This paper introduces a new enhanced Arabic stemming algorithm for solving the information retrieval problem,especially in medical documents.Our proposed algorithm is a light stemming algorithm for extracting stems an...This paper introduces a new enhanced Arabic stemming algorithm for solving the information retrieval problem,especially in medical documents.Our proposed algorithm is a light stemming algorithm for extracting stems and roots from the input data.One of the main challenges facing the light stemming algorithm is cutting off the input word,to extract the initial segments.When initiating the light stemmer with strong initial segments,the final extracting stems and roots will be more accurate.Therefore,a new enhanced segmentation based on deploying the Direct Acyclic Graph(DAG)model is utilized.In addition to extracting the powerful initial segments,the main two procedures(i.e.,stems and roots extraction),should be also reinforced with more efficient operators to improve the final outputs.To validate the proposed enhanced stemmer,four data sets are used.The achieved stems and roots resulted from our proposed light stemmer are compared with the results obtained from five other well-known Arabic light stemmers using the same data sets.This evaluation process proved that the proposed enhanced stemmer outperformed other comparative stemmers.展开更多
Frozen state from jammed state is one of the most interesting aspects produced when simulating the multidirectional pedestrian flow of high density crowds. Cases of real life situations for such a phenomenon are not e...Frozen state from jammed state is one of the most interesting aspects produced when simulating the multidirectional pedestrian flow of high density crowds. Cases of real life situations for such a phenomenon are not exhaustively treated.Our observations in the Hajj crowd show that freezing transition does not occur very often. On the contrary, penetrating a jammed crowd is a common aspect. We believe the kindness of pedestrians facing others whose walking is blocked is a main factor in eliminating the frozen state as well as in relieving the jammed state. We refine the social force model by incorporating a new social force to enable the simulated pedestrians to mimic the real behavior observed in the Hajj area.Simulations are performed to validate the work qualitatively.展开更多
文摘This paper introduces a new enhanced Arabic stemming algorithm for solving the information retrieval problem,especially in medical documents.Our proposed algorithm is a light stemming algorithm for extracting stems and roots from the input data.One of the main challenges facing the light stemming algorithm is cutting off the input word,to extract the initial segments.When initiating the light stemmer with strong initial segments,the final extracting stems and roots will be more accurate.Therefore,a new enhanced segmentation based on deploying the Direct Acyclic Graph(DAG)model is utilized.In addition to extracting the powerful initial segments,the main two procedures(i.e.,stems and roots extraction),should be also reinforced with more efficient operators to improve the final outputs.To validate the proposed enhanced stemmer,four data sets are used.The achieved stems and roots resulted from our proposed light stemmer are compared with the results obtained from five other well-known Arabic light stemmers using the same data sets.This evaluation process proved that the proposed enhanced stemmer outperformed other comparative stemmers.
文摘Frozen state from jammed state is one of the most interesting aspects produced when simulating the multidirectional pedestrian flow of high density crowds. Cases of real life situations for such a phenomenon are not exhaustively treated.Our observations in the Hajj crowd show that freezing transition does not occur very often. On the contrary, penetrating a jammed crowd is a common aspect. We believe the kindness of pedestrians facing others whose walking is blocked is a main factor in eliminating the frozen state as well as in relieving the jammed state. We refine the social force model by incorporating a new social force to enable the simulated pedestrians to mimic the real behavior observed in the Hajj area.Simulations are performed to validate the work qualitatively.
