Abstract: The venture capital becomes more and more advanced
and effective source of the innovation project financing, connected
with a high-risk level. In the developed countries, it plays a key role
in transforming innovation projects into successful businesses and
creating the prosperity of the modern economy. In Russia, there are
many necessary preconditions for creation of the effective venture
investment system: the network of the public institutes for innovation
financing operates; there is a significant number of the small and
medium-sized enterprises, capable to sell production with good
market potential. However, the current system does not confirm the
necessary level of efficiency in practice that can be substantially
explained by the absence of the accurate plan of action to form the
national venture model and by the lack of experience of successful
venture deals with profitable exits in Russian economy. This paper
studies the influence of various factors on the venture industry
development by the example of the IT-sector in Russia. The choice of
the sector is based on the fact, that this segment is the main driver of
the venture capital market growth in Russia, and the necessary set of
data exists. The size of investment of the second round is used as the
dependent variable. To analyse the influence of the previous round,
such determinant as the volume of the previous (first) round
investments is used. There is also used a dummy variable in
regression to examine that the participation of an investor with high
reputation and experience in the previous round can influence the size
of the next investment round. The regression analysis of short-term
interrelations between studied variables reveals prevailing influence
of the volume of the first round investments on the venture
investments volume of the second round. The most important
determinant of the value of the second-round investment is the value
of first–round investment, so it means that the most competitive on
the Russian market are the start-up teams that can attract more money
on the start, and the target market growth is not the factor of crucial
importance. This supports the point of view that VC in Russia is
driven by endogenous factors and not by exogenous ones that are
based on global market growth.
Abstract: There is not much effective guideline on development of design parameters selection on spring back for advanced high strength steel sheet metal in U-channel process during cold forming process. This paper presents the development of predictive model for spring back in U-channel process on advanced high strength steel sheet employing Response Surface Methodology (RSM). The experimental was performed on dual phase steel sheet, DP590 in Uchannel forming process while design of experiment (DoE) approach was used to investigates the effects of four factors namely blank holder force (BHF), clearance (C) and punch travel (Tp) and rolling direction (R) were used as input parameters using two level values by applying Full Factorial design (24 ). From a statistical analysis of variant (ANOVA), result showed that blank holder force (BHF), clearance (C) and punch travel (Tp) displayed significant effect on spring back of flange angle (β2 ) and wall opening angle (β1 ), while rolling direction (R) factor is insignificant. The significant parameters are optimized in order to reduce the spring back behavior using Central Composite Design (CCD) in RSM and the optimum parameters were determined. A regression model for spring back was developed. The effect of individual parameters and their response was also evaluated. The results obtained from optimum model are in agreement with the experimental values.
Abstract: The popularity of quality management system models
continues to grow despite the transitional crisis in 2008. Their
development is associated with demands of the new requirements for
entrepreneurs, such as risk analysis projects and more emphasis on
supervision of outsourced processes. In parallel, it is appropriate to
focus attention on the selection of companies aspiring to a quality
management system. This is particularly important in the automotive
supplier industry, where requirements transferred to the levels in the
supply chain should be clear, transparent and fairly satisfied. The
author has carried out a series of researches aimed at finding the
factors that allow for the effective implementation of the quality
management system in automotive companies. The research was
focused on four groups of companies: 1) manufacturing (parts and
assemblies for the purpose of sale or for vehicle manufacturers), 2)
service (repair and maintenance of the car) 3) services for the
transport of goods or people, 4) commercial (auto parts and vehicles).
The identified determinants were divided into two types of criteria:
internal and external, as well as hard and soft. The article presents the
hard – technical factors that an automotive company must meet in
order to achieve the goal of the quality management system
implementation.
Abstract: Atmospheric carbon dioxide emissions are considered
as the greatest environmental challenge the world is facing today.
The tasks to control the emissions include the recovery of CO2 from
flue gas. This concern has been improved due to recent advances in
materials process engineering resulting in the development of
inorganic gas separation membranes with excellent thermal and
mechanical stability required for most gas separations. This paper,
therefore, evaluates the performance of a highly selective inorganic
membrane for CO2 recovery applications. Analysis of results
obtained is in agreement with experimental literature data. Further
results show the prediction performance of the membranes for gas
separation and the future direction of research. The materials
selection and the membrane preparation techniques are discussed.
Method of improving the interface defects in the membrane and its
effect on the separation performance has also been reviewed and in
addition advances to totally exploit the potential usage of this
innovative membrane.
Abstract: This paper presents a novel algorithm for secure,
reliable and flexible transmission of big data in two hop wireless
networks using cooperative jamming scheme. Two hop wireless
networks consist of source, relay and destination nodes. Big data has
to transmit from source to relay and from relay to destination by
deploying security in physical layer. Cooperative jamming scheme
determines transmission of big data in more secure manner by
protecting it from eavesdroppers and malicious nodes of unknown
location. The novel algorithm that ensures secure and energy balance
transmission of big data, includes selection of data transmitting
region, segmenting the selected region, determining probability ratio
for each node (capture node, non-capture and eavesdropper node) in
every segment, evaluating the probability using binary based
evaluation. If it is secure transmission resume with the two- hop
transmission of big data, otherwise prevent the attackers by
cooperative jamming scheme and transmit the data in two-hop
transmission.
Abstract: Rapid growth of Information Technologies (IT) has
had huge influence on enterprises, and it has contributed to its
promotion and increasingly extensive use in enterprises. Information
Technologies have to a large extent determined the processes taking
place in an enterprise; what is more, IT development has brought the
need to adopt a brand new approach to human resources management
in an enterprise. The use of IT in human resource management
(HRM) is of high importance due to the growing role of information
and information technologies. The aim of this paper is to evaluate the
use of information technologies in human resources management in
enterprises. These practices will be presented in the following areas:
recruitment and selection, development and training, employee
assessment, motivation, talent management, personnel service.
Results of conducted survey show diversity of solutions applied in
particular areas of human resource management. In the future, further
development in this area should be expected, as well as integration of
individual HRM areas, growing mobile-enabled HR processes and
their transfer into the cloud. Presented IT solutions applied in HRM
are highly innovative, which is of great significance due to their
possible implementation in other enterprises.
Abstract: The paper presents new results concerning selection of
optimal information fusion formula for ensembles of C-OTDR
channels. The goal of information fusion is to create an integral
classificator designed for effective classification of seismoacoustic
target events. The LPBoost (LP-β and LP-B variants), the Multiple
Kernel Learning, and Weighing of Inversely as Lipschitz Constants
(WILC) approaches were compared. The WILC is a brand new
approach to optimal fusion of Lipschitz Classifiers Ensembles.
Results of practical usage are presented.
Abstract: In the present study, RBF neural networks were used
for predicting the performance and emission parameters of a
biodiesel engine. Engine experiments were carried out in a 4 stroke
diesel engine using blends of diesel and Honge methyl ester as the
fuel. Performance parameters like BTE, BSEC, Tex and emissions
from the engine were measured. These experimental results were
used for ANN modeling.
RBF center initialization was done by random selection and by
using Clustered techniques. Network was trained by using fixed and
varying widths for the RBF units. It was observed that RBF results
were having a good agreement with the experimental results.
Networks trained by using clustering technique gave better results
than using random selection of centers in terms of reduced MRE and
increased prediction accuracy. The average MRE for the performance
parameters was 3.25% with the prediction accuracy of 98% and for
emissions it was 10.4% with a prediction accuracy of 80%.
Abstract: The aim of this research is to identify the key factors in shipping company’s port selection in order to providing their requirement. To identify and rank factors that play the main role in selecting port for providing the ship requirement, at the first step, data were collected via Semi-structured interviews, the aim was to generate knowledge on how shipping company select the port and suppliers for providing their needs. 37 port selection factors were chosen from the previous researches and field interviews and have been categorized into two groups of port's factor and the factors of services of suppliers companies. The current study adopts a questionnaire survey to the main shipping companies' operators in Iran. Their responses reveal that level of services of supplying companies and customs rules play the important role in selecting the ports. Our findings could affect decisions made by port authorities to consider that supporting the privet sections for ship chandelling business could have the best result in attracting ships.
Abstract: Quality of Service (QoS) attributes as part of the
service description is an important factor for service attribute. It is not
easy to exactly quantify the weight of each QoS conditions since
human judgments based on their preference causes vagueness. As
web services selection requires optimization, evolutionary computing
based on heuristics to select an optimal solution is adopted. In this
work, the evolutionary computing technique Particle Swarm
Optimization (PSO) is used for selecting a suitable web services
based on the user’s weightage of each QoS values by optimizing the
QoS weight vector and thereby finding the best weight vectors for
best services that is being selected. Finally the results are compared
and analyzed using static inertia weight and deterministic inertia
weight of PSO.
Abstract: In the past few years, the amount of malicious software
increased exponentially and, therefore, machine learning algorithms
became instrumental in identifying clean and malware files through
(semi)-automated classification. When working with very large
datasets, the major challenge is to reach both a very high malware
detection rate and a very low false positive rate. Another challenge
is to minimize the time needed for the machine learning algorithm to
do so. This paper presents a comparative study between different
machine learning techniques such as linear classifiers, ensembles,
decision trees or various hybrids thereof. The training dataset consists
of approximately 2 million clean files and 200.000 infected files,
which is a realistic quantitative mixture. The paper investigates the
above mentioned methods with respect to both their performance
(detection rate and false positive rate) and their practicability.
Abstract: One of the crucial parameters of digital cryptographic
systems is the selection of the keys used and their distribution. The
randomness of the keys has a strong impact on the system’s security
strength being difficult to be predicted, guessed, reproduced, or
discovered by a cryptanalyst. Therefore, adequate key randomness
generation is still sought for the benefit of stronger cryptosystems.
This paper suggests an algorithm designed to generate and test
pseudo random number sequences intended for cryptographic
applications. This algorithm is based on mathematically manipulating
a publically agreed upon information between sender and receiver
over a public channel. This information is used as a seed for
performing some mathematical functions in order to generate a
sequence of pseudorandom numbers that will be used for
encryption/decryption purposes. This manipulation involves
permutations and substitutions that fulfill Shannon’s principle of
“confusion and diffusion”. ASCII code characters were utilized in the
generation process instead of using bit strings initially, which adds
more flexibility in testing different seed values. Finally, the obtained
results would indicate sound difficulty of guessing keys by attackers.
Abstract: A total of 115 yeast strains isolated from local cassava
processing wastes were measured for crude protein content. Among
these strains, the strain MSY-2 possessed the highest protein
concentration (>3.5 mg protein/mL). By using molecular
identification tools, it was identified to be a strain of Pichia
kudriavzevii based on similarity of D1/D2 domain of 26S rDNA
region. In this study, to optimize the protein production by MSY-2
strain, Response Surface Methodology (RSM) was applied. The
tested parameters were the carbon content, nitrogen content, and
incubation time. Here, the value of regression coefficient (R2) =
0.7194 could be explained by the model which is high to support the
significance of the model. Under the optimal condition, the protein
content was produced up to 3.77 g per L of the culture and MSY-2
strain contains 66.8 g protein per 100 g of cell dry weight. These
results revealed the plausibility of applying the novel strain of yeast
in single-cell protein production.
Abstract: We proposed a Hyperbolic Gompertz Growth Model
(HGGM), which was developed by introducing a shape parameter
(allometric). This was achieved by convoluting hyperbolic sine
function on the intrinsic rate of growth in the classical gompertz
growth equation. The resulting integral solution obtained
deterministically was reprogrammed into a statistical model and used
in modeling the height and diameter of Pines (Pinus caribaea). Its
ability in model prediction was compared with the classical gompertz
growth model, an approach which mimicked the natural variability of
height/diameter increment with respect to age and therefore provides
a more realistic height/diameter predictions using goodness of fit
tests and model selection criteria. The Kolmogorov Smirnov test and
Shapiro-Wilk test was also used to test the compliance of the error
term to normality assumptions while the independence of the error
term was confirmed using the runs test. The mean function of top
height/Dbh over age using the two models under study predicted
closely the observed values of top height/Dbh in the hyperbolic
gompertz growth models better than the source model (classical
gompertz growth model) while the results of R2, Adj. R2, MSE and
AIC confirmed the predictive power of the Hyperbolic Gompertz
growth models over its source model.
Abstract: The paper presents a new method for efficient
innovation process management. Even though the innovation
management methods, tools and knowledge are well established and
documented in literature, most of the companies still do not manage it
efficiently. Especially in SMEs the front end of innovation - problem
identification, idea creation and selection - is often not optimally
performed. Our eMIPS methodology represents a sort of "umbrella
methodology" - a well-defined set of procedures, which can be
dynamically adapted to the concrete case in a company. In daily
practice, various methods (e.g. for problem identification and idea
creation) can be applied, depending on the company's needs. It is
based on the proactive involvement of the company's employees
supported by the appropriate methodology and external experts. The
presented phases are performed via a mixture of face-to-face
activities (workshops) and online (eLearning) activities taking place
in eLearning Moodle environment and using other e-communication
channels. One part of the outcomes is an identified set of
opportunities and concrete solutions ready for implementation. The
other also very important result is connected to innovation
competences for the participating employees related with concrete
tools and methods for idea management. In addition, the employees
get a strong experience for dynamic, efficient and solution oriented
managing of the invention process. The eMIPS also represents a way
of establishing or improving the innovation culture in the
organization. The first results in a pilot company showed excellent
results regarding the motivation of participants and also as to the
results achieved.
Abstract: The material selection in the design of the sandwich
structures is very crucial aspect because of the positive or negative
influences of the base materials to the mechanical properties of the
entire panel. In the literature, it was presented that the selection of the
skin and core materials plays very important role on the behavior of
the sandwich. Beside this, the use of the correct adhesive can make
the whole structure to show better mechanical results and behavior.
In the present work, the static three-point bending tests were
performed on the sandwiches having an aluminum alloy foam core,
the skins made of three different types of fabrics and two different
commercial adhesives (flexible polyurethane and toughened epoxy
based) at different values of support span distances by aiming the
analyses of their flexural performance in terms of absorbed energy,
peak force values and collapse mechanisms. The main results of the
flexural loading are: force-displacement curves obtained after the
bending tests, peak force and absorbed energy values, collapse
mechanisms and adhesion quality. The experimental results presented
that the sandwiches with epoxy based toughened adhesive and the
skins made of S-Glass Woven fabrics indicated the best adhesion
quality and mechanical properties. The sandwiches with toughened
adhesive exhibited higher peak force and energy absorption values
compared to the sandwiches with flexible adhesive. The use of these
sandwich structures can lead to a weight reduction of the transport
vehicles, providing an adequate structural strength under operating
conditions.
Abstract: This paper shortly describes various types of biomass
and a growing number of facilities utilizing the biomass in the Czech
Republic. The considerable part of this paper deals with energy
parameters of the most frequently used types of biomass and results
of their gasification testing. Sixteen most used "Czech" woody plants
and grasses were selected; raw, element and biochemical analyses
were performed and basic calorimetric values, ash composition, and
ash characteristic temperatures were identified. Later, each biofuel
was tested in a fluidized bed gasifier. The essential part of this paper
provides results of the gasification of selected biomass types.
Operating conditions are described in detail with a focus on
individual fuels properties. Gas composition and impurities content
are also identified. In terms of operating conditions and gas quality,
the essential difference occurred mainly between woody plants and
grasses. The woody plants were evaluated as more suitable fuels for
fluidized bed gasifiers. Testing results significantly help with a
decision-making process regarding suitability of energy plants for
growing and with a selection of optimal biomass-treatment
technology.
Abstract: Machining of hard materials is a recent technology for
direct production of work-pieces. The primary challenge in
machining these materials is selection of cutting tool inserts which
facilitates an extended tool life and high-precision machining of the
component. These materials are widely for making precision parts for
the aerospace industry. Nickel-based alloys are typically used in
extreme environment applications where a combination of strength,
corrosion resistance and oxidation resistance material characteristics
are required. The present paper reports the theoretical and
experimental investigations carried out to understand the influence of
machining parameters on the response parameters. Considering the
basic machining parameters (speed, feed and depth of cut) a study has
been conducted to observe their influence on material removal rate,
surface roughness, cutting forces and corresponding tool wear.
Experiments are designed and conducted with the help of Central
Composite Rotatable Design technique. The results reveals that for a
given range of process parameters, material removal rate is favorable
for higher depths of cut and low feed rate for cutting forces. Low feed
rates and high values of rotational speeds are suitable for better finish
and higher tool life.
Abstract: To determine the potential of a low cost Irish
engineered timber product to replace high cost solid timber for use in
bending active structures such as gridshells a single Irish engineered
timber product in the form of orientated strand board (OSB) was
selected. A comparative study of OSB and solid timber was carried
out to determine the optimum properties that make a material suitable
for use in gridshells. Three parameters were identified to be relevant
in the selection of a material for gridshells. These three parameters
are the strength to stiffness ratio, the flexural stiffness of
commercially available sections, and the variability of material and
section properties. It is shown that when comparing OSB against
solid timber, OSB is a more suitable material for use in gridshells that
are at the smaller end of the scale and that have tight radii of
curvature. Typically, for solid timber materials, stiffness is used as an
indicator for strength and engineered timber is no different. Thus, low
flexural stiffness would mean low flexural strength. However, when
it comes to bending active gridshells, OSB offers a significant
advantage. By the addition of multiple layers, an increased section
size is created, thus endowing the structure with higher stiffness and
higher strength from initial low stiffness and low strength materials
while still maintaining tight radii of curvature. This allows OSB to
compete with solid timber on large scale gridshells. Additionally, a
preliminary sustainability study using a set of sustainability indicators
was carried out to determine the relative sustainability of building a
large-scale gridshell in Ireland with a primary focus on economic
viability but a mention is also given to social and environmental
aspects. For this, the Savill garden gridshell in the UK was used as
the functional unit with the sustainability of the structural roof
skeleton constructed from UK larch solid timber being compared
with the same structure using Irish OSB. Albeit that the advantages of
using commercially available OSB in a bending active gridshell are
marginal and limited to specific gridshell applications, further study
into an optimised engineered timber product is merited.
Abstract: Power Regeneration in Refrigeration Plant concept
has been analyzed and has been shown to be capable of saving about
25% power in Cryogenic Plants with the Power Regeneration System
(PRS) running under nominal conditions. The innovative component
Compressor Expander Group (CEG) based on turbomachinery has
been designed and built modifying CETT compressor and expander,
both selected for optimum plant performance. Experiments have
shown the good response of the turbomachines to run with R404a as
working fluid. Power saving up to 12% under PRS derated conditions
(50% loading) has been demonstrated. Such experiments allowed
predicting a power saving up to 25% under CEG full load.