Abstract: The current research paper assesses how the narrative of Chilean businesspeople about China shapes a new Orientalism Analyses on the role of non-state actors in foreign policy that have hitherto theorized about Orientalism as a narrative of hegemonic power. Hence, it has been instrumental to the efforts of imperialist powers to justify their mission civilisatrice. However, such conceptualization can seldom explain new complexities of international interactions at the height of globalization. Hence, we assessed the case of Chile, a small Latin American country, and its relationship with China, its largest trading partner. Through a discourse analysis of interviews with Chilean businesspeople engaged in the Chinese market, we could determine that Chile is building an Orientalist image of China. This new business Orientalism reinforces a relation of alterity based on commercial opportunities, traditional values, and natural dispositions. Hence, the perception of the Chinese Other amongst Chilean business people frames a new set of representations as part of the essentially commercial nature of current bilateral relations. It differs from previous frames, such as the racial bias frame of the early 20th century, or the anti-communist frame in reaction to Mao’s leadership. As in every narrative of alterity, there is not only a construction of the Other but also a definition of the Self. Consequently, this analysis constitutes a relevant case of the role of non-state actors in asymmetrical bilateral relations, where the non-state actors of the minor power build and act upon an Orientalist frame, which is not representative of its national status in the relation. This study emerges as a contribution on the relation amongst non-state actors in asymmetrical relations, where the smaller power’s business class acts on a negative prejudice of its interactions with its counterpart. The research builds upon the constructivist approach to international relations, linking the idea of Nation Branding with Orientalism in the case of Chile-China relations.
Abstract: Coastal regions are the one of the most commonly used places by the natural balance and the growing population. In coastal engineering, the most valuable data is wave behaviors. The amount of this data becomes very big because of observations that take place for periods of hours, days and months. In this study, some statistical methods such as the wave spectrum analysis methods and the standard statistical methods have been used. The goal of this study is the discovery profiles of the different coast areas by using these statistical methods, and thus, obtaining an instance based data set from the big data to analysis by using data mining algorithms. In the experimental studies, the six sample data sets about the wave behaviors obtained by 20 minutes of observations from Mersin Bay in Turkey and converted to an instance based form, while different clustering techniques in data mining algorithms were used to discover similar coastal places. Moreover, this study discusses that this summarization approach can be used in other branches collecting big data such as medicine.
Abstract: The paper presents the results of a detailed assessment of several modern Reynolds Averaged Navier-Stokes (RANS) turbulence models for prediction of C3X vane film cooling at various injection regimes. Three models are considered, namely the Shear Stress Transport (SST) model, the modification of the SST model accounting for the streamlines curvature (SST-CC), and the Explicit Algebraic Reynolds Stress Model (EARSM). It is shown that all the considered models face with a problem in prediction of the adiabatic effectiveness in the vicinity of the cooling holes; however, accounting for the Reynolds stress anisotropy within the EARSM model noticeably increases the solution accuracy. On the other hand, further downstream all the models provide a reasonable agreement with the experimental data for the adiabatic effectiveness and among the considered models the most accurate results are obtained with the use EARMS.
Abstract: Cloud Computing is a convenient model for on-demand networks that uses shared pools of virtual configurable computing resources, such as servers, networks, storage devices, applications, etc. The cloud serves as an environment for companies and organizations to use infrastructure resources without making any purchases and they can access such resources wherever and whenever they need. Cloud computing is useful to overcome a number of problems in various Information Technology (IT) domains such as Geographical Information Systems (GIS), Scientific Research, e-Governance Systems, Decision Support Systems, ERP, Web Application Development, Mobile Technology, etc. Companies can use Cloud Computing services to store large amounts of data that can be accessed from anywhere on Earth and also at any time. Such services are rented by the client companies where the actual rent depends upon the amount of data stored on the cloud and also the amount of processing power used in a given time period. The resources offered by the cloud service companies are flexible in the sense that the user companies can increase or decrease their storage requirements or the processing power requirements at any time, thus minimizing the overall rental cost of the service they receive. In addition, the Cloud Computing service providers offer fast processors and applications software that can be shared by their clients. This is especially important for small companies with limited budgets which cannot afford to purchase their own expensive hardware and software. This paper is an overview of the Cloud Computing, giving its types, principles, advantages, and disadvantages. In addition, the paper gives some example engineering applications of Cloud Computing and makes suggestions for possible future applications in the field of engineering.
Abstract: Several computationally challenging issues are
encountered while classifying complex natural scenes. In this
paper, we address the problems that are encountered in rotation
invariance with multi-intensity analysis for multi-scene overlapping.
In the present literature, various algorithms proposed techniques
for multi-intensity analysis, but there are several restrictions in
these algorithms while deploying them in multi-scene overlapping
classifications. In order to resolve the problem of multi-scenery
overlapping classifications, we present a framework that is based
on macro and micro basis functions. This algorithm conquers the
minimum classification false alarm while pigeonholing multi-scene
overlapping. Furthermore, a quadrangle multi-intensity decay is
invoked. Several parameters are utilized to analyze invariance
for multi-scenery classifications such as rotation, classification,
correlation, contrast, homogeneity, and energy. Benchmark datasets
were collected for complex natural scenes and experimented for
the framework. The results depict that the framework achieves
a significant improvement on gray-level matrix of co-occurrence
features for overlapping in diverse degree of orientations while
pigeonholing multi-scene overlapping.
Abstract: The increase of capital mobility across emerging economies has become an interesting topic for many economic policy makers. The current study tests the validity of Feldstein–Horioka puzzle for 5 BRICS countries. The sample period of the study runs from 2001 to 2014. The study uses the following parameter estimates well known as the Fully Modified OLS (FMOLS), and Dynamic OLS (DOLS). The results of the study show that investment and savings are cointegrated in the long run. The parameters estimated using FMOLS and DOLS are 0.85 and 0.74, respectively. These results imply that policy makers within BRICS countries have to consider flexible monetary and fiscal policy instruments to influence the mobility of capital with the bloc.
Abstract: With the increase in popularity of mobile devices,
new and varied forms of malware have emerged. Consequently,
the organizations for cyberdefense have echoed the need to deploy
more effective defensive schemes adapted to the challenges posed
by these recent monitoring environments. In order to contribute to
their development, this paper presents a malware detection strategy
for mobile devices based on sequence alignment algorithms. Unlike
the previous proposals, only the system calls performed during the
startup of applications are studied. In this way, it is possible to
efficiently study in depth, the sequences of system calls executed
by the applications just downloaded from app stores, and initialize
them in a secure and isolated environment. As demonstrated in the
performed experimentation, most of the analyzed malicious activities
were successfully identified in their boot processes.
Abstract: The benchmarking of tools for dynamic analysis of
vulnerabilities in web applications is something that is done
periodically, because these tools from time to time update their
knowledge base and search algorithms, in order to improve their
accuracy. Unfortunately, the vast majority of these evaluations are
made by software enthusiasts who publish their results on blogs
or on non-academic websites and always with the same evaluation
methodology. Similarly, academics who have carried out this type of
analysis from a scientific approach, the majority, make their analysis
within the same methodology as well the empirical authors. This
paper is based on the interest of finding answers to questions that
many users of this type of tools have been asking over the years,
such as, to know if the tool truly test and evaluate every vulnerability
that it ensures do, or if the tool, really, deliver a real report of all the
vulnerabilities tested and exploited. This kind of questions have also
motivated previous work but without real answers. The aim of this
paper is to show results that truly answer, at least on the tested tools,
all those unanswered questions. All the results have been obtained
by changing the common model of benchmarking used for all those
previous works.
Abstract: An increasing number of mobile devices with integrated
cameras has meant that most digital video comes from these devices.
These digital videos can be made anytime, anywhere and for different
purposes. They can also be shared on the Internet in a short period
of time and may sometimes contain recordings of illegal acts. The
need to reliably trace the origin becomes evident when these videos
are used for forensic purposes. This work proposes an algorithm
to identify the brand and model of mobile device which generated
the video. Its procedure is as follows: after obtaining the relevant
video information, a classification algorithm based on sensor noise
and Wavelet Transform performs the aforementioned identification
process. We also present experimental results that support the validity
of the techniques used and show promising results.
Abstract: Housings in developing countries have often inadequate
seismic protection, particularly for masonry. People choose this type
of structure since the cost and application are relatively cheap.
Seismic protection of masonry remains an interesting issue among
researchers. In this study, we develop a low-cost seismic isolation
system for masonry using fiber reinforced elastomeric isolators. The
elastomer proposed consists of few layers of rubber pads and fiber
lamina, making it lower in cost comparing to the conventional
isolators. We present a finite element (FE) analysis to predict the
behavior of the low cost rubber isolators undergoing moderate
deformations. The FE model of the elastomer involves a hyperelastic
material property for the rubber pad. We adopt a Yeoh hyperelasticity
model and estimate its coefficients through the available experimental
data. Having the shear behavior of the elastomers, we apply that
isolation system onto small masonry housing. To attach the isolators
on the building, we model the shear behavior of the isolation system
by means of a damped nonlinear spring model. By this attempt, the
FE analysis becomes computationally inexpensive. Several ground
motion data are applied to observe its sensitivity. Roof acceleration
and tensile damage of walls become the parameters to evaluate
the performance of the isolators. In this study, a concrete damage
plasticity model is used to model masonry in the nonlinear range.
This tool is available in the standard package of Abaqus FE software.
Finally, the results show that the low-cost isolators proposed are
capable of reducing roof acceleration and damage level of masonry
housing. Through this study, we are also capable of monitoring the
shear deformation of isolators during seismic motion. It is useful to
determine whether the isolator is applicable. According to the results,
the deformations of isolators on the benchmark one story building are
relatively small.
Abstract: Fabric as the first and most common layer that is in permanent contact with human skin is a very good interface to provide coverage, as well as heat and cold insulation. Phase change materials (PCMs) are organic and inorganic compounds which have the capability of absorbing and releasing noticeable amounts of latent heat during phase transitions between solid and liquid phases at a low temperature range. PCMs come across phase changes (liquid-solid and solid-liquid transitions) during absorbing and releasing thermal heat; so, in order to use them for a long time, they should have been encapsulated in polymeric shells, so-called microcapsules. Microencapsulation and nanoencapsulation methods have been developed in order to reduce the reactivity of a PCM with outside environment, promoting the ease of handling, decreasing the diffusion and evaporation rates. Methods of incorporation of PCMs in textiles such as electrospinning and determining thermal properties had been summarized. Paraffin waxes catch a lot of attention due to their high thermal storage density, repeatability of phase change, thermal stability, small volume change during phase transition, chemical stability, non-toxicity, non-flammability, non-corrosive and low cost and they seem to play a key role in confronting with climate change and global warming. In this article, we aimed to review the researches concentrating on the characteristics of PCMs and new materials and methods of microencapsulation.
Abstract: Social work education is competency based in nature. There is an expectation that graduates of social work programs throughout the world are to be prepared to practice at a level of competence, which is beneficial to both the well-being of individuals and community. Experiential learning is one way to prepare students for competent practice. The use of Problem-Based Learning (PBL) is a form experiential education that has been successful in a number of disciplines to bridge the gap between the theoretical concepts in the classroom to the real world. PBL aligns with the constructivist theoretical approach to learning, which emphasizes the integration of new knowledge with the beliefs students already hold. In addition, the basic tenants of PBL correspond well with the practice behaviors associated with social work practice including multi-disciplinary collaboration and critical thinking. This paper makes an argument for utilizing PBL in social work education.
Abstract: A simple design of array antenna is presented in this paper, supporting millimeter wave applications which can be used in short range wireless communications such as 5G applications. This design enhances the use of V-band, according to IEEE standards, as the antenna works in the 70 GHz band with bandwidth more than 11 GHz and peak gain more than 13 dBi. The design is simulated using different numerical techniques achieving a very good agreement.
Abstract: The preservation of historical Italian heritage, at the urban and architectural scale, has to consider restrictions and requirements connected with conservation issues and usability needs, which are often at odds with historical heritage preservation. Recent decades have been marked by the search for increased accessibility not only of public and private buildings, but to the whole historical city, also for people with disability. Moreover, in the last years the concepts of Smart City and Healthy City seek to improve accessibility both in terms of mobility (independent or assisted) and fruition of goods and services, also for historical cities. The principles of Inclusive Design have introduced new criteria for the improvement of public urban space, between current regulations and best practices. Moreover, they have contributed to transforming “special needs” into an opportunity of social innovation. These considerations find a field of research and analysis in the historical city of Venice, which is at the same time a site of UNESCO world heritage, a mass tourism destination bringing in visitors from all over the world and a city inhabited by an aging population. Due to its conformation, Venetian urban fabric is only partially accessible: about four thousand bridges divide thousands of islands, making it almost impossible to move independently. These urban characteristics and difficulties were the base, in the last 20 years, for several researches, experimentations and solutions with the aim of eliminating architectural barriers, in particular for the usability of bridges. The Venetian Municipality with the EBA Office and some external consultants realized several devices (e.g. the “stepped ramp” and the new accessible ramps for the Venice Marathon) that should determine an innovation for the city, passing from the use of mechanical replicable devices to specific architectural projects in order to guarantee autonomy in use. This paper intends to present the state-of-the-art in bridges accessibility, through an analysis based on Inclusive Design principles and on the current national and regional regulation. The purpose is to evaluate some possible strategies that could improve performances, between limits and possibilities of interventions. The aim of the research is to lay the foundations for the development of a strategic program for the City of Venice that could successfully bring together both conservation and improvement requirements.
Abstract: Air pollution and climate warming become more and more intensified in many areas, especially in urban areas. Environmental parameters are critical information to air pollution and weather monitoring. Thus, it is necessary to develop a suitable air pollution and weather monitoring system for urban areas. In this study, a vehicle monitoring system (VMS) based on the IoT technique is developed. Cars are selected as the research tool because it can reach a greater number of streets to collect data. The VMS can monitor different environmental parameters, including ambient temperature and humidity, and air quality parameters, including PM2.5, NO2, CO, and O3. The VMS can provide other information, including GPS signals and the vibration information through driving a car on the street. Different sensor modules are used to measure the parameters and collect the measured data and transmit them to a cloud server through the LoRa protocol. A user interface is used to show the sensing data storing at the cloud server. To examine the performance of the system, a researcher drove a Nissan x-trail 1998 to the area close to the Da’an District office in Taipei to collect monitoring data. The collected data are instantly shown on the user interface. The four kinds of information are provided by the interface: GPS positions, weather parameters, vehicle information, and air quality information. With the VMS, users can obtain the information regarding air quality and weather conditions when they drive their car to an urban area. Also, government agencies can make decisions on traffic planning based on the information provided by the proposed VMS.
Abstract: Power failure resulting from tower collapse due to violent seismic events might bring enormous and inestimable losses. The Chi-Chi earthquake, for example, strongly struck Taiwan and caused huge damage to the power system on September 21, 1999. Nearly 10% of extra high voltage (EHV) transmission towers were damaged in the earthquake. Therefore, seismic hazards of EHV transmission towers should be monitored and evaluated. The ultimate goal of this study is to establish a damage level assessment model for EHV transmission towers. The data of earthquakes provided by Taiwan Central Weather Bureau serve as a reference and then lay the foundation for earthquake simulations and analyses afterward. Some parameters related to the damage level of each point of an EHV tower are simulated and analyzed by the data from monitoring stations once an earthquake occurs. Through the Fourier transform, the seismic wave is then analyzed and transformed into different wave frequencies, and the data would be shown through a response spectrum. With this method, the seismic frequency which damages EHV towers the most is clearly identified. An estimation model is built to determine the damage level caused by a future seismic event. Finally, instead of relying on visual observation done by inspectors, the proposed model can provide a power company with the damage information of a transmission tower. Using the model, manpower required by visual observation can be reduced, and the accuracy of the damage level estimation can be substantially improved. Such a model is greatly useful for health and construction monitoring because of the advantages of long-term evaluation of structural characteristics and long-term damage detection.
Abstract: In this paper, we present a vocal ontology of
OpenStreetMap data for the apprehension of space by visually
impaired people. Indeed, the platform based on produsage gives a
freedom to data producers to choose the descriptors of geocoded
locations. Unfortunately, this freedom, called also folksonomy leads
to complicate subsequent searches of data. We try to solve this issue
in a simple but usable method to extract data from OSM databases in
order to send them to visually impaired people using Text To Speech
technology. We focus on how to help people suffering from visual
disability to plan their itinerary, to comprehend a map by querying
computer and getting information about surrounding environment in
a mono-modal human-computer dialogue.
Abstract: Redundancy requirements for UAV (Unmanned Aerial
Vehicle) are hardly faced due to the generally restricted amount
of available space and allowable weight for the aircraft systems,
limiting their exploitation. Essential equipment as the Air Data,
Attitude and Heading Reference Systems (ADAHRS) require several
external probes to measure significant data as the Angle of Attack
or the Sideslip Angle. Previous research focused on the analysis
of a patented technology named Smart-ADAHRS (Smart Air Data,
Attitude and Heading Reference System) as an alternative method to
obtain reliable and accurate estimates of the aerodynamic angles.
This solution is based on an innovative sensor fusion algorithm
implementing soft computing techniques and it allows to obtain a
simplified inertial and air data system reducing external devices.
In fact, only one external source of dynamic and static pressures
is needed. This paper focuses on the benefits which would be
gained by the implementation of this system in UAV applications.
A simplification of the entire ADAHRS architecture will bring to
reduce the overall cost together with improved safety performance.
Smart-ADAHRS has currently reached Technology Readiness Level
(TRL) 6. Real flight tests took place on ultralight aircraft equipped
with a suitable Flight Test Instrumentation (FTI). The output of
the algorithm using the flight test measurements demonstrates the
capability for this fusion algorithm to embed in a single device
multiple physical and virtual sensors. Any source of dynamic and
static pressure can be integrated with this system gaining a significant
improvement in terms of versatility.
Abstract: Fully autonomous small Unmanned Aerial Vehicles
(UAVs) are increasingly being used in many commercial applications.
Although a lot of research has been done to develop safe, reliable
and durable UAVs, accidents due to electronic and structural failures
are not uncommon and pose a huge safety risk to the UAV operators
and the public. Hence there is a strong need for an automated health
monitoring system for UAVs with a view to minimizing mission
failures thereby increasing safety. This paper describes our approach
to monitoring the electronic and structural components in a small
UAV without the need for additional sensors to do the monitoring.
Our system monitors data from four sources; sensors, navigation
algorithms, control inputs from the operator and flight controller
outputs. It then does statistical analysis on the data and applies
a rule based engine to detect failures. This information can then
be fed back into the UAV and a decision to continue or abort the
mission can be taken automatically by the UAV and independent of
the operator. Our system has been verified using data obtained from
real flights over the past year from UAVs of various sizes that have
been designed and deployed by us for various applications.
Abstract: The present paper investigates the effect of linear
thermal gradient on the steady-state creep behavior of rotating
isotropic disc using threshold stress based Sherby’s creep law.
The composite discs made of aluminum matrix reinforced with
silicon carbide particulate has been taken for analysis. The stress
and strain rate distributions have been calculated for discs rotating
at linear thermal gradation using von Mises’ yield criterion. The
material parameters have been estimated by regression fit of the
available experimental data. The results are displayed and compared
graphically in designer friendly format for the above said temperature
profile with the disc operating under uniform temperature profile. It is
observed that radial and tangential stresses show minor variation and
the strain rates vary significantly in the presence of thermal gradation
as compared to disc having uniform temperature.