Abstract: In new energy development, wind power has boomed.
It is due to the proliferation of wind parks and their operation in
supplying the national electric grid with low cost and clean resources.
Hence, there is an increased need to establish a proactive
maintenance for wind turbine machines based on remote control and
monitoring. That is necessary with a real-time wireless connection in
offshore or inaccessible locations while the wired method has many
flaws. The objective of this strategy is to prolong wind turbine
lifetime and to increase productivity. The hardware of a remote
control and monitoring system for wind turbine parks is designed. It
takes advantage of GPRS or Wi-Max wireless module to collect data
measurements from different wind machine sensors through IP based
multi-hop communication. Computer simulations with Proteus ISIS
and OPNET software tools have been conducted to evaluate the
performance of the studied system. Study findings show that the
designed device is suitable for application in a wind park.
Abstract: In this paper a scheme is proposed for generating
a programmable current reference which can be implemented
in the CMOS technology. The current can be varied over a
wide range by changing an external voltage applied to one
of the control gates of FGMOS (Floating Gate MOSFET).
For a range of supply voltages and temperature, CMOS
current reference is found to be dependent, this dependence
is compensated by subtracting two current outputs with the
same dependencies on the supply voltage and temperature.
The system performance is found to improve with the
use of FGMOS. Mathematical analysis of the proposed
circuit is done to establish supply voltage and temperature
independence. Simulation and performance evaluation of the
proposed current reference circuit is done using TANNER
EDA Tools. The current reference shows the supply and
temperature dependencies of 520 ppm/V and 312 ppm/oC,
respectively. The proposed current reference can operate down
to 0.9 V supply.
Abstract: Since, today in most countries around the world much
attention is paid to planning the smallest unit in the city i.e. the
residential neighborhoods to achieve sustainable urban development
goals, a variety of assessment tools have been developed to assess
and monitor the sustainability of new developments. One of the most
reliable and widely used assessment tools is LEED-ND rating system.
This paper whit the aim of assessing sustainability level of Roshdieh
neighborhood in Tabriz, has introduced this rating system and applied
it in the study area. The results indicate that Roshdieh has the
potential of achieving the standards of sustainable neighborhoods, but
the present situation is far from the ideal point.
Abstract: Off-site construction methods have played an
important role in the construction sector in the past few decades. It is
increasingly becoming a major alternative technique and strategic
direction compared to traditional in-situ method. It produces a
significant amount of value for the construction industry and the
economy more generally. To date, an impressive number of studies
have been lunched on the perceived perception of off-site
construction. However, it seems that a quantifying benefit on the
offsite construction area is lacking. Therefore, this paper examines
the recent research literature on the benefits of off- site construction
and provides future direction. In the beginning, this paper provides a
brief history and current value of the off-site construction followed
by a detailed discussion on the benefit of off-site construction. These
benefits include but not limited to time saving, quality improvement,
relieving skills shortages, cost reduction and productivity
improvement. Toward this end, off-site construction should learn
from other productive industry similar to services or manufacturing
industry by applying operational management tools and techniques
with extensive focus on employee empowerment will shed the light
on future uptake of Off-site construction. This study is of value in
providing scholars have a clear picture of perceived benefit of off-site
construction research and give an opportunities for future uptake of
off-site method.
Abstract: Life Cycle Cost (LCC) is one of the goals and key
pillars of the construction management science because it comprises
many of the functions and processes necessary, which assist
organisations and agencies to achieve their goals. It has therefore
become important to design and control assets during their whole life
cycle, from the design and planning phase through to disposal phase.
LCCA is aimed to improve the decision making system in the
ownership of assets by taking into account all the cost elements
including to the asset throughout its life.
Current application of LCC approach is impractical during
misunderstanding of the advantages of LCC. This main objective of
this research is to show a different relationship between capital cost
and long-term running costs. One hundred and thirty eight actual
building projects in United Kingdom (UK) were used in order to
achieve and measure the above-mentioned objective of the study. The
result shown that LCC is one of the most significant tools should be
considered on the decision making process.
Abstract: A novel simulation method to determine the
displacements of machine tools due to thermal factors is presented.
The specific characteristic of this method is the employment of
original CAD data from the design process chain, which is
interpreted by an algorithm in terms of geometry-based allocation of
convection and radiation parameters. Furthermore analogous models
relating to the thermal behaviour of machine elements are
automatically implemented, which were gained by extensive
experimental testing with thermography imaging. With this a
transient simulation of the thermal field and in series of the
displacement of the machine tool is possible simultaneously during
the design phase. This method was implemented and is already used
industrially in the design of machining centres in order to improve
the quality of herewith manufactured workpieces.
Abstract: Different strategies and tools are available at the oil
and gas industry for detecting and analyzing tension and possible
fractures in borehole walls. Most of these techniques are based on
manual observation of the captured borehole images. While this
strategy may be possible and convenient with small images and few
data, it may become difficult and suitable to errors when big
databases of images must be treated. While the patterns may differ
among the image area, depending on many characteristics (drilling
strategy, rock components, rock strength, etc.). In this work we
propose the inclusion of data-mining classification strategies in order
to create a knowledge database of the segmented curves. These
classifiers allow that, after some time using and manually pointing
parts of borehole images that correspond to tension regions and
breakout areas, the system will indicate and suggest automatically
new candidate regions, with higher accuracy. We suggest the use of
different classifiers methods, in order to achieve different knowledge
dataset configurations.
Abstract: Health analytics (HA) is used in healthcare systems
for effective decision making, management and planning of
healthcare and related activities. However, user resistances, unique
position of medical data content and structure (including
heterogeneous and unstructured data) and impromptu HA projects
have held up the progress in HA applications. Notably, the accuracy
of outcomes depends on the skills and the domain knowledge of the
data analyst working on the healthcare data. Success of HA depends
on having a sound process model, effective project management and
availability of supporting tools. Thus, to overcome these challenges
through an effective process model, we propose a HA process model
with features from rational unified process (RUP) model and agile
methodology.
Abstract: Web-based Cognitive Writing Instruction (WeCWI) is
a hybrid e-framework for the development of a web-based instruction
(WBI), which contributes towards instructional design and language
development. WeCWI divides its contribution in instructional design
into macro and micro perspectives. In macro perspective, being a 21st
century educator by disseminating knowledge and sharing ideas with
the in-class and global learners is initiated. By leveraging the virtue
of technology, WeCWI aims to transform an educator into an
aggregator, curator, publisher, social networker and ultimately, a
web-based instructor. Since the most notable contribution of
integrating technology is being a tool of teaching as well as a
stimulus for learning, WeCWI focuses on the use of contemporary
web tools based on the multiple roles played by the 21st century
educator. The micro perspective in instructional design draws
attention to the pedagogical approaches focusing on three main
aspects: reading, discussion, and writing. With the effective use of
pedagogical approaches through free reading and enterprises,
technology adds new dimensions and expands the boundaries of
learning capacity. Lastly, WeCWI also imparts the fundamental
theories and models for web-based instructors’ awareness such as
interactionist theory, cognitive information processing (CIP) theory,
computer-mediated communication (CMC), e-learning interactionalbased
model, inquiry models, sensory mind model, and leaning styles
model.
Abstract: Caused by shorter product life cycles and higher
product variety the importance of production ramp ups is increasing.
Even though companies are aware of that fact, up to 40% of the ramp
up projects still miss technical and economical requirements. The
success of a ramp up depends on the planning of human factors,
organizational aspects and technological solutions. Since only partly
considered in scientific literature, this paper lays its focus on the
human factor during production ramp up. There are only incoherent
methods which address the problems in this area. A systematic and
holistic method to improve the capabilities of the employees during
ramp up is missing. The Harada Method is a relatively young
approach for developing highly-skilled workers. It consists of
different worksheets which help employees to set guidelines and
reach overall objectives. This approach is going to be transferred into
a tool for ramp up management.
Abstract: The purpose of this research is to study of consumer
perception and understanding consumer buying behavior that related
between satisfied and factors affecting the purchasing. Methodology
can be classified between qualitative and quantitative approaches for
the qualitative research were interviews from middlemen who bought
organic vegetables, and middlemen related to production and
marketing system. A questionnaire was utilized as a tool to collect
data. Statistics utilized in this research included frequency,
percentage, mean, standard deviation, and multiple regression
analysis. The result show the reason to decision buying motives is
Fresh products of organic vegetables is the most significant factor on
individuals’ income, with a b of –.143, t = –2.470, the price of
organic vegetables is the most significant factor on individuals’
income, with a b of .176, t = 2.561, p value = .011. The results show
that most people with higher income think about the organic products
are expensive and have negative attitudes towards organic vegetable
as individuals with low and medium income level. Therefore,
household income had a significant influence on the purchasing
decision.
Abstract: An anthropometric study applied to 1,115 students of
the Faculty of Chemical Sciences and Engineering of the
Autonomous University of California. Thirteen individual
measurements were taken in a sitting position. The results obtained
allow forming a reliable anthropometric database for statistical
studies and analysis and inferences of specific distributions, so the
opinion of experts in occupational medicine recommendations may
emit to reduce risks resulting in an alteration of the vital signs during
the execution of their school activities. Another use of these analyses
is to use them as a reliable reference for future deeper research, to the
design of spaces, tools, utensils, workstations, with anthropometric
dimensions and ergonomic characteristics suitable to use.
Abstract: The paper presents combined automatic speech
recognition (ASR) of English and machine translation (MT) for
English and Croatian and Croatian-English language pairs in the
domain of business correspondence. The first part presents results of
training the ASR commercial system on English data sets, enriched
by error analysis. The second part presents results of machine
translation performed by free online tool for English and Croatian
and Croatian-English language pairs. Human evaluation in terms of
usability is conducted and internal consistency calculated by
Cronbach's alpha coefficient, enriched by error analysis. Automatic
evaluation is performed by WER (Word Error Rate) and PER
(Position-independent word Error Rate) metrics, followed by
investigation of Pearson’s correlation with human evaluation.
Abstract: This paper presents general results on the Java source
code snippet detection problem. We propose the tool which uses
graph and subgraph isomorphism detection. A number of solutions
for all of these tasks have been proposed in the literature. However,
although that all these solutions are really fast, they compare just the
constant static trees. Our solution offers to enter an input sample
dynamically with the Scripthon language while preserving an
acceptable speed. We used several optimizations to achieve very low
number of comparisons during the matching algorithm.
Abstract: This research is aimed to develop the online-class
scheduling management system and improve as a complex problem
solution, this must take into consideration in various conditions and
factors. In addition to the number of courses, the number of students
and a timetable to study, the physical characteristics of each class
room and regulations used in the class scheduling must also be taken
into consideration. This system is developed to assist management in
the class scheduling for convenience and efficiency. It can provide
several instructors to schedule simultaneously. Both lecturers and
students can check and publish a timetable and other documents
associated with the system online immediately. It is developed in a
web-based application. PHP is used as a developing tool. The
database management system was MySQL. The tool that is used for
efficiency testing of the system is questionnaire. The system was
evaluated by using a Black-Box testing. The sample was composed
of 2 groups: 5 experts and 100 general users. The average and the
standard deviation of results from the experts were 3.50 and 0.67.
The average and the standard deviation of results from the general
users were 3.54 and 0.54. In summary, the results from the research
indicated that the satisfaction of users were in a good level.
Therefore, this system could be implemented in an actual workplace
and satisfy the users’ requirement effectively.
Abstract: Kinematic data wisely correlate vector quantities in
space to scalar parameters in time to assess the degree of symmetry
between the intact limb and the amputated limb with respect to a
normal model derived from the gait of control group participants.
Furthermore, these particular data allow a doctor to preliminarily
evaluate the usefulness of a certain rehabilitation therapy.
Kinetic curves allow the analysis of ground reaction forces (GRFs)
to assess the appropriateness of human motion.
Electromyography (EMG) allows the analysis of the fundamental
lower limb force contributions to quantify the level of gait
asymmetry. However, the use of this technological tool is expensive
and requires patient’s hospitalization. This research work suggests
overcoming the above limitations by applying artificial neural
networks.
Abstract: Over the past era, there have been a lot of efforts and
studies are carried out in growing proficient tools for performing
various tasks in big data. Recently big data have gotten a lot of
publicity for their good reasons. Due to the large and complex
collection of datasets it is difficult to process on traditional data
processing applications. This concern turns to be further mandatory
for producing various tools in big data. Moreover, the main aim of
big data analytics is to utilize the advanced analytic techniques
besides very huge, different datasets which contain diverse sizes from
terabytes to zettabytes and diverse types such as structured or
unstructured and batch or streaming. Big data is useful for data sets
where their size or type is away from the capability of traditional
relational databases for capturing, managing and processing the data
with low-latency. Thus the out coming challenges tend to the
occurrence of powerful big data tools. In this survey, a various
collection of big data tools are illustrated and also compared with the
salient features.
Abstract: This paper aims at finding a suitable neural network
for monitoring congestion level in electrical power systems. In this
paper, the input data has been framed properly to meet the target
objective through supervised learning mechanism by defining normal
and abnormal operating conditions for the system under study. The
congestion level, expressed as line congestion index (LCI), is
evaluated for each operating condition and is presented to the NN
along with the bus voltages to represent the input and target data.
Once, the training goes successful, the NN learns how to deal with a
set of newly presented data through validation and testing
mechanism. The crux of the results presented in this paper rests on
performance comparison of a multi-layered feed forward neural
network with eleven types of back propagation techniques so as to
evolve the best training criteria. The proposed methodology has been
tested on the standard IEEE-14 bus test system with the support of
MATLAB based NN toolbox. The results presented in this paper
signify that the Levenberg-Marquardt backpropagation algorithm
gives best training performance of all the eleven cases considered in
this paper, thus validating the proposed methodology.
Abstract: This research paper aims to identify, analyze and rank
factors affecting labor productivity in Spain with respect to their
relative importance. Using a selected set of 35 factors, a structured
questionnaire survey was utilized as the method to collect data from
companies. Target population is comprised by a random
representative sample of practitioners related with the Spanish
construction industry. Findings reveal the top five ranked factors are
as follows: (1) shortage or late supply of materials; (2) clarity of the
drawings and project documents; (3) clear and daily task assignment;
(4) tools or equipment shortages; (5) level of skill and experience of
laborers. Additionally, this research also pretends to provide simple
and comprehensive recommendations so that they could be
implemented by construction managers for an effective management
of construction labor forces.
Abstract: This research proposes a novel reconstruction protocol
for restoring missing surfaces and low-quality edges and shapes in
photos of artifacts at historical sites. The protocol starts with the
extraction of a cloud of points. This extraction process is based on
four subordinate algorithms, which differ in the robustness and
amount of resultant. Moreover, they use different -but
complementary- accuracy to some related features and to the way
they build a quality mesh. The performance of our proposed protocol
is compared with other state-of-the-art algorithms and toolkits. The
statistical analysis shows that our algorithm significantly outperforms
its rivals in the resultant quality of its object files used to reconstruct
the desired model.