Abstract: This study investigated the relation between processing information and fitness level of active (fit) and sedentary (unfit) children drawn from rural and urban areas in Botswana. It was hypothesized that fit children would display faster simple reaction time (SRT), choice reaction times (CRT) and movement times (SMT). 60, third grade children (7.0 – 9.0 years) were initially selected and based upon fitness testing, 45 participated in the study (15 each of fit urban, unfit urban, fit rural). All children completed anthropometric measures, skinfold testing and submaximal cycle ergometer testing. The cognitive testing included SRT, CRT, SMT and Choice Movement Time (CMT) and memory sequence length. Results indicated that the rural fit group exhibited faster SMT than the urban fit and unfit groups. For CRT, both fit groups were faster than the unfit group. Collectively, the study shows that the relationship that exists between physical fitness and cognitive function amongst the elderly can tentatively be extended to the pediatric population. Physical fitness could be a factor in the speed at which we process information, including decision making, even in children.
Abstract: As a term for characterizing a process of devising a service system, the term ‘service engineering’ is still regarded as an ‘open’ research challenge due to unspecified details and conflicting perspectives. This paper presents consolidated service engineering ontologies in collecting, specifying and defining relationship between components pertinent within the context of service engineering. The ontologies are built by way of literature surveys from the collected conceptual works by collating various concepts into an integrated ontology. Two ontologies are produced: general service ontology and software service ontology. The software-service ontology is drawn from the informatics domain, while the generalized ontology of a service system is built from both a business management and the information system perspective. The produced ontologies are verified by exercising conceptual operationalizations of the ontologies in adopting several service orientation features and service system patterns. The proposed ontologies are demonstrated to be sufficient to serve as a basis for a service engineering framework.
Abstract: Analysis of fire data is a way for the implementation of any plan to improve the level of safety in cities. Such an analysis is able to reveal signs of changes in a given period and can be used as a measure of safety. The information of about 66,341 fires (from 2002 to 2012) released by Tehran Safety Services and Fire-Fighting Organization and data on the population and the number of households provided by Tehran Municipality and the Statistical Yearbook of Iran were extracted. Using the data, the fire changes, the rate of injuries, and mortality rate were determined and analyzed. The rate of injuries and mortality rate of fires per one million population of Tehran were 59.58% and 86.12%, respectively. During the study period, the number of fires and fire stations increased by 104.38% and 102.63%, respectively. Most fires (9.21%) happened in the 4th District of Tehran. The results showed that the recorded fire data have not been systematically planned for fire prevention since one of the ways to reduce injuries caused by fires is to develop a systematic plan for necessary actions in emergency situations. To determine a reliable source for fire prevention, the stages, definitions of working processes and the cause and effect chains should be considered. Therefore, a comprehensive statistical system should be developed for reported and recorded fire data.
Abstract: Turbocharger is a device that is driven by the turbine and increases efficiency and power output of the engine by forcing external air into the combustion chamber. This study focused on the distribution of stress on the turbine blades and total deformation that may occur during its working along with turbocharger to carry out its static structural analysis of turbine blades. Structural steel was selected as the material for turbocharger. Assembly of turbocharger and turbine blades was designed on PRO ENGINEER. Furthermore, the structural analysis is performed by using ANSYS. This research concluded that by using structural steel, the efficiency of engine is improved and by increasing number of turbine blades, more waste heat from combustion chamber is emitted.
Abstract: Differential is an integral part of four wheeled vehicle, and its main function is to transmit power from drive shaft to wheels. Differential assembly allows both rear wheels to turn at different speed along curved paths. It consists of four gears which are assembled together namely pinion, ring, spider and bevel gears. This research focused on the spider gear and its static structural analysis using ANSYS. The main aim was to evaluate the distribution of stresses on the teeth of the spider gear. This study also analyzed total deformation that may occur during its working along with bevel gear that is meshed with spider gear. Structural steel was chosen for spider gear in this research. Modeling and assembling were done on SolidWorks for both spider and bevel gear. They were assembled exactly same as in a differential assembly. This assembly was then imported to ANSYS. After observing results that maximum amount of stress and deformation was produced in the spider gear, it was concluded that structural steel material for spider gear possesses greater amount of strength to bear maximum stress.
Abstract: Electromagnetic Interference (EMI) shielded doors made from brass extruded channels need to be welded with shielded enclosures to attain optimum shielding performance. Control of welding induced distortion is a problem in welding dissimilar metals like steel and brass. In this research, soldering of the steel-brass joint has been proposed to avoid weld distortion. The material used for brass channel is UNS C36000. The thickness of brass is defined by the manufacturing process, i.e. extrusion. The thickness of shielded enclosure material (ASTM A36) can be varied to produce joint between the dissimilar metals. Steel sections of different gauges are soldered using (91% tin, 9% zinc) solder to the brass, and strength of joint is measured by standard test procedures. It is observed that thin steel sheets produce a stronger bond with brass. The steel sections further require to be welded with shielded enclosure steel sheets through TIG welding process. Stresses and deformation in the vicinity of soldered portion is calculated through FE simulation. Crack formation in soldered area is also studied through experimental work. It has been found that in thin sheets deformation produced due to applied force is localized and has no effect on soldered joint area whereas in thick sheets profound cracks have been observed in soldered joint. The shielding effectiveness of EMI shielded door is compromised due to these cracks. The shielding effectiveness of the specimens is tested and results are compared.
Abstract: This paper presents an optimization method based
on genetic algorithm for the energy management inside buildings
developed in the frame of the project Smart Living Lab (SLL)
in Fribourg (Switzerland). This algorithm optimizes the interaction
between renewable energy production, storage systems and energy
consumers. In comparison with standard algorithms, the innovative
aspect of this project is the extension of the smart regulation
over three simultaneous criteria: the energy self-consumption, the
decrease of greenhouse gas emissions and operating costs. The
genetic algorithm approach was chosen due to the large quantity
of optimization variables and the non-linearity of the optimization
function. The optimization process includes also real time data of the
building as well as weather forecast and users habits. This information
is used by a physical model of the building energy resources to predict
the future energy production and needs, to select the best energetic
strategy, to combine production or storage of energy in order to
guarantee the demand of electrical and thermal energy. The principle
of operation of the algorithm as well as typical output example of
the algorithm is presented.
Abstract: An automated fibre placement method has been
developed to build through-thickness reinforcement into carbon fibre
reinforced plastic laminates during their production, with the goal
of increasing delamination fracture toughness while circumventing
the additional costs and defects imposed by post-layup stitching
and z-pinning. Termed ‘inter-weaving’, the method uses custom
placement sequences of thermoset prepreg tows to distribute regular
fibre link regions in traditionally clean ply interfaces. Inter-weaving’s impact on mode I delamination fracture toughness
was evaluated experimentally through double cantilever beam tests
(ASTM standard D5528-13) on [±15°]9 laminates made from Park
Electrochemical Corp. E-752-LT 1/4” carbon fibre prepreg tape.
Unwoven and inter-woven automated fibre placement samples were
compared to those of traditional laminates produced from standard
uni-directional plies of the same material system. Unwoven automated fibre placement laminates were found to
suffer a mostly constant 3.5% decrease in mode I delamination
fracture toughness compared to flat uni-directional plies. Inter-weaving caused significant local fracture toughness increases
(up to 50%), though these were offset by a matching overall
reduction. These positive and negative behaviours of inter-woven
laminates were respectively found to be caused by fibre breakage
and matrix deformation at inter-weave sites, and the 3D layering
of inter-woven ply interfaces providing numerous paths of least
resistance for crack propagation.
Abstract: In the present work we developed an image processing
algorithm to measure water droplets characteristics during dropwise
condensation on pillared surfaces. The main problem in this process is
the similarity between shape and size of water droplets and the pillars.
The developed method divides droplets into four main groups based
on their size and applies the corresponding algorithm to segment each
group. These algorithms generate binary images of droplets based
on both their geometrical and intensity properties. The information
related to droplets evolution during time including mean radius and
drops number per unit area are then extracted from the binary images.
The developed image processing algorithm is verified using manual
detection and applied to two different sets of images corresponding
to two kinds of pillared surfaces.
Abstract: Structural design and analysis is an important and time-consuming process, particularly at the conceptual design stage. Decisions made at this stage can have an enormous effect on the entire project, as it becomes ever costlier and more difficult to alter the choices made early on in the construction process. Hence, optimisation of the early stages of structural design can provide important efficiencies in terms of cost and time. This paper suggests a structural design optimisation (SDO) framework in which Genetic Algorithms (GAs) may be used to semi-automate the production and optimisation of early structural design alternatives. This framework has the potential to leverage conceptual structural design innovation in Architecture, Engineering and Construction (AEC) projects. Moreover, this framework improves the collaboration between the architectural stage and the structural stage. It will be shown that this SDO framework can make this achievable by generating the structural model based on the extracted data from the architectural model. At the moment, the proposed SDO framework is in the process of validation, involving the distribution of an online questionnaire among structural engineers in the UK.
Abstract: Globular clusters (GC) are important objects for tracing
the early evolution of a galaxy. We study the correlation between the
cluster population and the global properties of the host galaxy. We
found that the correlation between cluster population (NGC) and
the baryonic mass (Mb) of the host galaxy are best described as
10
−5.6038Mb. In order to understand the origin of the U -shape
relation between the GC specific frequency (SN) and Mb (caused
by the high value of SN for dwarfs galaxies and giant ellipticals
and a minimum SN for intermediate mass galaxies≈ 1010M), we
derive a theoretical model for the specific frequency (SNth). The
theoretical model for SNth is based on the slope of the power-law
embedded cluster mass function (β) and different time scale (Δt) of
the forming galaxy. Our results show a good agreement between the
observation and the model at a certain β and Δt. The model seems
able to reproduce higher value of SNth of β = 1.5 at the midst
formation time scale.
Abstract: The Philippine White Mallard duck was compared with Pekin duck for potential meat production. A total of 50 ducklings were randomly assigned to five (5) pens per treatment after one month of brooding. Each pen containing five (5) ducks was considered as a replicate. The ducks were raised until 12 weeks of age and slaughtered at the end of the growing period. Meat from both breeds was analyzed. The data were subjected to the Independent-Sample T-test at 5% level of confidence. Results showed that post-mortem pH (0, 20 minutes, 50 minutes, 1 hour and 20 minutes, 1 hour and 50 minutes, and 24 hours ) did not differ significantly (P>0.05) between breeds. However, Pekin ducks (89.84±0.71) had a significantly higher water-holding capacity than Philippine White Mallard ducks (87.93±0.63) (P0.05) except for the yellowness of the lean muscles of the Pekin duck breast. Pekin duck meat (1.15±0.04) had significantly higher crude fat content than Philippine White Mallard (0.47±0.58). The study clearly showed that breed is a factor and provided some pronounced effects among the parameters. However, these results are considered as preliminary information on the meat quality of Philippine White Mallard duck. Hence, further studies are needed to understand and fully utilize it for meat production and develop different meat products from this breed.
Abstract: While struggling to succeed in today’s complex market environment and provide better customer experience and services, enterprises encompass digital transformation as a means for reaching competitiveness and foster value creation. A digital transformation process consists of information technology implementation projects, as well as organizational factors such as top management support, digital transformation strategy, and organizational changes. However, to the best of our knowledge, there is little evidence about digital transformation endeavors in organizations and how they perceive it – is it only about digital technologies adoption or a true organizational shift is needed? In order to address this issue and as the first step in our research project, a literature review is conducted. The analysis included case study papers from Scopus and Web of Science databases. The following attributes are considered for classification and analysis of papers: time component; country of case origin; case industry and; digital transformation concept comprehension, i.e. focus. Research showed that organizations – public, as well as private ones, are aware of change necessity and employ digital transformation projects. Also, the changes concerning digital transformation affect both manufacturing and service-based industries. Furthermore, we discovered that organizations understand that besides technologies implementation, organizational changes must also be adopted. However, with only 29 relevant papers identified, research positioned digital transformation as an unexplored and emerging phenomenon in information systems research. The scarcity of evidence-based papers calls for further examination of this topic on cases from practice.
Abstract: Digital transformation is one of the latest trends on the global market. In order to maintain the competitive advantage and sustainability, increasing number of organizations are conducting digital transformation processes. Those organizations are changing their business processes and creating new business models with the help of digital technologies. In that sense, one should also observe the role of business process management (BPM) and its maturity in driving digital transformation. Therefore, the goal of this paper is to investigate the role of BPM in digital transformation process within one organization. Since experiences from practice show that organizations from financial sector could be observed as leaders in digital transformation, an insurance company has been selected to participate in the study. That company has been selected due to the high level of its BPM maturity and the fact that it has previously been through a digital transformation process. In order to fulfill the goals of the paper, several interviews, as well as questionnaires, have been conducted within the selected company. The results are presented in a form of a case study. Results indicate that digital transformation process within the observed company has been successful, with special focus on the development of digital strategy, BPM and change management. The role of BPM in the digital transformation of the observed company is further discussed in the paper.
Abstract: Focus on reducing energy consumption in existing
buildings at large scale, e.g. in cities or countries, has been
increasing in recent years. In order to reduce energy consumption
in existing buildings, political incentive schemes are put in place and
large scale investments are made by utility companies. Prioritising
these investments requires a comprehensive overview of the energy
consumption in the existing building stock, as well as potential
energy-savings. However, a building stock comprises thousands
of buildings with different characteristics making it difficult to
model energy consumption accurately. Moreover, the complexity of
the building stock makes it difficult to convey model results to
policymakers and other stakeholders. In order to manage the complexity of the building stock, building
archetypes are often employed in building stock energy models
(BSEMs). Building archetypes are formed by segmenting the building
stock according to specific characteristics. Segmenting the building
stock according to building type and building age is common, among
other things because this information is often easily available. This
segmentation makes it easy to convey results to non-experts. However, using a single archetypical building to represent all
buildings in a segment of the building stock is associated with
loss of detail. Thermal characteristics are aggregated while other
characteristics, which could affect the energy efficiency of a building,
are disregarded. Thus, using a simplified representation of the
building stock could come at the expense of the accuracy of the
model. The present study evaluates the accuracy of a conventional
archetype-based BSEM that segments the building stock according
to building type- and age. The accuracy is evaluated in terms of the
archetypes’ ability to accurately emulate the average energy demands
of the corresponding buildings they were meant to represent. This is
done for the buildings’ energy demands as a whole as well as for
relevant sub-demands. Both are evaluated in relation to the type- and
the age of the building. This should provide researchers, who use
archetypes in BSEMs, with an indication of the expected accuracy
of the conventional archetype model, as well as the accuracy lost in
specific parts of the calculation, due to use of the archetype method.
Abstract: The study of static dielectric properties in a binary mixture of 1,2 dichloroethane (DE) and n,n dimethylformamide (DMF) polar liquids has been carried out in the frequency range of 10 MHz to 30 GHz for 11 different concentration using time domain reflectometry technique at 10ºC temperature. The dielectric relaxation study of solute-solvent mixture at microwave frequencies gives information regarding the creation of monomers and multimers as well as interaction between the molecules of the binary mixture. The least squares fit method is used to determine the values of dielectric parameters such as static dielectric constant (ε0), dielectric constant at high frequency (ε∞) and relaxation time (τ).
Abstract: What people say on social media has turned into a
rich source of information to understand social behavior. Specifically,
the growing use of Twitter social media for political communication
has arisen high opportunities to know the opinion of large numbers
of politically active individuals in real time and predict the global
political tendencies of a specific country. It has led to an increasing
body of research on this topic. The majority of these studies have
been focused on polarized political contexts characterized by only
two alternatives. Unlike them, this paper tackles the challenge
of forecasting Spanish political trends, characterized by multiple
political parties, by means of analyzing the Twitters Users political
tendency. According to this, a new strategy, named Tweets Analysis
Strategy (TAS), is proposed. This is based on analyzing the users
tweets by means of discovering its sentiment (positive, negative or
neutral) and classifying them according to the political party they
support. From this individual political tendency, the global political
prediction for each political party is calculated. In order to do this,
two different strategies for analyzing the sentiment analysis are
proposed: one is based on Positive and Negative words Matching
(PNM) and the second one is based on a Neural Networks Strategy
(NNS). The complete TAS strategy has been performed in a Big-Data
environment. The experimental results presented in this paper reveal
that NNS strategy performs much better than PNM strategy to analyze
the tweet sentiment. In addition, this research analyzes the viability
of the TAS strategy to obtain the global trend in a political context
make up by multiple parties with an error lower than 23%.
Abstract: Fe-based amorphous feedstock powders are used as the matrix into which various ratios of hard B4C nanoparticles (0, 5, 10, 15, 20 vol.%) as reinforcing agents were prepared using a planetary high-energy mechanical milling. The ball-milled nanocomposite feedstock powders were also sprayed by means of high-velocity oxygen fuel (HVOF) technique. The characteristics of the powder particles and the prepared coating depending on their microstructures and nanohardness were examined in detail using nanoindentation tester. The results showed that the formation of the Fe-based amorphous phase was noticed over the course of high-energy ball milling. It is interesting to note that the nanocomposite coating is divided into two regions, namely, a full amorphous phase region and homogeneous dispersion of B4C nanoparticles with a scale of 10–50 nm in a residual amorphous matrix. As the B4C content increases, the nanohardness of the composite coatings increases, but the fracture toughness begins to decrease at the B4C content higher than 20 vol.%. The optimal mechanical properties are obtained with 15 vol.% B4C due to the suitable content and uniform distribution of nanoparticles. Consequently, the changes in mechanical properties of the coatings were attributed to the changes in the brittle to ductile transition by adding B4C nanoparticles.
Abstract: Over the past decade, there has been a steep rise in
the data-driven analysis in major areas of medicine, such as clinical
decision support system, survival analysis, patient similarity analysis,
image analytics etc. Most of the data in the field are well-structured
and available in numerical or categorical formats which can be used
for experiments directly. But on the opposite end of the spectrum,
there exists a wide expanse of data that is intractable for direct
analysis owing to its unstructured nature which can be found in the
form of discharge summaries, clinical notes, procedural notes which
are in human written narrative format and neither have any relational
model nor any standard grammatical structure. An important step
in the utilization of these texts for such studies is to transform
and process the data to retrieve structured information from the
haystack of irrelevant data using information retrieval and data mining
techniques. To address this problem, the authors present Q-Map in
this paper, which is a simple yet robust system that can sift through
massive datasets with unregulated formats to retrieve structured
information aggressively and efficiently. It is backed by an effective
mining technique which is based on a string matching algorithm
that is indexed on curated knowledge sources, that is both fast
and configurable. The authors also briefly examine its comparative
performance with MetaMap, one of the most reputed tools for medical
concepts retrieval and present the advantages the former displays over
the latter.
Abstract: This paper presents a study of Lamb wave damage
diagnosis of composite delamination using instantaneous phase
data. Numerical experiments are performed using the finite element
method. Different sizes of delamination damages are modeled
using finite element package ABAQUS. Lamb wave excitation
and responses data are obtained using a pitch-catch configuration.
Empirical mode decomposition is employed to extract the intrinsic
mode functions (IMF). Hilbert–Huang Transform is applied to each
of the resulting IMFs to obtain the instantaneous phase information.
The baseline data for healthy plates are also generated using the
same procedure. The size of delamination is correlated with the
instantaneous phase change for damage diagnosis. It is observed that
the unwrapped instantaneous phase of shows a consistent behavior
with the increasing delamination size.