Abstract: Reticence is a prominent and complex phenomenon
which occurs in foreign language classrooms and influences students’
oral passivity. The present study investigated the extent in which
students experience reticence in the EFL classrooms and explored the
underlying factors triggering reticence. The participants were 104
Iranian freshmen undergraduate male and female EFL students, who
enrolled in listening and speaking courses, all majoring in English
studying at Islamic Azad University Isfahan (Khorasgan) Branch and
University of Isfahan, Isfahan, Iran. To collect the data, the Reticence
Scale-12 (RS-12) questionnaire which measures the level of reticence
consisting of six dimensions (anxiety, knowledge, timing,
organization, skills, and memory) was administered to the
participants. The statistical analyses showed that the reticent level
was high among the Iranian EFL undergraduate students, and their
major problems were feelings of anxiety and delivery skills.
Moreover, the results revealed that factors such as low English
proficiency, the teaching method, and lack of confidence contributed
to the students’ reticence in Iranian EFL classrooms. It can be
implied that language teachers’ awareness of learners’ reticence can
help them choose more appropriate activities and provide a friendly
environment enhancing hopefully more effective participation of EFL
learners. The findings can have implications for EFL teachers,
learners and policy makers.
Abstract: For the music composer Myriam Marbe the musical
time and memory represent 2 (complementary) phenomena with
conclusive impact on the settlement of new musical ontologies.
Summarizing the most important achievements of the contemporary
techniques of composition, her vision on the microform presented in
The Concert for Daniel Kientzy, saxophone and orchestra transcends
the linear and unidirectional time in favour of a flexible, multivectorial
speech with spiral developments, where the sound substance
is auto(re)generated by analogy with the fundamental processes of
the memory. The conceptual model is of an archetypal essence, the
music composer being concerned with identifying the mechanisms of
the creation process, especially of those specific to the collective
creation (of oral tradition). Hence the spontaneity of expression,
improvisation tint, free rhythm, micro-interval intonation, coloristictimbral
universe dominated by multiphonics and unique sound
effects, hence the atmosphere of ritual, however purged by the
primary connotations and reprojected into a wonderful spectacular
space. The Concert is a work of artistic maturity and enforces respect,
among others, by the timbral diversity of the three species of
saxophone required by the music composer (baritone, sopranino and
alt), in Part III Daniel Kientzy shows the performance of playing two
saxophones concomitantly. The score of the music composer Myriam
Marbe contains a deeply spiritualized music, full or archetypal
symbols, a music whose drama suggests a real cinematographic
movement.
Abstract: Historical narration is an act that necessarily develops
and deforms history. This “translation” is examined within the
historical and political context of the 1930 Berlin film premiere of
“All Quiet on the Western Front,” a film based on Erich Maria
Remarque’s 1928 best-selling novel. Both the film and the novel
appeared during an era in which life was conceived of as innately
artistic. The emergence of this “aestheticization” of memory and
history enabled conservative propaganda of the period to denounce
all art that did not adhere conceptually to its political tenets, with “All
Quiet” becoming yet another of its “victims.”
Abstract: In the Hierarchical Temporal Memory (HTM) paradigm
the effect of overlap between inputs on the activation of columns in
the spatial pooler is studied. Numerical results suggest that similar
inputs are represented by similar sets of columns and dissimilar inputs
are represented by dissimilar sets of columns. It is shown that the
spatial pooler produces these results under certain conditions for
the connectivity and proximal thresholds. Following the discussion
of the initialization of parameters for the thresholds, corresponding
qualitative arguments about the learning dynamics of the spatial
pooler are discussed.
Abstract: We have conducted the optimal synthesis of rootmean-
squared objective filter to estimate the state vector in the case if
within the observation channel with memory the anomalous noises
with unknown mathematical expectation are complement in the
function of the regular noises. The synthesis has been carried out for
linear stochastic systems of continuous - time.
Abstract: For optimal unbiased filter as mean-square and in the
case of functioning anomalous noises in the observation memory
channel, we have proved insensitivity of filter to inaccurate
knowledge of the anomalous noise intensity matrix and its
equivalence to truncated filter plotted only by non anomalous
components of an observation vector.
Abstract: Diminished antioxidant defense or increased
production of reactive oxygen species in the biological system can
result in oxidative stress which may lead to various
neurodegenerative diseases including Alzheimer’s disease (AD).
Microglial activation also contributes to the progression of AD by
producing several proinflammatory cytokines, nitric oxide (NO) and
prostaglandin E2 (PGE2). Oxidative stress and inflammation have
been reported to be possible pathophysiological mechanisms
underlying AD. In addition, the cholinergic hypothesis postulates that
memory impairment in patient with AD is also associated with the
deficit of cholinergic function in the brain. Although a number of
drugs have been approved for the treatment of AD, most of these
synthetic drugs have diverse side effects and yield relatively modest
benefits. Marine algae have great potential in pharmaceutical and
biomedical applications as they are valuable sources of bioactive
properties such as anticoagulation, antimicrobial, antioxidative,
anticancer and anti-inflammatory. Hence, this study aimed to provide
an overview of the properties of Malaysian seaweeds (Padina
australis, Sargassum polycystum and Caulerpa racemosa) in
inhibiting oxidative stress, neuroinflammation and cholinesterase
enzymes. These seaweeds significantly exhibited potent DPPH and
moderate superoxide anion radical scavenging ability (P
Abstract: Formal verification is proposed to ensure the
correctness of the design and make functional verification more
efficient. As cache plays a vital role in the design of System on Chip
(SoC), and cache with Memory Management Unit (MMU) and cache
memory unit makes the state space too large for simulation to verify,
then a formal verification is presented for such system design. In the
paper, a formal model checking verification flow is suggested and a
new cache memory model which is called “exhaustive search model”
is proposed. Instead of using large size ram to denote the whole cache
memory, exhaustive search model employs just two cache blocks. For
cache system contains data cache (Dcache) and instruction cache
(Icache), Dcache memory model and Icache memory model are
established separately using the same mechanism. At last, the novel
model is employed to the verification of a cache which is module of a
custom-built SoC system that has been applied in practical, and the
result shows that the cache system is verified correctly using the
exhaustive search model, and it makes the verification much more
manageable and flexible.
Abstract: ESPRIT-TLS method appears a good choice for high
resolution fault detection in induction machines. It has a very high
effectiveness in the frequency and amplitude identification.
Contrariwise, it presents a high computation complexity which
affects its implementation in real time fault diagnosis. To avoid this
problem, a Fast-ESPRIT algorithm that combined the IIR band-pass
filtering technique, the decimation technique and the original
ESPRIT-TLS method was employed to enhance extracting accurately
frequencies and their magnitudes from the wind stator current with
less computation cost. The proposed algorithm has been applied to
verify the wind turbine machine need in the implementation of an online,
fast, and proactive condition monitoring. This type of remote
and periodic maintenance provides an acceptable machine lifetime,
minimize its downtimes and maximize its productivity. The
developed technique has evaluated by computer simulations under
many fault scenarios. Study results prove the performance of Fast-
ESPRIT offering rapid and high resolution harmonics recognizing
with minimum computation time and less memory cost.
Abstract: This paper presents a method of hardening the 8051
micro-controller, able to assure reliable operation in the presence of
bit flips caused by radiation. Aiming at avoiding such faults in the
8051 micro-controller, Hamming code protection was used in its
SRAM memory and registers. A VHDL code has been used for this
hamming code protection.
Abstract: Near-infrared spectroscopy (NIRS) has been widely
used as a non-invasive method to measure brain activity, but it is
corrupted by baseline drift noise. Here we present a method to measure
regional cerebral blood flow as a derivative of NIRS output. We
investigate whether, when listening to languages, blood flow can
reasonably localize and represent regional brain activity or not. The
prefrontal blood flow distribution pattern when advanced
second-language listeners listened to a second language (L2) was most
similar to that when listening to their first language (L1) among the
patterns of mean and standard deviation. In experiments with 25
healthy subjects, the maximum blood flow was localized to the left
BA46 of advanced listeners. The blood flow presented is robust to
baseline drift and stably localizes regional brain activity.
Abstract: In-memory database systems are becoming popular
due to the availability and affordability of sufficiently large RAM and
processors in modern high-end servers with the capacity to manage
large in-memory database transactions. While fast and reliable inmemory
systems are still being developed to overcome cache misses,
CPU/IO bottlenecks and distributed transaction costs, disk-based data
stores still serve as the primary persistence. In addition, with the
recent growth in multi-tenancy cloud applications and associated
security concerns, many organisations consider the trade-offs and
continue to require fast and reliable transaction processing of diskbased
database systems as an available choice. For these
organizations, the only way of increasing throughput is by improving
the performance of disk-based concurrency control. This warrants a
hybrid database system with the ability to selectively apply an
enhanced disk-based data management within the context of inmemory
systems that would help improve overall throughput.
The general view is that in-memory systems substantially
outperform disk-based systems. We question this assumption and
examine how a modified variation of access invariance that we call
enhanced memory access, (EMA) can be used to allow very high
levels of concurrency in the pre-fetching of data in disk-based
systems. We demonstrate how this prefetching in disk-based systems
can yield close to in-memory performance, which paves the way for
improved hybrid database systems. This paper proposes a novel EMA
technique and presents a comparative study between disk-based EMA
systems and in-memory systems running on hardware configurations
of equivalent power in terms of the number of processors and their
speeds. The results of the experiments conducted clearly substantiate
that when used in conjunction with all concurrency control
mechanisms, EMA can increase the throughput of disk-based systems
to levels quite close to those achieved by in-memory system. The
promising results of this work show that enhanced disk-based
systems facilitate in improving hybrid data management within the
broader context of in-memory systems.
Abstract: Artificial Immune Systems (AIS), inspired by the
human immune system, are algorithms and mechanisms which are
self-adaptive and self-learning classifiers capable of recognizing and
classifying by learning, long-term memory and association. Unlike
other human system inspired techniques like genetic algorithms and
neural networks, AIS includes a range of algorithms modeling on
different immune mechanism of the body. In this paper, a mechanism
of a human immune system based on apoptosis is adopted to build an
Intrusion Detection System (IDS) to protect computer networks.
Features are selected from network traffic using Fisher Score. Based
on the selected features, the record/connection is classified as either
an attack or normal traffic by the proposed methodology. Simulation
results demonstrates that the proposed AIS based on apoptosis
performs better than existing AIS for intrusion detection.
Abstract: Existing methods of data mining cannot be applied on
spatial data because they require spatial specificity consideration, as
spatial relationships.
This paper focuses on the classification with decision trees, which
are one of the data mining techniques. We propose an extension of
the C4.5 algorithm for spatial data, based on two different approaches
Join materialization and Querying on the fly the different tables.
Similar works have been done on these two main approaches, the
first - Join materialization - favors the processing time in spite of
memory space, whereas the second - Querying on the fly different
tables- promotes memory space despite of the processing time.
The modified C4.5 algorithm requires three entries tables: a target
table, a neighbor table, and a spatial index join that contains the
possible spatial relationship among the objects in the target table and
those in the neighbor table. Thus, the proposed algorithms are applied
to a spatial data pattern in the accidentology domain.
A comparative study of our approach with other works of
classification by spatial decision trees will be detailed.
Abstract: This paper attempts to evaluate the effect of fire
damage on concrete by using nonlinear resonance vibration method,
one of the nonlinear nondestructive method. Concrete exhibits not
only nonlinear stress-strain relation but also hysteresis and discrete
memory effect which are contained in consolidated materials.
Hysteretic materials typically show the linear resonance frequency
shift. Also, the shift of resonance frequency is changed according to
the degree of micro damage. The degree of the shift can be obtained
through nonlinear resonance vibration method. Five exposure
scenarios were considered in order to make different internal micro
damage. Also, the effect of post-fire-curing on fire-damaged concrete
was taken into account to conform the change in internal damage.
Hysteretic nonlinearity parameter was obtained by amplitudedependent
resonance frequency shift after specific curing periods. In
addition, splitting tensile strength was measured on each sample to
characterize the variation of residual strength. Then, a correlation
between the hysteretic nonlinearity parameter and residual strength
was proposed from each test result.
Abstract: Chaotic analysis has been performed on the river flow time series before and after applying the wavelet based de-noising techniques in order to investigate the noise content effects on chaotic nature of flow series. In this study, 38 years of monthly runoff data of three gauging stations were used. Gauging stations were located in Ghar-e-Aghaj river basin, Fars province, Iran. Noise level of time series was estimated with the aid of Gaussian kernel algorithm. This step was found to be crucial in preventing removal of the vital data such as memory, correlation and trend from the time series in addition to the noise during de-noising process.
Abstract: The objectives were to study language learning strategies (LLSs) employed by Chinese students, and the frequency of LLSs they used, and examine the relationship between the use of LLSs and gender. The Strategy Inventory for Language Learning (SILL) by Oxford was administered to thirty-six Chinese students at Suan Sunandha Rajabhat University in Thailand. The data obtained was analyzed using descriptive statistics and chi-square tests. Three useful findings were found on the use of LLSs reported by Chinese students. First, Chinese students used overall LLSs at a high level. Second, among the six strategy groups, Chinese students employed compensation strategy most frequently and memory strategy least frequently. Third, the research results also revealed that gender had significant effect on Chinese Student’s use of overall LLSs.
Abstract: CNFET has emerged as an alternative material to
silicon for high performance, high stability and low power SRAM
design in recent years. SRAM functions as cache memory in
computers and many portable devices. In this paper, a new SRAM
cell design based on CNFET technology is proposed. The proposed
SRAM cell design for CNFET is compared with SRAM cell designs
implemented with the conventional CMOS and FinFET in terms of
speed, power consumption, stability, and leakage current. The
HSPICE simulation and analysis show that the dynamic power
consumption of the proposed 8T CNFET SRAM cell’s is reduced
about 48% and the SNM is widened up to 56% compared to the
conventional CMOS SRAM structure at the expense of 2% leakage
power and 3% write delay increase.
Abstract: Traditional Wireless Sensor Networks (WSNs) generally use static sinks to collect data from the sensor nodes via multiple forwarding. Therefore, network suffers with some problems like long message relay time, bottle neck problem which reduces the performance of the network.
Many approaches have been proposed to prevent this problem with the help of mobile sink to collect the data from the sensor nodes, but these approaches still suffer from the buffer overflow problem due to limited memory size of sensor nodes. This paper proposes an energy efficient scheme for data gathering which overcomes the buffer overflow problem. The proposed scheme creates virtual grid structure of heterogeneous nodes. Scheme has been designed for sensor nodes having variable sensing rate. Every node finds out its buffer overflow time and on the basis of this cluster heads are elected. A controlled traversing approach is used by the proposed scheme in order to transmit data to sink. The effectiveness of the proposed scheme is verified by simulation.
Abstract: This paper presents a comparative study between two
neural network models namely General Regression Neural Network
(GRNN) and Back Propagation Neural Network (BPNN) are used
to estimate radial overcut produced during Electrical Discharge
Machining (EDM). Four input parameters have been employed:
discharge current (Ip), pulse on time (Ton), Duty fraction (Tau) and
discharge voltage (V). Recently, artificial intelligence techniques, as
it is emerged as an effective tool that could be used to replace
time consuming procedures in various scientific or engineering
applications, explicitly in prediction and estimation of the complex
and nonlinear process. The both networks are trained, and the
prediction results are tested with the unseen validation set of the
experiment and analysed. It is found that the performance of both the
networks are found to be in good agreement with average percentage
error less than 11% and the correlation coefficient obtained for the
validation data set for GRNN and BPNN is more than 91%. However,
it is much faster to train GRNN network than a BPNN and GRNN is
often more accurate than BPNN. GRNN requires more memory space
to store the model, GRNN features fast learning that does not require
an iterative procedure, and highly parallel structure. GRNN networks
are slower than multilayer perceptron networks at classifying new
cases.