High-quality arguments are an essential part of decision-making. Automatically predicting the quality of an argument is a complex task that recently got much attention in argument mining. However, the annotation effort for this task is exceptionally
high. Therefore, we test uncertainty-based active learning (AL) methods on two popular argument-strength data sets to estimate whether sample-efficient learning can be enabled. Our extensive empirical evaluation shows that uncertainty-based acquisition functions can not surpass the accuracy reached with the random acquisition on these data sets.
We review two features of mixture of experts (MoE) models which we call averaging and clustering effects in the context of graph-based dependency parsers learned in a supervised probabilistic framework. Averaging corresponds to the ensemble combinati
on of parsers and is responsible for variance reduction which helps stabilizing and improving parsing accuracy. Clustering describes the capacity of MoE models to give more credit to experts believed to be more accurate given an input. Although promising, this is difficult to achieve, especially without additional data. We design an experimental set-up to study the impact of these effects. Whereas averaging is always beneficial, clustering requires good initialization and stabilization techniques, but its advantages over mere averaging seem to eventually vanish when enough experts are present. As a by product, we show how this leads to state-of-the-art results on the PTB and the CoNLL09 Chinese treebank, with low variance across experiments.
This research presents an empirical study about the behavior of High Strength Concrete
beams under the static cyclic loading. It determines the influence of cyclic loading on the
moment capacity and deflection of HSC beams. A comparison of the mome
nt capacity and
deflection in both kinds of loading (monotonic and cyclic loading) were achieved.
High Strength Concrete mixture was designed, based on the specifications of the American
code ACI 211.4R-93. Thirty six concrete beams were prepared, nine of them were tested
under monotonic loading and the rest of beams were tested under cyclic loading. The
cyclic loading was performed for (5,10,15) cycles, at a range from zero to 65%, 75%, 85%
of the minimum expected monotonic load.
The results showed that the cyclic loading have positive effect on the flexural behavior of
HSC members, whereas the moment capacity increased and the deflection decreased,
especially at a range from zero to 75% of the minimum expected monotonic load, when
the number of cycles was 5,10,15.
This research presents an empirical relationship between modulus
of elasticity with compressive strength concrete that is prepeard
from localized materials and containing several perecentages of
natural pozzolan (0 ,10 ,15, 20)% , also for tow cem
ent quantity
(350 ,400 ) Kg/m3 and for tow ages(28 ,90 ) day .Then comparing
the experimentally obtained result with the mechanical properties
calculated using the recommend relationship from the various
design codes. A new empirical relationship between elastic
modulus, and compressive strength for concrete containing natural
pozzolan is proposed.
The aim of this study was to evaluate and compare the effect of irrigation
solutions on the dentin flexural strength .(20) extracted third molars were
gathered with age avarege (18-24) years old, and the dentine bars that will
be prepared and designed for study with similar dimensions (width 1
mm, thickness 2 mm, Length of at least 7 mm).
The study of the effect of the common addition of Syrian Clay
and magnesium oxides on the specifications of the resulting
cement stone and specifically its effect on the elasticity of the
resulting stone.
An appropriate bond between glass‑ionomer and the superficial
resin materials is very important for the success of sandwich
technique. The aim of the present in vitro study was to evaluate the
effect of three surface treatments of conventional glass‑ionomer on
its shear bond strength to giomer
This study aimed to evaluate the fracture resistance of the E
glass Fiber Reinforced Composite when used to repair two different
kinds of dental porcelain.
Mobile wireless sensor network (MWSN) is a wireless ad hoc network that consists
of avery large number of tiny sensor nodes communicating with each other in which
sensornodes are either equipped with motors for active mobility or attached to mobile
objectsfor passive mobility. A real-time routing protocol for MWSN is an exciting area of
research
because messages in the network are delivered according to their end-to-end
deadlines
(packet lifetime) while sensor nodes are mobile. This paper proposes an enhanced
realtime
with load distribution (ERTLD) routing protocol for MWSN which is based on our
previousrouting protocol RTLD. ERTLD utilized corona mechanism and optimal
forwardingmetrics to forward the data packet in MWSN. It computes the optimal
forwarding nodebased on RSSI, remaining battery level of sensor nodes and packet
delayover one-hop. ERTLDensures high packet delivery ratio and experiences minimum
end-to-end delay in WSNand MWSN compared to baseline routing protocol. . In this paper
we consider a highly dynamic wireless sensor network system in which the sensor nodes
and the base station(sink) are mobile.ERTLD has been studied and verified and compared
with baseline routing protocols RTLD,MM-SPEED , RTLCthrough Network Simulator-
2(NS2)
شبكات الحساسات اللاسلكية
RTLD (Real-time with load distributed routing) Protocol
شبكات الحساسات اللاسلكية النقالة
بروتوكول التوجيه بالزمن الحقيقي مع توزيع الحمولة
بروتوكول التوجيه بالزمن الحقيقي المحسن مع توزيع الحمولة
معدل استقبال الرزمة
خيار التوجيه الأفضل
مؤشر قوة الاشارة المستقبلة
WSN(wireless sensor networks)
MWSN) Mobile wireless sensor networks)
ERTLD ( Enhanced Real-time with load distributed routing) Protocol
PRR(Packet Reception Rate)
Optimal Forwarding (OF)
RSSI: Received Signal Strength Indicator
MN(Mobile Node)
MS(Mobile sink)
المزيد..
The research aims to study is to study the effect of the pH factor of Pterocladia
capillacea on agar yield and some of its physical properties using different degrees of pH
(4- 5.5 - 5.5 - 6.5 - 7.5 - 7.5 - 8). The maximum yield of agar was 37.45%
at pH = 5 and
562g / cm2 and viscosity 10.7cP and 15.45% at pH = 8 with the highest strength of 768 g
/cm2 and viscosity of cP 156. The degree of melting and melting of agar Between (22-
33.5 οC) and (75- 86 οC), respectively.