It is shown that, particularly for terrestrial cellular telephony, the interference-suppression feature of CDMA (code division multiple access) can result in a many-fold increase in capacity over analog and even over competing digital techniques. A single-cell system, such as a hubbed satellite network, is addressed, and the basic expression for capacity is developed. The corresponding expressions for a multiple-cell system are derived. and the distribution on the number of users supportable per cell is determined. It is concluded that properly augmented and power-controlled multiple-cell CDMA promises a quantum increase in current cellular capacity. >

On the capacity of a cellular CDMA system

Underwater Wireless Sensor Networks (UWSNs) are expected to support a variety of civilian and military applications. In UWSNs, Medium Access Control (MAC) protocol has attracted strong attention due to its potentially large impact to the overall network performance. Unlike terrestrial networks, which mainly rely on radio waves for communications, UWSNs utilize acoustic waves, which pose a new research challenge in the design of MAC protocols. To present the development of MAC protocols in UWSNs, this paper surveys the current state-of-the-art MAC protocols for UWSNs. In the early development, the performance in terms of delay and throughput of the UWSNs has been the major concern of the MAC layer protocol design. Later, the design of energy-efficient MAC protocols becomes a new research focus because sensor nodes are generally powered by batteries which are less likely to be recharged. In this paper, we first describe the underwater acoustic environment and the challenges to the MAC protocols design in UWSNs. We then provide a comparative study of several types of MAC protocols according to current existing diverse implementations. Furthermore, open research issues will be summarized. Hopefully, this survey will inspire more active research in this area.

A Survey on MAC Protocols for Underwater Wireless Sensor Networks

The demand for high-quality and low-cost products with short development time in the dynamic global market has forced researchers and industries to focus on various effective product development strategies. The authors are carrying out research studies to explore the applicability of fuzzy logic and knowledge-based systems technologies to today’s competitive product design and development, with an emphasis on the design of high quality products at the conceptual design stage. A framework of a fuzzy FMEA (failure modes and rffects analysis) based evaluation approach for new product concepts is proposed in this paper. Based on the proposed approach and methodologies, a prototype system named EPDS-1, which can assist inexperienced users to perform FMEA analysis for quality and reliability improvement, alternative design evaluation, materials selection, and cost assessment, thus helping to enhance robustness of new products at the conceptual design stage. This paper presents the underlying concepts of the development and shows the practical application with the prototype system with a case study.

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Development of a fuzzy FMEA based product design system

The metal manganese is a potent magnetic resonance imaging (MRI) contrast agent that is essential in cell biology. Manganese-enhancedmagneticresonanceimaging(MEMRI) is providing unique information in an ever-growing number of applications aimed at understanding the anatomy, the integration,andthefunctionofneuralcircuitsbothinnormalbrain physiology as well as in translational models of brain disease. A major drawback to the use of manganese as a contrast agent, however, is its cellular toxicity. Therefore, paramount tothesuccessfulapplicationofMEMRIistheabilitytodeliver Mn 21 to the site of interest using as low a dose as possible while preserving detectability by MRI. In the present work, the different approaches to MEMRI in translational neuroimaging are reviewed and challenges for future identified from a practical standpoint.

/pdf/manganese-enhanced-mri-an-exceptional-tool-in-translational-2hio9kv1ia.pdf

Manganese-Enhanced MRI: An Exceptional Tool in Translational Neuroimaging

The consumption of animal by-products has continued to witness tremendous growth over the last decade. This is due to its potential to combat protein malnutrition and food insecurity in many countries. Shortly after slaughter, animal by-products are separated into edible or inedible parts. The edible part accounts for 55% of the production while the remaining part is regarded as inedible by-products (IEBPs). These IEBPs can be re-processed into sustainable products for agricultural and industrial uses. The efficient utilization of animal by-products can alleviate the prevailing cost and scarcity of feed materials, which have high competition between animals and humans. This will also aid in reducing environmental pollution in the society. In this regard, proper utilization of animal by-products such as rumen digesta can result in cheaper feed, reduction in competition and lower cost of production. Over the years, the utilization of animal by-products such as rumen digesta as feed in livestock feed has been successfully carried out without any adverse effect on the animals. However, there are emerging gaps that need to be further addressed regarding the food security and sustainability of the products. Therefore, the objective of this review highlights the efficacy and effectiveness of using animal by-products as alternative sources of feed ingredients, and the constraints associated with their production to boost livestock performance in the industry at large.

The Potential of Animal By-Products in Food Systems: Production, Prospects and Challenges

This paper aims to investigate the robust and distinguishable pattern of heart rate variability (HRV) signals, acquired from wearable electrocardiogram (ECG) or photoplethysmogram (PPG) sensors, for driver drowsiness detection. As wearable sensors are so vulnerable to slight movement, they often produce more noise in signals. Thus, from noisy HRV signals, we need to find good traits that differentiate well between drowsy and awake states. To this end, we explored three types of recurrence plots (RPs) generated from the R–R intervals (RRIs) of heartbeats: Bin-RP, Cont-RP, and ReLU-RP. Here Bin-RP is a binary recurrence plot, Cont-RP is a continuous recurrence plot, and ReLU-RP is a thresholded recurrence plot obtained by filtering Cont-RP with a modified rectified linear unit (ReLU) function. By utilizing each of these RPs as input features to a convolutional neural network (CNN), we examined their usefulness for drowsy/awake classification. For experiments, we collected RRIs at drowsy and awake conditions with an ECG sensor of the Polar H7 strap and a PPG sensor of the Microsoft (MS) band 2 in a virtual driving environment. The results showed that ReLU-RP is the most distinct and reliable pattern for drowsiness detection, regardless of sensor types (i.e., ECG or PPG). In particular, the ReLU-RP based CNN models showed their superiority to other conventional models, providing approximately 6–17% better accuracy for ECG and 4–14% for PPG in drowsy/awake classification.

Using Wearable ECG/PPG Sensors for Driver Drowsiness Detection Based on Distinguishable Pattern of Recurrence Plots

Continuous and programmable photomechanical jumping of polymer monoliths

Photoelectrochemical water splitting is the most efficient green engineering approach to convert the sun light into hydrogen energy. The formation of high surface area core-shell heterojunction with enhanced light-harvesting efficiency, elevated charge separation, and transport are key parameters in achieving the ideal water splitting performance of the photoanode. Herein, we demonstrate a first green engineering interfacial growth of the BiVO4 nanoparticles onto self-assembled WO3 nanoplates forming WO3/BiVO4 core-shell heterojunction for efficient PEC water splitting performance. The three different WO3 nanostructures (nanoplates, nanobricks, and stacked nanosheets) were self-assembled on fluorine doped tin oxide glass substrates via hydrothermal route at various pH (0.8–1.2) of the solutions. In comparison to nanobricks and stacked nanosheets, WO3 nanoplates displayed considerably elevated photocurrent density. Moreover, a simple and low cost green approach of modified chemical bath deposition technique was established for the optimal decoration of a BiVO4 nanoparticles on vertically aligned WO3 nanoplates. The boosted photoelectrochemical current density of 1.7 mA cm−2 at 1.23 V vs. reversible hydrogen electrode (RHE) under AM 1.5 G illumination was achieved for the WO3/BiVO4 heterojunction which can be attributed to a suitable band alignment for the efficient charge transfer from BiVO4 to WO3, increased light harvesting capability of outer BiVO4 layer, and high charge transfer efficiency of WO3 nanoplates.

Interfacial growth of the optimal BiVO4 nanoparticles onto self-assembled WO3 nanoplates for efficient photoelectrochemical water splitting.

We propose an efficient cooperative ARQ (Automatic Repeat reQuest) scheme for underwater acoustic communications, in which cooperative nodes are used to provide more reliable alternative paths for a specific source-to-destination connection. Based on the knowledge of inter-node distances, a cooperative region is defined to include all possible candidates for cooperative nodes from a given pair of source-destination nodes. When the destination node receives an erroneous packet, it asks for retransmission from a cooperative node, which is selected in a closest-one-first manner from the nodes in the cooperative region. The selection procedure continues until the retransmission is successful. In this paper, we evaluate the proposed scheme by comparing it with a conventional S&W ARQ in terms of throughput efficiency. Computer simulation results show that the proposed cooperative retransmission scheme can significantly improve the throughput by increasing the probability of successful retransmission.

A cooperative ARQ scheme in underwater acoustic sensor networks

This paper proposes an open computer language (OpenCL) parallel processing method to generate the elemental image arrays (EIAs) for hexagonal lens array from a three-dimensional (3D) object such as a volume data. Hexagonal lens array has a higher fill factor compared to the rectangular lens array case; however, each pixel of an elemental image should be determined to belong to the single hexagonal lens. Therefore, generation for the entire EIA requires very large computations. The proposed method reduces processing time for the EIAs for a given hexagonal lens array. By using the proposed image space parallel processing (ISPP) method, it can enhance the processing speed that generates the 3D display of real-time interactive integral imaging for hexagonal lens array. In our experiment, we implemented the EIAs for hexagonal lens array in real-time and obtained a good processing time for a large of volume data for multiple cases of lens arrays.

Jaewon Lee

Papers

Using Wearable ECG/PPG Sensors for Driver Drowsiness Detection Based on Distinguishable Pattern of Recurrence Plots

Continuous and programmable photomechanical jumping of polymer monoliths

Interfacial growth of the optimal BiVO4 nanoparticles onto self-assembled WO3 nanoplates for efficient photoelectrochemical water splitting.

A cooperative ARQ scheme in underwater acoustic sensor networks

Real-time 3D display system based on computer-generated integral imaging technique using enhanced ISPP for hexagonal lens array