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Thematische Bibliographien / Feature Identification and Location Experiment

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Auswahl der wissenschaftlichen Literatur zum Thema „Feature Identification and Location Experiment“

Autor: Grafiati

Veröffentlicht am 4. Juni 2021

Zuletzt aktualisiert am 29. Juli 2025

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Zeitschriftenartikel zum Thema "Feature Identification and Location Experiment"

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Almajalid, Rania, Juan Shan, Yaodong Du, and Ming Zhang. "Identification of Knee Cartilage Changing Pattern." Applied Sciences 9, no. 17 (2019): 3469. http://dx.doi.org/10.3390/app9173469.

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This paper studied the changing pattern of knee cartilage using 3D knee magnetic resonance (MR) images over a 12-month period. As a pilot study, we focused on the medial tibia compartment of the knee joint. To quantify the thickness of cartilage in this compartment, we utilized two methods: one was measurement through manual segmentation of cartilage on each slice of the 3D MR sequence; the other was measurement through cartilage damage index (CDI), which quantified the thickness on a few informative locations on cartilage. We employed the artificial neural networks (ANNs) to model the changin

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Zou, Li, and Haowen Cheng. "Research on Wind Turbine Blade Surface Damage Identification Based on Improved Convolution Neural Network." Applied Sciences 12, no. 18 (2022): 9338. http://dx.doi.org/10.3390/app12189338.

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Wind turbine blades are easily affected by the working environment and often show damage features such as cracks and surface shedding. An improved convolution neural network, ED Net, is proposed to identify their damage features. An EAC block based on the improved asymmetric convolution is introduced which strengthens the feature extraction during convolution. A DPCI_SC block, which is improved based on the attention module, is embedded to enhance the ability to obtain spatial location information of the damage. GELU is used as the activation function. The loss function is smoothed and labeled

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Ma, Haomiao, Yingfeng Xu, and Jianye Wang. "A Double Feature Extraction Method for Rolling Bearing Fault Diagnosis Based on Slope Entropy and Fuzzy Entropy." Mathematical Problems in Engineering 2022 (September 28, 2022): 1–11. http://dx.doi.org/10.1155/2022/9642550.

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Rolling bearings are the key components for the safe operation of mechanical equipment. It plays an irreplaceable role in the normal operation of mechanical equipment. Higher load makes higher failure rate of rolling bearing. Accurate identification of the fault location is an important step in the diagnosis of the rolling bearing fault. In recent years, the entropy features of rolling bearing vibration signals are usually extracted to identify fault. In this paper, a double feature extraction method based on slope entropy (SlE) and fuzzy entropy (FE) is proposed to recognize the fault state o

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Liu, Qiong, JiZhuang Hui, Li Luo, and YanPu Yang. "Target Identification and Location Algorithm Based on SURF-BRISK Operator." International Journal of Pattern Recognition and Artificial Intelligence 30, no. 06 (2016): 1655016. http://dx.doi.org/10.1142/s0218001416550168.

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Accurate and fast target image recognition is an important function of applications such as remote sensing imaging and medical imaging. However, an operator such as speeded up robust feature (SURF) cannot be accurately matched in the recognition process of a target image. This led us to propose the use of a method capable of matching identification, i.e. binary robust invariant scalable keypoints (BRISK) operators, in combination with SURF operators. The proposed algorithm combines the accuracy of SURF operators and the rapidity of BRISK operators to obtain a quick and accurate way of matching

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Pathmakumar, Thejus, M. A. Viraj J. Muthugala, S. M. Bhagya P. Samarakoon, Braulio Félix Gómez, and Mohan Rajesh Elara. "A Novel Path Planning Strategy for a Cleaning Audit Robot Using Geometrical Features and Swarm Algorithms." Sensors 22, no. 14 (2022): 5317. http://dx.doi.org/10.3390/s22145317.

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Robot-aided cleaning auditing is pioneering research that uses autonomous robots to assess a region’s cleanliness level by analyzing the dirt samples collected from various locations. Since the dirt sample gathering process is more challenging, adapting a coverage planning strategy from a similar domain for cleaning is non-viable. Alternatively, a path planning approach to gathering dirt samples selectively at locations with a high likelihood of dirt accumulation is more feasible. This work presents a first-of-its-kind dirt sample gathering strategy for the cleaning auditing robots by combinin

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Boal, Jaime, Álvaro Sánchez-Miralles, and Manuel Alvar. "Matching monocular lightweight features using N-gram techniques for topological location identification." Robotica 33, no. 9 (2014): 1835–49. http://dx.doi.org/10.1017/s0263574714001076.

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SUMMARYIn SLAM (simultaneous localization and mapping), the topological paradigm provides a more natural and compact solution that scales better with the size of the environment. Computer vision has always been regarded as the ideal sensor technology for topological feature extraction and description and several methods have been proposed in the literature, but they are either time-consuming, require plenty of different sensors, or are very sensitive to perceptual aliasing, all of which limit their application scope.This paper presents a fast-to-compute collection of features extracted from mo

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Homberg, Nicolas, Mariana Galvão Ferrarini, Christine Gaspin, and Marie-France Sagot. "MicroRNA Target Identification: Revisiting Accessibility and Seed Anchoring." Genes 14, no. 3 (2023): 664. http://dx.doi.org/10.3390/genes14030664.

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By pairing to messenger RNAs (mRNAs for short), microRNAs (miRNAs) regulate gene expression in animals and plants. Accurately identifying which mRNAs interact with a given miRNA and the precise location of the interaction sites is crucial to reaching a more complete view of the regulatory network of an organism. Only a few experimental approaches, however, allow the identification of both within a single experiment. Computational predictions of miRNA–mRNA interactions thus remain generally the first step used, despite their drawback of a high rate of false-positive predictions. The major compu

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Zeng, Jiang, Guang-Zhong Cao, Ye-Ping Peng, and Su-Dan Huang. "A Weld Joint Type Identification Method for Visual Sensor Based on Image Features and SVM." Sensors 20, no. 2 (2020): 471. http://dx.doi.org/10.3390/s20020471.

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In the field of welding robotics, visual sensors, which are mainly composed of a camera and a laser, have proven to be promising devices because of their high precision, good stability, and high safety factor. In real welding environments, there are various kinds of weld joints due to the diversity of the workpieces. The location algorithms for different weld joint types are different, and the welding parameters applied in welding are also different. It is very inefficient to manually change the image processing algorithm and welding parameters according to the weld joint type before each weld

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Cui, Lei, Qing Zhu, and Jing Kang Zhang. "Algorithm Study of Edge Location and Feature Measurement of Building Surface Crack Images." Applied Mechanics and Materials 380-384 (August 2013): 1045–49. http://dx.doi.org/10.4028/www.scientific.net/amm.380-384.1045.

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Old buildings surface cracks are more obvious with the accumulation of its disrepair, which will impact aesthetics, durability and even threaten the safety of persons and properties if feature values surpass the security thresholds. In this paper, firstly, the algorithm of the improved Canny operator gray threshold edge detection and location, based on traditional differential operators and sub-pixel positioning algorithms, achieve coarse location, furthermore, the sub-pixel location algorithm of Gaussian curve fitting based on neighbor gradient features realize sub-pixel precision positioning

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Li, Zhaoyang, Ping Xu, Jie Xing, and Chengxing Yang. "SDFormer: A Novel Transformer Neural Network for Structural Damage Identification by Segmenting the Strain Field Map." Sensors 22, no. 6 (2022): 2358. http://dx.doi.org/10.3390/s22062358.

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Damage identification is a key problem in the field of structural health monitoring, which is of great significance to improve the reliability and safety of engineering structures. In the past, the structural strain damage identification method based on specific damage index needs the designer to have rich experience and background knowledge, and the designed damage index is hard to apply to different structures. In this paper, a U-shaped efficient structural strain damage identification network SDFormer (structural damage transformer) based on self-attention feature is proposed. SDFormer rega

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Dissertationen zum Thema "Feature Identification and Location Experiment"

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Dingus, Cheryl Ann Venard. "Designs and methods for the identification of active location and dispersion effects." Columbus, Ohio : Ohio State University, 2005. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1133203441.

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Al-Msie', Deen Ra'Fat. "Construction de lignes de produits logiciels par rétro-ingénierie de modèles de caractéristiques à partir de variantes de logiciels : l'approche REVPLINE." Thesis, Montpellier 2, 2014. http://www.theses.fr/2014MON20024/document.

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Les lignes de produits logicielles constituent une approche permettant de construire et de maintenir une famille de produits logiciels similaires mettant en œuvre des principes de réutilisation. Ces principes favorisent la réduction de l'effort de développement et de maintenance, raccourcissent le temps de mise sur le marché et améliorent la qualité globale du logiciel. La migration de produits logiciels similaires vers une ligne de produits demande de comprendre leurs similitudes et leurs différences qui s'expriment sous forme de caractéristiques (features) offertes. Dans cette thèse, nous no

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Ghabach, Eddy. "Prise en charge du « copie et appropriation » dans les lignes de produits logiciels." Thesis, Université Côte d'Azur (ComUE), 2018. http://www.theses.fr/2018AZUR4056/document.

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Une Ligne de Produits Logiciels (LPL) supporte la gestion d’une famille de logiciels. Cette approche se caractérise par une réutilisation systématique des artefacts communs qui réduit le coût et le temps de mise sur le marché et augmente la qualité des logiciels. Cependant, une LPL exige un investissement initial coûteux. Certaines organisations qui ne peuvent pas faire face à un tel investissement, utilisent le « Clone-and-own » C&O pour construire et faire évoluer des familles de logiciels. Cependant, l'efficacité de cette pratique se dégrade proportionnellement à la croissance de la fam

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Kulkarni, Raghavendra B. "Inverse problems solution using spectral finite element methods." Thesis, 2021. https://etd.iisc.ac.in/handle/2005/5471.

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Inverse problems are very challenging as these problems involve, finding the cause by analyzing the effects. In structural dynamics problems, the effects are normally measured in terms of dynamic responses in structures. These responses which are used to find the cause generally have partial data, embedded with measurement noise, and are truncated. Due to these problems, inverse problems are generally ill-posed in most cases as against forward problems. In this dissertation, we solve five different types of inverse problems involving high-frequency transient loads. All these problems are sol

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Bücher zum Thema "Feature Identification and Location Experiment"

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Wilson, R. Gale. Radiometric responsivity determination for Feature Identification and Location Experiment (FILE) flown on Space Shuttle Mission 41-G. Langley Research Center, 1986.

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Radiometric responsivity determination for Feature Identification and Location Experiment (FILE) flown on Space Shuttle Mission 41-G. National Aeronautics and Space Administration, Scientific and Technical Information Branch, 1987.

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Buchteile zum Thema "Feature Identification and Location Experiment"

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Xu, Dawei, Yijie She, Zhonghua Tan, Ruiguang Li, and Jian Zhao. "Research on the Recognition of Internet Buzzword Features Based on Transformer." In Communications in Computer and Information Science. Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-8285-9_17.

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AbstractAccurate identification of Internet buzzwords plays an important role in positive Internet opinion guidance. A Transformer-based Internet buzzword feature recognition system was designed to address this problem. The traditional way of crawling data has been improved, a real-time crawling module has been added, and an Internet buzzword corpus has been constructed by itself. The traditional way of crawling data has been improved, a real-time crawling module has been added, and an Internet buzzword corpus has been constructed by itself. Traditional machine learning models suffer from grad

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Sui, Jianan, Yuehui Chen, Yi Cao, and Yaou Zhao. "Accurate Identification of Submitochondrial Protein Location Based on Deep Representation Learning Feature Fusion." In Lecture Notes in Computer Science. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-4749-2_50.

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Abhayadev, Malayil, and T. Santha. "Visual Importance Identification of Natural Images Using Location-Based Feature Selection Saliency Map." In Proceedings of International Conference on Artificial Intelligence, Smart Grid and Smart City Applications. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-24051-6_53.

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Vasumathy, M., and Mythili Thirugnanam. "An Integrated Approach for Optimal Feature Selection and Anatomic Location Identification on Pediatric Foreign Body Aspired Radiographic Images." In Knowledge Computing and its Applications. Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-8258-0_6.

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Dong, Zhipeng, Lei Chen, Weixing Song, Yangshuo Liu, and Jianshe Kang. "Bearing Fault Location Based on Feature Visualization of Convolutional Neural Network." In Advances in Transdisciplinary Engineering. IOS Press, 2022. http://dx.doi.org/10.3233/atde220042.

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In industrial production, bearing is one of the most common and indispensable key components. It is of great significance to prevent safety accidents caused by bearing failure, timely fault type identification, and accurate fault location positioning. In this paper, we propose a method for bearing fault location based on feature visualization of convolutional neural network (CNN). In this method, the bearing vibration signals are transformed into images and the Grad-CAM feature visualization method is used to find the feature regions of the images. Thus, the points of the feature regions are t

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Rose Bindu Joseph P. and Ezhilmaran Devarasan. "Fuzzy Techniques for Content-Based Image Retrieval." In Feature Dimension Reduction for Content-Based Image Identification. IGI Global, 2018. http://dx.doi.org/10.4018/978-1-5225-5775-3.ch003.

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Content-based image retrieval aims to acquire images from huge databases by analyzing their visual features like color, texture, shape, and spatial relationship. The search for superior accuracy in image retrieval has resulted in concentrating more on semantic gap reduction between the low-level features and high level human reasoning. Fuzzy theory is a prevailing methodology which helps in attaining this goal by using attributes and interpretations similar to human reasoning. The vagueness and impreciseness in image data and the retrieval process can be modeled by fuzzy sets. This chapter ana

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Iso Hayate, Wakamiya Shoko, and Aramaki Eiji. "Conditional Density Estimation of Tweet Location: A Feature-Dependent Approach." In Studies in Health Technology and Informatics. IOS Press, 2017. https://doi.org/10.3233/978-1-61499-830-3-408.

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Twitter-based public health surveillance systems have achieved many successes. Underlying this success, much useful information has been associated with tweets such as temporal and spatial information. For fine-grained investigation of disease propagation, this information is attributed a more important role. Unlike temporal information that is always available, spatial information is less available because of privacy concerns. To extend the availability of spatial information, many geographic identification systems have been developed. However, almost no origin of the user location can be ide

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Cooper, Geoffrey M., and Kenneth W. Adams. "The Nucleus." In The Cell. Oxford University Press, 2022. http://dx.doi.org/10.1093/hesc/9780197583746.003.0013.

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10.1 The Nuclear Envelope and Traffic between the Nucleus and the Cytoplasm 10.2 The Organization of Chromatin 10.3 Nuclear Bodies MOLECULAR MEDICINE Nuclear Lamina Diseases KEY EXPERIMENT Identification of Nuclear Localization Signals The presence of a nucleus is the principal feature that distinguishes eukaryotic from...

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Takahashi, Masaki, Mahito Fujii, Masahiro Shibata, Nobuyuki Yagi, and Shin’ichi Satoh. "Automatic Pitch Type Recognition System from Single-View Video Sequences of Baseball Broadcast Videos." In Methods and Innovations for Multimedia Database Content Management. IGI Global, 2012. http://dx.doi.org/10.4018/978-1-4666-1791-9.ch008.

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This article describes a system that automatically recognizes individual pitch types like screwballs and sliders in baseball broadcast videos. These decisions are currently made by human specialists in baseball, who are watching the broadcast video of the game. No automatic system has yet been developed for identifying individual pitch types from single view camera images. Techniques using multiple fixed cameras promise highly accurate pitch type identification, but the systems tend to be large. Our system is designed to identify the same pitch types using only the same single-view broadcast b

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Wolfe, Jeremy M., Dennis M. Levi, Lori L. Holt, et al. "Perceiving and Recognizing Objects." In Sensation & Perception. Oxford University Press, 2024. https://doi.org/10.1093/hesc/9780197663813.003.0005.

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This chapter explores the mechanisms enabling the brain to perceive and recognize objects, starting from simple visual features to complex object identification. It details the transition from early processing of edges and lines in the primary visual cortex (V1) to advanced analysis in the extrastriate and inferotemporal regions, highlighting the “what” and “where” pathways that distinguish object identity from spatial location. Midlevel vision addresses challenges in object perception, such as recognizing occluded or ambiguous objects, by organizing basic visual inputs into coherent entities

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Konferenzberichte zum Thema "Feature Identification and Location Experiment"

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Zhou, Kun, Youzhuo Zheng, Jiangfeng Yan, Jian Gu, and Qi Zhou. "Accurate Identification and Location Technology of Fault Types based on Multi-Dimensional Feature Fusion Analysis Algorithm." In 2025 3rd International Conference on Integrated Circuits and Communication Systems (ICICACS). IEEE, 2025. https://doi.org/10.1109/icicacs65178.2025.10968998.

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Liu, Ming, and David Chelidze. "Local Flow Variation Method for Damage Identification." In ASME 2005 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2005. http://dx.doi.org/10.1115/detc2005-85142.

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In this paper, a damage identification method called local flow variation is introduced. It is a practical implementation of a phase space warping concept. A hierarchical dynamical system is considered where a slow-time damage process causes drifts in the parameters of fast-time system describing measurable response of a structure. The method is based on the hypothesis that the probability distribution function of the fast-time trajectory in its phase space is a function of damage state. In this method, an ensemble of estimated expectations of trajectory in different locations of the reconstru

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YAJIMA, YOSHIYUKI, MURTUZA PETLADWALA, TAKAHIRO KUMURA, and CHUL-WOO KIM. "NATURAL FREQUENCY AND DISPLACEMENT RATIO BASED PROBABILISTIC DAMAGE IDENTIFICATION FOR BRIDGES USING FE MODEL UPDATE." In Structural Health Monitoring 2023. Destech Publications, Inc., 2023. http://dx.doi.org/10.12783/shm2023/37012.

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This paper proposes a natural frequency and displacement ratio-based probabilistic damage identification method for bridges using the finite element (FE) model update. When the damage location is known, it can be detected from an appropriate damagesensitive feature (DSF). However, damaged components are seldom known before inspections. This makes it difficult to find an appropriate DSF and damage identification is sometimes challenging. This paper aims to propose a method to solve this issue by integrating multiple DSFs, natural frequencies and displacement ratio, as a decisionlevel data fusio

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Senousy, Mohamed S., Tamer M. Khattab, Mohamed Al-Qaradawi, and Mohamed S. Gadala. "Identifying Crack Parameters in Slow Rotating Machinery Using Vibration Measurements and Hybrid Neuro-Particle Swarm Technique." In ASME 2010 International Mechanical Engineering Congress and Exposition. ASMEDC, 2010. http://dx.doi.org/10.1115/imece2010-39084.

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Low-cycle fatigue-initiated cracks may result in failure in slow-rotating equipments. Online monitoring to identify such fault/crack parameters, namely crack size and crack location, would be critical in providing an early warning signal to the operator and would be used in calculating estimate about the remaining safe life of the equipment in operation. In an earlier study, a scaled-down slow-rotating washer drum was constructed to experimentally investigate the vibrations of a cracked rotor and/or drums. Cracks were simulated using the bolt removal method (BRM), and the vibration signals ide

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Hou, Dongsheng, Weican Guo, and Jinyang Zheng. "A Method of Automatic Defect Recognition for Phased Array Ultrasonic Inspection of Polythene Electro-Fusion Joints." In ASME 2015 Pressure Vessels and Piping Conference. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/pvp2015-45397.

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Defect classification is the basis of defect safety assessment because defects of different types can lead to failure in different forms. However, the identification of defect type has long been a critical issue in ultrasonic inspection. Wave acoustic was applied in this study to investigate the sound scattering of metal wires in polyethylene (PE), which provided theoretical support for ultrasonic feature extraction. A method of defect recognition for PE electro-fusion (EF) joints was proposed based on pattern recognition of ultrasonic inspection images. According to location, shape, signal in

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Kazato, H., S. Hayashi, T. Kobayashi, et al. "Incremental Feature Location and Identification in Source Code." In 2013 17th European Conference on Software Maintenance and Reengineering (CSMR 2013). IEEE, 2013. http://dx.doi.org/10.1109/csmr.2013.52.

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Hayashi, Shinpei, Hiroshi Kazato, Takashi Kobayashi, et al. "Guiding Identification of Missing Scenarios for Dynamic Feature Location." In 2016 23rd Asia-Pacific Software Engineering Conference (APSEC). IEEE, 2016. http://dx.doi.org/10.1109/apsec.2016.068.

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Delaune, Xavier, Philippe Piteau, Vincent Debut, and Jose Antunes. "Experimental Validation of Inverse Techniques for the Remote Identification of Impact Forces in Gap-Supported Systems Subjected to Local and Flow Turbulence Excitations." In ASME 2010 Pressure Vessels and Piping Division/K-PVP Conference. ASMEDC, 2010. http://dx.doi.org/10.1115/pvp2010-26133.

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Predictive computations of the nonlinear dynamical responses of gap-supported tubes subjected to flow excitation have been the subject of active research. Nevertheless, experimental results are still necessary, for validation of the theoretical predictions as well as for asserting the integrity of field components. Because carefully instrumented test tubes and tube-supports are seldom possible, due to space limitations and to the severe environment conditions, there is a need for robust techniques capable of extracting relevant information from the actual vibratory response data. Although at t

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Lall, Pradeep, Tony Thomas, and Ken Blecker. "Prognostics and RUL Estimations of SAC305, SAC105 and SnAg Solders Under Temperature and Vibration Using Long Short-Term Memory (LSTM) Deep Learning." In ASME 2021 International Technical Conference and Exhibition on Packaging and Integration of Electronic and Photonic Microsystems. American Society of Mechanical Engineers, 2021. http://dx.doi.org/10.1115/ipack2021-74066.

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Abstract Prognostics and Remaining Useful Life (RUL) estimations of complex systems are essential to operational safety, increased efficiency, and help to schedule maintenance proactively. Modeling the remaining useful life of a system with many complexities is possible with the rapid development in the field of deep learning as a computational technique for failure prediction. Deep learning can adapt to multivariate parameters complex and nonlinear behavior, which is difficult using traditional time-series models for forecasting and prediction purposes. In this paper, a deep learning approach

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Nakano, Milsuo, Masao Nagamatsu, Kohei Suzuki, and Takuya Yoshimura. "Acoustic Double Holography Method and its Application to Engine Noise Research." In ASME 1997 Design Engineering Technical Conferences. American Society of Mechanical Engineers, 1997. http://dx.doi.org/10.1115/detc97/vib-3799.

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Abstract The acoustic holography (AH) method with single measuring plane has been well known as the conventional method and can be implemented by far field measurement with simple instruments. However, the noise source resolution of the AH is not sufficient. In order to improve the resolution in the noise source identification, several kinds of the acoustic holography methods have been so far proposed. For example, the near field acoustic holography (NAH) can provide high and accurate resolution of the holography by the nearfield measurement. However, the nearfield measurement within one wave

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Berichte der Organisationen zum Thema "Feature Identification and Location Experiment"

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Chen, Weixing. PR-378-083601-R02 Effect of Pressure Fluctuations on Growth Rate of Near-Neutral pH SCC. Pipeline Research Council International, Inc. (PRCI), 2017. http://dx.doi.org/10.55274/r0011010.

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This report summarizes the work completed in Phase 1 and Phase 2 of PRCI SCC-2-12 project: Effect of Pressure Fluctuations on Growth Rate of Near-Neutral pH SCC. The following two insights from the two-phase PRCI SCC 2-12 project can be proven to be the most important: 1) The identification of three types of pressure fluctuations and their different susceptibility to crack growth; 2) The importance of load interaction effects during variable amplitude pressure fluctuations in the prediction of crack growth rate. The work has enabled us to divide near-neutral pH SCC cracking into the following

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Kerber, Steve. Study of the Effectiveness of Fire Service Vertical Ventilation and Suppression Tactics in Single Family Homes. UL Firefighter Safety Research Institute, 2013. http://dx.doi.org/10.54206/102376/iwzc6477.

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Under the United States Department of Homeland Security (DHS) Assistance to Firefighter Grant Program, Underwriters Laboratories examined fire service ventilation and suppression practices as well as the impact of changes in modern house geometries. There has been a steady change in the residential fire environment over the past several decades. These changes include larger homes, more open floor plans and volumes, and increased synthetic fuel loads. This investigation examined the influence of these changes to the fire behavior and subsequent impact on firefighter tactics relative to horizont

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Ueti, Massaro Wilson, and Monica Leszkowicz Mazuz. Identification, characterization and testing of geographically conserved Babesia bovis vaccine antigen candidates. United States-Israel Binational Agricultural Research and Development Fund, 2022. http://dx.doi.org/10.32747/2022.8134143.bard.

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During the development of this project, we selected four potential B. bovis antigens for a subunit vaccine to prevent the clinical signs of acute bovine babesiosis. Selection of the target antigens was based on: (1) profile of expression in parasite blood stages; (2) prediction for protein location on the parasite surface and/or on the surface of infected red blood cells; and (3) target conservation between US and Israeli strains of B. bovis. Following these criteria, the B. bovis targets BBOV_IV009170, BBOV_III007410, BBOV_II001790, and BBOV_III008720 were selected. Full-length genomic sequen

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