Abstract: The research aimed to study the satisfaction of Suan Sunandha Rajabhat University students towards the university radio station which broadcasts in both analog on FM 97.25 MHz and online via the university website. The sample used in this study consists of undergraduate students year 1 to year 4 from 6 faculties i.e. Faculty of Education, Faculty of Humanities and Social Sciences, Faculty of Management Science and Faculty of Industrial Technology, and Faculty of Fine and Applied Arts totaling 200 students. The tools used for data collection is survey. Data analysis applied statistics that are percentage, mean and standard deviation. The results showed that Suan Sunandha Rajabhat University students were satisfied to the place of listening service, followed by channels of broadcasting that cover both analog signals on 97.25 MHz FM and online via the Internet. However, the satisfaction level of the content offered was very low. Most of the students want the station to improve the content. Entertainment content was requested the most, followed by sports content. The lowest satisfaction level is with the broadcasting quality through analog signal. Most students asked the station to improve on the issue. However, overall, Suan Sunandha Rajabhat University students were satisfied with the university radio station broadcasted online via the university website.
Abstract: At present, vibrations of rotors of gas transmittal unit evade sustainable forecasting. This paper describes elastic oscillation modes in resilient supports and rotor impellers modeled during computational experiments with regard to interference in the system of gas-dynamic flow and compressor rotor. Verification of aeroelastic approach was done on model problem of interaction between supersonic jet in shock tube with deformed plate. ANSYS 15.0 engineering analysis system was used as a modeling tool of numerical simulation in this paper. Finite volume method for gas dynamics and finite elements method for assessment of the strain stress state (SSS) components were used as research methods. Rotation speed and material’s elasticity modulus varied during calculations, and SSS components and gas-dynamic parameters in the dynamic system of gas-dynamic flow and compressor rotor were evaluated. The analysis of time dependence demonstrated that gas-dynamic parameters near the rotor blades oscillate at 200 Hz, and SSS parameters at the upper blade edge oscillate four times higher, i.e. with blade frequency. It has been detected that vibration amplitudes correction in the test points at magnetic bearings by aeroelasticity may correspond up to 50%, and about -π/4 for phases.
Abstract: This study aims to explore and compare the current
condition of community radio stations in Phutthamonthon district,
Nakhon Pathom province, Thailand, as well as the challenges they
are facing. Qualitative research tools including in-depth interviews;
documentary analysis; focus group interviews; and observation, are
used to examine the content, programming, and management
structure of three community radio stations currently in operation
within the district. Research findings indicate that the management
and operational approaches adopted by the two non-profit stations
included in the study, Salaya Pattana and Voice of Dhamma, are
more structured and effective than that of the for-profit Tune Radio.
Salaya Pattana – backed by the Faculty of Engineering, Mahidol
University, and the charity-funded Voice of Dhamma, are
comparatively free from political and commercial influence, and able
to provide more relevant and consistent community-oriented content
to meet the real demand of the audience. Tune Radio, on the other
hand, has to rely solely on financial support from political factions
and business groups, which heavily influence its content.
Abstract: Fuzzy regression models are useful for investigating
the relationship between explanatory variables and responses in fuzzy
environments. To overcome the deficiencies of previous models and
increase the explanatory power of fuzzy data, the graded mean
integration (GMI) representation is applied to determine
representative crisp regression coefficients. A fuzzy regression model
is constructed based on the modified dissemblance index (MDI),
which can precisely measure the actual total error. Compared with
previous studies based on the proposed MDI and distance criterion, the
results from commonly used test examples show that the proposed
fuzzy linear regression model has higher explanatory power and
forecasting accuracy.
Abstract: Forecasting electricity load plays a crucial role regards
decision making and planning for economical purposes. Besides, in
the light of the recent privatization and deregulation of the power
industry, the forecasting of future electricity load turned out to be a
very challenging problem. Empirical data about electricity load
highlights a clear seasonal behavior (higher load during the winter
season), which is partly due to climatic effects. We also emphasize
the presence of load periodicity at a weekly basis (electricity load is
usually lower on weekends or holidays) and at daily basis (electricity
load is clearly influenced by the hour). Finally, a long-term trend may
depend on the general economic situation (for example, industrial
production affects electricity load). All these features must be
captured by the model.
The purpose of this paper is then to build an hourly electricity load
model. The deterministic component of the model requires non-linear
regression and Fourier series while we will investigate the stochastic
component through econometrical tools.
The calibration of the parameters’ model will be performed by
using data coming from the Italian market in a 6 year period (2007-
2012). Then, we will perform a Monte Carlo simulation in order to
compare the simulated data respect to the real data (both in-sample
and out-of-sample inspection). The reliability of the model will be
deduced thanks to standard tests which highlight a good fitting of the
simulated values.
Abstract: Worldwide Interoperability for Microwave Access, is a broadband technology, which can effectively transmit a data across a group of users using Multicast and Broadcast Service. WiMAX belongs to a family of (IEEE 802.16) standards and is evolving as a fourth generation technology. WiMAX is the next generation technology that offers wireless access over long distances. MBS zone, which is a group of base stations that are broadcasting the same multicast packets which defines Multicast and Broadcast services. Handover is a process of transferring an ongoing call or data session from one channel connected to the core network to another channel. The handover causes authentication, delay, packet loss, jitter that mainly affects the communication. In this paper, we present a survey on handover security issues in WiMAX.
Abstract: The objective of this research is to forecast the monthly exchange rate between Thai baht and the US dollar and to compare two forecasting methods. The methods are Box-Jenkins’ method and Holt’s method. Results show that the Box-Jenkins’ method is the most suitable method for the monthly Exchange Rate between Thai Baht and the US Dollar. The suitable forecasting model is ARIMA (1,1,0) without constant and the forecasting equation is Yt = Yt-1 + 0.3691 (Yt-1 - Yt-2) When Yt is the time series data at time t, respectively.
Abstract: This study attempts to consider the linkage between management and computer sciences in order to develop the software named “IntelSymb” as a demo application to prove data analysis of non-energy* fields’ diversification, which will positively influence on energy dependency mitigation of countries. Afterward, we analyzed 18 years of economic fields of development (5 sectors) of 13 countries by identifying which patterns mostly prevailed and which can be dominant in the near future. To make our analysis solid and plausible, as a future work, we suggest developing a gateway or interface, which will be connected to all available on-line data bases (WB, UN, OECD, U.S. EIA) for countries’ analysis by fields. Sample data consists of energy (TPES and energy import indicators) and non-energy industries’ (Main Science and Technology Indicator, Internet user index, and Sales and Production indicators) statistics from 13 OECD countries over 18 years (1995-2012). Our results show that the diversification of non-energy industries can have a positive effect on energy sector dependency (energy consumption and import dependence on crude oil) deceleration. These results can provide empirical and practical support for energy and non-energy industries diversification’ policies, such as the promoting of Information and Communication Technologies (ICTs), services and innovative technologies efficiency and management, in other OECD and non-OECD member states with similar energy utilization patterns and policies. Industries, including the ICT sector, generate around 4 percent of total GHG, but this is much higher — around 14 percent — if indirect energy use is included. The ICT sector itself (excluding the broadcasting sector) contributes approximately 2 percent of global GHG emissions, at just under 1 gigatonne of carbon dioxide equivalent (GtCO2eq). Ergo, this can be a good example and lesson for countries which are dependent and independent on energy, and mainly emerging oil-based economies, as well as to motivate non-energy industries diversification in order to be ready to energy crisis and to be able to face any economic crisis as well.
Abstract: Promotion of the Fiber Reinforced Concrete (FRC) as a construction material for civil engineering projects has invoked numerous researchers to investigate their mechanical behavior. Even though there is satisfactory information about the effects of fiber type and length, concrete mixture, casting type and other variables on the strength and deformability parameters of FRC, the numerical modeling of such materials still needs research attention. The focus of this study is to investigate the feasibility of Concrete Damaged Plasticity (CDP) model in prediction of Macro-synthetic FRC structures behavior. CDP model requires the tensile behavior of concrete to be well characterized. For this purpose, a series of uniaxial direct tension and four point bending tests were conducted on the notched specimens to define bilinear tension softening (post-peak tension stress-strain) behavior. With these parameters obtained, the flexural behavior of macro-synthetic FRC beams were modeled and the results showed a good agreement with the experimental measurements.
Abstract: Centrifugal-casting machine is used in manufacturing
special machine components like multi-layer journal bearing used in
all internal combustion engine, steam, gas turbine and air craft turboengine
where isotropic properties and high precisions are desired.
Moreover, this machine can be used in manufacturing thin wall hightech
machine components like cylinder liners and piston rings of IC
engine and other machine parts like sleeves, and bushes. Heavy-duty
machine component like railway wheel can also be prepared by
centrifugal casting. A lot of technological developments are required
in casting process for production of good casted machine body and
machine parts. Usually defects like blowholes, surface roughness,
chilled surface etc. are found in sand casted machine parts. But these
can be removed by centrifugal casting machine using rotating
metallic die. Moreover, die rotation, its temperature control, and good
pouring practice can contribute to the quality of casting because of
the fact that the soundness of a casting in large part depends upon
how the metal enters into the mold or dies and solidifies. Poor
pouring practice leads to variety of casting defects such as
temperature loss, low quality casting, excessive turbulence, over
pouring etc. Besides these, handling of molten metal is very
unsecured and dangerous for the workers. In order to get rid of all
these problems, the need of an automatic pouring device arises. In
this research work, a robot assisted pouring device and a centrifugal
casting machine are designed, developed constructed and tested
experimentally which are found to work satisfactorily. The robot
assisted pouring device is further modified and developed for using it
in actual metal casting process. Lot of settings and tests are required
to control the system and ultimately it can be used in automation of
centrifugal casting machine to produce high-tech machine parts with
desired precision.
Abstract: This paper proposes a method of learning topics for
broadcasting contents. There are two kinds of texts related to
broadcasting contents. One is a broadcasting script, which is a series of
texts including directions and dialogues. The other is blogposts, which
possesses relatively abstracted contents, stories, and diverse
information of broadcasting contents. Although two texts range over
similar broadcasting contents, words in blogposts and broadcasting
script are different. When unseen words appear, it needs a method to
reflect to existing topic. In this paper, we introduce a semantic
vocabulary expansion method to reflect unseen words. We expand
topics of the broadcasting script by incorporating the words in
blogposts. Each word in blogposts is added to the most semantically
correlated topics. We use word2vec to get the semantic correlation
between words in blogposts and topics of scripts. The vocabularies of
topics are updated and then posterior inference is performed to
rearrange the topics. In experiments, we verified that the proposed
method can discover more salient topics for broadcasting contents.
Abstract: In this current contribution, authors are dedicated to
investigate influence of the crystal lamellae orientation on
electromechanical behaviors of relaxor ferroelectric Poly
(vinylidene fluoride –trifluoroethylene -chlorotrifluoroethylene)
(P(VDF-TrFE-CTFE)) films by control of polymer microstructure,
aiming to picture the full map of structure-property relationship. In
order to define their crystal orientation films, terpolymer films were
fabricated by solution-casting, stretching and hot-pressing process.
Differential scanning calorimetry, impedance analyzer, and tensile
strength techniques were employed to characterize crystallographic
parameters, dielectric permittivity, and elastic Young’s modulus
respectively. In addition, large electrical induced out-of-plane
electrostrictive strain was obtained by cantilever beam mode.
Consequently, as-casted pristine films exhibited surprisingly high
electrostrictive strain 0.1774% due to considerably small value of
elastic Young’s modulus although relatively low dielectric
permittivity. Such reasons contributed to large mechanical elastic
energy density. Instead, due to 2 folds increase of elastic Young’s
modulus and less than 50% augmentation of dielectric constant, fullycrystallized
film showed weak electrostrictive behavior and
mechanical energy density as well. And subjected to mechanical
stretching process, Film C exhibited stronger dielectric constant and
out-performed electrostrictive strain over Film B because edge-on
crystal lamellae orientation induced by uniaxially mechanical stretch.
Hot-press films were compared in term of cooling rate. Rather large
electrostrictive strain of 0.2788% for hot-pressed Film D in
quenching process was observed although its dielectric permittivity
equivalent to that of pristine as-casted Film A, showing highest
mechanical elastic energy density value of 359.5 J/m3. In hot-press
cooling process, dielectric permittivity of Film E saw values at 48.8
concomitant with ca.100% increase of Young’s modulus. Films with
intermediate mechanical energy density were obtained.
Abstract: Scripts are one of the basic text resources to understand
broadcasting contents. Topic modeling is the method to get the
summary of the broadcasting contents from its scripts. Generally,
scripts represent contents descriptively with directions and speeches,
and provide scene segments that can be seen as semantic units.
Therefore, a script can be topic modeled by treating a scene segment
as a document. Because scene segments consist of speeches mainly,
however, relatively small co-occurrences among words in the scene
segments are observed. This causes inevitably the bad quality of
topics by statistical learning method. To tackle this problem, we
propose a method to improve topic quality with additional word
co-occurrence information obtained using scene similarities. The
main idea of improving topic quality is that the information that
two or more texts are topically related can be useful to learn high
quality of topics. In addition, more accurate topical representations
lead to get information more accurate whether two texts are related
or not. In this paper, we regard two scene segments are related
if their topical similarity is high enough. We also consider that
words are co-occurred if they are in topically related scene segments
together. By iteratively inferring topics and determining semantically
neighborhood scene segments, we draw a topic space represents
broadcasting contents well. In the experiments, we showed the
proposed method generates a higher quality of topics from Korean
drama scripts than the baselines.
Abstract: This paper focuses on the mathematical modeling for
solidification of Al alloy in a cube mold cavity to study the
solidification behavior of casting process. The parametric
investigation of solidification process inside the cavity was
performed by using computational solidification/melting model
coupled with Volume of fluid (VOF) model. The implicit filling
algorithm is used in this study to understand the overall process from
the filling stage to solidification in a model metal casting process.
The model is validated with past studied at same conditions. The
solidification process is analyzed by including the effect of pouring
velocity as well as natural convection from the wall and geometry of
the cavity. These studies show the possibility of various defects
during solidification process.
Abstract: Opportunistic Routing (OR) increases the
transmission reliability and network throughput. Traditional routing
protocols preselects one or more predetermined nodes before
transmission starts and uses a predetermined neighbor to forward a
packet in each hop. The opportunistic routing overcomes the
drawback of unreliable wireless transmission by broadcasting one
transmission can be overheard by manifold neighbors. The first
cooperation-optimal protocol for Multirate OR (COMO) used to
achieve social efficiency and prevent the selfish behavior of the
nodes. The novel link-correlation-aware OR improves the
performance by exploiting the miscellaneous low correlated forward
links. Context aware Adaptive OR (CAOR) uses active suppression
mechanism to reduce packet duplication. The Context-aware OR
(COR) can provide efficient routing in mobile networks. By using
Cooperative Opportunistic Routing in Mobile Ad hoc Networks
(CORMAN), the problem of opportunistic data transfer can be
tackled. While comparing to all the protocols, COMO is the best as it
achieves social efficiency and prevents the selfish behavior of the
nodes.
Abstract: We regard forecasting of energy consumption by
private production areas of a large industrial facility as well as by the
facility itself. As for production areas, the forecast is made based on
empirical dependencies of the specific energy consumption and the
production output. As for the facility itself, implementation of the
task to minimize the energy consumption forecasting error is based
on adjustment of the facility’s actual energy consumption values
evaluated with the metering device and the total design energy
consumption of separate production areas of the facility. The
suggested procedure of optimal energy consumption was tested based
on the actual data of core product output and energy consumption by
a group of workshops and power plants of the large iron and steel
facility. Test results show that implementation of this procedure gives
the mean accuracy of energy consumption forecasting for winter
2014 of 0.11% for the group of workshops and 0.137% for the power
plants.
Abstract: Wind energy is rapidly emerging as the primary
source of electricity in the Philippines, although developing an
accurate wind resource model is difficult. In this study, Weather
Research and Forecasting (WRF) Model, an open source mesoscale
Numerical Weather Prediction (NWP) model, was used to produce a
1-year atmospheric simulation with 4 km resolution on the Ilocos
Region of the Philippines. The WRF output (netCDF) extracts the
annual mean wind speed data using a Python-based Graphical User
Interface. Lastly, wind resource assessment was produced using a
GIS software. Results of the study showed that it is more flexible to
use Python scripts than using other post-processing tools in dealing
with netCDF files. Using WRF Model, Python, and Geographic
Information Systems, a reliable wind resource map is produced.
Abstract: A method of effective planning and control of
industrial facility energy consumption is offered. The method allows
optimally arranging the management and full control of complex
production facilities in accordance with the criteria of minimal
technical and economic losses at the forecasting control. The method
is based on the optimal construction of the power efficiency
characteristics with the prescribed accuracy. The problem of optimal
designing of the forecasting model is solved on the basis of three
criteria: maximizing the weighted sum of the points of forecasting
with the prescribed accuracy; the solving of the problem by the
standard principles at the incomplete statistic data on the basis of
minimization of the regularized function; minimizing the technical
and economic losses due to the forecasting errors.
Abstract: The education sector is constantly faced with rapid
changes in technologies in terms of ensuring that the curriculum is up
to date and in terms of making sure that students are aware of these
technological changes. This challenge can be seen as the motivation
for this study, which is to examine the factors affecting computing
students’ awareness of the latest Information Technologies (ICTs).
The aim of this study is divided into two sub-objectives which are:
the selection of relevant theories and the design of a conceptual
model to support it as well as the empirical testing of the designed
model. The first objective is achieved by a review of existing
literature on technology adoption theories and models. The second
objective is achieved using a survey of computing students in the four
universities of the KwaZulu-Natal province of South Africa. Data
collected from this survey is analyzed using Statistical package for
the Social Science (SPSS) using descriptive statistics, ANOVA and
Pearson correlations. The main hypothesis of this study is that there is
a relationship between the demographics and the prior conditions of
the computing students and their awareness of general ICT trends and
of Digital Switch Over (DSO) a new technology which involves the
change from analog to digital television broadcasting in order to
achieve improved spectrum efficiency. The prior conditions of the
computing students that were considered in this study are students’
perceived exposure to career guidance and students’ perceived
curriculum currency. The results of this study confirm that gender,
ethnicity, and high school computing course affect students’
perceived curriculum currency while high school location affects
students’ awareness of DSO. The results of this study also confirm
that there is a relationship between students prior conditions and their
awareness of general ICT trends and DSO in particular.
Abstract: Recent investigations have demonstrated the global
sea level rise due to climate change impacts. In this study, climate
changes study the effects of increasing water level in the strait of
Hormuz. The probable changes of sea level rise should be
investigated to employ the adaption strategies. The climatic output
data of a GCM (General Circulation Model) named CGCM3 under
climate change scenario of A1b and A2 were used. Among different
variables simulated by this model, those of maximum correlation
with sea level changes in the study region and least redundancy
among themselves were selected for sea level rise prediction by using
stepwise regression. One of models (Discrete Wavelet artificial
Neural Network) was developed to explore the relationship between
climatic variables and sea level changes. In these models, wavelet
was used to disaggregate the time series of input and output data into
different components and then ANN was used to relate the
disaggregated components of predictors and input parameters to each
other. The results showed in the Shahid Rajae Station for scenario
A1B sea level rise is among 64 to 75 cm and for the A2 Scenario sea
level rise is among 90 t0 105 cm. Furthermore, the result showed a
significant increase of sea level at the study region under climate
change impacts, which should be incorporated in coastal areas
management.