Abstract: A large amount of software products offer a wide
range and number of features. This is called featuritis or creeping
featurism and tends to rise with each release of the product. Feautiris
often adds unnecessary complexity to software, leading to longer
learning curves and overall confusing the users and degrading their
experience. We take a look to a new design approach tendency that
has been coming up, the so-called “What You Get is What You
Need” concept that argues that products should be very focused,
simple and with minimalistic interfaces in order to help users conduct
their tasks in distraction-free ambiences. This isn’t as simple to
implement as it might sound and the developers need to cut down
features. Our contribution illustrates and evaluates this design method
through a novel distraction-free diagramming tool named Delineato
Pro for Mac OS X in which the user is confronted with an empty
canvas when launching the software and where tools only show up
when really needed.
Abstract: Over the past few years, a lot of research has been
conducted to bring Automatic Speech Recognition (ASR) into various
areas of Air Traffic Control (ATC), such as air traffic control
simulation and training, monitoring live operators for with the aim
of safety improvements, air traffic controller workload measurement
and conducting analysis on large quantities controller-pilot speech.
Due to the high accuracy requirements of the ATC context and its
unique challenges, automatic speech recognition has not been widely
adopted in this field. With the aim of providing a good starting
point for researchers who are interested bringing automatic speech
recognition into ATC, this paper gives an overview of possibilities
and challenges of applying automatic speech recognition in air traffic
control. To provide this overview, we present an updated literature
review of speech recognition technologies in general, as well as
specific approaches relevant to the ATC context. Based on this
literature review, criteria for selecting speech recognition approaches
for the ATC domain are presented, and remaining challenges and
possible solutions are discussed.
Abstract: This research paper presents guiding on how to design
social media into higher education courses. The research
methodology used a survey approach. The research instrument was a
questionnaire about guiding on how to design social media into
higher education courses. Thirty-one lecturers completed the
questionnaire. The data were scored by frequency and percentage.
The research results were the lecturers’ opinions concerning the
designing social media into higher education courses as follows: 1)
Lecturers deem that the most suitable learning theory is Collaborative
Learning. 2) Lecturers consider that the most important learning and
innovation Skill in the 21st century is communication and
collaboration skills. 3) Lecturers think that the most suitable
evaluation technique is authentic assessment. 4) Lecturers consider
that the most appropriate portion used as blended learning should be
70% in the classroom setting and 30% online.
Abstract: In this paper, we report the development of the device
for diagnostics of cardiovascular system state and associated
automated workstation for large-scale medical measurement data
collection and analysis. It was shown that optimal design for the
monitoring device is wristband as it represents engineering trade-off
between accuracy and usability. Monitoring device is based on the
infrared reflective photoplethysmographic sensor, which allows
collecting multiple physiological parameters, such as heart rate and
pulsing wave characteristics. Developed device uses BLE interface
for medical and supplementary data transmission to the coupled
mobile phone, which processes it and send it to the doctor's
automated workstation. Results of this experimental model
approbation confirmed the applicability of the proposed approach.
Abstract: Standard Gibbs energy of formation ΔGfor(298.15) of
lanthanide-iron double oxides of garnet-type crystal structure
R3Fe5O12 - RIG (R – are rare earth ions) from initial oxides are
evaluated. The calculation is based on the data of standard entropies
S298.15 and standard enthalpies ΔH298.15 of formation of compounds
which are involved in the process of garnets synthesis. Gibbs energy
of formation is presented as temperature function ΔGfor(T) for the
range 300-1600K. The necessary starting thermodynamic data were
obtained from calorimetric study of heat capacity – temperature
functions and by using the semi-empirical method for calculation of
ΔH298.15 of formation. Thermodynamic functions for standard
temperature – enthalpy, entropy and Gibbs energy - are
recommended as reference data for technological evaluations.
Through the structural series of rare earth-iron garnets the correlation
between thermodynamic properties and characteristics of lanthanide
ions are elucidated.
Abstract: In this article, we deal with a variant of the classical
course timetabling problem that has a practical application in many
areas of education. In particular, in this paper we are interested in
high schools remedial courses. The purpose of such courses is to
provide under-prepared students with the skills necessary to succeed
in their studies. In particular, a student might be under prepared in
an entire course, or only in a part of it. The limited availability
of funds, as well as the limited amount of time and teachers at
disposal, often requires schools to choose which courses and/or which
teaching units to activate. Thus, schools need to model the training
offer and the related timetabling, with the goal of ensuring the
highest possible teaching quality, by meeting the above-mentioned
financial, time and resources constraints. Moreover, there are some
prerequisites between the teaching units that must be satisfied. We
first present a Mixed-Integer Programming (MIP) model to solve
this problem to optimality. However, the presence of many peculiar
constraints contributes inevitably in increasing the complexity of
the mathematical model. Thus, solving it through a general-purpose
solver may be performed for small instances only, while solving
real-life-sized instances of such model requires specific techniques
or heuristic approaches. For this purpose, we also propose a heuristic
approach, in which we make use of a fast constructive procedure
to obtain a feasible solution. To assess our exact and heuristic
approaches we perform extensive computational results on both
real-life instances (obtained from a high school in Lecce, Italy) and
randomly generated instances. Our tests show that the MIP model is
never solved to optimality, with an average optimality gap of 57%.
On the other hand, the heuristic algorithm is much faster (in about the
50% of the considered instances it converges in approximately half of
the time limit) and in many cases allows achieving an improvement
on the objective function value obtained by the MIP model. Such an
improvement ranges between 18% and 66%.
Abstract: An approach was evaluated for the retrieval of soil
moisture of bare soil surface using bistatic scatterometer data in the
angular range of 200 to 700 at VV- and HH- polarization. The
microwave data was acquired by specially designed X-band (10
GHz) bistatic scatterometer. The linear regression analysis was done
between scattering coefficients and soil moisture content to select the
suitable incidence angle for retrieval of soil moisture content. The 250
incidence angle was found more suitable. The support vector
regression analysis was used to approximate the function described
by the input output relationship between the scattering coefficient and
corresponding measured values of the soil moisture content. The
performance of support vector regression algorithm was evaluated by
comparing the observed and the estimated soil moisture content by
statistical performance indices %Bias, root mean squared error
(RMSE) and Nash-Sutcliffe Efficiency (NSE). The values of %Bias,
root mean squared error (RMSE) and Nash-Sutcliffe Efficiency
(NSE) were found 2.9451, 1.0986 and 0.9214 respectively at HHpolarization.
At VV- polarization, the values of %Bias, root mean
squared error (RMSE) and Nash-Sutcliffe Efficiency (NSE) were
found 3.6186, 0.9373 and 0.9428 respectively.
Abstract: Indonesia has experienced annual forest fires that have
rapidly destroyed and degraded its forests. Fires in the peat swamp
forests of Riau Province, have set the stage for problems to worsen,
this being the ecosystem most prone to fires (which are also the most
difficult, to extinguish). Despite various efforts to curb deforestation,
and forest degradation processes, severe forest fires are still
occurring. To find an effective solution, the basic causes of the
problems must be identified. It is therefore critical to have an indepth
understanding of the underlying causal factors that have
contributed to deforestation and forest degradation as a whole, in
order to attain reductions in their rates. An assessment of the drivers of deforestation and forest
degradation was carried out, in order to design and implement
measures that could slow these destructive processes. Research was
conducted in Giam Siak Kecil–Bukit Batu Biosphere Reserve
(GSKBB BR), in the Riau Province of Sumatera, Indonesia. A
biosphere reserve was selected as the study site because such reserves
aim to reconcile conservation with sustainable development. A
biosphere reserve should promote a range of local human activities,
together with development values that are in line spatially and
economically with the area conservation values, through use of a
zoning system. Moreover, GSKBB BR is an area with vast peatlands,
and is experiencing forest fires annually. Various factors were
analysed to assess the drivers of deforestation and forest degradation
in GSKBB BR; data were collected from focus group discussions
with stakeholders, key informant interviews with key stakeholders,
field observation and a literature review. Landsat satellite imagery was used to map forest-cover changes
for various periods. Analysis of landsat images, taken during the
period 2010-2014, revealed that within the non-protected area of core
zone, there was a trend towards decreasing peat swamp forest areas,
increasing land clearance, and increasing areas of community oilpalm
and rubber plantations. Fire was used for land clearing and most
of the forest fires occurred in the most populous area (the transition
area). The study found a relationship between the deforested/
degraded areas, and certain distance variables, i.e. distance from
roads, villages and the borders between the core area and the buffer
zone. The further the distance from the core area of the reserve, the
higher was the degree of deforestation and forest degradation. Research findings suggested that agricultural expansion may be
the direct cause of deforestation and forest degradation in the reserve,
whereas socio-economic factors were the underlying driver of forest
cover changes; such factors consisting of a combination of sociocultural,
infrastructural, technological, institutional (policy and governance), demographic (population pressure) and economic
(market demand) considerations. These findings indicated that local
factors/problems were the critical causes of deforestation and
degradation in GSKBB BR. This research therefore concluded that
reductions in deforestation and forest degradation in GSKBB BR
could be achieved through ‘local actor’-tailored approaches such as
community empowerment.
Abstract: Different terms of the Statistical Process Control (SPC)
has sketch in the fuzzy environment. However, Measurement System
Analysis (MSA), as a main branch of the SPC, is rarely investigated
in fuzzy area. This procedure assesses the suitability of the data to be
used in later stages or decisions of the SPC. Therefore, this research
focuses on some important measures of MSA and through a new
method introduces the measures in fuzzy environment. In this
method, which works based on Buckley approach, imprecision and
vagueness nature of the real world measurement are considered
simultaneously. To do so, fuzzy version of the gauge capability (Cg
and Cgk) are introduced. The method is also explained through
example clearly.
Abstract: In this communication, a low-cost circularly
polarized wire antenna exhibiting improved gain performance for
Dedicated Short Range Communications (DSRC), vehicle-to-vehicle
(V2V) and vehicle-to-infrastructure (V2I) communications is
presented. The proposed antenna comprises a Y-shaped quarterwavelength
monopole antenna surrounded by two iterations of eight
conductive arched walls acting as parasitic elements to enhance the
overall antenna gain and to shape the radiation pattern in the H-plane.
A hemispherical radome shell is added to protect the antenna
structure and its effect on the antenna performance is discussed. The
designed antenna demonstrates antenna gain of 8.2 dB with
omnidirectional far-field radiation pattern in the H-plane. The gain of
the proposed antenna is also compared with the characteristic of the
stand-alone Y-shaped monopole to highlight the advantages of the
proposed approach.
Abstract: Feature selection has been used in many fields such as
classification, data mining and object recognition and proven to be
effective for removing irrelevant and redundant features from the
original dataset. In this paper, a new design of distributed intrusion
detection system using a combination feature selection model based
on bees and decision tree. Bees algorithm is used as the search
strategy to find the optimal subset of features, whereas decision tree
is used as a judgment for the selected features. Both the produced
features and the generated rules are used by Decision Making Mobile
Agent to decide whether there is an attack or not in the networks.
Decision Making Mobile Agent will migrate through the networks,
moving from node to another, if it found that there is an attack on one
of the nodes, it then alerts the user through User Interface Agent or
takes some action through Action Mobile Agent. The KDD Cup 99
dataset is used to test the effectiveness of the proposed system. The
results show that even if only four features are used, the proposed
system gives a better performance when it is compared with the
obtained results using all 41 features.
Abstract: Latin America is probably the region with greater
social inequality, contrary to the amount of rights enshrined in their
constitutions. In the last decade of the twentieth century, the area
resulted in significant changes to democratization and constitutional
changes. Through low-key public policy, political leaders activated
participation in the culture of human rights. The struggle for social
rights in Latin America has been a constant regulation. His
consecration at the constitutional level has chained search
application. The constitutionalization and judicial protection of these
rights have been crucial in countries like Argentina, Venezuela, Peru
and Colombia. This paper presents an analytical view on the
constitutionalization of social rights in the Latin American context
and its justiciability.
Abstract: File sharing in networks is generally achieved using
Peer-to-Peer (P2P) applications. Structured P2P approaches are
widely used in adhoc networks due to its distributed and scalability
features. Efficient mechanisms are required to handle the huge
amount of data distributed to all peers. The intrinsic characteristics of
P2P system makes for easier content distribution when compared to
client-server architecture. All the nodes in a P2P network act as both
client and server, thus, distributing data takes lesser time when
compared to the client-server method. CHORD protocol is a resource
routing based where nodes and data items are structured into a 1-
dimensional ring. The structured lookup algorithm of Chord is
advantageous for distributed P2P networking applications. However,
structured approach improves lookup performance in a high
bandwidth wired network it could contribute to unnecessary overhead
in overlay networks leading to degradation of network performance.
In this paper, the performance of existing CHORD protocol on
Wireless Mesh Network (WMN) when nodes are static and dynamic
is investigated.
Abstract: The purpose of this study is the discrimination of 28
postmenopausal with osteoporotic femoral fractures from an agematched
control group of 28 women using texture analysis based on
fractals. Two pre-processing approaches are applied on radiographic
images; these techniques are compared to highlight the choice of the
pre-processing method. Furthermore, the values of the fractal
dimension are compared to those of the fractal signature in terms of
the classification of the two populations. In a second analysis, the
BMD measure at proximal femur was compared to the fractal
analysis, the latter, which is a non-invasive technique, allowed a
better discrimination; the results confirm that the fractal analysis of
texture on calcaneus radiographs is able to discriminate osteoporotic
patients with femoral fracture from controls. This discrimination was
efficient compared to that obtained by BMD alone. It was also
present in comparing subgroups with overlapping values of BMD.
Abstract: The purpose of this article is to make an approach to
the Security Studies, exposing their theories and concepts to
understand the role that they have had in the interpretation of the
changes and continuities of the world order and their impact on
policies in facing the problems of the 21st century. The aim is to
build a bridge between the security studies as a subfield and the
meaning that has been given to the world order. The idea of epistemic
communities serves as a methodological proposal for the different
programs of research in security studies, showing their influence in
the realities of States, intergovernmental organizations and
transnational forces, moving to implement, perpetuate and project a
vision of the world order.
Abstract: In this paper, we provided a literature survey on the
artificial stock problem (ASM). The paper began by exploring the
complexity of the stock market and the needs for ASM. ASM
aims to investigate the link between individual behaviors (micro
level) and financial market dynamics (macro level). The variety of
patterns at the macro level is a function of the AFM complexity. The
financial market system is a complex system where the relationship
between the micro and macro level cannot be captured analytically.
Computational approaches, such as simulation, are expected to
comprehend this connection. Agent-based simulation is a simulation
technique commonly used to build AFMs. The paper proceeds by
discussing the components of the ASM. We consider the roles
of behavioral finance (BF) alongside the traditionally risk-averse
assumption in the construction of agent’s attributes. Also, the
influence of social networks in the developing of agents interactions is
addressed. Network topologies such as a small world, distance-based,
and scale-free networks may be utilized to outline economic
collaborations. In addition, the primary methods for developing
agents learning and adaptive abilities have been summarized.
These incorporated approach such as Genetic Algorithm, Genetic
Programming, Artificial neural network and Reinforcement Learning.
In addition, the most common statistical properties (the stylized facts)
of stock that are used for calibration and validation of ASM are
discussed. Besides, we have reviewed the major related previous
studies and categorize the utilized approaches as a part of these
studies. Finally, research directions and potential research questions
are argued. The research directions of ASM may focus on the macro
level by analyzing the market dynamic or on the micro level by
investigating the wealth distributions of the agents.
Abstract: Voting algorithms are extensively used to make
decisions in fault tolerant systems where each redundant module
gives inconsistent outputs. Popular voting algorithms include
majority voting, weighted voting, and inexact majority voters. Each
of these techniques suffers from scenarios where agreements do not
exist for the given voter inputs. This has been successfully overcome
in literature using fuzzy theory. Our previous work concentrated on a
neuro-fuzzy algorithm where training using the neuro system
substantially improved the prediction result of the voting system.
Weight training of Neural Network is sub-optimal. This study
proposes to optimize the weights of the Neural Network using
Artificial Bee Colony algorithm. Experimental results show the
proposed system improves the decision making of the voting
algorithms.
Abstract: Phonocardiography is important in appraisal of
congenital heart disease and pulmonary hypertension as it reflects the
duration of right ventricular systoles. The systolic murmur in patients
with intra-cardiac shunt decreases as pulmonary hypertension
develops and may eventually disappear completely as the pulmonary
pressure reaches systemic level. Phonocardiography and auscultation
are non-invasive, low-cost, and accurate methods to assess heart
disease. In this work an objective signal processing tool to extract
information from phonocardiography signal using Wavelet is
proposed to classify the murmur as normal or abnormal. Since the
feature vector is large, a Binary Particle Swarm Optimization (PSO)
with mutation for feature selection is proposed. The extracted
features improve the classification accuracy and were tested across
various classifiers including Naïve Bayes, kNN, C4.5, and SVM.
Abstract: To tackle the air pollution issues, Plug-in Hybrid
Electric Vehicles (PHEVs) are proposed as an appropriate solution.
Charging a large amount of PHEV batteries, if not controlled, would
have negative impacts on the distribution system. The control process
of charging of these vehicles can be centralized in parking lots that
may provide a chance for better coordination than the individual
charging in houses. In this paper, an optimization-based approach is
proposed to determine the optimum PHEV parking capacities in
candidate nodes of the distribution system. In so doing, a profile for
charging and discharging of PHEVs is developed in order to flatten
the network load profile. Then, this profile is used in solving an
optimization problem to minimize the distribution system losses. The
outputs of the proposed method are the proper place for PHEV
parking lots and optimum capacity for each parking. The application
of the proposed method on the IEEE-34 node test feeder verifies the
effectiveness of the method.
Abstract: Application of biochar to arable soils represents a new
approach to restore soil health and quality. Many studies reported the
positive effect of biochar application on soil fertility and
development of soil microbial community. Moreover biochar may
affect the soil water retention, but this effect has not been sufficiently
described yet. Therefore this study deals with the influence of
biochar application on: microbial activities in soil, availability of
mineral nitrogen in soil for microorganisms, mineral nitrogen
retention and plant production. To demonstrate the effect of biochar
addition on the above parameters, the pot experiment was realized.
As a model crop, Lactuca sativa L. was used and cultivated from
December 10th 2014 till March 22th 2015 in climate chamber in
thoroughly homogenized arable soil with and without addition of
biochar. Five variants of experiment (V1 – V5) with different regime
of irrigation were prepared. Variants V1 – V2 were fertilized by
mineral nitrogen, V3 – V4 by biochar and V5 was a control. The
significant differences were found only in plant production and
mineral nitrogen retention. The highest content of mineral nitrogen
in soil was detected in V1 and V2, about 250 % in comparison with
the other variants. The positive effect of biochar application on soil
fertility, mineral nitrogen availability was not found. On the other
hand results of plant production indicate the possible positive effect
of biochar application on soil water retention.