One-hour Intervals Research Articles

A dimensionality reduction method to select the most representative daylight illuminance distributions

ABSTRACTOne challenge when evaluating daylight distribution is dealing with the large amount of temporal and spatial data, visualizations and variability in illuminances that are assessed in buildings. Using a dimensionality reduction method based on principal component analysis, we identified the most representative annual daylight distributions. We modelled a rectangular room containing an analysis grid of 3200 illuminance sensor points and simulated 3285 different temporal daylight conditions using an annual occupancy schedule ranging from 08:00 to 17:00 with one-hour sampling intervals in two locations: Singapore and Oakland, California. Our approach explained 98% of the illuminance variability with three daylight distributions in Singapore, and 92% using six in Oakland, California. Our dimensionality reduction strategy was also generalized using a complex building geometry showing the utility of the method. We think this approach can be used to provide a more efficient and reliable method to analyse daylight performance in building practice.

NEURAL NETWORKS AS A MEANS TO PREDICTING THE STATE OF ISOLATION IN NETWORKS WITH ISOLATED NEUTRAL

Electrical insulation is an important parameter of the structural element of electrical equipment, provides reliability and durability of electrical networks with an isolated neutral and safe use of electricity in underground conditions. This article solves the problem of predicting changes in insulation resistance of electrical equipment, taking into account changes in external factors such as humidity and air temperature. An example of using a conventional neural network such as MLP did not give an acceptable result. To solve this problem, a recurrent neural network with longterm memory type LSTM was proposed. Its structure was developed. The simulation results showed that the neural network LSTM successfully coped with the task of predicting changes in insulation resistance, taking into account changing environmental factors. The prediction error for the one-hour interval was 0.052. The proposed idea of continuous monitoring of the insulation resistance with the prediction of its changes for a certain period will avoid sudden failures of electrical components, electric shock and fire caused by a decrease in insulation resistance below the critical value. The forecast of insulation resistance will allow in cases of delay of actuation of the device leakage at high rate of change of the insulation resistance, allows you to increase the efficiency of mining equipment through the reduction of damage from sudden shutdowns of the equipment underground mining machines in the course of their normal work.

Characteristics of probability distribution functions of low- and high-latitude current systems during Solar Cycle 24

Recent solar cycles (SCs) 21–24 have experienced a gradual decrease in their activity with considerable weakening during current SC 24. This is a unique opportunity to examine the long-term response of Earth’s low-latitude ring-current and high latitude auroral electrojet current systems during such systematically decreasing solar activity. With the advancement in technology, continuous recordings of ground/space magnetic field are available for the last few decades that allow us to explore the behaviour of probability distribution functions (PDFs) linked with the ring-current and auroral electrojet current systems for past five SCs (20–24). Also, PDFs linked with solar wind parameters that drive these current systems like magnetic field and velocity at Earth’s bow shock are examined. We noticed the significant narrowing of PDF of ring-current and auroral electrojet during SC 24. The number of one-hour intervals with Dst<-150 nT are less than 600 for SCs 20–23, which constitutes less than 0.7% of respective PDF, and number of one-hour intervals with Dst<-250 nT are less than 100 for SCs 20–23, which corresponds to less than 0.1% of respective PDF. But for SC 24 the Dst<-150 nT encountered only for 58 h, which corresponds to 0.06% of PDF and there are no intervals when Dst was <−250 nT. For auroral electrojet, the number of one-hour intervals with AE>750 nT and AE>1500 nT are less than 3060 and 70, respectively for SCs 20–23, which corresponds to <4% and <0.06% of respective PDFs. But for SC 24 the AE>750 nT encountered only for 1398 h, which corresponds to 1.7% of PDF and there are only 9 intervals when AE increased above 1500 nT, which is 0.01% of PDF. It implies that the probability of intense ring-current and auroral electrojet current during SC 24 was unusually low. Such narrowing is seen in PDFs of the interplanetary magnetic field and solar wind velocity as well. This fair quiet space weather experienced during SC 24 is attributed to the weakening of solar activity, which has subsequently influenced the strength of the interplanetary magnetic field and solar wind velocity at Earth’s bow shock.

Relative influence of forest and cropland on fluvial transport of soil organic carbon and nitrogen in the Nen River basin, northeastern China

Riverine transport of carbon and nitrogen strongly impacts terrestrial and aquatic ecosystem functions but is itself affected by changes in land cover and land use. China’s Nen River basin has experienced widespread conversion from forest to cropland in the past century, making it representative of similar global land use changes. We assessed organic carbon and nitrogen transport in this basin during 2018 and 2019, using water samples collected at one-hour intervals during the twelve flood events in two sub-basins (the Yalu and Yin rivers) dominated by forests and cropland, respectively. We also assessed dissolved organic carbon (DOC) and total dissolved nitrogen (TDN) concentrations from 19 sampling sites distributed throughout the Nen River basin, in combination with hydrological records, to investigate the impacts of land cover on riverine carbon and nitrogen fluxes. The forested Yalu river basin showed significantly higher DOC content and lower TDN content than Yin river basin. Riverine DOC concentrations during non-flood periods in the forested Yalu river basin were significantly higher than in the cultivated Yin river basin, but riverine TDN concentrations were lower. Throughout the Nen River basin and its sub-basins, riverine TDN content was proportional to cropland area. During the twelve flood events, riverine DOC and TDN varied widely over time in the Yin and Yalu river basins, possibly due to dilution effects of water originating from different land covers within the basins. Our results demonstrate that land cover is the principal cause of changes in riverine DOC and TDN content in this region.

Manual versus automatic identification of black-capped chickadee (Poecile atricapillus) vocalizations

One time-consuming aspect of bioacoustic research is identifying vocalizations from long audio recordings. SongScope (version 4.1.5. Wildlife Acoustics, Inc.) is a computer program capable of developing acoustic recognizers that can identify wildlife vocalizations. The goal of the current study was to compare the effectiveness of manual identification of black-capped chickadee vocalizations to identification by SongScope recognizers. A recognizer was developed for each main chickadee vocalization by providing previously annotated audio of chickadees. Six chickadees (three male, three female) were recorded in one-hour intervals with and without anthropogenic (i.e., man-made) noise to provide a variety of samples to test the recognizer. These recordings were analyzed via the recognizer and two human coders, with an additional third coder reviewing a random subset of recordings for reliability. Strong agreement was found between the human coders, κ = 0.76, p &lt; 0.00. Agreement between human coders and the recognizer was moderate for fee songs, κ = 0.46, p &lt; 0.00, and strong for fee-bee songs, κ = 0.77, p &lt; 0.00, as well as for chick-a-dee calls, κ = 0.82, p &lt; 0.00. Results showed that male chickadees produced more tseet calls in silence and females produced more gargle calls during noise. No differences were found in vocalizations based on time of day. Our observations also suggest that the chick-a-dee recognizer was capable of identifying gargle and tseet calls along with the intended chick-a-dee calls. Overall, SongScope was effective at identifying fee-bee songs and chick-a-dee calls, but not as effective for identifying fee songs. These recognizers can allow for faster acoustic analyses (by approximately four times) and be continuously improved for greater accuracy.

Effects of Acute Consumption of Noni and Chokeberry Juices vs. Energy Drinks on Blood Pressure, Heart Rate, and Blood Glucose in Young Adults.

The purpose of this study has been to determine the effect of acute consumption of noni and chokeberry juices vs. energy drinks on blood pressure, heart rate, and blood glucose. The subjects divided into 4 groups, which consumed three portions of noni or chokeberry juices (30 mL or 200 mL, respectively) and energy drink (ED) or water (200 mL) at one-hour intervals. All participants had their blood pressure (BP), both systolic and diastolic BP (SBP and DBP), as well as heart rate (HR) and blood glucose (BG), measured. Consumption of noni juice caused a significant decrease in SBP and DBP of 5.0% and 7.5%, respectively, while, the consumption of chokeberry juice slightly decreased only DBP by 3.6%. On the contrary, consumption of three portions of EDs caused a significant increase in DBP by 14.7%. The BG of participants consuming noni juice decreased by 7.3%, while the consumption of EDs increased BG by as much as 15.8%. Acute consumption of noni juice contributed to a significantly decreased SBP, DBP, and HR as well as a mild reduction of BG. Consumption of chokeberry juice caused only a slight reduction of DBP. Contrary to juices, EDs consumption resulted in an increase of blood pressure (especially DBP) and blood glucose. The results of the study showed that noni juice may be effective in lowering blood pressure and blood sugar levels, but there is a need to continue research on the long-term effect of this juice.

Relationship of turmeric and tamarind leaf extract ratio with induction time and antioxidant activity synergism

This study aims to determine the ratio of turmeric extract (TE) and tamarind leaf extract (TLE) which is suitable for the time of induction and the highest antioxidant synergism. The TE: TLE ratio examined is 10: 1; 10: 1.5 and 10: 2. The chosen variable is the amount of peroxide, observations carried out for 7 hours at one-hour intervals using ferric thiocyanate (FTC) method and thiobarbituric acid (TBA) method. The data than were made a graphic of the relationship between the time observations and absorbance, to show the induction time and synergism antioxidants. The results showed that all TE and TLE ratios had antioxidants that inhibited lipid oxidation reactions at the stage of initiation and propagation. TE and TLE ratios 10:1, 10:1,5 dan 10:2 have induction time, respectively 2.9577; 3.0206 and 3.1882 hours with FTC method, with the TBA method 3.6116; 3.706 and 3.8722 hours. Synergism antioxidant 103.534; 106.924 and 110.705%, with the FTC method, and with TBA 102.9393; 109.522 and 115.969%. The highest antioxidant synergism in both methods was shown by the ratio of TE:TLE = 10: 2.

Evaluation of wind energy potential and trends in Morocco

In recent years, the use of wind energy has become increasingly attractive for the successful and economic development. Wind energy is one of the fastest-growing renewable energy technologies of electricity generation. Wind energy has proved its potential in combating environmental degradation while ensuring a renewable, efficient and clean energy source. Good wind sites can even be competitive with traditional energy sources. In this paper, we used statistical methods namely Weibull probability density function for evaluating the wind energy potential as a power source in Morocco's regions, in particular Taza and Dakhla cities. Various methods were explored as wind variability, power density, standard deviation, Moroccan and WAsP methods for calculating the Weibull parameters using mean wind speed data measured at one-hour intervals. The wind data have been extracted at the height of 50 m and over a three-year period 2015–2017. Furthermore, the variations of monthly and annual wind speed are studied and the power and energy densities are evaluated. The monthly values of the Weibull shape parameter are on average 5.01 m/s at Taza and 9.04 m/s at Dakhla. The results obtained showed that the highest values of wind potential occur during March, July, September and December in Dakhla and during the December to March in Taza.

Day-Ahead Prediction of Microgrid Electricity Demand Using a Hybrid Artificial Intelligence Model

Improved-performance day-ahead electricity demand forecast is important to deliver necessary information for right decision of energy management of microgrids. It supports microgrid operators and stakeholders to have better decisions on microgrid flexibility, stability and control. The available conventional forecasting methods for electricity demand at national or regional level are not effective for electricity demand forecasting in microgrids. This is due to the fact that the electricity consumption in microgrids is many times less than the regional or national demands and it is highly volatile. In this paper, an integrated Artificial Intelligence (AI) based approach consisting of Wavelet Transform (WT), Simulated Annealing (SA) and Feedforward Artificial Neural Network (FFANN) is devised for day-ahead prediction of electric power consumption in microgrids. The FFANN is the basic forecasting engine of the proposed model. The WT is utilized to extract relevant features of the target variable (electric load data series) to obtain a cluster of enhanced-feature subseries. The extracted subseries of the past values of the electric load demand data are employed as the target variables to model the FFANN. The SA optimization technique is employed to obtain the optimal values of the FFANN weight parameters during the training process. Historical information of actual electricity consumption, meteorological variables, daily variations, weekly variations, and working/non-working day indicators have been employed to develop the forecasting tool of the devised integrated AI based approach. The approach is validated using electricity demand data of an operational microgrid in Beijing, China. The prediction results are presented for future testing days with one-hour time interval. The validation results demonstrated that the devised approach is capable to forecast the microgrid electricity demand with acceptably small error and reasonably short computation time. Moreover, the prediction performance of the devised approach has been evaluated relative to other four approaches and resulted in better prediction accuracy.

CRDI 기관에서 CITY MODE에 따른 바이오디젤 20% 적용특성

Biodiesel is a remarkable alternative fuel for the diesel engine among various countries. Various studies are carried out on the environmental and economic effects as well as the nature of diesel engine fuel biodiesel in the combustion process and emission characteristics. In this study, CRDI diesel engines used diesel fuel and 20 % biodiesel blend fuel (BD 20 %) as fuel, with City-mode exceeding 300 hours. Engine performance and emissions were sampled at one-hour intervals for analysis. The engine was inspected after testing to check the engine parts (valves and injectors). It was concluded that 300 hours of operation using BD 20 % does not cause abnormal deterioration of the engine or abnormal changes in engine power and exhaust gas.

A southern sky search for repeating fast radio bursts using the Australian SKA Pathfinder

We have conducted a search for bright repeating Fast Radio Bursts in our nearby Universe with the Australian Square Kilometer Array Pathfinder (ASKAP) in single-dish mode. We used eight ASKAP 12-m dishes, each equipped with a Chequerboard Phased Array Feed forming 36 beams on the sky, to survey $\sim$30,000 deg$^{2}$ of the southern sky ($-90^{\circ} < \delta < +30^{\circ}$) in 158 antenna days. The fluence limit of the survey is 22 Jyms. We report the detection of FRB 180515 in our survey. We found no repeating FRBs in a total mean observation of 3hrs per pointing divided into one-hour intervals, which were separated in time ranging between a day to a month. Using our non-detection, we exclude the presence of a repeating FRB similar to FRB 121102 closer than $z=0.004$ in the survey area --- a volume of at least $9.4 \times 10^4$Mpc$^3$ --- at 95% confidence.

Functional Assessment of Diluent Choice for Semen Cryopreservation from Stallions with High and Low Freezability

Background: fertility rates using horse frozen-thawed semen remain lower than in other livestock species. This fact further suggests that horse semen hold intrinsic sensitivity to cryoinjury that must be investigated. Moreover, there is a substantial influence of genetic factors and diluent choice upon horse cryopreservation outcome. Collectively, these genetic and technical properties of horse semen could be explored to identify factors or conditions that may increase semen viability after freeze-thawing. The aim of this work was to evaluate the effect of diluents Botu-Crio®,Lactose-EDTA®, and INRA-82® on cryopreserved semen from stallions with high (HFA) and low freezability (LFA).Materials, Methods &amp; Results: frozen-thawed semen was evaluated for motility, membrane integrity, and sperm DNA fragmentation using the thermoresistance test (TRT). Comparisons for each parameter were done in a pair-wise fashion between HFA and LFA semen at one-hour intervals during the TRT (0 h - 4 h). Sperm motility in HFA, regardless of the diluent, was larger (P &lt; 0.05) than LFA, both on 0h and 1h. In the 2h evaluation, sperm motility using Botu-Crio® and Lactose-EDTA® was greater (P &lt; 0.05) for HFA. Analysis of sperm membrane integrity was similar between HFA and LFA semen (P &gt; 0.05) at 0 h and 3 h. Sperm DNA fragmentation was lower (P &lt; 0.05) in HFA semen at 0 h and 1 h. Discussion: frozen-thawed semen from stallions of high freezing ability showed greater motility at all analysis, irrespectively of diluent choice, suggesting a strong influence of genetic factors on cryopreservation outcome. Membrane integrity was similar immediately after thawing but did differ later on other TRT time-points, irrespectively of diluent choice. As observed for motility, it was expected that sperm cells of stallions of HFA would show higher membrane integrity than their LFA counterparts. Sperm DNA fragmentation was quite low for both groups, as described in horses. Surprisingly, sperm DNA fragmentation incidence was constant throughout the analysis for both HFA and LFA. It was initially envisioned that increased DNA fragmentation would be found in semen from LFA stallions, since it is caused by multiple origins such as genetic factors. In conclusion, the semen diluent affects horse sperm motility after thawing, particularly from stallions with lower semen freezability.

Simulation of Threshold UV Exposure Time for Vitamin D Synthesis in South Korea

The threshold exposure time for synthesis of vitamin D was simulated by using a radiative transfer model considering variations in total ozone, cloud, and surface conditions. The prediction of total ozone took the form of an empirical linear regression with the variables of meteorological parameters in the upper troposphere and lower stratosphere and the climatology value of total ozone. Additionally, to consider cloud extinction after the estimation of clear-sky UV radiation using a radiative transfer model simulation, a cloud modification factor was applied. The UV irradiance was estimated at one-hour intervals, and then, to improve the temporal resolution of the exposure time simulation, it was interpolated to a one-minute resolution. Exposure times from the simulation clearly followed seasonal and diurnal cycles. However, upon comparison with observations, biases with large variations were found, and the discrepancy in the exposure time between the observations and simulations was higher in low UV irradiance conditions. The large deviations in the prediction errors for total ozone and the simplified assumption for the cloud modification factor contributed to the large deviations in exposure time differences between the model estimation and observations. To improve the accuracy of the simulated exposure time, improved predictions of total ozone with a more detailed cloud treatment will be essential.

Estimation of Hourly Link Population and Flow Directions from Mobile CDR

The rise in big data applications in urban planning and transport management is now widening and becoming a part of local government decision-making processes. Understanding people flow inside the city helps urban and transport planners build a healthy and lively city. Many flow maps are based on origin-and-destination points with crossing lines, which reduce the map’s readability and overall appearance. Today, with the emergence of geolocation-enabled handheld devices with wireless communication and networking capabilities, human mobility and the resulting events can be captured and stored as text-based geospatial big data. In this paper, we used one-week mobile-call-detail records (CDR) and a GIS road network model to estimate hourly link population and flow directions, based on mobile-call activities of origin–destination pairs with a shortest-path analysis for the whole city. Moreover, to gain the actual population size from the number of mobile-call users, we introduced a home-based magnification factor (h-MF) by integrating with the national census. Therefore, the final output link data have both magnitude (actual population) and flow direction at one-hour intervals between 06:00 and 21:00. The hourly link population and flow direction dataset are intended to optimize bus routes, solve traffic congestion problems, and enhance disaster and emergency preparedness.

Influence of hypoxic stimulation on angiogenesis and satellite cells in mouse skeletal muscle.

We clarified in our previous study that hypoxic training promotes angiogenesis in skeletal muscle, but the mechanism of angiogenesis in skeletal muscle remains unknown. In this study, we investigated the influence of differences in hypoxia exposure on angiogenesis in skeletal muscles at differing ages and metabolic characteristics at which the production of reactive oxygen species and nitric oxide may differ. Ten-week-old (young) and 20-month-old (old) mice were separated into control (N), continuous hypoxia (H), and intermittent hypoxia (IH) groups. The H group was exposed to 16% O2 hypoxia for 5 days and the IH group was exposed to 16% O2 hypoxia at one-hour intervals during the light period for 5 days. After completion of hypoxia exposure, the soleus and gastrocnemius muscles were immediately excised, and mRNA expression of angiogenesis- and satellite cell-related genes was investigated using real-time RT-PCR. In addition, muscle fiber type composition, muscle fiber area, number of satellite cells, and capillary density were measured immunohistochemically. In the young soleus muscle, the muscle fiber area was decreased in the H group, and mRNA expression of satellite cell activation-related MyoD, MHCe, and BDNF was significantly increased. On the other hand, in the old soleus muscle, nNOS and VEGF-A mRNA expression, and the capillary density were significantly increased in the H group. In the superficial portion of the gastrocnemius, mRNA expression of FGF2, an angiogenic factor secreted by satellite cells, was significantly increased in the young IH group. In addition, a positive correlation between VEGF-A mRNA expression and nNOS mRNA expression in the soleus muscle and eNOS mRNA expression in the superficial portion of the gastrocnemius was noted. These data demonstrated that age, hypoxia exposure method and muscle metabolic characteristics are related, which results in significant differences in angiogenesis.

Probabilistic Forecasting Model of Solar Power Outputs Based on the Naïve Bayes Classifier and Kriging Models

Solar power’s variability makes managing power system planning and operation difficult. Facilitating a high level of integration of solar power resources into a grid requires maintaining the fundamental power system so that it is stable when interconnected. Accurate and reliable forecasting helps to maintain the system safely given large-scale solar power resources; this paper therefore proposes a probabilistic forecasting approach to solar resources using the R statistics program, applying a hybrid model that considers spatio-temporal peculiarities. Information on how the weather varies at sites of interest is often unavailable, so we use a spatial modeling procedure called kriging to estimate precise data at the solar power plants. The kriging method implements interpolation with geographical property data. In this paper, we perform day-ahead forecasts of solar power based on the probability in one-hour intervals by using a Naïve Bayes Classifier model, which is a classification algorithm. We augment forecasting by taking into account the overall data distribution and applying the Gaussian probability distribution. To validate the proposed hybrid forecasting model, we perform a comparison of the proposed model with a persistence model using the normalized mean absolute error (NMAE). Furthermore, we use empirical data from South Korea’s meteorological towers (MET) to interpolate weather variables at points of interest.

Electromyographic Analysis of Shoulder Girdle Muscles in Volleyball Throw: A Reliability Study

Abstract Study aim: The aim of this study was to investigate the reliability of the electromyographic activity of selected shoulder girdle muscles during the overhead volleyball throw. Material and methods: The test-retest reliability of EMG activity of selected shoulder muscles during an overhead volleyball throw was investigated in 15 non-symptomatic university-level female volleyball players for within-day sessions (with a one-hour interval) and between-day sessions (with a one-week interval). Time broadness (a measure of coordination) and root mean square of electromyography signals were obtained. Results: A high within-day (0.85-0.99) and moderate to high between-day (0.68-0.93) intraclass correlation coefficient for normalized RMS activity and a high within-day and between-day intraclass correlation coefficient (0.94 and 0.80; respectively) for time broadness were observed. Absolute agreement of measurements had small values (0.15-1.96). Trends toward higher intraclass correlation coefficient values and lower standard error of measurements, minimum detectable change, mean differ­ences and limits of agreements values were observed for within-day reliability in all test results compared with between-day reliability. Conclusions: The results suggest that the activity of shoulder muscles can be reliably assessed during the overhead volleyball throw with the described procedure both in the amplitude domain (normalized average root mean square) and the time domain (time broadness of the activities).

Using a Genetic Algorithm with a Mathematical Programming Solver to Optimize a Real Water Distribution System

This research proposes a genetic algorithm that provides a solution to the problem of deficient distribution of drinking water via the current hydraulic network in the neighborhood “Fraccionamiento Real Montecasino” (FRM), in Huitzilac, Morelos, Mexico. The proposed solution is the addition of new elements to the FRM network. The new elements include storage tanks, pipes, and pressure-reducing valves. To evaluate the constraint satisfaction model of mass and energy conservation, the hydraulic EPANET solver (HES) is used with an optimization model to minimize the total cost of changes in the network (new pipes, tanks, and valves). A genetic algorithm was used to evaluate the optimization model. The analysis of the results obtained by the genetic algorithm for the FRM network shows that adequate and balanced pressures were obtained by means of small modifications to the existing network, which entailed minimal costs. Simulations were performed for an extended period, which means that the pressure was obtained by simulation with HSE at one-hour intervals, during the algorithm execution, to verify adequate pressure at a specific point in the system, or to make corrections to ensure proper distribution, this with the aim of having a final optimized network design.

A Comparative Study between Private-Sector and Automated Vehicle Identification System Data through Various Travel Time Reliability Measures

Traffic data from private-sector sources is increasingly used to estimate the travel time reliability of major road infrastructure. However, there is as yet no study evaluating the difference in estimating travel time reliability between the private-sector data and automated vehicle identification (AVI) based on radio frequency identification. As ground truth data, the AVI data were collected from an AVI system using toll tags and aggregated into five-minute intervals. As one of the representative traffic information providers, data from HERE was obtained through the Regional Integrated Traffic Information System, calculated in five-minute intervals. For the comparison, four kinds of measures were selected and estimated on the basis of the day of the week, specific time periods, and time of day in five-minute, 15-minute, and one-hour intervals. The statistical difference in travel time reliability was assessed through paired t-tests. According to the results, AVI and HERE data are comparable based on day of the week, specific time periods, and time of day at one-hour intervals, whereas at five-minute and 15-minute intervals, HERE and AVI data are not generally comparable. Thus, when estimating travel time reliability in real time, travel time reliability derived from HERE data may be different from the true travel time reliability. Considering that private-sector traffic data are currently used to estimate travel time reliability measures, the measures should be harmonized on the basis of robust statistics to provide more consistent measures related to the true travel time reliability.

Investigation of the Experimental Characterization of the Different Inorganic Light Emitting Diodes (LEDS) and the Photovoltaic Effect on These LED

&lt;p&gt;This paper describes our experiments on the electrical characterization of commercial light emitting diodes of different colors as well as their photoelectric effect. This experiment was conducted at the IMS of Bordeaux, which has a measurement bench allowing the intrinsic characterization of different light-emitting diodes in direct and reverse polarization. This bench also makes it possible to compare these experimental values with the theoretical values obtained by modeling.A second work done at the ENP of El-Harrach allowed us to put in place measurement means to show that there is a photovoltaic effect on the LEDs. For this purpose, we have measured the electrical characteristics of different LEDs and studied their light intensities using an EPLEY pyranometer. This work involved red, green , yellow ,white and blue LEDs. The photovoltaic behavior of light-emitting diodes (LEDs) was studied at ENP D'El Harrah Algeria, for a period of three days in March 2016. LEDs were exposed to solar radiation in the form of unitary units of LEDs. 9-16 hours These irradiated LEDs were monitored for photo-generated voltage and current at one-hour intervals. Solar radiation on a horizontal surface was measured using a Pyranometer.&lt;/p&gt;