Novel Web Metrics Based On Sentiment Analysis
Jelínek, Ivan; Malinský, Radek
2016 - anglický
In recent years, the Internet has been experiencing a huge boom in social networking,
blogging and discussing on online forums. With the growing popularity of these
communication channels, there have been arising a large number of comments on
various topics from many different types of users. Such information source is not only
useful for academic researchers, but also for commercial companies that would like
to gain a direct user feedback on price, quality, and other factors of their products.
However, obtaining comprehensive information from such a source is a challenging
task nowadays.
Several models have been proposed for the social media analysis on the Web.
However, many of these solutions are usually tailored to a specific purpose or data
type, and there is still lack of generality and unclear approach to handling the data.
Moreover, a web content diversity, a variety of technologies along with the website
structure differences, all of these make the Web a network of heterogeneous data,
where things are difficult to find. It is, therefore, necessary to design a suitable
metric that would reflect a semantic content of single pages in a better way.
In this thesis, the main emphasis has been placed on the evaluation of the Internet
trends, where the trend may be defined as anything from an event, product name,
name of a person or any expression, which is mentioned online. A general model
has been proposed to collect and analyse data from the Web. The analysis part
of the model is based on webometric principles that are enhanced by the methods
of sentiment and social network analysis. The extension of webometrics by the
combination of these methods leads up to gaining insights into the public opinion
with respect to some topic, and to a better machine understanding of a text.
iii
In particular, the main contributions of the dissertation thesis are as follows:
1. Proposal of the new theoretical model for gathering and processing data from
Web 2.0.
2. Definition of the methodology for the evaluation of Internet trends.
3. Adaptation of the newly designed methodology for the evaluation in social
network sphere.
4. Proposal of the new sentiment sense disambiguation methods to improve
sentiment classification for multiple-topic related words.
5. Architecture design of the new framework that provides an end-to-end approach
to the analysis of selected Internet trends.
Plné texty jsou dostupné v digitálním repozitáři ČVUT.
Novel Web Metrics Based On Sentiment Analysis
In recent years, the Internet has been experiencing a huge boom in social networking, blogging and discussing on online forums. With the growing popularity of these communication channels, there ...
Network Traffic Representations for Adaptive Intrusion Detection
Rehák, Martin; Pevný, Tomáš; Bartoš, Karel
2016 - anglický
New and unseen polymorphic malware, zero-day attacks, or other types of advanced persistent
threats are usually not detected by traditional security systems. This represents a challenge to
the network security industry as the amount and variability of attacks has been increasing. In
this thesis, we propose three key approaches, each dealing with this challenge at di erent levels
of abstraction.
In order to cope with an increasing volume of network tra c, we propose the adaptive sampling
method based on two concepts that mitigate the negative impact of sampling on the
raw input data: (i) Features used by the analytic algorithms are extracted before the sampling
and attached to the surviving
ows. The surviving
ows thus carry the representation of the
original statistical distribution in these attached features. (ii) Adaptive sampling that deliberatively
skews the distribution of the surviving data to over-represent the rare
ows or
ows with
rare feature values. This preserves the variability of the data and is critical for the analysis of
malicious tra c, such as the detection of stealthy, hidden threats. Our approach has been extensively
validated on standard NetFlow data, as well as on HTTP proxy logs that approximate
the use-case of enriched IPFIX for the network forensics.
Next, we propose a novel representation and classi cation system designed to detect both
known as well as previously unseen security threats. The classi ers use statistical feature representation
computed from the network tra c and learn to recognize malicious behavior. The
representation is designed and optimized to be invariant to the most common changes of malware
behaviors. This is achieved in part by a feature histogram constructed for each group of
network connections (
ows) and in part by a feature self-similarity matrix computed for each
group. The parameters of the representation (histogram bins) are optimized and learned based
on the training samples along with the classi ers. The proposed approach was deployed on large
corporate networks, where it detected 2,090 new variants of malware with 90% precision.
Finally, we propose a distributed and self-organized mechanism for the collaboration of multiple
heterogeneous detection systems. The mechanism is based on a game-theoretical approach
that optimizes the behavior of each detection system with respect to other systems in highly
dynamic environments. The game-theoretical model specializes the detection systems on speci c
types of malicious behaviors to collaboratively cover a wider range of attack classes. According
to our experimental evaluation on the real network tra c, the proposed mechanism shows clear
improvements caused by mutual specialization of individual detection systems.
All three approaches can be combined into a uni ed collaborative fusion system, analyzing
the input network tra c at di erent levels of abstraction. The bene ts of such combination were
demonstrated in the nal experiment, where we combined the proposed adaptive sampling with
a collaborative mechanism for detection systems deployed in multiple networks.
Plné texty jsou dostupné v digitálním repozitáři ČVUT.
Network Traffic Representations for Adaptive Intrusion Detection
New and unseen polymorphic malware, zero-day attacks, or other types of advanced persistent threats are usually not detected by traditional security systems. This represents a challenge to the ...
Travelling Waves in Distributed Control
Šebek, Michal; Martinec, Dan
2016 - anglický
Plné texty jsou dostupné v digitálním repozitáři ČVUT.
Travelling Waves in Distributed Control
Automatic User Interface Generation
Slavík, Pavel; Macík, Miroslav
2016 - anglický
Plné texty jsou dostupné v digitálním repozitáři ČVUT.
Automatic User Interface Generation
PROPERTY STUDIES OF PLASMA SPRAYED TITANATES
Ctibor, Pavel; Kotlan, Jiří; Sedláček, Josef
2016 - anglický
Use of plasma sprayed coatings is an important part of industrial production in many applications. This
technique is mainly used for applications such as thermal barrier and wear resistant layers. Application
of plasma sprayed coatings in the electronics industry lags behind its possibilities because there was lower
attention to electrical properties of these coatings worldwide. This work provides new knowledge about
the electrical and structural properties of titanates which are in the sintered state used as a dielectrics.
Calcium titanate and barium-strontium titanate as promising materials in the form of the coating were
selected as proper materials in this dissertation. Plasma deposited coatings exhibit di erent microstruc-
ture and often phase and chemical composition when compared to the sintered material. Coatings were
prepared by the conventional gas stabilized plasma torch as well as water stabilized plasma technology.
Many experimental methods were used to bring a new knowledge about these materials. The electrical
properties were studied by frequency dependence of relative permittivity and loss factor or by measuring
electrical breakdown strength, electrical resistivity and determination of band gap. The morphology of
coatings was studied by both light and electron microscopy. Phase composition was characterized by X-
ray di raction analysis including high temperature in-situ experiments. Raman spectroscopy and X-ray
photoelectron spectroscopy were used to analyze the chemical composition. The mechanical properties
were analyzed by microhardness and elastic modulus measurements. All these measurements and discus-
sion of the results bring a new knowledge about plasma deposited titanates and thereby contribute to
greater potential application of these materials in the electronics industry.
Plné texty jsou dostupné v digitálním repozitáři ČVUT.
PROPERTY STUDIES OF PLASMA SPRAYED TITANATES
Use of plasma sprayed coatings is an important part of industrial production in many applications. This technique is mainly used for applications such as thermal barrier and wear resistant layers. ...
Algorithms for Analysis of Nonlinear High-Frequency Circuits
Dobeš, Josef; Černý, David
2016 - anglický
The most efficient simulation solvers use composite procedures that adaptively rearrange
computation algorithms to maximize simulation performance. Fast and stable processing
optimized for given simulation problem is essential for any modern simulator. It is
characteristic for electronic circuit analysis that complexity of simulation is affected
by circuit size and used device models. Implementation of electronic device models in
program SPICE uses traditional implementation allowing fast computation but further
modification of model can be questionable.
The first fundamental thesis aim is scalability of the simulation based on the adaptive
internal solver composing different algorithms according to properties of simulation
problem to maximize simulation performance. In a case of the small circuit as faster
solution prove simple, straightforward methods that utilize arithmetic operations without
unnecessary condition jumping and memory rearrangements that can not be effectively
optimized by a compiler. The limit of small size simulation problems is related to
computation machine capabilities. The present day PC sets this limit to fifty independent
voltage nodes where inefficiency of calculation procedure does not play any role in overall
processor performance. The scalable solver must also be able to handle correctly simulation
of large-scale circuits that requires entirely different approach apart to standard size
circuits. The unique properties of simulation of the electronic circuits that played until this
time only the minor role suddenly gain on significance for circuits with several thousand
voltage nodes. In those particular cases, iterative algorithms based on Krylov subspace
methods provide better results from the aspect of performance than standard direct
methods. This thesis also proposes unique techniques of indexation of the large-scale
sparse matrix system. The primary purpose is to reduce memory requirements for storing
sparse matrices during simulation computation.
The second fundamental thesis aim is automatic adaptivity of device models definition
respecting current simulation state and settings. This principle is denoted as Functional
Chaining mechanism that is based on the principle of the automatic self-modifying
procedure utilizing state-of-the-art functional computation layer during the simulation
process. It can significantly improve mapping performance of circuit variables to device
models; it also allows autonomous redefinition of simulation algorithms during analysis
with an intention to reduce computation time. The core idea is based on utilization of
programming principles related to functional programming languages. It is also presents
possibilites of reimplementation to the modern object-oriented languages.
The third fundamental thesis aim focuses on simulation accuracy and reliability. Arbitrary
precision variable types can directly lead to increased simulation accuracy but on
the other hand; they can significantly decrease simulation performance. In last chapters,
there are several algorithms provided with the claim to provide better simulation accuracy
and suppress computation errors of floating point data types.
Plné texty jsou dostupné v digitálním repozitáři ČVUT.
Algorithms for Analysis of Nonlinear High-Frequency Circuits
The most efficient simulation solvers use composite procedures that adaptively rearrange computation algorithms to maximize simulation performance. Fast and stable processing optimized for given ...
Evaluation of motor speech disorders by acoustic analysis: differential diagnosis and monitoring of medical intervention
Čmejla, Roman; Tykalová, Tereza
2016 - anglický
Dysarthria is a motor speech disorder resulting from neurologic impairment affecting mainly
the control and execution of movements related to speech production. Occurrence of
dysarthria in adult age is commonly manifested as a consequence of degenerative disorder
such as Parkinson's disease (PD), Huntington's disease (HD), multiple system atrophy (MSA),
progressive supranuclear palsy (PSP) or cerebellar ataxia (CA). Interestingly, identification of
specific deviant speech characteristics can provide important clues about the underlying
pathophysiology and localization of neurological diseases. Speech may also serve as
a valuable marker of disease onset or treatment efficacy. Therefore, the main aims of this
doctoral thesis were (a) to design the feasible algorithms, methodologies or measurements that
would be sensitive and accurate enough to capture pathological changes in speech, (b) to
objectively quantify the effect of neurological disorder on speech production and (c) to relate
the potentially observed speech changes to overall motor performance or medication doses in
order to provide deeper insight into the pathophysiology of speech disturbances.
Several databases of PD, HD, MSA, PSP and CA patients as well as age-matched
healthy controls were obtained. During recording, all participants were instructed to perform
several speaking tasks such as sustained phonation, fast syllable repetition, reading passage or
monologue. In addition, various clinical information about patient's motor skills, cognitive
abilities or medication doses was available. The acoustic analyses were carried out to provide
quantitative objective evaluation of speech performances. Statistical analyses were applied to
search for possible group differences or correlations between speech and clinical metrics.
The results of this doctoral thesis are presented in the form of nine peer-reviewed
journal papers. In summary, we managed to objectively quantify the effect of neurological
disorder on speech production in PD, HD, MSA, PSP and CA patients. Furthermore, we
proved that the separation of patients from healthy controls based solely on speech is possible.
The differentiation among several types of parkinsonian disorders is also possible as we were
able to discriminate between MSA/PSP and PD with 95 % accuracy and between PSP and
MSA subjects with 75 % accuracy. In addition, a number of correlations were found between
clinical and speech characteristics. Considering PD, an adverse effect of levodopa on speech
fluency was found in PD patients after 3-6 years of taking medication. On the other hand, we
found improved or maintained speech performances (related mainly to consonant and vowel
articulation, pitch variability and number of pauses) in two-thirds of those PD patients
whereas speech deteriorated only in one-third; indicating general positive effect of long-term
dopaminergic therapy on dysarthria in early stages of PD. In conclusion, objective acoustic
analysis of motor speech disorders can significantly contribute to early and correct diagnosis
of the particular disorder and provide more insights into underlying pathophysiology of such
diseases.Dysartrie je porucha hlasu a řeči vznikající v důsledku poškození funkce části mozku, která je
zodpovědná zejména za řízení a provádění pohybů souvisejících s tvorbou řeči. Dysartrie se
v dospělosti běžně vyskytuje jako důsledek degenerativních onemocnění, mezi která patří
i Parkinsonova nemoc (PN), Huntingtonova nemoc (HN), mnohočetná systémová atrofie
(MSA), progresivní supranukleární obrna (PSO) nebo cerebelární ataxie (CA). Rozpoznání
a klasifikace specifických řečových charakteristik souvisejících s dysartrií může poskytnout
důležité informace o patofyziologii a lokalizaci neurologických onemocnění. Hodnocení míry
poškození řeči pak může též sloužit jako cenný ukazatel pro stanovení doby nástupu nemoci
či účinnosti léčby. Hlavní cíle této disertační práce jsou: (a) navrhnout vhodné algoritmy,
metody a měření, které by byly dostatečně citlivé a přesné, aby zachytily patologické změny
v řeči, (b) objektivně kvantifikovat vliv neurologických poruch na řečový projev a (c) hledat
souvislosti mezi pozorovanými změnami v řeči a celkovým motorickým stavem pacienta
či medikací, kterou užívá, za účelem hlubšího porozumění patofyziologii poruch řeči.
V rámci dizertace bylo pořízeno několik databází PN, HN, MSA, PSO a CA pacientů
a zdravých kontrol odpovídajícího věku. V průběhu nahrávání byli všichni účastníci studie
požádáni o provedení několika řečových úloh jako je prodloužená fonace, rychlé opakování
slabik, přečtení úryvku textu nebo vyprávění krátkého monologu. Dále byly pořízeny
záznamy s různými klinickými informacemi o stavu motorických či kognitivních schopností
pacienta nebo dávkách užívaných léků. Objektivní kvantitativní hodnocení řeči bylo
provedeno s pomocí akustických analýz. Statistické analýzy byly použity k hledání možných
rozdílů mezi skupinami či korelací mezi řečovými a klinickými charakteristikami.
Výsledky této disertační práce jsou prezentovány v podobě devíti IF publikací. Vliv
neurologické poruchy na produkci řeči se nám podařilo objektivně kvantifikovat u všech
zkoumaných nemocí včetně PN, HN, MSA, PSO a CA. Dále se ukázalo, že oddělení pacientů
od zdravých kontrol pouze na základě nahrávky řečového projevu je možné. Taktéž jsme
prokázali, že i diferenciace mezi několika velmi podobnými nemocemi parkinsonského typu
je možná. S použitím akustických analýz jsme byly schopni rozlišit mezi MSA/PSO a PN
s přesností 95 % a mezi PSO a MSA s přesností 75 %. Dále jsme objevili řadu korelací mezi
klinickými a řečovými charakteristikami. Nepříznivý účinek levodopy na plynulost řeči byl
nalezen u pacientů s PN po 3-6 letech užívání tohoto léku. Na druhé straně jsme pozorovali
zlepšení nebo alespoň zachování kvality řečového projevu (související zejména s přesností
artikulace souhlásek a samohlásek, variabilitou výšky hlasu a počtem pauz) u 2/3 těchto PN
pacientů, zatímco řeč se zhoršila pouze u 1/3. Tyto nálezy naznačující celkový pozitivní
účinek dlouhodobého užívání levodopy na dysartrii v brzkých stádiích PN. Závěrem lze říci,
že objektivní akustická analýza poruch řeči může významně přispět ke včasné a správné
diagnóze dané nemoci a také přispět k hlubšímu porozumění patofyziologii těchto chorob.
Plné texty jsou dostupné v digitálním repozitáři ČVUT.
Evaluation of motor speech disorders by acoustic analysis: differential diagnosis and monitoring of medical intervention
Dysarthria is a motor speech disorder resulting from neurologic impairment affecting mainly the control and execution of movements related to speech production. Occurrence of dysarthria in adult age ...
QUALITY CONTROL METHODS AND TOOLS FOR IMPROVEMENT OF EFFECTIVENESS OF MANUFACTURING PROCESSES
Mach, Pavel; Tarba, Larisa
2016 - anglický
The objective of this thesis is to uncover the usage of combining several modern methods for controlling and optimizing the manufacturing processes. The goal is to achieve manufacturing of high value-added products, monitor and control performance and the quality of the processes themselves in order to have fewer defects, to increase the non-defect production and improve the overall quality. Implementing innovative technologies into the manufacturing process and creating their mathematical model of effectiveness criteria of implementation allows evaluating the possible changes. Combining Lean Production, Six Sigma methodology and Fuzzy logic will give not only the broader view on all aspects, but also consider how to improve the manufacturing process and make it non defective, seamless and the most efficient.
The first part of the thesis describes the current situation of the electronics market, clarifies and explains the basic terms of methods, how they can be combined and used in manufacturing processes in order to increase and control the quality.
The second part of the thesis describes one of the manufacturing processes, i.e. Printed Circuit Board manufacturing, and development of the mathematical model and criteria for evaluation innovative technologies and their implementation into the manufacturing process.
The third part of the thesis is focused on methodology for optimizing the printed circuit board assembly process by minimizing the duration of sub processes, which potentially will decrease the lead time of the whole assembly process itself.
The fourth part of the thesis focuses on optimal strategy for implementing the innovative technologies into the manufacturing process as well as suggests the creation of policy manual of quality management system which will describe the interaction between individual processes within the organization.
Plné texty jsou dostupné v digitálním repozitáři ČVUT.
QUALITY CONTROL METHODS AND TOOLS FOR IMPROVEMENT OF EFFECTIVENESS OF MANUFACTURING PROCESSES
The objective of this thesis is to uncover the usage of combining several modern methods for controlling and optimizing the manufacturing processes. The goal is to achieve manufacturing of high ...
Quality Assessment of Post-Processed Images
Klíma, Miloš; Le Callet, Patrick; Fliegel, Karel; Krasula, Lukáš
2016 - anglický
The vast majority of the work done in the field of quality assessment
during last two decades has been dedicated to the quantification of
the distortion caused by the processing of an image. The original
image was, therefore, always considered to be of the best possible
quality. In this kind of scenario, the notion of quality can be
expressed as the fidelity of the processed version to the reference.
However, some post-processing algorithms enable to adjust
aesthetic properties of an image in order to enhance the perceived
quality. In such cases, the best possible quality image is not
available and the classical fidelity approach is no longer applicable.
The goal of this thesis is to revise the quality assessment
methodologies to cope with the challenges brought by the
post-processing into the quality evaluation. The post-processing
algorithms, relevant to the topic of this thesis, come from two groups
– image enhancement, represented by image sharpening, and
dynamic range compression (also known as tone-mapping)
techniques. Both subjective and objective quality assessment
methodologies applicable in these areas are studied and the
suitable solutions, outperforming the state-of-the-art methods, are
proposed. Moreover, a novel methodology for evaluating the
performance of objective quality metrics, overcoming the
shortcomings of the currently available methods, is presented.
Plné texty jsou dostupné v digitálním repozitáři ČVUT.
Quality Assessment of Post-Processed Images
The vast majority of the work done in the field of quality assessment during last two decades has been dedicated to the quantification of the distortion caused by the processing of an image. The ...
Robust recognition of strongly distorted speech
Pollák, Petr; Borský, Michal
2016 - anglický
The automatic speech recognition systems have become a part of our daily lives.
People often rely on virtual personal assistants in smartphones, use their voice to control
intelligent devices in cars and smart homes or communicate with automatic dialogue
systems in call-centres. Since these systems often suffer from a performance drop in
realistic acoustic conditions which are characterized by strong distortions, a large portion
of research still must be focused on robust front-end algorithms and acoustic modelling
methods for distorted speech recognition. This thesis is focused on these compensation
methods working at the level of front-end processing and acoustic modelling, whose aim is
to compensate the degradation introduced by a distant microphone, noisy environments
and a lossy compression.
The techniques for noisy and distant speech recognition studied in this thesis were focused
on front-end noise suppression techniques, feature normalization techniques, acoustic
model adaptations and discriminative training. Said techniques were evaluated in
three different car conditions and two different public environments. The experiments
have proved, that extended spectral subtraction can bring significant improvement even
for the state-of-the-art systems in public environments with a strong noise and for a
far-distance microphone recordings.
The evaluation of compressed speech recognition examined the degrading effects of
lossy compression on fundamental frequency, formants and smoothed LPC spectrum and
for standard MFCC and PLP features used for ASR. The low-pass filtering and the areas
of very low energy in a spectrogram were identified as the two main reasons of degradation.
The practical experiments evaluated the contributions of specific feature extraction setups,
combinations of normalization and compensation techniques, supervised and unsupervised
adaptation and discriminative training methods and finally the matched training. The
largest contributions were gained from the application of adaptation techniques, subspace
GMM and discriminative training.
A novel algorithm named Spectrally selective dithering (SSD) was proposed within this
thesis, which compensated the effect of spectral valleys. The contribution of said algorithm
was verified for both GMM-HMM and DNN-HMM speech recognition systems for Czech
and English and for a GMM-HMM system for German. The practical experiments proved
that the proposed algorithm can lower WER for all languages with GMM-HMM systems.
Concerning DNN-HMM system, a significant contribution was achieved only for Czech.
Plné texty jsou dostupné v digitálním repozitáři ČVUT.
Robust recognition of strongly distorted speech
The automatic speech recognition systems have become a part of our daily lives. People often rely on virtual personal assistants in smartphones, use their voice to control intelligent devices in ...
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