The Author’s Methodology of Forecasting Election Results on the Basis of Big Data by A. S. Kozin

“…Social networks generate a vast amount of unstructured data due to their use by thousands of users. …”
Get full text

Investigating imperceptibility of adversarial attacks on tabular data: An empirical analysis by Zhipeng He, Chun Ouyang, Laith Alzubaidi, Alistair Barros, Catarina Moreira

“…Adversarial attacks are a potential threat to machine learning models by causing incorrect predictions through imperceptible perturbations to the input data. While these attacks have been extensively studied in unstructured data like images, applying them to structured data, such as tabular data, presents new challenges. …”
Get full text

Structural Damage Identification Based on Rough Sets and Artificial Neural Network by Chengyin Liu, Xiang Wu, Ning Wu, Chunyu Liu

“…The proposed approach is tested with a 14-bay steel truss model for structural damage detection. The experimental results show that the damage features can be extracted efficiently from the combined utilization of RS and ANN methods even the volume of measurement data is enormous and with uncertainties.…”
Get full text

CREDIT SUPPORT FOR THE AGRICULTURAL SECTOR IN BULGARIA: STRUCTURAL ANALYSIS AND ECONOMIC DIMENSIONS by Hristo KOSTOV, Nadezhda BLAGOEVA, Vanya GEORGIEVA

“…This paper examines the dynamics and significance of lending in the agricultural sector of the Republic of Bulgaria and its connection with the sector's economic contribution. Using data from the Bulgarian National Bank and FAO for 2000-2023, the analysis focuses on the structure of loans by size and term and a comparative analysis of Bulgaria with EU-27 countries. …”
Get full text

The effects of alternating heads of state on structural transformation in sub-Saharan Africa by Saturnin Bertrand Nguenda Anya, Fabrice Nzepang

“…The objective of this paper is to investigate the effect of alternating heads of state on structural transformation in sub-Saharan Africa (SSA). …”
Get full text

Identification of Structural Damage in Bridges Using High-Frequency Vibrational Responses by Ivana Mekjavić

“…The present research aims to develop an effective and applicable structural damage detection method. A damage identification approach using only the changes of measured natural frequencies is presented. …”
Get full text

GeoFAN: Point Pattern Recognition in Spatial Vector Data by Zhuoyi Yang, Zeyi Li, Haitao Zhang, Wei Zhang, Yanwei Wang, Yihang Huang

“…However, the application of traditional methods to spatial vector data faces two difficulties. Firstly, these data are low signal-to-noise ratio data in which the point patterns are mixed with a large number of normal point clusters; thus, it is difficult to recognize point patterns from these unstructured data using traditional clustering or machine learning methods. …”
Get full text

Blockchain and Bigdata to Secure Data Using Hash and Salt Techniques by AlSelami Fudhah A.

“…Bigdata technologies helps in storing the unstructured data effectively and processing of such voluminous data is taken care of. …”
Get full text

Consistent genes associated with structural changes in clinical Alzheimer’s disease spectrum by Yingqi Lu, Yingqi Lu, Yingqi Lu, Xiaodong Zhang, Xiaodong Zhang, Liyu Hu, Qinxiu Cheng, Zhewei Zhang, Haoran Zhang, Zhuoran Xie, Yiheng Gao, Dezhi Cao, Shangjie Chen, Shangjie Chen, Jinping Xu

“…However, the neurobiological and pathogenic substrates underlying this structural atrophy across the AD spectrum remain largely understood.MethodsIn this study, we obtained structural MRI data from ADNI datasets, including 83 participants with early-stage cognitive impairments (EMCI), 83 with late-stage mild cognitive impairments (LMCI), 83 with AD, and 83 with normal controls (NC). …”
Get full text

ARTIFICIAL INTELLIGENCE AND BIG DATA ANALYSIS IN CRIME PREVENTION AND COMBAT by George-Marius ȚICAL

“…Machine learning algorithms, neural networks, and natural language processing enable the rapid analysis of unstructured data, enhancing the ability to predict and prevent crimes. …”
Get full text

Inference of Impulse Responses via Bayesian Graphical Structural VAR Models by Daniel Felix Ahelegbey

“…The BGSVAR framework provides a more efficient and interpretable method for estimating IRFs, which can enhance both forecasting performance and structural inferences in economic modelling. Through extensive simulations across various data-generating processes, we evaluate BGSVAR’s effectiveness in modelling dynamic interactions among US macroeconomic variables. …”
Get full text

Studies of structural and optical properties of sputtered SiC thin films by Mukesh Kumar Mukesh Kumar

Get full text

Monetary policy and income inequality in Brazil: structural vector autoregressive approach by Eshetie Woretaw Meried

“…Abstract The main objective of this study is to investigate the impact of monetary policy shock on income inequality in Brazil. To estimate the Structural Vector Autoregressive (SVAR) model, time series data is gathered from the first quarter of 1998 to the last quarter of 2021. …”
Get full text

An integrated structural and biophysical approach to study carbon metabolism in Mycobacterium tuberculosis by Evelyn Y.-W. Huang, Francis Kuang, Haozhe Wu, Chai Xin Yu, Xiaoxu Chen, Glenda Vasku, Le Thao Anh Nguyen, Katherine J. Jeppe, Anna K. Coussens, Brooke X.C. Kwai, Ivanhoe K.H. Leung

“…To fully understand their roles and modulation, it is crucial to investigate the relationship between their structure, catalytic mechanism, and function. In this perspective, by using three examples from our studies on Mycobacterium tuberculosis (Mtb) isocitrate lyase and related proteins, we highlight how an integrated approach combining structural, activity, and biophysical data provides insights into their biological functions. …”
Get full text

catena-Poly[[diphenyltin(IV)]-di-μ-isothiocyanato]: an unprecedented layered coordination polymer resulting from bridging κ2N:S thiocyanato ligands by Ann-Kathrin Pancratz, Anne Kamrowski, Hans Reuter

Get full text

Accurate segmentation of localized corrosion in structural alloys via deep learning by Liang Zhao, Jenifer Locke, Fei Xu, Tiankai Yao, Xiaolei Guo

Get full text

Structural and Dielectric Characterization of Sm2MgMnO6 by Moumin Rudra, Ritwik Maity, T.P.В Sinha

“…An electrical equivalent circuit consisting of the resistance and constant phase element is used to clarify the impedance data.…”
Get full text

Leveraging hybrid model for accurate sentiment analysis of Twitter data by Naga Surekha Jonnala, A. V. S. Ram Teja, S. Raja Rajeswari, Shaik Jakeer, Allamsetty Dheeraj, Shonak Bansal, Krishna Prakash, Shashank Singh, Mohammad Rashed Iqbal Faruque, K. S. Al-mugren

“…These outcomes underscore the strength of combining Bi-LSTM and Logistic Regression for sentiment analysis, offering a robust framework for analyzing unstructured textual data in social media contexts. This approach demonstrates significant potential for enhancing sentiment classification tasks in the ever-evolving digital landscape.…”
Get full text

NLP modeling recommendations for restricted data availability in clinical settings by Fabián Villena, Felipe Bravo-Marquez, Jocelyn Dunstan

“…Abstract Background Clinical decision-making in healthcare often relies on unstructured text data, which can be challenging to analyze using traditional methods. …”
Get full text

MicroGlycoDB: A database of microbial glycans using Semantic Web technologies by Sunmyoung Lee, Louis-David Leclercq, Yann Guerardel, Christine M. Szymanski, Thomas Hurtaux, Tamara L. Doering, Takane Katayama, Kiyotaka Fujita, Kazuhiro Aoki, Kiyoko F. Aoki-Kinoshita

“…We have developed a MicroGlycoDB database to provide integrated glycan information on important model microorganisms. The data is described using Semantic Web Technologies, which allow microbial glycan data to be represented in a structured format accessible by machines, thus facilitating data sharing and integration with other resources that catalog features such as pathways, diseases, or interactions. …”
Get full text