Abstract: Wireless Sensor Networks consist of inexpensive, low power sensor nodes deployed to monitor the environment and collect
data. Gathering information in an energy efficient manner is a critical aspect to prolong the network lifetime. Clustering algorithms have an advantage of enhancing the network lifetime. Current clustering algorithms usually focus on global re-clustering and local re-clustering separately. This paper, proposed a combination of those two reclustering methods to reduce the energy consumption of the network. Furthermore, the proposed algorithm can apply to homogeneous as well as heterogeneous wireless sensor networks. In addition, the cluster head rotation happens, only when its energy drops below a dynamic threshold value computed by the algorithm. The simulation result shows that the proposed algorithm prolong the network lifetime compared to existing algorithms.
Abstract: A technique proposed for the automatic detection
of spikes in electroencephalograms (EEG). A multi-resolution
approach and a non-linear energy operator are exploited. The
signal on each EEG channel is decomposed into three sub bands
using a non-decimated wavelet transform (WT). The WT is a
powerful tool for multi-resolution analysis of non-stationary signal
as well as for signal compression, recognition and restoration.
Each sub band is analyzed by using a non-linear energy operator,
in order to detect spikes. A decision rule detects the presence of
spikes in the EEG, relying upon the energy of the three sub-bands.
The effectiveness of the proposed technique was confirmed by
analyzing both test signals and EEG layouts.
Abstract: Many advanced Routing protocols for wireless sensor networks have been implemented for the effective routing of data. Energy awareness is an essential design issue and almost all of these routing protocols are considered as energy efficient and its ultimate objective is to maximize the whole network lifetime. However, the introductions of video and imaging sensors have posed additional challenges. Transmission of video and imaging data requires both energy and QoS aware routing in order to ensure efficient usage of the sensors and effective access to the gathered measurements. In this paper, the performance of the energy-aware QoS routing Protocol are analyzed in different performance metrics like average lifetime of a node, average delay per packet and network throughput. The parameters considered in this study are end-to-end delay, real time data generation/capture rates, packet drop probability and buffer size. The network throughput for realtime and non-realtime data was also has been analyzed. The simulation has been done in NS2 simulation environment and the simulation results were analyzed with respect to different metrics.
Abstract: In modern day disaster recovery mission has become
one of the top priorities in any natural disaster management regime.
Smart autonomous robots may play a significant role in such
missions, including search for life under earth quake hit rubbles,
Tsunami hit islands, de-mining in war affected areas and many other
such situations. In this paper current state of many walking robots are
compared and advantages of hexapod systems against wheeled robots
are described. In our research we have selected a hexapod spider
robot; we are developing focusing mainly on efficient navigation
method in different terrain using apposite gait of locomotion, which
will make it faster and at the same time energy efficient to navigate
and negotiate difficult terrain. This paper describes the method of
terrain negotiation navigation in a hazardous field.
Abstract: The objective of this study is to present the test
results of variable air volume (VAV) air conditioning system
optimized by two objective genetic algorithm (GA). The objective
functions are energy savings and thermal comfort. The optimal set
points for fuzzy logic controller (FLC) are the supply air temperature
(Ts), the supply duct static pressure (Ps), the chilled water
temperature (Tw), and zone temperature (Tz) that is taken as the
problem variables. Supply airflow rate and chilled water flow rate are
considered to be the constraints. The optimal set point values are
obtained from GA process and assigned into fuzzy logic controller
(FLC) in order to conserve energy and maintain thermal comfort in
real time VAV air conditioning system. A VAV air conditioning
system with FLC installed in a software laboratory has been taken for
the purpose of energy analysis. The total energy saving obtained in
VAV GA optimization system with FLC compared with constant air
volume (CAV) system is expected to achieve 31.5%. The optimal
duct static pressure obtained through Genetic fuzzy methodology
attributes to better air distribution by delivering the optimal quantity
of supply air to the conditioned space. This combination enhanced
the advantages of uniform air distribution, thermal comfort and
improved energy savings potential.
Abstract: The African Great Lakes Region refers to the zone
around lakes Victoria, Tanganyika, Albert, Edward, Kivu, and
Malawi. The main source of electricity in this region is hydropower
whose systems are generally characterized by relatively weak,
isolated power schemes, poor maintenance and technical deficiencies
with limited electricity infrastructures. Most of the hydro sources are
rain fed, and as such there is normally a deficiency of water during
the dry seasons and extended droughts. In such calamities fossil fuels
sources, in particular petroleum products and natural gas, are
normally used to rescue the situation but apart from them being nonrenewable,
they also release huge amount of green house gases to our
environment which in turn accelerates the global warming that has at
present reached an amazing stage. Wind power is ample, renewable,
widely distributed, clean, and free energy source that does not
consume or pollute water. Wind generated electricity is one of the
most practical and commercially viable option for grid quality and
utility scale electricity production. However, the main shortcoming
associated with electric wind power generation is fluctuation in its
output both in space and time. Before making a decision to establish
a wind park at a site, the wind speed features there should therefore
be known thoroughly as well as local demand or transmission
capacity. The main objective of this paper is to utilise monthly
average wind speed data collected from one prospective site within
the African Great Lakes Region to demonstrate that the available
wind power there is high enough to generate electricity. The mean
monthly values were calculated from records gathered on hourly
basis for a period of 5 years (2001 to 2005) from a site in Tanzania.
The documentations that were collected at a height of 2 m were
projected to a height of 50 m which is the standard hub height of
wind turbines. The overall monthly average wind speed was found to
be 12.11 m/s whereas June to November was established to be the
windy season as the wind speed during the session is above the
overall monthly wind speed. The available wind power density
corresponding to the overall mean monthly wind speed was evaluated
to be 1072 W/m2, a potential that is worthwhile harvesting for the
purpose of electric generation.
Abstract: This paper presents a multi-objective formulation for
optimal siting and sizing of distributed generation (DG) resources in
distribution systems in order to minimize the cost of power losses
and energy not supplied. The implemented technique is based on
particle swarm optimization (PSO) and weight method that employed
to obtain the best compromise between these costs. Simulation
results on 33-bus distribution test system are presented to
demonstrate the effectiveness of the proposed procedure.
Abstract: A new approach to predict the 3D structures of proteins by combining the knowledge-based method and Molecular Dynamics Simulation is presented on the chicken villin headpiece subdomain (HP-36). Comparative modeling is employed as the knowledge-based method to predict the core region (Ala9-Asn28) of the protein while the remaining residues are built as extended regions (Met1-Lys8; Leu29-Phe36) which then further refined using Molecular Dynamics Simulation for 120 ns. Since the core region is built based on a high sequence identity to the template (65%) resulting in RMSD of 1.39 Å from the native, it is believed that this well-developed core region can act as a 'nucleation center' for subsequent rapid downhill folding. Results also demonstrate that the formation of the non-native contact which tends to hamper folding rate can be avoided. The best 3D model that exhibits most of the native characteristics is identified using clustering method which then further ranked based on the conformational free energies. It is found that the backbone RMSD of the best model compared to the NMR-MDavg is 1.01 Å and 3.53 Å, for the core region and the complete protein, respectively. In addition to this, the conformational free energy of the best model is lower by 5.85 kcal/mol as compared to the NMR-MDavg. This structure prediction protocol is shown to be effective in predicting the 3D structure of small globular protein with a considerable accuracy in much shorter time compared to the conventional Molecular Dynamics simulation alone.
Abstract: Increased energy demand and the concern about
environment friendly technology, renewable bio-fuels are better
alternative to petroleum products. In the present study linseed oil was
used as alternative source for diesel engine fuel and the results were
compared with baseline data of neat diesel. Performance parameters
such as brake thermal efficiency (BTE) and brake specific fuel
consumption (BSFC) and emissions parameters such as CO,
unburned hydro carbon (UBHC), NOx, CO2 and exhaust temperature
were compared. BTE of the engine was lower and BSFC was higher
when the engine was fueled with Linseed oil compared to diesel fuel.
Emission characteristics are better than diesel fuel. NOx formation by
using linseed oil during the experiment was lower than diesel fuel.
Linseed oil is non edible oil, so it can be used as an extender of diesel
fuel energy source for small and medium energy needs.
Abstract: The power system network is becoming more
complex nowadays and it is very difficult to maintain the stability
of the system. Today-s enhancement of technology makes it
possible to include new energy storage devices in the electric
power system. In addition, with the aid of power electronic
devices, it is possible to independently exchange active and
reactive power flow with the utility grid. The main purpose of this
paper proposes a Proportional – Integral (PI) control based 48 –
pulse Inverter based Static Synchronous Series Compensator
(SSSC) with and without Superconducting Magnetic Energy
Storage (SMES) used for enhancing the transient stability and
regulating power flow in automatic mode. Using a test power
system through the dynamic simulation in Matlab/Simulink
platform validates the performance of the proposed SSSC with and
without SMES system.
Abstract: Using ab initio theoretical calculations, we present
analysis of fragmentation process. The analysis is performed in two
steps. The first step is calculation of fragmentation energies by ab
initio calculations. The second step is application of the energies to
kinetic description of process. The energies of fragments are
presented in this paper. The kinetics of fragmentation process can be
described by numerical models. The method for kinetic analysis is
described in this paper. The result - composition of fragmentation
products - will be calculated in future. The results from model can be
compared to the concentrations of fragments from mass spectrum.
Abstract: Spatial understanding and the understanding of
dynamic change in the spatial structure of molecules during a
reaction is essential for designing new molecules. Knowing the
physical processes in the reactions helps to speed up the designing
process. To support the designer with the correct representation of
the designed molecule as well as showing the dynamic behavior of
the whole reacting system is the goal of our application. Our system
shows the spatial deformation of the molecules at every time interval
by minimizing the energy level of the molecules. The position and
orientation of the molecules can be intuitively controlled by
manipulating objects of the real world using Augmented Reality
techniques. Our approach has the potential to speed up the design of
new molecules and help students to understand the chemical
processes better.
Abstract: Dehydration behavior gives a hint about thermal properties of materials. It is important for the usage areas and transportation of minerals. Magnesium borates can be used as additive materials in areas such as in the production of superconducting materials, in the composition of detergents, due to the content of boron in the friction-reducing additives in oils and insulating coating compositions due to their good mechanic and thermal properties.
In this study, thermal dehydration behavior of admontite (MgO(B2O3)3.7(H2O)), which is a kind of magnesium borate mineral, is experimented by microwave energy at 360W. Structure of admontite is suitable for the investigation of dehydration behavior by microwave because of its seven moles of crystal water. It is seen that admontite lost its 28.7% of weight at the end of the 120 minutes heating in microwave furnace.
Abstract: An exploration in the competency of the optical
multilevel Mapping Multiplexing Technique (MMT) system in
tolerating to the impact of nonlinearities as Self Phase Modulation
(SPM) during the presence of dispersion compensation methods. The
existence of high energy pulses stimulates deterioration in the chirp
compression process attained by SPM which introduces an upper
power boundary limit. An evaluation of the post and asymmetric prepost
fiber compensation methods have been deployed on the MMT
system compared with others of the same bit rate modulation formats.
The MMT 40 Gb/s post compensation system has 1.4 dB
enhancements to the 40 Gb/s 4-Arysystem and less than 3.9 dB
penalty compared to the 40 Gb/s OOK-RZsystem. However, the
optimized Pre-Post asymmetric compensation has an enhancement of
4.6 dB compared to the Post compensation MMT configuration for a
30% pre compensation dispersion.
Abstract: The international society focuses on the environment
protection and natural energy sources control for the global
cooperation against weather change and sustainable growth. The study
presents the overview of the water shortage status and the necessity of wastewater reuse facility in military facilities and for the possibility of
the introduction, compares the economics by means of cost-benefit
analysis. The military features such as the number of users of military barracks and the water use were surveyed by the design principles by
facility types, the application method of wastewater reuse facility was selected, the feed water, its application and the volume of reuse volume were defined and the expectation was estimated, confirming
the possibility of introducing a wastewater reuse possibility by means of cost-benefit analysis.
Abstract: This study presents energy saving in general-purpose
pumps widely used in industrial applications. Such pumps are
normally driven by a constant-speed electrical motor which in most
applications must support varying load conditions. This is equivalent
to saying the loading conditions mismatch the designed optimal
energy consumption requirements of the intended application thus
resulting in substantial energy losses. In the held experiments it was
indicated that combination of mechanical and electrical speed drives
can contribute to lower energy consumption in the pump without
negatively distorting the required performance indices of a typical
centrifugal pump at substantially lower energy consumption. The
registered energy savings were recorded to be within the 15-40%
margin. It was also indicated that although VSDs are installed at a
cost, the financial burden is balanced against the earnings resulting
from the associated energy savings.
Abstract: Severe acute respiratory syndrome (SARS) is a respiratory disease in humans which is caused by the SARS coronavirus. The treatment of coronavirus-associated SARS has been evolving and so far there is no consensus on an optimal regimen. The mainstream therapeutic interventions for SARS involve broad-spectrum antibiotics and supportive care, as well as antiviral agents and immunomodulatory therapy. The Protein- Ligand interaction plays a significant role in structural based drug designing. In the present work we have taken the receptor Angiotensin converting enzyme 2 and identified the drugs that are commonly used against SARS. They are Lopinavir, Ritonavir, Ribavirin, and Oseltamivir. The receptor Angiotensin converting enzyme 2 (ACE-2) was docked with above said drugs and the energy value obtained are as follows, Lopinavir (-292.3), Ritonavir (-325.6), Oseltamivir (- 229.1), Ribavirin (-208.8). Depending on the least energy value we have chosen the best two drugs out of the four conventional drugs. We tried to improve the binding efficiency and steric compatibility of the two drugs namely Ritonavir and Lopinavir. Several modifications were made to the probable functional groups (phenylic, ketonic groups in case of Ritonavir and carboxylic groups in case of Lopinavir respectively) which were interacting with the receptor molecule. Analogs were prepared by Marvin Sketch software and were docked using HEX docking software. Lopinavir analog 8 and Ritonavir analog 11 were detected with significant energy values and are probable lead molecule. It infers that some of the modified drugs are better than the original drugs. Further work can be carried out to improve the steric compatibility of the drug based upon the work done above for a more energy efficient binding of the drugs to the receptor.
Abstract: this paper presents an auto-regressive network called the Auto-Regressive Multi-Context Recurrent Neural Network (ARMCRN), which forecasts the daily peak load for two large power plant systems. The auto-regressive network is a combination of both recurrent and non-recurrent networks. Weather component variables are the key elements in forecasting because any change in these variables affects the demand of energy load. So the AR-MCRN is used to learn the relationship between past, previous, and future exogenous and endogenous variables. Experimental results show that using the change in weather components and the change that occurred in past load as inputs to the AR-MCRN, rather than the basic weather parameters and past load itself as inputs to the same network, produce higher accuracy of predicted load. Experimental results also show that using exogenous and endogenous variables as inputs is better than using only the exogenous variables as inputs to the network.
Abstract: Reducing energy consumption of embedded systems requires careful memory management. It has been shown that Scratch- Pad Memories (SPMs) are low size, low cost, efficient (i.e. energy saving) data structures directly managed at the software level. In this paper, the focus is on heuristic methods for SPMs management. A method is efficient if the number of accesses to SPM is as large as possible and if all available space (i.e. bits) is used. A Tabu Search (TS) approach for memory management is proposed which is, to the best of our knowledge, a new original alternative to the best known existing heuristic (BEH). In fact, experimentations performed on benchmarks show that the Tabu Search method is as efficient as BEH (in terms of energy consumption) but BEH requires a sorting which can be computationally expensive for a large amount of data. TS is easy to implement and since no sorting is necessary, unlike BEH, the corresponding sorting time is saved. In addition to that, in a dynamic perspective where the maximum capacity of the SPM is not known in advance, the TS heuristic will perform better than BEH.
Abstract: Structured catalysts formed from the growth of
zeolites on substrates is an area of increasing interest due to the
increased efficiency of the catalytic process, and the ability to
provide superior heat transfer and thermal conductivity for both
exothermic and endothermic processes.
However, the generation of structured catalysts represents a
significant challenge when balancing the relationship variables
between materials properties and catalytic performance, with the
Na2O, H2O and Al2O3 gel composition paying a significant role in
this dynamic, thereby affecting the both the type and range of
application.
The structured catalyst films generated as part of this
investigation have been characterised using a range of techniques,
including X-ray diffraction (XRD), Electron microscopy (SEM),
Energy Dispersive X-ray analysis (EDX) and Thermogravimetric
Analysis (TGA), with the transition from oxide-on-alloy wires to
hydrothermally synthesised uniformly zeolite coated surfaces being
demonstrated using both SEM and XRD. The robustness of the
coatings has been ascertained by subjecting these to thermal cycling
(ambient to 550oC), with the results indicating that the synthesis time
and gel compositions have a crucial effect on the quality of zeolite
growth on the FeCrAlloy wires.
Finally, the activity of the structured catalyst was verified by a
series of comparison experiments with standard zeolite Y catalysts in
powdered pelleted forms.