Tema ovog rada je određivanje mase nestandardnih tegova,
odnosno tegova koji nisu urađeni prema Međunarodnoj
preporuci OIML. U radu je opisan postupak određivanje mase
tegova sa proračunom merne nesigurnosti

Ovaj rad razmatra uticaj oslabljivača na merenje
harmonijskih izobličenja signala, koji se radi prilagođenja
nivoa vezuje na ulaz analizatora spektra. Imajući u vidu
frekvencijsku zavisnost slabljenja oslabljivača, izražena
je sumnja da njegov uticaj neće biti isti na osnovnoj
frekvenciji i njenim harmonicima. Kako u literaturi nije
razmatran ovaj aspekt, cilj istraživanja je bio da se
utvrdi uticaj oslabljivača na merenje harmonijskih
izobličenja. Analiza je obuhvatila tri varijante osnovnog
metoda baziranog na merenju harmonijskih izobličenja bez
primene oslabljivača i sa njim. Istraživanje je sprovedeno
u ograničenim uslovima koji se tiču odabira pogodnih
oslabljivača, frekvencije nosioca, merne nesigurnosti itd.
Eksperimentalni rezultati su pokazali da frekvencijska
karakteristika oslabljivača nema uticaj na merenje
harmonijskih izobličenja signala i da je njegov uticaj
opravdano zanemaren u literaturi.

U radu je opisano na koji način različiti tipovi
statističke obrade podataka utiču na rezultate merenja
stabilnosti oscilatora u vremenskom domenu. Istraživanje je
sprovedeno za oscilatore sa kvarcnom i rubidijumskom bazom,
pri čemu je poređenje izvršeno za nekoliko modela analize
podataka: Alanova i Hadamardova devijacija, u verzijama sa
i bez preklapanja.

U radu je predstavljena jedna metoda etaloniranja
stroboskopa upotrebom silicijumskog fotodetektora.
Predstavljanji su osnovni fizički i matematički rada
storposkopa, njihova primena, osnovne karakteristike i
ograničenja. Poseban osvrt u radu, dat je na budžet merne
nesigurnosti, glavne elemente budžeta merne nesigurnosti,
kao i proračun ukupne merne nesigurnosti tokom etaloniranja.

This paper presents an experimental investigation of
self-heating effects in precision resistors under different
thermal environments, with a focus on 1 Ω and 10 Ω
standards. The study examines resistor behavior under load
levels ranging from 2% to 80% of rated power at a
controlled ambient temperature of 23 °C. Measurements were
performed in both a temperature-controlled oil bath and an
air chamber in order to evaluate the influence of heat
dissipation conditions. In addition to steady-state
analysis, particular attention is given to how resistance
and temperature change over time during extended exposure
to constant load. Simultaneous monitoring of resistance and
internal temperature enabled a detailed assessment of
temperature rise (ΔT), resistance variation (ΔR), thermal
resistance (RT) and thermal stabilization processes. The
results reveal distinct differences between the two
environments and highlight the importance of time-dependent
effects in understanding self-heating and resistance
stability in precision resistors.

This paper presents the design of a cost-effective and
robust PCB device intended for irrigation in smart
agriculture,
with a specific focus on small and medium-sized farmers. The
system’s originality is in its dual irrigation regulation,
which
combines soil moisture data with hydraulic pressure
monitoring
using the MPX5700AP sensor. Unlike standard solutions that
rely
solely on moisture levels and timers, this integrated
approach
enables the detection of critical system failures such as
pipe
blockages, leakages, or pump “idle running”. The hardware is
based on the ESP32 microcontroller and utilizes LoRa
technology
for reliable, long-range communication in rural areas with
limited
network coverage. The device features a modular, cascade
power
supply system (+12V to +5V and +3V3) designed to withstand
harsh field conditions while protecting sensitive
components from
voltage spikes. By optimizing water and electricity
consumption,
this irrigation device design based on sensors aims to
mitigate
the negative effects of climate change and global warming,
provide predictive maintenance and malfunction detection of
the
pump and irrigation hose, increase crop yields, and ensure
the
sustainability of agricultural production through cost
effective
digitalization.

This paper contains an explanation of how a
fully functional control system is realized on a
microcontroller
and the different ways the user can interface with it. The
main
control loop is written in C language, specifically using
the
FreeRTOS embedded operating system. FreeRTOS enables the
microcontroller to handle multiple tasks, seemingly at
once. The
tasks include handling the system control loop, the Wi-Fi
functionality and other human – machine interface solutions
this project includes. The PC application written in Python
enables the user to communicate with the microcontroller
wirelessly.

This paper provides insight into how the electrooculogram
(EOG) can be measured and used in human-computer interface
(HCI) systems. The origin and method of acquisition of the
EOG signal are described. The difficulties for achieving
good measurements are presented, as well as difficulties
for user calibration and the possibilities for further
research and exploration. The aim of this paper is to study
the metrological difficulties in measuring EOG signals and
emphasize the future applications of the EOG based HCI
systems in practical uses.

This paper explores how to measure aircraft attitude using
Euler angles. It provides basics of this concept. The
sensors and filters for determination of attitude are
described. In addition, the paper introduces sources of
errors and uncertainties, along with calibration and
compensation techniques, to reduce errors. The goal is to
highlight the importance of accurate measurement of Euler
angles for reliable aircraft navigation, control and flight
safety.

This paper demonstrates communication between a digital
voltmeter that measures different voltage waveforms (sine,
triangular, square) from 200 mV to 20 V and an Arduino
Leonardo microcontroller which sends information about the
measured voltage to the computer. The use of a
microcontroller enables data processing and showing the
measuring value on the LCD display. One of the main goals
of the device is to improve the visual availability of
measurement data and processing on a computer. The use of
an external LCD display enables a clear, easy-to-read
display of the measured voltage, which facilitates the
monitoring and analysis of electrical parameters. In
addition to better visualization with the LCD, the
microcontroller can communicate with the computer, and thus
the processing and analysis of the measured data is carried
out.

This paper focuses on the analysis of metrological
improvements in electrocardiography (ECG) systems over
time, with the proposal of an artificial intelligence (AI)
algorithm to help improve the diagnostic department of
cardiology. The discussion reviews the comparison of analog
and digital ECG systems, the limitations of analog ECG
systems, the limitations of digital ECG systems and a
proposal for an AI model for the automatization of
metrological calibration with AI predictions of
cardiological diseases in real-time. The main idea is to
make the calibration process in real-time much more
reliable and automated aiming to save valuable time for
operators and try to support medical experts with real-time
detection of potential arrhythmia and prediction of
cardiovascular conditions by continuously analyzing the
live stream of physiological signals coming from digital
ECG devices.

This paper discusses general aspects of smart grids and
focuses on the detection and classification of power
quality in smart power grids using machine learning
algorithms. Power quality involves monitoring voltage
swells, voltage sags, voltage interruptions, harmonics,
frequency changes, and complex events involving multiple
problems in the power network. The problem of power quality
has become particularly important with the increasing use
of renewable energy sources, as the inclusion of large
consumers and producers of electricity creates significant
issues in the power network. This paper presents several
machine-learning methods for identifying power system
disturbances. For simplicity, the FFT transformation
extracts the characteristic features of the voltage
signals. After signal decomposition, the following
techniques are employed to classify power system
disturbance waveforms: Naive Bayes, Support Vector Machine
(SVM), K means, and Gaussian Mixture Model. Identification
of grid disturbances can be performed in real-time or as a
statistical analysis on a multi-month basis.