Abstract: Data mining idea is mounting rapidly in admiration
and also in their popularity. The foremost aspire of data mining
method is to extract data from a huge data set into several forms that
could be comprehended for additional use. The data mining is a
technology that contains with rich potential resources which could be
supportive for industries and businesses that pay attention to collect
the necessary information of the data to discover their customer’s
performances. For extracting data there are several methods are
available such as Classification, Clustering, Association,
Discovering, and Visualization… etc., which has its individual and
diverse algorithms towards the effort to fit an appropriate model to
the data. STATISTICA mostly deals with excessive groups of data
that imposes vast rigorous computational constraints. These results
trials challenge cause the emergence of powerful STATISTICA Data
Mining technologies. In this survey an overview of the STATISTICA
software is illustrated along with their significant features.
Abstract: The paper tackles the topic of determining the cost of
innovation in software development projects. Innovation can be
achieved either in a planned or unplanned manner. The paper
approaches the scenarios were innovation is planned for. As a starting
point an innovative software development project is analyzed. The
project is depicted step by step as it was implemented, from inception
to delivery. Costs that are proprietary to innovation in software
development are isolated based on the author’s personal experience
in managing the above mentioned project. Innovation costs
components identified by the author are then validated using open
discussions with software development professionals and projects
managers on LinkedIn groups. In order to receive relevant feedback
only groups that focus on software development and innovation
management are targeted. Additional innovation cost components
suggested by software development professionals and projects
managers are also considered. Based on the identified cost
components an indicator is built. The indicator is meant to formalize
the process of determining the cost of innovation in a software
development project. The indicator aggregates all the innovation cost
components that are identified in the research process. The process of
calculating each cost component is also described. Conclusions are
formulated and new related research topics are submitted for debate.
Abstract: This paper introduces a proposal scheme for an
Intelligent System applied to Pedagogical Advising using Case-Based
Reasoning, to find consolidated solutions before used for the new
problems, making easier the task of advising students to the
pedagogical staff. We do intend, through this work, introduce the
motivation behind the choices for this system structure, justifying the
development of an incremental and smart web system who learns
bests solutions for new cases when it’s used, showing technics and
technology.
Abstract: Nitrogen fertilizer is the most used and often the most
mismanaged nutrient input. Nitrogen management has tremendous
implications on crop productivity, quality and environmental
stewardship. Sufficient nitrogen is needed to optimum yield and
quality. Soil and in-season plant tissue testing for nitrogen status are
a time consuming and expensive process. Real time sensing of plant
nitrogen status can be a useful tool in managing nitrogen inputs. The
objectives of this project were to assess the reliability of remotely
sensed non-destructive plant nitrogen measurements compared to wet
chemistry data from sampled plant tissue, develop in-season nitrogen
recommendations based on remotely sensed data for improved
nitrogen use efficiency and assess the potential for determining yield
and quality from remotely sensed data. Very good correlations were
observed between early-season remotely sensed crop nitrogen status
and plant nitrogen concentrations and subsequent in-season fertilizer
recommendations. The transmittance/absorbance type meters gave
the most accurate readings. Early in-season fertilizer recommendation
would be to apply 40 kg nitrogen per hectare plus 15 kg nitrogen per
hectare for each unit difference measured with the SPAD meter
between the crop and reference area or 25 kg plus 13 kg per hectare
for each unit difference measured with the CCM 200. Once the crop
was sufficiently fertilized meter readings became inconclusive and
were of no benefit for determining nitrogen status, silage yield and
quality and grain yield and protein.
Abstract: Customer churn prediction is one of the most useful
areas of study in customer analytics. Due to the enormous amount
of data available for such predictions, machine learning and data
mining have been heavily used in this domain. There exist many
machine learning algorithms directly applicable for the problem of
customer churn prediction, and here, we attempt to experiment on
a novel approach by using a cognitive learning based technique in
an attempt to improve the results obtained by using a combination
of supervised learning methods, with cognitive unsupervised learning
methods.
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: Attributes and methods are the basic contents of an
object-oriented class. The connectivity among these class members
and the relationship between the class and other classes play an
important role in determining the quality of an object-oriented
system. Class cohesion evaluates the degree of relatedness of class
attributes and methods, whereas class coupling refers to the degree to
which a class is related to other classes. Researchers have proposed
several class cohesion and class coupling measures. However, the
correlation between class coupling and class cohesion measures has
not been thoroughly studied. In this paper, using classes of three
open-source Java systems, we empirically investigate the correlation
between several measures of connectivity-based class cohesion and
coupling. Four connectivity-based cohesion measures and eight
coupling measures are considered in the empirical study. The
empirical study results show that class connectivity-based cohesion
and coupling internal quality attributes are inversely correlated. The
strength of the correlation depends highly on the cohesion and
coupling measurement approaches.
Abstract: Despite the highly touted benefits, emerging
technologies have unleashed pervasive concerns regarding unintended
and unforeseen social impacts. Thus, those wishing to create safe and
socially acceptable products need to identify such side effects and
mitigate them prior to the market proliferation. Various methodologies
in the field of technology assessment (TA), namely Delphi, impact
assessment, and scenario planning, have been widely incorporated in
such a circumstance. However, literatures face a major limitation in
terms of sole reliance on participatory workshop activities. They
unfortunately missed out the availability of a massive untapped data
source of futuristic information flooding through the Internet. This
research thus seeks to gain insights into utilization of futuristic data,
future-oriented documents from the Internet, as a supplementary
method to generate social impact scenarios whilst capturing
perspectives of experts from a wide variety of disciplines. To this end,
network analysis is conducted based on the social keywords extracted
from the futuristic documents by text mining, which is then used as a
guide to produce a comprehensive set of detailed scenarios. Our
proposed approach facilitates harmonized depictions of possible
hazardous consequences of emerging technologies and thereby makes
decision makers more aware of, and responsive to, broad qualitative
uncertainties.
Abstract: This study is to fill up a research gap on examining the
differences in normative beliefs (namely acceptance of weaknesses,
acceptance of provoked aggression, and acceptance of unprovoked
aggression) among different subtypes of aggressors and
non-aggressors (reactive aggressors, proactive aggressors,
reactive-proactive aggressors, and non-aggressors). 2,236 students
(1,372 males and 864 females), aged from 11 to 18, completed a
self-reported questionnaire. Results revealed that (a) schoolchildren
with reactive-proactive aggression have the highest acceptance of
provoked aggression, the highest acceptance of unprovoked
aggression, and the lowest acceptance of weakness; (b) schoolchildren
with proactive aggression have higher acceptance of unprovoked
aggression and lower acceptance of weakness than reactive aggressors;
and (c) schoolchildren without aggression have the lowest acceptance
of provoked aggression, the lowest acceptance of unprovoked
aggression, and the highest acceptance of weakness.
Abstract: In this paper, we used data mining to extract
biomedical knowledge. In general, complex biomedical data
collected in studies of populations are treated by statistical methods,
although they are robust, they are not sufficient in themselves to
harness the potential wealth of data. For that you used in step two
learning algorithms: the Decision Trees and Support Vector Machine
(SVM). These supervised classification methods are used to make the
diagnosis of thyroid disease. In this context, we propose to promote
the study and use of symbolic data mining techniques.
Abstract: Electroencephalogram (EEG) is a noninvasive
technique that registers signals originating from the firing of neurons
in the brain. The Emotiv EEG Neuroheadset is a consumer product
comprised of 14 EEG channels and was used to record the reactions
of the neurons within the brain to two forms of stimuli in 10
participants. These stimuli consisted of auditory and visual formats
that provided directions of ‘right’ or ‘left.’ Participants were
instructed to raise their right or left arm in accordance with the
instruction given. A scenario in OpenViBE was generated to both
stimulate the participants while recording their data. In OpenViBE,
the Graz Motor BCI Stimulator algorithm was configured to govern
the duration and number of visual stimuli. Utilizing EEGLAB under
the cross platform MATLAB®, the electrodes most stimulated during
the study were defined. Data outputs from EEGLAB were analyzed
using IBM SPSS Statistics® Version 20. This aided in determining
the electrodes to use in the development of a brain-machine interface
(BMI) using real-time EEG signals from the Emotiv EEG
Neuroheadset. Signal processing and feature extraction were
accomplished via the Simulink® signal processing toolbox. An
Arduino™ Duemilanove microcontroller was used to link the Emotiv
EEG Neuroheadset and the right and left Mecha TE™ Hands.
Abstract: Due to the rapid increase of Internet, web opinion
sources dynamically emerge which is useful for both potential
customers and product manufacturers for prediction and decision
purposes. These are the user generated contents written in natural
languages and are unstructured-free-texts scheme. Therefore, opinion
mining techniques become popular to automatically process customer
reviews for extracting product features and user opinions expressed
over them. Since customer reviews may contain both opinionated and
factual sentences, a supervised machine learning technique applies
for subjectivity classification to improve the mining performance. In
this paper, we dedicate our work is the task of opinion
summarization. Therefore, product feature and opinion extraction is
critical to opinion summarization, because its effectiveness
significantly affects the identification of semantic relationships. The
polarity and numeric score of all the features are determined by
Senti-WordNet Lexicon. The problem of opinion summarization
refers how to relate the opinion words with respect to a certain
feature. Probabilistic based model of supervised learning will
improve the result that is more flexible and effective.
Abstract: This study investigated some results of the use of
digital art tools by junior school children in order to discover if these
tools could promote artistic ability and creativity. The study considers
the ease of use and usefulness of the tools as well as how to assess
artwork produced by digital means. As the use of these tools is a
relatively new development in Art education, this study may help
educators in their choice of which tools to use and when to use them.
The study also aims to present a model for the assessment of
students’ artistic development and creativity by studying their artistic
activity. This model can help in determining differences in students’
creative ability and could be useful both for teachers, as a means of
assessing digital artwork, and for students, by providing the
motivation to use the tools to their fullest extent. Sixteen students
aged nine to ten years old were observed and recorded while they
used the digital drawing tools. The study found that, according to the
students’ own statements, it was not the ease of use but the successful
effects the tools provided which motivated the children to use them.
Abstract: It has become an increasing evident that large
development influences the climate. There are concerns that rising
temperature over developed areas could have negative impact and
increase living discomfort within city boundaries. Temperature trends
in Ibadan city have received little attention, yet the area has
experienced heavy urban expansion between 1972 and 2014. This
research aims at examining the impact of landuse change on surface
temperature knowing that the built-up environment absorb and store
solar energy, resulting into the Urban Heat Island (UHI) effect. The
Landsat imagery was used to examine the landuse change for a
period of 42 years (1972-2014). Land Surface Temperature (LST)
was obtained by converting the thermal band to a surface temperature
map and zonal statistic analyses was used to examine the relationship
between landuse and temperature emission. The results showed that
the settlement area increased to a large extent while the area covered
by vegetation reduced during the study period. The spatial and
temporal trends of surface temperature are related to the gradual
change in urban landuse/landcover and the settlement area has the
highest emission. This research provides useful insight into the
temporal behavior of the Ibadan city.
Abstract: Based on the experimental data, the impact of
resistance and reactance of the winding, as well as the magnetic
permeability of the magnetic circuit steel material on the value of the
electromotive force of the induction converter is investigated. The
obtained results allow estimating the main technological spreads and
determining the maximum level of the electromotive force change.
By the method of experiment planning, the expression of a
polynomial for the electromotive force which can be used to estimate
the adequacy of mathematical models to be used at the investigation
and design of induction converters is obtained.
Abstract: Artificial intelligence applications are commonly used
in industry in many fields in parallel with the developments in the
computer technology. In this study, a fire room was prepared for the
resistance of wooden construction elements and with the mechanism
here, the experiments of polished materials were carried out. By
utilizing from the experimental data, an artificial neural network
(ANN) was modelled in order to evaluate the final cross sections of
the wooden samples remaining from the fire. In modelling,
experimental data obtained from the fire room were used. In the
developed system, the first weight of samples (ws-gr), preliminary
cross-section (pcs-mm2), fire time (ft-minute), and fire temperature
(t-oC) as input parameters and final cross-section (fcs-mm2) as output
parameter were taken. When the results obtained from ANN and
experimental data are compared after making statistical analyses, the
data of two groups are determined to be coherent and seen to have no
meaning difference between them. As a result, it is seen that ANN
can be safely used in determining cross sections of wooden materials
after fire and it prevents many disadvantages.
Abstract: Various personality profile tests are used to identify
personality strengths and limits in individuals, helping both
individuals and managers to optimize work and team effort in
organizations. One such test, the Hartman’s personality profile,
emphasizes four driving "core motives" influenced or affected by
both strengths and limitations classified into four colors: Red -
motivated by power; Blue - discipline and loyalty; White - peace; and
Yellow – fun loving. Two shortcomings of Hartman’s personality test
are noted; 1) only one selection for every item / situation allowed and
2) selection of an item / option even if not applicable. A test taker
may be as much nurturing as he is opinionated but since
“opinionated” seems less attractive the individual would likely select
nurturing, causing a misidentification in personality strengths and
limits. Since few individuals have a “strong” personality, it is
difficult to assess their true personality strengths and limits allowing
only one choice or requiring unwanted choices, undermining the
potential of the test. We modified Hartman’s personality profile
allowing test takers to make either multiple choices for any item /
situation or leave them blank if applicable. Sixty-eight participants
(38 males and 30 females), 17 - 49 years old, from countries in Asia,
Europe, N. America, CIS, Africa, Latin America, and Oceania were
included. 58 participants (85.3%) reported the modified test, allowing
multiple / no choices better identified their personality strengths and
limits, while 10 participants (14.7%) expressed the original (one
choice version) was sufficient. The overall results show that our
modified test enhanced the identification and balance of core
personalities’ strengths and limits, aiding test takers, managers and
organizations to better assess individual characteristics, particularly
useful in making task-related, teamwork, and management decisions.
Abstract: Macro invertebrates have been used to monitor
organic pollution in rivers and streams. Several biotic indices based
on macro invertebrates have been developed over the years including
the Biological Monitoring Working Party (BMWP). A new biotic
index, the Gammarus:Asellus ratio has been recently proposed as an
index of organic pollution. This study tested the validity of the
Gammarus:Asellus ratio as an index of organic pollution, by
examining the relationship between the Gammarus:Asellus ratio and
physical chemical parameters, and other biotic indices such as
BMWP and, Average Score Per Taxon (ASPT) from lakes and
streams at Markeaton Park, Allestree Park and Kedleston Hall,
Derbyshire. Macro invertebrates were sampled using the standard
five minute kick sampling techniques physical and chemical
environmental variables were obtained based on standard sampling
techniques. Eighteen sites were sampled, six sites from Markeaton
Park (three sites across the stream and three sites across the lake). Six
sites each were also sampled from Allestree Park and Kedleston Hall
lakes. The Gammarus:Asellus ratio showed an opposite significant
positive correlations with parameters indicative of organic pollution
such as the level of nitrates, phosphates, and calcium and also
revealed a negatively significant correlations with other biotic indices
(BMWP/ASPT). The BMWP score correlated positively significantly
with some water quality parameters such as dissolved oxygen and
flow rate, but revealed no correlations with other chemical
environmental variables. The BMWP score was significantly higher
in the stream than the lake in Markeaton Park, also The ASPT scores
appear to be significantly higher in the upper Lakes than the middle
and lower lakes. This study has further strengthened the use of
BMWP/ASPT score as an index of organic pollution. But additional
application is required to validate the use of Gammarus:Asellus as a
rapid bio monitoring tool.
Abstract: The aim of this paper is to perform experimental
modal analysis (EMA) of reinforced concrete (RC) square slabs.
EMA is the process of determining the modal parameters (Natural
Frequencies, damping factors, modal vectors) of a structure from a
set of frequency response functions FRFs (curve fitting). Although,
experimental modal analysis (or modal testing) has grown steadily in
popularity since the advent of the digital FFT spectrum analyzer in
the early 1970’s, studying all types of members and materials using
such method have not yet been well documented. Therefore, in this
work, experimental tests were conducted on RC square slab
specimens of dimensions 600mm x 600mmx 40mm. Experimental
analysis was based on freely supported boundary condition.
Moreover, impact testing as a fast and economical means of finding
the modes of vibration of a structure was used during the
experiments. In addition, Pico Scope 6 device and MATLAB
software were used to acquire data, analyze and plot Frequency
Response Function (FRF). The experimental natural frequencies
which were extracted from measurements exhibit good agreement
with analytical predictions. It is showed that EMA method can be
usefully employed to investigate the dynamic behavior of RC slabs.
Abstract: One image is worth more than thousand words.
Images if analyzed can reveal useful information. Low level image
processing deals with the extraction of specific feature from a single
image. Now the question arises: What technique should be used to
extract patterns of very large and detailed image database? The
answer of the question is: “Image Mining”. Image Mining deals with
the extraction of image data relationship, implicit knowledge, and
another pattern from the collection of images or image database. It is
nothing but the extension of Data Mining. In the following paper, not
only we are going to scrutinize the current techniques of image
mining but also present a new technique for mining images using
Genetic Algorithm.