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Improving the Segmentation of Arabic Handwriting Using Ligature Detection Technique

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Computers, Materials & Continua 2024年第5期79卷 2015-2034页

作者： Husam Ahmad Al Hamad Mohammad Shehab college of Computer Sciences and informatics Amman Arab UniversityAmman11953Jordan

Recognizing handwritten characters remains a critical and formidable challenge within the realm of computervision. Although considerable strides have been made in enhancing English handwritten character recognitionthrough various techniques, deciphering Arabic handwritten characters is particularly intricate. This complexityarises from the diverse array of writing styles among individuals, coupled with the various shapes that a singlecharacter can take when positioned differently within document images, rendering the task more perplexing. Inthis study, a novel segmentation method for Arabic handwritten scripts is suggested. This work aims to locatethe local minima of the vertical and diagonal word image densities to precisely identify the segmentation pointsbetween the cursive letters. The proposed method starts with pre-processing the word image without affectingits main features, then calculates the directions pixel density of the word image by scanning it vertically and fromangles 30° to 90° to count the pixel density fromall directions and address the problem of overlapping letters, whichis a commonly attitude in writing Arabic texts by many people. Local minima and thresholds are also determinedto identify the ideal segmentation area. The proposed technique is tested on samples obtained fromtwo datasets: Aself-curated image dataset and the IFN/ENIT dataset. The results demonstrate that the proposed method achievesa significant improvement in the proportions of cursive segmentation of 92.96% on our dataset, as well as 89.37%on the IFN/ENIT dataset.

关键词： Arabic handwritten segmentation image processing ligature detection technique intelligent recognition

Caffeic acid 3,4-dihydroxyphenethyl ester prevents colorectal cancer through inhibition of multiple cancer-promoting signal pathways in 1,2-Dimethylhydrazine/dextran sodium sulphate mouse model

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Journal of Traditional Chinese Medicine 2024年第1期44卷 70-77页

作者： JIN Tao ZHOU Qian SHEN Jichen ZHANG Zhizhong LIAN Xiaoyuan college of Pharmaceutical Sciences Zhejiang UniversityHangzhou 310058China Pharmaceutical informatics Institute College of Pharmaceutical SciencesZhejiang UniversityHangzhou 310058China Ocean college Zhoushan Campus of Zhejiang UniversityZhoushan 316021China

OBJECTIVE:To elucidate the potential feature and mechanism of the caffeic acid 3,4-dihydroxyphenethyl ester(CADPE)molecule,which can prevent colorectal cancer(CRC)in the 1,2-Dimethylhydrazine(DMH)/dextran sodium sulphate(DSS)-induced mouse model.METHODS:Institute of cancer research(ICR)male mice were injected with 20 mg/kg DMH for a week.After that,2%DSS was administered in the drinking water for another 7 d.The CADPE treatment was given to the DMH/DSS induced male mice at three different periods until their sacrifice.Histopathological examination was used for observing the CRC development at colonic mucosa.Immunohistochemistry(IHC),blood cells smearing and crypt damage scoring methods were used for investigating the anti-inflammation feature of CADPE related to CRC.The reversing targets searching method was applied with artificial intelligence(AI),computeraided drug designing(CADD)and Ingenuity Pathway Analysis(IPA)techniques for predicting the potential targets and mechanism of CADPE highly related to CRC.RESULTS:The data indicated that CADPE inhibited CRC tumor development in the colitis-associated DMH/DSS induced mouse model after giving the early treatment.CADPE also impeded the acute inflammation by decreasing the infiltration of neutrophils significantly during the initial stage of CRC development.Finally,our data showed that CADPE prevented CRC by blocking active sites of three pivotal protein targets including epidermal growth factor receptor(EGFR),extracellular signal-regulated kinase(ERK)and mammalian target of rapamycin(m TOR)in two major cancer development pathways.CONCLUSIONS:CADPE effectively prevented CRC at early stage of tumor germination in the DMH/DSS mouse model highly likely due to its anti-acute inflammation characteristic and the ability of blocking EGFR,ERK and m TOR activities in two highly related CRC developing pathways.

关键词： caffeic acids colorectal neoplasms inflammation chemoprevention Sarcandra glabra

Product Form Solution of a Queuing-Inventory System with Lost Sales and Server Vacation

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Journal of Systems Science & Complexity 2024年第2期37卷 729-758页

作者： YUE Dequan ZHANG Yuying XU Xiuli YUE Wuyi School of Science Yanshan UniversityQinhuangdao 066004China School of Economics and Management Yanshan UniversityQinhuangdao 066004China The Kyoto college of Graduate Studies for informatics Kyoto City 606-8225Japan

In this study,the authors consider an M/M/1 queuing system with attached inventory under an(s,S)control policy.The server takes multiple vacations whenever the inventory is depleted.It is assumed that the lead time and the vacation time follow exponential distributions.The authors formulate the model as a quasi-birth-and-dearth(QBD)process and derive the stability condition of the system.Then,the stationary distribution in product form for the joint process of the queue length,the inventory level,and the server’s status is obtained.Furthermore,the conditional distributions of the inventory level when the server is on and operational,and when it is off due to a vacation,are derived.Using the stationary distribution,the authors obtain some performance measures of the system.The authors investigate analytically the effect of the server’s vacation on the performance measures.Finally,several numerical examples are presented to investigate the effects of some parameters on the performance measures,the optimal policy,and the optimal cost.

关键词： Cost function multiple vacations product form solution queuing-inventory system (s S)control policy

A convolutional neural network to detect possible hidden data in spatial domain images

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Cybersecurity 2024年第1期7卷 37-52页

作者： Jean De La Croix Ntivuguruzwa Tohari Ahmad Department of informatics Institut Teknologi Sepuluh Nopember(ITS)Kampus ITS Keputih SukoliloSurabaya60111Indonesia African Center of Excellence in the Internet of Things College of Science and TechnologyUniversity of Rwanda3900KigaliRwanda

Hiding secret data in digital multimedia has been essential to protect the data.Nevertheless,attackers with a steganalysis technique may break them.Existing steganalysis methods have good results with conventional Machine Learning(ML)techniques;however,the introduction of Convolutional Neural Network(CNN),a deep learning paradigm,achieved better performance over the previously proposed ML-based techniques.Though the existing CNN-based approaches yield good results,they present performance issues in classification accuracy and stability in the network training phase.This research proposes a new method with a CNN architecture to improve the hidden data detection accuracy and the training phase stability in spatial domain images.The proposed method comprises three phases:pre-processing,feature extraction,and classification.Firstly,in the pre-processing phase,we use spatial rich model filters to enhance the noise within images altered by data hiding;secondly,in the feature extraction phase,we use two-dimensional depthwise separable convolutions to improve the signal-to-noise and regular convolutions to model local features;and finally,in the classification,we use multi-scale average pooling for local features aggregation and representability enhancement regardless of the input size variation,followed by three fully connected layers to form the final feature maps that we transform into class probabilities using the softmax function.The results identify an improvement in the accuracy of the considered recent scheme ranging between 4.6 and 10.2%with reduced training time up to 30.81%.

关键词： Information security Spatial domain steganalysis Deep learning Convolutional neural network Infrastructure

Urban growth scenario projection using heuristic cellular automata in arid areas considering the drought impact

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Journal of Arid Land 2024年第4期16卷 580-601页

作者： TANG Xiaoyan FENG Yongjiu LEI Zhenkun CHEN Shurui WANG Jiafeng WANG Rong TANG Panli WANG Mian JIN Yanmin TONG Xiaohua college of Surveying&Geo-informatics Tongji UniversityShanghai 200092China Shanghai Key Laboratory of Space Mapping and Remote Sensing for Planetary Exploration Tongji UniversityShanghai 200092China

Arid areas with low precipitation and sparse vegetation typically yield compact urban pattern,and drought directly impacts urban site selection,growth processes,and future scenarios.Spatial simulation and projection based on cellular automata(CA)models is important to achieve sustainable urban development in arid areas.We developed a new CA model using bat algorithm(BA)named bat algorithm-probability-of-occurrence-cellular automata(BA-POO-CA)model by considering drought constraint to accurately delineate urban growth patterns and project future scenarios of Urumqi City and its surrounding areas,located in Xinjiang Uygur Autonomous Region,China.We calibrated the BA-POO-CA model for the drought-prone study area with 2000 and 2010 data and validated the model with 2010 and 2020 data,and finally projected its urban scenarios in 2030.The results showed that BA-POO-CA model yielded overall accuracy of 97.70%and figure-of-merits(FOMs)of 35.50%in 2010,and 97.70%and 26.70%in 2020,respectively.The inclusion of drought intensity factor improved the performance of BA-POO-CA model in terms of FOMs,with increases of 5.50%in 2010 and 7.90%in 2020 than the model excluding drought intensity factor.This suggested that the urban growth of Urumqi City was affected by drought,and therefore taking drought intensity factor into account would contribute to simulation accuracy.The BA-POO-CA model including drought intensity factor was used to project two possible scenarios(i.e.,business-as-usual(BAU)scenario and ecological scenario)in 2030.In the BAU scenario,the urban growth dominated mainly in urban fringe areas,especially in the northern part of Toutunhe District,Xinshi District,and Midong District.Using exceptional and extreme drought areas as a spatial constraint,the urban growth was mainly concentrated in the"main urban areas-Changji-Hutubi"corridor urban pattern in the ecological scenario.The results of this research can help to adjust urban planning and development policies.Our model is readily applicable to simulating urban grow

关键词： bat algorithm cellular automata(CA) probability-of-occurrence drought intensity algorithm-probability-of-occurrence-cellular automata(BA-POO-CA)model arid areas

Ferroptosis mediators vary in metabolic syndrome,type-2 diabetes,and hypercholesterolemia:A meta-analysis report

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Genes & Diseases 2024年第3期11卷 109-112页

作者： Indra Kundu Ashlesha Pande Tannishtha Das Susan Idicula-Thomas Biomedical informatics Centre Indian Council of Medical Research-National Institute for Research in Reproductive and Child HealthMumbaiMaharashtra 400012India Department of Biotechnology St.Xavier's CollegeKolkataWest Bengal 700016India

Metabolic syndrome(MetS)is a complex disorder characterized by the coexistence of phenotypes such as obesity,hypertension,hyperglycemia,high triglyceride level,and low level of high-density lipoprotein cholesterol.Inflammation majorly driven by oxidative stress has an overarching role in obesity and IR-mediated mechanisms leading to Mets.Besides these factors.

关键词： obesity cholesterol diabetes

Adaptive Optimal Discrete-Time Output-Feedback Using an Internal Model Principle and Adaptive Dynamic Programming

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IEEE/CAA Journal of Automatica Sinica 2024年第1期11卷 131-140页

作者： Zhongyang Wang Youqing Wang Zdzisław Kowalczuk the college of Information Science and Technology Beijing University of Chemical TechnologyBeijing 100029China IEEE the Department of Robotics and Decision Systems Faculty of ElectronicsTelecommunications and InformaticsGdańsk University of TechnologyGdansk 80-233Poland

In order to address the output feedback issue for linear discrete-time systems, this work suggests a brand-new adaptive dynamic programming(ADP) technique based on the internal model principle(IMP). The proposed method, termed as IMP-ADP, does not require complete state feedback-merely the measurement of input and output data. More specifically, based on the IMP, the output control problem can first be converted into a stabilization problem. We then design an observer to reproduce the full state of the system by measuring the inputs and outputs. Moreover, this technique includes both a policy iteration algorithm and a value iteration algorithm to determine the optimal feedback gain without using a dynamic system model. It is important that with this concept one does not need to solve the regulator equation. Finally, this control method was tested on an inverter system of grid-connected LCLs to demonstrate that the proposed method provides the desired performance in terms of both tracking and disturbance rejection.

关键词： Adaptive dynamic programming(ADP) internal model principle(IMP) output feedback problem policy iteration(PI) value iteration(VI)

Shear Let Transform Residual Learning Approach for Single-Image Super-Resolution

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Computers, Materials & Continua 2024年第5期79卷 3193-3209页

作者： Israa Ismail Ghada Eltaweel Mohamed Meselhy Eltoukhy Department of Computer Science Faculty of Computers and InformaticsSuez Canal UniversityIsmailia51422Egypt Department of Information Technology College of Computing and Information Technology at KhulaisUniversity of JeddahJeddahSaudi Arabia

Super-resolution techniques are employed to enhance image resolution by reconstructing high-resolution images from one or more low-resolution inputs.Super-resolution is of paramount importance in the context of remote sensing,satellite,aerial,security and surveillance imaging.Super-resolution remote sensing imagery is essential for surveillance and security purposes,enabling authorities to monitor remote or sensitive areas with greater clarity.This study introduces a single-image super-resolution approach for remote sensing images,utilizing deep shearlet residual learning in the shearlet transform domain,and incorporating the Enhanced Deep Super-Resolution network(EDSR).Unlike conventional approaches that estimate residuals between high and low-resolution images,the proposed approach calculates the shearlet coefficients for the desired high-resolution image using the provided low-resolution image instead of estimating a residual image between the high-and low-resolution image.The shearlet transform is chosen for its excellent sparse approximation capabilities.Initially,remote sensing images are transformed into the shearlet domain,which divides the input image into low and high frequencies.The shearlet coefficients are fed into the EDSR network.The high-resolution image is subsequently reconstructed using the inverse shearlet transform.The incorporation of the EDSR network enhances training stability,leading to improved generated images.The experimental results from the Deep Shearlet Residual Learning approach demonstrate its superior performance in remote sensing image recovery,effectively restoring both global topology and local edge detail information,thereby enhancing image quality.Compared to other networks,our proposed approach outperforms the state-of-the-art in terms of image quality,achieving an average peak signal-to-noise ratio of 35 and a structural similarity index measure of approximately 0.9.

关键词： Super-resolution shearlet transform shearlet coefficients enhanced deep super-resolution network

Refined acoustic holography via nonlocal metasurfaces

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Science China(Physics,Mechanics & Astronomy) 2024年第7期67卷 113-123页

作者： Shuhuan Xie Hongyu Ma Junmei Cao Fangshuo Mo Qian Cheng Yong Li Tong Hao Institute of Acoustics School of Physics Science and EngineeringTongji UniversityShanghai 200092China Center for Spatial Information Science and Sustainable Development Applications Tongji UniversityShanghai 200092China college of Surveying and Geo-informatics Tongji UniversityShanghai 200092China

Holography can provide the desired wavefront phase and/or amplitude for imaging,particle manipulation,bacteria trapping,and cell patterning in optics and acoustics.However,previous work on acoustic holography is mostly based on local design optimization,either using active control of the sound source or relying on the structural design to provide the desired wavefront.Achieving precise control over the acoustic field remains a significant challenge.Here,we realize refined single-plane symmetric binary amplitude,asymmetric intensity gradient amplitude,and bi-objective hologram through the non-local holographic imaging theory that considers the acoustic coupling of structural units in detail.By taking into account the self-radiation and mutual radiation between many small units on a plate of well-designed thickness,as well as the transmission through the plate's apertures,we can effectively regulate the sound field behind the plate.We demonstrate the effectiveness of our approach through numerical simulations and experiments,showcasing a circle,a black hole,and a bi-objective with a circle and a square hologram.Notably,the acoustic black hole hologram precisely reconstructs the intensity gradient distribution at two bright spots.This non-local holographic imaging theory is valuable for the fine-intensity regulation of the sound field and is expected to be applied in ultrasound diagnosis and treatment,medical imaging,and other fields.

关键词： acoustic holograms non-local interactions fine intensity modulation acoustic metasurfaces