Arfa Siddiqu, Abdul Basit^*, Waheed Noor, Muhammad Asfandyar Khan, M. Saeed H. Kakar, Azam Khan

Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 875-885, 2023, DOI:10.32604/iasc.2023.036426

Abstract The optical character recognition for the right to left and cursive languages such as Arabic is challenging and received little attention from researchers in the past compared to the other Latin languages. Moreover, the absence of a standard publicly available dataset for several low-resource languages, including the Pashto language remained a hurdle in the advancement of language processing. Realizing that, a clean dataset is the fundamental and core requirement of character recognition, this research begins with dataset generation and aims at a system capable of complete language understanding. Keeping in view the complete and full autonomous recognition of the cursive… More >

Manjiang Xing^*

Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 1081-1090, 2023, DOI:10.32604/iasc.2023.034750

Abstract At present, the database cache model of power information system has problems such as slow running speed and low database hit rate. To this end, this paper proposes a database cache model for power information systems based on deep machine learning. The caching model includes program caching, Structured Query Language (SQL) preprocessing, and core caching modules. Among them, the method to improve the efficiency of the statement is to adjust operations such as multi-table joins and replacement keywords in the SQL optimizer. Build predictive models using boosted regression trees in the core caching module. Generate a series of regression tree… More >

Chien-Ming Chen¹, Zhenzhou Zhang¹, Jimmy Ming-Tai Wu¹, Kuruva Lakshmanna^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.1, pp. 733-759, 2023, DOI:10.32604/cmes.2023.027463

Abstract Periodic pattern mining has become a popular research subject in recent years; this approach involves the discovery of frequently recurring patterns in a transaction sequence. However, previous algorithms for periodic pattern mining have ignored the utility (profit, value) of patterns. Additionally, these algorithms only identify periodic patterns in a single sequence. However, identifying patterns of high utility that are common to a set of sequences is more valuable. In several fields, identifying high-utility periodic frequent patterns in multiple sequences is important. In this study, an efficient algorithm called MHUPFPS was proposed to identify such patterns. To address existing problems, three… More >

Amarjit Singh^*

Journal on Internet of Things, Vol.4, No.2, pp. 69-73, 2022, DOI:10.32604/jiot.2022.026170

Abstract Wireless sensor networks (WSNs) are created and affect our daily lives. You can find applications in various fields such as health, accident, life, manufacturing, production management, network management and many other fields. WSN now connects to the Internet of Things, connects the sensor to the Internet, and then uses it for collaboration and collaboration. However, when WSN is part of the internet we need to be able to study and analyze related terms. In this article, we’re going to look at different ways to get WSN online and identify the challenges that address in future as well. More >

Fei Wang¹, Jihyun Ma², Nan Zhao³, Chi Lin^3,*, Haixing Jiang^1,*

Oncologie, Vol.24, No.4, pp. 865-895, 2022, DOI:10.32604/oncologie.2022.025447

Abstract Objective: The characteristics of clinical features and prognoses among patients with different racial backgrounds have not been clearly studied. We thus investigated the clinical characteristics and overall survival (OS) differences among Asian, White, and Black patients with pancreatic neuroendocrine tumors (pNETs). Materials and Methods: The Surveillance, Epidemiology, and End Results (SEER) database was queried to identify patients with pNETs between 1983 and 2015. We performed univariable (UVA) and multivariable logistic regression (MVA) to assess the association between variables and race category. A Kaplan-Meier (KM) plot was used to calculate the OS rates. The Cox proportional hazard regression was used to… More >

Pei Yin¹, Jing Cheng^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.3, pp. 2387-2405, 2023, DOI:10.32604/cmes.2023.023666

Abstract With the development of the digital city, data and data analysis have become more and more important. The database is the foundation of data analysis. In this paper, the software system of the urban land planning database of Shanghai in China is developed based on MySQL. The conceptual model of the urban land planning database is proposed, and the entities, attributes and connections of this model are discussed. Then the E-R conceptual model is transformed into a logical structure, which is supported by the relational database management system (DBMS). Based on the conceptual and logical structures, by using SpringBoot as… More >

QIANG WANG^#, GUO ZHAO^#, LONGXIANG XIE^#, XUAN LI, XIXI YU, QIONGSHAN LI, BAOPING ZHENG, ZULIPINUER WUSIMAN, XIANGQIAN GUO^*

BIOCELL, Vol.47, No.2, pp. 367-371, 2023, DOI:10.32604/biocell.2023.025310

Abstract Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the pathogen of the ongoing coronavirus disease 2019 (COVID-19) global pandemic. Here, by centralizing published cell-based experiments, clinical trials, and virtual drug screening data from the NCBI PubMed database, we developed a database of SARS-CoV-2 inhibitors for COVID-19, dbSCI, which includes 234 SARS-CoV-2 inhibitors collected from publications based on cell-based experiments, 81 drugs of COVID-19 in clinical trials and 1305 potential SARS-CoV-2 inhibitors from bioinformatics analyses. dbSCI provides four major functions: (1) search the drug target or its inhibitor for SARS-CoV-2, (2) browse target/inhibitor information collected from cell experiments, clinical trials, and… More >

Hasanien K. Kuba¹, Mustafa A. Azzawi², Saad M. Darwish^3,*, Oday A. Hassen⁴, Ansam A. Abdulhussein⁵

CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 4119-4133, 2023, DOI:10.32604/cmc.2023.033182

Abstract It is crucial, while using healthcare data, to assess the advantages of data privacy against the possible drawbacks. Data from several sources must be combined for use in many data mining applications. The medical practitioner may use the results of association rule mining performed on this aggregated data to better personalize patient care and implement preventive measures. Historically, numerous heuristics (e.g., greedy search) and metaheuristics-based techniques (e.g., evolutionary algorithm) have been created for the positive association rule in privacy preserving data mining (PPDM). When it comes to connecting seemingly unrelated diseases and drugs, negative association rules may be more informative… More >

Marwan H. Hassan¹, Saad M. Darwish^2,*, Saleh M. Elkaffas³

CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 4417-4434, 2023, DOI:10.32604/cmc.2023.033175

Abstract Electronic patient data gives many advantages, but also new difficulties. Deadlocks may delay procedures like acquiring patient information. Distributed deadlock resolution solutions introduce uncertainty due to inaccurate transaction properties. Soft computing-based solutions have been developed to solve this challenge. In a single framework, ambiguous, vague, incomplete, and inconsistent transaction attribute information has received minimal attention. The work presented in this paper employed type-2 neutrosophic logic, an extension of type-1 neutrosophic logic, to handle uncertainty in real-time deadlock-resolving systems. The proposed method is structured to reflect multiple types of knowledge and relations among transactions’ features that include validation factor degree, slackness… More >

Tahir Alyas¹, Ali Alzahrani², Yazed Alsaawy², Khalid Alissa³, Qaiser Abbas², Nadia Tabassum^4,*

CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 2317-2330, 2023, DOI:10.32604/cmc.2023.032454

Abstract The query optimizer uses cost-based optimization to create an execution plan with the least cost, which also consumes the least amount of resources. The challenge of query optimization for relational database systems is a combinatorial optimization problem, which renders exhaustive search impossible as query sizes rise. Increases in CPU performance have surpassed main memory, and disk access speeds in recent decades, allowing data compression to be used—strategies for improving database performance systems. For performance enhancement, compression and query optimization are the two most factors. Compression reduces the volume of data, whereas query optimization minimizes execution time. Compressing the database reduces… More >