A comprehensive study of Bluetooth signal parameters for localization

We provide an elaborate discussion on Bluetooth signal parameters with respect to localization, whereby we collectively designate all types of Bluetooth specification parameters that are related to signal strength - such as RSSI, Link Quality, Received and Transmit Power Level - as Bluetooth signal, parameters. According to our analysis and experimental results, "RSSI" and "Transmit Power Level" turn out to be poor candidates for localization, while "Link Quality" has its limitations. On the other hand, "Received Power Level" correlates nicely with distance, which makes it the most desirable Bluetooth signal parameter to be used in location systems. We contend that it is vital to choose the appropriate signal parameter in Bluetooth location systems, and we expect our work to provide useful pointers in any future design of such systems. Existing systems can also benefit by adopting the appropriate Bluetooth signal parameter in their systems, and thereby, improve their location accuracy

Convolutional neural network training with artificial pattern for Bangla handwritten numeral recognition

Recognition of handwritten numerals has gained much interest in recent years due to its various application potentials. The progress of handwritten Bangla numeral is well behind Roman, Chinese and Arabic scripts although it is a major language in Indian subcontinent and is the first language of Bangladesh. Handwritten numeral classification is a high dimensional complex task and existing methods use distinct feature extraction techniques and various classification tools in their recognition schemes. Recently, convolutional neural network (CNN) is found efficient for image classification with its distinct features. In this study, a CNN based method has been investigated for Bangla handwritten numeral recognition. A moderated pre-processing has been adopted to produce patterns from handwritten scan images. On the other hand, CNN has been trained with the patterns plus a number of artificial patterns. A simple rotation based approach is employed to generate artificial patterns. The proposed CNN with artificial pattern is shown to outperform other existing methods while tested on a popular Bangla benchmark handwritten dataset

Multiple convolutional neural network training for Bangla handwritten numeral recognition

Recognition of handwritten numerals has gained much interest in recent years due to its various application potentials. The progress of handwritten Bangla numeral is well behind Roman, Chinese and Arabic scripts although it is a major language in Indian subcontinent and is the first language of Bangladesh. Handwritten numeral classification is a high-dimensional complex task and existing methods use distinct feature extraction techniques and various classification tools in their recognition schemes. Recently, convolutional neural network (CNN) is found efficient for image classification with its distinct features. In this study, three different CNNs with same architecture are trained with different training sets and combined their decisions for Bangla handwritten numeral recognition. One CNN is trained with ordinary training set prepared from handwritten scan images; and training sets for other two CNNs are prepared with fixed (positive and negative, respectively) rotational angles of original images. The proposed multiple CNN based approach is shown to outperform other existing methods while tested on a popular Bangla benchmark handwritten dataset

On Research Challenges in Hybrid Medium Access Control Protocols for IEEE 802.15.6 WBANs

IEEE 802.15.6 is a Wireless Body Area Network (WBAN) standard proposed to facilitate the exponentially growing interest in the field of health monitoring. This standard is flexible and outlines multiple basic Medium Access Control (MAC) protocols that are contention based and collision free to meet the WBAN Quality of Service (QoS) challenges. Typically, current research trends in WBAN MAC focus on designing a hybrid MAC that is a combination of basic MAC protocols. In this paper, we provide a first detailed survey of existing hybrid MAC protocols based on IEEE 802.15.6 which would be useful for the related research community. Firstly, the paper lists the design challenges of a WBAN MAC. Secondly, it highlights the significance of hybrid MAC protocols in meeting the design challenges while comparing them to standard MAC protocols. Thirdly, a critical and thorough comparison of existing hybrid MAC protocols is presented in terms of network QoS and WBAN specific parameters. Lastly, we identify key open research areas that are often neglected in hybrid MAC design and further propose some possible directions for future research

Low-Cost Aquifer Storage and Recovery: Implications for Improving Drinking Water Access for Rural Communities in Coastal Bangladesh

Fresh water resources are scarce in rural communities in the southern deltaic plains of Bangladesh where both shallow and deep groundwater is frequently brackish, and fresh water ponds have been increasingly salinized by inundation during storm surges and brackish-water aquaculture. Low-cost aquifer storage and recovery (ASR) schemes were constructed at 13 villages in three coastal districts by developing storage in shallow confined fine to medium sand aquifers overlain by variable thicknesses of silt and clay. A typical ASR scheme consisted of a double-chambered graded sand filtration tank with a volume of 19.5  m3 that feeds filtered pond water to four to six large diameter (d=30.5 or 56 cm) infiltration wells through PVC pipes fitted with stop valves and flow meters. The infiltration wells were completed at 18–31 m below ground and filled with well-sorted gravel capped with a thin layer of fine sand that acts as a second stage filter. Infiltration rates at 13 sites averaged 3  m3/day (range: 3–6  m3/day) over one year of operation. At 11 sites where water was abstracted, the recovery rate ranged from 5 to 40%. The source pond source water frequently had turbidity values of ≥100  NTU. After sand filtration, the turbidity is typically 5 NTU. Despite this, clogging management involving frequent (monthly to weekly) manual washing to remove fine materials deposited in the sand filtration tank and the infiltration wells is found to be necessary and effective, with post-manual-washing operational infiltration rates restored to annual average values. E. coli counts in recovered water are greatly reduced compared to raw pond water, although E. coli is still detected in about half of the samples. Arsenic in recovered water was detected to be at level of > 100  μg/L repeatedly at three sites, suggesting that As risks must be carefully managed and require further investigation

Neighbour-disjoint multipath for low-power and lossy networks

In this article, we describe a neighbour disjoint multipath (NDM) scheme that is shown to be more resilient amidst node or link failures compared to the two well-known node disjoint and edge disjoint multipath techniques. A centralised NDM was first conceptualised in our initial published work utilising the spatial diversity among multiple paths to ensure robustness against localised poor channel quality or node failures. Here, we further introduce a distributed version of our NDM algorithm adapting to the low-power and lossy network (LLN) characteristics. We implement our distributed NDM algorithm in Contiki OS on top of LOADng—a lightweight On-demand Ad hoc Distance Vector Routing protocol. We compare this implementation's performance with a standard IPv6 Routing Protocol for Low power and Lossy Networks (RPL), and also with basic LOADng, running in the Cooja simulator. Standard performance metrics such as packet delivery ratio, end-to-end latency, overhead and average routing table size are identified for the comparison. The results and observations are provided considering a few different application traffic patterns, which serve to quantify the improvements in robustness arising from NDM. The results are confirmed by experiments using a public sensor network testbed with over 100 nodes

Adenoviral expression of a bispecific VHH-based neutralizing agent that targets protective antigen provides prophylactic protection from anthrax in mice

Bacillus anthracis, the causative agent of anthrax, secretes three polypeptides, which form the bipartite lethal and edema toxins (LT and ET, respectively). The common component in these toxins, protective antigen (PA), is responsible for binding to cellular receptors and translocating the lethal factor (LF) and edema factor (EF) enzymatic moieties to the cytosol. Antibodies against PA protect against anthrax. We previously isolated toxin-neutralizing variable domains of camelid heavy-chain-only antibodies (VHHs) and demonstrated their in vivo efficacy. In this work, gene therapy with an adenoviral (Ad) vector (Ad/VNA2-PA) (VNA, VHH-based neutralizing agents) promoting the expression of a bispecific VHH-based neutralizing agent (VNA2-PA), consisting of two linked VHHs targeting different PA-neutralizing epitopes, was tested in two inbred mouse strains, BALB/cJ and C57BL/6J, and found to protect mice against anthrax toxin challenge and anthrax spore infection. Two weeks after a single treatment with Ad/VNA2-PA, serum VNA2-PA levels remained above 1 μg/ml, with some as high as 10 mg/ml. The levels were 10- to 100-fold higher and persisted longer in C57BL/6J than in BALB/cJ mice. Mice were challenged with a lethal dose of LT or spores at various times after Ad/VNA2-PA administration. The majority of BALB/cJ mice having serum VNA2-PA levels of >0.1 μg/ml survived LT challenge, and 9 of 10 C57BL/6J mice with serum levels of >1 μg/ml survived spore challenge. Our findings demonstrate the potential for genetic delivery of VNAs as an effective method for providing prophylactic protection from anthrax. We also extend prior findings of mouse strain-based differences in transgene expression and persistence by adenoviral vectors

A hop-count based positioning algorithm for wireless ad-hoc networks

We propose a range-free localization algorithm for a wireless ad-hoc network utilizing the hop-count metric’s ability to indicate proximity to anchors (i.e., nodes with known positions). In traditional sense, hop-count generally means the number of intermediate routers a datagram has to go through between its source and the destination node. We analytically show that hop-count could be used to indicate proximity relative to an anchor node. Our proposed algorithm is computationally feasible for resource constrained wireless ad-hoc nodes, and gives reasonable accuracy. We perform both real experiments and simulations to evaluate the algorithm’s performance. Experimental results show that our algorithm outperforms similar proximity based algorithms utilizing received signal strength and expected transmission count. We also analyze the impact of various parameters like the number of anchor nodes, placements of anchor nodes and varying transmission powers of the nodes on the hop-count based localization algorithm’s performance through simulation