Papers by Suradet Jitprapaikulsarn
In this paper, the already strong McEliece cryptosystem is enhanced with a two-dimensional finite... more In this paper, the already strong McEliece cryptosystem is enhanced with a two-dimensional finite Gaussian integer. By substituting the one-dimensional linear code with a two-dimensional code employing a finite Gaussian integer, a new system simultaneously increases the key space and the errors to be correct by syndrome decoding. We compare the proposed system against the classic McEliece system in three aspects: the work factors performing the trial of the attacks, the computational complexity cost, and the empirical running time of the system. Compared to the classic McEliece cryptosystem, the enhanced cryptosystem achieves a higher security level against key recovering and decoding attacks. By carefully selecting parameters, a small code element can improve the key strength without compromising the runtime efficiency.
TU-C-T-617-01: A Computer Model for Automatic Planning and Optimization for Gamma Knife Radiosurgery Using Auto-Positioning System
Medical Physics
Purpose: This research addresses the automatic‐planning of Gamma Knife radiosurgery using auto‐po... more Purpose: This research addresses the automatic‐planning of Gamma Knife radiosurgery using auto‐positioning system (APS). We previously reported a morphology‐guided automatic planning model via optimization of dose conformity and minimization of total number of shots with different collimator sizes. In this work, our goal is to develop an optimizationmodel that is adaptive to APS by using shots with same collimator.Method and Materials: Our three‐step optimization strategy is: (1) configure the initial shot set using a combined process of skeletonization and bin‐covering, (2) optimize the relative weight (exposure time) of each shot to improve target coverage while minimizing normal tissue toxicity, and (3) fine‐tune the shot configuration by adjusting shot locations, and adding or deleting shots to further improve the balance between target coverage and normal tissue toxicity. In the weight optimization phase in step 2, an easy‐to‐solve linear fractional program explicitly models the dual objectives and takes into account of dose‐renormalization (i.e., maximum is always renormalized to 100%). The fine‐tuning step explicitly takes into account of shot overlapping, dose renormalization and target shape thus making the tracking of hot spots and estimating the effects of shot movement, addition and/or deletion possible. Results: We have implemented this optimizationmodel on the Windows‐based platform and have tested it with seven previously treated clinical cases. The target volume ranges from 2.6 to 8.6 cc, while the number of shots used ranges from 13 to 39. Our computermodel generates plans in 1‐2 minutes, with compatible quality of physician's plans normally created in 1–4 hours. The target coverage is greater than 95% and PITV ranges from 1.29 to 2.26. Conclusions: Our computermodel can be used for real‐time planning, or for generating an initial plan followed by interactive optimization/fine‐tuning, or for creating multiple plans with different trade‐off objectives.
An Optimization-Based Treatment Planner for Gamma Knife Radiosurgery
Abstract: This research addresses the planning of Gamma Knife radiotherapy, which is an alternati... more Abstract: This research addresses the planning of Gamma Knife radiotherapy, which is an alternative to treating a variety of brain abnormalities with surgery. The principal aim of this work is to develop an automated planning system that will make it simpler, less time ...
Agile development methods: A Development paradigm for the Digital Ecosystem
Digital Ecosystems and …, Jan 1, 2008
An optimization-based treatment planner for gamma knife radiosurgery
Abstract: This research addresses the planning of Gamma Knife radiotherapy, which is an alternati... more Abstract: This research addresses the planning of Gamma Knife radiotherapy, which is an alternative to treating a variety of brain abnormalities with surgery. The principal aim of this work is to develop an automated planning system that will make it simpler, less time ...
Real-time inverse planning for Gamma Knife radiosurgery
Medical Physics, Jan 1, 2003
The challenges of real-time Gamma Knife inverse planning are the large number of variables involv... more The challenges of real-time Gamma Knife inverse planning are the large number of variables involved and the unknown search space a priori. With limited collimator sizes, shots have to be heavily overlapped to form a smooth prescription isodose line that conforms to the irregular target shape. Such overlaps greatly influence the total number of shots per plan, making pre-determination of the total number of shots impractical. However, this total number of shots usually defines the search space, a pre-requisite for most of the optimization methods. Since each shot only covers part of the target, a collection of shots in different locations and various collimator sizes selected makes up the global dose distribution that conforms to the target. Hence, planning or placing these shots is a combinatorial optimization process that is computationally expensive by nature. We have previously developed a theory of shot placement and optimization based on skeletonization. The real-time inverse planning process, reported in this paper, is an expansion and the clinical implementation of this theory. The complete planning process consists of two steps. The first step is to determine an optimal number of shots including locations and sizes and to assign initial collimator size to each of the shots. The second step is to fine-tune the weights using a linear-programming technique. The objective function is to minimize the total dose to the target boundary (i.e., maximize the dose conformity). Results of an ellipsoid test target and ten clinical cases are presented. The clinical cases are also compared with physician's manual plans. The target coverage is more than 99% for manual plans and 97% for all the inverse plans. The RTOG PITV conformity indices for the manual plans are between 1.16 and 3.46, compared to 1.36 to 2.4 for the inverse plans. All the inverse plans are generated in less than 2 min, making real-time inverse planning a reality.
Artificial neural networks for short-term energy forecasting: Accuracy and economic value
Neurocomputing, Jan 1, 1998
... Benjamin F. Hobbs a , * , Udi Helman a , Suradet Jitprapaikulsarn b , Sreenivas Konda b and D... more ... Benjamin F. Hobbs a , * , Udi Helman a , Suradet Jitprapaikulsarn b , Sreenivas Konda b and Dominic Maratukulam c. ... in Bangkok. Sreenivas Konda is a Ph.D. student in the CWRU Department of Electrical, Systems, Computer Engineering & Science. ...
Analysis of the value for unit commitment of improved load forecasts
Power Systems, …, Jan 1, 1999
... Dept. of Geography & Sreenivas Konda, Energy Delivery and Utilization... more ... Dept. of Geography & Sreenivas Konda, Energy Delivery and Utilization Division Electric Power Research institute Palo Alto, CA 94303 Environmental Engineering Vira Chankong, The Johns Hopkins University Baltimore, MD 21218 Kenneth A. Loparo Dept. ...
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Papers by Suradet Jitprapaikulsarn