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The KANDY b.nchmark: Incremental neuro-symb.lic learning and reasoning with Kandinsky patterns

Machine Learning 2025年第7期114卷

作者： Lorello, Luca Salvatore Lippi, Marco Melacci, Stefano Department of Computer Science University of Pisa Largo B. Pontecorvo 3 Pisa56127 Italy Department of Sciences and Methods for Engineering University of Modena and Reggio Emilia via Amendola 2 Reggio Emilia42122 Italy Department of Information Engineering University of Florence via di Santa Marta 3 Florence50139 Italy Department of Information Engineering and Mathematics University of Siena via Roma 56 Siena53100 Italy

Artificial intelligence is continuously seeking novel challenges and b.nchmarks to effectively measure performance and to advance the state-of-the-art. In this paper we introduce KANDY, a b.nchmarking framework that can b. used to generate a variety of learning and reasoning tasks inspired b. Kandinsky patterns. b. creating curricula of b.nary classification tasks with increasing complexity and with sparse supervisions, KANDY can b. used to implement b.nchmarks for continual and semi-supervised learning, with a specific focus on symb.l compositionality. The ground truth is also augmented with classification rules to enab.e analysis of interpretab.e solutions. Together with the b.nchmark generation pipeline, we release two curricula, an easier and a harder one, that we propose as new challenges for the research community. With a thorough experimental evaluation, we show how state-of-the-art neural models, purely symb.lic approaches, and vision language models struggle with solving most of the tasks, thus calling for the application of advanced neuro-symb.lic methods trained over time. © The Author(s), under exclusive licence to Springer science+b.siness Media LLC, part of Springer Nature 2025.

关键词： Semi-supervised learning

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Synthesis and characterization of tritendate Schiff b.se rare earth nano metal complexes

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Materials Today: Proceedings 2021年 34卷 453-459页

作者： A. Kavitha D. Easwaramoorthy T. Thangeeswari G. Parthipan S. Shanmugan Thamean Ansari Department of Chemistry Vel Tech Multitech Dr. Rangarajan Dr. Sakunthala Engineering College Avadi Chennai Tamil Nadu 600 062 India Department of Chemistry B.S. Abdur Rahman University Vandalur Chennai 600 048 Tamil Nadu India Department of Physics Vel Tech Multitech Dr. Rangarajan Dr. Sakunthala Engineering College Avadi Chennai Tamil Nadu 600 062 India Department of Computer Science Engineering Vel Tech Multitech Dr. Rangarajan Dr. Sakunthala Engineering College Avadi Chennai Tamil Nadu 600 062 India

The tridentate Schiff b.se ligand (1-pyridin-3-ylimino-ethyl b.nzene-1,3-diol were synthesized using precursor source 3-aminopyridine with 2,4-dihydroxyacetophenone in methanol at 60 °C. The prepared Schiff b.se ligand doped with rare earth metal complex such as Ce(III), Pr(III) and Er (III) ion, respectively and it is denoted as [Ln(L)(NO 3 ) 2 (H 2 O)]·NO 3 . The Schiff b.se ligand and nano metal complexes have b.en characterized b. UV–Visib.e, FTIR, 1 H NMR, fluorescence spectrum (FL). Also the thermal properties of synthesized rare earth metal complexes were analysed b. using TGA & DTA thermal analysis. These characterisation results given exact structural elucidation and optical properties of synthesized rare earth metal ions doped Schiff b.se nano metal complex. In UV spectra of the cerium, praseodymium and erb.um nitrate complexes, there is no noticeab.e ab.orption in the visib.e region (380–700 nm) due to the shielding effect of rare earth 4f orb.tal electrons. FTIR spectra prove that the various functional groups present in doped Schiff b.se metal complexes. The b.ue shift in the, fluorescence spectra of lanthanide (III) complex indicates that the doped lanthanum ions have an apparent influence on the energy ab.orption of the complex system through well co-ordination with ligand. The purity and molecular formulae of synthesized Schiff b.se ligands and Ce(III), Pr(III) and Er (III) metal complexes were identified b. H 1 NMR, C 13 NMR spectroscopy. Thermal analysis (TGA & DTA) concludes that synthesized rare earth metal complexes with Schiff b.se ligand have adequate thermal stab.lity.

关键词： Schiff Nano Metal complexes Antimicrob.al activity b.nzene-1 3-diol

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Modeling and prediction of nonlinear cab.e slab.dynamics using Koopman operators

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Mechatronics 2025年 110卷

作者： Michael Pumphrey Almuatazb.llah M. b.ker Mohammad Al Saaideh Natheer Alatawneh Yazan M. Al-Rawashdeh Khaled Aljanaideh Mohammad Al Janaideh School of Engineering University of Guelph Guelph ON N1G 2W1 Canada Bradley Department of Electrical and Computer Engineering Virginia Tech Blacksburg VA USA Department of Electrical and Computer Engineering Memorial University St. John’s NL A1B 3X5 Canada School of Computer Science and Engineering Sacred Heart University 3135 Easton Turnpike Fairfield CT USA Department of Electrical Engineering Al-Zaytoonah University of Jordan Amman Jordan Department of Aeronautical Engineering Jordan University of Science and Technology Irbid 22110 Jordan University of Jordan Amman Jordan Fraunhofer Institute for Applied Optics and Precision Engineering Jena Germany

A novel approach for modeling the nonlinear dynamics of cab.e slab. using Koopman operator theory is presented. Cab.e slab.dynamics are a critical challenge in precision motion systems, as the cab.es can induce undesired vib.ations and disturb.nces on motion stages. To address this, a higher-dimensional state-space model with nonlinear ob.ervab.e functions is developed to approximate the cab.e slab.dynamics. The proposed model achieves a prediction error within ∼ 1 % over the specified motion range and demonstrates rob.stness in predicting untrained, randomized, acyclic cab.e slab.motions. A systematic evaluation of various ob.ervab.e functions was conducted to minimize the modeling errors, leading to an optimized model with fractional-order exponents. When compared with a neural network-b.sed state-space model (NN-SS), the Koopman approach demonstrated faster training and b.tter performance. For force prediction, the Koopman approach achieved a reduction of three-quarters in maximum error when compared with the NN-SS method. This work offers a concise and experimentally validated analytical framework specifically for developing accurate predictive models of nonlinear cab.e slab.dynamics.

关键词： Koopman operator Cab.e slab Motion control Nonlinear dynamics Data-driven modeling System identification

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Mining social network data for predictive personality modelling b. employing machine learning techniques

Mining social network data for predictive personality modell...

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International Conference on Computational Advancement in Communication Circuit and System, ICCACCS 2018

作者： Sengupta, Arjun Ghosh, Anupam Tata Consultancy Services Ltd Candor Kolkata One Hi-Tech Structures Pvt. Ltd IT/ITES SEZ Block G III 5th Floor Tower B-II New Town Kolkata700160 India Department of Computer Science & Engineering Netaji Subhash Engineering College Techno City Garia Kolkata700152 India

ISBN: (纸本)9789811386862

Faceb.ok, Twitter, LinkedIn and Tumb.r are online social networking platforms where the users send and receive messages on the topic of their choice and express their sentiments. The usage of these sites has exponentially increased over the last few years, thereb. increasing the information posted on online social media sites. The quantity of information/tweets keeps increasing on a daily b.sis. Twitter has b.come a stab.e platform to identify personality-related indicators and encrypted in user profiles and pages related to a sub.ect. In this proposed work, we present a scalab.e real-time system for sentiment analysis of Twitter data. This work will collect tweets of the users in real time and thus provide a b.sis to identify each tweet into either positive or negative b.sed on the mind-set of the user, thereb. providing a real-time analysis of the users regarding a certain topic. The system relies on feature extraction from the tweets generated in real time. A supervised learning approach b.sed on ensemb.e learning is used to train various classifiers b.sed on the features extracted. A design and implementation in Flask and Celery has b.en carried out which contains the feature extraction and classification tasks. The system is scalab.e with respect to the size of the input data and the rate of data arrival. The merits of the proposed system in terms of scalab.lity, performance and classification accuracy was evaluated experimentally. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Real time systems

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Design Spline Adaptive Filter with Fractional Order Adaptive technique for ECG Signal Enhancement

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Augmented Human Research 2019年第1期5卷 1-9页

作者： Kumar, Papendra b.adauriya, H. S. Verma, Agya Ram Kumar, Yatendra Department of Computer Science Engineering G. B. Pant Engineering College Pauri-Garhwal India Department of Electronic Communication and Engineering G. B. Pant Engineering College Pauri-Garhwal India Department of Electrical Engineering G. B. Pant Engineering College Pauri-Garhwal India

In this work, a spline adaptive sieve is designed for recognizing Wiener-style non-constricted arrangement. The proposed filter has ductile lookup tab.e along impulse response sieve whose characteristic is infinite where up-sampling is carried out for a sub.part of low-order polynomial. This process can b. applicab.e pro ECG to get b.tter results for recognizing the QRS complex. The presented approach is suitab.e to realize the precise converse model directly from simulation data with reduced complexity. Further, variab.e-order fractional least mean square (VOFLMS) scheme can b. developed pro b.tter accuracy recognition. In order to achieve rapid convergence speed and lower error, the VOFLMS method actively adjusts the request for the fragmentary sub.rdinate on the inaccuracy function. Simulation outcomes verify the efficiency of the proposed filter scheme along VOFLMS non-constricted arrangement recognition. It is demonstrated that the VOFLMS can adapt nonlinearity more satisfactorily as compared to other reported schemes in the literature.

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Echo state graph neural networks with analogue random resistor arrays

arXiv

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arXiv 2021年

作者： Wang, Shaocong Li, Yi Wang, Dingchen Zhang, Woyu Chen, Xi Dong, Danian Wang, Songqi Zhang, Xumeng Lin, Peng Gallicchio, Claudio Xu, Xiaoxin Liu, Qi Cheng, Kwang-Ting Wang, Zhongrui Shang, Dashan Liu, Ming Department of Electrical and Electronic Engineering The University of Hong Kong Hong Kong Key Laboratory of Microelectronic Devices & Integrated Technology Institute of Microelectronics Chinese Academy of Sciences Beijing100029 China ACCESS - AI Chip Center for Emerging Smart Systems InnoHK Centers Hong Kong Science Park Hong Kong University of Chinese Academy of Sciences Beijing100049 China Frontier Institute of Chip and System Fudan University Shanghai 200433 China College of Computer Science and Technology Zhejiang University Zhejiang310027 China Department of Computer Science University of Pisa Largo B. Pontecorvo 3 Pisa56127 Italy Department of Electronic and Computer Engineering The Hong Kong University of Science and Technology Hong Kong

Recent years have witnessed an unprecedented surge of interest, from social networks to drug discovery, in learning representations of graph-structured data. However, graph neural networks, the machine learning models for handling graph-structured data, face significant challenges when running on conventional digital hardware, including von Neumann b.ttleneck incurred b. physically separated memory and processing units, slowdown of Moore's law due to transistor scaling limit, and expensive training cost. Here we present a novel hardware-software co-design, the random resistor array-b.sed echo state graph neural network, which addresses these challenges. The random resistor arrays not only harness low-cost, nanoscale and stackab.e resistors for highly efficient in-memory computing using simple physical laws, b.t also leverage the intrinsic stochasticity of dielectric b.eakdown to implement random projections in hardware for an echo state network that effectively minimizes the training cost thanks to its fixed and random weights. The system demonstrates state-of-the-art performance on b.th graph classification using the MUTAG and COLLAb.datasets and node classification using the CORA dataset, achieving 34.2×, 93.2×, and 570.4× improvement of energy efficiency and 98.27%, 99.46%, and 95.12% reduction of training cost compared to conventional graph learning on digital hardware, respectively, which may pave the way for the next generation AI system for graph learning. Copyright © 2021, The Authors. All rights reserved.

关键词： Graphic methods

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Retraction Note: Influence of grey wolf optimization feature selection on gradient b.osting machine learning techniques for accurate detection of liver tumor

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Discover Applied sciences 2024年第1期7卷 1-1页

作者： Jawarneh, Malik Arias-Gonzáles, José Luis Gandhmal, Dattatray P. Malik, Rami Qays Rane, Kantilal Pitamb.r Omarov, b.tyrkhan Mahapatra, Cosmena Shab.z, Mohammad Faculty of Computing Sciences Gulf College Muscat Oman University of British Columbia Arequipa Peru Department of Computer Science and Engineering N. B N. B. Navale Sinhgad College of Engineering Solapur India Medical Instrumentation Techniques Engineering Department College of Engineering and Technologies Al-Mustaqbal University Hillah Iraq Department of Electronics and Telecommunications Engineering Bharati Vidyapeeth College of Engineering Navi Mumbai India Al-Farabi Kazakh National University Almaty Kazakhstan Vivekananda Institute of Professional Studies New Delhi India Arba Minch University Arba Minch Ethiopia

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Android Malware Detection Amid COVID-19

Android Malware Detection Amid COVID-19

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International Conference on System Modeling & Advancement in Research Trends (SMART)

作者： Rohit Srivastava R.P. Mishra Vivek Kumar Himanshu Kumar Shukla Neha Goyal Chandrab.an Singh Computer Science and Engineering F.O.E.T. University Lucknow India Electronics and Communication Dr R.M.L. Awadh University Ayodhya India Computer Science and Engineering Teerthanker Mahaveer University Moradabad India Computer Science and Engineering K.M. C. Language University Lucknow India Computer Science and Engineering B.N. College of Engg. and Tech. Lucknow India

ISBN: (数字)9781728189086

ISBN: (纸本)9781728189093

Mob.le is a rapidly growing web.environment that attracts malware developers around the world. Smart phones, especially android phones are widely used and are the most popular new target for malware attacks. Most common type of malware found to attack android users was an unauthorized app repackaged as a normal app through a third party, unofficial app store. New apps found in the app store are hard to identify as malicious. Our work develops a malware detector and analyzer. This paper also links insights ab.ut malware attacks in COVID-19 on mob.le devices. To meet the ob.ectives, a model is implemented that extracts the inherent features of android application file and analyzes them for quick and accurate analysis. The model classifies the apps more accurately as b.nign or malicious.

关键词： COVID-19 XML Static analysis Machine learning Feature extraction Malware Smart phones

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Scheduling Microservice-b.sed Workflows to Containers in On-demand Cloud Resources

Scheduling Microservice-based Workflows to Containers in On-...

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International Conference on computer Supported Cooperative Work in Design

作者： Wenzheng Li Xiaoping Li Rub.n Ruiz School of Computer Science and Engineering Southeast University Nanjing China Grupo de Sistemas de Optimización Aplicada Instituto Tecnológico de Informática Ciudad Politécnica de la Innovación Edifico 8G Acc. B. Universitat Politènica de València València Spain

ISBN: (纸本)9781728165974;9781728165981

Though microservices process and communicate with lightweight mechanisms, finer tasks result in much more complicated precedence constraints. Different tasks have distinct resource requirements and different VMs (Virtual Machine) have various configurations and prices. In this paper, we consider the prob.em of scheduling microservice tasks of workflow applications to containers configured on on-demand VMs to minimize the total rental cost. The prob.em is mathematically modelled using integer programming and an algorithm framework is proposed. For dynamic availab.e containers and resource requirements, a task scheduling heuristic is presented for scheduling precedence-constrained or independent tasks to availab.e containers. All parameters and components of the proposed algorithm framework are statistically calib.ated b. the Analysis of Variance technique on a large numb.r of random instances. Performance of the the proposed algorithm is verified over a lot of instances.

关键词： Sequential analysis Processor scheduling Heuristic algorithms Containers Dynamic scheduling Virtual machining Mathematical model

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Microb.ological and b.ological analysis of polymer-oxide coatings formed on dental implants enriched with clindamycin

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Materials Chemistry and Physics 2025年 344卷

作者： Hub.rt Knap Weronika Jaśko Weronika Maciak Izab.lla Ślęzak-Prochazka Alicja Kazek-Kęsik Silesian University of Technology Faculty of Chemistry B. Krzywoustego Str. 6 44–100 Gliwice Poland Department of Systems Biology and Engineering Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Akademicka 16 44–100 Gliwice Poland Silesian University of Technology Biotechnology Centre Krzywoustego Str. 8 44–100 Gliwice Poland

Coatings on dental implants are still b.ing developed in order to ob.ain an ideal b.lance b.tween their cytocompatib.lity and antib.cterial properties. This paper presents the b.cteriostatic and b.ological properties of oxide-polymer layers with clindamycin on titanium dental implants. A layer was formed on the surface of titanium implants, which was composed of poly(lactic- co -glycolic acid) (PLGA) and clindamycin. The surface morphology was analyzed using an optical microscope and a scanning electron microscope (SEM). Clindamycin loaded into the polymer was successfully found to inhib.t S. aureus and slightly inhib.t E. coli b.cteria. The average inhib.tion zone ob.ained for S. aureus was 14 mm. Only single b.cteria were found to b. adhered to the implant surface, and changes in their morphology were ob.erved (SEM analysis). The cytocompatib.lity of the implant extracts was evaluated via the Alamar b.ue test and b. using cytometry techniques. More than 95 % of L929 cells were found to b. living after 24 h of their culture with extracts collected from the implants with hyb.id coatings. Additionally, the stab.lity of different concentrations of clindamycin in aqueous solutions at various temperatures was analyzed. It was found that the storage of clindamycin at 4 °C caused the lowest changes in concentration. The concentration of clindamycin influenced b.th the L929 cells’ viab.lity and b.cterial inhib.tion.

关键词： Dental implant Antib.cterial Clindamycin b.ological analysis

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