Searched for: author%3A%22Al-Ars%2C+Z.%22
(1 - 20 of 76)

Pages

document
Mokveld, T.O. (author), Al-Ars, Z. (author), Sistermans, Erik A. (author), Reinders, M.J.T. (author)
Background<br/><br/>Non-Invasive Prenatal Testing is often performed by utilizing read coverage-based profiles obtained from shallow whole genome sequencing to detect fetal copy number variations. Such screening typically operates on a discretized binned representation of the genome, where (ab)normality of bins of a set size is judged relative...
journal article 2023
document
Hesam, A.S. (author), Pijpers, Frank (author), Rademakers, Fons (author), Al-Ars, Z. (author)
poster 2023
document
Tian, Yongding (author), Guo, Zhuoran (author), Zhang, Jiaxuan (author), Al-Ars, Z. (author)
Many researchers have proposed replacing the aggregation server in federated learning with a blockchain system to improve privacy, robustness, and scalability. In this approach, clients would upload their updated models to the blockchain ledger and use a smart contract to perform model averaging. However, the significant delay and limited...
journal article 2023
document
Cromjongh, Casper (author), Tian, Y. (author), Hofstee, H.P. (author), Al-Ars, Z. (author)
In spite of progress on hardware design languages, the design of high-performance hardware accelerators forces many design decisions specializing the interfaces of these accelerators in ways that complicate the understanding of the design and hinder modularity and collaboration. In response to this challenge, Tydi is presented as an open...
conference paper 2023
document
Al-Ars, Z. (author), Agba, Obinna (author), Guo, Zhuoran (author), Boerkamp, C. (author), Jaber, Ziyaad (author), Jaber, Tareq (author)
This paper offers a systematic method for creating medical knowledge-grounded patient records for use in activities involving differential diagnosis. Additionally, an assessment of machine learning models that can differentiate between various conditions based on given symptoms is also provided. We use a public disease-symptom data source called...
conference paper 2023
document
Sarkar, A. (author), Al-Ars, Z. (author), Bertels, K.L.M. (author)
In this research, we extend the universal reinforcement learning agent models of artificial general intelligence to quantum environments. The utility function of a classical exploratory stochastic Knowledge Seeking Agent, KL-KSA, is generalized to distance measures from quantum information theory on density matrices. Quantum process...
conference paper 2023
document
Trentin, Vinicius (author), Ma, Chenxu (author), Villagra, Jorge (author), Al-Ars, Z. (author)
Motion prediction is a key factor towards the full deployment of autonomous vehicles. It is fundamental in order to assure safety while navigating through highly interactive complex scenarios. In this work, the framework IAMP (Interaction-Aware Motion Prediction), producing multi-modal probabilistic outputs from the integration of a Dynamic...
conference paper 2023
document
Reukers, Matthijs A. (author), Tian, Y. (author), Al-Ars, Z. (author), Hofstee, H.P. (author), Brobbel, M. (author), Peltenburg, J.W. (author), van Straten, J. (author)
Tydi is an open specification for streaming dataflow designs in digital circuits, allowing designers to express how composite and variable-length data structures are transferred over streams using clear, data-centric types. These data types are extensively used in a many application domains, such as big data and SQL applications. This way,...
journal article 2023
document
Ji, M. (author), Al-Ars, Z. (author), Hofstee, H.P. (author), Chang, Yuchun (author), Zhang, Baolin (author)
Convolutional neural networks (CNNs) are to be effective in many application domains, especially in the computer vision area. In order to achieve lower latency CNN processing, and reduce power consumption, developers are experimenting with using FPGAs to accelerate CNN processing in several applications. Current FPGA CNN accelerators usually use...
journal article 2023
document
Mokveld, T.O. (author), Al-Ars, Z. (author), Sistermans, Erik A. (author), Reinders, M.J.T. (author)
In prenatal diagnostics, NIPT screening utilizing read coverage-based profiles obtained from shallow WGS data is routinely used to detect fetal CNVs. From this same data, fragment size distributions of fetal and maternal DNA fragments can be derived, which are known to be different, and often used to infer fetal fractions. We argue that the...
journal article 2022
document
Krol, A.M. (author), Sarkar, A. (author), Ashraf, I. (author), Al-Ars, Z. (author), Bertels, K.L.M. (author)
Unitary decomposition is a widely used method to map quantum algorithms to an arbitrary set of quantum gates. Efficient implementation of this decomposition allows for the translation of bigger unitary gates into elementary quantum operations, which is key to executing these algorithms on existing quantum computers. The decomposition can be used...
journal article 2022
document
Arvanitis, P. (author), Betting, Jan Harm L.F. (author), Bosman, Laurens W.J. (author), Al-Ars, Z. (author), Strydis, C. (author)
Mice and rats can rapidly move their whiskers when exploring the environment. Accurate description of these movements is important for behavioral studies in neuroscience. Whisker tracking is, however, a notoriously difficult task due to the fast movements and frequent crossings and juxtapositionings among whiskers. We have recently developed...
conference paper 2022
document
Park, Seongyeon (author), Kim, Hajin (author), Ahmad, T. (author), Ahmed, N. (author), Al-Ars, Z. (author), Hofstee, H.P. (author), Kim, Youngsok (author), Lee, Jinho (author)
Sequence alignment forms an important backbone in many sequencing applications. A commonly used strategy for sequence alignment is an approximate string matching with a two-dimensional dynamic programming approach. Although some prior work has been conducted on GPU acceleration of a sequence alignment, we identify several shortcomings that limit...
conference paper 2022
document
Breitwieser, Lukas (author), Hesam, A.S. (author), De Montigny, Jean (author), Vavourakis, Vasileios (author), Iosif, Alexandros (author), Jennings, Jack (author), Kaiser, Marcus (author), Manca, Marco (author), Di Meglio, Alberto (author), Al-Ars, Z. (author), Rademakers, Fons (author), Mutlu, Onur (author), Bauer, Roman (author)
Motivation: Agent-based modeling is an indispensable tool for studying complex biological systems. However, existing simulation platforms do not always take full advantage of modern hardware and often have a field-specific software design. Results: We present a novel simulation platform called BioDynaMo that alleviates both of these problems....
journal article 2022
document
Abrahamse, Robin (author), Hadnagy, A. (author), Al-Ars, Z. (author)
The concept of memory disaggregation has recently been gaining traction in research. With memory disaggregation, data center compute nodes can directly access memory on adjacent nodes and are therefore able to overcome local memory restrictions, introducing a new data management paradigm for distributed computing. This paper proposes and...
conference paper 2022
document
Ahmad, T. (author), Al-Ars, Z. (author), Hofstee, H.P. (author)
Moving structured data between different big data frameworks and/or data warehouses/storage systems often cause significant overhead. Most of the time more than 80% of the total time spent in accessing data is elapsed in serialization/de-serialization step. Columnar data formats are gaining popularity in both analytics and transactional...
conference paper 2022
document
Ahmad, T. (author), Ma, Chengxin (author), Al-Ars, Z. (author), Hofstee, H.P. (author)
Current cluster scaled genomics data processing solutions rely on big data frameworks like Apache Spark, Hadoop and HDFS for data scheduling, processing and storage. These frameworks come with additional computation and memory overheads by default. It has been observed that scaling genomics dataset processing beyond 32 nodes is not efficient on...
conference paper 2022
document
Ahmad, T. (author), Al-Ars, Z. (author), Hofstee, H.P. (author)
Background Recently many new deep learning–based variant-calling methods like DeepVariant have emerged as more accurate compared with conventional variant-calling algorithms such as GATK HaplotypeCaller, Sterlka2, and Freebayes albeit at higher computational costs. Therefore, there is a need for more scalable and higher performance workflows of...
review 2021
document
Sarkar, A. (author), Al-Ars, Z. (author), Almudever, Carmen G. (author), Bertels, K.L.M. (author)
With small-scale quantum processors transitioning from experimental physics labs to industrial products, these processors in a few years are expected to scale up and be more robust for efficiently computing important algorithms in various fields. In this paper, we propose a quantum algorithm to address the challenging field of data processing...
journal article 2021
document
Peltenburg, J.W. (author), van Straten, J. (author), Brobbel, M. (author), Al-Ars, Z. (author), Hofstee, H.P. (author)
As big data analytics systems are squeezing out the last bits of performance of CPUs and GPUs, the next near-term and widely available alternative industry is considering for higher performance in the data center and cloud is the FPGA accelerator. We discuss several challenges a developer has to face when designing and integrating FPGA...
journal article 2021
Searched for: author%3A%22Al-Ars%2C+Z.%22
(1 - 20 of 76)

Pages