02502nas a2200145 4500008004100000245010000041210006900141260001200210300001100222490000700233520203100240100001802271700002102289856004602310 2024 eng d00aA Brief Review of the Automation of Dependency Satisfaction With in Microservices Architectures0 aBrief Review of the Automation of Dependency Satisfaction With i c09/2024 a99-1070 v223 a

Accelerated advances in network speed, re- liability, and security have increased the demand for soft- ware and services to move from being stored and pro- cessed locally on users’ devices to being managed by third parties that can be accessed through the network. This has led to the need to develop new software archi- tectures and software architectures that meet these new requirements. One example of software architecture is the recent emergence of a microservices architecture to meet online service providers’ maintenance and scalability requirements. Microservices is an architecture style that focuses on breaking down a system into small, lightweight services that are intentionally created to perform a highly cohesive business function, and it is an evolution of the traditional service-oriented architecture style. The practi- cal projection of microservices architecture in informa- tion engineering is several small applications that work together to provide an integrated service that appears to the external medium as a single application. Each of these applications has its own independent source code and deals with data sources that are different from the rest. As a result, it has an independent development team. Partial applications depend on each other to accomplish their functions, and therefore, any modification to one of the services will affect the work of the rest of the ser- vices; in large applications that require keeping the sys- tem always available, we must perform the process of publishing updates for parts of the system without stop- ping it completely, so we must monitor the impact of modi- fications and forecast system status before new updates are deployed. In achieving this prediction, we must know the dependencies between different services to arrive at a cognitive model representing the dependencies between services or applications.

1 aEsrawi, Ammar1 aAlkhatib, Bassel uhttps://10.0.23.137/jdim/2024/22/3/99-10702449nas a2200145 4500008004100000245005400041210005300095260001200148300001000160490000700170520203100177100001802208700002102226856005602247 2024 eng d00aCan ChatGPT Predict Stock Market Price Movements?0 aCan ChatGPT Predict Stock Market Price Movements c09/2024 a91-980 v223 a

Accelerated advances in network speed, re- liability, and security have increased the demand for soft- ware and services to move from being stored and pro- cessed locally on users’ devices to being managed by third parties that can be accessed through the network. This has led to the need to develop new software archi- tectures and software architectures that meet these new requirements. One example of software architecture is the recent emergence of a microservices architecture to meet online service providers’ maintenance and scalability requirements. Microservices is an architecture style that focuses on breaking down a system into small, lightweight services that are intentionally created to perform a highly cohesive business function, and it is an evolution of the traditional service-oriented architecture style. The practi- cal projection of microservices architecture in informa- tion engineering is several small applications that work together to provide an integrated service that appears to the external medium as a single application. Each of these applications has its own independent source code and deals with data sources that are different from the rest. As a result, it has an independent development team. Partial applications depend on each other to accomplish their functions, and therefore, any modification to one of the services will affect the work of the rest of the ser- vices; in large applications that require keeping the sys- tem always available, we must perform the process of publishing updates for parts of the system without stop- ping it completely, so we must monitor the impact of modi- fications and forecast system status before new updates are deployed. In achieving this prediction, we must know the dependencies between different services to arrive at a cognitive model representing the dependencies between services or applications.

1 aEsrawi, Ammar1 aAlkhatib, Bassel uhttp://www.dline.info/jdim/wp-content/uploads/2.pdf01594nas a2200145 4500008004100000245006900041210006700110260001200177300001000189490000700199520114200206100002101348700003201369856004701401 2023 eng d00aASR Features Extraction Using MFCC And LPC: A Comparative Study-0 aASR Features Extraction Using MFCC And LPC A Comparative Study c06/2023 a39-490 v213 a

The field of Automatic Speaker Recognition (ASR) is an important and open field for researchers and scientists, especially as it has become essential in facilitating the work we do in our daily lives. Such as digital authentication and electronic transactions, and consider It as a secure environment to authenticate users' access to their accounts. Many technologies have been developed in the field of recognition but so far, there is no complete tool or method for speaker identification, the most important step in ASR is the extraction of voice features. Many methods and tools can be used to extract the speaker’s vocal characteristics (voice features), which in turn will identify the user and recognize his voice spectrum through the phonetic linguistic message. In this paper, two methods will be studied, each using a different technique MFCC, which uses a logarithmic scale, and LPC, which uses a linear scale. The method used in ASR should have minimal error because it is an important authentication technology like a fingerprint, where two different people cannot have the same voice spectral range (voiceprint).

1 aAlkhatib, Bassel1 aEddin, Mohammad, Madian Kam uhttp://www.dline.info/download.php?sn=375701580nas a2200145 4500008004100000245006600041210006300107260001200170300001000182490000700192520114700199100002001346700002101366856004701387 2023 eng d00aA Step towards Semantic Digital Library in the Arabic Region-0 aStep towards Semantic Digital Library in the Arabic Region c06/2023 a29-380 v213 a

The use of semantic web technologies is very limited in Arab libraries, even with the existence of important historical and literary documents, and the great digitization movement now, the documents are still trapped within the databases of the separated libraries and are not visible to search engines. The research aims to Study the applications of semantic web technologies in catalogs of digital, hybrid libraries and catalogs of public libraries, exploring the main ontologies and conceptual Data models used in the field, and the possibilities of reusing them with Arab libraries, or the need to build new ontologies, studying the necessary steps, tools, and best practices, define the difficulties and challenges facing the Arabic semantic library and searching for possible technical solutions, our experiments target the heterogeneous databases of small, medium or large libraries, considering that some Arabic library catalogs are not following a standard Data Model, to contribute to the research and development of integrating bibliographic data of Arab libraries and moving towards the Semantic web and Linked Open Data.

1 aAlsahar, Maysah1 aAlkhatib, Bassel uhttp://www.dline.info/download.php?sn=375601653nas a2200145 4500008004100000245006900041210006700110260001200177300001000189490000700199520120100206100003201407700002101439856004701460 2022 eng d00aASR Features Extraction Using MFCC and LPC: A Comparative Study-0 aASR Features Extraction Using MFCC and LPC A Comparative Study c09-2022 a79-890 v203 a

The field of Automatic Speaker Recognition (ASR) is an important and open field for researchers and scientists, especially as it has become essential in facilitating the work we do in our daily lives. Many technologies have been developed in the recognition field. Such as digital authentication and electronic transactions; consider It a secure environment to authenticate user's access to their accounts. Still, so far, there is no complete tool or method for speaker identification, the most crucial step in ASR is the extraction of voice features. Many techniques and tools can extract the speaker's vocal characteristics (voice features), identifying the user and recognising his voice spectrum through the phonetic and linguistic message. In this paper, two methods will be studied, each using a different technique MFCC, which uses a logarithmic scale, and LPC, which uses a linear scale. The method used in ASR should have a minimal error because it is a crucial authentication technology like a fingerprint, where two different people cannot have the same voice spectral range (voiceprint).

1 aEddin, Mohammad, Madian Kam1 aAlkhatib, Bassel uhttp://www.dline.info/download.php?sn=356601591nas a2200157 4500008004100000245006200041210006200103260001200165300001200177490000700189520114100196100002101337700002101358700001701379856003701396 2022 eng d00aDeep Learning Model CNN With LSTM For Speaker Recognition0 aDeep Learning Model CNN With LSTM For Speaker Recognition c12/2022 a131-1470 v203 a

Speech recognition is one of the most important research fields nowadays because of its necessity in our daily lives and to raise the fields of security to the highest level, It’s a task of speech processing, and our main scope in this paper is on speaker verification, which is to identify persons from their voices where the process depends on digitizing the sound waves into a form that allows the system to deal with it. The verification process is based on the characteristics of the speaker's voice (voice biometrics) and sends it to a further process to extract the features of that voice using the feature extraction method and using AI techniques to perform the task of identification. MFCC is used for the task of features extraction and obtains the spectrogram of a given voice signal where it represents a bank of information about the voice and sends it to the CNN model for further processing for training the model on that signal to verify if the voice belongs to a user in the system or it’s a new enrollment.

1 aAlkhatib, Bassel1 aMadian, Mohammad1 aEddin, Kamal uhttps://dline.info/newl/node/75501488nas a2200157 4500008004100000245005800041210005600099260001200155300001000167490000700177520104200184100001701226700002101243700001901264856004701283 2022 eng d00aA Survey of Sentiment Analysis in the Arabic Language0 aSurvey of Sentiment Analysis in the Arabic Language c03/2022 a10-240 v203 a

 â€œWhat the others think?” is an essential question for individuals, companies, and governments. All need to know the public opinions to make their decisions wisely. In the last decade, sentiment analysis and opinion mining have become one of the growing research areas. This paper presents the current state of sentiment analysis and opinion mining research. In particular, researches those deals with the Arabic language. We tried to cover the techniques and methods in sentiment analysis and the challenges in the field. We described the leading methods and approaches that have been introduced in the literature for Arabic Sentiment analysis and opinion mining. The main contributions of this paper include the sophisticated categorizations of a large number of recent articles about Arabic Sentiment analysis. These articles are categorized according to their contributions in the various sentiment analysis techniques.

1 aJAFAR, Kamel1 aAlkhatib, Bassel1 aWANNOUS, Hazem uhttp://www.dline.info/download.php?sn=344900452nas a2200133 4500008004100000245008300041210006900124260001200193300001000205490000700215100002100222700001900243856005600262 2019 eng d00aCrawling the Dark Web: A Conceptual Perspective, Challenges and Implementation0 aCrawling the Dark Web A Conceptual Perspective Challenges and Im c04/2019 a51-600 v171 aAlkhatib, Bassel1 aBasheer, Randa uhttp://dline.info/fpaper/jdim/v17i2/jdimv17i2_1.pdf01705nas a2200145 4500008004100000245008600041210006900127260001200196300001000208490000700218520123800225100002101463700001901484856005601503 2019 eng d00aCrawling the Dark Web: A Conceptual Perspective, Challenges and Implementation–0 aCrawling the Dark Web A Conceptual Perspective Challenges and Im c04/2019 a51-600 v173 a

 Internet and network technologies have evolved dramatically in the last two decades, with rising users’ demands to preserve their identities and privacy. Researchers have developed approaches to achieve users’ demands, where the biggest part of the internet has formed, the Deep Web. However, as the Deep Web provides the resort for many benign users who desire to preserve their privacy, it also became the perfect floor for hosting illicit activities, which generated the Dark Web. This leads to the necessity of finding automated solutions to support law and security agencies in collecting information from the Dark Web to disclose such activities. In this paper, we illustrate the concepts needed for the development of a crawler that collects information from a dark website. We start from discussing the three layers of the Internet, the characteristics of the hidden and private networks, and the technical features of Tor network. We also addressed the challenges facing the dark web crawler. Finally, we presented our experimental system that fetches data from a dark market. This approach helps in putting a single dark website under investigation, and can be a seed for future research and development.

1 aAlkhatib, Bassel1 aBasheer, Randa uhttp://dline.info/fpaper/jdim/v17i2/jdimv17i2_1.pdf00437nas a2200133 4500008004100000245008600041210006900127260001200196300001200208490000700220100002100227700001800248856003700266 2018 eng d00aBuilding a Herbal Medicine Ontology Aligned with Symptoms and Diseases Ontologies0 aBuilding a Herbal Medicine Ontology Aligned with Symptoms and Di c06/2018 a114-1260 v161 aAlkhatib, Bassel1 aBriman, Dania uhttps://dline.info/newl/node/67600778nas a2200145 4500008004100000245009000041210006900131260001200200300001200212490000700224520030600231100002100537700001800558856005600576 2018 eng d00aBuilding a Herbal Medicine Ontology Aligned with Symptoms and Diseases Ontologies –0 aBuilding a Herbal Medicine Ontology Aligned with Symptoms and Di c06/2018 a114-1260 v163 a

The use of traditional medicine is increasing rapidly in many societies due to its efficiency and affordability. The locally available herbs are basically used in the treatment of symptoms and diseases. Herbal Medicines have proved effective in many cases and outperformed the chemical drugs.

1 aAlkhatib, Bassel1 aBriman, Dania uhttp://dline.info/fpaper/jdim/v16i3/jdimv16i3_2.pdf