Efficient recursive least squares parameter estimation algorithm for accurate nanoCMOS variable gain amplifier performances

ABSTRACT

With the aggressive scaling of integrated circuit technology, parametric estimation is a critical task for designers who looked for solutions to the challenges of some Nanoscale CMOS parameters. This paper presented the prediction of primary parameters of CMOS transistor for 16 nm to 10 nm process nodes using both of Bisquare Weights (BW) method and a novel recursive least squares (RLS) parameter estimation algorithm. The proposed RLS algorithm consists of the minimisation of a quadratic criterion relating to the prediction error in order to attain the best estimated parameters of the developed mathematical model. The obtained results thanks to the proposed RLS algorithm were better than those reached using the BW method. Comparisons between Predictive Technology Model (PTM) data and parameters estimated with RLS algorithm were made to check the validity and the consistency of the proposed algorithm. These predicted primary parameters were helpful to estimate and to optimise the performances of the Variable Gain Amplifier (VGA) which was a basic circuit element with a key role in the design of new upcoming receivers.     

Influence of Inoculant Type on the Microstructure Characteristics and Mechanical Properties of Ductile Iron

Transactions of the Indian Institute of Metals - The inoculation process of molten cast iron defines the final microstructure of the produced castings. The current study is concerned with the...     

COACT: a query interface language for collaborative databases

Data curation activities in collaborative databases mandate that collaborators interact until they converge and agree on the content of their data. In a previous work, we presented a cloud-based collaborative database system that promotes and enables collaboration and data curation scenarios. Our system classifies different versions of a data item to either pending, approved, or rejected. The approval or rejection of a certain version is done by the database Principle Investigators (or PIs) based on its value. Our system also allows collaborators to view the status of each version and help PIs take decisions by providing feedback based on their experiments and/or opinions. Most importantly, our system provided mechanisms for history tracking of different versions to trace the modifications and approval/rejection done by both collaborators and PIs on different versions of a data item. We labeled our system as Update-Pending-Approval model (or UPA). In this paper, we describe a high level SQL query interface language for PIs and collaborators to interact with the UPA framework. We define a set of UPA keywords that are used as a part of the history tracking mechanism to select specific versions of a data item, and a set of UPA options that select specific versions based on possible future decisions of PIs. We implemented our query interface mechanism on top of Apache Phoenix, taking into consideration that the UPA system was implemented on top of Apache HBase. We test the performance of the UPA query language by executing several queries that contain different complexity levels and discuss their results.     

Partial syndrome-based system-level fault diagnosis using game theory

This paper introduces a novel diagnosis approach, using game theory, to solve the comparison-based system-level fault identification problem in distributed and parallel systems based on the asymmetric comparison model. Under this diagnosis model tasks are assigned to pairs of nodes and the results of executing these tasks are compared. Using the agreements and disagreements among the nodes’ outputs, i.e. the input syndrome, the fault diagnosis algorithm identifies the fault status of the system’s nodes, under the assumption that at most t of these nodes can permanently fail simultaneously. Since the introduction of the comparison model, significant progress has been made in both theory and practice associated with the original model and its offshoots. Nevertheless, the problem of efficiently identifying the set of faulty nodes when not all the comparison outcomes are available to the fault identification algorithm prior to initiating the diagnosis phase, i.e. partial syndromes, remains an outstanding research issue. In this paper, we first show how game theory can be adapted to solve the fault diagnosis problem by maximising the payoffs of all players (nodes). We then demonstrate, using results from a thorough simulation, the effectiveness of this approach in solving the fault identification problem using partial syndromes from randomly generated diagnosable systems of different sizes and under various fault scenarios. We have considered large diagnosable systems, and we have experimented extreme faulty situations by simulating all possible fault sets even those that are less likely to occur in practice. Over all the extensive simulations we have conducted, the new game-theory-based diagnosis algorithm performed very well and provided good diagnosis results, in terms of correctness, latency, and scalability, making it a viable addition or alternative to existing diagnosis algorithms.     

Positive sliding mode control for blood glucose regulation

Biological systems involving positive variables as concentrations are some examples of so-called positive systems. This is the case of the glycemia–insulinemia system considered in this paper. To cope with these physical constraints, it is shown that a positive sliding mode control (SMC) can be designed for glycemia regulation. The largest positive invariant set (PIS) is obtained for the insulinemia subsystem in open and closed loop. The existence of a positive SMC for glycemia regulation is shown here for the first time. Necessary conditions to design the sliding surface and the discontinuity gain are derived to guarantee a positive SMC for the insulin dynamics. SMC is designed to be positive everywhere in the largest closed-loop PIS of plasma insulin system. Two-stage SMC is employed; the last stage SMC2 block uses the glycemia error to design the desired insulin trajectory. Then the plasma insulin state is forced to track the reference via SMC1. The resulting desired insulin trajectory is the required virtual control input of the glycemia system to eliminate blood glucose (BG) error. The positive control is tested in silico on type-1 diabetic patients model derived from real-life clinical data.     

Preparation and characterization of doped manganese dioxides

Doped manganese dioxide samples, containing cations of different valency, were prepared. The doped and undoped samples contained small amounts of physically held and chemically bound water. The X-ray diffraction patterns of the doped samples were very similar to the pattern of the undoped sample and they all belong to the-modification mixed with-MnO₂ and-Mn₂O₃. The specific surface area of the samples measured by nitrogen adsorption and calculated by the _s-method was in the range 2–5 m²g^–1, indicating a lower porosity and a lower reactivity compared to the-forms. From measurements of pore radii the pores were classified as lying in the mesopore/macropore range (8–35 nm). A decrease in the mean pore radius was observed for the doped samples except for that doped with Li⁺ ions.     

Correction to: A subthreshold low-power CMOS LC-VCO with high immunity to PVT variations

This paper presents a capacitor-free low dropout (LDO) linear regulator based on a dual loop topology. The regulator utilizes two feedback loops to satisfy the challenges of hearing aid devices, which include fast transient performance and small voltage spikes under rapid load-current changes. The proposed design works without the need of a decoupling capacitor connected at the output and operates with a 0–100 pF capacitive load. The design has been taped out in a \(0.18\,\upmu \hbox {m}\) CMOS process. The proposed regulator has a low component count, area of \(0.012\, \hbox {mm}^2\) and is suitable for system-on-chip integration. It regulates the output voltage at 0.9 V from a 1.0–1.4 V supply. The measured results for a current step load from 250 to 500 \(\upmu \hbox {A}\) with a rise and fall time of \(1.5\,\upmu \hbox {s}\) are an overshoot of 26 mV and undershoot of 26 mV with a settling time of \(3.5\,\upmu \hbox {s}\) when \({C_L}\) between 0 and 100 pF. The proposed LDO regulator consumes a quiescent current of only \(10.5\,\upmu \hbox {A}\). The design is suitable for application with a current step edge time of 1 ns while maintaining \(\Delta V_{out}\) of 64 mV.     

Hydrodynamics characterization of the Maxblend impeller

The hydrodynamic characteristics of the Maxblend^TM impeller have been investigated in the case of viscous Newtonian fluids. Both laboratory experiments and 3D finite element based computational fluid dynamics (CFD) simulations have been carried out. The power consumption, the mixing evolution yielding the mixing time, and the effect of baffles in the laminar and transition flow regimes have been determined. It was found that the limit Reynolds number between the laminar and transition regimes is approximately 25 and 38 for the unbaffled and baffled configurations, respectively. Based on the range of Reynolds numbers studied in this work, the best window performance of the Maxblend^TM mixer where fast and homogenous mixing is achieved is the end of the laminar regime and the early transition regime with baffles.     

Identification of weak and strong organic acids in atmospheric aerosols by capillary electrophoresis/mass spectrometry and ultra-high-resolution fourier transform ion cyclotron resonance mass spectrometry

A novel approach using a combination of capillary electrophoresis/mass spectrometry (CE/MS) and off-line Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) revealed the structural details of acidic constituents of atmospheric organic aerosol. Both techniques utilized electrospray ionization (ESI), a soft ionization method, to facilitate the analysis of complex mixtures of organic compounds. CE/ESI-MS using an UltraTrol LN-precoated capillary and acidic background electrolytes at different pH values (2.5 and 4.7) was used to differentiate between weak (carboxylic) and strong (sulfonic) organic acids. On the basis of the electrophoretic mobility, m/z constraints from CE/ESI(-)-MS, and elemental composition information retrieved from off-line FTICR-MS, a variety of aliphatic and aromatic carboxylic acids (CHO-bearing molecules), nitrogen-containing carboxylic acids (CHON-bearing molecules), organosulfates (CHOS-bearing molecules), and (nitrooxy)organosulfates (CHONS-bearing molecules) were tentatively identified in the Oasis-HLB-extracted urban PM(2.5) (particulate matter with an aerodynamic diameter of <2.5 μm). The chemical known/unknown structures of detected compounds were confirmed by the semiempirical Offord model (effective mobility linearly correlated to Z/M(2/3)). The majorities of the identified compounds are products of atmospheric reactions and are known contributors to secondary organic aerosols.