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ـه1445 رفــــس� ددـــــ ـــــعلا Forum 16
م2023 س�طس�غأا
Recently, in July 2023, the researchers from the Security Engineering PSU's Research Achievements for the Second
Lab (SEL) at Prince Sultan university has been awarded the “Copyright
Registration Certificate” for the software ASParse –V3 (Auto Static Quarter of 2023
Parsing Tool- Version 3) from the Saudi Authority for Intellectual
Property (SAIP).
The authors of ASParse –V3 are Dr. Iman Almomani, Eng. Rahaf
Alkhadra, Eng. Muhannad Qasem, Eng. Tala Almashat and Dr. Walid
Elshafai.
ASParse-V3 is a GUI-based cross-platform static analysis tool. It
supports customization in the analysis process, where users can input
their files and customize the scanning features, such as keywords
and file types. The application also allows users to export the
scanning results and visualize them using the interactive dashboards.
ASParse-V3 can parse thoroughly any given file. This can be utilized
as a preprocessing step to extract features, apply static analysis,
generate datasets, and train machine learning models. In addition,
ASParse V3 offers features exportation of the scanning results to
different file formats, including JSON and CSV files. ASParseV3 is
developed to meet market requirements while improving traditional
static analysis application. ASParse-V3 is a better tool than others,
because it is cross-platform and portable in that it performs static
analysis and features parsing of different file systems for many
operating systems. In addition, this version of ASParse is efficient
and fast due to its use of concurrent scanning. ASParse-V3 can parse
any file type, extracting static features, efficient malware analysis,
constructing datasets of static features, and preprocessing datasets
for ML training. ASParse-V3 has many applications including,
Cybersecurity Desktop applications, File Parsing, Malware Static
Analysis, Features extractions, Datasets generation. RIC is pleased to share PSU's research achievements for the second quarter of 2023. Compared with data from the first quarter
The registration of these copyright works is an important milestone of 2023:
for the SEL Lab and Prince Sultan University. We would like to ● Scopus publications increased by 43.6% (555 in Q1 2023)
congratulate the team on their remarkable achievement! ● Active researchers increased by 20.8% (130 in Q1 2023)
First PSU Paper Accepted In CVPR
Researchers from Prince Sultan University have accomplished a
significant milestone in high-resolution image dehazing with their
latest CVPR2023 paper, "Streamlined Global and Local Features
Combinator (SGLC) for High-Resolution Image Dehazing," developed
by an outstanding team including Bilel Benjdira (Ph.D., SMIEEE),
Anas M. Ali, and Anis Koubaa.
The innovative SGLC approach from Prince Sultan University's
research team optimizes dehazing models using two consecutive
blocks, GFG and LFE, achieving significant improvements in the PSNR
metric and demonstrating adaptability with various architectures.
Read the paper:
https://lnkd.in/gxbtQZ3G
The researchers also secured a notable 5th position among 17
shortlisted participants in the fiercely competitive NTIRE Non-
Homogeneous Dehazing Challenge2023. This achievement
showcases the effectiveness of the SGLC model in tackling intricate
dehazing tasks and emphasizes the team's unwavering commitment
to advancing the field.