2017 - Engineeringhttp://dr.lib.sjp.ac.lk/handle/123456789/70382024-03-29T11:20:19Z2024-03-29T11:20:19ZIntelligent System for High Resolution Computed Tomography (HRCT) Image Analysis: A conceptChandrasena, S.Subasinghe, A.http://dr.lib.sjp.ac.lk/handle/123456789/78052022-02-24T05:53:29Z2017-01-01T00:00:00ZIntelligent System for High Resolution Computed Tomography (HRCT) Image Analysis: A concept
Chandrasena, S.; Subasinghe, A.
2017-01-01T00:00:00ZJoint Assignment of Power, Routing, and Spectrum in Static Flexible-Grid NetworksYan, LiAgrell, ErikDharmaweera, M.NWymeersch, Henkhttp://dr.lib.sjp.ac.lk/handle/123456789/70972022-12-14T05:22:18Z2017-01-01T00:00:00ZJoint Assignment of Power, Routing, and Spectrum in Static Flexible-Grid Networks
Yan, Li; Agrell, Erik; Dharmaweera, M.N; Wymeersch, Henk
Attached; This paper proposes a novel network planning
strategy to jointly allocate physical layer resources together with
the routing and spectrum assignment in transparent nonlinear
flexible-grid optical networks with static traffic demands. The
physical layer resources, such as power spectral density, modulation format, and carrier frequency, are optimized for each
connection. By linearizing the Gaussian noise model, both an
optimal formulation and a low complexity decomposition heuristic are proposed. Our methods minimize the spectrum usage
of networks, while satisfying requirements on the throughput
and quality of transmission. Compared with existing schemes
that allocate a uniform power spectral density to all connections,
our proposed methods relax this constraint and, thus, utilize
network resources more efficiently. Numerical results show that
by optimizing the power spectral density per connection, the
spectrum usage can be reduced by around 20% over uniform
power spectral density schemes.
2017-01-01T00:00:00ZImproving numerical sea ice predictions in the Arctic Ocean by data assimilation using satellite observationsMudunkotuwa, D.Y.De Silva, L.W.A.Yamaguchi, H.http://dr.lib.sjp.ac.lk/handle/123456789/70952022-12-14T05:21:38Z2017-01-01T00:00:00ZImproving numerical sea ice predictions in the Arctic Ocean by data assimilation using satellite observations
Mudunkotuwa, D.Y.; De Silva, L.W.A.; Yamaguchi, H.
Attached; This study focuses on improving sea ice predictions in the Arctic Ocean by introducing data
assimilation into an ice-ocean coupled Ice-POM model that is used to predict sea ice conditions in the
Arctic sea routes. Ocean part of the model used in this study is based on the Princeton Ocean Model
(POM). The ice model considers discrete characteristics of ice along the ice edge. The model domain
consists of the Arctic Ocean, Greenland-Iceland-Norwegian (GIN) seas and the Northern Atlantic
Ocean. The model grid is with 25km horizontal resolution. An improved nudging method that takes
the observation errors into account is used in this study. Observation errors are varied in accordance
with the season and the location. Sea ice concentration, sea ice thickness and sea ice velocity are
assimilated simultaneously. Assimilation improved ocean and ice conditions significantly. This is
evident from the changes in sea ice extent, sea ice thickness and ocean salinity.
2017-01-01T00:00:00ZAn approach to deal with free riders in assessed group work. A case study in an undergraduate engineering programMudunkotuwa, D.Y.Samarasekara, G.N.Nandapala, K.Priyadarshani, K.A.M.http://dr.lib.sjp.ac.lk/handle/123456789/70942022-12-14T05:20:51Z2017-01-01T00:00:00ZAn approach to deal with free riders in assessed group work. A case study in an undergraduate engineering program
Mudunkotuwa, D.Y.; Samarasekara, G.N.; Nandapala, K.; Priyadarshani, K.A.M.
Attached; Group work are an essential component of engineering education programs. It is a challenge to assess
individual contributions in a group work assessment. General approach is to provide an identical
grade to all the group members. However, the problem with this approach is that of free riders, who
benefits but contributes less than their fair share of the tasks in the group work. To overcome this
issue a novel approach was employed. Two group assessments were considered in the analysis. After
each assessment, the group was asked to submit a single report with a chapter on individual
contributions. Students were asked to indicate the percentage of contribution from each member
clearly specifying individual contribution. Students were asked to provide strong justification when
two group members were given the same contribution percentage. Based on a questioner consisting
of open-ended and multiple answer questions, 167 student feedback statements received. These
statements were used to investigate the fairness and acceptability of the employed method.
Majority of (94%) students were satisfied with the percentage of contribution received from the
group and 80% stated that it is fair to be evaluated by peers. Students have commended the method
to be evaluated by peers since peers know the best about how each member have performed. Those
who stated that the method is unfair, raised the difficulties of assigning a unique percentage for each
member and requested to assign the same marks to several students. With this revision authors
propose the usage of aforementioned method to avoid free riders
2017-01-01T00:00:00Z