Heritage Institute of Technology

About: Heritage Institute of Technology is a based out in . It is known for research contribution in the topics: Steganography & Support vector machine. The organization has 581 authors who have published 1045 publications receiving 8345 citations.

Quantum anomalous Hall phase and half-metallic phase in ferromagnetic (111) bilayers of 4 d and 5 d transition metal perovskites

Abstract: Extraordinary electronic phases can form in artificial oxide heterostructures, which will provide a fertile ground for new physics and also give rise to novel device functions. Based on a systematic first-principles density functional theory study of the magnetic and electronic properties of the (111) superlattices ${({AB\text{O}}_{3})}_{2}/{({AB}^{\ensuremath{'}}{\mathrm{O}}_{3})}_{10}$ of $4d$ and $5d$ transition metal perovskite ($B$ = Ru, Rh, Ag, Re, Os, Ir, Au; ${AB}^{\ensuremath{'}}{\mathrm{O}}_{3}={\mathrm{LaAlO}}_{3}, {\mathrm{SrTiO}}_{3})$, we demonstrate that due to quantum confinement, bilayers ${({\text{La}B\text{O}}_{3})}_{2}$ ($B$ = Ru, Re, Os) and ${({\text{Sr}B\text{O}}_{3})}_{2}$ ($B$ = Rh, Os, Ir) are ferromagnetic with ordering temperatures up to room temperature. In particular, bilayer ${({\mathrm{LaOsO}}_{3})}_{2}$ is an exotic spin-polarized quantum anomalous Hall insulator, while the other ferromagnetic bilayers are metallic with large Hall conductances comparable to the conductance quantum. Furthermore, bilayers ${({\mathrm{LaRuO}}_{3})}_{2}$ and ${({\mathrm{SrRhO}}_{3})}_{2}$ are half metallic, while the bilayer ${({\mathrm{SrIrO}}_{3})}_{2}$ exhibits a peculiar colossal magnetic anisotropy. Our findings thus show that $4d$ and $5d$ metal perovskite (111) bilayers are a class of quasi-two-dimensional materials for exploring exotic quantum phases and also for advanced applications such as low-power nanoelectronics and oxide spintronics.

In-vitro evaluation of targeted release of probiotic Lactobacillus casei (2651 1951 RPK) from synbiotic microcapsules in the gastrointestinal (GI) system: Experiments and modeling

Abstract: The microencapsulation processes serve potentially to protect probiotic cells against adversity in the GI tract. The article focuses on the behavior and release characteristics of Lactobacillus casei from synbiotic microcapsules. Monod (μmax = 0.78 h−1, Ks = 2.44 g/L) Haldane (μmax = 0.05 h−1, Ks = 0.2 g/L, KI = 0.52 g/L) and summative models are followed by L. casei during its growth on lactose, inulin and the combination of these carbohydrates respectively. The internal micro-encapsulation efficiency (98%) for synbiotic microcapsules (24 μm) has been optimized with respect to concentrations of sodium alginate (2%), tween-80 and post-cooling temperature (25 °C) using Response Surface Methodology. In agreement with the prediction of proposed “burst release” mechanism, probiotic cells are released after 50 min if 1 g synbiotic microcapsules are initially suspended in 10 mL simulated large intestinal juice. A mathematical model has been developed to predict the concentration profiles of microcapsules and released probiotic cells in the GI system and has been validated through the successful comparison of simulated data with the results of in-vitro experiments. The concentration of released probiotic cells rises to 1.7E10/L in the large intestine. Interestingly, this is the first study on the prediction of release of L. casei from synbiotic microcapsules and is expected to be useful for similar systems.

A Network-TOPSIS Based Fuzzy Decision Support System for Supplier Selection in Risky Supply Chain

Abstract: Supplier selection is a multi-criteria decision making problem involving several conflicting criteria on which decision maker's knowledge is not precise. A systematic methodology is proposed by integrating fuzzy extent analysis, fuzzy cognitive map and fuzzy decision map forming a fuzzy decision network with fuzzy-TOPSIS to select appropriate supplier providing flexibility to decision makers. Here linguistic values in triangular fuzzy numbers are preferred to represent relative importance among inter-dependence criteria in preference matrix for local weight as well as steady-state matrix for inner-dependence criteria in fuzzy cognitive map stage. The proposed method makes use of fuzzy decision map for global weights of criteria and fuzzy TOPSIS for assessing the alternatives based on global weight. The steps of the method are described first and a numerical example for supplier selection in textile supply chain is given to illustrate the proposed method.

A Graph-Based 3D IC Partitioning Technique

Abstract: Netlist partitioning is an important part of thephysical design of 3D IC chips. Each subcircuit correspondingto a partition is subsequently assigned to a suitable device layerin the design phase. This paper proposes a netlist partitioningtechnique that intends to minimize the number of inter-layerinterconnections while maintaining the area constraints. This, inturn, will minimze the area and cost associated with the Through-Silicon Vias (TSVs) needed in the design. The proposed methodstarts with an BFS-based initial solution and then improves ititeratively using a heuristic. Experimental results demonstratethat by reassigning some modules to other layers, our algorithmcould achieve up to 45% reduction in the number of TSVs onseveral benchmark circuits compared to earlier approaches. Theresulting increase in floor area due to movement of modules acrosslayers, is almost compensated by the decrease in TSV-area. Thuswhile satisfying the area-constraints, it allows us to reduce thenumber of TSVs as well as the IR-drop and delay associated withthe vias.

On-Board Signal Quality Assessment Guided Compression of Photoplethysmogram for Personal Health Monitoring

Abstract: Photoplethysmography (PPG) is a popular diagnostic tool for the assessment of various cardiovascular functions. Under continuous ambulatory measurements, PPG data get corrupted due to motion artifact (MA). Thus, on-board pulse signal quality assessment (SQA) before transmission can save the battery life of the wearable device for portable health monitoring applications. This article describes an SQA guided compression (SQAGC) of PPG data using a modified gain-shaped vector quantization (GSVQ) technique. The SQA was performed using kurtosis and autocorrelation to generate a binary classification rule to detect good quality pulses. Only these were considered for further compression. A notable contribution is reconstruction error minimization using the extracted features from the residual signal using a deep autoencoder (DAE), achieving a low percentage root-mean-squared difference (PRD). The SQAGC technique was evaluated using public databases like MIMIC-II, BIDMC, and PRRB as well as with real volunteers’ PPG collected in the laboratory environment. The SQA achieved an accuracy of 96.5% to identify good quality PPG segments out of expert annotated 9200 beats. The compression factor (and PRD) with 400 min duration data from Physionet MIMIC-II, BIDMC, PRRB, and volunteers’ data were 15.8 (and 0.31), 15.7 (and 0.21), 17.8 (and 0.33), and 18.2 (and 0.59), respectively, using 12-bit resolution and 125 Hz sampling. A real-time on-device implementation using quad-core ARM Cortex-A53, 1.2 GHz, supported by 1 GB RAM, achieved a latency of 546 ms with 327 kB of memory engagement for a 3 s PPG window. The compression ratio (CR) achieved comparable results, while PRD outperforms the published results using MIMIC-II data set.