Suddhasatwa Chakraborty and Saswati Mazumdar
Laboratory Experiment Based Studies on Effect of Peripheral Source on on-Axis Visual Performance

Alexander Yu. Basov, George V. Boos,, Vladimir P. Budak, and Anton V. Grimailo
Luminance Factor Modelling for an Arbitrary Surface

Alexei A. Bartsev and Alexandra A. Bartseva
Methodology of Imaging Photometric Device Using in Museum

Vyacheslav A. Panin and Mikhail A. Fedorishchev
Mobile Device and Method for Photosynthetic Photon Flux Density Measurement in Greenhouse

Anatoly Sh. Chernyak, Mikhail A. Fedorishchev, and Alyona B. Kuznetsova
Improvement of Mobile Method for Road Photometric Parameters Measurements

George V. Boos, Vladimir P. Budak, Ekaterina I. Ilyina, and Tatyana V. Meshkova
Scaling of Visual Tasks Sensations from Human Centric Lighting Point of View

Suddhasatwa Chakraborty and Saswati Mazumdar
Laboratory Experiment Based Studies on Effect of Peripheral Source on on-Axis Visual Performance

Alexander Yu. Basov, George V. Boos,, Vladimir P. Budak, and Anton V. Grimailo
Luminance Factor Modelling for an Arbitrary Surface

Alexei A. Bartsev and Alexandra A. Bartseva
Methodology of Imaging Photometric Device Using in Museum

Vyacheslav A. Panin and Mikhail A. Fedorishchev
Mobile Device and Method for Photosynthetic Photon Flux Density Measurement in Greenhouse

Anatoly Sh. Chernyak, Mikhail A. Fedorishchev, and Alyona B. Kuznetsova
Improvement of Mobile Method for Road Photometric Parameters Measurements

George V. Boos, Vladimir P. Budak, Ekaterina I. Ilyina, and Tatyana V. Meshkova
Scaling of Visual Tasks Sensations from Human Centric Lighting Point of View

The behavioural relationship among peripheral vision and onaxis vision is a very important parameter required to be investigated thoroughly. In this paper the influence of peripheral vision on onaxis vision has been investigated in a controlled environment. One behavioural experimentbased studies have been carried out to validate the relationship rigidly. In this experiment, the effect of peripheral vision on onaxis performance of a driver in a motorized road is a very important parameter considered. In this simulationbased study a driver simulator is used. There is a peripheral controlled glare source, which has been introduced at offaxis with respect to the line of sight. The glare source contrast (positive and negative) with respect to the background has been changed gradually and all the subjects (drivers) were made occupied with an onaxis task. The detection of peripheral glare source with respect to the onaxis performance of the subjects (drivers) has been recorded as detection time and also the number of misses for identifying the peripheral source.

1. Boyce, P. Lighting for Driving: Roads, Vehicles, Signs, and Signals, Boca Ranton // USA: CRC Press, 2008.
2. Bommel, W. Road Lighting Fundamentals, Technology and Application // Springer Publication, 2015.
3. Boyce, P.R. Human Factors in Lighting, Third Edition // CRC Press Published April 7, 2014.
4. Volker, S. Generalization and validation of visibility concepts/ is visibility a good counter of quality of light? // CIE Expert workshop a New Vision of Visibility for Roadway Lighting, Technische Universitat Berlin, Germany, 2018.
5. Bullough, J. D., Rea, M.S. Simulated driving performance and peripheral detection at mesopic and low photopic light levels // Lighting Research and Technology, 2000, Vol. 32, pp. 194-198.
6. Van Bommel, W. J. M., De Boer, J.B. Road Lighting. Eindhoven // Philips Technical Library, 1980.
7. CIE115, Technical Report on Lighting of Roads for Motor and Pedestrian Traffic, 2010.
8. Lingard, R., Rea, M. Offaxis detection at mesopic light levels in a driving context // J. Illum. Eng. Soc., 2002, Vol. 31, pp. 33-39.
9. JWAM, A. Target detection and driving behaviour measurements in a driving simulator at mesopic light levels // Ophthalmic and Physiological Optics, 2006, Vol. 26, pp. 264-280.
10. Akashi, Y., Rea, M. Peripheral detection while driving under a mesopic light level // J. Illum. Eng. Soc., 2002, Vol. 31, pp. 85-94.
11. Recommended System for Mesopic Photometry Based on Visual Performance, Technical Report No. 191 // CIE, 2010.
12. Cengiz, C., Visual performance under mesopic conditions: towards determination of adaptation luminance // Doctoral Dissertations 163, Aalto University publication series, 2015.
13. MOVE: Mesopic optimization of visual efficiency, performance based model for mesopic photometry // Helsinki University of Technology, Lighting Laboratory, Finland, 2005.
14. Rea, M.S. Visual performance modelling and roadway safety at night // CIE Expert workshop a New Vision of Visibility for Roadway Lighting, Technische Universitat Berlin, Germany, 2018.
15. Onaygil, S. Determination of road lighting automation scenarios based on visibility calculations // CIE Expert workshop a New Vision of Visibility for Roadway Lighting, Technische Universitat Berlin, Germany, 2018
16. Holladay, L.L. The fundamentals of glare and visibility // Journal of the Optical Society of America A, 1926, Vol. 12, pp. 271-319.
17. Akashi, Y., Neches, J. The effects of task load on peripheral target detection // Proceedings of the Commission Internationale de lТa?clairage, 25th Session, Commission Internationale de lТa? clairage, 2003, pp. D4/44-D4/47.
18. Fotios, S., Uttley, J., Cheal, C. Maintaining foveal fixation during a peripheral detection task // Lighting Research and Technology, 2016, Vol. 48, pp. 898-909.
19. Winter, J., Fotios, S., Volker, S. The effects of glare and in homogeneous visual fields on contrast detection in the context of driving // Lighting Research and Technology, 2016, Vol. 0, pp. 1-15.
20. Stiles, WS. The effect of glare on the luminance difference threshold // Proceedings of the Royal Society London B, 1929, #104, pp. 322-355.
21. Frederiksen, E., Rotne, N. Calculation of Visibility in Road Lighting // Report No 17, The Danish Illumination Engineering Laboratory, Denmark, March 1978.
22. TC4-36. Visibility design for roadway lighting // Report draft CIE, 2008.

1. Maghe, L. Characterization of Road Surfaces using a Mobile Gonioreflectometer // CIE International Symposium on Road Surface Photometric Characteristics, 2008, 16 p.
2. Adams, M.L., Larsen, E.W. Fast iterative methods for discreteordinates particle transport calculations // Progress in Nuclear Energy, 2002, Vol. 40(1), pp. 3-159.
3. Budak, V.P., Klyukov, D.A., Korkin, S.V. Convergence acceleration of radiative transfer equation solution at strongly anisotropic scattering // Light Scattering Reviews 5. Single Light Scattering and Radiative Transfer, 2010, pp. 147-204.
4. Fryer, G.J., Frazer, L.N. Seismic waves in stratified anisotropic media // Geophys. J.R. Astr. Soc., 1984, Vol. 78, pp. 691-698.
5. Basov, A.Y. Development of a gonioreflectometer for measuring reflective properties of road surfaces // Master thesis, 2017, 74 p.
6. Budak, V.P., Grimailo, A.V. Light reflection from real surfaces: Probabilistic model of the layer radiance factor // CEUR Workshop Proceedings, 2020, 2744.
7. Basov, A.Y., Boos, G.V., Budak, V.P., Grimailo, A.V. Numericalanalytical model of the luminance factor of an arbitrary surface // Proceedings of the Conference CIE2021, OP54, p. 423-430.

1. CIE157-2004: Control of Damage to Museum Objects by Optical Radiation.
2. CIE244-2021: Characterization of Imaging Luminance Measurement Devices (ILMDs).
3. Schanda, J., Csuti, P., Szabo, F., 2014. Museum lighting with LEDs: LED lighting for the Sistine Chapel. Proc. of CIE2014 УLighting Quality and Energy EfficiencyФ. Kuala Lumpur, Malaysia, 23-26 April, pp. 629-637.
4. ZaidelТ, A. N., 1985. Measurement errors of physical quantities. Leningrad: Nauka, pp. 112.
5. ISO 5725-6, 1994. Accuracy (trueness and precision) of measurement methods and results - Part 6: Use in practice of accuracy values.
6. MI 2083-90, 1992. State system for ensuring the uniformity of measurements. Indirect measurements. Determination of measurement results and estimation of their errors. Moscow: Committee for Standardization and Metrology of the USSR.
7. Bartsev, A.A., Bartseva, A.A. Illuminance Distribution Measurement of Museum Objects Using Digital Imaging Luminance Meter // Proceedings of the CIE2021 Conference, September 27-29, Malaysia, pp. 598-606.

1. GOST R55706-2013 Outdoor utility lighting. Classification and norms.
2. GOST R55707-2013 Illumination of external utilitarian. Measuring methods of standardized parameters.
3. GOST R58107.1-2018 General use automobile roads lighting. Norms and methods of calculation.
4. GOST R58107.2-2018 General use automobile roads lighting. Method of measurement of road surface illuminance by mobile way.
5. GOST R58107.3-2018 General use automobile roads lighting. Method of measurement of road surface luminance by mobile way.
6. SP 52.13330.2016 Code of rules. Natural and artificial lighting. Updated version of SNIP 23-05-95*.
7. HELMUT, F., JURGEN, E. 1995. Bestimmung des Mindestruckstrahlwertes im Gebrauchszustand fur retroreflektierende Materialien zur Verkehrssicherung, Forschung Strassenbau und Strassenverkehrstechnik, Heft 713.
8. CIE2011. CIE194:2011. On site measurement of the photometric properties of road and tunnel lighting.
9. Zatari, A., Dodds, G., Mcmenemy, K., Robinson, R. 2004. Glare, Luminance and Illuminance Measurements of Road Lighting Using Vehicle Mounted CCD Cameras // Leucos, Vol. 1, # 2, October 2004, pp. 85-106.
10. P. Iacomussi, G. Rossi, M. Castellano УThe Development of a new mobile photometric laboratoryФ, CIE Midterm Meeting Congresso Internacional de Illuminacion, Leon 2005.
11. METinfo | Vol. 21 | No. 1/2014 |1 Journal de metrologie Edition speciale/mars 2015 УVoie libre a la mesure dynamique de la lumiere en tunnelsФ
12. GOST R8.736-2011 УState system for ensuring the uniformity of measurements. Multiple Direct measurements. Methods of measurement results processing. Main positionsФ.
13. GOST R ISO 5725-1 - 2002 УAccuracy (trueness and precision) of measurement methods and results. Part 1. General principles and definitionsФ.
14. Chernyak, A. Sh., Fedorishchev, M.A., Kuznetsova, A.B. Optimisation of a Mobile Method for Measuring Road Lighting Characteristics (Luminance and Illuminance) // Proceedings of the CIE2021 Conference, September 27-29, Malaysia, pp. 654-662.

1. Neumann, D. (Ed.) The Structure of Light: Richard Kelly and the Illumination of Modern Architecture, New Haven // CT: Yale University Press, 2011. 224p.
2. Boyce, P.R. Human Factors in Lighting 3rd Edition // CRC Press, 2014.
3. Budak, V.P., Zheltov, V.S., Meshkova, T.V., Notfullin, R. Sh. Evaluation of illumination quality based on spatialangular luminance distribution // Light and Engineering, 2017, Vol. 25, #4, pp. 24-31.
4. Saunders, J.E. The role of the level and diversity of horizontal illumination in an appraisal of a simple office task // Lighting Res. Technol., 1969, #1, pp. 37-46.
5. Slater, A.I., Perry, M.J., Carter, D.J. Illuminance differences between desks: Limits of acceptability // Lighting Res. Technol., 1993, #25, pp. 91-103.
6. Luckiesh, M., Guth, S.K. Luminance in the visual field at borderline between comfort and discomfort // Illuminating Engineering, 1949, Vol. 44, #11, pp. 650-670.
7. Luckiesh, M., Holladay, L.L. Glare and Visibility // Transactions of the IES, 1925, Vol. 20, pp. 221252. 8. Bommel, W. Interior Lighting. Fundamentals // Technology and Application, Springer, Cham, 2019. 9. Budak, V., Ilyina, E. Psychovisual Perception Scale Based on a Neural Network // CEUR Workshop Proceedings, 2020, 2744, paper 65.
10. Kotik, G. G., Matveev, A. B., Pereima, V. V., Tokhadze, I.L. Categorical quality assessments and their interrelation on the psychophysical scale // Svetotekhnika, 1975, #3, pp. 3-5.
11. Budak, V. P., Zheltov, V. S., Meshkova, T. V., Chembaev, V. D. A new criterion for lighting quality and its approbation in laboratory conditions // Bulletin of the MEI, 2020, #1, pp. 73-81.
12. Budak, V. P., Ilyina, E.I. Construction of a psychophysical scale of visual comfort of lighting based on a neural network: preparation of an experiment // Light and Engineering, 2021, #2, pp. 30-36.
13. Boos, G., Budak, V., Ilyina, E., Meshkova, T. Scaling of Sensations During the Performance of Visual Tasks in Relation to Human Centric Lighting // Proceedings of the CIE2021 Conference, September 27-29, Malaysia, pp. 772-779.

1. Koknel Yener, A. Daylight Analysis in Classrooms with Solar Control // Architectural Science Review, 2002, Vol. 45, #4, pp. 311-316.
2. Aykal, F. D., Gumus, B., Unver, F. R., Ozgur, M. An Approach in Evaluation of Re Functioned Historical Buildings in view of Natural Lighting A Case Study in Diyarbakir Turkey // Light and Engineering, 2011, Vol. 19, #2, pp. 64-76.
3. Onaygil, S., Guler, O. Determination of the Energy Saving by Daylight Responsive Lighting Control Systems with an Example from Istanbul // Building and Environment, 2003, Vol. 38, #7, pp. 973-977.
4. Unver, F. R., Ozturk, L., Ak?n Ad?guzel, S., Celik, O. Effect of the facade alternatives on the daylight illuminance in offices // Energy and Buildings, 2003, Vol. 35, #8, pp. 737-746.
5. Koknel Yener, A. Performance Analysis of Window Glazing from Visual Comfort and Energy Conservation Points of View // Architectural Science Review, 2003, V46, #4, pp. 395-401.
6. Kurtay, C. Design of the External Environment for Favorable Daylight in Large Volumes // Gazi University Journal of the Faculty of Engineering and Architecture, 2002, Vol. 17, #3, pp. 75-87.
7. Unver, F. R., Ozturk, L. An example of facade colour design of mass housing // Color Research and Application, 2001, Vol. 27, #4, pp. 291-299.
8. Giray, E. Dynamic lighting and its application // MasterТs Thesis, Yildiz Technical University, Institute of Natural and Applied Sciences, 2009
9. Tuncel, A. Lighting design in restaurants, food and beverage and entertainment venues the effect of light and color on the formation of the atmosphere, 2009.
10. Aktas, I. The effects of dynamic lighting on human health, 2012.
11. Schlangen, L., L. E Lang, D., Cajochen, C., Nikunen, H., Tahkamo, L. Accelerate SSL Innovat?on for EUROPE, 2014.
12. Apayd?n, S. The effects of lighting design in offices on space design in terms of sustainability, 2012.
13. Dogan Yusuf, F. Investigation of lighting conditions in patient rooms: a case study in Izmir MasterТs thesis, 2017.
14. CEN EN12464-1:2011 (Main) Light and lighting - Lighting of work places - Part 1: Indoor work places, 01Jun2011.
15. TSE - TS EN12464-1 Light and lighting - Lighting of work places - Part 1: Indoor work places, 21 February 2013.
16. International WELL Building InstituteCircadian Lighting Design Q4-2020, Melanopic Light Intensity for Work Areas 2020 version.
17. International WELL Building InstituteCircadian Lighting Design, Light, Light Features Q4-2020 version, 2020.
18. Demirci, H. Investigation of lighting and colour phenomena in building design from the point of view of bioharmology and bioprocess. F?rat University Institute of Natural and Applied Sciences, Bioengineering, 2008.
19. Buttgereit, F., Smolen, J. S., Coogan, A. N., Cajochen, C. Clocking in: chronobiology in rheumatoid arthritis // Nature Reviews Rheumatology, 2015, Vol. 11, #6, pp. 349.
20. Rea, M. S., Figueiro, M. G., Bierman, A., Hamner, R. Modelling the spectral sensitivity of the human circadian system // Lighting Research and Technology, 2012, Vol. 44, #4, pp. 386-396.
21. Sahin, D. The Assessment of The Physiological and Psychological Effects of Lighting Design on Occupants, 2013 // Doctoral dissertation, Istanbul Technical University, Institute of Science and Technology, 2012.
22. Walerczyk, S., Hclpc, C., and Wizards, L.L. Human centric lighting // Architectural SSl, 2012. pp. 20-26.
23. Smolders, K. C. H.J. Daytime light exposure: effects and preferences, 2013.
24. Ozturk, L. The effect of luminance distribution on interior perception // Architectural Science Review, 2003, Vol. 46, #3, pp. 233-238.
25. Cengiz, C., Cengiz M.S. 2021. The Relationship Between Shadow and Visional Comfort in Indoor Areas // II. International Halich Congress On Mult?d?sc?pl?nary Scientific Research, 29-30 October 2021, Istanbul.
26. Cengiz, C., Cengiz M.S. 2021. Using Symmetric and Asymmetric Lens In Urban Lighting // II. Internat?onal Halich Congress On Multidisciplinary Scientific Research, 29-30 October 2021, Istanbul.
27. Efe, S.B., Varhan, D. Interior Lighting of a Historical Building by Using LED Luminaires A Case Study of Fatih Pasa Mosque // Light and Engineering, 2020, Vol. 28, #4, pp. 77-83.
28. Guler, O., Onaygil, S. The Effect of Luminance Uniformity on Visibility Level in Road Lighting // Lighting Research and Technology, 2003, Vol. 35, #3, pp. 199-215.
29. The Light Review, Explainer: Melanopic Lux. 30th July 2019/John Bullock/Explainer // Health and Wellbeing, Tech Hub.
30. ZVEIAkademie, 2021.
31. Boyce, Peter R. Human factors in lighting Third Edition. 2014. ISBN9780429104763
32. Boyce, Peter R. 2021. Light, lighting, and human health // Lighting Research and Technology. First Published April 28, 2021.
33. C?buk, M., Cengiz, M.S. Determination of Energy Consumption According To Wireless Network Topologies In GridFree Lighting Systems // Light and Engineering, 2020, Vol. 28, #2, pp. 67-76.
34. Cengiz, M.S. Simulation and Design Study for Interior Zone Luminance In Tunnel Lighting // Light and Engineering, 2019, Vol. 27, #2, pp. 42-51.
35. Cengiz, M.S. Effects of Luminaire Angle and Illumination Topology on Illumination Parameters In Road Lighting // Light and Engineering, 2020, Vol. 28, #4.
36. Eren, M., Yap?c?, I., Y?ld?r?m, S., Cengiz, C., Gencer, G., Palta, O., Aybay, E., Yurci, Y. 2017. Driver circuit effects in Lighting Systems // IOSR Journal of Electrical and Electronics Engineering, 12(6) Ver.III, pp. 1-4.
37. Cengiz, M.S. The Relationship between Maintenance Factor and Lighting Level in Tunnel Lighting // Light and Engineering, 2019, Vol. 27, #3, pp. 75-88.
38. Cengiz, C., Cengiz, M.S., Yurci, Y., Kaynakl?, M., Parlaky?ld?z, S., Ilcihan, Z. 2017. Realization of warming in lighting // IOSR Journal of Electrical and Electronics Engineering, 12(6) Ver.II, pp. 83-85.
39. Onaygil S. TEDAS General Directorate Vocational Training Seminar, TEDAS Printing House, Ankara, 2005. pp. 1-70.
40. Akalp, O., Ozbay, H., Efe S.B. Design and Analysis of HighEfficient Driver Model for LED Luminaires // Light and Engineering, 2021, Vol. 29, #2, pp. 96-106.
41. Cengiz M.S., Cengiz, C. Numerical Analysis of Tunnel LED Lighting Maintenance Factor // IIUM Engineering Journal, 2018, Vol. 19, #2, pp. 154-163.
42. Efe, S.B. UPFC Based RealTime Optimization of Power Systems for Dynamic Voltage Regulation // Computer Modeling in Engineering and Sciences, 2018, Vol. 116, #3, pp. 391-406.
43. Onaygil S., Guler, O. TEDAS General Directorate Vocational Training SeminarGolbas? Training Facilities, Road Lighting Seminar January 23-24, 2007.
44. Cengiz M.S. Effects of Luminaire Angle on Illumination Performance in Tunnel Lighting // Balkan Journal of Electrical and Computer Engineering, 2019, Vol. 7, #3, pp. 250-256.

Electrical and radiation characteristics of inductively-coupled ferrite-free low mercury pressure discharges exited at a frequency of 13.56 MHz and discharge plasma power, Ppl = (5 ? 300) W, in closed-loop quartz tubes of 815 mm in length and of 16.6 mm in diameter were experimentally stud-ied. Discharges were excited and maintained with the help of one-turn induction coil made from litz wire and disposed on the tube wall surface along tube perimeter. Tubes were filled with mercury vapour (~ 10Ц2 Torr) and argon (0.5, 0.7, 1.0, and 2.0) Torr. As discharge plasma power, Ppl, were increased from 130 W to 275 W, coil resonant frequency (RF) voltage grew from (560 ? 700) V up to (840 ? 860) V, RF coil current grew from (1.4 ? 1.8) A up to (2.4 ? 2.6) ј. Coil power losses was highest in the lamp with argon pressure of 0.5 Torr and grew from 30 W (Ppl = 150 W) to 70 W (Ppl = 230 W). UV resonant (254 nm) radiation flux grew with plasma power and was highest in the lamp (pAr = 0.5 Tоrr) while UV radiation generation ef-ficiency of this lamp had maximal value of 34 % at plasma power of 130 W.

1. Isupov, M.V., Krotov, S.V., Litvintzev, A.Y., Ulanov, I.M. An induction UV Lamp // Light and Engineering, 2008, Vol. 16, #1, pp. 67-71.
2. Kobayashi, S. and Hatano, A. Highintensity lowpressure electrodeless mercuryargon lamp for UV disinfection of wastewater // Journal of Water and Environment Technology, 2005, V 3, # 1, pp. 71-76.
3. Levchenko, V.A., Popov, O.A., Svitnev, S.A., Starshinov, P.V. Electrical and radiation characteristics of a transformer type lamp with a discharge tube of 16.6 mm diameter // Light and Engineering, 2016, V 24, # 2, pp. 77-81.
4. Svitnev, S.A., Popov, O.A., Levchenko, V.A., Starshinov, P.A. Characteristics of low pressure ferritefree inductive discharge // Part 2. Plasma radiation characteristics. Uspekhi prikladnoi fiziki, 2016. # 4, pp. 372-384.
5. Starshinov, P.V., Popov, O.A., Ilikeeva, R.A., Bureeva, D.A., Irkhin, I.V., Levchenko, V.A., Terekhov, G.P. High efficiency ferritefree closedloop inductively - coupled low mercury pressure discharge UV lamps // Light and Engineering, 2020, # 3, pp. 75-79.
6. Karmazinov, F.V., Kostyuchenko, S.V., Kudryavtsev, N.N., Hramenkov, S.V. Ultraviolet technologies in the modern world / A collective monograph. Dolgoprudny: Intellect Publishing House, 2012, 392 p.
7. Popov, O.A. and Chandler, R.T. Ferritefree high power electrodeless fluorescent lamp operated at a frequency of 160-1000 kHz // Plasma Sources Science and Technology, 2002, V.11, pp. 218-227.
8. Starshinov, P.V., Popov, O.A., Irkhin, I.V., Levchenko, V.A., Vasina, V.N. Electrodeless UV lamp on the basis of low pressure mercury discharge in a closed ferritefree tube // Light and Engineering, 2019, # 6, pp. 133-136.
9. Svitnev, S.A., Popov, O.A., Levchenko, V.A., Starshinov, P.A. Characteristics of low pressure ferritefree inductive discharge // Part 1. RF inductor electrical characteristics. Uspekhi prikladnoi fiziki, 2016. # 2, pp. 139-149.
10. Godyak, V.A., Popov, O.A., Hanna, A.K. Effects of electrode space charge sheath at RF discharge electrodynamic characteristics // Radiotekhnika i electronika, 1976. V21, pp. 2639-2641.
11. Raizer, Yu.P., Shneider, M.N., Yatsenko, N.A. Radiofrequency capacitive Discharges / Moscow: Nauka. Fizmatlit, 1995, 310 p.
12. Popov, O.A., Chandler, R.T., Maya, J. Inductivelycoupled linear light source operated at frequencies of 2-14 MHz // Light & Engineering, 2009. V17, # 1, pp. 98-105.
13. Popov, O.A. An effective light source based on inductive ferritefree discharge operated at frequencies 300-3000 kHz // Tech. Phys., 2007, V77, # 6, pp. 74-80.
14. Piejak, R.B., Godyak, V.A., Alexandrovich, B.M. ј Simple Analyses of an Inductive RF Discharge // Plasma Sources Science and Technology, 1992. V1, pp. 179-185.
15. Popov, O.A. and Maya, J. Characteristics of Electrodeless Ferritefree Fluorescent Lamp Operated at Frequencies of 1-15 MHz // Plasma Sources Science and Technology, 2000. # 9, pp. 227-235.
16. Rokhlin, G.N. Discharge light sources / ћ.: Energoatomizdat. 1991. 720 p.
17. Raizer Yu.P. Gas discharge physics / ћ.: Nauka. 1987.
18. Nikiforova, V.A., Popov, O.A. RF frequency and discharge current effects on plasma parameters radial distributions in the ferritefree inductivelycoupled discharge in the closedloop tube / MPEI Bulletin, 2012. #1, pp. 108-114.
19. Lee, H.C., Oh, S.J., Chung, C.W. Experimental observation of the skin effect on plasma uniformity in inductively coupled plasmas with a radio frequency bias // Plasma Sources Science and Technology, 2012. V21, # 3, 035003.
20. Aleksandrov, A.F., Vavilin, K.V., KralТkina, E.A., Neklyudova, P.A., Pavlov, V.B. Plasma parameters investigation of the RF inductive plasma source with diameter 46 cm // Part 1. Plasma parameters in the skin layer. Applied Physics [Prikladnaya fizika], 2013. #5, pp. 34-37.

Objects in nearinfrared (NIR) images can often have different linear scales and shapes than the same objects in optical images for visible spectrum (RedGreenBlue, RGB). Therefore they can require different computer vision methods for detection, tracking, and classification. This paper devoted to the methods by which the problems of moving objects detecting and tracking in NIR images are solved. The main characteristics of moving objects in image sequences are highlighted. Advantages and disadvantages of different methods for detecting and tracking objects in NIR images of airspace are considered and two of the most promising methods classes are selected. Studies have been carried out on the effectiveness of LucasKanade method, which is one of the methods of local optical flow, and the ORB method of scaleinvariant transformation of features when detecting and tracking moving objects in NIR images. In numerical experiments, more than 5000 NIR images containing moving objects of three types were used as well as three combinations of considered methods. It is shown which combination is the most accurate in the tasks of moving objects detection and tracking and can be used for airspace automatic operational control and management based on computer vision systems. Probably, other combinations of methods from the two considered classes also can help to increase accuracy of moving objects detection and tracking in airspace by NIR images.

1. Steger, C., Ulrich, M., Wiedemann, C. Machine Vision Algorithms and Applications / Weinheim: WileyVCH, 2018.
2. Zakharova, A.A., Korostelyov, D.A. Methods for Construction and Research Stereometric Visual Images of Multicriteria Alternatives // CEUR Workshop Proceedings, 2020. Vol. 2744, Part 2. Paper 23–1, doi:10.51130/graphicon2020–2–3–23.
3. ISO 20473:2007. Optics and photonics –Spectral bands, Geneva, 2007. 3 p.
4. Siwei, Y., Shaozuo, Y., Bingchen, Z., Yin, W. Reducing the feature divergence of RGB and nearinfrared images using Switchable Normalization // 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2020. pp. 206–211.
5. Mishchenko, A.M., Rachkovsky, S.S., Smolin, V.A., Yakimenko, I.V. Results of Spatial Structure of Atmosphere Radiation in a Spectral Range (1.5–2) µm // Light & Engineering, 2018. Vol. 26, No. 3. pp. 7–14.
6. Kataev, M. Yu., Dadonova, M.M., Efremenko, D. S. Illumination Correction of MultiTime RGB Images Obtained with an Unmanned Aerial Vehicle // Light & Engineering, 2021, Vol. 29, # 2, pp. 50–58.
7. Shaikh, S., Saeed, K., Chaki, N. Moving Object Detection Using Background Subtraction. // Springer Briefs in Computer Science. Springer, Cham, 2014, doi.org/10.1007/978–3–319–07386–6_3.
8. Alpatov, B.A., Babayan, P.V., Balashov, O.E., Stepashkin, A.I. Metody avtomaticheskogo obnaruzheniya i soprovozhdeniya ob”ektov // Obrabotka izobrazhenij i upravlenie. Moscow: Radiotekhnika, 2008. 176 p.
9. Ivanov, V.A., Kirichuk, V.S., Kosyh, V.P., Sinel’shchikov, V.V. Osobennosti obnaruzheniya tochechnyh ob”ektov v izobrazheniyah, formiruemyh matrichnym priyomnikom // Avtometriya, 2016. Vol. 52(2). pp. 10–19, doi:10.15372/AUT20160202.
10. Berezin, V.V., Cyculin, A.K. Obnaruzhenie i ocenivanie koordinat izobrazhenij tochechnyh ob”ektov v zadachah astronavigacii i adaptivnoj optiki // Vestnik Tihookeanskogo gosudarstvennogo universiteta, 2008. Vol. 1. pp. 11–20.
11. Kvarnstrom, M. et al. Image analysis algorithms for cell contour recognition in budding yeast // Optics express, 2008. Vol. 16. pp. 12943–12957, doi:10.1364/OE.16.012943.
12. Sablina, V.A., Novikov, A.I., Nikiforov, M. B., Loginov, A.A. Contour analysis application for object detection in aerial image sequence // 2014 3rd Mediterranean Conference on Embedded Computing (MECO), Budva, 2014. pp. 102–107, doi:10.1109/MECO.2014.6862668.
13. Kuhne, G., Richter, S., Beier, M. Motionbased segmentation and contourbased classification of video objects // Proceedings of the 9th ACM international conference on Multimedia, 2001. pp. 41–50, doi:10.1145/500141.500150.
14. Vishnyakov, B.V., Vizil’ter, Yu.V., Lagutenkov, A.V. Ispol’zovanie modificirovannogo metoda opticheskih potokov v zadache obnaruzheniya i mezhkadrovogo proslezhivaniya dvizhushchihsya ob”ektov // Vestnik komp’yuternyh i informacionnyh tekhnologij, 2007. Vol. 5. pp. 2–8.
15. Bolotova, Yu.A. Druki, A.A., Spicyn, V. G. Metody i algoritmy intellektual’noj obrabotki cifrovyh izobrazhenij / Ucheb. Posobie. Tomsk: Izdvo Tomskogo politekhnicheskogo universiteta, 2016. 208 p.
16. Vizil’ter, Yu.V., Vishnyakov, B.V. Issledovanie povedeniya avtoregressionnyh fil’trov v zadache vydeleniya i analiza dvizheniya na cifrovyh videoposledovatel’nostyah. Vestnik komp’yuternyh i informacionnyh tekhnologij, 2008. Vol. 8. pp. 2–8.
17. Beklemishev, N.D. The algorithm for the video tracking of the moving object // Preprints of the Keldysh Institute of Applied Mathematics, 2018. pp. 57–65, doi:10.20948/prepr2018–57.
18. Mitrofanov, S.A. Sravnenie effektivnosti razlichnyh metodov intellektual’nogo analiza dannyh v zadachah raspoznavaniya izobrazhenij // Innovacionnaya nauka, 2015. Vol. 12–2. pp. 96–98.
19. Tao, M., Bai, J., Kohli, P., Paris S. Simple Flow: A Noniterative, Sublinear Optical Flow Algorithm // Computer Graphics Forum, 2012. Vol. 31, doi:10.1111/j.1467–8659.2012.03013.x.
20. Gunnar Farneback “Twoframe motion estimation based on polynomial expansion” // Proceedings of the 13th Scandinavian conference on Image analysis (SCIA’03). SpringerVerlag, Berlin, Heidelberg, 2003. pp. 363–370. doi:10.1007/3–540–45103X_50
21. Bouguet, J.Y. Pyramidal implementation of the lucas kanade feature tracker // Intel Corporation, Microprocessor Research Labs, 1999.
22. Rublee, E., Rabaud, V., Konolige, K., Bradski, G. ORB: an efficient alternative to SIFT or SURF // Proceedings of the IEEE International Conference on Computer Vision, 2011. pp. 2564–2571. doi:10.1109/ICCV.2011.6126544.

Afterimages are common and frequent perceptual phenomena of everyday life. A typical appearance is the negative УghostФ image of a bright light source when we turn away from it. In the case of significant colour contrast, the afterimage can be coloured. The perceived false imageТs strength decreases gradually and completely disappears in a (10-100) s timescale.
The underlying processes have multiple components: a quick adaptation on the retinal level, and a slower adaptation on the neural level. Several studies discuss these mechanisms, but there are still important questions to be answered.
In our research, we apply the toplevel, blackbox style approach: instead of focusing on the inner details, we ask human test subjects to test and measure the duration and Уstrength scoreФ of the same lighttransitions. Our goal is to find the main features that affect the duration and subjective strength of the colour afterimages. Specifically, we examine whether the age and gender of the test subjects or the colourimetry parameters affect these parameters.
Two set of experiments were performed: colourcolour transitions with 41 and colourgrey transitions with 16 test subjects between 19 and 62.
We found that gender has no measurable influence, but age makes a difference in high significance. Both experiment types confirmed that over 40 years the average duration of colour afterimages decreases.

1. Mikamo, M., Slomp, M., Raytchev, B., Tamaki, T., Kaneda, K. Perceptually inspired afterimage synthesis // Computers and Graphics, 2013, Vol. 37, pp. 247-255.
2. Horvath, A., Domotor, G. Computational Simulation of Mesopic Vision Based on Camera Recordings // Light and Engineering, 2014, Vol. 22, #1, pp. 61-67.
3. Rinner, O., Gegenfurtner, K.R. Time course of chromatic adaptation for colour appearance and discrimination // Vision Research, 2017, Vol. 40, pp. 1813-1826.
4. Dong, B., Holm, L., Bao, M. Cortical mechanisms for afterimage formation: evidence from interocular grouping // Nature Scientific Reports, 2017, Vol. 7, p. 1-13.
5. Linksz, A. An essay on colour vision and clinical colourvision tests // Grune and Stratton, New York, USA, 1964, 254 p.
6. Hurvich, L.M. Colour Vision // Sinauer Associates Inc., Sunderland, Massachusetts, 1981, 326 p.
7. Alpern, M., Maaseidvaag, F., Ohba, N. The kinetics of cone visual pigments in man // Vision Research, 1971, #11, pp. 539-549.
8. Smith, C.V. Densitometric measurement of human cone photopigment kinetics // Vision Res., 1983, Vol. 23, #5, pp. 517-524.
9. Hayhoe, M. M., Benimoff, N. I., Hood, D.C. The time course of multiplicative and subtractive adaptation processes // Vision Research, 1987, #27, pp. 1981-1996.
10. Kefalov, V.J. Rod and cone visual pigments and phototransduction through pharmacological, genetic, and physiological approaches // The Journal of Biological Chemistry, 2012, Vol. 287, #3, pp. 1635-1641.
11. Stanikunas, R., Kulbokaite, V., Svegzda, A., Vaitkevicius, H., Daugirdiene, A., Kulikowski, J. J., Murray, I.J. Chromatic fading following complete adaptation to unique hues // Journal of Vision, 2020, Vol. 20, #6, 20 p.
12. Zaidi, Q., Ennis, R., Cao, D., Lee, B.B. Neural locus of colour afterimages // Current Biology, 2012, Vol. 22, #3, pp. 220-4.
13. Kingdom, F. A. A., Touma, S., Jennings, B.J. Negative afterimages facilitate the detection of real images // Vision Research, 2020, #170, pp. 25-34.
14. Virsu, V., Laurinen, P. Longlasting afterimages caused by neural adaptation // Vision Research, 1977, Vol. 17, #7, pp. 853-860.
15. Suzuki, T., Okajima, K., Funai, T. Development of senile miosis simulator adapting to variable illumination in colour environments // Optical Review, 2012, #19, pp. 174-181.
16. Elliott, W., Webster, Individual and agerelated variation in chromatic contrast adaptation // Journal of Vision 2012, Vol. 12, #8.
17. Werner, A., Bayer, A., Schwarz, G., Zrenner, E, Paulus, W. Effects of ageing on postreceptoral shortwavelength gain control: Transient tritanopia increases with age // Vision Research, 2010, #50, pp. 1641-1648.
18. Wuerger, Colour constancy across the life span: Evidence for Compensatory Mechanisms // Plos One, 2013.
19. Knoblauch, K., VitalDurand, F., Barbur, J.L. Variation of chromatic sensitivity across the life span // Vis. Res., 2001, #41, pp. 23-36
20. Sturr, J. F., Church, K. L., Taub, H.A. Early light adaptation in young, middleaged, and older observers // Perception and Psychophysics, 1985, #37, pp. 455-458.
21. Reidenbach, H.D. Determination of the time dependence of coloured afterimages, Proceedings Ophthalmic Technologies XVIII, 2008, Vol. 6844, 68441N.
22. Phuangsuwan, C., Ikeda, M., Mepeam, J. Colour appearance of afterimages compared to the chromatic adaptation of illumination // Colour research and application, 2018.
23. Ikeda, M., Phuangsuwan, C. Strong effect of the simultaneous colour contrast in an afterimage // Colour research and application, 2018.
24. Kline and Nestor Persistence of complementary afterimages as a function of adult age and exposure // Experimental Aging Research, 1977, Vol. 3, #3.
25. Garai, L., Horvath, A. Modelling of human colour perception depending on quick colour shifts on screen // 9th IEEE International Conference on Cognitive Infocommunications (CogInfoCom), 2018, pp. 223-226.
26. Garai, L., Horvath, A. Simulation of colour afterimages: an approach to computing colour afterimage // Hungarian Journal of Industry and Chemistry, 2019, #47, pp. 17-23.
27. Ekroll, V., Faul, F. Perceptual organization in colour perception: inverting the gamut expansion effect // iPerception, 2013, Vol. 4, pp. 328-332.
28. Schanda, J. Colourimetry: understanding the CIE system // John Wiley and Sons Inc., Hoboken, New Jersey, 2007, 467 p.
29. CIE15 Colourimetry, 2018.
30. Nicholls, A. Confidence limits, error bars and method comparison in molecular modeling. Part 2: comparing methods // J Comput Aided Mol Des 30, 2016, pp. 103-126.

Daylight harvesting is an apparent way of utilizing green energy in modern buildings which leads to sustainable development. In modern days, a huge amount of energy is consumed for lighting applications. So, in this article, we approached a novel photovoltaicbased daylighting system that can replicate the sunlight into an electric light inside a room. In general, this task is dependent on a photovoltaic cell and its maximum power point tracking for maximum energy conversion/extraction (daylight to electricity). So, we have developed a unique algorithm for this task which will lead to a maximum extraction of current based on the daylight condition outside. The MPPT algorithm is controlled by a microcontroller and the output light from the system is proportionate replication of the daylight available outside the room. The microcontroller controls the boost converter duty cycle for maximum power extraction. This article consists of detailed circuit diagrams and algorithm used for this whole system. This system is capable of lighting up a series of LED luminaires from a single photovoltaic cell.

1. Bhattacharjee, Sh. Artificial Skylight –  a photovoltaic based approach for daylight harvesting // Masters tech. thesis, School of Illumination Technology and Design, Jadavpur University, August 2021.
2. Ruck, N., Aschehoug, O., Aydinli, S., Jens, Ch. Daylight in Buildings –  A sourcebook on daylighting system and components // International Energy Agency Energy Conservation in Buildings and Community Systems Programm, June 2000.
3. Ander, G.D. Daylighting performance and design, 2nd edition // Building Engineer, 2003.
4. Rajib, M. Studies and development of a new intelligent controllerbased hybrid (solar & conventional) power management System // Master degree dissertation, Jadavpur University, 2013.
5. Esram, T., Champman, P.L. Comparison of photovoltaic array maximum power point tracking techniques // IEEE transactions on energy conversion, 2007, Vol. 22, #2, pp. 439–449.
6. Pandey, A., Dasgupta, N., Mukherjee, A.K. Highperformance algorithm for drift avoidance and fast tracking in solar MPPT systems // IEEE transactions on energy conversion, 2008, Vol. 22, #2, pp. 681–689.
7. Hohm, D. P., Ropp, M.E. Comparative study of maximum power point tracking algorithms // Prog. Photovolt: Res. Appl., 2003, Vol. 11, pp. 47–62.
8. Hua, C., Lin, J., Shen, C. Implementation of a DSPcontrolled photovoltaic system with peak power tracking // IEEE Trans. Ind. Electron., 1998, Vol. 45, #1, pp. 99–107.
9. Hart, D.W. Power electronics  // ISBN978–0–07–338067–4.
10. Mazidi, M. A., Mazidi, J. G., McKinla, R.D. The 8051 microcontroller and embedded systems, 2nd edition // Pearson, 2006.

1. Maxwell, J.C. On the Theory of Compound Colours and the Relations of the Colours of the Spectrum // Philosophical Transactions of the Royal Society of London, 1860, Vol. 150, Part 1.pp. 57-84.
2. Konig, A., Dieterici, C. Die Gnindempfindungen und ihre InlensitatsVertheilung im Spectrum // Sitzungsbenchte Akademie der Wissenschaften in Berlin, 1886, S. l.: S.n., pp. 805-829.
3. John Guild. The colorimetric properties of the spectrum // Philosophical Transactions of the Royal Society of London, 1931, Vol. A230, pp. 149-187.
4. Wright, W. D. A redetermination of the trichromatic coefficients of the spectral colours // Transactions of the Optical Society, 1928, Vol. 30, pp. 141-164.
5. Speranskaya N.I. Definition of Tristimulus Values of Spectrum Colours for 27 Normal Observers [Opredeleniye koordinat tsvetov spektra dlya 27 normalnykh nablyudateley] // Optika i spektroskopiya, 1959, Vol. 7, # 5, pp. 710-720.
6. Stiles, W.S. Increment thresholds and the mechanisms of colour vision // Doc. Ophthalmol., 1949, V. 3, pp. 138-152.
7. CIE (Commission Internationale de lТEclairage) Proc. 8th Session, Cambridge, England, September 1931, pp. 19-29.
8. CIE (Commission Internationale de lТEclairage), Proc. 15th Session (Paris, France: Bureau Central de la CIE, 1964), Vol. A, pp. 113-120.
9. Stockman A. Cone fundamentals and CIE standards // Current Opinion in Behavioural Sciences, 2019, Vol. 30, pp. 87-93.
10. Boos, G.V., Grigoryev, A.A., Rybina, V.A. The Experimental Research Installation for the Determination of Monochromatic Thresholds of Human Visual System // Light & Engineering Journal, 2021, Vol. 29, # 6, pp. 34-42.
11. Boos, G.V. Definition of Probability of Detection of Colour Objects against Colour Backgrounds Based on the Statistical Model of Human Threshold Chromatic Vision [Opredeleniye veroyatnosti obnaruzheniya tsvetnykh obТyektov na tsvetnykh fonakh na osnove statisticheskoy modeli porogovogo tsvetovogo zreniya cheloveka] // Svetotekhnika, 2017, # 6, pp. 27-31.
12. Linnik, Yu.V. The Least Squares Method and Basics of Mathematical and Statistical Theory of Observations Processing [Metod naimenshikh kvadratov i osnovy matematikostatisticheskoy teorii obrabotki nablyudeniy] / 2nd Edition, Moscow: Gos. izdvo fiz.mat. Lit, 1962, 354 p.
13. Yustova, E.N. Definition of Coordinate Axes of the Main Physiological System Based on Tests Involving ColourBlinds [Opredeleniye koordinatnykh osey osnovnoy fiziologicheskoy sistemy iz opytov s tsvetoslepymi] // Proceedings of the Academy of Sciences of the USSR, 1948, Vol. 63, # 4, pp. 383-385.
14. Boos, G.V., Grigoryev, A.A. New Approach in the Determination of Qualitative Characteristics of Outdoor Illumination Installations // Light & Engineering Journal, 2016, Vol. 24, pp. 51-57.
15. Nyberg, N.D. Determination of the Position of Primary Blue Colour in the Colour Triangle [Opredeleniye polozheniya v tsvetovom treugolnike osnovnogo sinego tsveta] // Proceedings of the USSR Academy of Sciences, 1949, Vol. 65, # 2, pp. 159-162.
16. CIE (Commission Internationale de lТEclairage) Proc. 8th Session, Cambridge, England, September 1931, pp. 19-29.
17. CIE (Commission Internationale de lТEclairage), Proc. 15th Session (Paris, France: Bureau Central de la CIE, 1964), Vol. A, p. 113.
18. CIE2006, CIE170-1:2006 Fundamental Chromaticity Diagram with Physiological Axes - Part 1: Vienna: CIE.
19. MacAdam, David L. Visual Sensitivities to Colour Differences in Daylight // Journal of the Optical Society of America, 1942, Vol. 32, # 5, pp. 247-274.