Compressive Sensing based Detector for Sparse Signal Modulation in Precoded OFDM

In this paper, we propose a sparse signal modulation (SSM) method for precoded orthogonal frequency division multiplexing (OFDM) systems and study the signal detection. Although a receiver is able to exploit a path diversity gain with random precoding in OFDM, the complexity of the receiver is usually high as the orthogonality is not retained due to precoding. However, with SSM, we can derive a low-complexity detector that can provide reasonably good performances with a low sparsity ratio based on the notion of compressive sensing (CS). An important feature of a CS detector is that it can estimate SSM signals with a small fraction of the received signals over sub-carriers. This feature can allow us to build a low cost receiver with a small number of demodulators.

Microelectronic manufacturing of a microsensor based on polyaniline for ammonia gas sensing

The fabrication and operation of an ammonia chemoresistor is described. The sensor responds to changes in the resistance (impedance) of a thin layer of conductive polymer is due to changes in ammonia concentration. The polyaniline film was deposited by electroless plating (dipping) method on interdigitated array made by photolithographic technique. The PANI film was characterized by UV/VIS and IR Spectroscopy and respectively, Atomic Force Microscopy. Impedance Spectroscopy was used for sensor characterization

Deriving meteorological variables across Africa for the study and control of vector-borne disease:a comparison of remote sensing and spatial interpolation of climate

This paper presents the results of an investigation into the utility of remote sensing (RS) using meteorological satellites sensors and spatial interpolation (SI) of data from meteorological stations, for the prediction of spatial variation in monthly climate across continental Africa in 1990. Information from the Advanced Very High Resolution Radiometer (AVHRR) of the National Oceanic and Atmospheric Administration's (NOAA) polar-orbiting meteorological satellites was used to estimate land surface temperature (LST) and atmospheric moisture. Cold cloud duration (CCD) data derived from the High Resolution Radiometer (HRR) onboard the European Meteorological Satellite programme's (EUMETSAT) Meteosat satellite series were also used as a RS proxy measurement of rainfall. Temperature, atmospheric moisture and rainfall surfaces were independently derived from SI of measurements from the World Meteorological Organization (WMO) member stations of Africa. These meteorological station data were then used to test the accuracy of each methodology, so that the appropriateness of the two techniques for epidemiological research could be compared. SI was a more accurate predictor of temperature, whereas RS provided a better surrogate for rainfall; both were equally accurate at predicting atmospheric moisture. The implications of these results for mapping short and long-term climate change and hence their potential for the study anti control of disease vectors are considered. Taking into account logistic and analytical problems, there were no clear conclusions regarding the optimality of either technique, but there was considerable potential for synergy.

Monitoring of saliva pH using miniaturized sensing tools as an indicator of oral health

The monitoring of oral disease is important, not alone for oral health, but for the detection and prevention of
systemic disease. The link between oral health and systemic disease is the focus of many studies, with
indications emerging of a causal link [1]. For disease diagnostics, blood has typically been the fluid of choice
for analysis, the retrieval of which is invasive and therefore unsuitable for wearable technology. Analysis of
saliva, however, is less invasive than that of blood, requires little or no pre-treatment and is abundantly
available. A strong correlation has been found between the analytes of blood and saliva [2] with saliva
containing biomarkers for diseases such as diabetes, oral cancer and cardiovascular disease. The development of
an implantable multi-parametric wireless sensor, to monitor both salivary analytes and changes in gingival
temperature, is the aim of this research project.
The aim of our current study is to detect changes in salivary pH, using a gold electrode with a pHsensitive
iridium oxide layer, and an Ion Sensitive Field Effect Transistor probe. Characterisation studies were
carried out in artificial saliva (AS). A salivary pH of between 4.5pH-7.5pH [3], and gingival temperature
between 35°C-38°C [4], were identified as the target range of interest for the human oral environment. Sensor
measurements were recorded in solutions of varying pH and temperature. An ISFET probe was then implanted
into a prototype denture and characterised in AS. This study demonstrates the suitability of ISFET and gold
electrode pH sensors for incorporation into implantable oral sensors.
[1] G. Taylor and W. Borgnakke, “Periodontal disease: associations with diabetes, glycemic control and
complications,” Oral Dis., vol. 14, no. 3, pp. 191–203, Apr. 2008.
[2] E. Tékus, M. Kaj, E. Szabó, N. L. Szénási, I. Kerepesi, M. Figler, R. Gábriel, and M. Wilhelm,
“Comparison of blood and saliva lactate level after maximum intensity exercise,” Acta Biol. Hung., vol. 63
Suppl 1, pp. 89–98, 2012.
[3] S. Naveen, M. L. Asha, G. Shubha, A. Bajoria, and A. Jose, “Salivary Flow Rate, pH and Buffering
Capacity in Pregnant and Non Pregnant Women - A Comparative Study,” JMED Res., pp. 1–8, Feb. 2014.
[4] A. F. Holthuis and F. S. Chebib, “Observations on temperature and temperature patterns of the gingiva. I.
The effect of arch, region and health,” J. Periodontol., vol. 54, no. 10, pp. 624–628, Oct. 1983

Practical Spectrum Aggregation for Secondary Networks with Imperfect Sensing

We investigate a collision-sensitive secondary network that intends to opportunistically aggregate and utilize spectrum of a primary network to achieve higher data rates. In opportunistic spectrum access with imperfect sensing of idle primary spectrum, secondary transmission can collide with primary transmission. When the secondary network aggregates more channels in the presence of the imperfect sensing, collisions could occur more often, limiting the performance obtained by spectrum aggregation. In this context, we aim to address a fundamental query, that is, how much spectrum aggregation is worthy with imperfect sensing. For collision occurrence, we focus on two different types of collision: one is imposed by asynchronous transmission; and the other by imperfect spectrum sensing. The collision probability expression has been derived in closed-form with various secondary network parameters: primary traffic load, secondary user transmission parameters, spectrum sensing errors, and the number of aggregated sub-channels. In addition, the impact of spectrum aggregation on data rate is analysed under the constraint of collision probability. Then, we solve an optimal spectrum aggregation problem and propose the dynamic spectrum aggregation approach to increase the data rate subject to practical collision constraints. Our simulation results show clearly that the proposed approach outperforms the benchmark that passively aggregates sub-channels with lack of collision awareness.

A Coordination and Ligand Replacement Based Three-Input Colorimetric Logic Gate Sensing Platform for Melamine, Mercury Ions, and Cysteine

Discrimination of different species in various target scopes within a single sensing platform can provide many advantages such as simplicity, rapidness, and cost effectiveness. Here we design a three-input colorimetric logic gate based on the aggregation and anti-aggregation of gold nanoparticles (Au NPs) for the sensing of melamine, cysteine, and Hg2+. The concept takes advantages of the highly specific coordination and ligand replacement reactions between melamine, cysteine, Hg2+, and Au NPs. Different outputs are obtained with the combinational inputs in the logic gates, which can serve as a reference to discriminate different analytes within a single sensing platform. Furthermore, besides the intrinsic sensitivity and selectivity of Au NPs to melamine-like compounds, the “INH” gates of melamine/cysteine and melamine/Hg2+ in this logic system can be employed for sensitive and selective detections of cysteine and Hg2+, respectively.

Novel titania sol-gel derived film for luminescence-based oxygen sensing.

A novel method for the preparation of titania sol–gel derived oxygen sensors based on the ruthenium(II) dye, [Ru(bpy)3]2+, is described. A titania sol–gel paste film was cast onto microscope slides, and the dye ion-paired to the deprotonated, hydroxylated groups on the film's surface from an aqueous solution of the dye at pH 11. The resulting sensor film is extremely oxygen sensitive, with a PO2 (S = 1/2) value (i.e. the partial pressure of oxygen required in order to reduce the original, oxygen free, luminescence intensity by 50%) of 0.011 atm. The sensor undergoes 95% response to oxygen in 4 s, and shows 95% recovery of its luminescence in argon within 7 s.

Belief change with noisy sensing in the situation calculus

Situation calculus has been applied widely in arti?cial intelligence to model and reason about actions and changes in dynamic systems. Since actions carried out by agents will cause constant changes of the agents’ beliefs, how to manage
these changes is a very important issue. Shapiro et al. [22] is one of the studies that considered this issue. However, in this framework, the problem of noisy sensing, which often presents in real-world applications, is not considered. As a
consequence, noisy sensing actions in this framework will lead to an agent facing inconsistent situation and subsequently the agent cannot proceed further. In this paper, we investigate how noisy sensing actions can be handled in iterated
belief change within the situation calculus formalism. We extend the framework proposed in [22] with the capability of managing noisy sensings. We demonstrate that an agent can still detect the actual situation when the ratio of noisy sensing actions vs. accurate sensing actions is limited. We prove that our framework subsumes the iterated belief change strategy in [22] when all sensing actions are accurate. Furthermore, we prove that our framework can adequately handle belief introspection, mistaken beliefs, belief revision and belief update even with noisy sensing, as done in [22] with accurate sensing actions only.

From Sensing to Molecular Logic: A Journey

A personal account of the establishment of luminescent PET (photoinduced electron transfer) sensing and its development into molecular logic is given. Several applications of these two research areas, e.g. blood electrolyte diagnostics, ‘lab-on-amolecule’ systems and molecular computational identification (MCID) are illustrated.