Abstract: Geological and tectonic framework indicates that
Bangladesh is one of the most seismically active regions in the world.
The Bengal Basin is at the junction of three major interacting plates:
the Indian, Eurasian, and Burma Plates. Besides there are many
active faults within the region, e.g. the large Dauki fault in the north.
The country has experienced a number of destructive earthquakes due
to the movement of these active faults. Current seismic provisions of
Bangladesh are mostly based on earthquake data prior to the 1990.
Given the record of earthquakes post 1990, there is a need to revisit
the design provisions of the code. This paper compares the base shear
demand of three major cities in Bangladesh: Dhaka (the capital city),
Sylhet, and Chittagong for earthquake scenarios of magnitudes
7.0MW, 7.5MW, 8.0MW, and 8.5MW using a stochastic model. In
particular, the stochastic model allows the flexibility to input region
specific parameters such as shear wave velocity profile (that were
developed from Global Crustal Model CRUST2.0) and include the
effects of attenuation as individual components. Effects of soil
amplification were analysed using the Extended Component
Attenuation Model (ECAM). Results show that the estimated base
shear demand is higher in comparison with code provisions leading to
the suggestion of additional seismic design consideration in the study
regions.
Abstract: In this paper, we propose the variational EM inference
algorithm for the multi-class Gaussian process classification model
that can be used in the field of human behavior recognition. This
algorithm can drive simultaneously both a posterior distribution of a
latent function and estimators of hyper-parameters in a Gaussian
process classification model with multiclass. Our algorithm is based
on the Laplace approximation (LA) technique and variational EM
framework. This is performed in two steps: called expectation and
maximization steps. First, in the expectation step, using the Bayesian
formula and LA technique, we derive approximately the posterior
distribution of the latent function indicating the possibility that each
observation belongs to a certain class in the Gaussian process
classification model. Second, in the maximization step, using a derived
posterior distribution of latent function, we compute the maximum
likelihood estimator for hyper-parameters of a covariance matrix
necessary to define prior distribution for latent function. These two
steps iteratively repeat until a convergence condition satisfies.
Moreover, we apply the proposed algorithm with human action
classification problem using a public database, namely, the KTH
human action data set. Experimental results reveal that the proposed
algorithm shows good performance on this data set.
Abstract: In the Solid-State-Drive (SSD) performance, whether
the data has been well parallelized is an important factor. SSD
parallelization is affected by allocation scheme and it is directly
connected to SSD performance. There are dynamic allocation and
static allocation in representative allocation schemes. Dynamic
allocation is more adaptive in exploiting write operation parallelism,
while static allocation is better in read operation parallelism.
Therefore, it is hard to select the appropriate allocation scheme when
the workload is mixed read and write operations. We simulated
conditions on a few mixed data patterns and analyzed the results to
help the right choice for better performance. As the results, if data
arrival interval is long enough prior operations to be finished and
continuous read intensive data environment static allocation is more
suitable. Dynamic allocation performs the best on write performance
and random data patterns.
Abstract: It is very important for a developing nation to
developing their infrastructure on the prime priority because their
infrastructure particularly their roads and transportation functions as a
blood in the system. Almost 1.1 billion populations share the travel
and transportation industry in India. On the other hand, the Pakistan
transportation industry is also extensive and elevating about 170
million users of transportation. Indian and Pakistani specifically
within bus industry are well connected within and between the urban
and rural areas. The transportation industry is radically helping the
economic alleviation of both countries. Due to high economic
instability, unemployment and poverty rate both countries
governments are very serious and committed to help for boosting
their economy. They believe that any form of transportation
development would play a vital role in the development of land,
infrastructure which could indirectly support many other industries’
developments, such as tourism, freighting and shipping businesses,
just to mention a few. However, it seems that their previous
transportation planning in the due course has failed to meet the fast
growing demand. As with the span of time, both the countries are
looking forward to a long-term, and economical solutions, because
the demand is from time to time keep appreciating and reacting
according to other key economic drivers. Content analysis method
and case study approach is used in this paper and secondary data
from the bureau of statistic is used for case analysis. The paper
focused on the mobility concerns of the lower and middle-income
people in India and Pakistan. The paper is aimed to highlight the
weaknesses, opportunities and limitations resulting from low priority
industry for a government, which is making the either country's
public suffer. The paper has concluded that the main issue is
identified as the slow, inappropriate, and unfavorable decisions which
are not in favor of long-term country’s economic development and
public interest. The paper also recommends to future research
avenues for public and private transportation, which is continuously
failing to meet the public expectations.
Abstract: Liver segmentation from medical images poses more
challenges than analogous segmentations of other organs. This
contribution introduces a liver segmentation method from a series of
computer tomography images. Overall, we present a novel method for
segmenting liver by coupling density matching with shape priors.
Density matching signifies a tracking method which operates via
maximizing the Bhattacharyya similarity measure between the
photometric distribution from an estimated image region and a model
photometric distribution. Density matching controls the direction of
the evolution process and slows down the evolving contour in regions
with weak edges. The shape prior improves the robustness of density
matching and discourages the evolving contour from exceeding liver’s
boundaries at regions with weak boundaries. The model is
implemented using a modified distance regularized level set (DRLS)
model. The experimental results show that the method achieves a
satisfactory result. By comparing with the original DRLS model, it is
evident that the proposed model herein is more effective in addressing
the over segmentation problem. Finally, we gauge our performance of
our model against matrices comprising of accuracy, sensitivity, and
specificity.
Abstract: The practical efficient approach is suggested for
estimation of the seismoacoustic sources energy in C-OTDR
monitoring systems. This approach is represents the sequential plan
for confidence estimation both the seismoacoustic sources energy, as
well the absorption coefficient of the soil. The sequential plan
delivers the non-asymptotic guaranteed accuracy of obtained
estimates in the form of non-asymptotic confidence regions with
prescribed sizes. These confidence regions are valid for a finite
sample size when the distributions of the observations are unknown.
Thus, suggested estimates are non-asymptotic and nonparametric,
and also these estimates guarantee the prescribed estimation accuracy
in form of prior prescribed size of confidence regions, and prescribed
confidence coefficient value.
Abstract: The education sector is constantly faced with rapid
changes in technologies in terms of ensuring that the curriculum is up
to date and in terms of making sure that students are aware of these
technological changes. This challenge can be seen as the motivation
for this study, which is to examine the factors affecting computing
students’ awareness of the latest Information Technologies (ICTs).
The aim of this study is divided into two sub-objectives which are:
the selection of relevant theories and the design of a conceptual
model to support it as well as the empirical testing of the designed
model. The first objective is achieved by a review of existing
literature on technology adoption theories and models. The second
objective is achieved using a survey of computing students in the four
universities of the KwaZulu-Natal province of South Africa. Data
collected from this survey is analyzed using Statistical package for
the Social Science (SPSS) using descriptive statistics, ANOVA and
Pearson correlations. The main hypothesis of this study is that there is
a relationship between the demographics and the prior conditions of
the computing students and their awareness of general ICT trends and
of Digital Switch Over (DSO) a new technology which involves the
change from analog to digital television broadcasting in order to
achieve improved spectrum efficiency. The prior conditions of the
computing students that were considered in this study are students’
perceived exposure to career guidance and students’ perceived
curriculum currency. The results of this study confirm that gender,
ethnicity, and high school computing course affect students’
perceived curriculum currency while high school location affects
students’ awareness of DSO. The results of this study also confirm
that there is a relationship between students prior conditions and their
awareness of general ICT trends and DSO in particular.
Abstract: The importance of agribusiness development is
proved in accordance with the trends in the agricultural sector of
Georgia. Agribusiness environment and the consequences of the
agricultural reforms are evaluated. The factors hindering the
development of agribusiness are revealed and the ways for
overcoming these problems are suggested. SWOT analysis is done in
order to identify the needs of agribusiness. The needs of agribusiness
development in Georgia are evaluated by priorities: prevention of
diseases and reduction of the harm caused by these diseases,
accessibility of long-term agricultural loans with low interest rates,
improving qualification of farmers, the level of education and usage
of modern technologies, changes in legislation, accessibility to high
quality agricultural machinery, and the development of infrastructure.
Based on the outcomes of the research, agribusiness development
strategies in Georgia are suggested and appropriate priorities of
economic policy are determined. Conclusions are made and based on
these conclusions, some recommendations are suggested.
Abstract: The purpose of the study was to examine lifelong
education for teachers as a tool for achieving effective teaching and
learning. Lifelong education enhances social inclusion, personal
development, citizenship, employability, teaching and learning,
community and the nation. It is imperative that the teacher needs to
update his knowledge regularly to be able to perform optimally, since
he has a major position in the inculcation of desirable elements in
students, and the challenges of lifelong education were also
discussed. Descriptive survey design was adopted for the study. A
simple random sampling technique was used to select 80 teachers as
sample from a population of 105 senior secondary school teachers in
Makurdi Local Government Area of Benue State. A 20-item self
designed questionnaire subjected to expert validation and reliability
was used to collect data. The reliability Alpha coefficient of 0.87 was
established using Cronbach’s Alpha technique, mean scores and
standard deviation were used to answer the 2 research questions
while chi-square was used to analyse data for the 2 null hypotheses,
which states that lifelong education for teachers is not a significant
tool for achieving effective teaching and lifelong education for
teachers does not significantly impact on effective learning. The
findings of the study revealed that, lifelong education for teachers can
be used as a tool for achieving effective teaching and learning, and
the study recommended among others that government, organizations
and individuals should in collaboration put lifelong education
programmes for teachers on the priority list. The paper concluded
that the strategic position of lifelong education for teachers towards
enhanced teaching, learning and the production of quality manpower
in the society makes it imperative for all hands to be on “deck” to
support the programme financially and otherwise.
Abstract: The objective of this study was to synthesize and
characterize the poly(alkenoic acid)s with different molecular
structures, use these polymers to formulate a dental cement
restorative, and study the effect of molecular structures on reaction
kinetics, viscosity, and mechanical strengths of the formed polymers
and cement restoratives. In this study, poly(alkenoic acid)s with
different molecular structures were synthesized. The purified
polymers were formulated with commercial Fuji II LC glass fillers to
form the experimental cement restoratives. The reaction kinetics was
studied via 1HNMR spectroscopy. The formed restoratives were
evaluated using compressive strength, diametral tensile strength,
flexural strength, hardness and wear-resistance tests. Specimens were
conditioned in distilled water at 37oC for 24 h prior to testing. Fuji II
LC restorative was used as control. The results show that the higher
the arm number and initiator concentration, the faster the reaction
was. It was also found that the higher the arm number and branching
that the polymer had, the lower the viscosity of the polymer in water
and the lower the mechanical strengths of the formed restorative. The
experimental restoratives were 31-53% in compressive strength, 37-
55% in compressive modulus, 80-126% in diametral tensile strength,
76-94% in flexural strength, 4-21% in fracture toughness and 53-96%
in hardness higher than Fuji II LC. For wear test, the experimental
restoratives were only 5.4-13% of abrasive and 6.4-12% of attritional
wear depths of Fuji II LC in each wear cycle. The aging study also
showed that all the experimental restoratives increased their strength
continuously during 30 days, unlike Fuji II LC. It is concluded that
polymer molecular structures have significant and positive impact on
mechanical properties of dental cement restoratives.
Abstract: This paper presents the design and implementation
details of a complete unmanned aerial system (UAS) based
on commercial-off-the-shelf (COTS) components, focusing on
safety, security, search and rescue scenarios in GPS-denied
environments. In particular, The aerial platform is capable
of semi-autonomously navigating through extremely low-light,
GPS-denied indoor environments based on onboard sensors only,
including a downward-facing optical flow camera. Besides, an
additional low-cost payload camera system is developed to stream
both infra-red video and visible light video to a ground station in
real-time, for the purpose of detecting sign of life and hidden humans.
The total cost of the complete system is estimated to be $1150,
and the effectiveness of the system has been tested and validated
in practical scenarios.
Abstract: People, throughout the history, have made estimates
and inferences about the future by using their past experiences.
Developing information technologies and the improvements in the
database management systems make it possible to extract useful
information from knowledge in hand for the strategic decisions.
Therefore, different methods have been developed. Data mining by
association rules learning is one of such methods. Apriori algorithm,
one of the well-known association rules learning algorithms, is not
commonly used in spatio-temporal data sets. However, it is possible
to embed time and space features into the data sets and make Apriori
algorithm a suitable data mining technique for learning spatiotemporal
association rules. Lake Van, the largest lake of Turkey, is a
closed basin. This feature causes the volume of the lake to increase or
decrease as a result of change in water amount it holds. In this study,
evaporation, humidity, lake altitude, amount of rainfall and
temperature parameters recorded in Lake Van region throughout the
years are used by the Apriori algorithm and a spatio-temporal data
mining application is developed to identify overflows and newlyformed
soil regions (underflows) occurring in the coastal parts of
Lake Van. Identifying possible reasons of overflows and underflows
may be used to alert the experts to take precautions and make the
necessary investments.
Abstract: Analytical techniques for measuring and planning
railway capacity expansion activities have been considered in this
article. A preliminary mathematical framework involving track
duplication and section sub divisions is proposed for this task. In
railways, these features have a great effect on network performance
and for this reason they have been considered. Additional motivations
have also arisen from the limitations of prior models that have not
included them.
Abstract: Carbon Fiber Reinforced Plastics (CFRPs) are widely
used for advanced applications, in particular in aerospace, automotive
and wind energy industries. Once cured to near net shape, CFRP
parts need several finishing operations such as trimming, milling or
drilling in order to accommodate fastening hardware and meeting the
final dimensions. The present research aims to study the effect of the
cutting temperature in trimming on the mechanical strength of high
performance CFRP laminates used for aeronautics applications. The
cutting temperature is of great importance when dealing with
trimming of CFRP. Temperatures higher than the glass-transition
temperature (Tg) of the resin matrix are highly undesirable: they
cause degradation of the matrix in the trimmed edges area, which can
severely affect the mechanical performance of the entire component.
In this study, a 9.50mm diameter CVD diamond coated carbide tool
with six flutes was used to trim 24-plies CFRP laminates. A
300m/min cutting speed and 1140mm/min feed rate were used in the
experiments. The tool was heated prior to trimming using a
blowtorch, for temperatures ranging from 20°C to 300°C. The
temperature at the cutting edge was measured using embedded KType
thermocouples. Samples trimmed for different cutting
temperatures, below and above Tg, were mechanically tested using
three-points bending short-beam loading configurations. New cutting
tools as well as worn cutting tools were utilized for the experiments.
The experiments with the new tools could not prove any correlation
between the length of cut, the cutting temperature and the mechanical
performance. Thus mechanical strength was constant, regardless of
the cutting temperature. However, for worn tools, producing a cutting
temperature rising up to 450°C, thermal damage of the resin was
observed. The mechanical tests showed a reduced mean resistance in
short beam configuration, while the resistance in three point bending
decreases with increase of the cutting temperature.
Abstract: A problem of complex mineral resources development is urgent and priority, it is aimed at realization of the processes of their ecologically safe development, one of its components is revealing the influence of the forms of element compounds in raw materials and in the processing products. In view of depletion of the precious metal reserves at the traditional deposits in the XXI century the large-size open cast deposits, localized in black shale strata begin to play the leading role. Carbonaceous (black) shales carry a heightened metallogenic potential. Black shales with high content of carbon are widely distributed within the scope of Bureinsky massif. According to academician Hanchuk`s data black shales of Sutirskaya series contain generally PGEs native form. The presence of high absorptive towards carbonaceous matter gold and PGEs compounds in crude ore results in decrease of valuable components extraction because of their sorption into dissipated carbonaceous matter.
Abstract: The market competition is moving from the single
firm to the whole supply chain because of increasing competition and
growing need for operational efficiencies and customer orientation.
Supply chain management allows companies to look beyond their
organizational boundaries to develop and leverage resources and
capabilities of their supply chain partners. This creates competitive
advantages in the marketplace and because of this SCM has acquired
strategic importance. Lean Approach is a management strategy that focuses on reducing
every type of waste present in an organization. This approach is
becoming more and more popular among supply chain managers. The supply chain application of lean approach is not frequent. In
particular, it is not well studied which are the impacts of lean
approach principles in a supply chain context. In literature there are
only few studies aimed at understanding the qualitative impact of the
lean approach in supply chains. Therefore, the goal of this research
work is to study the impacts of lean principles implementation along
a supply chain. To achieve this, a simulation model of a threeechelon
multi-product supply chain has been built. Kanban system (and several priority policies) and setup time
reduction degrees are implemented in the lean-configured supply
chain to apply pull and lot-sizing decrease principles respectively. To
evaluate the benefits of lean approach, lean supply chain is compared
with an EOQ-configured supply chain. The simulation results show
that Kanban system and setup-time reduction improve inventory
stock level. They also show that logistics efforts are affected to lean
implementation degree. The paper concludes describing
performances of lean supply chain in different contexts.
Abstract: Inference plays an important role in the learning
process and it can lead to a rapid acquisition of a second language.
When learning a non-native language i.e., a critical language like
Arabic, the students depend on the teacher’s support most of the time
to learn new concepts. The students focus on memorizing the new
vocabulary and stress on learning all the grammatical rules. Hence,
the students became mechanical and cannot produce the language
easily. As a result, they are unable to predicate the meaning of words
in the context by relying heavily on the teacher, in that they cannot
link their prior knowledge or even identify the meaning of the words
without the support of the teacher. This study explores how the
teacher guides students learning during the inference process and
what are the processes of learning that can direct student’s inference.
Abstract: This paper studied the flow shop scheduling problem under machine availability constraints. The machines are subject to flexible preventive maintenance activities. The nonresumable scenario for the jobs was considered. That is, when a job is interrupted by an unavailability period of a machine it should be restarted from the beginning. The objective is to minimize the total tardiness time for the jobs and the advance/tardiness for the maintenance activities. To solve the problem, a genetic algorithm was developed and successfully tested and validated on many problem instances. The computational results showed that the new genetic algorithm outperforms another earlier proposed algorithm.
Abstract: A Mobile Adhoc Network (MANET) is a collection of mobile nodes that communicate with each other with wireless links and without pre-existing communication infrastructure. Routing is an important issue which impacts network performance. As MANETs lack central administration and prior organization, their security concerns are different from those of conventional networks. Wireless links make MANETs susceptible to attacks. This study proposes a new trust mechanism to mitigate wormhole attack in MANETs. Different optimization techniques find available optimal path from source to destination. This study extends trust and reputation to an improved link quality and channel utilization based Adhoc Ondemand Multipath Distance Vector (AOMDV). Differential Evolution (DE) is used for optimization.
Abstract: As a basic physiology need, threat to sufficient food
production is threat to human survival. Food security has been an
issue that has gained global concern. This paper looks at the food
security in Nigeria by assessing the availability of food and
accessibility of the available food. The paper employed multiple
linear regression technique and graphic trends of growth rates of
relevant variables to show the situation of food security in Nigeria.
Results of the tests revealed that population growth rate was higher
than the growth rate of food availability in Nigeria for the earlier
period of the study. Commercial bank credit to agricultural sector,
foreign exchange utilization for food and the Agricultural Credit
Guarantee Scheme Fund (ACGSF) contributed significantly to food
availability in Nigeria. Food prices grew at a faster rate than the
average income level, making it difficult to access sufficient food. It
implies that prior to the year 2012; there was insufficient food to feed
the Nigerian populace. However, continued credit to the food and
agricultural sector will ensure sustained and sufficient production of
food in Nigeria. Microfinance banks should make sufficient credit
available to smallholder farmer. Government should further control
and subsidize the rising price of food to make it more accessible by
the people.