Carbon-based TiO2-x heterostructure nanocomposites for enhanced photocatalytic degradation of dye molecules

Application of brown titanium dioxide (TiO_2-x) and its modified composite forms in the photocatalytic decomposition of organic pollutants in the environment is a promising way to provide solutions for environmental redemption. Herein, we report the synthesis of effective and stable TiO_2-x nanoparticles with g-C₃N₄, RGO, and multiwalled carbon nanotubes (CNTs) using a simple hydrothermal method. Among all the as-synthesized samples, excellent photocatalytic degradation activity was observed for RGO-TiO_2-x nanocomposite with high rate constants of 0.075 min^?1_, 0.083 min^?1 and 0.093 min^?1 for methylene blue, rhodamine-B, and rosebengal dyes under UV–Visible light irradiation, respectively. The altered bandgap (1.8 eV) and the large surface area of RGO-TiO_2-x nanocomposite impacts on both absorption of visible light and efficiency of photogenerated charge electron (e^?)/hole (h⁺) pair separation. This resulted in enhanced photocatalytic property of carbon-based TiO_2-x nanocomposites. A systematic study on the influence of different carbon nanostructures on the photocatalytic activity of brown TiO_2-x is carried out.     

Energy Minimization for Real-Time Data Gathering in Wireless Sensor Networks

This paper studies the challenging problem of energy minimization for data gathering over a multiple-sources single-sink communication substrate in wireless sensor networks by exploring the energy-latency tradeoffs using rate adaptation techniques. We consider a real-time scenario for mission-critical applications, where the data gathering must be performed within a specified latency constraint. We first propose an offline numerical optimization algorithm with performance analysis for a special case with a complete binary data gathering tree. Then, by discretizing the transmission time, we present a simple, distributed on-line protocol that relies only on the local information available at each sensor node. Extensive simulations were conducted for both long and short-range communication scenarios using two different source placement models. We used the baseline of transmitting all packets at the highest speed and shutting down the radios afterwards. Our simulation results show that compared with this baseline, up to 90% energy savings can be achieved by our techniques (both off-line and on-line), under different settings of several key system parameters     

Microwave-Assisted Synthesis of Fine Particle Oxides Employing Wet Redox Mixtures

Interaction of electromagnetic radiation with a physical mixture of metal nitrates and amides/hydrazides is observed to initiate high-temperature reactions, useful for realizing several high-temperature ceramic materials. A judicious choice of such redox mixtures undergoes exothermic reactions when they couple with microwave radiation. The coupling of electromagnetic radiation with metal salts and amides/hydrazides depends on the dielectric properties of the individual components in the reaction mixture. The approach has been used to prepare γ-Fe₂O₃, Fe₃O₄, MgCr₂O₄, α-CaCr₂O₄, and La_0.7Ba_0.3MnO₃.     

Multivariability speaker recognition database in Indian scenario

In this paper we describe the collection and organization of the speaker recognition database in Indian scenario named as IITG Multivariability Speaker Recognition Database. The database contains speech from 451 speakers speaking English and other Indian languages both in conversational and read speech styles recorded using various sensors in parallel under different environmental conditions. The database is organized into four phases on the basis of different conditions employed for the recording. The results of the initial studies conducted on a speaker verification system exploring the impact of mismatch in training and test conditions using the collected data are also included. A copy of this database can be obtained from the authors by contacting them.     

Effect ofθ-alumina formation on the growth kinetics of alumina-forming superalloys

Alumina-forming ODS superalloys are excellent oxidation-resistant materials. Their resistance relies upon the establishment of a stable, slow-growing, and adherent -alumina. In the present investigation, these alloys exhibited unstable and relatively less adherent -alumina phase, which increased the oxidation rate in the transient stage and converted into -alumina in the later part of the exposure. The oxide-growth process was found to depend upon various parameters such as temperature, time, and presence of an active elecment in the superalloy. Characterization carried out by XRD, SEM/EDAX, and AES on oxidized ODS and non-ODS alloys demonstrated a significant influence of the active element, Y, on the transformation of - to -alumina. SIMS analysis of two-stage oxidation at 900°C for two different durations evidently showed that the change in the transport process is due to -to--alumina transformation. On the basis of these results, a new and consistent mechanism is proposed to explain the influence of -alumina and its transformation on growth kinetics and the effect of yttrium on the transformation leading to good scale adherence and oxidation resistance.     

The optimal control approach to generalized multiprocessor scheduling

In this paper we present several new results in the theory of homogeneous multiprocessor scheduling. We start with some assumptions about the behavior of tasks, with associated precedence constraints, as processor power is applied. We assume that as more processors are applied to a task, the time taken to compute it decreases, yielding some speedup. Because of communication, synchronization, and task scheduling overhead, this speedup increases less than linearly with the number of processors applied. We also assume that the number of processors which can be assigned to a task is a continuous variable, with a view to exploiting continuous mathematics. The optimal scheduling problem is to determine the number of processors assigned to each task, and task sequencing, to minimize the finishing time.These assumptions allow us to recast the optimal scheduling problem in a form which can be addressed by optimal control theory. Various theorems can be proven which characterize the optimal scheduling solution. Most importantly, for the special case where the speedup function of each task isp , wherep is the amount of processing power applied to the task, we can directly solve our equations for the optimal solution. In this case, for task graphs formed from parallel and series connections, the solution can be derived by inspection. The solution can also be shown to be shortest path from the initial to the final state, as measured by anl _1/ distance metric, subject to obstacle constraints imposed by the precedence constraints.This research has been funded in part by the Advanced Research Project Agency monitored by ONR under Grant No. N00014-89-J-1489, in part by Draper Laboratory, in part by DARPA Contract No. N00014-87-K-0825, and in part by NSF Grant No. MIP-9012773. The first author is now with AT&T Bell Laboratories and the second author is with BBN Incorporated.     

Subsegmental,segmental and suprasegmental processing of linear prediction residual for speaker information

This work processes linear prediction (LP) residual in the time domain at three different levels, extracts speaker information, and demonstrates their significance and also different nature for text-independent speaker recognition. The subsegmental analysis considers LP residual in blocks of 5 msec with shift of 2.5 msec to extract speaker information. The segmental analysis extracts speaker information by processing in blocks of 20 msec with shift of 2.5 msec. The suprasegmental speaker information is extracted by viewing in blocks of 250 msec with shift of 6.25 msec. The speaker identification and verification studies performed using NIST-99 and NIST-03 databases demonstrate that the segmental analysis provides best performance followed by subsegmental analysis. The suprasegmental analysis gives the least performance. However, the evidences from all the three levels of processing seem to be different and combine well to provide improved performance, demonstrating different speaker information captured at each level of processing. Finally, the combined evidence from all the three levels of processing together with vocal tract information further improves the speaker recognition performance.