325 research outputs found
Optimisation of vendor-managed inventory systems
Imperial Users onl
Structure-Based Bayesian Sparse Reconstruction
Sparse signal reconstruction algorithms have attracted research attention due
to their wide applications in various fields. In this paper, we present a
simple Bayesian approach that utilizes the sparsity constraint and a priori
statistical information (Gaussian or otherwise) to obtain near optimal
estimates. In addition, we make use of the rich structure of the sensing matrix
encountered in many signal processing applications to develop a fast sparse
recovery algorithm. The computational complexity of the proposed algorithm is
relatively low compared with the widely used convex relaxation methods as well
as greedy matching pursuit techniques, especially at a low sparsity rate.Comment: 29 pages, 15 figures, accepted in IEEE Transactions on Signal
Processing (July 2012
Effect Of Crumb Rubber Aggregate On Toughness And Impact Energy Of Steel Fiber Concrete
Theoretically, concrete properties such as toughness, ductility, and energy absorption capacity can be improved by adding crumb rubber aggregate from waste tires. Therefore, this intended research work is to support the lack of previous studies by focusing on toughness and impact behavior of concrete containing crumb rubber aggregates with steel fiber. Fine aggregates were partially replaced by crumb rubber at 5%, 10%, 15%, 17.5%, 20%, 22.5%, and 25%. Additionally, 0.5% by volume of hooked end steel fiber was used with an aspect ratio of 80 and 60mm in length. Several specimens including cylinders, beams and slabs were prepared to investigate the toughness and impact behaviour of steel fiber concrete containing crumb rubber. Other properties such as fracture energy, stress intensity, critical strain energy release rate, and J-integral were also investigated. A preliminary impact resistance of beams was obtained using 4.54 kg falling hammer whereas for impact behavior of plain and steel fiber-reinforced rubberized concrete, an instrumented machine of 2.5 kg falling load was used. Simulation was carried out using FEM with LUSAS V14 to predict load deflection behavior of these beams under impact load. A reasonable good agreement was attained between the predicted values and experimental results of impact test. It was noticed that the impact energy of concrete slabs under low-velocity falling iron ball has increased with the increase of crumb rubber in both normal and steel fiber concrete up to 20%. However, a reduction of impact energy was observed when the replacement ratio of fine aggregate by crumb rubber was more than 20%. In conclusion, rubberized concrete containing steel fiber has shown a potential better performance under impact load which could eventually promote healthy environment using recycled waste tires
THE QUANTIFICATION OF THE FLY ASH ADSORPTION CAPACITY FOR THE PURPOSE OF CHARACTERIZATION AND USE IN CONCRETE
Fly ash has been shown to be an effective replacement for portland cement in concrete mixtures. However, many fly ash materials contain unburned carbon from the combustion process. Unburned carbon in fly ash adsorbs air entraining admixtures (AEAs) reducing their effectiveness in providing a specified air void system in concrete materials. Measurement tools and methods for characterization of the adsorption properties of fly ash materials are necessary for beneficial use of fly ash materials in concrete. In this research, two methods were developed to measure and quantify the adsorption capacity AEAs on fly ash materials. The first method is the fly ash iodine number, a simple laboratory procedure that measures the adsorption capacity of fly ash based on iodine adsorption. The second is the application of direct adsorption isotherms. This test can be used to quantify the amount of AEA adsorbed by fly ash in concrete.
When the iodine number test is combined with the direct adsorption isotherms, the AEAs dosage predictions can be made by simply measuring the fly ash iodine number of the fly ash, then use the fly ash iodine number-direct adsorption correlation to predict the amount of AEA adsorbed, which represent the required dosage adjustment.
These two tests provide a robust, simple, and practical methodology for engineers to use in the specification of AEA quantities required for concrete mixes when Portland cement is replaced by fly ash
Implementation And Optimization Of A Secure, Scalable, And Robust Long-Range Low-Power Mesh Network For Enhanced Geo-Location Accuracy And Efficient Data Aggregation
The burgeoning realm of the Internet of Things (IoT) calls for advanced communication networks that can support an ever-increasing number of connected devices. Among these, Low Power Wide Area Networks (LPWANs), specifically LoRaWAN technology, have emerged as frontrunners due to their long-range, low-power capabilities, ideally suiting IoT\u27s expansive nature. This dissertation presents a comprehensive study on enhancing LoRaWAN technology to overcome the existing limitations in geolocation accuracy and data aggregation efficiency. The work is set against the backdrop of the technology\u27s vulnerability to signal attenuation in obstacle-rich environments and its challenges in scaling to accommodate dense networks without performance degradation. Moreover, the security of data transmission within such networks is scrutinized, with a specific focus on enhancing encryption protocols and visualization tools for more effective network management. The dissertation\u27s contributions are manifold, including the development of a private server framework utilizing Advanced Encryption Standard (AES) to fortify data transmission security. Furthermore, the integration of Grafana mapping solutions with LoRaWAN servers is explored to enable sophisticated data visualization and analytics. An adaptive algorithm is proposed to dynamically adjust the spreading factor based on signal strength indicators, improving network coverage and throughput. A rebroadcast location-unaware protocol specifically optimized for mesh network conditions in IoT domains is also introduced alongside a scalable geofencing system for remote monitoring. Central to this study is the innovative approach to geolocation, which eschews traditional GPS reliance. By harnessing parameters like Received Signal Strength Indicator (RSSI), Signal-to-Noise Ratio (SNR), and Time Difference of Arrival (TDOA), combined with machine learning and location triangulation methods, the research aims to conserve power while ensuring precise location tracking. This dissertation is organized into eight chapters, methodically detailing the problem statement, literature review, methodology, implementation, results, and conclusions. It culminates in suggesting future research directions that continue to push the boundaries of LoRaWAN technology, paving the way for its broader application in diverse IoT domains.
Index Terms- Geolocation Accuracy, IoT, LoRaWAN
Gesture Recognition System Application to early childhood education
One of the most socially and culturally advantageous uses of human-computer interaction is enhancing playing and learning for children. In this study, gesture interactive game-based learning (GIGL) is tested to see if these kinds of applications are suitable to stimulate working memory (WM) and basic mathematical skills (BMS) in early childhood (5-6 years old) using a hand gesture recognition system. Hand gesture is being performed by the user and to control a computer system by that incoming information. We can conclude that the children who used GIGL technology showed a significant increase in their learning performance in WM and BMS, surpassing those who did normal school activities
Study of Y-Chromosome STR Markers in United Arab Emirates Population
The recently introduced 6-dye Yfiler Plus multiplex which includes 27 Y-STR loci (DYS576, DYS389I, DYS635, DYS389II, DYS627, DYS460, DYS458, DYS19, YGATAH4, DYS448, DYS391, DYS456, DYS390, DYS438, DYS392, DYS518, DYS570, DYS437, DYS385 a/b, DYS449, DYS393, DYS439, DYS481, DYF387S1a/b and DYS533) has been used to study 343 UAE Arab male individuals using Yfiler Plus® amplification kit. This set includes seven rapidly mutating loci (RM Y-STRs). These RM Y-STRs are useful for discriminating between closely related and unrelated males.. According to measures of genetic diversity the highest diversity were observed at loci DYS385=(0.94984), DYF387S1=(0.930523) and DYS449=(0.895402). Therefore, these loci should be considered the most diverse and polymorphic for forensic testing which can be used to distinguish between male relatives. 313 haplotypes were observed in UAE Arab male population and 15 haplotypes were shared between two individuals. Discrimination capacity for 27 loci among the UAE Arab male population was determined to be 95.43% whereas haplotype diversity was found to be 0.99973. AMOVA results showed that UAE Arab male population was placed at far genetic distance from European populations such as Denmark, Italy, Spain and United States. While it shows closer genetic distance to the regional populations from Iran, Iraq, Egypt, Yemen and Kuwait
Hybrid Scheduling/Signal-Level Coordination in the Downlink of Multi-Cloud Radio-Access Networks
In the context of resource allocation in cloud-radio access networks, recent
studies assume either signal-level or scheduling-level coordination. This
paper, instead, considers a hybrid level of coordination for the scheduling
problem in the downlink of a multi-cloud radio-access network, as a means to
benefit from both scheduling policies. Consider a multi-cloud radio access
network, where each cloud is connected to several base-stations (BSs) via high
capacity links, and therefore allows joint signal processing between them.
Across the multiple clouds, however, only scheduling-level coordination is
permitted, as it requires a lower level of backhaul communication. The frame
structure of every BS is composed of various time/frequency blocks, called
power-zones (PZs), and kept at fixed power level. The paper addresses the
problem of maximizing a network-wide utility by associating users to clouds and
scheduling them to the PZs, under the practical constraints that each user is
scheduled, at most, to a single cloud, but possibly to many BSs within the
cloud, and can be served by one or more distinct PZs within the BSs' frame. The
paper solves the problem using graph theory techniques by constructing the
conflict graph. The scheduling problem is, then, shown to be equivalent to a
maximum-weight independent set problem in the constructed graph, in which each
vertex symbolizes an association of cloud, user, BS and PZ, with a weight
representing the utility of that association. Simulation results suggest that
the proposed hybrid scheduling strategy provides appreciable gain as compared
to the scheduling-level coordinated networks, with a negligible degradation to
signal-level coordination
Hybrid Radio/Free-Space Optical Design for Next Generation Backhaul Systems
The deluge of date rate in today's networks imposes a cost burden on the
backhaul network design. Developing cost efficient backhaul solutions becomes
an exciting, yet challenging, problem. Traditional technologies for backhaul
networks include either radio-frequency backhauls (RF) or optical fibers (OF).
While RF is a cost-effective solution as compared to OF, it supports lower data
rate requirements. Another promising backhaul solution is the free-space optics
(FSO) as it offers both a high data rate and a relatively low cost. FSO,
however, is sensitive to nature conditions, e.g., rain, fog, line-of-sight.
This paper combines both RF and FSO advantages and proposes a hybrid RF/FSO
backhaul solution. It considers the problem of minimizing the cost of the
backhaul network by choosing either OF or hybrid RF/FSO backhaul links between
the base-stations (BS) so as to satisfy data rate, connectivity, and
reliability constraints. It shows that under a specified realistic assumption
about the cost of OF and hybrid RF/FSO links, the problem is equivalent to a
maximum weight clique problem, which can be solved with moderate complexity.
Simulation results show that the proposed solution shows a close-to-optimal
performance, especially for practical prices of the hybrid RF/FSO links
On Minimizing the Maximum Broadcast Decoding Delay for Instantly Decodable Network Coding
In this paper, we consider the problem of minimizing the maximum broadcast
decoding delay experienced by all the receivers of generalized instantly
decodable network coding (IDNC). Unlike the sum decoding delay, the maximum
decoding delay as a definition of delay for IDNC allows a more equitable
distribution of the delays between the different receivers and thus a better
Quality of Service (QoS). In order to solve this problem, we first derive the
expressions for the probability distributions of maximum decoding delay
increments. Given these expressions, we formulate the problem as a maximum
weight clique problem in the IDNC graph. Although this problem is known to be
NP-hard, we design a greedy algorithm to perform effective packet selection.
Through extensive simulations, we compare the sum decoding delay and the max
decoding delay experienced when applying the policies to minimize the sum
decoding delay [1] and our policy to reduce the max decoding delay. Simulations
results show that our policy gives a good agreement among all the delay aspects
in all situations and outperforms the sum decoding delay policy to effectively
minimize the sum decoding delay when the channel conditions become harsher.
They also show that our definition of delay significantly improve the number of
served receivers when they are subject to strict delay constraints
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