Significant increases in the volume of big spatial data have driven researchers and practitioners to build specialized systems to process and analyze this data. Existing efforts focus on either big raster data, e.g., ...
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This paper reports the results for a senior-freshman teaming event that took place during the fall quarter 2004. It describes the rational for the event, the design leadership required of the seniors, the structure of...
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This paper reports the results for a senior-freshman teaming event that took place during the fall quarter 2004. It describes the rational for the event, the design leadership required of the seniors, the structure of the design environment, project reports, student reactions, and the event evaluations. This is the second year that our biomedical engineering seniors have been coupled with our engineering and computerscience freshmen on a joint design project. The first year results were promising enough to continue doing it the second year. The second year had improved expectations for the seniors coupled with more time to interact with the freshmen. Seniors gained valuable experience leading a design team while the freshmen gained experience teaming and interacting with upperclassmen. This event was possible as the director of the freshman engineering and computerscienceprogram was also the professor for the initial course in BME senior design. Over all this has been a win-win effort.
Identifying novel drugs that can interact with target proteins is a highly challenging, time-consuming, and costly task in drug discovery and development. Numerous machine learning-based models have recently been util...
Identifying novel drugs that can interact with target proteins is a highly challenging, time-consuming, and costly task in drug discovery and development. Numerous machine learning-based models have recently been utilized to accelerate the drug discovery process. However, these existing methods are primarily uni-tasking, either designed to predict drug-target interaction (DTI) or generate new drugs. Through the lens of pharmacological research, these tasks are intrinsically interconnected and play a critical role in effective drug development. Therefore, the learning models must be utilized in such a manner to learn the structural properties of drug molecules, the conformational dynamics of proteins, and the bioactivity between drugs and targets. To this end, this paper develops a novel multitask learning framework that can predict drug-target binding affinities and simultaneously generate new target-aware drug variants, using common features for both tasks. In addition, we developed the FetterGrad algorithm to address the optimization challenges associated with multitask learning particularly those caused by gradient conflicts between distinct tasks. Comprehensive experiments on three real-world datasets demonstrate that the proposed model provides an effective mechanism for predicting drug-target binding affinities and generating novel drugs, thus greatly facilitating the drug discovery process.
This work introduces a two-dimensional modal logic to represent agents' Concurrent Common Knowledge in distributed systems. Unlike Common Knowledge, Concurrent Common Knowledge is a kind of agreement reachable in ...
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In the United States, more than 10% of traditional electrical engineeringprograms have combined with computerscience into a single department \Historically computerscienceprograms emerged from mathematics or elect...
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Network security is a crucial component of Information Technology, yet organizations continue to grapple with meeting established security benchmarks. Given the rise in cyber-attacks and the continuous emergence of ne...
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作者:
Rabiha, Suciana GhadatiWibowo, AntoniLukasHeryadi, YayaComputer Science Department
BINUS Graduate Program-Doctor of Computer Science. Information Systems Department BINUS Online Learning Bina Nusantara University Jakarta11480 Indonesia Computer Science Department
BINUS Graduate Program-Doctor of Computer Science Bina Nusantara University 11480 Indonesia
Faculty of Engineering Universitas Katolik Indonesia Atma Jaya Indonesia Computer Science Department
BINUS Graduate Program - Doctor of Computer Science Bina Nusantara University 11480 Indonesia
One of the health problems that require special attention is diabetes, besides the growth of this disease infection is increasing in various circles ranging from children, adults, men, women and the elderly. So to det...
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Currently, online Shopping platforms have grown significantly, especially during the COVID-19 pandemic. This condition motivates the need for analyzing how the users/customers' opinions on using such platform. Sen...
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Graphs are among the most frequently used structures in computerscience. Some of the properties that must be checked in many applications are connectivity, acyclicity and the Eulerian and Hamiltonian properties. In t...
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This paper proposes an efficient method to implement RSA decryption algorithm. RSA cryptosystem is the most attractive and popular security technique for many applications, such as electronic commerce and secure inter...
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