The Protocol Independent Multicast - Sparse Mode (PIM-SM) uses one center (referred here as the Rendezvous Point “RP”) for all sources in a multicast group. PIM-SM distributes the multicast traffic of a source through a so-called shared distribution
tree, whose root is at a predefined core called Rendezvous Point (RP). It also builds source-specific trees to the sources whose data rates exceed a defined threshold. In the literature, several investigations are done to improve and provide an efficient mechanism for the dynamic relocation of the RP depending on the sources or the members of the multicast group. In this paper, we extend the investigation of three search algorithms used to find the optimal RP position. To evaluate the performance of these algorithms, Estimated Tree Cost (ETC) and our improvement Enhanced Estimated Tree Cost (EETC), are used. The reason behind our choice these two methods is a comparative investigation of the RP-selection methods proposed in the literature. From the comparison we can see that ETC finds the most optimal position of the rendezvous point. The Hill-Climbing algorithm and the standard PIM-SM protocol with static RP-selection are used as a reference for comparison. Our algorithms result in a lower network load compared to RP-selection algorithm. However, they need additional control messages.
Advanced Reservation (AR) is used to guarantee resource provisioning for many different types of
applications including workflows. This technique is still under a huge controversy in both Business and
Research communities because of its potentialit
y of reducing resource utilization. Most of the works
proposed in this domain suggest reservation for the whole workflow schedule, and on all available
resources at the same time, which worsen the problem of resource utilization.
Many solutions are introduced to improve resource utilization under advanced reservation through
generating relaxed and elastic reservation plans that local scheduling systems could modify to improve
utilization and decrease internal fragmentation. These solutions depend mainly on changing rigid AR,
which considered to be the most difficult kind of reservation, into relaxed and elastic ones through adding
extra time on the resulted schedule and then distributing it on all tasks of the workflow.
This paper presents a new autonomic algorithm (EWARP) for producing elastic reservation plans for
workflow applications which doesn’t add extra times. Instead, it depends on exploiting the timing gaps
produced by the different scheduling algorithms. The new algorithm use the technique of discovering
timing gaps, but modifies it, and adds to it to be used for producing an elastic reservation plan for
workflows. The results presented in this paper demonstrate how the proposed algorithm outperforms
existing works in the fields by a lower bound approximating 25%.This shows that (EWARP) algorithm
offer efficient and practical solutions for the problem of scheduling workflow applications under QoS
constrains.
Many researches showed the ability of advance reservation to improve the predictability of the
system; that allows it to deliver the applications required time constrains. Applications with
many tasks require the system to ensure a number of reserv
ations on many different distributed
resources, which usually carried out through multi-level negotiation adding by that additional
overhead on the application total response time. The extra overhead depends on many
parameters including system workload and contention. Workflows add more complexity due to
their tasks’ dependencies; thus, any rejection of or delay for a task reservation would increase
application complete time.
This paper suggests the use of elastic advanced reservation plans that depend on time gaps
presented in the sub-optimal schedules, in order to improve the reservation acceptance rate. It
presents an elastic co-reservation agent which provides the needed reservations using First Fit
allocation strategy.
The results show the ability of the proposed agent to always improve the acceptance rate with an
average of (22.25%). The more important came out result is the agent ability to increase the
reservation acceptance rate with the increasing of system competence, reaching (48.4%) for
simultaneous 90 users at the system.
In this paper we describe a cepstral model of the vocal tract which models both formants and antiformants.
The investigated model is more precise compared to the linear prediction model, which models
only the formants of the vocal tract. The expone
ntial function is used for the inverse transformation.
However, it is difficult to implement this function on a digital signal processor. To solve this issue we use a
continued fraction expansion to approximate the exponential function. The transfer function that
approximates the exponential function is realized by using the Infinite Impulse Response (IIR) digital
filter, in which branches type Finite Impulse Response (FIR) digital filters are included. The coefficients
of the FIR digital filters are just the coefficients of the real speech cepstrum. The state-space difference
equations are proposed and implemented on a DSP56300 fixed-point digital signal processor (Motorola).
Finally, the results of the digital signal processor implementation for chosen vowels and consonants are
evaluated.
Speech databases form the main foundation in the construction of automatic
utterance, speaker recognition and speech recognition systems in different languages and
dialects. The elements of the speech database are audio files recorded for people's
voices in
the required language or dialect. The more the speech database is enriched with
comprehensive elements the more it contributes to produce systems that communicate with
the excellent performed machine. According to the lack of speech databases for the Syrian
dialects, the research did one. The created database contained sixteen voluntaries from
different Syrian dialects. Voluntaries' voices were recorded in different recording
conditions that is for studying the effect of variety of dialects, gender and the conditions of
recording on the vowel polygons. This research invested the created speech database in the
field of generating and analyzing of vowel polygons, as the vowel polygon is a geometric
polygon where its vertices represent the values of formant frequencies, and the area of the
polygon represents the output acoustic space.
In this research, a new comparison criterion was proposed to study properties of the
audio signal for each of the varieties of smokers and non-smoking persons. For this
purpose, a database for smokers has been created. The smoker database contains
12 Syrian
native speakers, six of them were smokers and the others were non-smokers. The smokers
had been smoking for more than 10 years. All speakers were men and their ages ranging
between 35 and 42 years old. They live in rural towns and speak the same dialect.
Syrian vowels can be classified into long vowels and short ones. The long vowels are
/AA/, /UU/, /II/ pronounced as ([ ي, و, ا ]) and the short vowels are /A/, /U/, /I/ pronounced
as ([ كسرة, ضمة, فتحة ]). In this study, the Speakers have to pronounce the following sentence
/I love Syria/ pronounced as ([ أَنَاْ أَحَبُّ سُوْرِيْة ]), and it was spoken during three hours. This
sentence is rich with vowels.
For each speaker, a long vowel triangle in ten planes and a short vowel triangle in ten
planes as well were generated and analyzed. A new criterion was suggested to determine
the most suitable vowel triangle for smoker distinction. This criterion depends on
calculating the different distances among all centers of vowel triangles in each plane and
determining the minimal distance called d. For each plane, the most suitable vowel triangle
had been set as AIU35 short vowel triangle and AAIIUU45 long vowel triangle.
Suspension system is considered one of the most important components of modern
automobiles as it is the responsible for the vehicle’s stability, balance and safety. The
presence of robust controller is very necessary in order to ensure full interac
tion between
suspension components and making accurate decisions at the right time. This paper
proposes to design an Extended Adaptive Neuro Fuzzy Inference System (EANFIS)
controller for suspension system in quarter car model. The proposed controller is used as
decision maker In order to contribute in absorbing shocks caused by bumpy roads, and to
prevent vibrations from reaching the cockpit. Furthermore, it provides stability and
coherence required to reduce the discomfort felt by passengers, which arises from road
roughness, which in turn, improve the road handling. The MATLAB Simulink is used to
simulate the proposed controller with the controlled model and to display the responses of
the controlled model under different types of disturbance. In addition, a comparison
between EANFIS controller, Fuzzy controller and open loop model (passive suspension)
was done with different types of disturbance on order to evaluate the performance of the
proposed model. Controller has shown excelled performance in terms of reducing
displacements, velocity and acceleration.
The speech recognition is one of the most modern technologies, which entered force
in various fields of life, whether medical or security or industrial techniques. Accordingly,
many related systems were developed, which differ from each otherin fea
ture extraction
methods and classification methods.
In this research,three systems have been created for speech recognition.They differ
from each other in the used methods during the stage of features extraction.While the first
system used MFCC algorithm, the second system used LPCC algorithm, and the third
system used PLP algorithm.All these three systems used HMM as classifier.
At the first, the performance of the speechrecognitionprocesswas studied and
evaluatedfor all the proposedsystems separately. After that, the combination algorithm was
applied separately on eachpair of the studied system algorithmsin order to study the effect
of using the combination algorithm onthe improvement of the speech recognition process.
Twokinds of errors(simultaneous errors and dependent errors) were usedto evaluate
the complementaryof each pair of the studied systems, and to study the effectiveness of the
combination on improving the performance of speech recognition process. It can be seen
from the results of the comparison that the best improvement ratio of speech recognition
has been obtained in the case of collection MFCC and PLP algorithms with recognition
ratio of 93.4%.
In this research, some of audio signal properties have been studied according to the
speaker's vocal tract shape. A database of audio files has been recorded. These files belong
to 57 men whose age between 35 and 45. All speakers came from the same
academic and
social culture. Furthermore, they don't suffer from any problems in hearings and utterance.
The vowel database was created in perfect recording conditions. The spent time
needed for recording process was about five minutes for each speaker who said the Arabic
word " سألتمُونِيهَا " three times. That word is very rich of vowel letters. It composes of the
whole Arabic long vowel.
Based on the analysis study of the recorded audio signals, the relationship between
the formant frequencies and the length of speaker's vocal tract has been studied. The results
show an inverse proportion for the first three frequencies F1, f2, F3 and no clear
relationship for the two other frequencies F4, F5.
