Offensive Hebrew Corpus and Detection using BERT

Offensive language detection has been well studied in many languages, but it is lagging behind in low-resource languages, such as Hebrew. In this paper, we present a new offensive language corpus in Hebrew. A total of 15,881 tweets were retrieved from Twitter. Each was labeled with one or more of five classes (abusive, hate, violence, pornographic, or none offensive) by Arabic-Hebrew bilingual speakers. The annotation process was challenging as each annotator is expected to be familiar with the Israeli culture, politics, and practices to understand the context of each tweet. We fine-tuned two Hebrew BERT models, HeBERT and AlephBERT, using our proposed dataset and another published dataset. We observed that our data boosts HeBERT performance by 2% when combined with D_OLaH. Fine-tuning AlephBERT on our data and testing on D_OLaH yields 69% accuracy, while fine-tuning on D_OLaH and testing on our data yields 57% accuracy, which may be an indication to the generalizability our data offers. Our dataset and fine-tuned models are available on GitHub and Huggingface.Comment: 8 pages, 1 figure, The 20th ACS/IEEE International Conference on Computer Systems and Applications (AICCSA

Predicting the Strength of Fiber Reinforced High Performance Concrete Based on Push-Off Tests

This paper reports the results of an investigation into the strength of fiber reinforced high-performance concrete (FRHPC)based on push-off tests. Both experimental and analytical studies were performed. In the experimental study, eight FRHPC push-off specimens were tested. Two types of fibers, straight and hooked-end, in conjunction with percentage of volume fraction of steel fibers,0.5%, 1.0%, 1.5% and 2.0% were used. In the analytical study, a new proposed expression was derived based on experimental data in this research and available data from the literature. These include high strength concrete (HSC) with compressive strength of 40 < f'c < 107 MPa. The investigated variables were, fibers factor (F), area of reinforcement perpendicular to shear plane (ρvfy), and concrete compressive strength (f'c). The proposed expression gave good prediction for the direct shear strength of the tested specimens-the proposed expression predicted the direct shear stress resistance of tested/calculated values with a coefficient of variation (COV) of 12.88 percent

WojoodNER 2023: The First Arabic Named Entity Recognition Shared Task

We present WojoodNER-2023, the first Arabic Named Entity Recognition (NER) Shared Task. The primary focus of WojoodNER-2023 is on Arabic NER, offering novel NER datasets (i.e., Wojood) and the definition of subtasks designed to facilitate meaningful comparisons between different NER approaches. WojoodNER-2023 encompassed two Subtasks: FlatNER and NestedNER. A total of 45 unique teams registered for this shared task, with 11 of them actively participating in the test phase. Specifically, 11 teams participated in FlatNER, while $8$ teams tackled NestedNER. The winning teams achieved F1 scores of 91.96 and 93.73 in FlatNER and NestedNER, respectively

NTRU-Like Random Congruential Public-Key Cryptosystem for Wireless Sensor Networks

Wireless sensor networks (WSNs) are the core of the Internet of Things and require cryptographic protection. Cryptographic methods for WSN should be fast and consume low power as these networks rely on battery-powered devices and microcontrollers. NTRU, the fastest and secure public key cryptosystem, uses high degree, N, polynomials and is susceptible to the lattice basis reduction attack (LBRA). Congruential public key cryptosystem (CPKC), proposed by the NTRU authors, works on integers modulo q and is easily attackable by LBRA since it uses small numbers for the sake of the correct decryption. Herein, RCPKC, a random congruential public key cryptosystem working on degree N=0 polynomials modulo q, is proposed, such that the norm of a two-dimensional vector formed by its private key is greater than q. RCPKC works as NTRU, and it is a secure version of insecure CPKC. RCPKC specifies a range from which the random numbers shall be selected, and it provides correct decryption for valid users and incorrect decryption for an attacker using LBRA by Gaussian lattice reduction. RCPKC asymmetric encryption padding (RAEP), similar to its NTRU analog, NAEP, is IND-CCA2 secure. Due to the use of big numbers instead of high degree polynomials, RCPKC is about 27 times faster in encryption and decryption than NTRU. Furthermore, RCPKC is more than three times faster than the most effective known NTRU variant, BQTRU. Compared to NTRU, RCPKC reduces energy consumption at least thirty times, which allows increasing the life-time of unattended WSNs more than thirty times

الأشجار والشجيرات المتزاجدة في الحرم الرئيس للجامعة الإسلامية بغزة، قطاع غزة، فلسطين

The Gaza Strip, which has a population of about 2.0 million and an area of about 365 km2, has many higher education institutions. The green quadrates, corridors and gardens of these institutions are commonly cultivated with many horticultural plants including trees and shrubs that provide many environmental, health, and aesthetic values. The Palestinian universities of the Gaza Strip have never been studied for the composition and numbers of their trees and shrubs. Therefore, the current study aims at identifying and recording the trees and shrubs prevailing and enhancing the ecology and environmental health aspects of the main campus of the Islamic University of Gaza (MC-IUG). Frequent surveys and observations were carried out during a six-month study extended from February, 2018 to July, 2018 in order to identify and totally count the trees and shrubs existing at MC-IUG. A total number of 2248 trees and shrubs belonging to 53 species, 25 families and 16 orders were identified and recorded at the MC-IUG. The Gymnosperms included 5 species (9.43%) only, while the Angiosperms was represented by 48 species (90.57%), of which the monocots were 9 species (16.98%) and the dicots were 39 species (73.59%). Rosales was the biggest order and comprised 9 (16.98%) of the recorded species. It was followed by Lamiales and Myrtales which comprised 5 (9.43%) for each. The orders Pinales, Arecales, Asparagales and Malpighiales were represented by 4 species (7.55%) for each. Moraceae was the biggest family and comprised 8 (15.09%) of the recorded species. It was followed by the two families Arecaceae and Asparagaceae, which comprised 5 species (9.43% for each). Six tree and shrub species (11.32%) of MC-IUG were found to exceed the threshold of 100 individuals for each. These comprised 1657 individuals (73.71%) of the 2248 counted. The Chinese Hibiscus (Hibiscus rosa-sinensis) was, by far, the most common species. It comprised 31.98% of the individuals counted. This was followed by the Benjamin Fig (Ficus benjamina) (10.45%), Hopbush (Dodonea viscose) and Moringa (Moringa oleifera) (8.63% for each), Dwarf Umbrella Tree (Schefflera arboricola) (8.19%) and Weeping Fig (Ficus nitida) (5.82%). The majority of tree and shrub species 49 (92.45%) recoded in the current study are exotic, while the native ones are restricted to only 4 species (7.55%). Finally, the current study recommends the selection of tree and shrub species corresponding with the local prevailing environmental conditions in order to ensure the ecological and environmental health values needed by the university community.The Gaza Strip, which has a population of about 2.0 million and an area of about 365 km2, has many higher education institutions. The green quadrates, corridors and gardens of these institutions are commonly cultivated with many horticultural plants including trees and shrubs that provide many environmental, health, and aesthetic values. The Palestinian universities of the Gaza Strip have never been studied for the composition and numbers of their trees and shrubs. Therefore, the current study aims at identifying and recording the trees and shrubs prevailing and enhancing the ecology and environmental health aspects of the main campus of the Islamic University of Gaza (MC-IUG). Frequent surveys and observations were carried out during a six-month study extended from February, 2018 to July, 2018 in order to identify and totally count the trees and shrubs existing at MC-IUG. A total number of 2248 trees and shrubs belonging to 53 species, 25 families and 16 orders were identified and recorded at the MC-IUG. The Gymnosperms included 5 species (9.43%) only, while the Angiosperms was represented by 48 species (90.57%), of which the monocots were 9 species (16.98%) and the dicots were 39 species (73.59%). Rosales was the biggest order and comprised 9 (16.98%) of the recorded species. It was followed by Lamiales and Myrtales which comprised 5 (9.43%) for each. The orders Pinales, Arecales, Asparagales and Malpighiales were represented by 4 species (7.55%) for each. Moraceae was the biggest family and comprised 8 (15.09%) of the recorded species. It was followed by the two families Arecaceae and Asparagaceae, which comprised 5 species (9.43% for each). Six tree and shrub species (11.32%) of MC-IUG were found to exceed the threshold of 100 individuals for each. These comprised 1657 individuals (73.71%) of the 2248 counted. The Chinese Hibiscus (Hibiscus rosa-sinensis) was, by far, the most common species. It comprised 31.98% of the individuals counted. This was followed by the Benjamin Fig (Ficus benjamina) (10.45%), Hopbush (Dodonea viscose) and Moringa (Moringa oleifera) (8.63% for each), Dwarf Umbrella Tree (Schefflera arboricola) (8.19%) and Weeping Fig (Ficus nitida) (5.82%). The majority of tree and shrub species 49 (92.45%) recoded in the current study are exotic, while the native ones are restricted to only 4 species (7.55%). Finally, the current study recommends the selection of tree and shrub species corresponding with the local prevailing environmental conditions in order to ensure the ecological and environmental health values needed by the university community