Abstract: Passive systems were born with the purpose of the
greatest exploitation of solar energy in cold climates and high
altitudes. They spread themselves until the 80-s all over the world
without any attention to the specific climate and the summer
behavior; this caused the deactivation of the systems due to a series
of problems connected to the summer overheating, the complex
management and the rising of the dust.
Until today the European regulation limits only the winter
consumptions without any attention to the summer behavior but, the
recent European EN 15251 underlines the relevance of the indoor
comfort, and the necessity of the analytic studies validation by
monitoring case studies.
In the porpose paper we demonstrate that the solar wall is an
efficient system both from thermal comfort and energy saving point
of view and it is the most suitable for our temperate climates because
it can be used as a passive cooling sistem too. In particular the paper
present an experimental and numerical analisys carried out on a case
study with nine different solar passive systems in Ancona, Italy.
We carried out a detailed study of the lodging provided by the
solar wall by the monitoring and the evaluation of the indoor
conditions.
Analyzing the monitored data, on the base of recognized models
of comfort (ISO, ASHRAE, Givoni-s BBCC), is emerged that the
solar wall has an optimal behavior in the middle seasons. In winter
phase this passive system gives more advantages in terms of energy
consumptions than the other systems, because it gives greater heat
gain and therefore smaller consumptions. In summer, when outside
air temperature return in the mean seasonal value, the indoor comfort
is optimal thanks to an efficient transversal ventilation activated from
the same wall.
Abstract: Frequent patterns are patterns such as sets of features or items that appear in data frequently. Finding such frequent patterns has become an important data mining task because it reveals associations, correlations, and many other interesting relationships hidden in a dataset. Most of the proposed frequent pattern mining algorithms have been implemented with imperative programming languages such as C, Cµ, Java. The imperative paradigm is significantly inefficient when itemset is large and the frequent pattern is long. We suggest a high-level declarative style of programming using a functional language. Our supposition is that the problem of frequent pattern discovery can be efficiently and concisely implemented via a functional paradigm since pattern matching is a fundamental feature supported by most functional languages. Our frequent pattern mining implementation using the Haskell language confirms our hypothesis about conciseness of the program. The performance studies on speed and memory usage support our intuition on efficiency of functional language.
Abstract: This work discusses an innovative methodology for
deployment of service quality characteristics. Four groups of organizational features that may influence the quality of services are identified: human resource, technology, planning, and organizational
relationships. A House of Service Quality (HOSQ) matrix is built to
extract the desired improvement in the service quality characteristics
and to translate them into a hierarchy of important organizational
features. The Mean Square Error (MSE) criterion enables the
pinpointing of the few essential service quality characteristics to be
improved as well as selection of the vital organizational features. The
method was implemented in an engineering supply enterprise and
provides useful information on its vital service dimensions.
Abstract: Noise contamination in a magnetic resonance (MR)
image could occur during acquisition, storage, and transmission in
which effective filtering is required to avoid repeating the MR
procedure. In this paper, an iterative asymmetrical triangle fuzzy
filter with moving average center (ATMAVi filter) is used to reduce
different levels of salt and pepper noise in a brain MR image. Besides
visual inspection on filtered images, the mean squared error (MSE) is
used as an objective measurement. When compared with the median
filter, simulation results indicate that the ATMAVi filter is effective
especially for filtering a higher level noise (such as noise density =
0.45) using a smaller window size (such as 3x3) when operated
iteratively or using a larger window size (such as 5x5) when operated
non-iteratively.
Abstract: The purposes of this study are 1) to study the over 20-year attempt of Mahakan fort community to negotiate with Bangkok Metropolitan Administration (BMA) to remain in their residential area belonging to the state, and 2) to apply the new social and cultural dimension between the state and the community as an alternative for local participation in keeping their residential area. This is a qualitative research, and the findings reveal that the community claimed their ancestors’ right as owners of this piece of land for over 200 years. The community, therefore, requested to take part in the preservation of land, culture and local intellect and the area management in terms of being a learning resource on the cultural road in Rattanakosin Island. However, BMA imposed the law concerning the community area relocation in Rattanakosin Island. The result of law enforcement led to the failure of the area relocation, and the hard hit on physical structure of the area including the overall deterioration of the cultural road renovated in the year 1982, the 200 years’ celebration of Bangkok. The enforcement of law by the state required the move of the community, and the landscape improvement based on the capital city plan. However, this enforcement resulted in the unending conflicts between the community and the state, and the solution of this problem was unclear. At the same time the community has spent a long time opposing the state’s action, and preparing themselves by administrating the community behind Mahakan fortress with community administrative committee under the suggestion of external organization by registering all community members, providing funds for community administration. At the meantime the state lacked the continuation of the enforcement due to political problem and BMA’s administration problem. It is, therefore, suggested that an alternative solution to this problem lie at the negotiation between the state and the community with the purpose of the collaboration between the two to develop the area under the protective law of each side.
Abstract: Wireless sensor networks include small nodes which
have sensing ability; calculation and connection extend themselves
everywhere soon. Such networks have source limitation on
connection, calculation and energy consumption. So, since the nodes
have limited energy in sensor networks, the optimized energy
consumption in these networks is of more importance and has created
many challenges. The previous works have shown that by organizing
the network nodes in a number of clusters, the energy consumption
could be reduced considerably. So the lifetime of the network would
be increased. In this paper, we used the Queen-bee algorithm to
create energy efficient clusters in wireless sensor networks. The
Queen-bee (QB) is similar to nature in that the queen-bee plays a
major role in reproduction process. The QB is simulated with J-sim
simulator. The results of the simulation showed that the clustering by
the QB algorithm decreases the energy consumption with regard to
the other existing algorithms and increases the lifetime of the
network.
Abstract: As a matter of the fact that online social networks like
Twitter, Facebook and MySpace have experienced an extensive
growth in recent years. Social media offers individuals with a tool for
communicating and interacting with one another. These social
networks enable people to stay in touch with other people and
express themselves. This process makes the users of online social
networks active creators of content rather than being only consumers
of traditional media. That’s why millions of people show strong
desire to learn the methods and tools of digital content production
and necessary communication skills. However, the booming interest
in communication and interaction through online social networks and
high level of eagerness to invent and implement the ways to
participate in content production raise some privacy and security
concerns.
This presentation aims to open the assumed revolutionary,
democratic and liberating nature of the online social media up for
discussion by reviewing some recent political developments in
Turkey. Firstly, the role of Internet and online social networks in
mobilizing collective movements through social interactions and
communications will be questioned. Secondly, some cases from Gezi
and Okmeydanı Protests and also December 17-25 period will be
presented in order to illustrate misinformation and manipulation in
social media and violation of individual privacy through online social
networks in order to damage social unity and stability contradictory
to democratic nature of online social networking.
Abstract: The customary practice of identifying industrial sickness is a set traditional techniques which rely upon a range of manual monitoring and compilation of financial records. It makes the process tedious, time consuming and often are susceptible to manipulation. Therefore, certain readily available tools are required which can deal with such uncertain situations arising out of industrial sickness. It is more significant for a country like India where the fruits of development are rarely equally distributed. In this paper, we propose an approach based on Artificial Neural Network (ANN) to deal with industrial sickness with specific focus on a few such units taken from a less developed north-east (NE) Indian state like Assam. The proposed system provides decision regarding industrial sickness using eight different parameters which are directly related to the stages of sickness of such units. The mechanism primarily uses certain signals and symptoms of industrial health to decide upon the state of a unit. Specifically, we formulate an ANN based block with data obtained from a few selected units of Assam so that required decisions related to industrial health could be taken. The system thus formulated could become an important part of planning and development. It can also contribute towards computerization of decision support systems related to industrial health and help in better management.
Abstract: This paper introduces a new approach for the performance
analysis of adaptive filter with error saturation nonlinearity in
the presence of impulsive noise. The performance analysis of adaptive
filters includes both transient analysis which shows that how fast
a filter learns and the steady-state analysis gives how well a filter
learns. The recursive expressions for mean-square deviation(MSD)
and excess mean-square error(EMSE) are derived based on weighted
energy conservation arguments which provide the transient behavior
of the adaptive algorithm. The steady-state analysis for co-related
input regressor data is analyzed, so this approach leads to a new
performance results without restricting the input regression data to
be white.
Abstract: In this paper we compare the response of linear and
nonlinear neural network-based prediction schemes in prediction of
received Signal-to-Interference Power Ratio (SIR) in Direct
Sequence Code Division Multiple Access (DS/CDMA) systems. The
nonlinear predictor is Multilayer Perceptron MLP and the linear
predictor is an Adaptive Linear (Adaline) predictor. We solve the
problem of complexity by using the Minimum Mean Squared Error
(MMSE) principle to select the optimal predictors. The optimized
Adaline predictor is compared to optimized MLP by employing
noisy Rayleigh fading signals with 1.8 GHZ carrier frequency in an
urban environment. The results show that the Adaline predictor can
estimates SIR with the same error as MLP when the user has the
velocity of 5 km/h and 60 km/h but by increasing the velocity up-to
120 km/h the mean squared error of MLP is two times more than
Adaline predictor. This makes the Adaline predictor (with lower
complexity) more suitable than MLP for closed-loop power control
where efficient and accurate identification of the time-varying
inverse dynamics of the multi path fading channel is required.
Abstract: The aim of this paper is description of the notion of
the death for prisoners and the ways of deal with. They express
indifference, coldness, inability to accept the blame, they have no
shame and no empathy. Is it enough to perform acts verging on the
death. In this paper we described mechanisms and regularities of selfdestructive
behaviour in the view of the relevant literature? The
explanation of the phenomenon is of a biological and sociopsychological
nature. It must be clearly stated that all forms of selfdestructive
behaviour result from various impulses, conflicts and
deficits. That is why they should be treated differently in terms of
motivation and functions which they perform in a given group of
people. Behind self-destruction there seems to be a motivational
mechanism which forces prisoners to rebel and fight against the hated
law and penitentiary systems. The imprisoned believe that pain and
suffering inflicted on them by themselves are better than passive
acceptance of repression. The variety of self-destruction acts is wide,
and some of them take strange forms. We assume that a life-death
barrier is a kind of game for them. If they cannot change the
degrading situation, their life loses sense.
Abstract: The more recent satellite projects/programs makes
extensive usage of real – time embedded systems. 16 bit processors
which meet the Mil-Std-1750 standard architecture have been used in
on-board systems. Most of the Space Applications have been written
in ADA. From a futuristic point of view, 32 bit/ 64 bit processors are
needed in the area of spacecraft computing and therefore an effort is
desirable in the study and survey of 64 bit architectures for space
applications. This will also result in significant technology
development in terms of VLSI and software tools for ADA (as the
legacy code is in ADA).
There are several basic requirements for a special processor for
this purpose. They include Radiation Hardened (RadHard) devices,
very low power dissipation, compatibility with existing operational
systems, scalable architectures for higher computational needs,
reliability, higher memory and I/O bandwidth, predictability, realtime
operating system and manufacturability of such processors.
Further on, these may include selection of FPGA devices, selection
of EDA tool chains, design flow, partitioning of the design, pin
count, performance evaluation, timing analysis etc.
This project deals with a brief study of 32 and 64 bit processors
readily available in the market and designing/ fabricating a 64 bit
RISC processor named RISC MicroProcessor with added
functionalities of an extended double precision floating point unit
and a 32 bit signal processing unit acting as co-processors. In this
paper, we emphasize the ease and importance of using Open Core
(OpenSparc T1 Verilog RTL) and Open “Source" EDA tools such as
Icarus to develop FPGA based prototypes quickly. Commercial tools
such as Xilinx ISE for Synthesis are also used when appropriate.
Abstract: The emergence of person-centred discourse based
around notions of 'personal development planning- and 'work'life
balance' has taken hold in education and the workplace in recent
years. This paper examines this discourse with regard to recent
developments in higher education as well as the inter-related issue of
work-life balance in occupational careers. In both cases there have
been national and trans-national policy initiatives directed towards
improving both personal opportunities and competitive advantage in
a global knowledge-based economy. However, despite an increasing
concern with looking outward at this globalised educational and
employment marketplace, there is something of a paradox in
encouraging people to look inward at themselves in order to become
more self-determined. This apparent paradox is considered from a
discourse analytic perspective in terms of the ideological effects of an
increasing concern with the personal world. Specifically, it is argued
that there are tensions that emerge from a concern with an innerdirected
process of self-reflection that dissolve any engagement with
wider political issues that impact upon educational and career
development.
Abstract: This paper presents the methodology from machine
learning approaches for short-term rain forecasting system. Decision
Tree, Artificial Neural Network (ANN), and Support Vector Machine
(SVM) were applied to develop classification and prediction models
for rainfall forecasts. The goals of this presentation are to
demonstrate (1) how feature selection can be used to identify the
relationships between rainfall occurrences and other weather
conditions and (2) what models can be developed and deployed for
predicting the accurate rainfall estimates to support the decisions to
launch the cloud seeding operations in the northeastern part of
Thailand. Datasets collected during 2004-2006 from the
Chalermprakiat Royal Rain Making Research Center at Hua Hin,
Prachuap Khiri khan, the Chalermprakiat Royal Rain Making
Research Center at Pimai, Nakhon Ratchasima and Thai
Meteorological Department (TMD). A total of 179 records with 57
features was merged and matched by unique date. There are three
main parts in this work. Firstly, a decision tree induction algorithm
(C4.5) was used to classify the rain status into either rain or no-rain.
The overall accuracy of classification tree achieves 94.41% with the
five-fold cross validation. The C4.5 algorithm was also used to
classify the rain amount into three classes as no-rain (0-0.1 mm.),
few-rain (0.1- 10 mm.), and moderate-rain (>10 mm.) and the overall
accuracy of classification tree achieves 62.57%. Secondly, an ANN
was applied to predict the rainfall amount and the root mean square
error (RMSE) were used to measure the training and testing errors of
the ANN. It is found that the ANN yields a lower RMSE at 0.171 for
daily rainfall estimates, when compared to next-day and next-2-day
estimation. Thirdly, the ANN and SVM techniques were also used to
classify the rain amount into three classes as no-rain, few-rain, and
moderate-rain as above. The results achieved in 68.15% and 69.10%
of overall accuracy of same-day prediction for the ANN and SVM
models, respectively. The obtained results illustrated the comparison
of the predictive power of different methods for rainfall estimation.
Abstract: This study applied the Theory of Planned Behavior
model in predicting dietary behavior among Type 2 diabetics in a
Kenyan environment. The study was conducted for three months
within the diabetic clinic at Kisii Hospital in Nyanza Province in
Kenya and adopted sequential mixed methods design combing both
qualitative and quantitative phases. Qualitative data was analyzed
using grounded theory analysis method. Structural equation modeling
using maximum likelihood was used to analyze quantitative data.
The results based on the common fit indices revealed that the theory
of planned behavior fitted the data acceptably well among the Type 2
diabetes and within dietary behavior {χ2 = 223.3, df = 77, p = .02,
χ2/df = 2.9, n=237; TLI = .93; CFI =.91; RMSEA (90CI) = .090(.039,
.146)}. This implies that the Theory of Planned Behavior holds and
forms a framework for promoting dietary practice among Type 2
diabetics.
Abstract: Study of soil properties like field capacity (F.C.) and permanent wilting point (P.W.P.) play important roles in study of soil moisture retention curve. Although these parameters can be measured directly, their measurement is difficult and expensive. Pedotransfer functions (PTFs) provide an alternative by estimating soil parameters from more readily available soil data. In this investigation, 70 soil samples were collected from different horizons of 15 soil profiles located in the Ziaran region, Qazvin province, Iran. The data set was divided into two subsets for calibration (80%) and testing (20%) of the models and their normality were tested by Kolmogorov-Smirnov method. Both multivariate regression and artificial neural network (ANN) techniques were employed to develop the appropriate PTFs for predicting soil parameters using easily measurable characteristics of clay, silt, O.C, S.P, B.D and CaCO3. The performance of the multivariate regression and ANN models was evaluated using an independent test data set. In order to evaluate the models, root mean square error (RMSE) and R2 were used. The comparison of RSME for two mentioned models showed that the ANN model gives better estimates of F.C and P.W.P than the multivariate regression model. The value of RMSE and R2 derived by ANN model for F.C and P.W.P were (2.35, 0.77) and (2.83, 0.72), respectively. The corresponding values for multivariate regression model were (4.46, 0.68) and (5.21, 0.64), respectively. Results showed that ANN with five neurons in hidden layer had better performance in predicting soil properties than multivariate regression.
Abstract: Thailand-s health system is challenged by the rising
number of patients and decreasing ratio of medical
practitioners/patients, especially in rural areas. This may tempt
inexperienced GPs to rush through the process of anamnesis with the
risk of incorrect diagnosis. Patients have to travel far to the hospital
and wait for a long time presenting their case. Many patients try to
cure themselves with traditional Thai medicine. Many countries are
making use of the Internet for medical information gathering,
distribution and storage. Telemedicine applications are a relatively
new field of study in Thailand; the infrastructure of ICT had
hampered widespread use of the Internet for using medical
information. With recent improvements made health and technology
professionals can work out novel applications and systems to help
advance telemedicine for the benefit of the people. Here we explore
the use of telemedicine for people with health problems in rural areas
in Thailand and present a Telemedicine Diagnosis System for Rural
Thailand (TEDIST) for diagnosing certain conditions that people
with Internet access can use to establish contact with Community
Health Centers, e.g. by mobile phone. The system uses a Web-based
input method for individual patients- symptoms, which are taken by
an expert system for the analysis of conditions and appropriate
diseases. The analysis harnesses a knowledge base and a backward
chaining component to find out, which health professionals should be
presented with the case. Doctors have the opportunity to exchange
emails or chat with the patients they are responsible for or other
specialists. Patients- data are then stored in a Personal Health Record.
Abstract: Artifact rejection plays a key role in many signal processing applications. The artifacts are disturbance that can occur during the signal acquisition and that can alter the analysis of the signals themselves. Our aim is to automatically remove the artifacts, in particular from the Electroencephalographic (EEG) recordings. A technique for the automatic artifact rejection, based on the Independent Component Analysis (ICA) for the artifact extraction and on some high order statistics such as kurtosis and Shannon-s entropy, was proposed some years ago in literature. In this paper we try to enhance this technique proposing a new method based on the Renyi-s entropy. The performance of our method was tested and compared to the performance of the method in literature and the former proved to outperform the latter.
Abstract: The purpose of this study was to develop a “teachers’
self-efficacy scale for high school physical education teachers
(TSES-HSPET)” in Taiwan. This scale is based on the self-efficacy
theory of Bandura [1], [2]. This study used exploratory and
confirmatory factor analyses to test the reliability and validity. The
participants were high school physical education teachers in Taiwan.
Both stratified random sampling and cluster sampling were used to
sample participants for the study. 350 teachers were sampled in the
first stage and 234 valid scales (male 133, female 101) returned.
During the second stage, 350 teachers were sampled and 257 valid
scales (male 143, female 110, 4 did not indicate gender) returned. The
exploratory factor analysis was used in the first stage, and it got
60.77% of total variance for construct validity. The Cronbach’s alpha
coefficient of internal consistency was 0.91 for sumscale, and
subscales were 0.84 and 0.90. In the second stage, confirmatory factor
analysis was used to test construct validity. The result showed that the
fit index could be accepted (χ2 (75) =167.94, p
Abstract: This paper suggests a rethinking of the existing
research about Genetically Modified (GM) food. Since the first batch
of GM food was commercialised in the UK market, GM food rapidly
received and lost media attention in the UK. Disagreement on GM
food policy between the US and the EU has also drawn scholarly
attention to this issue. Much research has been carried out intending to
understand people-s views about GM food and the shaping of these
views. This paper was based on the data collected in twenty-nine
semi-structured interviews, which were examined through Erving
Goffman-s idea of self-presentation in interactions to suggest that the
existing studies investigating “consumer attitudes" towards GM food
have only considered the “front stage" in the dramaturgic metaphor.
This paper suggests that the ways in which people choose to present
themselves when participating these studies should be taken into
account during the data analysis.