CS Project Abstract Booklet

Transcription

INDEX| Computer Science Abstracts
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Project Title
Access Right Delegation for Secure Group Information System
Dynasis – Secure Group Information Sharing System
Secure Light Explorer (slExplorer)
Enhancing User Experience (UX) using Microsoft Kinect
Med-Vision: A novel DICOM Viewer
Zimmedari- Instilling Social Responsibility, combating
Deep Learning using MPJ Express
EquiLenz
MPJ Express Runtime for Hadoop Yarn
CALVRI: Challan Accident License & Vehicle Registration
Detection and Grading of Proliferative Diabetic Retinopathy
Automated Trading
Sentiment Analysis Opinion Mining
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INDEX| Computer Science Abstracts
Sr
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
Project Title
EquiLenz
Automated Trading
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13
Group Members
Ahsan Moavia [2011-NUST-SEECS-CS-333]
Hafiz Muhammad Ibraheem Javed [2011-NUST-SEECS-CS-343]
Raza Ali [2011-NUST-SEECS-CS-355]
Advisor Awais Shibli Co Advisor Abdul Ghafoor Abbasi
Project Abstract
Large organizations often require different departments to collaborate efficiently for smooth and secure flow
of information. So there is a need to devise a mechanism which allows multiple organizations or departments
to share each other’s sensitive resources without breaching security mechanism in place. Dynamic delegation is
a mechanism which can be used to create policies of limited duration to delegate certain access rights to others.
Our project “Access Right Delegation for Secure Group Information System” aims not only on providing
authentication and authorization mechanism but Dynamic delegation as well. Authorized users, without the
involvement of system administrator can 'Delegate' available resources and 'Revoke' these delegated rights at
any time. This system is complemented with Policy Administration Point (PAP) which is user friendly interface,
Policy Enforcement Point (PEP) which enforces decisions made by the Policy Decision Point (PDP). Using latest
technologies like ‘Spring Framework’ and ‘Hibernate’ a generic code is designed which is robust and reusable.
1
Group Members
Ahsan Moavia [2011-NUST-SEECS-CS-333]
Hafiz Muhammad Ibraheem Javed [2011-NUST-SEECS-CS-343]
Raza Ali [2011-NUST-SEECS-CS-355]
Project Abstract
Large organizations often require different departments to collaborate efficiently for smooth and secure flow
of information. So there is a need to devise a mechanism which allows multiple organizations or departments
to share each other’s sensitive resources without breaching security mechanism in place. Dynamic delegation is
a mechanism which can be used to create policies of limited duration to delegate certain access rights to others.
Our project “Access Right Delegation for Secure Group Information System” aims not only on providing
authentication and authorization mechanism but Dynamic delegation as well. Authorized users, without the
involvement of system administrator can 'Delegate' available resources and 'Revoke' these delegated rights at
any time. This system is complemented with Policy Administration Point (PAP) which is user friendly interface,
Policy Enforcement Point (PEP) which enforces decisions made by the Policy Decision Point (PDP). Using latest
technologies like ‘Spring Framework’ and ‘Hibernate’ a generic code is designed which is robust and reusable
1
Group Members
Mansoor Ahmed [2011-NUST-SEECS-CS-346]
Saifullah [2011-NUST-SEECS-CS-358]
Yasir Ali [2011-NUST-SEECS-CS-367]
Project Abstract
In today’s era of technology, there are a number of security threats we tend to ignore, for instance Privacy
breach, Hacking, Traffic monitoring etc. Existing software solutions don’t focus on secure resource sharing and
group management as per user’s need. The organizations therefore rely on external email providers and other
expensive group collaboration and project management solutions.
Dynamic Secure Group Information sharing system helps to solve these problems and provides secure system
using well known security standards. These standards provide a security framework for creating and managing
cryptographic groups and offer a quantitative basis for security assurance. It focuses on development of an
open source and freeware solution that features secure group management and resource sharing. It also
manages the access to dynamically created groups based on events and time.
This uses GSAKMP (Group Secure Association Key Management Protocol) for high end group security. It
creates X509 Identities of users and effective authorization mechanism using Policy Token. It also provides
secure distribution of keys to members of group for encrypted resource sharing. The complete system is
developed using latest technologies standard like Spring Framework and Hibernate. Moreover, it is fast and
extensible enough to add any other required feature.
2
Group Members
Mansoor Ahmed [2011-NUST-SEECS-CS-346]
Saifullah [2011-NUST-SEECS-CS-358]
Yasir Ali [2011-NUST-SEECS-CS-367]
Project Abstract
In today’s era of technology, there are a number of security threats we tend to ignore, for instance Privacy
breach, Hacking, Traffic monitoring etc. Existing software solutions don’t focus on secure resource sharing and
group management as per user’s need. The organizations therefore rely on external email providers and other
expensive group collaboration and project management solutions.
Dynamic Secure Group Information sharing system helps to solve these problems and provides secure system
using well known security standards. These standards provide a security framework for creating and managing
cryptographic groups and offer a quantitative basis for security assurance. It focuses on development of an
open source and freeware solution that features secure group management and resource sharing. It also
manages the access to dynamically created groups based on events and time.
This uses GSAKMP (Group Secure Association Key Management Protocol) for high end group security. It
creates X509 Identities of users and effective authorization mechanism using Policy Token. It also provides
secure distribution of keys to members of group for encrypted resource sharing. The complete system is
developed using latest technologies standard like Spring Framework and Hibernate. Moreover, it is fast and
extensible enough to add any other required feature.
2
Group Member
Maria Rahat [2011-NUST-SEECS-CS-377]
Advisor Abdul Ghafoor Abbasi
Project Abstract
Mobile phone devices are a key component of our daily life. Owner of the device carries their personal
information, financial data and many other sensitive files in their mobile devices. If an attacker steals your
mobile phone then he/she can easily extract secret information from it. The file explorer has the access to
pictures, music, videos, documents, and other files on your Android devices. It also allows sharing files with
other android users or internet applications. In this project, we are planning to develop a secure file explorer
which will not only protect the local files but also provides a secure channel to share these files. In order to
design slExplorer, we will consider local authentication, peer authentication and establishment of secure
channel. slExplorer allows users to protect their file through passwords. The files are then encrypted with
these passwords and stored in local storage. The users can decrypt and view files only when the correct
password is entered. A password manager manages the passwords related to each file. The file is shared
through online repository i.e. Dropbox using asymmetric cryptography.
3
Group Member
Maria Rahat [2011-NUST-SEECS-CS-377]
Advisor Abdul Ghafoor Abbasi
Project Abstract
Mobile phone devices are a key component of our daily life. Owner of the device carries their personal
information, financial data and many other sensitive files in their mobile devices. If an attacker steals your
mobile phone then he/she can easily extract secret information from it. The file explorer has the access to
pictures, music, videos, documents, and other files on your Android devices. It also allows sharing files with
other android users or internet applications. In this project, we are planning to develop a secure file explorer
which will not only protect the local files but also provides a secure channel to share these files. In order to
design slExplorer, we will consider local authentication, peer authentication and establishment of secure
channel. slExplorer allows users to protect their file through passwords. The files are then encrypted with
these passwords and stored in local storage. The users can decrypt and view files only when the correct
password is entered. A password manager manages the passwords related to each file. The file is shared
through online repository i.e. Dropbox using asymmetric cryptography.
3
Group Members
Faizan Zahid [2011-NUST-SEECS-CS-340]
Advisor Faisal Khan Co Advisor Maajid Maqbool
Project Abstract
This project focuses on enhancing the User Experience and usability of Google Earth. There is a need for a
Natural User Interface (NUI) for Google Earth and Google Earth Street View. This combination could serve to
reduce reliance on GPS navigation devices, thereby eliminating a major distraction and increasing safety on the
road.The idea is to improve the user experience by replacing traditional mouse/keyboard inputs by hand
gestures. For instance, imagine Google Earth being displayed on a projected screen. The end user will be able to
rotate, zoom and hover the Earth just by using his/her hand gestures. It’s like exploring the world in mid-air
without any hardware interaction. The basic idea is to simulate the navigation of Google earth in an effective
and easy to use way. This project will create virtual reality based environment using Microsoft Kinect sensor.
The approach is to recognize hand gestures using Kinect depth sensors and then map them to the
corresponding navigation inputs for Google Earth. This project has the following Goals and Objectives:
• Build a Natural User Interface for Google Earth and Google Street View using the Microsoft Kinect.
• Allow the user to control the Google Earth interface using hand point tracking.
• Allow the user to control Google Earth Street View using skeleton tracking.
• Added voice recognition to fly over to specific countries and enter street view
• Allow the user to move between modes and modify options using gesture recognition.
• Create an experience that may allow users to memorize routes more quickly.
• Make a fun and immersive experience for the user.
• Package the final web based application that is easy to install, initiate and use.
• Encourage active use of electronics and software through a movement-dependent interface.
4
Group Members
Faizan Zahid [2011-NUST-SEECS-CS-340]
Advisor Faisal Khan Co Advisor Maajid Maqbool
Project Abstract
This project focuses on enhancing the User Experience and usability of Google Earth. There is a need for a
Natural User Interface (NUI) for Google Earth and Google Earth Street View. This combination could serve to
reduce reliance on GPS navigation devices, thereby eliminating a major distraction and increasing safety on the
road.
The idea is to improve the user experience by replacing traditional mouse/keyboard inputs by hand gestures.
For instance, imagine Google Earth being displayed on a projected screen. The end user will be able to rotate,
zoom and hover the Earth just by using his/her hand gestures. It’s like exploring the world in mid-air without
any hardware interaction. The basic idea is to simulate the navigation of Google earth in an effective and easy
to use way. This project will create virtual reality based environment using Microsoft Kinect sensor.
The approach is to recognize hand gestures using Kinect depth sensors and then map them to the
corresponding navigation inputs for Google Earth. This project has the following Goals and Objectives:
• Build a Natural User Interface for Google Earth and Google Street View using the Microsoft Kinect.
• Allow the user to control the Google Earth interface using hand point tracking.
• Allow the user to control Google Earth Street View using skeleton tracking.
• Added voice recognition to fly over to specific countries and enter street view
• Allow the user to move between modes and modify options using gesture recognition.
• Create an experience that may allow users to memorize routes more quickly.
• Make a fun and immersive experience for the user.
• Package the final web based application that is easy to install, initiate and use.
• Encourage active use of electronics and software through a movement-dependent interface.
4
Group Members
Aakifa Ishtiaq [2011-NUST-SEECS-CS-371]
Joveria Rubaab [2011-NUST-SEECS-CS-376]
Muhammad Umer Khan [2011-NUST-SEECS-CS-353]
Advisor Khalid Latif Co Advisor Muhammad Muddassir Malik
Project Abstract
DICOM is a standard for modeling, storing, printing and transmitting information from medical imaging devices
to healthcare systems. It is pervasively used in medical imaging in combination with different image formats
and communication protocols. DICOM-based Medical Imaging Viewers provide the necessary capability for the
doctors to interpret and analyze medical images such as brain scans and other modalities generated by
radiology devices. The technology world moved from desktop to laptops, and very recently, even from laptops
to tablets and phablets. On the contrary, DICOM-based Viewers are still traditional, mostly disconnected and
offer fewer options for mobility.
We propose a novel DICOM based Medical Image Viewer for tablets. This will allow targeted audience to view
high resolution medical scans on their handhelds and tablets. Practitioners will be able to apply different image
processing techniques for enhancing the medical images leading to improved readability and better diagnosis.
The Viewer also offers 3D Modelling and colour coding to assist in diagnosis.
5
Group Members
Aakifa Ishtiaq [2011-NUST-SEECS-CS-371]
Joveria Rubaab [2011-NUST-SEECS-CS-376]
Muhammad Umer Khan [2011-NUST-SEECS-CS-353]
Advisor Khalid Latif Co Advisor Muhammad Muddassir Malik
Project Abstract
DICOM is a standard for modeling, storing, printing and transmitting information from medical imaging devices
to healthcare systems. It is pervasively used in medical imaging in combination with different image formats
and communication protocols. DICOM-based Medical Imaging Viewers provide the necessary capability for the
doctors to interpret and analyze medical images such as brain scans and other modalities generated by
radiology devices. The technology world moved from desktop to laptops, and very recently, even from laptops
to tablets and phablets. On the contrary, DICOM-based Viewers are still traditional, mostly disconnected and
offer fewer options for mobility.
We propose a novel DICOM based Medical Image Viewer for tablets. This will allow targeted audience to view
high resolution medical scans on their handhelds and tablets. Practitioners will be able to apply different image
processing techniques for enhancing the medical images leading to improved readability and better diagnosis.
The Viewer also offers 3D Modelling and colour coding to assist in diagnosis.
5
Group Members
Ameer Hamza [2011-NUST-SEECS-CS-335]
Waqas Latif [2011-NUST-SEECS-CS-366]
Zaki Ur Rehman Malik [2011-NUST-SEECS-CS-369]
Advisor Maajid Maqbool Co Advisor Shamyl Mansoor
Project Abstract
Local community problems whilst prevalent in every society, seldom get media attention. People too, do not
have the time or inclination to report such daily challenges owing to tedious and complex procedures and lack
of faith in the governing bodies. All these factors contribute to such challenges remaining under the radar;
undetected, unnoticed and hence unsolved.
Zimmedari is going to be a vicinity-based mobile application based social network, expressly targeted to
promote local community interaction to identify and solve challenges collectively faced by the
Community. It will enable the residents of a community to be more vocal about the challenges they face on a
daily basis and get help from the community around them to effectively combat these challenges including but
not limited to civic infrastructure maintenance issues, educational problems, health and security concerns and
environmental issues. The social network takes a gamified approach to problem solving incorporating a
scoring model based on the number of problems reported and solved by a citizen resulting in community and
citizen standings to keep things more challenging and interesting, and leading the way to a better, more
responsible community.
6
Group Members
Ameer Hamza [2011-NUST-SEECS-CS-335]
Waqas Latif [2011-NUST-SEECS-CS-366]
Zaki Ur Rehman Malik [2011-NUST-SEECS-CS-369]
Advisor Maajid Maqbool Co Advisor Shamyl Mansoor
Project Abstract
Local community problems whilst prevalent in every society, seldom get media attention. People too, do not
have the time or inclination to report such daily challenges owing to tedious and complex procedures and lack
of faith in the governing bodies. All these factors contribute to such challenges remaining under the radar;
undetected, unnoticed and hence unsolved.
Zimmedari is going to be a vicinity-based mobile application based social network, expressly targeted to
promote local community interaction to identify and solve challenges collectively faced by the
Community. It will enable the residents of a community to be more vocal about the challenges they face on a
daily basis and get help from the community around them to effectively combat these challenges including but
not limited to civic infrastructure maintenance issues, educational problems, health and security concerns and
environmental issues. The social network takes a gamified approach to problem solving incorporating a
scoring model based on the number of problems reported and solved by a citizen resulting in community and
citizen standings to keep things more challenging and interesting, and leading the way to a better, more
responsible community
6
Group Members
Haider Adeel Agha [2011-NUST-SEECS-CS-344]
Salman Saeed [2011-NUST-SEECS-CS-359]
Advisor Tahir Azim Co Advisor Aamir Shafi
Project Abstract
Deep neural networks have shown high accuracy in tasks of object recognition. However, training these
networks is slow due to its computational cost, especially when the network and the dataset are large. Our
project aims to speed up deep network training without sacrificing accuracy by parallelizing it over multiple
processors using the Java-based MPJ Express library.
Our network contains three layers, a convolutional, pooling and fully connected layer softmax layer. The
convolutional layer extracts features from the input data, the pooling layer downsamples the input by
summarizing neurons from a small spatial neighborhood and the softmax layer classifies the images. The filters
applied to images in convolution and pooling layers are equally divided amongst the processors and their
results are combined on a single processor which executes the fully connected layer.
We train the network using the MNIST handwriting dataset which consists of 50,000 training and 10,000 test
images. Training this network in parallel on an Amazon EC2 cluster yields an accuracy of 95% on the test
dataset while showing linear speedup in training time for up to 4 processors. With more processors, training
time continues to decrease monotonically, but at a sub-linear rate due to increased communication costs.
7
Group Members
Haider Adeel Agha [2011-NUST-SEECS-CS-344]
Salman Saeed [2011-NUST-SEECS-CS-359]
Advisor Tahir Azim Co Advisor Aamir Shafi
Project Abstract
Deep neural networks have shown high accuracy in tasks of object recognition. However, training these
networks is slow due to its computational cost, especially when the network and the dataset are large. Our
project aims to speed up deep network training without sacrificing accuracy by parallelizing it over multiple
processors using the Java-based MPJ Express library.
Our network contains three layers, a convolutional, pooling and fully connected layer softmax layer. The
convolutional layer extracts features from the input data, the pooling layer downsamples the input by
summarizing neurons from a small spatial neighborhood and the softmax layer classifies the images. The filters
applied to images in convolution and pooling layers are equally divided amongst the processors and their
results are combined on a single processor which executes the fully connected layer.
We train the network using the MNIST handwriting dataset which consists of 50,000 training and 10,000 test
images. Training this network in parallel on an Amazon EC2 cluster yields an accuracy of 95% on the test
dataset while showing linear speedup in training time for up to 4 processors. With more processors, training
time continues to decrease monotonically, but at a sub-linear rate due to increased communication costs.
7
EquiLenz
Group Members
Azqa Nadeem [2011-NUST-SEECS-CS-373]
Faiza Ashfaq [2011-NUST-SEECS-CS-374]
Muhammad Saghir [2011-NUST-SEECS-CS-351]
Advisor Dr Anis ur Rehman Co Advisor Dr. Asad Anwar Butt
Project Abstract
Equation solving used to be tedious, but not anymore! EquiLenz, an android application, will change the way
equations are solved – more convenient and less error prone. Just by pointing a camera phone at any equation,
typeset or handwritten, EquiLenz will recognize it, solve and display the solution. Under the hood, the
application packs in a robust, flexible and complicated expression solver, capable of solving both linear and
quadratic equations. Moreover, the application also features a step-by-step solution that can be saved and
shared with friends.
8
EquiLenz
Group Members
Azqa Nadeem [2011-NUST-SEECS-CS-373]
Faiza Ashfaq [2011-NUST-SEECS-CS-374]
Muhammad Saghir [2011-NUST-SEECS-CS-351]
Advisor Dr Anis ur Rehman Co Advisor Dr. Asad Anwar Butt
Project Abstract
Equation solving used to be tedious, but not anymore! EquiLenz, an android application, will change the way
equations are solved – more convenient and less error prone. Just by pointing a camera phone at any equation,
typeset or handwritten, EquiLenz will recognize it, solve and display the solution. Under the hood, the
application packs in a robust, flexible and complicated expression solver, capable of solving both linear and
quadratic equations. Moreover, the application also features a step-by-step solution that can be saved and
shared with friends.
8
Group Members
Hamza Zafar [2011-NUST-SEECS-CS-345]
Muhammad Nouman Shahzad [2011-NUST-SEECS-CS-350]
Saad Hussain Syed
[2011-NUST-SEECS-CS-356]
Advisor Amir Shafi Co Advisor Dr. Asad Waqar
Project Abstract
Many organizations—including academic, research and commercial institutions—have invested heavily in
setting up High Performance Computing (HPC) facilities for running computational science applications. On the
other hand, the Apache Hadoop software has become a popular, reliable, and scalable open-source framework
for processing large-scale data (Big Data). Realizing the importance and significance of Big Data, an increasing
number of organizations are investing in relatively cheaper Hadoop clusters for executing their mission critical
data processing applications. An issue here is that, the system administrators at these sites might have to
maintain two parallel facilities for running HPC and Hadoop computations. In this context, a Hadoop YARNbased runtime system is developed for MPJ Express—a Java based open-source MPI—that allows executing
parallel MPI-like Java applications on Hadoop clusters. This project increases the performance of iterative
machine learning applications on Hadoop systems using MPJ Express. In this context a K-Means clustering
application is written to benchmark the runtime. In addition, a number of real world applications—sorting,
searching, graph processing problems—are developed for Problem Based Benchmark Suite (PBBS), which is an
open source repository to compare different parallel programming methodologies in terms of performance and
code quality.
9
Group Members
Hamza Zafar [2011-NUST-SEECS-CS-345]
Muhammad Nouman Shahzad [2011-NUST-SEECS-CS-350]
Saad Hussain Syed
Advisor Amir Shafi Co Advisor Dr. Asad Waqar
Project Abstract
Many organizations—including academic, research and commercial institutions—have invested heavily in
setting up High Performance Computing (HPC) facilities for running computational science applications. On the
other hand, the Apache Hadoop software has become a popular, reliable, and scalable open-source framework
for processing large-scale data (Big Data). Realizing the importance and significance of Big Data, an increasing
number of organizations are investing in relatively cheaper Hadoop clusters for executing their mission critical
data processing applications. An issue here is that, the system administrators at these sites might have to
maintain two parallel facilities for running HPC and Hadoop computations. In this context, a Hadoop YARNbased runtime system is developed for MPJ Express—a Java based open-source MPI—that allows executing
parallel MPI-like Java applications on Hadoop clusters. This project increases the performance of iterative
machine learning applications on Hadoop systems using MPJ Express. In this context a K-Means clustering
application is written to benchmark the runtime. In addition, a number of real world applications—sorting,
searching, graph processing problems—are developed for Problem Based Benchmark Suite (PBBS), which is an
open source repository to compare different parallel programming methodologies in terms of performance and
code quality
9
Group Members
Nida Noor
Sumbul Aftab [2011-NUST-SEECS-CS-380]
Advisor Dr. Kashif Sharif Co Advisor Samin Khaliq
Project Abstract
CALVRI is a self-contained online application to promote e-governance in Pakistan. The application aims to
automate the paper-based challan issuance and information system currently in use by the Islamabad Traffic
Police. It enables the general public to access, view and update their driving license and vehicle registration
information, apply online for driving license renewal and pay challans and token taxes through online and
mobile payment options. The Traffic Wardens are able to issue challans online, receive real time alerts and
updates, submit custom incident reports, and view location based statistics while on-duty.
10
Group Members
Nida Noor
Sumbul Aftab [2011-NUST-SEECS-CS-380]
Advisor Dr. Kashif Sharif Co Advisor Samin Khaliq
Project Abstract
CALVRI is a self-contained online application to promote e-governance in Pakistan. The application aims to
automate the paper-based challan issuance and information system currently in use by the Islamabad Traffic
Police. It enables the general public to access, view and update their driving license and vehicle registration
information, apply online for driving license renewal and pay challans and token taxes through online and
mobile payment options. The Traffic Wardens are able to issue challans online, receive real time alerts and
updates, submit custom incident reports, and view location based statistics while on-duty.
10
Group Members
Bilal Ahmad [2011-NUST-SEECS-CS-337]
Fubha Manal Burney [2011-NUST-SEECS-CS-341]
Talal Ibrahim[2011-NUST-SEECS-CS-362]
Advisor: Dr. Muhammad Moazam Fraz Co Advisor: Samin Khaliq
Project Abstract
Retino CAD is a Mobile PanOptic Ophthalmoscope based automated decision support system designed for the
detection of early symptoms of Proliferative Diabetic Retinopathy (PDR).
Proliferative diabetic retinopathy (PDR), an advanced stage of Diabetic Retinopathy, is a condition that carries
a high risk of severe visual impairment. The hallmark of PDR is neovascularization, the growth of abnormal
new vessels. Retinal image is acquired through Ophthalmoscope which leads to two parallel processing
sequences; one of them drives to a procedure that identifies both new blood vessels and normal vessels and the
other one reduces false responses to non-vessel edges. Both generated binary vessel maps, hold vital
information which must be processed separately. Local morphology features are measured from each binary
vessel map to produce two separate feature sets. Dual classification is performed on both feature sets
independently using Ensemble Bagged/Boosted Decision Trees. The system then combines these individual
classification outcomes through majority voting and determines the presence of PDR.
Retino CAD is especially suited for all diabetic patients to prevent them from vision loss by detecting the
symptoms of PDR beforehand reducing the manual grading workload with the capability of detecting the
presence of new vessels whilst reducing false responses.
11
Group Members
Bilal Ahmad [2011-NUST-SEECS-CS-337]
Fubha Manal Burney [2011-NUST-SEECS-CS-341]
Talal Ibrahim[2011-NUST-SEECS-CS-362]
Advisor: Dr. Muhammad Moazam Fraz Co Advisor: Samin Khaliq
Project Abstract
Retino CAD is a Mobile PanOptic Ophthalmoscope based automated decision support system designed for the
detection of early symptoms of Proliferative Diabetic Retinopathy (PDR).
Proliferative diabetic retinopathy (PDR), an advanced stage of Diabetic Retinopathy, is a condition that carries
a high risk of severe visual impairment. The hallmark of PDR is neovascularization, the growth of abnormal
new vessels. Retinal image is acquired through Ophthalmoscope which leads to two parallel processing
sequences; one of them drives to a procedure that identifies both new blood vessels and normal vessels and the
other one reduces false responses to non-vessel edges. Both generated binary vessel maps, hold vital
information which must be processed separately. Local morphology features are measured from each binary
vessel map to produce two separate feature sets. Dual classification is performed on both feature sets
independently using Ensemble Bagged/Boosted Decision Trees. The system then combines these individual
classification outcomes through majority voting and determines the presence of PDR.
Retino CAD is especially suited for all diabetic patients to prevent them from vision loss by detecting the
symptoms of PDR beforehand reducing the manual grading workload with the capability of detecting the
presence of new vessels whilst reducing false responses.
11
Automated Trading
Group Members
Kausar Perveen [2011-NUST-SEECS-BE-SE-266]
Syeda Sundus Zehra [2011-NUST-SEECS-BE-SE-288]
Anjli [2011-NUST-SEECS-CS-372
Project Abstract
Advisor: Sohail Iqbal Co Advisor: Hilal Butt
This project involves the creation of a mobile-based intelligent stock trading system that saves investors time
by minimizing the role of the broker. It offers various modes to the user whereby the user can construct
portfolios, stay updated with the latest market news, get recommendations on which shares to buy or sell,
graphically view the performance of companies on the Karachi Stock Exchange and customize portfolios based
on the budget and investment strategy being employed. The system’s app also involves a tutorial mode which
teaches new users on how to use the App. A major feature in the App is that it offers a game mode which
provides investors a virtual trading platform that can show users what they can get out of their investments if
they invest a certain amount of money and buy a certain number of shares in a company. Besides, the App also
involves Facebook subscriptions and a SMS-based alert system that informs users where they stand at the
moment in respect to the investments they have made and what profitability they can potentially get out of it.
For forecasting and prediction purposes, the App uses recent and intermediate momentum strategies,
contrarian strategies, trend analysis, moving averages and past trends. These predictions are done on Server
side that is hosted on SEECS domain and alerts are then sent to client side. In short, with the help of this trading
system, a businessman can perform rapid and profitable investments in minimum time , minimum user
involvement and maximum accuracy.
12
Automated Trading
Group Members
Kausar Perveen [2011-NUST-SEECS-BE-SE-266]
Syeda Sundus Zehra [2011-NUST-SEECS-BE-SE-288]
Anjli [2011-NUST-SEECS-CS-372
Advisor: Sohail Iqbal Co Advisor: Hilal Butt
Project Abstract
This project involves the creation of a mobile-based intelligent stock trading system that saves investors time
by minimizing the role of the broker. It offers various modes to the user whereby the user can construct
portfolios, stay updated with the latest market news, get recommendations on which shares to buy or sell,
graphically view the performance of companies on the Karachi Stock Exchange and customize portfolios based
on the budget and investment strategy being employed. The system’s app also involves a tutorial mode which
teaches new users on how to use the App. A major feature in the App is that it offers a game mode which
provides investors a virtual trading platform that can show users what they can get out of their investments if
they invest a certain amount of money and buy a certain number of shares in a company. Besides, the App also
involves Facebook subscriptions and a SMS-based alert system that informs users where they stand at the
moment in respect to the investments they have made and what profitability they can potentially get out of it.
For forecasting and prediction purposes, the App uses recent and intermediate momentum strategies,
contrarian strategies, trend analysis, moving averages and past trends. These predictions are done on Server
side that is hosted on SEECS domain and alerts are then sent to client side. In short, with the help of this trading
system, a businessman can perform rapid and profitable investments in minimum time , minimum user
involvement and maximum accuracy.
12
Group Members
Junaid Khan [2010-NUST-SEECS-BE-SE-239]
Waqar Ali [2011-NUST-SEECS-CS-365]
Advisor: Dr. Muneeb Ullah Co Advisor: Sir. Maajid Maqbool
Project Abstract
Sentiment analysis and opinion mining is the field of study that analyzes people's opinions, sentiments,
evaluations, attitudes, and emotions from written language. It is one of the most active research areas in
natural language processing and is also widely studied in data mining, Web mining, and text mining.
We are aiming to develop a Smart phone app (iOS App) to help buyers to buy new smart phone based upon the
experience of users who are already using that phone.
We are extracting tweets about the latest smart phone launched. Data pre-processing is performed on the raw
data to remove punctuations, numbers, #tags, and unwanted links. Then the well-Structured data is classified
into +ve or –ve classes using lexicon and machine learning approach. Based on this classification we are
drawing graphical representation of the overall sentiments of the people about different smart phones. The
end product is an iOS based App which uses these results to help you select your new smart phone.
13
Group Members
Junaid Khan [2010-NUST-SEECS-BE-SE-239]
Waqar Ali [2011-NUST-SEECS-CS-365]
Advisor: Dr. Muneeb Ullah Co Advisor: Sir. Maajid Maqbool
Project Abstract
Sentiment analysis and opinion mining is the field of study that analyzes people's opinions, sentiments,
evaluations, attitudes, and emotions from written language. It is one of the most active research areas in
natural language processing and is also widely studied in data mining, Web mining, and text mining.
We are aiming to develop a Smart phone app (iOS App) to help buyers to buy new smart phone based upon the
experience of users who are already using that phone.
We are extracting tweets about the latest smart phone launched. Data pre-processing is performed on the raw
data to remove punctuations, numbers, #tags, and unwanted links. Then the well-Structured data is classified
into +ve or –ve classes using lexicon and machine learning approach. Based on this classification we are
drawing graphical representation of the overall sentiments of the people about different smart phones. The
end product is an iOS based App which uses these results to help you select your new smart phone.
13

CS Project Abstract Booklet

Transcription

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