Abstract: The purpose of this research is to construct a watching system that monitors human activity in a room and detects abnormalities at an early stage to prevent unattended deaths of people living alone. In this article, we propose a method whereby highly urgent abnormal conditions of a person are determined by changes in the concentration of CO2 generated from activity and respiration in a room. We also discussed the effects the amount of activity has on the determination. The results showed that this discrimination method is not dependent on the amount of activity and is effective in judging highly urgent abnormal conditions.
Abstract: Wireless Body Area Network (WBAN) is a short-range
wireless communication around human body for various applications
such as wearable devices, entertainment, military, and especially
medical devices. WBAN attracts the attention of continuous health
monitoring system including diagnostic procedure, early detection of
abnormal conditions, and prevention of emergency situations.
Compared to cellular network, WBAN system is more difficult to
control inter- and inner-cell interference due to the limited power,
limited calculation capability, mobility of patient, and
non-cooperation among WBANs.
In this paper, we compare the performance of resource allocation
scheme based on several Pseudo Orthogonal Codewords (POCs) to
mitigate inter-WBAN interference. Previously, the POCs are widely
exploited for a protocol sequence and optical orthogonal code. Each
POCs have different properties of auto- and cross-correlation and
spectral efficiency according to its construction of POCs. To identify
different WBANs, several different pseudo orthogonal patterns based
on POCs exploits for resource allocation of WBANs. By simulating
these pseudo orthogonal resource allocations of WBANs on
MATLAB, we obtain the performance of WBANs according to
different POCs and can analyze and evaluate the suitability of POCs
for the resource allocation in the WBANs system.
Abstract: This paper presents an application of Artificial Neural
Network (ANN) algorithm for improving power system voltage
stability. The training data is obtained by solving several normal and
abnormal conditions using the Linear Programming technique. The
selected objective function gives minimum deviation of the reactive
power control variables, which leads to the maximization of
minimum Eigen value of load flow Jacobian. The considered reactive
power control variables are switchable VAR compensators, OLTC
transformers and excitation of generators. The method has been
implemented on a modified IEEE 30-bus test system. The results
obtain from the test clearly show that the trained neural network is
capable of improving the voltage stability in power system with a
high level of precision and speed.
Abstract: Implementation of advanced technologies requires
sophisticated instruments that deal with the operation, control,
restoration and protection of rapidly growing power system network
under normal and abnormal conditions. Presently, the applications of
Phasor Measurement Unit (PMU) are widely found in real time
operation, monitoring, controlling and analysis of power system
network as it eliminates the various limitations of supervisory control
and data acquisition system (SCADA) conventionally used in power
system. The use of PMU data is very rapidly increasing its
importance for online and offline analysis. Wide area measurement
system (WAMS) is developed as new technology by use of multiple
PMUs in power system. The present paper proposes a model of
Matlab based PMU using Discrete Fourier Transform (DFT)
algorithm and evaluation of its operation under different
contingencies. In this paper, PMU based two bus system having
WAMS network is presented as a case study.
Abstract: Supermarkets are the most electricity-intensive type of
commercial buildings. The unsuitable indoor environment of a
supermarket provided by abnormal HVAC operations incurs waste
energy consumption in refrigeration systems. This current study
briefly describes significantly solid backgrounds and proposes easyto-
use analysis terminology for investigating the impact of HVAC
operations on refrigeration power consumption using the field-test
data obtained from building automation system (BAS). With solid
backgrounds and prior knowledge, expected energy interactions
between HVAC and refrigeration systems are proposed through
Pearson’s correlation analysis (R value) by considering correlations
between equipment power consumption and dominantly independent
variables (driving force conditions).The R value can be conveniently
utilized to evaluate how strong relations between equipment
operations and driving force parameters are. The calculated R values
obtained from field data are compared to expected ranges of R values
computed by energy interaction methodology. The comparisons can
separate the operational conditions of equipment into faulty and
normal conditions. This analysis can simply investigate the condition
of equipment operations or building sensors because equipment could
be abnormal conditions due to routine operations or faulty
commissioning processes in field tests. With systematically solid and
easy-to-use backgrounds of interactions provided in the present
article, the procedures can be utilized as a tool to evaluate the proper
commissioning and routine operations of HVAC and refrigeration
systems to detect simple faults (e.g. sensors and driving force
environment of refrigeration systems and equipment set-point) and
optimize power consumption in supermarket buildings. Moreover,
the analysis will be used to further study the FDD research for
supermarkets in future.
Abstract: In this research, the goal was construction of a system by which multiple sensors were used to observe the daily life behavior of persons living alone (while respecting their privacy), using this information to judge such conditions as bad physical condition or falling in the home, etc., so that these abnormal conditions can be made known to relatives and third parties. The daily life patterns of persons living alone are expressed by the number of responses of sensors each time that a set time period has elapsed. By comparing data for the prior two weeks, it was possible to judge a situation as “normal” when the person was in good physical condition or as “abnormal” when the person was in bad physical condition.
Abstract: loss of feedwater accident is one of the frequently sever accidents in steam boiler facilities. It threatens the system structural integrity and generates serious hazards and economic loses. The safety analysis of the thermal installations, based extensively on the numeric simulation. The simulation analysis using realistic computer codes like Relap5/Mod3.2 will help understand steam boiler thermal-hydraulic behavior during normal and abnormal conditions. In this study, we are interested on the evaluation of the radiant steam boiler assessment and response to loss-of-feedwater accident. Pressure, temperature and flow rate profiles are presented in various steam boiler system components. The obtained results demonstrate the importance and capability of the Relap5/Mod3.2 code in the thermal-hydraulic analysis of the steam boiler facilities.