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: Traditional document representation for classification
follows Bag of Words (BoW) approach to represent the term weights.
The conventional method uses the Vector Space Model (VSM) to
exploit the statistical information of terms in the documents and they
fail to address the semantic information as well as order of the terms
present in the documents. Although, the phrase based approach
follows the order of the terms present in the documents rather than
semantics behind the word. Therefore, a semantic concept based
approach is used in this paper for enhancing the semantics by
incorporating the ontology information. In this paper a novel method
is proposed to forecast the intraday stock market price directional
movement based on the sentiments from Twitter and money control
news articles. The stock market forecasting is a very difficult and
highly complicated task because it is affected by many factors such
as economic conditions, political events and investor’s sentiment etc.
The stock market series are generally dynamic, nonparametric, noisy
and chaotic by nature. The sentiment analysis along with wisdom of
crowds can automatically compute the collective intelligence of
future performance in many areas like stock market, box office sales
and election outcomes. The proposed method utilizes collective
sentiments for stock market to predict the stock price directional
movements. The collective sentiments in the above social media have
powerful prediction on the stock price directional movements as
up/down by using Granger Causality test.
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.
Abstract: The building sector is responsible, in many
industrialized countries, for about 40% of the total energy
requirements, so it seems necessary to devote some efforts in this
area in order to achieve a significant reduction of energy
consumption and of greenhouse gases emissions.
The paper presents a study aiming at providing a design
methodology able to identify the best configuration of the system
building/plant, from a technical, economic and environmentally point
of view.
Normally, the classical approach involves a building's energy
loads analysis under steady state conditions, and subsequent selection
of measures aimed at improving the energy performance, based on
previous experience made by architects and engineers in the design
team. Instead, the proposed approach uses a sequence of two wellknown
scientifically validated calculation methods (TRNSYS and
RETScreen), that allow quite a detailed feasibility analysis.
To assess the validity of the calculation model, an existing,
historical building in Central Italy, that will be the object of
restoration and preservative redevelopment, was selected as a casestudy.
The building is made of a basement and three floors, with a
total floor area of about 3,000 square meters.
The first step has been the determination of the heating and
cooling energy loads of the building in a dynamic regime by means,
which allows simulating the real energy needs of the building in
function of its use. Traditional methodologies, based as they are on
steady-state conditions, cannot faithfully reproduce the effects of
varying climatic conditions and of inertial properties of the structure.
With this model is possible to obtain quite accurate and reliable
results that allow identifying effective combinations building-HVAC
system.
The second step has consisted of using output data obtained as
input to the calculation model, which enables to compare different
system configurations from the energy, environmental and financial
point of view, with an analysis of investment, and operation and
maintenance costs, so allowing determining the economic benefit of
possible interventions.
The classical methodology often leads to the choice of
conventional plant systems, while our calculation model provides a
financial-economic assessment for innovative energy systems and
low environmental impact.
Computational analysis can help in the design phase, particularly
in the case of complex structures with centralized plant systems, by
comparing the data returned by the calculation model for different
design options.
Abstract: Pulmonary Function Tests are important non-invasive
diagnostic tests to assess respiratory impairments and provides
quantifiable measures of lung function. Spirometry is the most
frequently used measure of lung function and plays an essential role
in the diagnosis and management of pulmonary diseases. However,
the test requires considerable patient effort and cooperation,
markedly related to the age of patients resulting in incomplete data
sets. This paper presents, a nonlinear model built using Multivariate
adaptive regression splines and Random forest regression model to
predict the missing spirometric features. Random forest based feature
selection is used to enhance both the generalization capability and the
model interpretability. In the present study, flow-volume data are
recorded for N= 198 subjects. The ranked order of feature importance
index calculated by the random forests model shows that the
spirometric features FVC, FEF25, PEF, FEF25-75, FEF50 and the
demographic parameter height are the important descriptors. A
comparison of performance assessment of both models prove that, the
prediction ability of MARS with the `top two ranked features namely
the FVC and FEF25 is higher, yielding a model fit of R2= 0.96 and
R2= 0.99 for normal and abnormal subjects. The Root Mean Square
Error analysis of the RF model and the MARS model also shows that
the latter is capable of predicting the missing values of FEV1 with a
notably lower error value of 0.0191 (normal subjects) and 0.0106
(abnormal subjects) with the aforementioned input features. It is
concluded that combining feature selection with a prediction model
provides a minimum subset of predominant features to train the
model, as well as yielding better prediction performance. This
analysis can assist clinicians with a intelligence support system in the
medical diagnosis and improvement of clinical care.
Abstract: In this paper, the problem of fault detection and
isolation in the attitude control subsystem of spacecraft formation
flying is considered. In order to design the fault detection method, an
extended Kalman filter is utilized which is a nonlinear stochastic state
estimation method. Three fault detection architectures, namely,
centralized, decentralized, and semi-decentralized are designed based
on the extended Kalman filters. Moreover, the residual generation
and threshold selection techniques are proposed for these
architectures.
Abstract: Fungal mutant strains have produced cellulase and
xylanase enzymes, and have induced high hydrolysis with enhanced
of rice straw. The mutants were obtained by exposing Penicillium
strain to UV-light treatments. Screening and selection after treatment
with UV-light were carried out using cellulolytic and xylanolytic
clear zones method to select the hypercellulolytic and
hyperxylanolytic mutants. These mutants were evaluated for their
cellulase and xylanase enzyme production as well as their abilities for
biodegradation of rice straw. The mutant 12 UV/1 produced 306.21%
and 209.91% cellulase and xylanase, respectively, as compared with
the original wild type strain. This mutant showed high capacity of
rice straw degradation. The effectiveness of tested mutant strain and
that of wild strain was compared in relation to enhancing the
composting process of rice straw and animal manures mixture. The
results obtained showed that the compost product of inoculated
mixture with mutant strain (12 UV/1) was the best compared to the
wild strain and un-inoculated mixture. Analysis of the composted
materials showed that the characteristics of the produced compost
were close to those of the high quality standard compost. The results
obtained in the present work suggest that the combination between
rice straw and animal manure could be used for enhancing the
composting process of rice straw and particularly when applied with
fungal decomposer accelerating the composting process.