Generation of square and triangular wave with independently controllable frequency and amplitude using OTAs only and its application in PWM

This paper presents a self-generating square/triangular wave generator using only the CMOS Operational Transconductance Amplifiers (OTAs) and a grounded capacitor. The output frequency and amplitude of the proposed circuit can be independently and electronically adjusted. The proposed circuit validates its advantage by consuming less amount of power, which is about 71.3 µW. The theoretical aspects are authentically showcased using the PSPICE simulation results. The performance of the proposed circuit is also verified through pre layout and post layout simulation results using the 90 nm GPDK CMOS parameters. A prototype of this circuit has been made using commercially available IC CA3080 for experimental verification. Experimentation also gives the similar output as per the theoretical proposition. The designed circuit is also made applicable to perform pulse width modulation (PWM).     

Atomic‐Scale CoOx Species in Metal–Organic Frameworks for Oxygen Evolution Reaction

The activity of electrocatalysts strongly depends on the number of active sites, which can be increased by downsizing electrocatalysts. Single‐atom catalysts have attracted special attention due to atomic‐scale active sites. However, it is a huge challenge to obtain atomic‐scale CoO_x catalysts. The Co‐based metal–organic frameworks (MOFs) own atomically dispersed Co ions, which motivates to design a possible pathway to partially on‐site transform these Co ions to active atomic‐scale CoO_x species, while reserving the highly porous features of MOFs. In this work, for the first time, the targeted on‐site formation of atomic‐scale CoO_x species is realized in ZIF‐67 by O₂ plasma. The abundant pores in ZIF‐67 provide channels for O₂ plasma to activate the Co ions in MOFs to on‐site produce atomic‐scale CoO_x species, which act as the active sites to catalyze the oxygen evolution reaction with an even better activity than RuO₂.     

A Study of the Parasitic Properties of the Schottky Barrier Diode

In this paper, we present a newly designed parameter extraction method of the Schottky barrier diode (SBD) with the purpose of measuring and studying its parasitic properties. This method includes three kinds of auxiliary configurations and is named as three-configuration parameter extraction method (TPEM). TPEM has such features as simplicity of operation, self-consistence, and accuracy. With TPEM, the accurate parasitic parameters of the diode can be easily obtained. Taking a GaAs SBD as an example, the pad-to-pad capacitance is 7 fF, the air-bridge finger self-inductance 11 pH, the air-bridge finger self-resistance 0.6 Ω, and the finger-to-pad capacitance 2.1 fF. A more accurate approach to finding the value of the series resistant of the SBD is also proposed, and then a complete SBD model is built. The evaluation of the modeling technology, as well as TPEM, is implemented by comparing the simulated and measured I-V curves and the S-parameters. And good agreements are observed. By using TPEM, the influence of the variation of the geometric parameters is studied, and several ways to reduce the parasitic effect are presented. The results show that the width of the air-bridge finger and the length of the channel are the two largest influencing parameters, with the normalized impact factors 0.56 and 0.29, respectively. By using TPEM and the modeling technology presented in this paper, a design process of the SBD is proposed. As an example, a type of SBD suitable for 500–600 GHz zero-biased detection is designed, and the agreement between the simulated and measured results has been improved. SBDs for other applications could be designed in a similar way.     

Insights on the Side Panels of the <Emphasis Type="Italic">Franciscan Triptych</Emphasis> by Fra Angelico Using Terahertz Time-Domain Imaging (THz-TDI)

The side panels of the Franciscan Triptych (St. Jerome, St. John the Baptist, and the Archangel Gabriel and St. Francis, St. Onofrio, and the Virgin Annunciate, by Fra Angelico, before 1429) were scanned by means of terahertz time-domain imaging (THz-TDI). THz analysis supplied information on the stratigraphy of the panel paintings and the associated construction, “gessoing” and gilding techniques. Furthermore, THz-TDI provided information regarding the location of restoration materials within the painting stratigraphy on St. Jerome, St. John the Baptist, and the Archangel Gabriel, as well as on the extension and nature of subsurface cracks in the panel painting of St. Francis, St. Onofrio, and the Virgin Annunciate.     

A Reliability-Aware Methodology to Isolate Timing-Critical Paths under Aging

Temporal unreliability due to aging, such as Negative-Bias Temperature Instability (NBTI) and Hot Carrier Injection (HCI) effects etc., in the CMOS circuits may not appear just after the chip production, instead it becomes apparent when it is used under certain workload and environmental conditions over time. Identifying aged paths that may become critical to circuit performance, is a real challenge for many researchers and reliability engineers. In this work, firstly we identify a set of parameters that impact the circuit performance under aging and use them in the proposed algorithm which is substantially faster than commercially available SPICE simulator with an approx 94% accuracy in estimating path delays. Secondly, we explore the possibility of using the proposed methodology, instead of using time expensive SPICE and pessimistic static timing analysis (STA), to identify a set of speed-limiting paths under aging. Experimental results demonstrate the effectiveness of the proposed algorithm and the associated methodology in comparison to SPICE simulated results.     

Machine learning based optimized live virtual machine migration over WAN links

Live virtual machine migration is one of the most promising features of data center virtualization technology. Numerous strategies have been proposed for live migration of virtual machines on local area networks. These strategies work perfectly in their respective domains with negligible downtime. However, these techniques are not suitable to handle live migration over wide area networks and results in significant downtime. In this paper we have proposed a Machine Learning based Downtime Optimization (MLDO) approach which is an adaptive live migration approach based on predictive mechanisms that reduces downtime during live migration over wide area networks for standard workloads. The main contribution of our work is to employ machine learning methods to reduce downtime. Machine learning methods are also used to introduce automated learning into the predictive model and adaptive threshold levels. We compare our proposed approach with existing strategies in terms of downtime observed during the migration process and have observed improvements in downtime of up to 15 %.     

Centralized dynamic frequency allocation for cell-edge demand satisfaction in fractional frequency reuse networks

Fractional frequency reuse (FFR) has emerged as a well-suited remedy for inter-cell interference reduction in the next-generation networks by allocating frequency reuse factor (FRF) of unity for the cell-center (CC) and higher FRF for the cell-edge (CE) users. However, this strict FFR comes at a cost of equal partitioning of frequency resources to the CE which most likely has varying demands in current networks. In order to mitigate this, we propose a centralized dynamic resource allocation scheme which allocates demand-dependent resources to CE users. The proposed scheme therefore outperforms the fixed allocation scheme of strict FFR for both CC and CE users. Complexity analysis provides a fair means of analyzing the suitability of proposed algorithm. We have also compared the proposed methodology with a reference dynamic fractional frequency reuse (DFFR) scheme. Results show maximum performance gain of up to 30% for 3 reference cells employing Rayleigh fading—through normalized area spectral efficiency (ASE) analysis for both fixed allocation and DFFR. Spectral efficiency analysis also indicates per-cell performance gain for both CC and CE users. Further, detailed three-dimensional ASE plots give insights into the affects to other cells. Due to dynamic nature of traffic loads, the proposed scheme is a candidate solution for satisfying the demands of individual cells.     

Fair QoS multi-resource allocation for uplink traffic in WLAN

In wireless local area network (WLAN), improving the quality of service (QoS) of users is often at odd with striking fairness among users. In this work, we suggest that in WLAN, multiple types of network resources should be jointly allocated to users to achieve “QoS fairness”, which is a new fairness concept targeting at balancing QoS and fairness in WLAN by allocating multiple types of network resources to users. To this end, we first transform user QoS requirements to multi-resource demands and apply the dominant resource fairness scheme to allocate network resources for each user. We prove several salient QoS-based fairness properties based on a model mapping between QoS and resources. We further discuss about more general conditions for diverse mapping models where QoS fairness properties can be satisfied. We find that the QoS fairness properties can be guaranteed as long as the mapping model meets a few practical requirements, indicating the wide applicability of our scheme. To consolidate our multi-resource allocation scheme, we design a practical protocol for WLAN. The simulation results validate that the QoS fairness can be guaranteed in practical WLAN scenario.     

Path Loss Models for Low-Height Mobiles in Forest and Urban

This paper presents path loss measurements at 2.1 GHz in forest and urban areas. Empirical path loss models have been presented for low-height dual-mobility channels. Three test scenarios are considered for the transmitter (Tx) and receiver (Rx) placed inside the test vehicle or on a test cart pushed at walking speed. Based on measurements, the in-leaf and single-slope path loss models are presented. The path loss exponents for the dual-mobility channels are found to be between 2.1 and 3.4 in urban and 8.0 in forest, with higher reference when antennas are placed inside the vehicle.     

Network Coding Based Converge-Cast Scheme in Wireless Sensor Networks

The converge-cast in wireless sensor networks (WSNs) is widely applied in many fields such as medical applications and the environmental monitoring. WSNs expect not only providing routing with high throughput but also achieving efficient energy saving. Network coding is one of the most promising techniques to reduce the energy consumption. By maximizing the encoding number, the message capacity per package can be extended to the most efficient condition. Thus, many researchers have focused their work on this field. Nevertheless, the packages sent by the outer nodes need to be temporary stored and delayed in order to maximize the encoding number. To find out the balance between inserting the delay time and maximizing the encoding number, a Converge-cast Scheme based on data collection rate prediction (CSRP) is proposed in this paper. To avoid producing the outdated information, a prediction method based on Modifying Index Curve Model is presented to deal with the dynamic data collection rate of every sensor in WSNs. Furthermore, a novel coding conditions based on CDS is proposed to increase the coding opportunity and to solve the collision problems. The corresponding analysis and experimental results indicate that the feasibility and efficiency of the CSRP is better than normal conditions without the prediction.