Browse Topic: Identification

Items (10,275)
Identification of different types of turns during field operation of off-road vehicles is critical in the overall vehicle development as it is helpful in identifying & optimizing machine performance, correct duty cycle, fuel economy, stability analysis, accurate path planning, customer usage pattern & designing the critical components, etc. In this study, a machine learning (ML) based methodology has been developed to detect the off-road vehicle turns using vehicle & GPS parameters. Three most common types of off-road vehicles turn conditions e.g., Straight line, Bulb turn, and Three-Point turn have been considered. Different vehicle parameters (like latitude & longitude, compass bearing, yaw rate, vehicle speed, swash plate angle, engine speed, percent load at vehicle speed, raise lower front & PTO channels) generated during field test have been used here. These vehicle parameters are further processed, analysed and used in ML learning model building. Four ML models e.g., SVM, K-NN
Rai, RohitGangsar, Purushottam
The reliability and durability of off-highway vehicles are crucial for industries like construction, mining, and agriculture. Failures in such machines not only disrupt operations but can also lead to significant economic losses and safety concerns. Effective failure and warranty analysis processes are essential to improve customer support, minimize downtime, and enhance equipment life cycle. This paper outlines a comprehensive 7-step failure analysis methodology tailored for off-highway vehicles, accompanied by warranty analysis using Weibull, 6MIS, and 12MIS IPTV. It details the process from problem identification through permanent solution implementation, emphasizing tools and techniques necessary for sustainable improvements. The structured approach provides an actionable blueprint for OEMs and service teams to enhance customer satisfaction, support sustainable development goals, and maintain regulatory compliance.
Mulla, TosifThakur, AnilTripathi, Ashish
This specification covers a fluorosilicone (FVMQ) rubber in the form of molded rings.
AMS CE Elastomers Committee
In order to explore the actual safety management effect of safety signs and better carry out on-site safety management, this article independently developed an evaluation scale for the management effect of safety signs. Taking a certain marine engineering equipment manufacturing enterprise as the object, the management of safety signs was evaluated and analyzed. Firstly, 11 questions from the SPSSAU online analysis scale were selected as measurement indicators to test safety label management. Factor analysis was used to select three factors: cognitive function, compliance behavior, and leadership attitude. Secondly, a safety identification management model was constructed based on structural equation modeling (SEM) with three factors as latent variable factors. Through fitting tests, it was found that cognitive effects, compliance behaviors, and leadership attitudes have a certain impact on management effectiveness, and there is a positive correlation between the three latent variable
Wang, ChunyuanYang, GuihuaLi, XinyaoZhu, Jie
This specification establishes the performance requirements for the identification of wire and cable by indirect markings that have been applied to electrical insulating materials including heat shrink sleeving, wrap around labels and “tie-on” tags as well as any other types of materials used for indirect marking. This specification covers the processes used to mark these materials, including impact ink marking, thermal transfer, hot stamp, and lasers, etc. This specification does not cover the direct marking on insulated electrical wires and cables.
AE-8A Elec Wiring and Fiber Optic Interconnect Sys Install
This specification covers tungsten carbide-cobalt in the form of powder.
AMS F Corrosion and Heat Resistant Alloys Committee
Our research focuses on developing a novel loss function that significantly improves object matching accuracy in multi-robot systems, a critical capability for Safety, Security, and Rescue Robotics (SSRR) applications. By enhancing the consistency and reliability of object identification across multiple viewpoints, our approach ensures a comprehensive understanding of environments with complex layouts and interlinked infrastructure components. We utilize ZED 2i cameras to capture diverse scenarios, demonstrating that our proposed loss function, inspired by the DETR framework, outperforms traditional methods in both accuracy and efficiency. The function’s ability to adapt to dynamic and high-risk environments, such as disaster response and critical infrastructure inspection, is further validated through extensive experiments, showing superior performance in real-time decision-making and operational effectiveness. This work not only advances the state of the art in SSRR but also
Brown, Taylor J.Vincent, GraceNakamoto, KyleBhattacharya, Sambit
This SAE Standard establishes the minimum circuit identification and requirements for Multi-Voltage Power Distribution Systems (MVPDS) for use on trucks and buses. A Multi-Voltage Power Distribution System is one that distributes two or three voltages, up to 60 VDC, to power the controls, instruments, and devices.
Truck and Bus Electrical Systems Committee
This specification covers procedures for tab marking of bare welding wire to provide positive identification of cut lengths and spools.
AMS B Finishes Processes and Fluids Committee
This standard establishes the dimensional and visual quality requirements, lot requirements, and packaging and labeling requirements for O-rings molded from AMS7274 rubber. It shall be used for procurement purposes.
A-6C2 Seals Committee
E-25 General Standards for Aerospace and Propulsion Systems
This SAE Aerospace Standard (AS) provides requirements for design and installation of aircraft jacking pad adapters and the mating jack socket interface to permit use of standard jacking equipment to be used in civil and military transport aircraft. The adapter defined herein shall be the key interface between the aircraft and the aircraft jack(s).
AGE-3 Aircraft Ground Support Equipment Committee
This paper presents an analytical approach for identifying suspension kingpin alignment parameters based on screw axis theorem and differential calculation model. The suspension kingpin caster and inclination alignment parameters can produce additional tire force, which affects vehicle handling dynamics. In wheel steering process, the multi-link suspension control arms lead to movement of the imaginary kingpin, which can cause change in suspension kingpin alignment parameters. According to the structure mechanism of commercial vehicle multi-link independent suspension, the kinematics characteristics of imaginary kingpin were analyzed based on the screw axis theorem. The angular velocity and translation velocity vectors were calculated. In order to avoid the influence of bushing deformation, the unique differential identification model was established to evaluate the suspension kingpin alignment parameters, and the identification results were compared with the ADAMS/Car data. The
Ding, JinquanHou, JunjianZhao, DengfengGuo, Yaohua
There is an increasing effort to reduce noise pollution across different industries worldwide. From a transportation standpoint, pass-by regulations aim to achieve this and have been implementing increasingly stricter emissions limits. Testing according to these standards is a requirement for homologation, but does little to help manufacturers understand why their vehicles may be failing to meet limits. Using a developed methodology such as Pass-by Source Path Contribution (SPC, also known as TPA) allows for identification of dominant contributors to the pass-by receivers along with corresponding acoustic source strengths. This approach is commonly used for passenger vehicles, but can be impractical for off-highway applications, where vehicles are often too large for most pass-by-suitable chassis dynamometers. A hybrid approach is thereby needed, where the same techniques and instrumentation used in the indoor test are applied to scenarios in an outdoor environment. This allows for
Freeman, ToddEngels, BretThuesen, Ben
This paper discusses a systematic process that was developed to evaluate the acoustic performance of a production dash system. In this case it is for an electric vehicle application. The production dash panel was tested under different configurations to understand the importance of passthroughs in the acoustics of the system. Results show that often the performance of the passthroughs strongly affects the overall performance of the dash system and this may become the limiting factor to increase the system sound transmission loss. To understand the acoustic strength of different passthroughs and their effects on the overall system, the dash with passthroughs underwent extensive testing. Subsequently, a test procedure using flat panels was developed to quantify the performance of individual passthroughs on a part level. This data can be used by the OEM to develop STL targets that can be considered in the grommet design early in the vehicle development process.
Saha, PranabBaack, GregoryGeissler, ChristianKaluvakota, SrikanthPilz, Fernando
This paper introduces a novel, automated approach for identifying and classifying full vehicle mode shapes using Graph Neural Networks (GNNs), a deep learning model for graph-structured data. Mode shape identification and naming refers to classifying deformation patterns in structures vibrating at natural frequencies with systematic naming based on the movement or deformation type. Many times, these mode shapes are named based on the type of movement or deformation involved. The systematic naming of mode shapes and their frequencies is essential for understanding structural dynamics and “Modal Alignment” or “Modal Separation” charts used in Noise, Vibration and Harshness (NVH) analysis. Current methods are manual, time-consuming, and rely on expert judgment. The integration of GNNs into mode shape classification represents a significant advancement in vehicle modal identification and structure design. Results demonstrate that GNNs offer superior accuracy and efficiency compared to
Tohmuang, SitthichartSwayze, James L.Fard, MohammadFayek, HaythamMarzocca, PiergiovanniBhide, SanjayHuber, John
This SAE Aerospace Standard (AS) establishes minimum requirements for eddy current inspection of circular holes in nonferrous, metallic, low conductivity (less than 5% IACS) aircraft engine hardware with fasteners removed. The inspection is intended to be performed at maintenance and overhaul facilities on engine run hardware.
AMS K Non Destructive Methods and Processes Committee
This SAE Aerospace Standard (AS) defines the requirements for a convoluted polytetrafluoroethylene (PTFE) lined, metallic reinforced, hose assembly suitable for use in aerospace fluid systems at temperatures between -65 °F and 400 °F for Class 1 assembly, -65 °F and 275 °F for Class 2 assembly, and at operating pressures per Table 1. The use of these hose assemblies in pneumatic storage systems is not recommended. In addition, installations in which the limits specified herein are exceeded, or in which the application is not covered specifically by this standard, shall be subject to the approval of the procuring activity.
G-3, Aerospace Couplings, Fittings, Hose, Tubing Assemblies
Blistering in aesthetic parts poses a significant challenge, affecting overall appearance and eroding brand image from the customer's perspective and blister defects disrupt painting line efficiency, resulting in increased rework and rejection rates. This paper investigates the causes and effects of blistering, particularly in the context of internal soundness of Aluminum castings, emphasizing the crucial role of Computed Tomography in defect analysis. Computed Tomography is an advanced Non-Destructive Testing technique used to examine the internal soundness of a material. This study follows a structured 7-step QC story approach, from problem identification to standardization, to accurately identify the root Cause and implement corrective actions to eliminate blister defect. The findings reveal a strong link between internal soundness and surface quality. Based on the root cause, changes in the casting process and die design were made to improve internal soundness, leading to reduced
D, BalachandarNataraj, Naveenkumar
In this work, a modified Ahmed body with both upsweep and downsweep was used to create a complex wake. The time-averaged streamline topology revealed that the wake was composed primarily of a torus past the vertical base and two pairs of streamwise-oriented vortices on the upper and lower slant edges. Several vortex identification methods including three-dimensional (3D) (Q−, λ2−, Ω−criteria, and Liutex method) and two-dimensional (2D) (Γ1−criterion) methods were compared to determine the effectiveness in identifying complex wake structures. Of the 3D methods analyzed, none produced wholly satisfactory results. The Q− and λ2−criteria were plagued by well noted issues; failing to separate shear from rotation and threshold sensitivity which led to inconsistently identifying the weaker torus. The Ω−criterion addressed all of these concerns, especially identifying the torus consistently. However, the identified torus structure did not reflect the physical structure observed using the
Aultman, MatthewDuan, Lian
To address the issue of signal aliasing when multiple particles pass through a metallic particle sensor, which can lead to misidentification of particle count, we employ numerical simulation methods for an in-depth investigation. We developed a mathematical model of a three-coil inductive metal particle sensor to explore the signal variations induced by the passage of a single particle. We utilized micro-element simulation analysis to dissect the signal generated by a single particle, elucidating the underlying change process. Focusing on dual ferromagnetic particles as the subject of study, we conducted simulations and demodulation of the induced voltage under various combinations of sizes and spacings to investigate the influence patterns of dual adjacent ferromagnetic particles on the sensor's induced signal. Further research into the peak signals of different diameter particles at a constant spacing revealed that, for a given spacing, the ratio of peak signals between particles of
Chen, SenShen, YitaoQiang, GuiyanZheng, ZhengWang, ZheyuHao, YinHu, Ting
This SAE Recommended Practice provides the lighting function identification codes for use on all passenger vehicles, trucks, trailers, motorcycles, and emergency vehicles.
Lighting Standard Practices Committee
Innovators at NASA Johnson Space Center have developed an adaptable Radio Frequency Identification (RFID) system that optimizes transmission for priority data as targets move in and out of passive coverage areas. The method extends the range, and reduces data latency, of ultra-low power battery-assisted passive (BAP) RFID sensor tags, improving previously developed store-and-forward techniques to support autonomous operations in complex environments where RFID interrogator access may be strained.
This standard will apply primarily to the vehicle classes identified in SAE J3194. It provides a schema for utilizing alphanumeric values to represent identifying information such as the manufacturer or vehicle provider, year of manufacture, model, vehicle type, weight, width, speed, and power source. Although conceptually similar to a Vehicle Identification Number (VIN), this standard does not classify or intend to suggest classification of these vehicles as motor vehicles for regulatory or safety data purposes. The location for placement of these identifiers on the vehicle, type of label, permanence, and visibility are out of scope for this document.
Powered Micromobility Vehicles Committee
In intelligent transportation systems (ITS), traffic flow prediction is a necessary tool for effective traffic management. By identifying and extracting key nodes in the network, it is possible to achieve efficient traffic flow prediction of the whole network using “partial” nodes, as the key nodes contain essential information about changes in the state of the traffic network. This paper proposes a key node identification method based on revised penalty local structure entropy (RPLE) for specific traffic networks. This method takes into account the influence of node distance and traffic flow on identifying important nodes within the traffic network. By introducing a modified penalty term and a comprehensive weight, it achieves a certain level of accuracy in traffic flow prediction using data from key nodes in the network. We compared the RPLE method with different key node identification methods and combined it with different prediction models to compare the traffic flow prediction
Shu, XinRan, Bin
This paper presents advanced intelligent monitoring methods aimed at enhancing the quality and durability of asphalt pavement construction. The study focuses on two critical tasks: foreign object detection and the uniform application of tack coat oil. For object recognition, the YOLOv5 algorithm is employed, which provides real-time detection capabilities essential for construction environments where timely decisions are crucial. A meticulously annotated dataset comprising 4,108 images, created with the LabelImg tool, ensures the accurate detection of foreign objects such as leaves and cigarette butts. By utilizing pre-trained weights during model training, the research achieved significant improvements in key performance metrics, including precision and recall rates. In addition to object detection, the study explores color space analysis through the HSV (Hue, Saturation, Value) model to effectively differentiate between coated and uncoated pavement areas following the application of
Hu, YufanFan, JianweiTang, FanlongMa, Tao
The rapid expansion of metro systems in major cities worldwide has resulted in the accumulation of vast amounts of travel data through Automatic Fare Collection (AFC) systems. While this data is crucial for enhancing and optimizing transportation networks, it also raises significant concerns regarding passenger privacy due to the potential exposure of individual travel patterns. In this paper, we propose a novel privacy risk assessment model aimed at quantifying the uniqueness of travel trajectories and evaluating the associated privacy threats. Utilizing AFC data from Chengdu collected in March 2021, we first employ an information entropy approach to assess the uniqueness of travel trajectories across different time granularities. We then apply the K-Means clustering algorithm to classify these trajectories into categories based on their uniqueness levels, enabling us to investigate how factors like travel time and routes influence trajectory uniqueness. To further understand the
Fan, XiaotingQu, XuYang, Hongtai
This material type has resistance to hot air, but generally has poor resistance to fuels and lubricants, but usage is not limited to such applications. Each application should be considered separately. This material type has a typical service temperature range of -85 to 500 °F (-65 to 260 °C). The operating temperature range of the material is a general temperature range, but the presence of particular fluids and design parameters may modify this range. Recommendations on the material selection are based on available technical data and are offered as suggestions only. Each user should make his own tests to determine the suitability for his own particular use.
A-6C2 Seals Committee
In recent years, Additive Manufacturing (AM), more especially Fused Deposition Modeling (FDM), has emerged as a very promising technique for the production of complicated forms while using a variety of materials. Polyethylene Terephthalate Glycol, sometimes known as PETG, is a thermoplastic material that is widely used and is renowned for its remarkable strength, resilience to chemicals, and ease of processing. Through the use of Taguchi Grey Relational Analysis (GRA), the purpose of this investigation is to improve the process parameters of the FDM technology for PETG material. In order to investigate the influence that several FDM process parameters, such as layer thickness, infill density, printing speed, and nozzle temperature, have on significant outcome variables, such as dimensional accuracy, surface quality, and mechanical qualities, an empirical research was conducted. For the purpose of constructing the regression prediction model, the obtained dataset is used to make
Natarajan, ManikandanPasupuleti, ThejasreeShanmugam, LoganayaganKatta, Lakshmi NarasimhamuSilambarasan, RKiruthika, Jothi
This SAE Recommended Practice establishes recommended procedures for the issuance, assignment, and structure of Identification Numbers on a uniform basis by states or provinces for use in an Assigned Identification Number (AIN).
VIN - WMI Technical Committee
Additive Manufacturing (AM), specifically Fused Deposition Modeling (FDM), has transformed the manufacturing industry by allowing the creation of intricate shapes using different materials. Polylactic Acid (PLA) is a biodegradable thermoplastic that is commonly used in additive manufacturing (AM) because of its environmentally friendly nature, affordability, and ease of processing. This study aims to optimize the parameters of Fused Deposition Modeling (FDM) for PLA material using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) approach. The researchers performed experimental trials to examine the impact of important FDM parameters, such as layer thickness, infill density, printing speed, and nozzle temperature, on critical outcomes, including dimensional accuracy, surface finish, and mechanical properties. The methodology of design of experiments (DOE) enabled a systematic exploration of parameters. The TOPSIS approach, a technique for making decisions
Natarajan, ManikandanPasupuleti, ThejasreeD, PalanisamyKatta, Lakshmi NarasimhamuSilambarasan, R
Researchers have developed a gel polymer-based triboelectric nanogenerator (TENG) that generates electrical signals from body movement to power electronics like LEDs and functions as a self-powered touch panel for user identification. The device can stretch up to 375 percent of its original size and withstand rigorous mechanical deformations, making it suitable for wearable applications. TENGs that convert mechanical energy such as body movement to electrical energy offer a solution to power wearable devices without relying on batteries.
Sodium-ion batteries (SIBs) make their marks in energy storage and electric vehicles due to their abundant reserves, cost-effectiveness, environmental resilience, and high safety. However, maintaining high battery performance in intricate operating conditions is challenging, which necessitates precise control based on timely and accurate acquisition of operation parameters, especially for the state of charge (SOC). Equivalent circuit model (ECM) is the most widely used in the evaluation of SOC. In this work, a 2nd-order resistor-capacitor ECM (2ORC-ECM) is chosen because of its balance between accuracy and computational efficiency. Furthermore, dynamic parameters in the 2ORC-ECM are accurately identified online by introducing an enhanced recursive least squares method with a forgetting factor. Finally, the proposed method is carried out based on the measured data of commercial SIBs. The results show that the proposed method can mitigate data saturation effectively while ensuring high
Qi, HonghaoPan, LyumingXu, XiaoqianRao, HaoyaoYu, YueshengLiu, XiangchiZhu, YifeiYang, CanWu, WeixiongLi, YubaiLi, WenjiaZeng, LinXu, QianRen, JiayouWei, Lei
Monitoring the rotor temperature of drive machines is crucial for the safety and performance of electric vehicles. However, due to the complex operating conditions of electric vehicles, the thermal parameters of vehicular induction machines (IMs) vary significantly and are difficult to identify accurately. This article first establishes a concise but effective thermal network for IMs and analyzes the influencing factors of thermal parameters. Then, a parameter identification network (PIN) with multiple parallel branches is constructed to learn the mapping relationship between electromechanical variables and thermal parameters. Afterward, temperature datasets for network training are built through bench testing. Finally, the effectiveness of identified parameters for rotor temperature estimation application is verified, demonstrating improved interpretability, generalization ability, and accuracy compared to an end-to-end neural network.
Jiang, ShangHu, Zhishuo
This SAE Recommended Practice establishes a procedure for the issuance and assignment of a World Manufacturer Identifier (WMI) on a uniform basis to vehicle manufacturers that may desire to incorporate it in their Vehicle Identification Numbers (VIN). This recommended practice is intended to be used in conjunction with the recommendations for VIN systems described in SAE J853, SAE J187, SAE J272, and other SAE reports for VIN systems. These procedures were developed to assist in identifying the vehicle as to its point of origin. It was felt that review and coordination of the WMI by a single organization would avoid duplication of manufacturer identifiers and assist in the identification of vehicles by agencies such as those concerned with motor vehicle titling and registration, law enforcement, and theft recovery.
VIN - WMI Technical Committee
This SAE Recommended Practice describes the basic content requirements, barcode specifications, and functional test specifications of the vehicle identification number (VIN) label. On the vehicle, the VIN label is to be mounted in a readily accessible location for use of a barcode scanning device.
VIN - WMI Technical Committee
The flow structure and unsteadiness of shock wave–boundary layer interaction (SWBLI) has been studied using rainbow schlieren deflectometry (RSD), ensemble averaging, fast Fourier transform (FFT), and snapshot proper orthogonal decomposition (POD) techniques. Shockwaves were generated in a test section by subjecting a Mach = 3.1 free-stream flow to a 12° isosceles triangular prism. The RSD pictures captured with a high-speed camera at 5000 frames/s rate were used to determine the transverse ray deflections at each pixel of the pictures. The interaction region structure is described statistically with the ensemble average and root mean square deflections. The FFT technique was used to determine the frequency content of the flow field. Results indicate that dominant frequencies were in the range of 400 Hz–900 Hz. The Strouhal numbers calculated using the RSD data were in the range of 0.025–0.07. The snapshot POD technique was employed to analyze flow structures and their associated
Datta, NarendraOlcmen, SemihKolhe, Pankaj
SAE J3108 Recommended Practice (RP) provides fuel and hazard guidance for first and second responders of incidents associated with alternative fueled vehicles. The intent of SAE J3108-1 is to present responders with a limited number of intuitive letters and colors. The International community is in the process of adopting International Standards Organization (ISO) 17840, which provides first and second responders with a standardized format for emergency information. While the ISO 17840 format in coloring and lettering can be adopted and should be encouraged when possible, it is intended for large and heavy vehicles. SAE J3108-1 provides a means for responders to recognize fuel and vehicle type on North American light duty vehicles due to size constraints preventing use of ISO 17840 labels.1 While encouraged to be adopted or referenced by vehicle manufacturers, this RP has been developed for the use of States and other Governmental bodies. The RP is not intended to replace the standards
Hybrid - EV Committee
G-3, Aerospace Couplings, Fittings, Hose, Tubing Assemblies
G-3, Aerospace Couplings, Fittings, Hose, Tubing Assemblies
To meet light-weighting and safety target of automotive vehicles, different Aluminium alloys are used in various body parts. Apart from conventional manufacturing process of gravity die casting (GDC), advanced manufacturing process such as low pressure die casting (LPDC), high pressure die casting (HPDC) and extrusion processes are also used to form complex automotive body parts. Steel parts are majorly used in automotive applications across world. However, steel has limitations with respect to light-weighting. To achieve light-weighting, now a days, there is trend to use these complex Aluminium parts in automotive industry to replace steel and integrate multiple parts into a single one. Aluminium has emerged as great potential for light-weighting and reducing complexity of handling multiple parts at an automotive plant. There is a challenge to identify suitable etchant for microstructural characterization of Aluminium alloy parts that can be made through various manufacturing
Deshmukh, MansiJain, VikasMisal, SwapnaliPaliwal, Lokesh
Mode identification, particularly Modal Map Generation, is pivotal within the NVH (Noise, Vibration, and Harshness) domain for managing the performance of complex systems like TBIW/Powertrain. This study addresses the critical task of accurately identifying Global / Local behavior of a particular system as single entity (Complete TBIW, Power train) or all the systems attached to main structure (Sub Systems i.e Seat , Fuel Tank , Pump etc), which is crucial for effective NVH post-processing. Introducing a novel tool/methodology developed by the Applus IDIADA team, this paper presents an efficient approach to Global & Local mode identification across subsystems, TBIW, and Powertrain levels. Leveraging ".op2" file content, mainly Strain Energy Density[1] and Displacement [2], the tool integrates Machine Learning Techniques [3] to produce mode predictions along with detailed visual outputs such as graphs , pie chart , modal charts etc. Implemented as a Python-based solution compatible with
Naphad, AniruddhaLama Borrajo, InesPatil Sr, HitendraChandratre, SudipRana, Upendra
RADAR antennae come in varying sizes and shapes. They are often employed in heterogeneous systems (i.e., systems that use multiple detection methods) that are employed to detect and visualize objects. Object identification in the context of automated vehicle behavior design could require extensive data sets to train algorithms that have the potential to make dynamic driving decisions. A widely available platform would increase the ability of researchers learn about automated systems and to gather data, which may be necessary for training automated vehicle systems. This work describes the application of a 77 GHz, portable antenna to the description of standard fleet vehicles as well as a suite of soft targets contextualized within polar plots. This work shows that object detection and identification is possible in off-the-shelf portable systems that combine readily available materials and software in a reproducible manner. The described system and algorithm create a visual correlate
Chen, AaronHartman, EthanLin, VincentManahan, TaylorSidhu, AnmolEichaker, Lauren
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