Low Complexity V-BLAST MIMO-OFDM Detector by Successive Iterations Reduction

V-BLAST detection method suffers large computational complexity due to its successive detection of symbols. In this paper, we propose a modified V-BLAST algorithm to decrease the computational complexity by reducing the number of detection iterations required in MIMO communication systems. We begin by showing the existence of a maximum number of iterations, beyond which, no significant improvement is obtained. We establish a criterion for the number of maximum effective iterations. We propose a modified algorithm that uses the measured SNR to dynamically set the number of iterations to achieve an acceptable bit-error rate. Then, we replace the feedback algorithm with an approximate linear function to reduce the complexity. Simulations show that significant reduction in computational complexity is achieved compared to the ordinary V-BLAST, while maintaining a good BER performance.Comment: 6 pages, 7 figures, 2 tables. The final publication is available at www.aece.r

Bayesian image restoration and bacteria detection in optical endomicroscopy

Optical microscopy systems can be used to obtain high-resolution microscopic images of tissue cultures and ex vivo tissue samples. This imaging technique can be translated for in vivo, in situ applications by using optical fibres and miniature optics. Fibred optical endomicroscopy (OEM) can enable optical biopsy in organs inaccessible by any other imaging systems, and hence can provide rapid and accurate diagnosis in a short time. The raw data the system produce is difficult to interpret as it is modulated by a fibre bundle pattern, producing what is called the “honeycomb effect”. Moreover, the data is further degraded due to the fibre core cross coupling problem. On the other hand, there is an unmet clinical need for automatic tools that can help the clinicians to detect fluorescently labelled bacteria in distal lung images. The aim of this thesis is to develop advanced image processing algorithms that can address the above mentioned problems. First, we provide a statistical model for the fibre core cross coupling problem and the sparse sampling by imaging fibre bundles (honeycomb artefact), which are formulated here as a restoration problem for the first time in the literature. We then introduce a non-linear interpolation method, based on Gaussian processes regression, in order to recover an interpretable scene from the deconvolved data. Second, we develop two bacteria detection algorithms, each of which provides different characteristics. The first approach considers joint formulation to the sparse coding and anomaly detection problems. The anomalies here are considered as candidate bacteria, which are annotated with the help of a trained clinician. Although this approach provides good detection performance and outperforms existing methods in the literature, the user has to carefully tune some crucial model parameters. Hence, we propose a more adaptive approach, for which a Bayesian framework is adopted. This approach not only outperforms the proposed supervised approach and existing methods in the literature but also provides computation time that competes with optimization-based methods

Collaborative delivery strategies for goods delivery

Transportation sector has the highest growth rate of greenhouse gas emissions compared to other sectors. The fact that the current practice of freight transportation strategies is not sustainable in the long run, motivates the urgent need of sustainable transportation strategies with less negative effects on the environment and the society. As one of the possible sustainable solutions, collaborative planning of freight delivery has attracted the interest of professional and scientific communities. This work illustrates some strategies of the collaborative freight transportation.&nbsp

Development of an efficient Ad Hoc broadcasting scheme for critical networking environments

Mobile ad hoc network has been widely deployed in support of the communications in hostile environment without conventional networking infrastructure, especially in the environments with critical conditions such as emergency rescue activities in burning building or earth quick evacuation. However, most of the existing ad hoc based broadcasting schemes either rely on GPS location or topology information or angle-of-arrival (AoA) calculation or combination of some or all to achieve high reachability. Therefore, these broadcasting schemes cannot be directly used in critical environments such as battlefield, sensor networks and natural disasters due to lack of node location and topology information in such critical environments. This research work first begins by analyzing the broadcast coverage problem and node displacement form ideal locations problem in ad hoc networks using theoretical analysis. Then, this research work proposes an efficient broadcast relaying scheme, called Random Directional Broadcasting Relay (RDBR), which greatly reduces the number of retransmitting nodes and end-to-end delay while achieving high reachability. This is done by selecting a subset of neighboring nodes to relay the packet using directional antennas without relying on node location, network topology and complex angle-of-arrival (AoA) calculations. To further improve the performance of the RDBR scheme in complex environments with high node density, high node mobility and high traffic rate, an improved RDBR scheme is proposed. The improved RDBR scheme utilizes the concept of gaps between neighboring sectors to minimize the overlap between selected relaying nodes in high density environments. The concept of gaps greatly reduces both contention and collision and at the same time achieves high reachability. The performance of the proposed RDBR schemes has been evaluated by comparing them against flooding and Distance-based schemes. Simulation results show that both proposed RDBR schemes achieve high reachability while reducing the number of retransmitting nodes and end-to-end delay especially in high density environments. Furthermore, the improved RDBR scheme achieves better performance than RDBR in high density and high traffic environment in terms of reachability, end-to-end delay and the number of retransmitting nodes

Bayesian Analyses of the Burr Type ? Distribution under Doubly Type ?? censored samples using different Priors and Loss functions

The Bayesian analysis of the Burr type  distribution (Exponentiated Rayleigh) has been considered in the paper.  The Gamma, Exponential, Chi-Squared and Jeffrey prior have been assumed for posterior analysis. The estimation has been made under doubly type  censored samples. The Bayes estimation has been obtained under eight different loss functions (Squared error, Quadratic, Weighted, Linear exponential, Precautionary, Entropy, De Groot and non-Linear exponential loss functions). The simulation study has been conducted to compare by mean square error (MSE) for the performance of various estimators. Keyword: Bayesian Analyses, Exponentiated Rayleigh Distribution, Burr type  distribution, Loss function, Prior, Posterior, (Squared error, Quadratic, Weighted, Linear exponential, Precautionary, Entropy, De Groot and non-Linear exponential) loss functions

A general framework for hepatic iron overload quantification using MRI

Magnetic resonance imaging (MRI) has been considered for the quantification of iron overload in the liver. Iron overload was found to correlate with T2* measurement using T2* weighted images. In this work, we address the problem of iron overload estimation in the liver using MRI. We propose a general framework for all liver models proposed in the literature. The iron overload estimation task is then formulated as a minimization problem, and suitable regularization functions are assigned to the unknown model parameters. Subsequently, an alternating direction method of multipliers (ADMM) is used to estimate these unknown parameters. Three different models are derived, tested and compared; namely the single exponential (SEXP), the bi-exponential (BiEXP), and the exponential plus constant (CEXP). Simulations conducted using synthetic datasets indicate good correlation between estimated and ground truth T2* for all models. Moreover, the algorithms are evaluated using MRI scans of nine patients of different iron concentrations, using a 3-Tesla MRI scanner. The estimated T2* values of the proposed approaches are found to correlate with those obtained by the MRI scanner console. Moreover, the proposed approaches outperform several existing methods in the literature for iron overload estimation

Synthesis and evaluation of some new 1,3,4-oxadiazoles bearing thiophene, thiazole, coumarin, pyridine and pyridazine derivatives as antiviral agents

In an attempt to produce heterocyclic compounds based on 1,3,4-oxadiazole derivatives with potential antiviral activity, the synthesis of compound 1 [2-(5-thioxo-4,5-dihydro-1,3,4-oxadiazol-2-yl)acetonitrile] was performed through the reaction of cyanoacetic acid hydrazide with carbon disulfide in alcoholic potassium hydroxide. Compound 1 has an activating methylene group, so it was directed toward some specific reactions. Thus, aryldiazonium chlorides reacted with compound 1 affording hydrazono derivatives 2a,b,c. Also, aromatic aldehydes reacted with compound 1 to produce compounds 3a,b. Furthermore, cyclic ketones were subjected to synthesis of fused thiophene derivatives 4a,b via the reaction with compound 1 in the presence of elemental sulfur. In addition, 1,3,4-oxadiazole derivative 1 when reacted with isothiocyanates, salicylaldehyde or 1,3-dicarbonyl compounds formed thiazole derivatives 5a,b, coumarin derivative 6 and alkenyl derivatives 7a,b resp. Compound 7b underwent cyclization to afford pyridine derivative 8. Arylhydrazono derivatives 9a,b were produced through the reaction of compound 7a with aryldiazonium chlorides. The latter products 9a,b underwent cyclization to produce pyridazine derivatives 10a,b. Finally 1,3,4-oxadiazole derivative 1 was directed toward the reaction with hydrazine derivatives, bromoacetophenone and ethylchloroacetate affording compounds 11a,b, 12 and 13, resp. The fused thiophene derivatives 14a,b were produced via the reaction of compounds 4a,b with a mixture of malononitrile and ethylorthoformate. Antiviral activity of the synthesized products showed that 5-(4-amino-3-ethyl-2-thioxo-2,3-dihydrothiazol-5-yl)-1,3,4-oxadiazole-2(3H)-thione (5a) and 5-(4-amino-3-phenyl-2-thioxo-2,3-dihydrothiazol-5-yl)-1,3,4-oxadiazole-2(3H)-thione (5b) act as the most active agents against Feline herpes virus, Feline corona virus, Herpes simplex virus-1 and Herpes simplex virus-2, whereas compound 2-(5-(2-phenyl- hydrazono)-4,5-dihydro-1,3,4-oxadiazol-2-yl)acetonitrile (11b) was the most effective against Vaccinia virus, Herpes simplex virus (TK-KOS-ACVr ), Coxsackie virus B4 and Vesicular stomatitis virus

A 3D Conditional Diffusion Model for Image Quality Transfer -- An Application to Low-Field MRI

Low-field (LF) MRI scanners (<1T) are still prevalent in settings with limited resources or unreliable power supply. However, they often yield images with lower spatial resolution and contrast than high-field (HF) scanners. This quality disparity can result in inaccurate clinician interpretations. Image Quality Transfer (IQT) has been developed to enhance the quality of images by learning a mapping function between low and high-quality images. Existing IQT models often fail to restore high-frequency features, leading to blurry output. In this paper, we propose a 3D conditional diffusion model to improve 3D volumetric data, specifically LF MR images. Additionally, we incorporate a cross-batch mechanism into the self-attention and padding of our network, ensuring broader contextual awareness even under small 3D patches. Experiments on the publicly available Human Connectome Project (HCP) dataset for IQT and brain parcellation demonstrate that our model outperforms existing methods both quantitatively and qualitatively. The code is publicly available at \url{this https URL}

A MILP model for an integrated project scheduling and multi-skilled workforce allocation with flexible working hours

In this paper, we integrate two decision problems arising in various applications such as production planning and project management: the project scheduling problem, which consists in scheduling a set of precedence-constrained tasks, where each task requires executing a set of skills to be performed, and the workforce allocation problem which includes assigning workers as scarce resources to the skills of each task. These two problems are interrelated as the tasks durations are not predefined, but depend on the number of workers assigned to that task as well as their skill levels. We here present a mixed integer linear programming model that considers important real life aspects related to the flexibility in the use of human resources, such as multi-skilled workers whose skill levels are different and measured by their efficiencies. Hence, execution times of the same workload by different workers vary according to these efficiencies. Moreover, the model considers the flexible working time of employees; i.e. the daily and weekly workload of a given worker may vary from one period to another according to the work required. Furthermore, efficient team building is incorporated in this model; i.e. assigning an expert worker and one or more apprentice worker(s) together with the purpose of skill development thanks to knowledge transfer. A numerical example is provided to check the performance of the model

Multiband Handset Antenna System for UMTS/LTE/WLAN/Sub-6 5G and mmWave 5G Future Smartphones

In this paper, a new antenna system for rapidly emerging multifunction devices is presented. The proposed antenna system consists of four antenna components each one operating at different frequency bands separately. The designed antennas are isolated and integrated on a single substrate. The first antenna is designed to operate at 1920–2170 MHz covering the UMTS band, whereas the second antenna is proposed for the lower band 5G systems and WiMAX operating within the frequency range of 3.4–4.2 GHz. Furthermore, another antenna is designed to cover the higher band 5G system and the IEEE 820.11a WLAN within the frequency range of 5.1–5.85 GHz. Finally, a 28 GHz bowtie-based MIMO antenna array is designed and simulated for the mmWave future 5G mobile networks. The proposed antennas were designed and simulated by using CST microwave studio. The results showed that all of the proposed antennas exhibited excellent reflection characteristics below −20 dB at the resonant frequency and achieved high radiation efficiency reached 99% in some cases with a peak gain ranging between 4–6 dBi. The proposed antenna system helps smartphones to perform multitasks and achieve a better-quality operation especially with the enormous growth of IoT techniques