Interferometric Reflectance Imaging Sensor (IRIS) for Molecular Kinetics with a Low-Cost, Disposable Fluidic Cartridge

2019 ◽  
pp. 15-28
Author(s):  
James W. Needham ◽  
Nese Lortlar Ünlü ◽  
Celalettin Yurdakul ◽  
M. Selim Ünlü
Keyword(s):  
Low Cost ◽  
Imaging Sensor

scholarly journals Tomographic Proximity Imaging Using Conductive Sheet for Object Tracking

Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2736
Author(s):  
Zehao Li ◽  
Shunsuke Yoshimoto ◽  
Akio Yamamoto
Keyword(s):  
Inverse Problem ◽  
Theoretical Model ◽  
Low Cost ◽  
Hand Tracking ◽  
Depth Camera ◽  
Capacitance Density ◽  
Evaluation Test ◽  
Density Problem ◽  
Imaging Sensor ◽  
Tomographic Approach

This paper proposes a proximity imaging sensor based on a tomographic approach with a low-cost conductive sheet. Particularly, by defining capacitance density, physical proximity information is transformed into electric potential. A novel theoretical model is developed to solve the capacitance density problem using the tomographic approach. Additionally, a prototype is built and tested based on the model, and the system solves an inverse problem for imaging the capacitance density change that indicates the object’s proximity change. In the evaluation test, the prototype reaches an error rate of 10.0–15.8% in horizontal localization at different heights. Finally, a hand-tracking demonstration is carried out, where a position difference of 33.8–46.7 mm between the proposed sensor and depth camera is achieved at 30 fps.

In situ quantitative field emission imaging using a low-cost CMOS imaging sensor

2022 ◽  
Vol 40 (1) ◽  
pp. 014202
Author(s):  
Andreas Schels ◽  
Simon Edler ◽  
Florian Herdl ◽  
Walter Hansch ◽  
Michael Bachmann ◽  
...  
Keyword(s):  
Field Emission ◽  
Low Cost ◽  
Imaging Sensor

scholarly journals Instrument-Free Protein Microarray Fabrication for Accurate Affinity Measurements

Biosensors ◽  
2020 ◽  
Vol 10 (11) ◽  
pp. 158
Author(s):  
Iris Celebi ◽  
Matthew T. Geib ◽  
Elisa Chiodi ◽  
Nese Lortlar Ünlü ◽  
Fulya Ekiz Kanik ◽  
...  
Keyword(s):  
Signal To Noise Ratio ◽  
Low Cost ◽  
Protein Microarray ◽  
Active Surface ◽  
Protein Microarrays ◽  
Free Protein ◽  
Microarray Fabrication ◽  
Antigen Antibody ◽  
Imaging Sensor ◽  
Protein Assays

Protein microarrays have gained popularity as an attractive tool for various fields, including drug and biomarker development, and diagnostics. Thus, multiplexed binding affinity measurements in microarray format has become crucial. The preparation of microarray-based protein assays relies on precise dispensing of probe solutions to achieve efficient immobilization onto an active surface. The prohibitively high cost of equipment and the need for trained personnel to operate high complexity robotic spotters for microarray fabrication are significant detriments for researchers, especially for small laboratories with limited resources. Here, we present a low-cost, instrument-free dispensing technique by which users who are familiar with micropipetting can manually create multiplexed protein assays that show improved capture efficiency and noise level in comparison to that of the robotically spotted assays. In this study, we compare the efficiency of manually and robotically dispensed α-lactalbumin probe spots by analyzing the binding kinetics obtained from the interaction with anti-α-lactalbumin antibodies, using the interferometric reflectance imaging sensor platform. We show that the protein arrays prepared by micropipette manual spotting meet and exceed the performance of those prepared by state-of-the-art robotic spotters. These instrument-free protein assays have a higher binding signal (~4-fold improvement) and a ~3-fold better signal-to-noise ratio (SNR) in binding curves, when compared to the data acquired by averaging 75 robotic spots corresponding to the same effective sensor surface area. We demonstrate the potential of determining antigen-antibody binding coefficients in a 24-multiplexed chip format with less than 5% measurement error.

scholarly journals Experimental Study of Visual Corona under Aeronautic Pressure Conditions Using Low-Cost Imaging Sensors

Sensors ◽  
2020 ◽  
Vol 20 (2) ◽  
pp. 411 ◽  
Author(s):  
Jordi-Roger Riba ◽  
Álvaro Gómez-Pau ◽  
Manuel Moreno-Eguilaz
Keyword(s):  
Experimental Study ◽  
High Voltage ◽  
Low Cost ◽  
Partial Discharge ◽  
Radio Interference ◽  
Uv Spectrum ◽  
Aerospace Applications ◽  
Low Levels ◽  
Imaging Sensors ◽  
Imaging Sensor

Visual corona tests have been broadly applied for identifying the critical corona points of diverse high-voltage devices, although other approaches based on partial discharge or radio interference voltage measurements are also widely applied to detect corona activity. Nevertheless, these two techniques must be applied in screened laboratories, which are scarce and expensive, require sophisticated instrumentation, and typically do not allow location of the discharge points. This paper describes the detection of the visual corona and location of the critical corona points of a sphere-plane gap configurations under different pressure conditions ranging from 100 to 20 kPa, covering the pressures typically found in aeronautic environments. The corona detection is made with a low-cost CMOS imaging sensor from both the visible and ultraviolet (UV) spectrum, which allows detection of the discharge points and their locations, thus significantly reducing the complexity and costs of the instrumentation required while preserving the sensitivity and accuracy of the measurements. The approach proposed in this paper can be applied in aerospace applications to prevent the arc tracking phenomenon, which can lead to catastrophic consequences since there is not a clear protection solution, due to the low levels of leakage current involved in the pre-arc phenomenon.

scholarly journals A Low-Cost and Ultralight Unmanned Aerial Vehicle-Borne Multicamera Imaging System Based on Smartphones

2022 ◽  
Vol 2022 ◽  
pp. 1-15
Author(s):  
Huachao Yang ◽  
Hefang Bian ◽  
Bin Li ◽  
Weihua Bi ◽  
Xingtao Zhao
Keyword(s):  
Imaging System ◽  
Low Cost ◽  
3D Models ◽  
Digital Cameras ◽  
Typical Application ◽  
Textural Quality ◽  
Small Device ◽  
Aerial Vehicle ◽  
Automatic Capture ◽  
Imaging Sensor

Newly developed oblique photogrammetry (OP) techniques based on unmanned aerial vehicles (UAVs) equipped with multicamera imaging systems are widely used in many fields. Smartphones cost less than the cameras commonly used in the existing UAV OP system, providing high-resolution images from a built-in imaging sensor. In this paper, we design and implement a novel low-cost and ultralight UAV OP system based on smartphones. Firstly, five digital cameras and their accessories detached from the smartphones are then fitted into a very small device to synchronously shoot images at five different perspective angles. An independent automatic capture control system is also developed to realize this function. The proposed smartphone-based multicamera imaging system is then mounted on a modified version of an existing lightweight UAV platform to form a UAV OP system. Three typical application examples are then considered to evaluate the performance of this system through practical experiments. Our results indicate that both horizontal and vertical location accuracy of the generated 3D models in all three test applications achieve centimeter-level accuracy with respect to different ground sampling distances (GSDs) of 1.2 cm, 2.3 cm, and 3.1 cm. The accuracy of the two types of vector maps derived from the corresponding 3D models also meet the requirements set by the surveying and mapping standards. The textural quality reflected by the 3D models and digital ortho maps (DOMs) are also distinguishable and clearly represent the actual color of different ground objects. Our experimental results confirm the quality and accuracy of our system. Although flight efficiency and the accuracy of our designed UAV OP system are lower than that of the commercial versions, it provides several unique features including very low-cost, ultralightweight, and significantly easier operation and maintenance.

scholarly journals Low-Cost Thermal Camera-Based Counting Occupancy Meter Facilitating Energy Saving in Smart Buildings

Energies ◽  
2021 ◽  
Vol 14 (15) ◽  
pp. 4542
Author(s):  
Marek Kraft ◽  
Przemysław Aszkowski ◽  
Dominik Pieczyński ◽  
Michał Fularz
Keyword(s):  
Thermal Imaging ◽  
Network Architecture ◽  
Low Cost ◽  
Machine Learning Algorithms ◽  
Infrared Sensors ◽  
Neural Network Architecture ◽  
Binary Information ◽  
Reduce Energy Consumption ◽  
Imaging Sensor ◽  
Established Technique

Using passive infrared sensors is a well-established technique of presence monitoring. While it can significantly reduce energy consumption, more savings can be made when utilising more modern sensor solutions coupled with machine learning algorithms. This paper proposes an improved method of presence monitoring, which can accurately derive the number of people in the area supervised with a low-cost and low-energy thermal imaging sensor. The method utilises U-Net-like convolutional neural network architecture and has a low parameter count, and therefore can be used in embedded scenarios. Instead of providing simple, binary information, it learns to estimate the occupancy density function with the person count and approximate location, allowing the system to become considerably more flexible. The tests show that the method compares favourably to the state of the art solutions, achieving significantly better results.

Location Detection of Informative Bright Region in Tunnel Scenes Using Lighting and Traffic Lane Cues

2015 ◽  
Vol 19 (2) ◽  
pp. 255-263 ◽  
Author(s):  
Jiajun Lu ◽  
◽  
Fangyan Dong ◽  
Kaoru Hirota ◽  
Keyword(s):  
Visual Information ◽  
Visual Cues ◽  
Dynamic Range ◽  
Low Cost ◽  
Image Sensor ◽  
Road Tunnel ◽  
Bright Region ◽  
Traffic Lane ◽  
Location Detection ◽  
Imaging Sensor

To locate Informative Bright Region (IBR) in which visual information is missing owing to limited dynamic range of image sensor, an algorithm is proposed that combines the geometric properties of visual cues into a confidence map. The location of an IBR in a road tunnel scene is estimated in real-time under the condition in which most of the vision information inside the IBR is lost. The algorithm is evaluated by comparing the estimated location of IBR with that annotated by multiple human observers in a self-built tunnel scene video dataset recorded by a car-mounted camera, and the algorithm achieves a running time of 10 ms for each frame. The algorithm aims to provide control timing of imaging sensor on a low-cost platform such as a vehicle driving recorder to enhance the visual contents captured in over-exposed regions.

Instrument-Free Protein Microarray Fabrication for Accurate Affinity Measurements

2020 ◽  
Author(s):  
Iris Celebi ◽  
Matthew T. Geib ◽  
Elisa Chiodi ◽  
Nese Lortlar Ünlü ◽  
Fulya Ekiz Kanik ◽  
...  
Keyword(s):  
Signal To Noise Ratio ◽  
Low Cost ◽  
Protein Microarray ◽  
Active Surface ◽  
Protein Microarrays ◽  
Free Protein ◽  
Microarray Fabrication ◽  
Antigen Antibody ◽  
Imaging Sensor ◽  
Protein Assays

Protein microarrays have gained popularity as an attractive tool for various fields, including drug and biomarker development, and diagnostics. Thus, multiplexed binding affinity measurements in microarray format has become crucial. The preparation of microarray-based protein assays relies on precise dispensing of probe solutions to achieve efficient immobilization onto an active surface. The prohibitively high cost of equipment and the need for trained personnel to operate high complexity robotic spotters for microarray fabrication are significant detriments for researchers, especially for small laboratories with limited resources. Here, we present a low-cost, instrument-free dispensing technique by which users who are familiar with micropipetting can manually create multiplexed protein assays that show improved capture efficiency and noise level in comparison to that of the robotically spotted assays. In this study, we compare the efficiency of manually and robotically dispensed α-Lactalbumin probe spots by analyzing the binding kinetics obtained from the interaction with anti-α-Lactalbumin antibodies, using the interferometric reflectance imaging sensor platform. We show that the protein arrays prepared by micropipette manual spotting meet and exceed the performance of those prepared by state-of-the-art robotic spotters. These instrument-free protein assays have higher binding signal (~4-fold improvement) and a ~3-fold better signal-to-noise ratio (SNR) in binding curves, when compared to the data acquired by averaging of 75 robotic spots corresponding to the same effective sensor surface area. We demonstrate the potential of determining antigen-antibody binding coefficients in 24-multiplexed chip format with less than 5% measurement error.

Instrument-Free Protein Microarray Fabrication for Accurate Affinity Measurements

2020 ◽  
Author(s):  
Iris Celebi ◽  
Matthew T. Geib ◽  
Elisa Chiodi ◽  
Nese Lortlar Ünlü ◽  
Fulya Ekiz Kanik ◽  
...  
Keyword(s):  
Signal To Noise Ratio ◽  
Low Cost ◽  
Protein Microarray ◽  
Active Surface ◽  
Protein Microarrays ◽  
Free Protein ◽  
Microarray Fabrication ◽  
Antigen Antibody ◽  
Imaging Sensor ◽  
Protein Assays

Protein microarrays have gained popularity as an attractive tool for various fields, including drug and biomarker development, and diagnostics. Thus, multiplexed binding affinity measurements in microarray format has become crucial. The preparation of microarray-based protein assays relies on precise dispensing of probe solutions to achieve efficient immobilization onto an active surface. The prohibitively high cost of equipment and the need for trained personnel to operate high complexity robotic spotters for microarray fabrication are significant detriments for researchers, especially for small laboratories with limited resources. Here, we present a low-cost, instrument-free dispensing technique by which users who are familiar with micropipetting can manually create multiplexed protein assays that show improved capture efficiency and noise level in comparison to that of the robotically spotted assays. In this study, we compare the efficiency of manually and robotically dispensed α-Lactalbumin probe spots by analyzing the binding kinetics obtained from the interaction with anti-α-Lactalbumin antibodies, using the interferometric reflectance imaging sensor platform. We show that the protein arrays prepared by micropipette manual spotting meet and exceed the performance of those prepared by state-of-the-art robotic spotters. These instrument-free protein assays have higher binding signal (~4-fold improvement) and a ~3-fold better signal-to-noise ratio (SNR) in binding curves, when compared to the data acquired by averaging of 75 robotic spots corresponding to the same effective sensor surface area. We demonstrate the potential of determining antigen-antibody binding coefficients in 24-multiplexed chip format with less than 5% measurement error.

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