Implementation of a Remote Activation Alarm System by the Citizens of the District of Carabayllo, Lima-Peru

Citizen insecurity is a reality with which we must coexist, the cities of Latin America are among the most violent and insecure in the world. According to the statistics of the National Police of Peru, they report that by 2017 the crimes of theft or robbery were the most common because they had a monthly average of 15348 complaints, equivalent to 66.9% of the total crimes nationwide. The INEI (National Institute of Statistics and Informatics) revealed that in the same year the district of Carabayllo obtained 1.85% of the total complaints in Metropolitan Lima, occupying the 17th place in the ranking of districts with the highest number of complaints for this crime. That is why in the present research work a way to counteract these criminal acts was proposed, the first thing is to be located within the operating range of the RF module, so that the remote transmission control can activate it, the RF module will be connected to the power outlet and the siren. The siren will oversee persuading the criminal, in addition to alerting the neighbors about the events that are happening. It was obtained as a result that the system fulfills its purpose, it can be alerted in real time about some attempted theft or at the instant of a threat situation, only by pressing the button of the remote control we can persuade the criminals either by scaring them with the sound or with the help of the neighbors. Keywords-- Citizen insecurity, RF Module, Siren, Remote Control

A countrywide analysis of 27 solar power plants installed at different climates

The world is still heavily using nonconventional energy sources, which are worryingly based on carbon. The step is now alternative energy sources hoping that they will be more environmentally friendly. One of the important energy conversion forms by using these sources is photovoltaic solar systems. These type of power plants is on the increase in everyday on the world. Before investment a solar power plant in a specified region, a techno-economic analyse is performed for that power plant by using several meteorological data like solar irradiance and ambient temperature. However, this analyses generally lacks evaluation on effects of climatic and geographical conditions. In this work, 5 years of data of 27 grid-connected photovoltaic power plants are investigated, which are installed on seven different climate types in Turkey. Firstly, the power plants are categorized considering the tilt angles and Köppen–Gieger climate classification. The performance evaluations of the plants are mainly conducted using monthly average efficiencies and specific yields. The monthly average efficiencies, which were classified using the tilts and climate types were from 12 to 17%, from 12 to 16% and from 13 to 15% for tilts 30°/10°, 25° and 20°, respectively. The variation in the specific yields decrease with elevation as y(x) = − 0.068x + 1707.29 (kWh/kWp). As the performances of photovoltaic systems for some locations within the Csb climatic regions may relatively lower than some other regions with same climate type. Thus, techno-economic performance for PVPP located in this climate classification should be carefully treated.

Seasonal Distribution of the Radio Wave Refraction Index over the Territory of Buryatia

The values of the atmospheric refraction index N for ultra-short radio waves for the territory of Buryatia according to the data of meteorological stations were calculated. The monthly average values N contours maps for the central months of the seasons of 2020 were constructed. It is shown the humidity of Lake Baikal and the relief significantly influence N. On average, the values of the refractive index near the lake are 20–30 N-units higher. It is revealed the monthly average N values have maxima in winter and summer with minimums in spring and autumn, with the main maximum occurring in July.

Phytodiversity in Relation to Some Environmental Factors Of Some Wetland Habitats

The present research work was carried out on phytodiversity in relation to some environmental factors of three ponds namely, Pond-1, Pond-2 and Pond-3 of Zanjira upazila at Shariatpur district, Bangladesh where a total of 13 parameters were measured for one year. Monthly average different parameters of three ponds varied : air temperature from 23.5-36.50˚ C, water temperature 21-30.50 ˚ C,pH 7.10-8.50, TDS 55-227 mg/l, EC 103-463 μS/cm, DO 2.90-19.94 mg/l, alkalinity 0.73-5.40 meq/l, SRP 7.11-229.84 μg/l, SRS0.84-13.34 mg/l, NO3-N0.02-0.96 mg/l, chla1. 18-31.97 μg/l, phaeopigment 0.26-5.46 μg/l and phytoplankton density 6.50-119.50×106 ind/l. The total number of 122 species of phytoplankton were recorded in the studied ponds. Phytoplankton density showed positive correlation with air temperature, water temperature, pH, TDS, EC, alkalinity and SRP for Pond-1. Phytoplankton density showed positive correlation with pH, TDS, EC, DO and alkalinity for Pond-2. On the other hand phytoplankton density of Pond-3 showed positive correlation with air temperature, water temperature, TDS, EC, alkalinity, SRP, SRS, NO3-N and chlorophyll-a. During the period of present investigation some aquatic plants were found to grow in those shallow margins of the studied three ponds. Results indicated that Pond-1 is in a position undergoing eutrophic status, Pond-2 and Pond-3 are in the oligotrophic status. If the anthropogenic disturbances are continued in these ponds, it is likely that in near future these ponds would turn to eutrophic. Bangladesh J. Bot. 50(4): 1087-1094, 2021 (December)

Effects of Customized Skin Diagnosis Service on Participation-based Consumer Segmentation

Purpose: This study aimed to verify the possibility of consumer segmentation of customized cosmetic skin diagnosis services by identifying the needs of potential customers related to their consumption value, participation level, and pursuit benefits for each type of customized cosmetic service.Methods: An online survey was conducted for 13 days in September 2020 on individuals aged at least 20 years, living in Seoul and its metropolitan area. Among 483 received responses, only 393 were used for an analysis; insufficient responses and those written by residents living outside of the included region were excluded. Data were analyzed as per frequency analysis, factor analysis, reliability analysis, one-way ANOVA, post-hoc analysis, correlation analysis, and regression analysis.Results: Findings confirmed that consumer segmentation is possible in the customized cosmetic skin diagnosis services and customized ingredients services. After analyzing the average difference of consumption value, participation level, and pursuit benefits, the monthly average purchasing cost in cosmetics showed significant differences. Participation level, consumption value, and benefits were positively correlated. Participation level affects the consumption value.Conclusion: The customized cosmetic skin diagnosis service can serve as the foundation for the skin cosmetic industry development and as part of systematic and secure skincare.

Analysis and correlation of ultraviolet solar radiation from routine meteorological measurements over Egypt

For three years (1990-92) measurements of the monthly average daily global, G, and ultraviolet, UV, solar radiation incident on a horizontal surface at Cairo (30°15'N, 31°17'E) and Aswan (23°58'N, 32°47'E) are presented. processed and analysed. It was found that the computed monthly average daily values for the obtained solar radiation components, G and UV, were (18.1 MJ/m2, 0.55 MJ/m2, for Cairo and (22.1 MJ/m2, 0.71 MJ/m2, for Aswan. The effect of atmospheric dust on the measured solar radiation components is also investigated and discussed. The ratio of the ultraviolet to global radiation (UV/G) are calculated and compared with other sites in the Arabian Peninsula. A regression analysis has been done to find a correlation between G and UV at the selected sites during the three year period and the recommended correlation equations have also been stated. Since the meteorological measurements of UV solar radiation are not available over Egypt. except at Cairo (Lower Egypt) and Aswan (Upper Egypt) stations, our correlation equations can be used to calculate this component from the available global solar radiation measurements at any site in the two zones of Upper and Lower Egypt.

Enabling Year-round Cultivation in the Nordics-Agrivoltaics and Adaptive LED Lighting Control of Daily Light Integral

High efficacy LED lamps combined with adaptive lighting control and greenhouse integrated photovoltaics (PV) could enable the concept of year-round cultivation. This concept can be especially useful for increasing the production in the Nordic countries of crops like herbaceous perennials, forest seedlings, and other potted plants not native of the region, which are grown more than one season in this harsh climate. Meteorological satellite data of this region was analyzed in a parametric study to evaluate the potential of these technologies. The generated maps showed monthly average temperatures fluctuating from −20 °C to 20 °C throughout the year. The natural photoperiod and light intensity also changed drastically, resulting in monthly average daily light integral (DLI) levels ranging from 45–50 mol·m−2·d−1 in summer and contrasting with 0–5 mol·m−2·d−1 during winter. To compensate, growth room cultivation that is independent of outdoor conditions could be used in winter. Depending on the efficacy of the lamps, the electricity required for sole-source lighting at an intensity of 300 µmol·m−2·s−1 for 16 h would be between 1.4 and 2.4 kWh·m−2·d−1. Greenhouses with supplementary lighting could help start the cultivation earlier in spring and extend it further into autumn. The energy required for lighting highly depends on several factors such as the natural light transmittance, the light threshold settings, and the lighting control protocol, resulting in electric demands between 0.6 and 2.4 kWh·m−2·d−1. Integrating PV on the roof or wall structures of the greenhouse could offset some of this electricity, with specific energy yields ranging from 400 to 1120 kWh·kW−1·yr−1 depending on the region and system design.

SARIMA modeling of the monthly average maximum and minimum temperatures in the eastern plateau region of India

The SARIMA time series model is fitted to the monthly average maximum and minimum temperature data sets collected at Giridih, India for the years 1990-2011. From the time-series plots, we observe that the patterns of both the series are quite different; maximum temperature series contain sharp peaks in almost all the years while it is not true for the minimum temperature series and hence both the series are modeled separately (also for the sake of simplicity). SARIMA models are selected based on observing autocorrelation function (ACF) and partial autocorrelation function (PACF) of the monthly temperature series. The model parameters are obtained by using maximum likelihood method with the help of three tests [i.e., standard error, ACF and PACF of residuals and Akaike Information Criteria (AIC), Bayesian Information Criteria (BIC) and corrected Akaike Information Criteria (AICc)]. Adequacy of the selected models is determined using diagnostic checking with the standardized residuals, ACF of residuals, normal Q-Q plot of the standardized residuals and p-values of the Ljung-Box statistic. The models ARIMA (1; 0; 2) × (0; 1; 1)12 and ARIMA (0; 1; 1) × (1; 1; 1)12 are finally selected for forecasting of monthly average maximum and minimum temperature values respectively for the eastern plateau region of India.

Improved HIV case finding among key populations after differentiated data driven community testing approaches in Zambia

Introduction Open Doors, an HIV prevention project targeting key populations in Zambia, recorded low HIV positivity rates (9%) among HIV testing clients, compared to national adult prevalence (12.3%), suggesting case finding efficiency could be improved. To close this gap, they undertook a series of targeted programmatic and management interventions. We share the outcomes of these interventions, specifically changes in testing volume, HIV positivity rate, and total numbers of key populations living with HIV identified. Methods The project implemented a range of interventions to improve HIV case finding using a Total Quality Leadership and Accountability (TQLA) approach. We analyzed program data for key populations who received HIV testing six months before the interventions (October 2017–March 2018) and 12 months after (April 2018–March 2019). Interrupted time series analysis was used to evaluate the impact on HIV positivity and total case finding and trends in positivity and case finding over time, before and after the interventions. Results While the monthly average number of HIV tests performed increased by only 14% post-intervention, the monthly average number of HIV positive individuals identified increased by 290%. The average HIV positivity rate rose from 9.7% to 32.4%. Positivity rates and case finding remained significantly higher in all post-intervention months. Similar trends were observed among FSW and MSM. Conclusions The Open Doors project was able to reach large numbers of previously undiagnosed key populations by implementing a targeted managerial and technical intervention, resulting in a significant increase in the HIV positivity rate sustained over 12 months. These results demonstrate that differentiated, data-driven approaches can help close the 95-95-95 gaps among key populations.

Development of Statistically Downscaled Regional Climate Model based on Representative Concentration Pathways for Ipoh, Subang and KLIA Sepang in Peninsular Malaysia

Climate change is one of the challenging global issues that our world is facing and it is intensely debated on the international agenda. It is a fact that climate change has brought about many disastrous events on a global scale which affect our livelihoods. Climate models are commonly used by researchers to study the magnitude of the changing climate and to simulate future climate projections. Most climate models are developed based on various interactions among the Earth’s climate components such as the land surface, oceans, atmosphere and sea-ice. In this study, the second-generation Canadian Earth System Model (CanESM2) was statistically downscaled to develop a regional climate model (RCM) based on three representative concentration pathways (RCPs): RCP2.6, RCP4.5 and RCP8.5. The RCM will be used to simulate the average minimum and maximum temperatures and average precipitation for Ipoh, Subang and KLIA Sepang in Peninsular Malaysia for the years 2006 to 2100. The simulated data were bias corrected using the historical observation data of monthly average minimum and maximum temperatures and monthly average rainfall retrieved from the Malaysian Meteorological Department (MMD). The different trends of the simulated data for all the three locations based on the RCP2.6, RCP4.5 and RCP8.5 were evaluated for future climate projection.