Latitude Values Research Articles

A cross-regional examination of camelid herding practices in Peru from 900 BCE to 1450 CE: Insights from stable isotopes in camelid bone collagen and fiber.

The economic, socio-political, and cultural significance of camelids in the Andean region is well-recognized, yet an understanding of their management evolution over pre-historical periods remains limited. This study aims to fill this gap by conducting the first cross-regional assessment of camelid pastoralism in Peru from 900 BCE to 1470 CE, using stable carbon and nitrogen isotopic compositions from the bone collagen and fibers of 577archaeological camelids across 21 sites. This research investigates the spatio-temporal shifts in camelid dietary habits, focusing on how the rise of intensive agriculture may have influenced change and led to the evolution of distinct roles for camelids in coastal versus non-coastal Andean economies. Our analysis indicates an increase in δ13C values over time on the coast, suggesting a shift towards maize-based camelid diets. Conversely, δ13C values decrease over time in highland environments, suggesting camelids consumed relatively more wild C3 forage and/or cultivated crops such as tubers. The study also reveals a significant positive relationship between latitude and δ15N values, suggesting increasing environmental aridity enriches δ15N in bone collagen. After controlling for this latitudinal effect, we observe a rise in δ15N values in both coastal and non-coastal camelids, suggesting that in later periods camelids may have been foddered in agricultural fields that were enriched with guano or dung fertilizer used to intensify production. Importantly, this research uncovers a distinct dietary divergence between coastal and inland camelids. The observed divergence in diets suggests contrasting socio-economic uses of camelids, where coastal camelids were predominantly involved in ceremonial and political activities, while those in non-coastal areas were crucial to the subsistence economy.

Determining the influence of seasonal tilt angle on the efficiency of fixed solar photovoltaic modules

The object of this study is photovoltaic modules with different seasonal tilt angles at different geographical latitudes. The average annual efficiency of photovoltaic modules with different seasonal angles set at different geographical latitudes has been determined as the annual weighted average value of the cosine of the angle of incidence of solar rays on the plane of the photovoltaic module. The influence of seasonal tilt angles of photovoltaic modules at different geographical latitudes on their average annual efficiency was analyzed. Approximate values of the seasonal tilt angles of photovoltaic modules at different geographic latitudes take values that differ from the geographic latitude value by plus 15° for the winter period and minus 15° for the summer period. Modeling the average annual efficiency of photovoltaic modules depending on the seasonal tilt angles at different geographical latitudes made it possible to obtain refined values of the seasonal tilt angles of photovoltaic modules. Thus, at the latitude of 0°, 10°, 20°, 30°, 40°, 50°, and 60°, the tilt angle of photovoltaic modules for the winter period will be 14.8°, 24.6°, 34.5°. 44.4°, 54.1°, 63.6°, and 73°, respectively, and for summer ‒ minus 14.5°, minus 4.6°, 5°, 15.1°, 25.1°, 34.9°, and 44.7°. Dependences were obtained for determining the seasonal tilt angles of photovoltaic modules depending on the value of geographic latitude. The difference in the average annual efficiency of photovoltaic modules, which are installed at seasonal angles, and photovoltaic modules, which track the position of the Sun in the vertical plane, is 0.4 %. The results could be used as a basis for evaluating the efficiency of photovoltaic modules when determining the seasonal tilt angle at different geographic latitudes

Decision Tree-Based Direction Detection Using IMU Data in Autonomous Robots

Location detection plays a crucial role in various applications. In this study, a machine learning (ML) method using inertial measurement unit (IMU) data was developed to determine direction with the Global Positioning System (GPS). In this study, an electronic board was designed using an Arduino Mega, Altimu-10 IMU sensor, GPS module, and SD card module. This electronic board was placed on a car to create a new dataset. This dataset consists of 1952x11 data. The dataset was obtained using accelerometer (x, y, z), gyroscope (x, y, z), compass (x, y, z), and GPS sensor data. The Decision Tree Algorithm was proposed for direction determination in this study. The angles between each position and the previous position were calculated using the latitude and longitude values obtained from the collected data. Then, the data were divided into 4 classes: North, East, South, and West, based on specific angle ranges. Finally, a direction detection model was developed using IMU data in the proposed method, achieving an accuracy of approximately 82.11%.

COMPARATIVE ANALYSIS OF DIFFERENT VARIANTS OF AZIMUTHAL CONFORMAL PROJECTION FOR THE TERRITORY OF THE REPUBLIC OF SERBIA

<p>The paper analyzes four variants of conformal azimuthal projections for the territory of the Republic of Serbia. In the procedure, a double conformal mapping was applied. As it is common practice to perform mapping in azimuthal projections from a sphere to a plane, it was initially necessary to perform a conformal mapping from the ellipsoid to the sphere, after which a conformal mapping from the sphere to the plane was executed. The central point of the projection is a point with a value of 44° north latitude and 21° east longitude. The mapping territory is trapezoidal in shape, defined by the values of the geographic latitudes and longitudes of the southernmost (41°53'), northernmost (46°11'), westernmost (18°49'), and easternmost (23°) points in the territory of the Republic of Serbia. The mapping variants are defined based on different values of linear scale at the central point of the projection. Data processing was carried out within the Jupyter Notebook component, part of the Anaconda software package, using the Python programming language. The results are presented numerically, graphically, and visualized using AutoCAD software.</p>

WOMAN SAFETY APP

In today’s world, people using smart phones have increased rapidly and hence, a smart phone can be used efficiently for personal security or various other protection purposes. The heinous incident that outraged the entire nation has woken us to go for the safety issues and so a host of new apps have been developed to provide security systems to women via their phones. This project presents, an Android Application for the Safety of Women, this app can be activated by just shaking phone three times, whenever need arises. By just three times shake identifies the location of place through GPS and sends a message comprising this location URL to the registered contacts to help the one in dangerous situations. The unique feature of this application is to send the message to the registered contacts after the phone is shook for three times. Instant location tracking information via SMS helps to find the location of the victim quickly and can be rescued safely. A wide range of tracking systems has been developed for tracking vehicles and displaying their position on a map, applications has been developed which tracks the mobility of a human being. Now a days tracking a person’s mobility has become a crucial issue, specifically in case of women. If tracking a criminal could be implemented as a system which is cost effective and can be used for tracking a human being using a GPS equipped mobile phone rather than using a handheld GPS receiver. The main aim of our project is to develop an application that reduces the overall cost of tracking based on GPS system, which is satellite-based service, and it is available 24X7 everywhere in the whole world. GPS system can be used to get location which includes details like latitude, longitude and altitude values along with the time details, etc. It is a free of cost service available to every individual. In order to track the movement of the person we have used Google maps for mapping the location sent by the mobile phone. The mobile phone fetches the GPS location which communicates with the server using General Packet Radio Service (GPRS). This system is a low-cost service which is wireless data communication system. Mobile phone equipped with GPS receiver are easily available in the market, it is a latest technology. The mobile phone technology has enabled us to communicate across the world. The GPRS is one of the best and cheapest mode of communication available today. Key Words: Android, GPS, URL, Registered Contacts

Determining the influence of mounting angle on the average annual efficiency of fixed solar photovoltaic modules

The object of this study is photovoltaic modules with different options for the angle of their installation to the horizon at different geographical latitudes. The scientific problem to solve was determining the dependence of the average annual efficiency of solar photovoltaic modules on the mounting angle of photovoltaic modules and the value of geographical latitude. It has been proven that the efficiency of installation of solar photovoltaic modules can be increased by reducing the angle of their inclination to the horizon depending on the value of the geographical latitude at which they are installed. The average annual efficiency of photovoltaic modules with different mounting angles to the horizon at different geographical latitudes was determined as the annual weighted average value of the cosine of the angle of incidence of solar rays on the plane of the photovoltaic module. The maximum of the average annual efficiency of photovoltaic modules corresponds to a smaller value of the angle of their installation to the horizon than the value of the geographical latitude. So, with a latitude value of 10°, 20°, 30°, 40°, 50°, and 60°, the mounting angle of photovoltaic modules to the horizon will be 9.5°, 18.8°, 28°, 37°, 45.8°, and 54°, respectively. A dependence was derived that allows determining the mounting angle of photovoltaic modules to the horizon dependent on the value of the geographical latitude at which they are installed. A mathematical expression was also constructed that makes it possible to determine the average annual efficiency of photovoltaic modules depending on the angle of their installation to the horizon for different values of geographic latitude. The results could be used in calculating the average annual efficiency of photovoltaic modules based on the adjusted values of the angle of their installation to the horizon at different geographical latitudes

Design and Implementation of Smart Blind Stick for Obstacle Detection and Navigation System

The design, advancement, and evaluation of an IoT -enabled smart stick that can detect and alert users to obstacles is presented in this study to help visually impaired persons traverse the outside world. A water sensor deployed to identify puddles and other wet surfaces in the user's route, and ultrasonic sensors for detecting obstacles are all used in the suggested design. Additionally, after correctly detecting and recognising items, the user receives voice feedback through earphones regarding various obstacles and objects. The suggested smart stick has two modes: the first detects and recognises obstacles and provides speech feedback; the second mode employs ultrasonic sensors for detecting and response through vibration motors to inform about the direction of the obstacle. The suggested method enables users to alternate between the two modes based on their preferences and the surroundings. Additionally, the user's latitude and longitude values are recorded and uploaded to the IoT platform for efficient tracking through global system for wireless communication modules, allowing the user or device to be tracked in real time on the dashboard. An IoT-enabled environment generates an alert signal in the form of an SMS with Google Maps link generated using latitude and longitude coordinates, and this serves as a panic button for emergency assistance. The smart stick's design includes features such a long battery life, size adjustment, waterproofing, and light weight. Robust features, portability, stability, ease of access, and energy efficiency are all guaranteed by the entire design.

Upward and Poleward (but Not Phenological) Shifts in a Forest Tenebrionid Beetle in Response to Global Change in a Mediterranean Area.

There is an increasing volume of literature on the impact of climate change on insects. However, there is an urgent need for more empirical research on underrepresented groups in key areas, including species for which the effects of climatic change may seem less evident. The present paper illustrates the results of a study on a common forest tenebrionid beetle, Accanthopus velikensis (Piller and Mitterpacher, 1783), at a regional scale within the Mediterranean basin. Using a large set of records from Latium (central Italy), changes in the median values of elevation, latitude, longitude, and phenology between two periods (1900-1980 vs. 1981-2022) were tested. Records of A. velikensis in the period 1981-2022 showed median values of elevation and latitude higher than those recorded in the first period. Thus, in response to rising temperatures, the species became more frequent at higher elevation and in northern places. By contrast, A. velikensis does not seem to have changed its activity pattern in response to increased temperatures, but this might be an artifact due to the inclusion of likely overwintering individuals. The results obtained for A. velikensis indicate that even thermally euryoecious species can show changes in their elevational and latitudinal distribution, and that poleward shifts can be apparent even within a small latitudinal gradient.

Determination of Radiation Value by Month Using Artificial Neural Network Model; Ankara, Sivas, Erzurum example

This research examines the estimation of solar radiation using artificial neural network (ANN) models in Turkish cities with similar latitude values such as Ankara, Sivas and Erzurum. The aim of this study is to investigate whether cities at similar latitudes exhibit similar trends in solar radiation values, despite their geographical differences. In this study, solar radiation prediction was made for 3 cities with a single-layer neural network. Monthly solar radiation intensity was estimated for the 10-year period between 2012 and 2022 with a total of 4764 samples taken from the General Directorate of State Meteorology. An artificial neural network model was developed with 8 units in the first hidden layer and 4 units in the second hidden layer. The optimizer used in compiling the model was determined as Adam, the loss function as 'mean_squared_error' and the metric as 'mse'. ReLU activation function was used in the input layer and hidden layers. A 10-year solar radiation intensity value was used in the output layer. 70% of the data set is reserved for training and 30% for testing data set. As a result, similar solar radiation trends were obtained in the same latitude regions, the results were confirmed by meteorological data.

상수관망 관리를 위한 3D 공간정보 시스템 및 모델 프로토타입 개발

Recently, water supply problems and the advent of the 4th Industrial Revolution, smart water supply network management using digital twin technology is becoming needs. In this study, to develop a prototype of the model and system 3D visualization information system for water supply network management based on own technology without restrictions on licenses. Based on the data from the ME(2017), an inventory DB according to the Level classification was established, and for 3D visualization based on 2D information systems, 9-steps of implementation process and verification were conducted. Comparing and analyzing the values of latitude and longitude of polygons, it was confirmed that the reliability and accuracy of the two-dimensional information system implemented in this study were secured. Therefore, 3D visualization was performed using this, and the process of designing data linkage plans within the program and implementing 3D visualization was established. The results of this study are considered insignificant in the construction of a network management space server with high economic benefits and high reliability and accuracy of GIS.

Autonomous method for a strapdown inertial navigation system calibration in operation in operation

Strapdown inertial navigation systems (SINS) are widely used in modern air transport. The service life of such systems is decades. During this time, the characteristics of such systems may deteriorate due to the degradation of inertial sensors - gyroscopes and accelerometers. Under these conditions, in order to maintain the required accuracy of the SINS during the entire period of operation, it is necessary either to periodically carry out routine maintenance with the onboard system, or to continuously adapt the used sensor measurement model in terms of compensating for errors that arise. The second direction, which we will call calibration, has the advantage over the first one that it is carried out automatically by the system itself and does not require any additional equipment or additional maintenance work. The known method of SINS recalibration is based on the integration of information from the SINS and from the receiver of satellite radio navigation signals (SRNS). Such calibration, firstly, significantly depends on the availability and quality of satellite information, and secondly, it is possible only for integrated navigation systems in which the inertial subsystem is supplemented by a SRNS receiver. In contrast to the known method, this article solves the problem of autonomous SINS calibration, which is carried out after each flight. The solution is based on a linearized inertial navigation error model based on the boundary conditions of the state vector (at the beginning and end of the flight). The external information used consists only of the initial values of the coordinates and the current measurements of the baroaltimeter. As a result of the decision at the end of the flight, the errors of gyroscopes and accelerometers are determined, as well as the error in determining the final values of latitude and longitude in the SINS. Sensor errors can be used in subsequent system activations, which improves the accuracy of its operation as a whole. The analysis of the suitability and effectiveness of the developed methodology was carried out on a typical flight simulation program.

Antitheft Mobile Tracking System

Originally the GPS continuously acquires the satellite data and stores the latitude and longitude. With the help of the proposed system, we can track our mobile. In the proposed system, if we want to track mobile position also we need to shoot a communication to our device, by which it gets actuated. Once the operation gets actuated it takes the current latitude and longitude position values from the GPS. It sends a correspondence to the particular dispatch ID predefined at enrollment. It would be possible to track children's current locales using the proposed system.

Taxi fare prediction based on multiple machine learning models

The use of taxis as a fundamental mode of transportation in everyday life has led to the increased popularity of various ride-hailing applications such as Uber and Lyft, enabling users to conveniently request and view the predicted fare for their desired destination. Accurately predicting the fare is thus of significant importance. In this study, machine learning models were employed to forecast taxi fares based on factors such as distance and passenger count. As the initial data only contained latitude and longitude values, the Haversine formula was utilized to calculate the distance between two locations. Moreover, the raw data was plagued with inconsistencies such as negative fares and grossly exaggerated distances, which were resolved by implementing four data cleaning criteria. Following the preprocessing stage, three distinct models (i.e., linear regression, decision tree, and random forest) were trained and evaluated using the root mean square error metric. The results indicated that the random forest model produced the smallest error (1.264), followed by the decision tree model with a similar error rate (1.277), and lastly, the linear regression model with the highest error (1.718). Thus, the random forest model demonstrated superior performance and is recommended for accurate fare predictions.

Modeling and estimation of solar radiation of Karachi through artificial neural network (ANN) using temperature and dew-point

The most influential source of energy in our lives is solar energy. Solar energy reaches the earth in three different forms, i.e., Global, diffused, and Direct Solar Radiation. The Solar flux at the earth's surface depends on the intensity of these radiations and is a function of the values of latitude and longitude. The earth's temperature and hence dewpoint are greatly affected by solar flux. This idea is used for predicting solar radiation with input parameters, temperature, and dewpoint along with day number and month. The method of prediction of solar radiation used in the study is Artificial Neural Network (ANN). ANN has four variables in the input, ten neurons in the hidden layer, and three output parameters GSR. DSR and BSR. Six different types of errors, namely, Root Mean Square error (RMSE), Mean Absolute Error (MABE), Mean percent error (MAPE), Chi-square, Coefficient of Determination, Kolmogorov Smirnov, have been calculated for training, testing, and validation mode to check the accuracy of estimation. The values of all the errors are low, which indicates the prediction of solar radiation is reliable.

Accident Detection Using Raspberry Pi

Abstract: It is observed that, the major hindrance on road is due to heavy traffic flow during peak hours especially when people commute to work. The total number of vehicles or objects exceeds its capacity by causing a blockage for emergency vehicles such as fire fighter and rescue vehicles, furthermore wastage of fuels adds more to the environmental pollution which is not adoptable for a country’s economic growth. In order to develop an efficient, reliable, cleaner and safer mode of transportation,it is necessary to make the road transportation system automated as much as pos- sible.To track the vehicle, we need to send the message to GSM device, so that it gets activated. It also gets activated by detecting the accident on the vibration sensor connected to the raspberry pi controller. Once the GSM is activated it receives the last latitude and longitude position value and send message to the emergency serverwhich is predefined in the program. The process of image processing it detect the face of person and by using alarm it give the indication of that person

Impact of Cancer-Related Virtual Visits on Travel Distance, Travel Time, and Carbon Dioxide (CO2) Emissions during the COVID-19 Pandemic in Manitoba, Canada.

CancerCare Manitoba (CCMB) introduced virtual visits at the beginning of the COVID-19 pandemic to replace many in-person visits. This study examines the impact of virtual visits for cancer care on travel distance, travel time, and carbon dioxide (CO2) emissions. We included all visits to CCMB for invasive and in situ cancers from 1 April 2020 to 31 December 2022. Data were extracted from CCMB's electronic health record. The percentage of visits done virtually by month was reported by age, gender, cancer diagnosis, and regional health authority of residence. Postal codes for patients' residences and clinic locations were converted into latitude and longitude values. Travel distance, travel time, and CO2 emissions associated with travel were estimated. The percentage of virtual visits was highest during the months when COVID-19 restrictions were present in Manitoba and represent more than 50% of such monthly visits. Virtual visits increased with age, were highest among men with urogenital cancer, and were lowest among northern Manitoba residents. The median travel time per visit ranged from 30 min in Winnipeg to 15 h in the Northern Region. The estimated travel distance saved varied from 420,000 to 750,000 km per month. Estimated travel time saved varied from 5500 to 9600 h per month. Estimated CO2 emissions prevented varied from 87 to 155 metric tons per month. Virtual care is an important tool for better supporting those living with cancer by substantially decreasing travel distance and time. Virtual care also contributes to reducing greenhouse gas emissions.

English

Soil health in terms of plant available nutrients is crucial to estimate the yield potential of agricultural land in an area. Based on the availability of soil health data, it is possible to set yield targets using various yield prediction models. This study was initiated to estimate the concentration of DTPA-extractable micronutrients in Tehsil Muzaffargarh and to develop a database that can be used to develop predictive models. Soil samples (n=11537) were collected from Muzaffargarh (0-15 cm depth). The latitude and longitude values of sampling points were recorded for the purpose of georeferencing the soil samples. Micronutrients such as zinc (Zn), copper (Cu), iron (Fe) and manganese (Mn) were extracted with diethylenetriamine penta-acetate (DTPA) extraction solution and their concentrations were determined with atomic absorption spectrophotometer. Water soluble boron (B) was determined spectrophotometrically using Azomethine-H as colour developing reagent. Critical limits established by the National Agricultural Research Center (NARC) Islamabad, Pakistan, were used as a benchmark for grading micronutrient status. The ordinary kriging technique was used to visualize the micronutrient status in the surveyed area and digital maps were prepared using Quantum Geographic Information System (QGIS) software. Results showed that the range of DTPA-extractable micronutrients Zn, Fe, Mn, and Cu ranged from 0.10-5.92, 0.01-12.51, 0.09-10.00 and 0.03-8.08 µg/g, respectively. Boron concentration ranged from 0.02-1.98µg/g. Most of the soils in the studied area had adequate levels of Zn (61.9%) and Cu (48.6%) while 45.8, 43.3 and 55.4 % of the soil samples fell into the marginal category in terms of Cu, Mn, and B, respectively. The results revealed the widespread deficiency of DTPA-extractable Fe (< 4.5mg kg-1 in 74% soil samples) in Tehsil Muzaffargarh. The digitized maps developed from this study would serve as primary source to locate micronutrient deficient areas and also set site-specific yield targets along with other biophysical factors. However, these maps need ground truthing after crop harvest each year.

Country-level socioeconomic status relates geographical latitude to the onset of RA: a worldwide cross-sectional analysis in the METEOR registry

ObjectiveAge at rheumatoid arthritis (RA) onset varies by geographical latitude. We have investigated to what extent differences in patient-specific factors and country-level socioeconomic indicators explain this variability.MethodsPatients with RA from...

Design and implementation of school bus information and tracking system application

The school bus is a means of transportation that is very attractive to students because it is free. This study aims to develope an application that can track school bus trips and provide information about bus passengers. Bus location information sent to the user application can help students estimate the arrival time of the school bus at the pick-up point. In addition, information on the identity of school bus passengers can be used by parents to monitor the whereabouts of their children going to or from school on the bus. This application uses the global positioning system (GPS) of the smartphone on the school bus to find out the location of the bus and send it along with passenger identification information to the user application. To read passenger identities, near field communication (NFC) cards are used as passenger identity cards by tapping them on a smartphone on a school bus. Tests have been carried out on all functions of the application features and testing the accuracy of location reading and tracking of school bus trips, obtained latitude and longitude tolerance values of about 3.2 meters.

Computing optimum solar tilt angles for photovoltaic applications through python code simulation

AbstractCarrying out the dual objectives of computing the optimized tilt angles for multiple locations in Pakistan along with recommending a generalized approach for the estimation of optimum tilt angle for any location in country, this study was conducted. Python code was developed for the optimization purpose of daily, monthly, seasonally, biannually and annual solar tilt angle. Detailed analysis was presented for one location (Karachi) and a comparative analysis of optimum tilt angle conditions has been conducted for all investigated sites. Daily optimum tilt angles were found to vary from −12.0° to 55.5°. Similarly, monthly optimized tilt angles were found to vary from −11.5° (in June) to 55.0° (in December). Furthermore, seasonal tilt angles were found as 46.0 °, 2.0 °, 0.5 ° and 45.0 ° in winter, spring, summer and autumn respectively. Finally, annual optimum tilt angle (fixed throughout the year) was found as 25.5° (closer to the latitude value of Karachi). It has been found that daily adjustment of tilt angle causes a gain of 6.85% in annual energy yields when compared with fixed angle throughout the year. Similarly, energy gains were found as 0.15%, 1.24% and 6.83%, when tilt angle was adjusted daily as compared to monthly, seasonal and biannual adjustment cases respectively. The optimum tilt angle for three pairs of locations having comparable latitudes were compared and it was found that the sites having comparable latitudes do not have any marked difference in their optimum tilt angle values.