model, such as the form of their probability densities, their spectral contents, etc. Then the term blind is often replaced by semiblind. This chapter reports the semi BSS machine learning applications on audio and bio signal processing. DOI: 10.4018/978-1-4666-1833-6.ch003
A Theoretical Study of Performance of an Orthogonal Multiplexing Data Transmission Scheme

This paper presents a theoretical analysis of the performance of an orthogonal multiplexing data transmission scheme (parallel transmission scheme) subject to a number of degrading factors normally encountered by a practical operating system. The factors considered jointly are sampling time error, carrier phase offset, and nonideal phase characteristics of transmitting and receiving filters. Performance is measured by the familiar criterion of eye opening of the received data signal. A closed-form expression for the eye opening is obtained. It is shown that the lengthy nonlinear functions in the solution can be closely approximated by simple piecewise linear functions for parameter values of interest. The optimum settings of the sampling time and the carrier phase are determined for given filter phase distortion. Also, considering all factors, simple formulas are developed for computing interchannel interferences, intersymbol interference, and the resulting eye opening. Simple relationships between the eye opening and filter phase distortion are explored, and a concept of parametric eye is introduced to aid in filter design. An illustrative example is considered which shows that the impairment of the system performance is not excessive for a reasonable range of system design parameters.
The Cooperative Defense Overlay Network: A Collaborative Automated Threat Information Sharing Framework for a Safer Internet

With the ever-growing proliferation of hardware and software-based computer security exploits and the increasing power and prominence of distributed attacks, network and system administrators are often forced to make a difficult decision: expend tremendous resources on defense from sophisticated and continually evolving attacks from an increasingly dangerous Internet with varying levels of success; or expend fewer resources on defending against common attacks on “low hanging fruit,” hoping to avoid the less common but incredibly devastating zero-day worm or botnet attack. Home networks and small organizations are usually forced to choose the latter option and in so doing are left vulnerable to all but the simplest of attacks. While automated tools exist for sharing information about network-based attacks, this sharing is typically limited to administrators of large networks and dedicated security-conscious users, to the exclusion of smaller organizations and novice home users. In this thesis we propose a framework for a cooperative defense overlay network (CODON) in which participants with varying technical abilities and resources can contribute to the security and health of the internet via automated crowdsourcing, rapid information sharing, and the principle of collateral defense.
A 10 b 20 MHz 30 mW pipelined interpolating CMOS ADC

A pipelined interpolating ADC which employs a chopper inverter amplifier capable of operating at low supply voltage is described. The DNL (differential nonlinearity) is less than +or-0.5 LSB at 20-MHz conversion frequency. The signal-to-noise and distortion ratio is 55 dB at 1 MHz for a 2 V pp analog input. The INL (integral nonlinearity) is less than +or-1.0 LSB. This ADC dissipates 30 mW with 2.5-V single supply at a 20-MHz conversion rate. The active area is 2.5 mm*2.6 mm in 0.8- mu m CMOS. The input capacitance is 12 pF. <<ETX>>
The Use of Stylometry for Email Author Identification: A Feasibility Study

It is recognized that authors have unique writing styles in which it is possible to find a simple statistical model. This paper makes an attempt to explain the methodology of developing and optimizing a stylometry program which quantifies the writing styles of various authors using 62 stylistic features found in emails. The feature extraction and pattern classification program was developed for a Pace University SSCSIS Doctorate of Professional Studies student, Professor Sandy Westcott who was completing her thesis on stylometry. The C#-based system is used to identify the author of an arbitrary email using stylometry features. Raw keystroke data, collected from an Internet-based Java applet in an earlier keystroke biometric study conducted by Dr. Mary Valliani, was converted into simple text files, appropriate features were extracted and a pattern classifier was implemented.
Selection of an optimal modulation scheme for digital communications over low voltage power lines

There is an ever increasing demand for environmental management of buildings, office automation, security monitoring or remote control of customer appliances and remote meter reading. The AC low voltage power line would be an ideal communications medium for digital data. Several systems for power line communications (PLC) were presented. The reliability of PLC is strongly influenced by time-variant and frequency-selective attenuation and interference on the power line channel. Various experiments were made to evaluate different PLC systems and set up a channel model. This paper gives a short summary of typical transfer characteristics and interference to be observed at power line networks. It is shown that at transmission over a single phase of the power supply system the maximum phase jitter of the time-variant transfer function is in most cases below 90/spl deg/. In the second part important modulation schemes are evaluated for applicability to power line communications. This evaluation considers chirp modulation, direct sequencing phase shift keying modulation (PN/PSK) and hopping techniques with spectral redundancy given by carriers with M different frequencies. The selection of the optimal modulation technique considers the European standard EN 50065, which restricts both the frequency range and the maximum signal amplitude. This paper deals with modulation schemes, using M frequencies, namely classic frequency hopping modulation (MFH) and the multifrequency,phase modulation (MFH/PSK and MF/PSK). Significant advantages of M frequency phase modulation in comparison with classic frequency hopping are pointed out.
An Approach of Multiple-Quality Segment Protection Based on p-Cycle for the Optical Multicast

Abstract In the optical multicast network, node and link failures have much important influence on the network survivability. A node failure or link failure may lead to multiple destination nodes can not receive data. A multiple-quality segment protection approach based on pre-configured cycle (p-Cycle) was presented to improve the link utilization and reduce the delay of high priority multicast in the paper. Simulation results showed that the segment protection approach under p-Cycle could ensure the 100% full protection of node and link failures, and high-priority traffic has less propagation delay.
Adaptive rate control scheme for handoff and its performance evaluation in mobile multimedia networks

An adaptive rate control scheme based on QoS priority for handoff success in WCDMA networks is proposed. Our scheme improves the call drop rate by adaptively managing the data rates of existing lower priority users when resources are insufficient. We describe a way that a resource can be dynamically allocated. We evaluate the performance variation in terms of a system capacity and a call dropping probability and the delay of downgraded traffic by the proposed scheme. The results show our scheme increases system capacity and decreases the call dropping probability at the cost of small delay of the data traffic. The proposed scheme has a better system utilization than guard channel (GC) scheme and it can be implemented independently of GC scheme for maximizing system performance. This scheme can also be used for the call admission control (CAC) to decrease call blocking and improve handoff control.
Register renaming and dynamic speculation: an alternative approach

Presents a novel microparallel taxonomy for machines with multiple-instruction processing capabilities including VLIW, superscalar, and decoupled machines. The taxonomy is based upon the static or dynamic behavior of four abstract, operational stages that an instruction passes through. These stages are fetch, decode, execute, and retire. This two valued, four variable taxonomy results in sixteen ways that a processor's microarchitecture can be specified. The paper categorizes different machine instances that are either actual implementations or proposed systems within the taxonomy framework. Four new processor microarchitectures are postulated which provide additional features and are instances of the remaining unexplored microparallel classifications. <<ETX>>
Colour-encoded structured light for digitisation of real-time 3D data

The paper describes the implementation of a colour-encoded structured light 3D digitiser to be used to measure the human face during continuous speech. The algorithms currently used to give results on static, lightly coloured objects are outlined, including a novel method of stripe identification using an extension of minimum cost-matching for strings. Visually acceptable results are shown, and ongoing work is described. >
The Karlsruhe dextrous hand: grasp planning, programming and real-time control

In this paper the framework of an intelligent control system of a multi-finger robot hand is described, that is especially tailored for sensor-based object handling and assembly. The research has concerned with the Karlsruhe dextrous hand, a modular three-finger hand with 9 degrees of freedom, independent finger modules and integrated sensors. The total system structure consists of three embedded subsystems, with a planning and supervisory system on the top, which has a blackboard-like architecture to exchange information with a distributed real-time control system that provides force/position control strategies for dextrous grasping and manipulating of arbitrary objects. A programming and simulation system supports the object/task-based description of all robot and gripper actions required to perform a specific operation. <<ETX>>
Prediction of the space-frequency correlation function for base station diversity reception

A model is proposed to estimate the signal statistics for urban-area base stations with highly elevated antennas. Based on the model, the envelope correlation of the received signal is estimated in the case of hybrid space-frequency diversity reception at the base. It is shown that the spatial correlation or the complex signals is determined of the mean angle of arrival and the width of the incoming beam. Useful closed-form approximations for inline and broadside antenna orientations are obtained. Comparisons between the theoretical model and available experimental data provide adequate justification for the model. It is shown that the lowest spatial correlations among all the possible angular orientations an obtained when the mean direction of the incoming signals is perpendicular to the axis of the base antennas. For this case, an antenna separation of 26/spl lambda/ is required to achieve an envelope correlation of 0.7 when the width of the incoming beam is 0.7/spl deg/, and this separation reduces to 9/spl lambda/ for a width of 3/spl deg/. The results indicate that the required spacings can be further reduced by using frequency diversity in conjunction with space diversity. Generalization of the model to incorporate local scattering effects is also proposed.
AQM-based audio steganalysis and its realisation through rule induction with a genetic learner

Steganography, the means for covert communication, creates a potential problem when it is misused for planning criminal activities. Differentiating anomalous audio document from pure audio document is difficult. This paper presents a Genetic Algorithm based approach to audio steganalysis. The basic idea is that the various audio quality metrics calculated on cover audio signals and on stego audio signals vis-a-vis their denoised versions are statistically different. GA is employed to derive a set of classification rules from audio data using these audio quality metrics, and the support-confidence framework is utilised as a fitness function to judge the quality of each rule. The generated rules are then used to detect or classify the audio documents in a real-time environment Experimental results show that the proposed technique provides promising detection rates.
Financial black holes: accounting for privately financed roads in the UK

Recent years have seen a change in how public assets are financed with a move towards more private finance, particularly in the transport, defence, health and education sectors. This change in policy and the additional complexity involved in such schemes raises important questions for reporting and accountability. How can the public understand where public money is going, how it is being used, whether it is value for money, the risks involved and the extent of future commitments and liabilities?
R-BTMA: a MAC protocol for short-range mobile radio communications

A reservation-Aloha-like (R-Aloha-like) protocol is studied in a decentralized mobile radio network context, with some hypotheses and assumptions and under specific constraints. Periodical traffic with parameter sharing and local communications are special characteristics of the model. The studied system faced problems, such as hidden nodes, fast changes in the network topology, and intervehicle communications. To solve or reduce some of these problems, the R-BTMA MAC protocol is introduced. It uses two distinct physical channels: a data channel and a busy-tone channel for signaling. Simulations are presented to evaluate the R-BTMA performance. The main service considered is parameter sharing with a regular traffic: one packet per frame and per vehicle. Numerical results show the improvements in channel throughput. The reaccess delay is evaluated. <<ETX>>
Determination of Safe regions in Optimized Dynamically Updatable Programs

Every software needs to be updated either to fix bugs or to add new features. To update a running system, developers typically shut down the system for a while, apply the patch and then resume execution. However, many continuously running system cannot afford to halt or would prefer not to. One of the most convenient solutions to this problem is dynamic software update where the program is updated while the program is in execution the running program is stopped at program point p, then the program is updated to new version and after that execution resumes from p onwards. p should be a safe point to have the dynamic update safe. Till date, many dynamic updating systems have been developed like Ginseng, JVolve etc. None of the present literature has defined update safety in dynamically updatable programs. They have concentrated on type safety. We would define update safety in this report. Also, none of these works considered program optimization issues at the time of determining safe points. However, both the old version and new version codes are optimized by the compiler, so update to old version code may enable some optimization opportunities that were not possible otherwise or it may disable some previously performed optimizations. Therefore, not only the updates but also the optimizations and de-optimizations resulting from the updates change the code. In this report, we present a methodology to determine safe points in a program considering both updates and enabling and disabling of optimizations by the updates. We have implemented a system in LLVM to determine the safe regions in a program considering program optimizations. Our system can be integrated with any dynamic update system.
Hand gesture recognition system using single-mixture source separation and flexible neural trees

Surface Electromyography (sEMG) is widely used in evaluating the functional status of hands to assist in hand gesture recognition in many fields of treatment and rehabilitation. Multi-channel parallel interfaces (MCPIs) or time-division multiple access (TDMA) interfaces are the main technologies for the man–machine communication medium of sEMG recognition instruments. However, they can also result in a complex circuit connection and noise interference. A hand gesture recognition model based on sEMG signals by using single-mixture source separation and flexible neural trees (FNTs) is a breakthrough model of hand gesture recognition designed to conquer the above defects. It distinguishes itself from the traditional MCPI or TDMA interfaces by more accurate and reliable measurements of signals. Single-mixture source separation by use of ensemble empirical mode decomposition (EEMD), principal component analysis (PCA) and independent component analysis (ICA) is a novel single-input multiple-output (SIMO) blind separation method, which can simplify the two interfaces described above. The FNT model is generated and evolved based on the pre-defined simple instruction sets, which can solve the highly structure dependent problem of the artificial neural network. The testing has been conducted using several experiments conducted with five participants. The EEMD-PCA-ICA algorithm can blind separate single mixed signals with higher cross-correlation and lower relative root mean squared error. The results indicate that the model is able to classify four different hand gestures up to 97.48% accuracy.
Market Basket Analysis Algorithm on Map/Reduce in AWS EC2

As the web, social networking, and smartphone application have been popular, the data has grown drastically everyday. Thus, such data is called Big Data. Google met Big Data earlier than others and recognized the importance of the storage and computation of Big Data. Thus, Google implemented its parallel computing platform with Map/Reduce approach on Google Distributed File Systems (GFS) in order to compute Big Data. Map/Reduce motivates to redesign and convert the existing sequential algorithms to Map/Reduce algorithms for Big Data so that the paper presents Market Basket Analysis algorithm with Map/Reduce, one of popular data mining algorithms. The algorithm is to sort data set and to convert it to (key, value) pair to fit with Map/Reduce. Amazon Web Service (AWS) provides Apache Hadoop platform that provide Map/Reduce computing on Hadoop Distributed File Systems (HDFS) as one of many its services. In the paper, the proposed algorithm is executed on Amazon EC2 Map/Reduce platform with Hadoop. The experimental results show that the code with Map/Reduce increases the performance as adding more nodes but at a certain point, Map/Reduce has the limitation of exploring the parallelism with a bottle-neck that does not allow the performance gain. It is believed that the operations of distributing, aggregating, and reducing data in the nodes of Map/Reduce should cause the bottle-neck.
Joint transmit and receive multi-user MIMO decomposition approach for the downlink of multi-user MIMO systems

We propose a joint transmit and receive decomposition approach for the downlink of multi-user MIMO systems. This approach makes use of the assumption of part of the receiver structure in computing the solution for the transmit processing. With this assumption, this approach decomposes a multi-user MIMO downlink channel into multiple parallel independent single-user MIMO downlink channels. A new degree of freedom is obtained by making the number of data streams variable. Sample simulation results are provided and these show the potential of the proposed scheme.
Scheduling the CAN bus with earliest deadline techniques

Controller area networks (CANs) are widely used in real-time automobile control and are gaining wider acceptance as a standard for factory automation. This paper discusses the applicability of earliest-deadline-first (EDF) techniques to the scheduling of CAN messages. EDF can guarantee higher network utilization than fixed-priority schemes like deadline- or rate-monotonic (DM, RM), but it is difficult to implement in local area networks or local buses. The reason is the need for updating the deadlines (priorities) at each scheduling round and the limited number of priority levels offered by the arbitration protocol. This deadline encoding problem results in an additional priority inversion factor when considering the schedulability analysis of hard real-time messages. This paper describes an effective deadline encoding method and discusses its implementation and its effects on the guarantee analysis. In spite of a limited processor overhead (less than 5% of CPU time), the proposed EDF implementation allows an increase (up to 20%) in the feasible network workload. This tradeoff will be made more convenient as controller technology evolves.
Multilevel Codes for Unequal Error Protection

Two combined unequal error protection (UEP) coding and modulation schemes are proposed. The first method multiplexes different coded signal constellations, with each coded constellation providing a different level of error protection. In this method, a codeword specifies the multiplexing rule and the choice of the codeword from a fixed codebook is used to convey additional important information. The decoder determines the multiplexing rule before decoding the rest of the data. The second method is based on partitioning a signal constellation into disjoint subsets in which the most important data sequence is encoded, using most of the available redundancy, to specify a sequence of subsets. The partitioning and code construction is done to maximize the minimum Euclidean distance between two different valid subset sequences. This leads to ways of partitioning the signal constellations into subsets. The less important data selects a sequence of signal points to be transmitted from the subsets. A side benefit of the proposed set partitioning procedure is a reduction in the number of nearest neighbors, sometimes even over the uncoded signal constellation. >
Learning by means of free associative neurons

Introduces a new learning method: free associative neurons (FAN). FAN is composed of independent units with autonomous learning capabilities. The learning power of FAN is based on the association of its units and on the use of granularity for representing information. As a method for representing complex environments, FAN can be used in pattern recognition, classification and diagnosis. This paper is focused on the principles governing FAN. We also discuss some results and compare them to well-known artificial neural network algorithms.
Conducting ethnographic research on language-like visual communication.

This paper provides guidance to academics, new researchers, and practicing designers or business people on how to conduct ethnographic research on visual communications that are language-like in that they contain forms linked to specific meanings. The paper adapts Spradley's (1980) detailed steps for conducting ethnographic research to ethnography that is focused on visual communication. An argument is made that it is useful to employ linguistic frameworks in such research because the field of linguistics already has a well-developed theory base from which researchers can develop theory that is specific to visual communication.