Abstract: From ancient times Turkic languages have been in
contact with numerous representatives of different language families.
The article discusses the Turkic - Indian language contact and were
shown promise and necessity of this trend for the Turkic linguistics, were given Turkic - Indian lexical parallels in the framework of the nostratic language's macro family. The research work has done on the base of lexical parallels (LP) -of Turkic (which belong to the Altaic family of languages) and Indian (including Dravidian and Indo-Aryan languages).
Abstract: We present a novel scheme to evaluate sinusoidal functions with low complexity and high precision using cubic spline interpolation. To this end, two different approaches are proposed to find the interpolating polynomial of sin(x) within the range [- π , π]. The first one deals with only a single data point while the other with two to keep the realization cost as low as possible. An approximation error optimization technique for cubic spline interpolation is introduced next and is shown to increase the interpolator accuracy without increasing complexity of the associated hardware. The architectures for the proposed approaches are also developed, which exhibit flexibility of implementation with low power requirement.
Abstract: In this empirical research, how marketing managers evaluate their firms- performances and decide to make innovation is examined. They use some standards which are past performance of the firm, target performance of the firm, competitor performance, and average performance of the industry to compare and evaluate the firms- performances. It is hypothesized that marketing managers and owners of the firm compare the firms- current performance with these four standards at the same time to decide when to make innovation relating to any aspects of the firm, either management style or products. Relationship between the comparison of the firm-s performance with these standards and innovation are searched in the same regression model. The results of the regression analysis are discussed and some recommendations are made for future studies and applicants.
Abstract: Embedded systems need to respect stringent real
time constraints. Various hardware components included in such
systems such as cache memories exhibit variability and therefore
affect execution time. Indeed, a cache memory access from an
embedded microprocessor might result in a cache hit where the
data is available or a cache miss and the data need to be fetched
with an additional delay from an external memory. It is therefore
highly desirable to predict future memory accesses during
execution in order to appropriately prefetch data without incurring
delays. In this paper, we evaluate the potential of several artificial
neural networks for the prediction of instruction memory
addresses. Neural network have the potential to tackle the nonlinear
behavior observed in memory accesses during program
execution and their demonstrated numerous hardware
implementation emphasize this choice over traditional forecasting
techniques for their inclusion in embedded systems. However,
embedded applications execute millions of instructions and
therefore millions of addresses to be predicted. This very
challenging problem of neural network based prediction of large
time series is approached in this paper by evaluating various neural
network architectures based on the recurrent neural network
paradigm with pre-processing based on the Self Organizing Map
(SOM) classification technique.
Abstract: The objectives of this research are to produce
prototype coconut oil based solvent offset printing inks and to
analyze a basic quality of printing work derived from coconut oil
based solvent offset printing inks, by mean of bringing coconut oil
for producing varnish and bringing such varnish to produce black
offset printing inks. Then, analysis of qualities i.e. CIELAB value,
density value, and dot gain value of printing work from coconut oil
based solvent offset printing inks which printed on gloss-coated
woodfree paper weighs 130 grams were done. The research result of
coconut oil based solvent offset printing inks indicated that the
suitable varnish formulation is using 51% of coconut oil, 36% of
phenolic resin, and 14% of solvent oil 14%, while the result of
producing black offset ink displayed that the suitable formula of
printing ink is using varnish mixed with 20% of coconut oil, and the
analyzing printing work of coconut oil based solvent offset printing
inks which printed on paper, the results were as follows: CIELAB
value of black offset printing ink is at L* = 31.90, a* = 0.27, and b* =
1.86, density value is at 1.27 and dot gain value was high at mid tone
area of image area.
Abstract: In modern human computer interaction systems
(HCI), emotion recognition is becoming an imperative characteristic.
The quest for effective and reliable emotion recognition in HCI has
resulted in a need for better face detection, feature extraction and
classification. In this paper we present results of feature space analysis
after briefly explaining our fully automatic vision based emotion
recognition method. We demonstrate the compactness of the feature
space and show how the 2d/3d based method achieves superior features
for the purpose of emotion classification. Also it is exposed that
through feature normalization a widely person independent feature
space is created. As a consequence, the classifier architecture has
only a minor influence on the classification result. This is particularly
elucidated with the help of confusion matrices. For this purpose
advanced classification algorithms, such as Support Vector Machines
and Artificial Neural Networks are employed, as well as the simple k-
Nearest Neighbor classifier.
Abstract: Falling has been one of the major concerns and threats
to the independence of the elderly in their daily lives. With the
worldwide significant growth of the aging population, it is essential
to have a promising solution of fall detection which is able to operate
at high accuracy in real-time and supports large scale implementation
using multiple cameras. Field Programmable Gate Array (FPGA) is a
highly promising tool to be used as a hardware accelerator in many
emerging embedded vision based system. Thus, it is the main
objective of this paper to present an FPGA-based solution of visual
based fall detection to meet stringent real-time requirements with
high accuracy. The hardware architecture of visual based fall
detection which utilizes the pixel locality to reduce memory accesses
is proposed. By exploiting the parallel and pipeline architecture of
FPGA, our hardware implementation of visual based fall detection
using FGPA is able to achieve a performance of 60fps for a series of
video analytical functions at VGA resolutions (640x480). The results
of this work show that FPGA has great potentials and impacts in
enabling large scale vision system in the future healthcare industry
due to its flexibility and scalability.
Abstract: With the development of Internet and databases application techniques, the demand that lots of databases in the Internet are permitted to remote query and access for authorized users becomes common, and the problem that how to protect the copyright of relational databases arises. This paper simply introduces the knowledge of cloud model firstly, includes cloud generators and similar cloud. And then combined with the property of the cloud, a method of protecting relational databases copyright with cloud watermark is proposed according to the idea of digital watermark and the property of relational databases. Meanwhile, the corresponding watermark algorithms such as cloud watermark embedding algorithm and detection algorithm are proposed. Then, some experiments are run and the results are analyzed to validate the correctness and feasibility of the watermark scheme. In the end, the foreground of watermarking relational database and its research direction are prospected.
Abstract: Research in quantum computation is looking for the consequences of having information encoding, processing and communication exploit the laws of quantum physics, i.e. the laws which govern the ultimate knowledge that we have, today, of the foreign world of elementary particles, as described by quantum mechanics. This paper starts with a short survey of the principles which underlie quantum computing, and of some of the major breakthroughs brought by the first ten to fifteen years of research in this domain; quantum algorithms and quantum teleportation are very biefly presented. The next sections are devoted to one among the many directions of current research in the quantum computation paradigm, namely quantum programming languages and their semantics. A few other hot topics and open problems in quantum information processing and communication are mentionned in few words in the concluding remarks, the most difficult of them being the physical implementation of a quantum computer. The interested reader will find a list of useful references at the end of the paper.
Abstract: There is a real threat on the VIPs personal pages on
the Social Network Sites (SNS). The real threats to these pages is
violation of privacy and theft of identity through creating fake pages
that exploit their names and pictures to attract the victims and spread
of lies. In this paper, we propose a new secure architecture that
improves the trusting and finds an effective solution to reduce fake
pages and possibility of recognizing VIP pages on SNS. The
proposed architecture works as a third party that is added to
Facebook to provide the trust service to personal pages for VIPs.
Through this mechanism, it works to ensure the real identity of the
applicant through the electronic authentication of personal
information by storing this information within content of their
website. As a result, the significance of the proposed architecture is
that it secures and provides trust to the VIPs personal pages.
Furthermore, it can help to discover fake page, protect the privacy,
reduce crimes of personality-theft, and increase the sense of trust and
satisfaction by friends and admirers in interacting with SNS.
Abstract: In this paper, a mathematical model of human immunodeficiency
virus (HIV) is utilized and an optimization problem is
proposed, with the final goal of implementing an optimal 900-day
structured treatment interruption (STI) protocol. Two type of commonly
used drugs in highly active antiretroviral therapy (HAART),
reverse transcriptase inhibitors (RTI) and protease inhibitors (PI), are
considered. In order to solving the proposed optimization problem an
adaptive memetic algorithm with population management (AMAPM)
is proposed. The AMAPM uses a distance measure to control the
diversity of population in genotype space and thus preventing the
stagnation and premature convergence. Moreover, the AMAPM uses
diversity parameter in phenotype space to dynamically set the population
size and the number of crossovers during the search process.
Three crossover operators diversify the population, simultaneously.
The progresses of crossover operators are utilized to set the number
of each crossover per generation. In order to escaping the local optima
and introducing the new search directions toward the global optima,
two local searchers assist the evolutionary process. In contrast to
traditional memetic algorithms, the activation of these local searchers
is not random and depends on both the diversity parameters in
genotype space and phenotype space. The capability of AMAPM in
finding optimal solutions compared with three popular metaheurestics
is introduced.
Abstract: The research object was apple-black currant
marmalade candies. Experiments were carried out at the Faculty of
Food Technology of the Latvia University of Agriculture. An active
packaging in combination with modified atmosphere (MAP, CO2
100%) was examined and compared with traditional packaging in air
ambiance. Polymer Multibarrier 60 and paper bags were used.
Influence of iron based oxygen absorber in sachets of 500 cc
obtained from Mitsubishi Gas Chemical Europe Ageless® was tested
on the quality during the shelf of marmalade. Samples of 80±5 g
were packaged in polymer pouches (110 mm x 110 mm),
hermetically sealed by MULTIVAC C300 vacuum chamber machine,
and stored in room temperature +20.0±1.0 °C. The physiochemical
properties – weight losses, moisture content, hardness, aw, pH, colour,
changes of atmosphere content (CO2 and O2) in headspace of packs,
and microbial conditions were analysed before packaging and in the
1st, 3rd , 5th, 8th, 11th and 15th weeks of storage.
Abstract: Space-time block code(STBC) has been studied to get
full diversity and full rate in multiple input multiple output(MIMO)
system. Achieving full rate is difficult in cooperative communications
due to the each user consumes the time slots for transmitting
information in cooperation phase. So combining MIMO systems
with cooperative communications has been researched for full diversity
and full rate. In orthogonal frequency division multiple access
(OFDMA) system, it is an alternative way that each user shares their
allocated subchannels instead of using the MIMO system to improve
the transmission rate. In this paper, a Decode-and-forward (DF)
based cooperative communication scheme is proposed. The proposed
scheme has improved transmission rate and reliability in multi-path
fading channel of the OFDMA up-link condition by modified STBC
structure and subchannel sharing.
Abstract: Content-based music retrieval generally involves analyzing, searching and retrieving music based on low or high level features of a song which normally used to represent artists, songs or music genre. Identifying them would normally involve feature extraction and classification tasks. Theoretically the greater features analyzed, the better the classification accuracy can be achieved but with longer execution time. Technique to select significant features is important as it will reduce dimensions of feature used in classification and contributes to the accuracy. Artificial Immune System (AIS) approach will be investigated and applied in the classification task. Bio-inspired audio content-based retrieval framework (B-ACRF) is proposed at the end of this paper where it embraces issues that need further consideration in music retrieval performances.
Abstract: Latvia is the fourth in the world by means of broadband internet speed. The total number of internet users in Latvia exceeds 70% of its population. The number of active mailboxes of the local internet e-mail service Inbox.lv accounts for 68% of the population and 97.6% of the total number of internet users. The Latvian portal Draugiem.lv is a phenomenon of social media, because 58.4 % of the population and 83.5% of internet users use it. A majority of Latvian company profiles are available on social networks, the most popular being Twitter.com. These and other parameters prove the fact consumers and companies are actively using the Internet.
However, after the authors in a number of studies analyzed how enterprises are employing the e-environment, namely, e-environment tools, they arrived to the conclusions that are not as flattering as the aforementioned statistics. There is an obvious contradiction between the statistical data and the actual studies. As a result, the authors have posed a question: Why are entrepreneurs resistant to e-tools? In order to answer this question, the authors have addressed the Technology Acceptance Model (TAM). The authors analyzed each phase and determined several factors affecting the use of e-environment, reaching the main conclusion that entrepreneurs do not have a sufficient level of e-literacy (digital literacy).
The authors employ well-established quantitative and qualitative methods of research: grouping, analysis, statistic method, factor analysis in SPSS 20 environment etc.
The theoretical and methodological background of the research is formed by, scientific researches and publications, that from the mass media and professional literature, statistical information from legal institutions as well as information collected by the author during the survey.
Abstract: This research aims to create a model for analysis of student motivation behavior on e-Learning based on association rule mining techniques in case of the Information Technology for Communication and Learning Course at Suan Sunandha Rajabhat University. The model was created under association rules, one of the data mining techniques with minimum confidence. The results showed that the student motivation behavior model by using association rule technique can indicate the important variables that influence the student motivation behavior on e-Learning.
Abstract: Sports Sciences has been historically supported by the positivism idea of science, especially by the mechanistic/reductionist and becomes a field that views experimentation and measurement as the mayor research domains. The disposition to simplify nature and the world by parts has fragmented and reduced the idea of bodyathletes as machine. In this paper we intent to re-think this perception lined by Complexity Theory. We come with the idea of athletes as a reflexive and active being (corporeity-body). Therefore, the construction of a training that considers the cultural, biological, psychological elements regarding the experience of the human corporal movements in a circumspect and responsible way could bring better chances of accomplishment. In the end, we hope to help coaches understand the intrinsic complexity of the body they are training, how better deal with it, and, in the field of a deep globalization among the different types of knowledge, to respect and accepted the peculiarities of knowledge that comprise this area.
Abstract: Although Face detection is not a recent activity in the
field of image processing, it is still an open area for research. The
greatest step in this field is the work reported by Viola and its recent
analogous is Huang et al. Both of them use similar features and also
similar training process. The former is just for detecting upright
faces, but the latter can detect multi-view faces in still grayscale
images using new features called 'sparse feature'. Finding these
features is very time consuming and inefficient by proposed methods.
Here, we propose a new approach for finding sparse features using a
genetic algorithm system. This method requires less computational
cost and gets more effective features in learning process for face
detection that causes more accuracy.
Abstract: The lack of inclusive housing in Australia contributes
to the marginalization and exclusion of people with disability and
older people from family and community life. The Australian
government has handed over the responsibility of increasing the
supply of inclusive housing to the housing industry through an agreed
national access standard and a voluntary strategy. Voluntary
strategies have not been successful in other constituencies and little is
known about what would work in Australia today. Findings from a
research project into the voluntariness of the housing industry
indicate that a reliable and consistent supply is unlikely without an
equivalent increase in demand. The strategy has, however, an
important role to play in the task of changing housing industry
practices towards building more inclusive communities.
Abstract: Product customization is an essential requirement for
manufacturing firms to achieve higher customers- satisfaction and
fulfill business target. In order to achieve these objectives, firms need
to handle both external varieties such as customer preference,
government regulations, cultural considerations etc and internal
varieties such as functional requirements of product, production
efficiency, quality etc. Both of the varieties need to be accumulated
and integrated together for the purpose of producing customized
product. These varieties are presented and discussed in this paper
along with the perspectives of modular product design and
development process. Other development strategies such as
modularity, component commonality, product family design and
product platform are presented with a view to achieve product variety
quickly and economically. A case example both for the concept of
modular design and platform based product development process is
also presented with the help of design structure matrix (DSM) tool.
This paper is concluded with several managerial implications and
future research direction.