scholarly journals Cognitive Code-Division Channelization with Admission Control

2012 ◽  
Vol 2012 ◽  
pp. 1-9 ◽  
Author(s):  
Kanke Gao ◽  
Onur Ozdemir ◽  
Dimitris A. Pados ◽  
Stella N. Batalama ◽  
Tommaso Melodia ◽  
...  
Keyword(s):  
Admission Control ◽  
High Energy ◽  
Primary System ◽  
Computationally Efficient ◽  
Total Energy Consumption ◽  
Efficient Manner ◽  
Interference Temperature ◽  
Secondary Network ◽  
Joint Resource Allocation ◽  
Primary Interference

We consider the problem of joint resource allocation and admission control in a secondary code-division network coexisting with a narrowband primary system. Our objective is to find the maximum number of admitted secondary links and then find the optimal transmitting powers and code sequences of those secondary links such that the total energy consumption of the secondary network is minimized subject to the conditions that primary interference temperature constraints, secondary signal-to-interference-plus-noise ratio (SINR) constraints and secondary peak power constraints are all satisfied. This is an NP-hard optimization problem which motivates the development of suboptimal algorithms. We propose a novel iterative algorithm to solve this problem in a computationally efficient manner. Numerical results demonstrate that the proposed algorithm provides excellent solutions that result in high energy efficiency and large admitted percentage of secondary links.

scholarly journals Energy Consumption Analysis and Characterization of Healthcare Facilities in the United States

Energies ◽  
2019 ◽  
Vol 12 (19) ◽  
pp. 3775 ◽  
Author(s):  
Khaled Bawaneh ◽  
Farnaz Ghazi Nezami ◽  
Md. Rasheduzzaman ◽  
Brad Deken
Keyword(s):  
United States ◽  
Energy Consumption ◽  
Energy Intensity ◽  
The United States ◽  
High Energy ◽  
Total Energy Consumption ◽  
Healthcare Facilities ◽  
Energy Consumption Analysis ◽  
Consumption Data ◽  
End Use

Healthcare facilities in the United States account for 4.8% of the total area in the commercial sector and are responsible for 10.3% of total energy consumption in this sector. The number of healthcare facilities increased by 22% since 2003, leading to a 21% rise in energy consumption and an 8% reduction in energy intensity per unit of area (544.8 kWh/m2). This study provides an analytical overview of the end-use energy consumption data in healthcare systems for hospitals in the United States. The energy intensity of the U.S. hospitals ranges from 640.7 kWh/m2 in Zone 5 (very hot) to 781.1 kWh/m2 in Zone 1 (very cold), with an average of 738.5 kWh/m2. This is approximately 2.6 times higher than that of other commercial buildings. High energy intensity in the healthcare facilities, particularly in hospitals, along with energy costs and associated environmental concerns make energy analysis crucial for this type of facility. The proposed analysis shows that U.S. healthcare facilities have higher energy intensity than those of most other countries, especially the European ones. This necessitates the adoption of more energy-efficient approaches to the infrastructure and the management of healthcare facilities in the United States.

scholarly journals Computationally Efficient Magnetic Resonance Imaging Based Surface Contact Modeling as a Tool to Evaluate Joint Injuries and Outcomes of Surgical Interventions Compared to Finite Element Modeling

2014 ◽  
Vol 136 (4) ◽  
Author(s):  
Joshua E. Johnson ◽  
Phil Lee ◽  
Terence E. McIff ◽  
E. Bruce Toby ◽  
Kenneth J. Fischer
Keyword(s):  
Finite Element ◽  
Finite Element Modeling ◽  
Joint Mechanics ◽  
Computationally Efficient ◽  
Efficient Manner ◽  
Element Modeling ◽  
Joint Injuries ◽  
Surface Contact ◽  
Joint Contact ◽  
Contact Pressures

Joint injuries and the resulting posttraumatic osteoarthritis (OA) are a significant problem. There is still a need for tools to evaluate joint injuries, their effect on joint mechanics, and the relationship between altered mechanics and OA. Better understanding of injuries and their relationship to OA may aid in the development or refinement of treatment methods. This may be partially achieved by monitoring changes in joint mechanics that are a direct consequence of injury. Techniques such as image-based finite element modeling can provide in vivo joint mechanics data but can also be laborious and computationally expensive. Alternate modeling techniques that can provide similar results in a computationally efficient manner are an attractive prospect. It is likely possible to estimate risk of OA due to injury from surface contact mechanics data alone. The objective of this study was to compare joint contact mechanics from image-based surface contact modeling (SCM) and finite element modeling (FEM) in normal, injured (scapholunate ligament tear), and surgically repaired radiocarpal joints. Since FEM is accepted as the gold standard to evaluate joint contact stresses, our assumption was that results obtained using this method would accurately represent the true value. Magnetic resonance images (MRI) of the normal, injured, and postoperative wrists of three subjects were acquired when relaxed and during functional grasp. Surface and volumetric models of the radiolunate and radioscaphoid articulations were constructed from the relaxed images for SCM and FEM analyses, respectively. Kinematic boundary conditions were acquired from image registration between the relaxed and grasp images. For the SCM technique, a linear contact relationship was used to estimate contact outcomes based on interactions of the rigid articular surfaces in contact. For FEM, a pressure-overclosure relationship was used to estimate outcomes based on deformable body contact interactions. The SCM technique was able to evaluate variations in contact outcomes arising from scapholunate ligament injury and also the effects of surgical repair, with similar accuracy to the FEM gold standard. At least 80% of contact forces, peak contact pressures, mean contact pressures and contact areas from SCM were within 10 N, 0.5 MPa, 0.2 MPa, and 15 mm2, respectively, of the results from FEM, regardless of the state of the wrist. Depending on the application, the MRI-based SCM technique has the potential to provide clinically relevant subject-specific results in a computationally efficient manner compared to FEM.

An Energy-Efficient DRAM Cache Architecture for Mobile Platforms With PCM-Based Main Memory

2022 ◽  
Vol 21 (1) ◽  
pp. 1-22
Author(s):  
Dongsuk Shin ◽  
Hakbeom Jang ◽  
Kiseok Oh ◽  
Jae W. Lee
Keyword(s):  
Energy Consumption ◽  
Main Memory ◽  
Battery Life ◽  
Mobile Platforms ◽  
Total Energy Consumption ◽  
Efficient Manner ◽  
Hybrid Memory ◽  
Spatial Locality ◽  
Cache Architecture ◽  
Energy Delay Product

A long battery life is a first-class design objective for mobile devices, and main memory accounts for a major portion of total energy consumption. Moreover, the energy consumption from memory is expected to increase further with ever-growing demands for bandwidth and capacity. A hybrid memory system with both DRAM and PCM can be an attractive solution to provide additional capacity and reduce standby energy. Although providing much greater density than DRAM, PCM has longer access latency and limited write endurance to make it challenging to architect it for main memory. To address this challenge, this article introduces CAMP, a novel DRAM c ache a rchitecture for m obile platforms with P CM-based main memory. A DRAM cache in this environment is required to filter most of the writes to PCM to increase its lifetime, and deliver highest efficiency even for a relatively small-sized DRAM cache that mobile platforms can afford. To address this CAMP divides DRAM space into two regions: a page cache for exploiting spatial locality in a bandwidth-efficient manner and a dirty block buffer for maximally filtering writes. CAMP improves the performance and energy-delay-product by 29.2% and 45.2%, respectively, over the baseline PCM-oblivious DRAM cache, while increasing PCM lifetime by 2.7×. And CAMP also improves the performance and energy-delay-product by 29.3% and 41.5%, respectively, over the state-of-the-art design with dirty block buffer, while increasing PCM lifetime by 2.5×.

Vibration Suppression of an Elastically Supported Beam With Closely Spaced Natural Frequencies

2020 ◽  
Author(s):  
Haizhou Liu ◽  
Hao Gao
Keyword(s):  
Natural Frequencies ◽  
Vibration Suppression ◽  
Fixed Point Theory ◽  
Dynamic Performance ◽  
Point Theory ◽  
Primary System ◽  
Computationally Efficient ◽  
Wide Range ◽  
Univariate Optimization ◽  
Elastically Supported

Abstract Vibration suppression of distributed parameter systems is of great interest and has a wide range of applications. The dynamic performance of a primary system can be improved by adding dynamic vibration absorbers (DVA). Although the relevant topics have been studied for decades, the trade-off between capability of suppressing multiple resonant peaks and complexity of absorbers has not been well addressed. In this paper, the vibration suppression problem of a uniform Euler-Bernoulli beam with closely spaced natural frequencies is investigated. To achieve desired vibration reduction, a two-DOF DVA is connected to the beam through a pair of a spring and a dashpot. By introducing a virtual ground spring, the parameters of the absorber are determined via extended fixed point theory. The proposed method only requires univariate optimization and is computationally efficient. Numerical examples conducted verify the viability of the proposed method and the effectiveness of a two-DOF DVA in suppressing double resonances.

scholarly journals Mathematical Model of Pressure Formation Process along the Helix Channel Length of Screw Grinder

2020 ◽  
Author(s):  
Valery Pelenko ◽  
Ilkhom Usmanov ◽  
Vyacheslav Pokholchenko ◽  
Irina Smirnova
Keyword(s):  
Energy Consumption ◽  
Mathematical Description ◽  
Analytical Description ◽  
High Energy ◽  
Channel Length ◽  
Operating Conditions ◽  
Technical Equipment ◽  
Mining Equipment ◽  
Technological Parameters ◽  
Total Energy Consumption

The improvement of the technical equipment effectiveness is currently becoming particularly important. This applies not only to large and high-energy-intensive machines, but also to household appliances, the total energy consumption of which often exceeds the energy consumption of the overall equipment. These types of devices include, in particular, grinding and cutting equipment. The mathematical description of the processes carried out on this equipment is generalized and can be extended to a wider class of machines, including waste processing and mining equipment. The technological parameters, the design of screw grinders, and the processes of movement, deformation, extrusion and cutting carried out in them are characterized by a significant number of factors affecting the energy intensity. The main ones are the geometric parameters of the screw, machine’s body, cross knife, grinding plate’s thickness, the number and diameter of holes in it, as well as the product’s physical-mechanical characteristics and operating conditions. The most important for the mathematical description are the zones and processes where the main share of the consumed power is spent. The complexity of their analytical description is due to a simplified consideration of either individual technological zones of grinders’ existing designs, or the use of unreasonable simplifications.

DEVELOPMENT AND ANALYSIS OF AN INTEGRATED MILD/PARTIAL GASIFICATION COMBINED (IMPGC) CYCLE

2021 ◽  
pp. 1-34
Author(s):  
Ting Wang ◽  
Henry Long
Keyword(s):  
Power Plants ◽  
Energy Content ◽  
Energy Resource ◽  
Rankine Cycle ◽  
High Energy ◽  
Combined Cycle ◽  
Cycle Performance ◽  
Efficient Manner ◽  
Volumetric Heating ◽  
Partial Gasification

Abstract Around 50% of the world's electrical power supply comes from the Rankine cycle, and the majority of existing Rankine cycle plants are driven by coal. Given how unattractive coal is as an energy resource in spite of its high energy content, it becomes necessary to find a way to utilize coal in a cleaner and more efficient manner. Designed as a potential retrofit option for existing Rankine cycle plants, the Integrated Mild/Partial Gasification Combined (IMPGC) Cycle is an attractive concept in cycle design that can greatly increase the efficiency of coal-based power plants, particularly for retrofitting an old Rankine cycle plant. Compared to the Integrated Gasification Combined Cycle (IGCC), IMPGC uses mild gasification to purposefully leave most of the volatile matters within the feedstock intact (hence, yielding more chemical energy) compared to full gasification and uses partial gasification to leave some of the remaining char un-gasified compared to complete gasification. The larger hydrocarbons left over from the mild gasification process grant the resulting syngas a higher volumetric heating value, leading to a more efficient overall cycle performance. This is made possible due to the invention of a warm gas cleanup process invented by Research Triangle Institute (RTI), called the High Temperature Desulfurization Process (HTDP), which was recently commercialized. The leftover char can then be burned in a conventional boiler to boost the steam output of the bottom cycle, further increasing the efficiency of the plant, capable of achieving a thermal efficiency of 47.9% (LHV). This paper will first analyze the individual concepts used to create the baseline IMPGC model, including the mild and partial gasification processes themselves, the warm gas cleanup system, and the integration of the boiler with the heat recovery steam generator (HRSG). This baseline will then be compared with four other common types of power plants, including subcritical and ultra-supercritical (USC) Rankine cycles, IGCC, and natural gas. The results show that IMPGC consistently outperforms all other forms of coal-based power. IMPGC is more efficient than the standard subcritical Rankine cycle by nine percentage points, more than a USC Rankine cycle by nearly four points, and more than IGCC by seven points.

scholarly journals On the Performance of Random Cognitive mmWave Sensor Networks

Sensors ◽  
2019 ◽  
Vol 19 (14) ◽  
pp. 3184 ◽  
Author(s):  
Yi Song ◽  
Weiwei Yang ◽  
Zhongwu Xiang ◽  
Biao Wang ◽  
Yueming Cai
Keyword(s):  
Sensor Node ◽  
Signal Beam ◽  
Closed Form Expression ◽  
Primary Sensor ◽  
Interference Temperature ◽  
Secondary Network ◽  
Propagation Law ◽  
Temperature Constraint ◽  
Power Region ◽  
Guard Zone

This paper investigates the secrecy performance of a cognitive millimeter wave (mmWave) wiretap sensor network, where the secondary transmitter (SU-Tx) intends to communicate with a secondary sensor node under the interference temperature constraint of the primary sensor node. We consider that the random-location eavesdroppers may reside in the signal beam of the secondary network, so that confidential information can still be intercepted. Also, the interference to the primary network is one of the critical issues when the signal beam of the secondary network is aligned with the primary sensor node. Key features of mmWave networks, such as large number of antennas, variable propagation law and sensitivity to blockages, are taken into consideration. Moreover, an eavesdropper-exclusion sector guard zone around SU-Tx is introduced to improve the secrecy performance of the secondary network. By using stochastic geometry, closed-form expression for secrecy throughput (ST) achieved by the secondary sensor node is obtained to investigate secrecy performance. We also carry out the asymptotic analysis to facilitate the performance evaluation in the high transmit power region. Numerical results demonstrate that the interference temperature constraint of the primary sensor node enables us to balance secrecy performance of the secondary network, and provides interesting insights into how the system performance of the secondary network that is influenced by various system parameters: eavesdropper density, antenna gain and sector guard zone radius. Furthermore, blockages are beneficial to improve ST of the secondary sensor node under certain conditions.

scholarly journals Towards Gas Discrimination and Mapping in Emergency Response Scenarios Using a Mobile Robot with an Electronic Nose

Sensors ◽  
2019 ◽  
Vol 19 (3) ◽  
pp. 685 ◽  
Author(s):  
Han Fan ◽  
Victor Hernandez Bennetts ◽  
Erik Schaffernicht ◽  
Achim Lilienthal
Keyword(s):  
Emergency Response ◽  
Electronic Nose ◽  
Gas Sensing ◽  
Practical Significance ◽  
Computationally Efficient ◽  
Urban Search And Rescue ◽  
Efficient Manner ◽  
Distribution Maps ◽  
Gas Identification ◽  
Sampling Procedures

Emergency personnel, such as firefighters, bomb technicians, and urban search and rescue specialists, can be exposed to a variety of extreme hazards during the response to natural and human-made disasters. In many of these scenarios, a risk factor is the presence of hazardous airborne chemicals. The recent and rapid advances in robotics and sensor technologies allow emergency responders to deal with such hazards from relatively safe distances. Mobile robots with gas-sensing capabilities allow to convey useful information such as the possible source positions of different chemicals in the emergency area. However, common gas sampling procedures for laboratory use are not applicable due to the complexity of the environment and the need for fast deployment and analysis. In addition, conventional gas identification approaches, based on supervised learning, cannot handle situations when the number and identities of the present chemicals are unknown. For the purpose of emergency response, all the information concluded from the gas detection events during the robot exploration should be delivered in real time. To address these challenges, we developed an online gas-sensing system using an electronic nose. Our system can automatically perform unsupervised learning and update the discrimination model as the robot is exploring a given environment. The online gas discrimination results are further integrated with geometrical information to derive a multi-compound gas spatial distribution map. The proposed system is deployed on a robot built to operate in harsh environments for supporting fire brigades, and is validated in several different real-world experiments of discriminating and mapping multiple chemical compounds in an indoor open environment. Our results show that the proposed system achieves high accuracy in gas discrimination in an online, unsupervised, and computationally efficient manner. The subsequently created gas distribution maps accurately indicate the presence of different chemicals in the environment, which is of practical significance for emergency response.

scholarly journals Integrative Bayesian Network Analysis of Genomic Data

2014 ◽  
Vol 13s2 ◽  
pp. CIN.S13786 ◽  
Author(s):  
Yang Ni ◽  
Francesco C. Stingo ◽  
Veerabhadran Baladandayuthapani
Keyword(s):  
Bayesian Network ◽  
Cancer Progression ◽  
Rapid Development ◽  
Genomic Data ◽  
Biological Knowledge ◽  
Network Approach ◽  
Computationally Efficient ◽  
Efficient Manner ◽  
New Genes ◽  
Genome Wide

Rapid development of genome-wide profiling technologies has made it possible to conduct integrative analysis on genomic data from multiple platforms. In this study, we develop a novel integrative Bayesian network approach to investigate the relationships between genetic and epigenetic alterations as well as how these mutations affect a patient's clinical outcome. We take a Bayesian network approach that admits a convenient decomposition of the joint distribution into local distributions. Exploiting the prior biological knowledge about regulatory mechanisms, we model each local distribution as linear regressions. This allows us to analyze multi-platform genome-wide data in a computationally efficient manner. We illustrate the performance of our approach through simulation studies. Our methods are motivated by and applied to a multi-platform glioblastoma dataset, from which we reveal several biologically relevant relationships that have been validated in the literature as well as new genes that could potentially be novel biomarkers for cancer progression.

Framework for virtual hybrid simulation of TADAS frames using opensees and abaqus

2016 ◽  
Vol 24 (11) ◽  
pp. 2165-2179 ◽  
Author(s):  
Azin Ghaffary ◽  
Reza Karami Mohammadi
Keyword(s):  
Hybrid Simulation ◽  
Sufficient Accuracy ◽  
Hysteretic Behavior ◽  
Software Framework ◽  
Fe Model ◽  
Computationally Efficient ◽  
Element Analysis ◽  
Efficient Manner ◽  
Coupled Codes ◽  
Comparison Of The Results

Virtual hybrid simulation is a computationally-efficient method that enables coupling of two or more finite element analysis programs. In this study, benefits of this technique in predicting both cyclic and seismic response of a one-story one-bay frame equipped with a Triangular-plate Added Damping and Stiffness (TADAS) damper are evaluated. For this purpose, a detailed FE model of the damper is built in Abaqus to take into account precise modelling of its hysteretic behavior as well as a number of important features related to the geometric characteristics of the including parts of the device, while the remainder of the structure is modelled in OpenSees. Continuous exchange of the data between the coupled codes is conducted through the software framework, OpenFresco. Comparison of the results with experimental outcomes is presented, which proves the ability of the introduced technique in modelling the behavior of such structures in an efficient manner while preserving sufficient accuracy. At the end, a series of dynamic virtual hybrid simulations of the frame are performed which provide useful insights into design of TADAS frames.

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