Abstract: This paper is largely a response/critique of Samuel P. Huntington´s Clash of Civilizations thesis. The overriding argument is that Huntington´s thesis is characterized by failure to distinguish between ´groups´ and ´categories´. Multinational civilizations overcoming their internal collective action problems, which would enable them to pursue a unified strategy vis-à-vis the West, is a rather foundational assumption in his theory. Without assigning sufficient intellectual attention to the processes through which multinational civilizations may gain capacity for concerted action i.e. become a group, he contended that the post-cold-war world would be shaped in large measure by interactions among seven or eight major civilizations. Thus, failure in providing a convincing analysis of multi-national civilizations´ transition from categories to groups is a significant weakness in Huntington´s clash theory. It is also suggested that so-called Islamic terrorism and the war on terror is not to be taken as an expression of presence of clash between a Western and an Islamic civilization, as terrorist organizations would be superfluous in a world characterized by clash of civilizations. Consequences of multinational civilizations becoming a group are discussed in relation to contemporary Western superiority.
Abstract: This paper presents a thirteen-level asymmetrical
cascaded H-bridge single phase inverter. In this configuration, the
desired output voltage level is achieved by connecting the DC sources in
different combinations by triggering the switches. The modes of
operation are explained well for positive level generations. Moreover, a
comparison is made with conventional topologies of diode clamped,
flying capacitors and cascaded-H-bridge and some recently proposed
topologies to show the significance of the proposed topology in terms of
reduced part counts. The simulation work has been carried out in
MATLAB/Simulink environment. The experimental work is also carried
out for lower rating to verify the performance and feasibility of the
proposed topology. Further the results are presented for different loading
conditions.
Abstract: This paper studies in details about the need of quadcopter in various fields especially in the place of remote area where the road transportation facility is very less. It is used to monitor and collect data in a specific region. The movement of this quadcopter is controlled by the Raspberry Pi. FPV camera is used for capturing the image and will transmit the image to the receiver which can be monitored using an android smart phone. This is mainly used for surveillance purpose and hidden activities can be captured.
Abstract: Most accidents occur in urban areas, and the most related casualties are vulnerable road users (pedestrians and cyclists). The traffic calming measures (TCMs) are widely used and considered to be successful in reducing speed and traffic volume. However, TCMs create unwanted effects include: noise, emissions, energy consumption, vehicle delays and emergency response time (ERT). Different vertical and horizontal TCMs have been already applied nationally (Sweden) and internationally with different impacts. It is a big challenge among traffic engineers, planners, and policy-makers to choose and priorities the best TCMs to be implemented. This study will assess the existing guidelines for TCMs in relation to safety and ERT with focus on data from Norrkoping city in Sweden. The expected results will save lives, time, and money on particularly Swedish Roads. The study will also review newly technologies and how they can improve safety and reduce ERT.
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: Grape seeds are waste products of wineries and often referred to as an important agricultural and industrial waste product with the potential to be used in pharmaceutical, food, and cosmetic applications. In this study, grape seed oil from traditional Ionian varieties was examined for the determination of the quality and the characteristics of each variety. Initially, the fatty acid methyl ester (FAME) profiles were analyzed using Gas Chromatography-Mass Spectrometry, after transesterification. Furthermore, other quality parameters of the grape seed oils were determined by Spectroscopy techniques, UV-Vis and Raman included. Moreover, the antioxidant capacity of the oil was measured by 2,2'-azino-bis-3-ethylbenzothiazoline-6-sulfonic acid (ABTS) and 2,2-Diphenyl-1-picrylhydrazyl (DPPH) assays and their antioxidant capacity expressed in Trolox equivalents. K and ΔΚ indices were measured in 232, 268, 270 nm, as an oil quality index. The results indicate that the air-dried grape seed total oil content ranged from 5.26 to 8.77% w/w, which is in accordance with the other grape seed varieties tested in similar studies. The composition of grape seed oil is predominated with linoleic and oleic fatty acids, with the linoleic fatty acid ranging from 53.68 to 69.95% and both the linoleic and oleic fatty acids totaling 78-82% of FAMEs, which is analogous to the fatty acid composition of safflower oil. The antioxidant assays ABTS and DPPH scored high, exhibiting that the oils have potential in the cosmetic and culinary businesses. Above that, our results demonstrate that Ionian grape seed oils have prospects that can go further than cosmetic or culinary use, into the pharmaceuticals industry. Finally, the reclamation of grape seeds from wineries waste stream is in accordance with the bio-economy strategic framework and contributes to environmental protection.
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: Knee collateral ligaments play a significant role in restraining excessive frontal motion (varus/valgus rotations). In this investigation, a multiscale frame was developed based on structural hierarchies of the collateral ligaments starting from the bottom (tropocollagen molecule) to up where the fibred reinforced structure established. Experimental data of failure tensile test were considered as the principal driver of the developed model. This model was calibrated statistically using Bayesian calibration due to the high number of unknown parameters. Then the model is scaled up to fit the real structure of the collateral ligaments and simulated under realistic boundary conditions. Predications have been successful in describing the observed transient response of the collateral ligaments during tensile test under pre- and post-damage loading conditions. Collateral ligaments maximum stresses and strengths were observed near to the femoral insertions, a results that is in good agreement with experimental investigations. Also for the first time, damage initiation and propagation were documented with this model as a function of the cross-link density between tropocollagen molecules.
Abstract: This paper deals with measuring and modelling of the quality of the machined surface of the metal machining process. The average surface roughness (Ra) which represents the quality of the machined part was measured during the dry turning of the AISI 4140 steel. A large number of factors with the unknown relations among them influences this parameter, and that is why mathematical modelling is extremely complicated. Different values of cutting speed, feed rate, depth of cut (cutting regime) and workpiece hardness causes different surface roughness values. Modelling with soft computing techniques may be very useful in such cases. This paper presents the usage of the fuzzy logic-based system for determining metal machining process parameter in order to find the proper values of cutting regimes.
Abstract: In this study, the absorbed dose of human organs after injection of 177Lu-DOTATOC was studied based on the biodistribution of the complex in adenocarcinoma breast cancer bearing mice. For this purpose, the biodistribution of the radiolabelled complex was studied and compartmental modeling was applied to calculate the absorbed dose with high precision. As expected, 177Lu-DOTATOC illustrated a notable specific uptake in tumor and pancreas, organs with high level of somatostatin receptor on their surface and the effectiveness of the radio-conjugate for targeting of the breast adenocarcinoma tumors was indicated. The elicited results of modeling were the exponential equations, and those are utilized for obtaining the cumulated activity data by taking their integral. The results also exemplified that non-target absorbed-doses such as the liver, spleen and pancreas were approximately 0.008, 0.004, and 0.039, respectively. While these values were so much lower than target (tumor) absorbed-dose, it seems due to this low toxicity, this complex is a good agent for therapy.
Abstract: Many research projects require accurate delineation of the different land cover type of the agricultural area. Especially it is critically important for the definition of specific plants like cannabis. However, the complexity of vegetation stands structure, abundant vegetation species, and the smooth transition between different seconder section stages make vegetation classification difficult when using traditional approaches such as the maximum likelihood classifier. Most of the time, classification distinguishes only between trees/annual or grain. It has been difficult to accurately determine the cannabis mixed with other plants. In this paper, a mixed distribution models approach is applied to classify pure and mix cannabis parcels using Worldview-2 imagery in the Lakes region of Turkey. Five different land use types (i.e. sunflower, maize, bare soil, and cannabis) were identified in the image. A constrained Gaussian mixture discriminant analysis (GMDA) was used to unmix the image. In the study, 255 reflectance ratios derived from spectral signatures of seven bands (Blue-Green-Yellow-Red-Rededge-NIR1-NIR2) were randomly arranged as 80% for training and 20% for test data. Gaussian mixed distribution model approach is proved to be an effective and convenient way to combine very high spatial resolution imagery for distinguishing cannabis vegetation. Based on the overall accuracies of the classification, the Gaussian mixed distribution model was found to be very successful to achieve image classification tasks. This approach is sensitive to capture the illegal cannabis planting areas in the large plain. This approach can also be used for monitoring and determination with spectral reflections in illegal cannabis planting areas.
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: Various processes are modelled using a discrete phase,
where particles are seeded from a source. Such particles can represent
liquid water droplets, which are affecting the continuous phase by
exchanging thermal energy, momentum, species etc. Discrete phases
are typically modelled using parcel, which represents a collection of
particles, which share properties such as temperature, velocity etc.
When coupling the phases, the exchange rates are integrated over
the cell, in which the parcel is located. This can cause spikes and
fluctuating exchange rates. This paper presents an alternative method of coupling a discrete
and a continuous plug flow phase. This is done using triangular
parcels, which span between nodes following the dynamics of single
droplets. Thus, the triangular parcels are propagated using the corner
nodes. At each time step, the exchange rates are spatially integrated
over the surface of the triangular parcels, which yields a smooth
continuous exchange rate to the continuous phase. The results shows that the method is more stable, converges
slightly faster and yields smooth exchange rates compared with
the steam tube approach. However, the computational requirements
are about five times greater, so the applicability of the alternative
method should be limited to processes, where the exchange rates are
important. The overall balances of the exchanged properties did not
change significantly using the new approach.
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: The constant monitoring of blood glucose level is necessary for maintaining health of patients and to alert medical specialists to take preemptive measures before the onset of any complication as a result of diabetes. The current clinical monitoring of blood glucose uses invasive methods repeatedly which are uncomfortable and may result in infections in diabetic patients. Several attempts have been made to develop non-invasive techniques for blood glucose measurement. In this regard, the existing methods are not reliable and are less accurate. Other approaches claiming high accuracy have not been tested on extended dataset, and thus, results are not statistically significant. It is a well-known fact that acetone concentration in breath has a direct relation with blood glucose level. In this paper, we have developed the first of its kind, reliable and high accuracy breath analyzer for non-invasive blood glucose measurement. The acetone concentration in breath was measured using MQ 138 sensor in the samples collected from local hospitals in Pakistan involving one hundred patients. The blood glucose levels of these patients are determined using conventional invasive clinical method. We propose a linear regression classifier that is trained to map breath acetone level to the collected blood glucose level achieving high accuracy.
Abstract: Classification of high resolution polarimetric Synthetic Aperture Radar (PolSAR) images plays an important role in land cover and land use management. Recently, classification algorithms based on Bag of Visual Words (BOVW) model have attracted significant interest among scholars and researchers in and out of the field of remote sensing. In this paper, BOVW model with pixel based low-level features has been implemented to classify a subset of San Francisco bay PolSAR image, acquired by RADARSAR 2 in C-band. We have used segment-based decision-making strategy and compared the result with the result of traditional Support Vector Machine (SVM) classifier. 90.95% overall accuracy of the classification with the proposed algorithm has shown that the proposed algorithm is comparable with the state-of-the-art methods. In addition to increase in the classification accuracy, the proposed method has decreased undesirable speckle effect of SAR images.
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.