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A visual modeling method for spatiotemporal and multidimensional features in epidemiological analysis:Applied COVID-19 aggregated datasets

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Computational Visual Media 2024年第1期10卷 161-186页

作者： Yu Dong Christy Jie Liang Yi Chen Jie Hua School of Computer Science University of Technology SydneySydneyNSW2007Australia Beijing Key Laboratory of Big Data technology for Food Safety Beijing Technology and Business UniversityBeijing100048China

The visual modeling method enables flexible interactions with rich graphical depictions of data and supports the exploration of the complexities of epidemiological ***,most epidemiology visualizations do not support the combined analysis of objective factors that might influence the transmission situation,resulting in a lack of quantitative and qualitative *** address this issue,we developed a portrait-based visual modeling method called+*** method considers the spatiotemporal features of virus transmission patterns and multidimensional features of objective risk factors in communities,enabling portrait-based exploration and comparison in epidemiological *** applied+msRNAer to aggregate COVID-19-related datasets in New South Wales,Australia,combining COVID-19 case number trends,geo-information,intervention events,and expert-supervised risk factors extracted from local government area-based *** perfected the+msRNAer workflow with collaborative views and evaluated its feasibility,effectiveness,and usefulness through one user study and three subject-driven case *** feedback from experts indicates that+msRNAer provides a general understanding for analyzing comprehension that not only compares relationships between cases in time-varying and risk factors through portraits but also supports navigation in fundamental geographical,timeline,and other factor *** adopting interactions,experts discovered functional and practical implications for potential patterns of long-standing community factors regarding the vulnerability faced by the *** confirmed that+msRNAer is expected to deliver visual modeling benefits with spatiotemporal and multidimensional features in other epidemiological analysis scenarios.

关键词： visual modeling epidemiological analysis spatiotemporal multidimensional COVID-19

A New Method for Diagnosis of Leukemia Utilizing a Hybrid DL-ML Approach for Binary and Multi-Class Classification on a Limited-Sized Database

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Computer Modeling in Engineering & Sciences 2024年第4期139卷 593-631页

作者： Nilkanth Mukund Deshpande Shilpa Gite Biswajeet Pradhan Abdullah Alamri Chang-Wook Lee Department of Electronics&Telecommunication LavaleSymbiosis Institute of TechnologySymbiosis International(Deemed University)PuneMaharashtra412115India Electronics&Telecommunication Dr.Vithalrao Vikhe Patil College of EngineeringAhmednagarMaharashtra414111India Artificial Intelligence and Machine Learning Department Symbiosis Institute of TechnologySymbiosis International(Deemed)UniversityPune412115India Symbiosis Centre of Applied AI(SCAAI) Symbiosis International(Deemed)UniversityPune412115India Centre for AdvancedModelling and Geospatial Information Systems(CAMGIS) School of Civil and Environmental EngineeringFaculty of Engineering&ITUniversity of Technology SydneySydneyAustralia Earth Observation Centre Institute of Climate ChangeUniversiti Kebangsaan MalaysiaBangiSelangor43600Malaysia Department of Geology&Geophysics College of ScienceKing Saud UniversityP.O.Box 2455Riyadh11451Saudi Arabia Department of Science Education Kangwon National UniversityChuncheon-si24341Korea

Infection of leukemia in humans causes many complications in its later *** impairs bone marrow’s ability to produce *** diagnosis of human blood cells is a well-known and well-proven technique for diagnosis in this *** binary classification is employed to distinguish between normal and leukemiainfected *** addition,various subtypes of leukemia require different *** sub-classes must also be detected to obtain an accurate diagnosis of the type of *** entails using multi-class classification to determine the leukemia *** is usually done using a microscopic examination of these blood *** to the requirement of a trained pathologist,the decision process is critical,which leads to the development of an automated software framework for *** utilized state-of-the-art machine learning approaches,such as Support Vector Machine(SVM),Random Forest(RF),Na飗e Bayes,K-Nearest Neighbor(KNN),and others,to provide limited accuracies of *** advanced deep-learning methods are also *** to constrained dataset sizes,these approaches result in over-fitting,reducing their outstanding *** study introduces a deep learning-machine learning combined approach for leukemia *** uses deep transfer learning frameworks to extract and classify features using state-of-the-artmachine learning *** transfer learning frameworks such as VGGNet,Xception,InceptionResV2,Densenet,and ResNet are employed as feature *** extracted features are given to RF and XGBoost classifiers for the binary and multi-class classification of leukemia *** the experimentation,a very popular ALL-IDB dataset is used,approaching a maximum accuracy of 100%.A private real images dataset with three subclasses of leukemia images,including Acute Myloid Leukemia(AML),Chronic Lymphocytic Leukemia(CLL),and Chronic Myloid Leukemia(CML),is also employed to generalize the *** d

关键词： Leukemia diagnosis deep learning machine learning random forest XGBoost

SH2B1 Tunes Hippocampal ERK Signaling to Influence Fluid Intelligence in Humans and Mice

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Research 2024年第3期2023卷 369-389页

作者： Xiujuan Du Yuhua Yan Juehua Yu Tailin Zhu Chu-Chung Huang Lingli Zhang Xingyue Shan Ren Li Yuan Dai Hui LV Xiao-Yong Zhang Jianfeng Feng Wei-Guang Li Qiang Luo Fei Li Developmental and Behavioral Pediatric Department Brain and Behavioral Research Unit of Shanghai Institute for Pediatric Research and Ministry of Education-Shanghai Key Laboratory for Children's Environmental HealthXinhua Hospital Affiliated to Shanghai Jiao Tong University School of MedicineShanghai 200092China Developmental and Behavioral Pediatric Department Shanghai Xinhua Children's HospitalShanghai 200092China National Clinical Research Center for Aging and Medicine at Huashan Hospital Institute of Science and Technology for Brain-lnspired IntelligenceMinistry of Education-Key Laboratory of Computational Neuroscience and Brain-lnspired IntelligenceFudan UniversityShanghai 200433China State Key Laboratory of Medical Neurobiology and Ministry of Education Frontiers Center for Brain Science Institutes of Brain Science and Human Phenom InstituteFudan UniversityShanghai 200032China Shanghai Key Laboratory of Brain Functional Genomics(Ministry of Education) School of Life SciencesEast China Normal UniversityShanghai 200062China Department of Rehabilitation Medicine Huashan HospitalInstitute for Translational Brain ResearchState Key Laboratory of Medical Neurobiology and Ministry of Education Frontiers Center for Brain ScienceFudan UniversityShanghai 200032China Center for Experimental Studies and Research The First Affliated Hospital of Kunming Medical UniversityKunming 650032China Shanghai Research Center for Brain Science and Brain-lnspired Intelligence Shanghai201210China Institute of Cognitive Neuroscience School of Psychology and Cognitive ScienceEast China Normal UniversityShanghai 200062China.

Fluid intelligence is a cognitive domain that encompasses general reasoning, pattern recognition, and problem-solving abilities independent of task-specific experience. Understanding its genetic and neural underpinnings is critical yet challenging for predicting human development, lifelong health, and well-being. One approach to address this challenge is to map the network of correlations between intelligence and other constructs. In the current study, we performed a genome-wide association study using fluid intelligence quotient scores from the UK Biobank to explore the genetic architecture of the associations between obesity risk and fluid intelligence. Our results revealed novel common genetic loci (SH2B1, TUFM, ATP2A1, and FOXO3) underlying the association between fluid intelligence and body metabolism. Surprisingly, we demonstrated that SH2B1 variation influenced fluid intelligence independently of its effects on metabolism but partially mediated its association with bilateral hippocampal volume. Consistently, selective genetic ablation of Sh2b1 in the mouse hippocampus, particularly in inhibitory neurons, but not in excitatory neurons, significantly impaired working memory, short-term novel object recognition memory, and behavioral flexibility, but not spatial learning and memory, mirroring the human intellectual performance. Single-cell genetic profiling of Sh2B1-regulated molecular pathways revealed that Sh2b1 deletion resulted in aberrantly enhanced extracellular signal-regulated kinase (ERK) signaling, whereas pharmacological inhibition of ERK signaling reversed the associated behavioral impairment. Our cross-species study thus provides unprecedented insight into the role of SH2B1 in fluid intelligence and has implications for understanding the genetic and neural underpinnings of lifelong mental health and well-being.

关键词： metabolism impaired reversed

Challenges and Limitations in Speech Recognition technology:A Critical Review of Speech Signal Processing Algorithms,Tools and Systems

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Computer Modeling in Engineering & Sciences 2023年第5期135卷 1053-1089页

作者： Sneha Basak Himanshi Agrawal Shreya Jena Shilpa Gite Mrinal Bachute Biswajeet Pradhan Mazen Assiri Computer Science and Information technology Department Symbiosis Institute of TechnologySymbiosis International(Deemed University)Pune412115India Symbiosis Centre for Applied Artificial Intelligence Symbiosis International(Deemed University)Pune412115India Centre for Advanced Modelling and Geospatial Information Systems(CAMGIS) School of Civil and Environmental EngineeringFaculty of Engineering and Information TechnologyUniversity of Technology SydneyNew South Wales2007Australia Center of Excellence for Climate Change Research King Abdulaziz UniversityJeddah21589Saudi Arabia Earth Observation Centre Institute of Climate ChangeUniversity Kebangsaan MalaysiaBangiSelangor43600Malaysia

Speech recognition systems have become a unique human-computer interaction(HCI)*** is one of the most naturally developed human abilities;speech signal processing opens up a transparent and hand-free computation *** paper aims to present a retrospective yet modern approach to the world of speech recognition *** development journey of ASR(Automatic Speech Recognition)has seen quite a few milestones and breakthrough technologies that have been highlighted in this paper.A step-by-step rundown of the fundamental stages in developing speech recognition systems has been presented,along with a brief discussion of various modern-day developments and applications in this *** review paper aims to summarize and provide a beginning point for those starting in the vast field of speech signal *** speech recognition has a vast potential in various industries like telecommunication,emotion recognition,healthcare,etc.,this review would be helpful to researchers who aim at exploring more applications that society can quickly adopt in future years of evolution.

关键词： Speech recognition automatic speech recognition(ASR) mel-frequency cepstral coefficients(MFCC) hidden Markov model(HMM) artificial neural network(ANN)

Effect of microlimestone on properties of self-consolidating concrete with manufactured sand and mineral admixture

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Frontiers of Structural and Civil Engineering 2020年第6期14卷 1545-1560页

作者： Fulin Qu Wengui Li Xiaohui Zeng Zhiyu Luo Kejin Wang Daichao Sheng School of Civil and Environmental Engineering University of Technology SydneySydney NSW 2007Australia School of Civil Engineering Central South UniversitChangsha 410075China Department of Civil Construction and Environmental Engineeringlowa State UniversityAmesIA 50011USA

Self-consolidating concrete(SCC)with manufactured sand(MSCC)is crucial to guarantee the quality of concrete construction technology and the associated *** properties of MSCC with different microlimestone powder(MLS)replacements of retreated manufactured sand(TMsand)are investigated in this *** result indicates that high-performance SCC,made using TMsand(TMSCC),achieved high workability,good mechanical properties,and durability by optimizing MLS content and adding fy ash and silica *** particular,the TMSCC with 12%MLS content exhibits the best workability,and the TMSCC with 4%MLS content has the highest strength in the late age,which is even better than that of SCC made with the river sand(R sand).Though MLS content slightly affects the hydration reaction of cement and mainly plays a role in the nucleation process in concrete structures compared to silica fume and fly ash,increasing MLS content can evidently have a significant impact on the early age hydration *** with MLS content ranging from 8%to 12%may be a suitable alternative for the Rsand used in the SCC as fine *** obtained results can be used to promote the application of SCC made with manufactured sand and mineral admixtures for concrete-based infrastructure.

关键词： microlimestone powder manufactured sand retreated manufactured sand self-consolidating concrete mineral admixture

From smart to empathic cities

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Frontiers of Architectural Research 2021年第1期10卷 3-16页

作者： Nimish Biloria Faculty of Design Architecture and Buildins University of Technology SydneyNSW2007Australia

This paper acknowledges the contemporary neoliberal mode of operation of Smart *** pitfalls of Smart Cities concerning its propensity towards techno-centric and efficiency-focused governance are identified,with diminutive emphasis on social equity and human-centric urban ***,the paper elaborates upon an alternative mode of person-environment-interaction based approach towards placemaking:Empathic *** approach implies embracing a shift from efficiency to sufficiency and wellbeing embedded regenerative perspective for conceiving the built ***,the variable dimensions of urban growth and governance,which gave rise to the smart city,are *** embedded neoliberal operational agenda of smart cities are *** this basis,the underpinnings of an empathic city are established by acknowledging the shift from technocentric to human-centric and from product-based to context-based smart city and wellbeing *** toward urban development are proposed,such as embracing a regenerative perspective wherein the city and its constituents need to be understood as interdependent systemic elements while embracing a human-centric and ethical ***,a transition from efficiency to sufficiency-oriented practices and a shift towards inclusive modes of participatory governance are proposed as fundamental principles for an empathic future of the built environment.

关键词： Empathic city Smart city Wellbeing Neoliberalism Regenerative model

Rapid GFAP and Iba1 expression changes in the female rat brain following spinal cord injury

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Neural Regeneration Research 2022年第2期17卷 378-385页

作者： Mawj Mandwie Jordan A.Piper Catherine A.Gorrie Kevin A.Keay Giuseppe Musumeci Ghaith Al-Badri Alessandro Castorina Laboratory of Cellular and Molecular Neuroscience(LCMN) School of Life ScienceFaculty of ScienceUniversity of Technology SydneySydneyNSWAustralia Neural Injury Research Unit School of Life ScienceFaculty of ScienceUniversity of Technology SydneySydneyNSWAustralia School of Medical Sciences(Neuroscience) The University of SydneySydneyNSWAustralia Department of Biomedical and Biotechnological Sciences AnatomyHistology and Movement Sciences SectionSchool of MedicineUniversity of CataniaCataniaItaly

Evidence suggests that rapid changes to supporting glia may predispose individuals with spinal cord injury(SCI) to such comorbidities. Here, we interrogated the expression of astrocyte-and microglial-specific markers glial fibrillary acidic protein(GFAP) and ionized calcium binding adaptor molecule 1(Iba1) in the rat brain in the first 24 hours following SCI. Female Sprague-Dawley rats underwent thoracic laminectomy;half of the rats received a mild contusion injury at the level of the T10 vertebral body(SCI group), the other half did not(Sham group). Twenty-four hours post-surgery the amygdala, periaqueductal grey, prefrontal cortex, hypothalamus, lateral thalamus, hippocampus(dorsal and ventral) in rats were collected. GFAP and Iba1 m RNA and protein levels were measured by real-time quantitative polymerase chain reaction and Western blot. In SCI rats, GFAP m RNA and protein expression increased in the amygdala and hypothalamus. In contrast, gene and protein expression decreased in the thalamus and dorsal hippocampus. Interestingly, Iba1 transcripts and proteins were significantly diminished only in the dorsal and ventral hippocampus, where gene expression diminished. These findings demonstrate that as early as 24 hours post-SCI there are region-specific disruptions of GFAP and Iba1 transcript and protein levels in higher brain regions. All procedures were approved by the university of technology sydney Institutional Animal Care and Ethics Committee(UTS ACEC13-0069).

关键词： affective disorders astrocytes glial fibrillary acidic protein ionized calcium binding adaptor molecule 1 memory microglia neurotrauma spinal cord injury

Earthquake-induced liquefaction hazard mapping at national-scale in Australia using deep learning techniques

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Geoscience Frontiers 2023年第1期14卷 118-132页

作者： Ratiranjan Jena Biswajeet Pradhan Mansour Almazroui Mazen Assiri Hyuck-Jin Park Centre for Advanced Modelling and Geospatial Information Systems(CAMGIS) School of Civil and Environmental EngineeringFaculty of Engineering and Information TechnologyUniversity of Technology SydneyAustralia Center of Excellence for Climate Change Research Department of MeteorologyKing Abdulaziz UniversityJeddah 21589Saudi Arabia Department of Energy and Mineral Resources Engineering Sejong UniversityChoongmu-gwan209 Neungdong-roGwangjin-guSeoul 05006Korea Earth Observation Centre Institute of Climate ChangeUniversiti Kebangsaan Malaysia43600 UKMBangiSelangorMalaysia

Australia is a relatively stable continental region but not tectonically inert,having geological conditions that are susceptible to liquefaction when subjected to earthquake ground *** hazard assessment for Australia was conducted because no Australian liquefaction maps that are based on modern Al techniques are currently *** this study,several conditioning factors including Shear wave velocity(Vs30),clay content,soil water content,soil bulk density,soil thickness,soil pH,distance from river,slope and elevation were considered to estimate the liquefaction potential index(LPI).By considering the Probabilistic Seismic Hazard Assessment(PSHA)technique,peak ground acceleration(PGA)was derived for 50 yrs period(500 and 2500 yrs return period)in ***,liquefaction hazard index(LHI)(effects based on the size and depth of the liquefiable areas)was estimated by considering the LPI along with the 2%and 10%exceedance probability of earthquake ***,ground acceleration data from the Geoscience Australia projecting 2%and 10%exceedance rate of PGA for 50 yrs were used in this study to produce earthquake induced soil liquefaction hazard ***,deep neural net-works(DNNs)were also exerted to estimate liquefaction hazard that can be reported as liquefaction hazard base maps for Australia with an accuracy of 94%and 93%,*** per the results,very-high liquefaction hazard can be observed in Western and Southern Australia including some parts of *** research is the first ever country-scale study to be considered for soil liquefaction hazard in Australia using geospatial information in association with PSHA and deep learning *** study used an earthquake design magnitude threshold of Mw 6 using the source model *** resulting maps present the earthquake-triggered liquefaction hazard and are intending to establish a conceptual structure to guide more detailed investigations as may be requir

关键词： Earthquake induced liquefaction PSHA Deep learning GIS Australia

Explainable Artificial Intelligence-A New Step towards the Trust in Medical Diagnosis with AI Frameworks:A Review

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Computer Modeling in Engineering & Sciences 2022年第12期133卷 843-872页

作者： Nilkanth Mukund Deshpande Shilpa Gite Biswajeet Pradhan Mazen Ebraheem Assiri Department of Electronics&Telecommunication LavaleSymbiosis Institute of TechnologySymbiosis International(Deemed University)Pune412115India Electronics&Telecommunication Vilad GhatDr.Vithalrao Vikhe Patil College of EngineeringAhmednagarMaharashtra414111India Centre for AdvancedModelling and Geospatial Information Systems(CAMGIS) School of Civil and Environmental EngineeringFaculty of Engineering&ITUniversity of Technology SydneySydney2007Australia Center of Excellence for Climate Change Research King Abdulaziz UniversityJeddah21589Saudi Arabia Earth Observation Centre Universiti KebangsaanInstitute of Climate ChangeMalaysiaSelangor43600Malaysia Department of Computer Science LavaleSymbiosis Institute of TechnologySymbiosis International(Deemed University)Pune412115India Symbiosis Center for Applied Artificial Intelligence(SCAAI) LavaleSymbiosis International(Deemed University)Pune412115India

Machine learning(ML)has emerged as a critical enabling tool in the sciences and industry in recent ***’s machine learning algorithms can achieve outstanding performance on an expanding variety of complex tasks-thanks to advancements in technique,the availability of enormous databases,and improved computing *** learning models are at the forefront of this ***,because of their nested nonlinear structure,these strong models are termed as“black boxes,”as they provide no information about how they arrive at their *** a lack of transparencies may be unacceptable in many applications,such as the medical domain.A lot of emphasis has recently been paid to the development of methods for visualizing,explaining,and interpreting deep *** situation is substantially different in safety-critical *** lack of transparency of machine learning techniques may be limiting or even disqualifying issue in this ***,when single bad decisions can endanger human life and health(e.g.,autonomous driving,medical domain)or result in significant monetary losses(e.g.,algorithmic trading),depending on an unintelligible data-driven system may not be an *** lack of transparency is one reason why machine learning in sectors like health is more cautious than in the consumer,e-commerce,or entertainment *** is the term introduced in the preceding *** AImodel’s black box nature will become explainable with these *** in the medical domain,diagnosing a particular disease through AI techniques would be less adapted for commercial *** models’explainable natures will help them commercially in diagnosis decisions in the medical *** paper explores the different frameworks for the explainability of AI models in the medical *** available frameworks are compared with other parameters,and their suitability for medical fields is also discussed.

关键词： Medical imaging explainability artificial intelligence XAI