Abstract: In this paper, we present a robust algorithm to recognize extracted text from grocery product images captured by mobile phone cameras. Recognition of such text is challenging since text in grocery product images varies in its size, orientation,
style, illumination, and can suffer from perspective distortion.
Pre-processing is performed to make the characters scale and
rotation invariant. Since text degradations can not be appropriately
defined using well-known geometric transformations such
as translation, rotation, affine transformation and shearing, we
use the whole character black pixels as our feature vector.
Classification is performed with minimum distance classifier
using the maximum likelihood criterion, which delivers very
promising Character Recognition Rate (CRR) of 89%. We
achieve considerably higher Word Recognition Rate (WRR) of
99% when using lower level linguistic knowledge about product
words during the recognition process.
Abstract: The paper describes a Chinese shadow play animation
system based on Kinect. Users, without any professional training, can
personally manipulate the shadow characters to finish a shadow play
performance by their body actions and get a shadow play video
through giving the record command to our system if they want. In our
system, Kinect is responsible for capturing human movement and
voice commands data. Gesture recognition module is used to control
the change of the shadow play scenes. After packaging the data from
Kinect and the recognition result from gesture recognition module,
VRPN transmits them to the server-side. At last, the server-side uses
the information to control the motion of shadow characters and video
recording. This system not only achieves human-computer interaction,
but also realizes the interaction between people. It brings an
entertaining experience to users and easy to operate for all ages. Even
more important is that the application background of Chinese shadow
play embodies the protection of the art of shadow play animation.
Abstract: In this paper, Fuzzy C-Means clustering with
Expectation Maximization-Gaussian Mixture Model based hybrid
modeling algorithm is proposed for Continuous Tamil Speech
Recognition. The speech sentences from various speakers are used
for training and testing phase and objective measures are between the
proposed and existing Continuous Speech Recognition algorithms.
From the simulated results, it is observed that the proposed algorithm
improves the recognition accuracy and F-measure up to 3% as
compared to that of the existing algorithms for the speech signal from
various speakers. In addition, it reduces the Word Error Rate, Error
Rate and Error up to 4% as compared to that of the existing
algorithms. In all aspects, the proposed hybrid modeling for Tamil
speech recognition provides the significant improvements for speechto-
text conversion in various applications.
Abstract: The Smart Help for persons with disability (PWD) is a
part of the project SMARTDISABLE which aims to develop relevant
solution for PWD that target to provide an adequate workplace
environment for them. It would support PWD needs smartly through
smart help to allow them access to relevant information and
communicate with other effectively and flexibly, and smart editor
that assist them in their daily work. It will assist PWD in knowledge
processing and creation as well as being able to be productive at the
work place. The technical work of the project involves design of a
technological scenario for the Ambient Intelligence (AmI) - based
assistive technologies at the workplace consisting of an integrated
universal smart solution that suits many different impairment
conditions and will be designed to empower the Physically disabled
persons (PDP) with the capability to access and effectively utilize the
ICTs in order to execute knowledge rich working tasks with
minimum efforts and with sufficient comfort level. The proposed
technology solution for PWD will support voice recognition along
with normal keyboard and mouse to control the smart help and smart
editor with dynamic auto display interface that satisfies the
requirements for different PWD group. In addition, a smart help will
provide intelligent intervention based on the behavior of PWD to
guide them and warn them about possible misbehavior. PWD can
communicate with others using Voice over IP controlled by voice
recognition. Moreover, Auto Emergency Help Response would be
supported to assist PWD in case of emergency. This proposed
technology solution intended to make PWD very effective at the
work environment and flexible using voice to conduct their tasks at
the work environment. The proposed solution aims to provide
favorable outcomes that assist PWD at the work place, with the
opportunity to participate in PWD assistive technology innovation
market which is still small and rapidly growing as well as upgrading
their quality of life to become similar to the normal people at the
workplace. Finally, the proposed smart help solution is applicable in
all workplace setting, including offices, manufacturing, hospital, etc.
Abstract: Recent concerns about the value of teaching cursive
handwriting in the classroom are based on the belief that cursive
handwriting or penmanship is an outdated and unnecessary skill in
today’s online world. The discussion of this issue begins with a
description of current initiatives to eliminate handwriting instruction
in schools. This is followed by a brief history of cursive writing
through the ages. Next considered is a description of its benefits as a
preliminary process for younger children as compared with
immediate instruction in keyboarding, particularly in the areas of
vision, cognition, motor skills and automatic fluency. Also
considered, is cursive’s companion, paper itself, and the impact of a
paperless, “screen and keyboard” environment. The discussion
concludes with a consideration of the unique contributions of cursive
and keyboarding as written forms of communication, along with their
respective surfaces, paper and screen. Finally, an assessment of the
practical utility of each skill is followed by an informal assessment of
what is lost and what remains as we move from a predominantly
paper and pen world of handwriting to texting and keyboarding in an
environment of screens.
Abstract: The paper presents combined automatic speech
recognition (ASR) of English and machine translation (MT) for
English and Croatian and Croatian-English language pairs in the
domain of business correspondence. The first part presents results of
training the ASR commercial system on English data sets, enriched
by error analysis. The second part presents results of machine
translation performed by free online tool for English and Croatian
and Croatian-English language pairs. Human evaluation in terms of
usability is conducted and internal consistency calculated by
Cronbach's alpha coefficient, enriched by error analysis. Automatic
evaluation is performed by WER (Word Error Rate) and PER
(Position-independent word Error Rate) metrics, followed by
investigation of Pearson’s correlation with human evaluation.
Abstract: This paper presents general results on the Java source
code snippet detection problem. We propose the tool which uses
graph and subgraph isomorphism detection. A number of solutions
for all of these tasks have been proposed in the literature. However,
although that all these solutions are really fast, they compare just the
constant static trees. Our solution offers to enter an input sample
dynamically with the Scripthon language while preserving an
acceptable speed. We used several optimizations to achieve very low
number of comparisons during the matching algorithm.
Abstract: The paper presents the results of clusterization by
Kohonen self-organizing maps (SOM) applied for analysis of array of
Raman spectra of multi-component solutions of inorganic salts, for
determination of types of salts present in the solution. It is
demonstrated that use of SOM is a promising method for solution of
clusterization and classification problems in spectroscopy of multicomponent
objects, as attributing a pattern to some cluster may be
used for recognition of component composition of the object.
Abstract: The article is devoted to the problem of political
discourse and its reflection on mass cognition. This article is
dedicated to describe the myth as one of the main features of political
discourse. The dominance of an expressional and emotional
component in the myth is shown. Precedent phenomenon plays an
important role in distinguishing the myth from the linguistic point of
view. Precedent phenomena show the linguistic cognition, which is
characterized by their fame and recognition. Four types of myths
such as master myths, a foundation myth, sustaining myth,
eschatological myths are observed. The myths about the national idea
are characterized by national specificity. The main aim of the
political discourse with the help of myths is to influence on the mass
consciousness in order to motivate the addressee to certain actions so
that the target purpose is reached owing to unity of forces.
Abstract: One of the major goals of Spoken Dialog Systems
(SDS) is to understand what the user utters.
In the SDS domain, the Spoken Language Understanding (SLU)
Module classifies user utterances by means of a pre-definite
conceptual knowledge. The SLU module is able to recognize only the
meaning previously included in its knowledge base. Due the vastity
of that knowledge, the information storing is a very expensive
process.
Updating and managing the knowledge base are time-consuming
and error-prone processes because of the rapidly growing number of
entities like proper nouns and domain-specific nouns. This paper
proposes a solution to the problem of Name Entity Recognition
(NER) applied to a SDS domain. The proposed solution attempts to
automatically recognize the meaning associated with an utterance by
using the PANKOW (Pattern based Annotation through Knowledge
On the Web) method at runtime.
The method being proposed extracts information from the Web to
increase the SLU knowledge module and reduces the development
effort. In particular, the Google Search Engine is used to extract
information from the Facebook social network.
Abstract: In this paper the issue of dimensionality reduction is
investigated in finger vein recognition systems using kernel Principal
Component Analysis (KPCA). One aspect of KPCA is to find the
most appropriate kernel function on finger vein recognition as there
are several kernel functions which can be used within PCA-based
algorithms. In this paper, however, another side of PCA-based
algorithms -particularly KPCA- is investigated. The aspect of
dimension of feature vector in PCA-based algorithms is of
importance especially when it comes to the real-world applications
and usage of such algorithms. It means that a fixed dimension of
feature vector has to be set to reduce the dimension of the input and
output data and extract the features from them. Then a classifier is
performed to classify the data and make the final decision. We
analyze KPCA (Polynomial, Gaussian, and Laplacian) in details in
this paper and investigate the optimal feature extraction dimension in
finger vein recognition using KPCA.
Abstract: In the past, the most comprehensively adopted light
source was incandescent light bulbs, but with the appearance of LED
light sources, traditional light sources have been gradually replaced by
LEDs because of its numerous superior characteristics. However,
many of the standards do not apply to LEDs as the two light sources
are characterized differently. This also intensifies the significance of
studies on LEDs. As a Kansei design study investigating the visual
glare produced by traffic arrows implemented with LEDs, this study
conducted a semantic analysis on the styles of traffic arrows used in
domestic and international occasions. The results will be able to
reduce drivers’ misrecognition that results in the unsuccessful arrival
at the destination, or in traffic accidents. This study started with a
literature review and surveyed the status quo before conducting
experiments that were divided in two parts. The first part involved a
screening experiment of arrow samples, where cluster analysis was
conducted to choose five representative samples of LED displays. The
second part was a semantic experiment on the display of arrows using
LEDs, where the five representative samples and the selected ten
adjectives were incorporated. Analyzing the results with
Quantification Theory Type I, it was found that among the
composition of arrows, fletching was the most significant factor that
influenced the adjectives. In contrast, a “no fletching” design was
more abstract and vague. It lacked the ability to convey the intended
message and might bear psychological negative connotation including
“dangerous,” “forbidden,” and “unreliable.” The arrow design
consisting of “> shaped fletching” was found to be more concrete and
definite, showing positive connotation including “safe,” “cautious,”
and “reliable.” When a stimulus was placed at a farther distance, the
glare could be significantly reduced; moreover, the visual evaluation
scores would be higher. On the contrary, if the fletching and the shaft
had a similar proportion, looking at the stimuli caused higher
evaluation at a closer distance. The above results will be able to be
applied to the design of traffic arrows by conveying information
definitely and rapidly. In addition, drivers’ safety could be enhanced
by understanding the cause of glare and improving visual
recognizability.
Abstract: In this paper, we propose a method that allows faster and more accurate detection of traffic lights by a vision sensor during driving, DGPS is used to obtain physical location of a traffic light, extract from the image information of the vision sensor only the traffic light area at this location and ascertain if the sign is in operation and determine its form. This method can solve the problem in existing research where low visibility at night or reflection under bright light makes it difficult to recognize the form of traffic light, thus making driving unstable. We compared our success rate of traffic light recognition in day and night road environments. Compared to previous researches, it showed similar performance during the day but 50% improvement at night.
Abstract: The study explored the role of metacognition in foreign language anxiety on a sample of 411 Taiwanese students of English as a Foreign Language. The reading strategy inventory was employed to evaluate the tertiary learners’ level of metacognitive awareness and a semi-structured background questionnaire was also used to examine the learners’ perceptions of their English proficiency and satisfaction of their current English learning. In addition, gender and academic level differences in employment of reading strategies were investigated. The results showed the frequency of reading strategy use increase slightly along with academic years and males and females actually employ different reading strategies. The EFL tertiary learners in the present study utilized cognitive strategies more frequently than metacognitive strategies or support strategies. Male students use metacognitive strategy more often while female students use cognitive and support strategy more frequently.
Abstract: We present results from experimental price-setting oligopolies in which green firms undertake different levels of energy-saving investments motivated by public subsidies and demand-side advantages. We find that consumers reveal higher willingness to pay for greener sellers’ products. This observation in conjunction to the fact that greener sellers set higher prices is compatible with the use and interpretation of energy-saving behaviour as a differentiation strategy. However, sellers do not exploit the resulting advantage through sufficiently high price-cost margins, because they seem trapped into “run to stay still” competition. Regarding the use of public subsidies to energy-saving sellers we uncover an undesirable crowding-out effect of consumers’ intrinsic tendency to support green manufacturers. Namely, consumers may be less willing to support a green seller whose energy-saving strategy entails a direct financial benefit. Finally, we disentangle two alternative motivations for consumer’s attractions to pro-social firms; first, the self-interested recognition of the firm’s contribution to the public and private welfare and, second, the need to compensate a firm for the cost entailed in each pro-social action. Our results show the prevalence of the former over the latter.
Abstract: In this paper, it is proposed to improve Daisy Descriptor based face recognition using a novel One-Bit Transform (1BT) based pre-registration approach. The 1BT based pre-registration procedure is fast and has low computational complexity. It is shown that the face recognition accuracy is improved with the proposed approach. The proposed approach can facilitate highly accurate face recognition using DAISY descriptor with simple matching and thereby facilitate a low-complexity approach.
Abstract: Micro-reading is a new way of reading depended on short messages of mobile phones, network articles and short literary forms, which impacts greatly on traditional way of reading. The effect of "micro-reading" is deeper especially for those growing middle school students and college students. Aiming at the problem with the development of college students' micro-reading and based on the influence of schema theory on the research of cognition of reading, this paper is to analyze the comparison between micro-reading and traditional reading and explore reading strategies in micro-era based on the negative and positive effect which schema theory has on micro-reading.
Abstract: The inhibition of SH2 domain regulated protein-protein interactions is an attractive target for developing an effective chemotherapeutic approach in the treatment of disease. Molecular simulation is a useful tool for developing new drugs and for studying molecular recognition. In this study, we searched potential drug compounds for the inhibition of SH2 domain by performing structural similarity search in PubChem Compound Database. A total of 37 compounds were screened from the database, and then we used the LibDock docking program to evaluate the inhibition effect. The best three compounds (AP22408, CID 71463546 and CID 9917321) were chosen for MD simulations after the LibDock docking. Our results show that the compound CID 9917321 can produce a more stable protein-ligand complex compared to other two currently known inhibitors of Src SH2 domain. The compound CID 9917321 may be useful for the inhibition of SH2 domain based on these computational results. Subsequently experiments are needed to verify the effect of compound CID 9917321 on the SH2 domain in the future studies.
Abstract: This study examined the predictive effects of moral competence, prosocial norms and positive behavior recognition on school misbehavior among Chinese junior secondary school students. Results of multiple regression analysis showed that students were more likely to misbehave in school when they had lower levels of moral competence and prosocial norms, and when they perceived their positive behavior being less likely recognized. Practical implications were discussed on how to guide students to make the right choices to behave appropriately in school. Implications for future research were also discussed.
Abstract: To develop the useful acoustic environmental
recognition system, the method of estimating 3D-position of a
stationary random acoustic source using bispectral analysis of
4-point detected signals is proposed. The method uses information
about amplitude attenuation and propagation delay extracted from
amplitude ratios and angles of auto- and cross-bispectra of the
detected signals. It is expected that using bispectral analysis affects
less influence of Gaussian noises than using conventional power
spectral one. In this paper, the basic principle of the method is
mentioned first, and its validity and features are considered from
results of the fundamental experiments assumed ideal circumstances.