Abstract: As the mobile Internet has become widespread in
recent years, communication based on mobile networks is increasing.
As a result, security threats have been posed with regard to the
abnormal traffic of mobile networks, but mobile security has been
handled with focus on threats posed by mobile malicious codes, and
researches on security threats to the mobile network itself have not
attracted much attention. In mobile networks, the IP address of the data
packet is a very important factor for billing purposes. If one mobile
terminal use an incorrect IP address that either does not exist or could
be assigned to another mobile terminal, billing policy will cause
problems. We monitor and analyze 3G mobile data networks traffics
for a period of time and finds some abnormal IP packets. In this paper,
we analyze the reason for abnormal IP packets on 3G Mobile Data
Networks. And we also propose an algorithm based on IP address table
that contains addresses currently in use within the mobile data network
to detect abnormal IP packets.
Abstract: Coal tar is a liquid by-product of the process of coal
gasification and carbonation. This liquid oil mixture contains various
kinds of useful compounds such as phenol, o-cresol, and p-cresol.
These compounds are widely used as raw material for insecticides,
dyes, medicines, perfumes, coloring matters, and many others.
This research needed to be done that given the optimum conditions
for the separation of phenol, o-cresol, and p-cresol from the coal tar
by solvent extraction process. The aim of the present work was to
study the effect of two kinds of aqueous were used as solvents:
methanol and acetone solutions, the effect of temperature (298, 306,
and 313K) and mixing (30, 35, and 40rpm) for the separation of
phenol, o-cresol, and p-cresol from coal tar by solvent extraction.
Results indicated that phenol, o-cresol, and p-cresol in coal tar
were selectivity extracted into the solvent phase and these
components could be separated by solvent extraction. The aqueous
solution of methanol, mass ratio of solvent to feed, Eo/Ro=1,
extraction temperature 306K and mixing 35 rpm were the most
efficient for extraction of phenol, o-cresol, and p-cresol from coal tar.
Abstract: We integrate TiN/Ni/HfO2/Si RRAM cell with a
vertical gate-all-around (GAA) nanowire transistor to achieve
compact 4F2 footprint in a 1T1R configuration. The tip of the Si
nanowire (source of the transistor) serves as bottom electrode of the
memory cell. Fabricated devices with nanowire diameter ~ 50nm
demonstrate ultra-low current/power switching; unipolar switching
with 10μA/30μW SET and 20μA/30μW RESET and bipolar switching
with 20nA/85nW SET and 0.2nA/0.7nW RESET. Further, the
switching current is found to scale with nanowire diameter making the
architecture promising for future scaling.
Abstract: The “PYRAMIDS" Block Cipher is a symmetric encryption algorithm of a 64, 128, 256-bit length, that accepts a variable key length of 128, 192, 256 bits. The algorithm is an iterated cipher consisting of repeated applications of a simple round transformation with different operations and different sequence in each round. The algorithm was previously software implemented in Cµ code. In this paper, a hardware implementation of the algorithm, using Field Programmable Gate Arrays (FPGA), is presented. In this work, we discuss the algorithm, the implemented micro-architecture, and the simulation and implementation results. Moreover, we present a detailed comparison with other implemented standard algorithms. In addition, we include the floor plan as well as the circuit diagrams of the various micro-architecture modules.
Abstract: Designing and implementing intelligent systems has become a crucial factor for the innovation and development of better products of space technologies. A neural network is a parallel system, capable of resolving paradigms that linear computing cannot. Field programmable gate array (FPGA) is a digital device that owns reprogrammable properties and robust flexibility. For the neural network based instrument prototype in real time application, conventional specific VLSI neural chip design suffers the limitation in time and cost. With low precision artificial neural network design, FPGAs have higher speed and smaller size for real time application than the VLSI and DSP chips. So, many researchers have made great efforts on the realization of neural network (NN) using FPGA technique. In this paper, an introduction of ANN and FPGA technique are briefly shown. Also, Hardware Description Language (VHDL) code has been proposed to implement ANNs as well as to present simulation results with floating point arithmetic. Synthesis results for ANN controller are developed using Precision RTL. Proposed VHDL implementation creates a flexible, fast method and high degree of parallelism for implementing ANN. The implementation of multi-layer NN using lookup table LUT reduces the resource utilization for implementation and time for execution.
Abstract: This study reports results of a meta-analytic path analysis e-learning Acceptance Model with k = 27 studies, Databases searched included Information Sciences Institute (ISI) website. Variables recorded included perceived usefulness, perceived ease of use, attitude toward behavior, and behavioral intention to use e-learning. A correlation matrix of these variables was derived from meta-analytic data and then analyzed by using structural path analysis to test the fitness of the e-learning acceptance model to the observed aggregated data. Results showed the revised hypothesized model to be a reasonable, good fit to aggregated data. Furthermore, discussions and implications are given in this article.
Abstract: Social Business Process Management (SBPM)
promises to overcome limitations of traditional BPM by allowing
flexible process design and enactment through the involvement of
users from a social community. This paper proposes a meta-model
and architecture for socially driven business process management
systems. It discusses the main facets of the architecture such as goalbased
role assignment that combines social recommendations with
user profile, and process recommendation, through a real example of
a charity organization.
Abstract: The main aim of this paper was to investigate the
existing architecture in Cyprus, and thus identify and describe the
overall architectural rationale of the built environment. In Cyprus,
where individuals live in a society that reflects postmodern
paradigms rather than modern ones, the existing built environment
has many different reflections of the structure of its society.
Abstract: The purposes of this study are 1) to identify
learning styles of university students in Bangkok, and 2) to study
the frequency of the relevant instructional context of the identified
learning styles. Learning Styles employed in this study are those of
Honey and Mumford, which include 1) Reflectors, 2) Theorists, 3)
Pragmatists, and 4) Activists. The population comprises 1383
students and 5 lecturers. Research tools are 2 questionnaires – one
used for identifying students- learning styles, and the other used for
identifying the frequency of the relevant instructional context of
the identified learning styles.
The research findings reveal that 32.30 percent - are Activists,
while 28.10 percent are Theorists, 20.10 are Reflectors, and 19.50
are Pragmatists. In terms of the relevant instructional context of the
identified 4 learning styles, it is found that the frequency level of
the instructional context is totally in high level. Moreover, 2 lists of
the context being conducted most frequently are 'Lead'in activity
to review background knowledge,- and 'Information retrieval
report.' And these two activities serve the learning styles of
theorists and activists. It is, therefore, suggested that more
instructional context supporting the activists, the majority of the
population, learning best by doing, as well as emotional learning
situation should be added.
Abstract: A hybrid learning automata-genetic algorithm (HLGA) is proposed to solve QoS routing optimization problem of next generation networks. The algorithm complements the advantages of the learning Automato Algorithm(LA) and Genetic Algorithm(GA). It firstly uses the good global search capability of LA to generate initial population needed by GA, then it uses GA to improve the Quality of Service(QoS) and acquiring the optimization tree through new algorithms for crossover and mutation operators which are an NP-Complete problem. In the proposed algorithm, the connectivity matrix of edges is used for genotype representation. Some novel heuristics are also proposed for mutation, crossover, and creation of random individuals. We evaluate the performance and efficiency of the proposed HLGA-based algorithm in comparison with other existing heuristic and GA-based algorithms by the result of simulation. Simulation results demonstrate that this paper proposed algorithm not only has the fast calculating speed and high accuracy but also can improve the efficiency in Next Generation Networks QoS routing. The proposed algorithm has overcome all of the previous algorithms in the literature.
Abstract: The following study aims to outline, whether the
perceptions of entrepreneurs about their entrepreneurial activities and
the underlying meanings of their activities are universal or whether
they vary systematically across cultures. In contrast to previous
studies, the phenomenographical approach and the resulting findings
of this study provide new insights into what constitutes
entrepreneurship by drawing an inference from the perceptions of
entrepreneurs in the United States and in Germany. Culture is shown
to have an important impact on entrepreneurship, since the
underlying meanings of entrepreneurship vary significantly among
the two sample groups. Furthermore, the study sheds more light on
the culturally contingent 'why' of entrepreneurship by looking at the
internal motivations of individuals instead of exclusively focusing on
character traits or external influences of the respective economic
environments.
Abstract: It is believed that major account on language diversity must be taken in learning, and especially in learning using ICT. This paper-s objective is to exhibit language and communication barriers in learning, to approach the topic from socioculture and cognitivist perspectives, and to give exploratory solutions of handling such barriers. The review is mainly conducted by approaching the journal Computers & Education, but also an initially broad search was conducted. The results show that not much attention is paid on language and communication barriers in an immediate relation to learning using ICT. The results shows, inter alia, that language and communication barriers are caused because of not enough account is taken on both the individual-s background and the technology.
Abstract: Functional gastrointestinal disorders affect millions of people spread all age regardless of race and sex. There are, however, rare diagnostic methods for the functional gastrointestinal disorders because functional disorders show no evidence of organic and physical causes. Our research group identified recently that the gastrointestinal tract well in the patients with the functional gastrointestinal disorders becomes more rigid than healthy people when palpating the abdominal regions overlaying the gastrointestinal tract. Aim of this study is, therefore, to develop a diagnostic system for the functional gastrointestinal disorders based on ultrasound technique, which can quantify the characteristic above related to the rigidity of the gastrointestinal tract well. Ultrasound system was designed. The system consisted of transmitter, ultrasonic transducer, receiver, TGC, and CPLD, and verified via a phantom test. For the phantom test, ten soft-tissue specimens were harvested from porcine. Five of them were then treated chemically to mimic a rigid condition of gastrointestinal tract well, which was induced by functional gastrointestinal disorders. Additionally, the specimens were tested mechanically to identify if the mimic was reasonable. The customized ultrasound system was finally verified through application to human subjects with/without functional gastrointestinal disorders (Normal and Patient Groups). It was identified from the mechanical test that the chemically treated specimens were more rigid than normal specimen. This finding was favorably compared with the result obtained from the phantom test. The phantom test also showed that ultrasound system well described the specimen geometric characteristics and detected an alteration in the specimens. The maximum amplitude of the ultrasonic reflective signal in the rigid specimens (0.2±0.1Vp-p) at the interface between the fat and muscle layers was explicitly higher than that in the normal specimens (0.1±0.0Vp-p). Clinical tests using our customized ultrasound system for human subject showed that the maximum amplitudes of the ultrasonic reflective signals near to the gastrointestinal tract well for the patient group (2.6±0.3Vp-p) were generally higher than those in normal group (0.1±0.2Vp-p). Here, maximum reflective signals was appeared at 20mm depth approximately from abdominal skin for all human subjects, corresponding to the location of the boundary layer close to gastrointestinal tract well. These results suggest that newly designed diagnostic system based on ultrasound technique may diagnose enough the functional gastrointestinal disorders.
Abstract: This paper addresses control of commutation of switched reluctance (SR) motor without the use of a physical position detector. Rotor position detection schemes for SR motor based on magnetisation characteristics of the motor use normal excitation or applied current /voltage pulses. The resulting schemes are referred to as passive or active methods respectively. The research effort is in realizing an economical sensorless SR rotor position detector that is accurate, reliable and robust to suit a particular application. An effective and reliable means of generating commutation signals of an SR motor based on inductance profile of its stator windings determined using active probing technique is presented. The scheme has been validated online using a 4-phase 8/6 SR motor and an 8-bit processor.
Abstract: This study was aimed to study the probability about
the production of fiberboard made of durian rind through latex with
phenolic resin as binding agent. The durian rind underwent the
boiling process with NaOH [7], [8] and then the fiber from durian
rind was formed into fiberboard through heat press. This means that
durian rind could be used as replacement for plywood in plywood
industry by using durian fiber as composite material with adhesive
substance. This research would study the probability about the
production of fiberboard made of durian rind through latex with
phenolic resin as binding agent. At first, durian rind was split,
exposed to light, boiled and steamed in order to gain durian fiber.
Then, fiberboard was tested with the density of 600 Kg/m3 and 800
Kg/m3. in order to find a suitable ratio of durian fiber and latex.
Afterwards, mechanical properties were tested according to the
standards of ASTM and JIS A5905-1994. After the suitable ratio was
known, the test results would be compared with medium density
fiberboard (MDF) and other related research studies. According to
the results, fiberboard made of durian rind through latex with
phenolic resin at the density of 800 Kg/m3 at ratio of 1:1, the
moisture was measured to be 5.05% with specific gravity (ASTM D
2395-07a) of 0.81, density (JIS A 5905-1994) of 0.88 g/m3, tensile
strength, hardness (ASTM D2240), flexibility or elongation at break
yielded similar values as the ones by medium density fiberboard
(MDF).
Abstract: In this paper, we propose a new modular approach called neuroglial consisting of two neural networks slow and fast which emulates a biological reality recently discovered. The implementation is based on complex multi-time scale systems; validation is performed on the model of the asynchronous machine. We applied the geometric approach based on the Gerschgorin circles for the decoupling of fast and slow variables, and the method of singular perturbations for the development of reductions models.
This new architecture allows for smaller networks with less complexity and better performance in terms of mean square error and convergence than the single network model.
Abstract: One very interesting field of research in Pattern Recognition that has gained much attention in recent times is Gesture Recognition. In this paper, we consider a form of dynamic hand gestures that are characterized by total movement of the hand (arm) in space. For these types of gestures, the shape of the hand (palm) during gesturing does not bear any significance. In our work, we propose a model-based method for tracking hand motion in space, thereby estimating the hand motion trajectory. We employ the dynamic time warping (DTW) algorithm for time alignment and normalization of spatio-temporal variations that exist among samples belonging to the same gesture class. During training, one template trajectory and one prototype feature vector are generated for every gesture class. Features used in our work include some static and dynamic motion trajectory features. Recognition is accomplished in two stages. In the first stage, all unlikely gesture classes are eliminated by comparing the input gesture trajectory to all the template trajectories. In the next stage, feature vector extracted from the input gesture is compared to all the class prototype feature vectors using a distance classifier. Experimental results demonstrate that our proposed trajectory estimator and classifier is suitable for Human Computer Interaction (HCI) platform.
Abstract: An accident is an unexpected and unplanned situation
that happens and affects human in a negative outcome. The accident
can cause an injury to a human biological organism. Thus, the
provision of initial care for an illness or injury is very important
move to prepare the patients/victims before sending to the doctor. In
this paper, a First Aid Application is developed to give some
directions for preliminary taking care of patient/victim via Android
mobile device. Also, the navigation function using Google Maps API
is implemented in this paper for searching a suitable path to the
nearest hospital. Therefore, in the emergency case, this function can
be activated and navigate patients/victims to the hospital with the
shortest path.
Abstract: The Kansei engineering is a technology which
converts human feelings into quantitative terms and helps designers
develop new products that meet customers- expectation. Standard
Kansei engineering procedure involves finding relationships between
human feelings and design elements of which many researchers have
found forward and backward relationship through various soft
computing techniques. In this paper, we proposed the framework of
Kansei engineering linking relationship not only between human
feelings and design elements, but also the whole part of product, by
constructing association rules. In this experiment, we obtain input
from emotion score that subjects rate when they see the whole part of
the product by applying semantic differentials. Then, association
rules are constructed to discover the combination of design element
which affects the human feeling. The results of our experiment
suggest the pattern of relationship of design elements according to
human feelings which can be derived from the whole part of product.
Abstract: Iodine radionuclides in accident releases under severe
accident conditions at NPP with VVER are the most radiationimportant
with a view to population dose generation at the beginning
of the accident. To decrease radiation consequences of severe
accidents the technical solutions for severe accidents management
have been proposed in MIR.1200 project, with consideration of the
measures for suppression of volatile iodine forms generation in the
containment. Behavior dynamics of different iodine forms in the
containment under severe accident conditions has been analyzed for
the purpose of these technical solutions justification.