Software Defined Wireless Sensor Networks (SDWSN) is emerged to overcome the additional energy consumption in WSN. Even then the sensor nodes in the SDWSN suffer from scarce battery resources. Generally, the Radio Frequency (RF) transmitters are deployed around the base station in the SDWSN to overcome the high energy consumption problem. To enhance harvesting energy and coverage of nodes in the network, a new energy harvesting technique using RF transmitters with Multiple Input and Single Output (MISO) beamforming is proposed. In this method, multiple antenna RF transmitters and single antenna sensor nodes are deployed. The optimization problem subject to Signal to Noise Ratio (SNR) and energy harvesting constraints is formulated for hybrid beamforming design to reduce the transmit power in the network. The optimization problem based on convex Second Order Cone Programming (SOCP) is derived to get the optimal solution for hybrid beamforming design. The beamforming technique is used to steer the beam in the desired direction and null to the other direction improves the energy harvesting. The simulation results show that the proposed technique provides better average harvesting energy, average transmit power, average residual energy and throughput than the existing RF transmitter based energy harvesting methods.
{"title":"A Novel Energy Efficient Harvesting Technique for SDWSN using RF Transmitters with MISO Beamforming","authors":"Subaselvi Sundarraj, Gunaseelan Konganathan","doi":"10.34028/iajit/20/1/13","DOIUrl":"https://doi.org/10.34028/iajit/20/1/13","url":null,"abstract":"Software Defined Wireless Sensor Networks (SDWSN) is emerged to overcome the additional energy consumption in WSN. Even then the sensor nodes in the SDWSN suffer from scarce battery resources. Generally, the Radio Frequency (RF) transmitters are deployed around the base station in the SDWSN to overcome the high energy consumption problem. To enhance harvesting energy and coverage of nodes in the network, a new energy harvesting technique using RF transmitters with Multiple Input and Single Output (MISO) beamforming is proposed. In this method, multiple antenna RF transmitters and single antenna sensor nodes are deployed. The optimization problem subject to Signal to Noise Ratio (SNR) and energy harvesting constraints is formulated for hybrid beamforming design to reduce the transmit power in the network. The optimization problem based on convex Second Order Cone Programming (SOCP) is derived to get the optimal solution for hybrid beamforming design. The beamforming technique is used to steer the beam in the desired direction and null to the other direction improves the energy harvesting. The simulation results show that the proposed technique provides better average harvesting energy, average transmit power, average residual energy and throughput than the existing RF transmitter based energy harvesting methods.","PeriodicalId":13624,"journal":{"name":"Int. Arab J. Inf. Technol.","volume":"167 ","pages":"125-133"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72555248","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In recent years, the quantities and types of malwares have grown explosively, which bring many challenges to identify and detect them. In order to improve the identification efficiency of malicious code, a malicious code feature representation method based on feature dimension reduction is proposed. By fusing the Gini impurity increment and the Improved Term Frequency-Inverse Document Frequency algorithm (ITF-IDF), ΔGini-Improving Term frequency inverse document frequency (ΔGini-ITFIDF) method is presented, which can get more valuable assembly instruction features for family detection. ΔGini-ITFIDF standardizes the assembly instructions of the PE disassembly files, then, measures the two indicators of the expected error rate increment and weight of the malicious code assembly instruction features, and obtains more valuable features to identify malicious codes. The experimental results show that the classification accuracy of the ITF-IDF algorithm is significantly improved compared with the ITF-IDF algorithm. At the same time, ΔGini-ITFIDF can effectively improve the classification performance.
{"title":"A method of extracting malware features based on gini impurity increment and improved TF-IDF","authors":"Shimiao Sun, Yashu Liu","doi":"10.34028/iajit/20/3/14","DOIUrl":"https://doi.org/10.34028/iajit/20/3/14","url":null,"abstract":"In recent years, the quantities and types of malwares have grown explosively, which bring many challenges to identify and detect them. In order to improve the identification efficiency of malicious code, a malicious code feature representation method based on feature dimension reduction is proposed. By fusing the Gini impurity increment and the Improved Term Frequency-Inverse Document Frequency algorithm (ITF-IDF), ΔGini-Improving Term frequency inverse document frequency (ΔGini-ITFIDF) method is presented, which can get more valuable assembly instruction features for family detection. ΔGini-ITFIDF standardizes the assembly instructions of the PE disassembly files, then, measures the two indicators of the expected error rate increment and weight of the malicious code assembly instruction features, and obtains more valuable features to identify malicious codes. The experimental results show that the classification accuracy of the ITF-IDF algorithm is significantly improved compared with the ITF-IDF algorithm. At the same time, ΔGini-ITFIDF can effectively improve the classification performance.","PeriodicalId":13624,"journal":{"name":"Int. Arab J. Inf. Technol.","volume":"48 1","pages":"419-427"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75584257","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In recent years, digital news has become increasingly prevalent, with many people getting their news and information from online sources rather than traditional print or broadcast media. This shift has been driven, in part, by the convenience and accessibility of digital platforms, as well as the ability to personalize and customize news feeds. Digital news also allows for greater interactivity and engagement with readers and can reach a global audience almost instantly. News articles contain a plethora of hidden spatial information that, when shared with readers, increases comprehension of current events. Only a few news aggregation systems make this information available to users. Many stories, on the other hand, are not clearly geotagged with their spatial information. In this work, we propose the MapNews framework, a novel system that gathers, analyzes, and presents news articles on a map interface, allowing users to take advantage of their underlying spatial information. MapNews pulls content from several different internet news sources and, using a custom-built geotagger, it extracts geographic content from articles. A rapid online clustering method is used to organize articles into story clusters. Panning and zooming MapNews' map interface allows readers to receive news based on geographic location and category importance, and they will view distinct articles depending on their location. MapNews achieved an ARI score of 0.89 for clustering and an accuracy of 95% in usability testing
{"title":"MAPNEWS: a framework for aggregating and organizing online news articles","authors":"Jeelani Ahmed, Muqeem Ahmed","doi":"10.34028/iajit/20/3/10","DOIUrl":"https://doi.org/10.34028/iajit/20/3/10","url":null,"abstract":"In recent years, digital news has become increasingly prevalent, with many people getting their news and information from online sources rather than traditional print or broadcast media. This shift has been driven, in part, by the convenience and accessibility of digital platforms, as well as the ability to personalize and customize news feeds. Digital news also allows for greater interactivity and engagement with readers and can reach a global audience almost instantly. News articles contain a plethora of hidden spatial information that, when shared with readers, increases comprehension of current events. Only a few news aggregation systems make this information available to users. Many stories, on the other hand, are not clearly geotagged with their spatial information. In this work, we propose the MapNews framework, a novel system that gathers, analyzes, and presents news articles on a map interface, allowing users to take advantage of their underlying spatial information. MapNews pulls content from several different internet news sources and, using a custom-built geotagger, it extracts geographic content from articles. A rapid online clustering method is used to organize articles into story clusters. Panning and zooming MapNews' map interface allows readers to receive news based on geographic location and category importance, and they will view distinct articles depending on their location. MapNews achieved an ARI score of 0.89 for clustering and an accuracy of 95% in usability testing","PeriodicalId":13624,"journal":{"name":"Int. Arab J. Inf. Technol.","volume":"26 1","pages":"376-386"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72976373","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Motion estimation and motion compensation are the accepted process in H.264 and H.265 video coding standard to reduce temporal redundancy. Several fast block matching algorithms have been developed to reduce the calculation cost in the motion estimation process. But quick block matching algorithms often lead to a local minimum. Several researchers used different population-based nature-inspired algorithms to perform block matching. Algorithms like genetic algorithm, differential evolution, particle swarm optimization were used in numerous motion estimation algorithms. Different algorithms used a fitness approximation strategy to reduce computation cost. Jaya algorithm-based block matching is the most efficient block matching algorithm in the available literature. Jaya algorithm is free from algorithmic specific parameter which speeds up the process. This article proposes a few modifications to the traditional cuckoo search algorithm and then, a block matching algorithm was proposed based on the modified cuckoo search algorithm. Fitness approximation, adaptive termination, and zero motion prejudgment modules were used with the modified cuckoo search algorithm to reduce the number of redundant calculations. The performance of the proposed algorithm was compared with the exhaustive search algorithm and other benchmarking algorithms in terms of Peak Signal to Noise Ratio (PSNR), Structure Similarity Index (SSIM), and average search point required to calculate a motion vector for a block. The proposed algorithm delivers better performance compared to the benchmarking algorithms.
{"title":"Modified cuckoo search algorithm for motion vector estimation","authors":"S. Acharjee, S. S. Chaudhuri","doi":"10.34028/iajit/20/3/6","DOIUrl":"https://doi.org/10.34028/iajit/20/3/6","url":null,"abstract":"Motion estimation and motion compensation are the accepted process in H.264 and H.265 video coding standard to reduce temporal redundancy. Several fast block matching algorithms have been developed to reduce the calculation cost in the motion estimation process. But quick block matching algorithms often lead to a local minimum. Several researchers used different population-based nature-inspired algorithms to perform block matching. Algorithms like genetic algorithm, differential evolution, particle swarm optimization were used in numerous motion estimation algorithms. Different algorithms used a fitness approximation strategy to reduce computation cost. Jaya algorithm-based block matching is the most efficient block matching algorithm in the available literature. Jaya algorithm is free from algorithmic specific parameter which speeds up the process. This article proposes a few modifications to the traditional cuckoo search algorithm and then, a block matching algorithm was proposed based on the modified cuckoo search algorithm. Fitness approximation, adaptive termination, and zero motion prejudgment modules were used with the modified cuckoo search algorithm to reduce the number of redundant calculations. The performance of the proposed algorithm was compared with the exhaustive search algorithm and other benchmarking algorithms in terms of Peak Signal to Noise Ratio (PSNR), Structure Similarity Index (SSIM), and average search point required to calculate a motion vector for a block. The proposed algorithm delivers better performance compared to the benchmarking algorithms.","PeriodicalId":13624,"journal":{"name":"Int. Arab J. Inf. Technol.","volume":"13 1","pages":"340-348"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91247933","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In context of high speed broadband communication, 5G optical communication has become a most stimulating and motivating domain in research. Recent cellular network LTE (4G) will not be adequate and effective to fulfill the needs of higher data rate, higher bandwidth, low latency and Quality of service.To achieve the above requirements and to address the challenges 5G optical communication have major considerations, the incorporation of Dense Wavelength Division Multiplexing (DWDM), Millimeter wave (mm-wave) communication, eMBB to make efficient decisions.This article summarize the empowering technology for DWDM, mm-wave signal communication and enhanced Mobile Broadband uses 5G optical communication as an evolution from 4G-LTE communication amenities, with fast communications, good throughput and high capacity, it is a successful aspirant for the increasing broadband communications. Such empowering technology, focused mainly on improving the network structure and efficiency, involves producing the mm-wave broadband signal with easy and cost adequate systems. This paper gives a thorough review on developing and empowering advancements identified with optical communication framework that can meet the huge data rate request of broadband. The article further addresses the research gaps and outlines the important future research direction for enhancing communication using DWDM.
{"title":"Intensification and interpretation of performance in 5G adopting millimeter wave: a survey and future research direction","authors":"Nivethitha Vijayaraj, A. Sivasubramanian","doi":"10.34028/iajit/20/4/6","DOIUrl":"https://doi.org/10.34028/iajit/20/4/6","url":null,"abstract":"In context of high speed broadband communication, 5G optical communication has become a most stimulating and motivating domain in research. Recent cellular network LTE (4G) will not be adequate and effective to fulfill the needs of higher data rate, higher bandwidth, low latency and Quality of service.To achieve the above requirements and to address the challenges 5G optical communication have major considerations, the incorporation of Dense Wavelength Division Multiplexing (DWDM), Millimeter wave (mm-wave) communication, eMBB to make efficient decisions.This article summarize the empowering technology for DWDM, mm-wave signal communication and enhanced Mobile Broadband uses 5G optical communication as an evolution from 4G-LTE communication amenities, with fast communications, good throughput and high capacity, it is a successful aspirant for the increasing broadband communications. Such empowering technology, focused mainly on improving the network structure and efficiency, involves producing the mm-wave broadband signal with easy and cost adequate systems. This paper gives a thorough review on developing and empowering advancements identified with optical communication framework that can meet the huge data rate request of broadband. The article further addresses the research gaps and outlines the important future research direction for enhancing communication using DWDM.","PeriodicalId":13624,"journal":{"name":"Int. Arab J. Inf. Technol.","volume":"10 1","pages":"600-608"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84315059","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Using MCDM and FaaS in automating the eligibility of business rules in the decision-making process","authors":"Riadh Ghlala, Z. Aouina Kodia, L. B. Said","doi":"10.34028/iajit/20/2/9","DOIUrl":"https://doi.org/10.34028/iajit/20/2/9","url":null,"abstract":"","PeriodicalId":13624,"journal":{"name":"Int. Arab J. Inf. Technol.","volume":"36 1","pages":"224-233"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83955991","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Dhivya Samraj, Kuppuchamy Ramasamy, M. Karuppusamy
In this research, Particle Swarm Optimization (PSO) based image equalization is projected to enhance the contrast of different breast cancer images. Breast cancer is the highest and another important root of tumor disease in females worldwide. Mass and microcalcification clusters are a significant early signs of breast cancer. The mortality rate can effectively be decreased by early diagnosis and treatment. Most practical approach for the early detection and identification of breast cancer diseases is mammography. Mammographic images contaminated by noise usually involve image enhancement techniques to aid interpretation. Contrast enhancement is divided into two categories: development of direct contrast and enhancement of indirect contrast. Indirect contrast improvement is used in the image histogram update. Histogram Equalization (HE) is the modest enhancement of the indirect contrast approach usually used for contrast enhancement. The proposed method's average entropy is 5.3251 with the highest structural similarity index 0.99725. The best contrast improvement of this method is 1.0404 and PSNR is 46.3803. The MSE value is 2157.08. This paper recommends an innovative method of enhancing digital mammogram image contrast based on different histogram equalization approaches. The performance of the projected method has been related to other prevailing techniques using the parameters, namely, discrete entropy, contrast improvement index, structural similarity index measure, mean square error, and peak signal-to-noise ratio. Investigational findings indicate that the projected strategy is efficient and robust and shows better results than others.
{"title":"Evolutionary computing model for finding breast cancer masses using image enhancement procedures with artificial intelligent algorithms","authors":"Dhivya Samraj, Kuppuchamy Ramasamy, M. Karuppusamy","doi":"10.34028/iajit/20/4/10","DOIUrl":"https://doi.org/10.34028/iajit/20/4/10","url":null,"abstract":"In this research, Particle Swarm Optimization (PSO) based image equalization is projected to enhance the contrast of different breast cancer images. Breast cancer is the highest and another important root of tumor disease in females worldwide. Mass and microcalcification clusters are a significant early signs of breast cancer. The mortality rate can effectively be decreased by early diagnosis and treatment. Most practical approach for the early detection and identification of breast cancer diseases is mammography. Mammographic images contaminated by noise usually involve image enhancement techniques to aid interpretation. Contrast enhancement is divided into two categories: development of direct contrast and enhancement of indirect contrast. Indirect contrast improvement is used in the image histogram update. Histogram Equalization (HE) is the modest enhancement of the indirect contrast approach usually used for contrast enhancement. The proposed method's average entropy is 5.3251 with the highest structural similarity index 0.99725. The best contrast improvement of this method is 1.0404 and PSNR is 46.3803. The MSE value is 2157.08. This paper recommends an innovative method of enhancing digital mammogram image contrast based on different histogram equalization approaches. The performance of the projected method has been related to other prevailing techniques using the parameters, namely, discrete entropy, contrast improvement index, structural similarity index measure, mean square error, and peak signal-to-noise ratio. Investigational findings indicate that the projected strategy is efficient and robust and shows better results than others.","PeriodicalId":13624,"journal":{"name":"Int. Arab J. Inf. Technol.","volume":"31 1","pages":"632-643"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89416417","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The main purpose of the classification of fingerprints is to devise a formula by which a given collection of fingerprints can be tracked and registered. To accelerate the system for classifying fingerprints, it is necessary to utilize fingerprint image characteristics and avoid the different fingerprint forms arising from fingerprint rotation. This paper presents a simple, new approach to the extraction of characteristics from fingerprint images. The proposed method demonstrates that, for a given image, the features remain constant even after being subjected to a wide range of rotations; thus, it creates an array of characteristics which can be used to identify a person from their fingerprint. To achieve this goal, a basic hit-and-miss operation with different structural components is used to detect and count various features in the fingerprint picture; these features are directly identified based on the texture of the fingerprint. The chosen features are used to index the finger image by generating a frequency of occurrences for each one, such that every fingerprint is represented as a vector of these features. The application of the proposed method shows efficient utilization of execution time and memory usage.
{"title":"A simple and stable method of creating fingerprint features with image rotation","authors":"Mohamad M. Al-Laham, M. Al-Ma’aitah, Z. Alqadi","doi":"10.34028/iajit/20/4/15","DOIUrl":"https://doi.org/10.34028/iajit/20/4/15","url":null,"abstract":"The main purpose of the classification of fingerprints is to devise a formula by which a given collection of fingerprints can be tracked and registered. To accelerate the system for classifying fingerprints, it is necessary to utilize fingerprint image characteristics and avoid the different fingerprint forms arising from fingerprint rotation. This paper presents a simple, new approach to the extraction of characteristics from fingerprint images. The proposed method demonstrates that, for a given image, the features remain constant even after being subjected to a wide range of rotations; thus, it creates an array of characteristics which can be used to identify a person from their fingerprint. To achieve this goal, a basic hit-and-miss operation with different structural components is used to detect and count various features in the fingerprint picture; these features are directly identified based on the texture of the fingerprint. The chosen features are used to index the finger image by generating a frequency of occurrences for each one, such that every fingerprint is represented as a vector of these features. The application of the proposed method shows efficient utilization of execution time and memory usage.","PeriodicalId":13624,"journal":{"name":"Int. Arab J. Inf. Technol.","volume":"13 1","pages":"686-692"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86236963","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The Software industry’s rapid growth contributes to the need for new technologies. PRICE software system uses Predictive Object Point (POP) as a size measure to estimate Effort and cost. A refined POP metric value for object-oriented software written in Java can be calculated using the Automated POP Analysis tool. This research used 25 open-source Java projects. The refined POP metric improves the drawbacks of the PRICE system and gives a more accurate size measure of software. This paper uses refined POP metrics with curve-fitting neural networks and multi-layer perceptron neural network-based deep learning to estimate the software development effort. Results show that this approach gives an effort estimate closer to the actual Effort obtained through Constructive Cost Estimation Model (COCOMO) estimation models and thus validates refined POP as a better size measure of object-oriented software than POP. Therefore we consider the MLP approach to help construct the metric for the scale of the Object-Oriented (OO) model system.
{"title":"Estimation model for enhanced predictive object point metric in OO software size estimation using deep learning","authors":"Vijay Yadav, Raghuraj Singh, Vibhash Yadav","doi":"10.34028/iajit/20/3/1","DOIUrl":"https://doi.org/10.34028/iajit/20/3/1","url":null,"abstract":"The Software industry’s rapid growth contributes to the need for new technologies. PRICE software system uses Predictive Object Point (POP) as a size measure to estimate Effort and cost. A refined POP metric value for object-oriented software written in Java can be calculated using the Automated POP Analysis tool. This research used 25 open-source Java projects. The refined POP metric improves the drawbacks of the PRICE system and gives a more accurate size measure of software. This paper uses refined POP metrics with curve-fitting neural networks and multi-layer perceptron neural network-based deep learning to estimate the software development effort. Results show that this approach gives an effort estimate closer to the actual Effort obtained through Constructive Cost Estimation Model (COCOMO) estimation models and thus validates refined POP as a better size measure of object-oriented software than POP. Therefore we consider the MLP approach to help construct the metric for the scale of the Object-Oriented (OO) model system.","PeriodicalId":13624,"journal":{"name":"Int. Arab J. Inf. Technol.","volume":"14 1","pages":"293-302"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74849673","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A Rule-Induction Approach for Building an Arabic Language Interfaces to Databases","authors":"Hanane Bais, M. Machkour","doi":"10.34028/iajit/20/1/6","DOIUrl":"https://doi.org/10.34028/iajit/20/1/6","url":null,"abstract":"","PeriodicalId":13624,"journal":{"name":"Int. Arab J. Inf. Technol.","volume":"19 1","pages":"49-56"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80773866","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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