Simple Shift Research Articles

Improving speaker de-identification with functional data analysis of f0 trajectories

Due to a constantly increasing amount of speech data that is stored in different types of databases, voice privacy has become a major concern. To respond to such concern, speech researchers have developed various methods for speaker de-identification. The state-of-the-art solutions utilize deep learning solutions which can be effective but might be unavailable or impractical to apply for, for example, under-resourced languages. Formant modification is a simpler, yet effective method for speaker de-identification which requires no training data. Still, remaining intonational patterns in formant-anonymized speech may contain speaker-dependent cues. This study introduces a novel speaker de-identification method, which, in addition to simple formant shifts, manipulates f0 trajectories based on functional data analysis. The proposed speaker de-identification method will conceal plausibly identifying pitch characteristics in a phonetically controllable manner and improve formant-based speaker de-identification up to 25%.

Dynamic RF Combining for Multi-Antenna Ambient Energy Harvesting

Ambient radio frequency (RF) energy harvesting (EH) technology is key to realize self-sustainable, always-on, low-power, massive Internet of Things networks. Typically, rigid (non-adaptable to channel fluctuations) multi-antenna receive architectures are proposed to support reliable EH operation. Herein, we introduce a dynamic RF combining architecture for ambient RF EH use cases, and exemplify the attainable performance gains via three simple phase shifts’ exploration mechanisms, namely, brute force (BF), sequential testing (ST) and codebook based (CB). Among the proposed mechanisms, BF demands the highest power consumption, while CB requires the highest-resolution phase shifters, thus tipping the scales in favor of ST. Finally, we show that the performance gains of ST over a rigid RF combining scheme increase with the number of receive antennas and energy transmitters’ deployment density.

A commentary of “The brain evolutionary mechanism of feeding preference”: 10 remarkable discoveries from 2020 in Nature

The fly Drosophila sechellia feeds exclusively on the toxic noni fruit (Morinda citrifolia). What makes this species such a picky eater compared with its generalist relatives? Auer et al. cracked the case using the genome-editing tool CRISPR/Cas9 [1]. One sensory neuron class expressing the odorant receptor 22a (Or22a) protein is more abundant in D. sechellia than in other fly species. The group established that small changes in Or22a's amino-acid sequence have contributed to D. sechellia’s preference for noni. They also identified several other evolutionary changes that might contribute to this apparently simple behavioral shift. Even tiny flies that love stinky fruit can provide powerful insight into how brains evolve to shape complex behaviors.①①Original source in Chinese: Yufeng Pan, The brain evolutionary mechanism of feeding preference, Bulletin of National Natural Science Foundation of China. 35 (2) (2021) 242–243.

Ground-roll extraction using the Karhunen-Loeve transform in the time-frequency domain

Ground-roll suppression is critical for seismic reflection data processing. Many standard methods, i.e., f-k fan filtering, fail when spatially aliased surface wave interference is present in the data. Spatial aliasing is a common problem; receiver spacing is often not dense enough to extract wavenumbers of low-velocity surface waves. It has long been known that the Karhunen-Loeve (KL) transform can be used to suppress aliased ground roll. However, the ground roll should be flattened before suppression, which is challenging due to the dispersion of surface wave velocities. I propose to solve this problem via the time-frequency domain. I apply the S-transform, which was previously shown to perform well in the multichannel analysis of surface waves. A simple complex-valued constant phase shift is a suitable model of surface wave propagation in common-frequency S-transform gathers. Therefore, it is easy to flatten the corresponding S-transform narrow-band frequency surface wave packet and extract it from the data by principal component analysis of the corresponding complex-valued data-covariance matrix. As the result, our S-transform KL (SKL) method filters the aliased ground roll without damaging the reflection amplitudes. The advantages of SKL filtering have been confirmed by synthetic- and field-data processing.

Band-to-Band Registration of FY-1C/D Visible-IR Scanning Radiometer High-Resolution Picture Transmission Data

The visible-IR scanning radiometer (VIRR) of FY1-C/D meteorological satellites consists of 10 bands with 4 different focal plane assemblies (FPAs). However, there are significant band-to-band registration (BBR) errors between different bands, which cannot be compensated for by a simple shift in the along-scan direction. A rigorous BBR frame was proposed to analyze the sources of misregistration in the whisk-broom camera. According to theory, the 45° scanning mirror introduces tangent function style misregistration in the along-track direction and secant function style misregistration in the across-track direction between different bands if the bands are not in the same optical axis. As proven by the experiments of both FY-1C and FY-1D, the image rotation caused by the 45° scanning mirrors plays a major role in the misregistration. However, misregistration between different FPAs does not strictly adhere to this theory. Therefore, a polynomial-based co-registration method was proposed to model the BBR errors for the VIRR. To achieve 0.1 pixel accuracy, a fourth-degree polynomial was used for BBR in the along-scan direction, and a fifth-degree polynomial was used for the along-track direction. For the reflective bands, the root-mean-square errors (RMSEs) of misregistration could be improved from 3 pixels to 0.11 pixels. Limited by matching accuracy, the RMSEs of misregistration between thermal bands and reflective bands were approximately 0.2 to 0.4 pixels, depending on the signal-to-noise ratio.

FPGA Implementation of Elliptic-Curve Diffie Hellman Protocol

This paper presents an efficient crypto processor architecture for key agreement using ECDH (Elliptic-curve Diffie Hellman) protocol over . The composition of our key-agreement architecture is expressed in consisting of the following: (i) Elliptic-curve Point Multiplication architecture for public key generation (DESIGN-I) and (ii) integration of DESIGN-I with two additional routing multiplexers and a controller for shared key generation (DESIGN-II). The arithmetic operators used in DESIGN-I and DESIGN-II contain an adder, squarer, a multiplier and inversion. A simple shift and add multiplication method is employed to retain lower hardware resources. Moreover, an essential inversion operation is operated using the Itoh-Tsujii algorithm with similar hardware resources of used squarer and multiplier units. The proposed architecture is implemented in a Verilog HDL. The implementation results are given on a Xilinx Virtex-7 FPGA (field-programmable gate array) device. For DESIGN-I and DESIGN-II over , (i) the utilized Slices are 3983 and 4037, (ii) the time to compute one public key and a shared secret is 553.7 μs and 1170.7 μs and (iii) the consumed power is 29 μW and 57 μW. Consequently, the achieved area optimized and power reduced results show that the proposed ECDH architecture is a suitable alternative (to generate a shared secret) for the applications that require low hardware resources and power consumption.

Simple Doppler Frequency Shift Measurement Scheme Based on Microwave Photonics

Based on the theory of microwave photonics, we propose a new scheme to measure the Doppler frequency shift (DFS) in a radar system. This scheme is a single-channel system based on dual-parallel Mach–Zehnder modulator (DPMZM). And the frequencies of the transmitted signal and the reference signal are added together to form a combined signal. Then we add the combined signal and the echo signal to the two sub-modulators (sub-MZMs) of DPMZM, respectively. By measuring the beat signal output by the photoelectric modulator (PD), the DFS can be measured, whose error is maintained at −0.8Hz to 0.8Hz. The DFS’s direction is determined by comparing the frequencies of the obtained signal and the reference signal. The system has the advantages of wide operating frequency range, simple structure, low cost, and easy integration.

A Folding Approach for Multiple Antenna Arrays Using Low-Resolution ADCs

Both massive multiple-input multiple-output (MIMO) and millimeter wave (mmWave) systems are receiving much attention for 5G and beyond-5G wireless access. When using a large antenna array, there are numerous challenges in designing low-power and cost-effective hardware. Most notably, the traditional approach of using high-resolution analog-to-digital converters (ADCs) at each element leads to both costly and high-power consumption devices. This has motivated research on multiple antenna arrays that use a low-resolution ADC at each element. We present a new framework for designing a multiple antenna array using a low-resolution ADC at each element, with the low-resolution ADC composed of simple shift and modulo analog processing and a sign quantizer. This modulo technique, called folding, has previously been utilized in the design of high-speed high-resolution ADCs. Using theory from folded ADCs, we show how to jointly design the modulo processing used across the elements. We show that our framework can provide substantial rate improvements including providing a linear growth in rate with the number of antennas at high SNR, as opposed to the logarithmic growth with the number of antennas provided by a sign-based low-resolution ADC array. We also explore how antenna ordering strategies can be used. We utilize Monte Carlo simulations to back our analysis.

Alkali-metal induced electronic structure evolution in Sn4Sb3 studied by angle-resolved photoemission spectroscopy

We report on an angle-resolved photoemission spectroscopy study of the effect of in-situ cesium (Cs) dosing on the surface electronic structure of Sn4Sb3, a newly emerging candidate of topological semimetallic superconductor. As the chemical potential of the system increases upon Cs dosing, we observed an electronic structure evolution that features an increasing sharpness of band features as well as a momentum- and band-dependent energy shift of the bands at low binding energies. These observations go beyond a simple rigid band shift model and are manifestations of quantum confinement of electronic states near the surface due to Cs decoration. By studying the evolution of Cs 5p core level as functions of Cs dosage and photoelectron emission angle, we found Cs atoms deposit on the sample surface at low dosages and tend to intercalate underneath the surface at high dosages. This process is accompanied by a gradual suppression of a surface band splitting, an observation that can be captured by simplified first-principles calculations in both cases with the deposition/intercalation occurring on top of/underneath the first Sn–Sb bilayer. Our finding highlights an intriguing possibility of an unexpected dimensionality reduction in Sn4Sb3 caused by Cs intercalation at interstitial sites that promises its novel surface properties different from the bulk.

A predator-prey system with generalized Holling type IV functional response and Allee effects in prey

The transition between strong and weak Allee effects in prey provides a simple regime shift in ecology. In this paper, we study the interplay between the functional response of Holling type IV and both strong and weak Allee effects. The model investigated here presents complex dynamics and high codimension bifurcations. In particular, nilpotent cusp singularity of order 3 and degenerate Hopf bifurcation of codimension 3 are completely analyzed. Remarkably it is the first time that three limit cycles are discovered in predator-prey models with multiplicative Allee effects. Moreover, a new unfolding of nilpotent saddle of codimension 3 with a fixed invariant line is discovered and fully developed, and the existence of codimension 2 heteroclinic bifurcation is proven. Our work extends the existing results of predator-prey systems with Allee effects. The bifurcation analysis and diagram allow us to give biological interpretations of predator-prey interactions.

All-Optical Pulsed Signal Doppler Frequency Shift Measurement System

A simple and all-optical Doppler frequency shift (DFS) measurement system is presented. It is based on a dual-drive Mach Zehnder modulator (DDMZM) driven by a transmitted signal and an echo signal received by an antenna. A low-frequency sawtooth wave is applied to the DDMZM DC port to frequency shift the carrier and sidebands generated by the transmitted signal. Beating of a frequency-shifted transmitted signal sideband and an echo signal sideband at the photodetector produces a low-frequency electrical signal. The DFS, and consequently the speed and moving direction of a target, can be obtained from the frequency of this low-frequency electrical signal. The DDMZM used in the proposed DFS measurement system does not need to be operated at a specific point in the transfer function and hence it has no bias drift problem. The proposed DFS measurement technique can be used in both CW and pulsed radar systems. Experimental results demonstrate the proposed DFS measurement system has a wide operating frequency range of 10 GHz to 19.95 GHz, small DFS measurement error of less than ±0.6 Hz and long-term stable performance. Results also demonstrate, for the first time, DFS measurement of a pulsed signal using a microwave photonic technique.

High-Efficiency Single-Stage On-Board Charger for Electrical Vehicles

This paper presents an isolated single-stage on-board electric vehicle charger without an intermediate DC-link. Based on an isolated current-source topology, the converter features soft-switching in semiconductors regardless of load variation for the full AC line voltage range. Moreover, it requires no external snubber or clamp circuits. The power factor correction and voltage regulation are provided by a relatively simple phase shift modulation, while the amount of circulating energy is kept at minimum. The charger is distinguished by its efficiency characteristic – the maximum is achieved in the constant power charging mode. The control method, component stresses, and design constraints of the topology are analyzed. The concept is verified using a 3 kW experimental SiC-based prototype, which reaches a peak efficiency of 96.4%. Moreover, the charger has demonstrated efficiencies above 95% with the THD of 4.1% when operating in constant power mode at the maximal power.

The ‘Perfect’ Conversion: Dramatic Increase in CO2 Efflux from Shellfish Ponds and Mangrove Conversion in China

Aquaculture, particularly shellfish ponds, has expanded dramatically and become a major cause of mangrove deforestation and “blue carbon” loss in China. We present the first study to examine CO2 efflux from marine aquaculture/shellfish ponds and in relation to land-use change from mangrove forests in China. Light and dark sediment CO2 efflux from shellfish ponds averaged at 0.61 ± 0.07 and 0.90 ± 0.12 kg CO2 m−2 yr−1 (= 37.67 ± 4.89 and 56.0 ± 6.13 mmol m−2 d−1), respectively. The corresponding rates (−4.21 ± 4.54 and 41.01 ± 4.15 mmol m−2 d−1) from the adjacent mangrove forests that were devoid of aquaculture wastewater were lower, while those from the adjacent mangrove forests (3.48 ± 7.83 and 73.02 ± 5.76 mmol m−2 d−1)) receiving aquaculture wastewater markedly increased. These effluxes are significantly higher than those reported for mangrove forests to date, which is attributable to the high nutrient levels and the physical disturbance of the substrate associated with the aquaculture operation. A rise of 1 °C in the sediment temperature resulted in a 6.56% rise in CO2 released from the shellfish ponds. Combined with pond area data, the total CO2 released from shellfish ponds in 2019 was estimated to be ~12 times that in 1983. The total annual CO2 emission from shellfish ponds associated with mangrove conversion reached 2–5 Tg, offsetting the C storage by mangrove forests in China. These are significant environmental consequences rather than just a simple shift of land use. Around 30% higher CO2 emissions are expected from aquaculture ponds (including shellfish ponds) compared to shellfish ponds alone. Total annual CO2 emission from shellfish ponds will likely decrease to the level reported in early 1980 under the pond area-shrinking scenario, but it will be more than doubled under the business-as-usual scenario projected for 2050. This study highlights the necessity of curbing the expansion of aquaculture ponds in valuable coastal wetlands and increasing mangrove restoration to abandoned ponds.

A new parallel processing architecture for accelerating image encryption based on chaos

This study introduces a novel parallel processing architecture for accelerating image encryption based on chaos. In the proposed architecture, whole image data is split into partitions of particular size to create separate encryption threads. As the proposed cryptosystem employs several identical chaotic ciphers running concurrently and independently to process the partitions, it greatly leverages the degree of parallelism to some extent. A powerful output mixing logic based on an additional chaotic function, and simple exclusive-OR and shift operations is innovatively incorporated to ensure inter-partition diffusion. Since there is no dependency on previous data bytes in the introduced logic, blending operations applied on the outputs of independent encryption threads can be concurrently executed by exploiting loop-level parallelism to the extent allowed by data processing units available. The number of blending operations that should be carried out for an image is kept proportional to the partition size which also directly determines the number of separate encryption threads created. In order to measure encryption/decryption runtimes, the proposed architecture has been tested on two different multi-core CPUs, namely 4-core and 8-core. The obtained results show that the proposed cryptosystem parallelising sequential operations by introducing a multi-threaded encryption architecture is much faster than the base cipher and most of the other state-of-the-art algorithms. Having successfully passed various security tests, the proposed cryptosystem manifests its robustness against cryptographic attacks, and hence become evident that it is efficient for secure transmission.

Crystal lattice image reconstruction from Moiré sampling scanning transmission electron microscopy

A wide range of reconstruction methods exist nowadays to retrieve data from their undersampled acquisition schemes. In the context of Scanning Transmission Electron Microscopy (STEM), compressed sensing methods successfully demonstrated the ability to retrieve crystalline lattice images from undersampled electron micrographs. In this manuscript, an alternative method is proposed based on the principles of Moiré sampling by intentionally generating aliasing artifacts and correcting them afterwards. The interference between the scanning grid of the electron beam raster and the crystalline lattice results in the formation of predictable sets of Moiré fringes (STEM Moiré hologram). Since the aliasing artifacts are simple spatial frequency shifts applied on each crystalline reflection, the crystal lattices can be recovered from the STEM Moiré hologram by reverting the aliasing frequency shifts from the Moiré reflections. Two methods are presented to determine the aliasing shifts for all the resolved crystalline reflections. The first approach is a prior knowledge-based method using information on the spatial frequency distribution of the crystal lattices (a common case in practice). The other option is a multiple sampling approach using different sampling parameters and does not require any prior knowledge. As an example, the Moiré sampling recovery method detailed in this manuscript is applied to retrieve the crystalline lattices from a STEM Moiré hologram recorded on a silicon sample. The great interest of STEM Moiré interferometry is to increase the field of view (FOV) of the electron micrograph (up to several microns). The Moiré sampling recovery method extends the application of the STEM imaging of crystalline materials towards low magnifications.

Criterion for the occurrence of the macro destruction and formation of breaking during metal deformation

When generalizing the geometrically nonlinear law of Murnaghan elasticity to plasticity, a formally mathematical criterion was introduced for deformational macrofracture (macrocrack appearance) associated with an increase in elastic and plastic anisotropy as a failure cause. The use of the double potentiality of the governing equations in stresses and their velocities made it possible to obtain the reliable information on the structure of the deviatory section of the yield surface, the existence of which is a classical hypothesis in solid mechanics. The normal vector to the surface of the deviatory section is selected from two mutually orthogonal eigenvectors of the constructed operator. There are two families of regular concave surfaces, and a section surface is formed by joining the parts of two representatives of the families at singular points. To select normal vectors, the obtained ratio for them is used for isotropy. In connection with the considered problem of a double simple shift, it is established that multiple eigenvalues appear for the both normal vectors. To unambiguously determine the normal vector at a regular point, it is necessary to exclude the presence of multiple eigenvalues for the both normal vectors at the same time. At a singular point, the appearance of a multiple eigenvalue of one of the normal vectors is still unacceptable. These two conditions are necessary and sufficient to validate the governing equations of the generalized Murnaghan model. Otherwise, a macrocrack occurs. The theoretical construction is supported by the developed software complexes.

Millennial and gen Z perspective towards eco-office campaign implementation in public sector

This study explains millennial and Gen-Z attitudes, perspectives, and behaviors in implementing the eco-office concept. As a qualitative method study, the study uses primary data through semi-structured interviews and secondary data collected from reports, public/private publications, and census results, using the Yin case study model as data analysis. The study results reveal that the biggest challenge in implementing new policies is self-thinking. Leaders, as change agents, play an essential role in penetrating messages that make them act pro-environment. The reward system will be very effective, especially providing satisfaction for self-actualization. The findings of this study have implications for policymakers as input. For example, the results show that social media plays a crucial role in increasing environmental awareness. In addition, simple shifts such as electronic media use at work will cut the file chain, making it more effective and favored by young people. They understand the consequences of their actions on the environment and have the education, motivation, and social awareness to participate in the green movement. However, beliefs and actions are not fully integrated, and investigating and understanding their behavior and unique needs in the workplace will lead employees to integrate and succeed together to support the environment.

Energy-Efficient Logarithmic Square Rooter for Error-Resilient Applications

Approximate computing is an emerging computing technique for designing energy- and resource-efficient arithmetic circuits for error-resilient applications. Square root (SQR) computation is a fundamental and complex operation in various signal/image processing tasks. It demands high resource and energy consumption, making the square-rooter a crucial design element. This brief proposes a low-complexity logarithmic-based energy-efficient approximate square rooter (LESQ) for computing integer SQR using simple addition and shift operations. A partial error compensation scheme is also suggested for improved accuracy. The proposed approximate square rooter also enables various accuracy configurable modes to tradeoff error with hardware efficiency for targeted application requirements. LESQ achieves energy- and area-delay savings of up to 80% and 60%, respectively, compared to an accurate array-based square-rooter design. The proposed approximate design is tested on error-tolerant applications, such as image processing and amplitude modulation (AM) communication system.

Leadership election reform in the British Labour party: democratisation or power struggle?

This article examines the impact of reforms on the outcome of Labour party leadership contests since the premiership of Tony Blair. From a theoretical perspective, these reforms are characterised by a tension between a general trend towards increasing “democratisation” of political parties and the power interests of intra-party actors. While there have been significant changes to both the nomination stage and the final ballot, the impact of these changes has to be strongly qualified. Instead of a major “democratisation” through targeted and deliberate reform measures, simple shifts in the power structure between strategic actors are more prominent among reform effects. Meanwhile, the trend towards “democratisation” in relation to the final ballot stage was largely driven by the massive membership surge since 2015, as well as low-key reform measures unconnected to handing ordinary party members more influence over the election process.

Ensemble learning for large-scale crowd flow prediction

The Kumbh Mela festival is the largest mass gathering in the world that is celebrated every three years. In 2016, it attracted over 70 million people to Ujjain, India. The Mahakal temple is the “heart” of the festival that attracts a huge number of pilgrims and needs to accommodate with massive crowds. These types of events pose significant safety challenges as large-scale mass gatherings are often associated with risks such as crowd crushes. There have been a number of serious incidents documented in recent history such as the Hajj crush at Mina, Mecca, Saudi Arabia (2006 and 2015), the Lame Horse crush during a fire at Perm, Russia (2009), the Love Parade disaster at Duisburg, Germany (2010), and the Kumbh Mela stampede at Allahabad, Uttar Pradesh, India (2013) to name a few. Safety assurance at events of such tremendous size is closely connected with crowd control and understanding the general behaviour of the crowd. One of the basic challenges in understanding crowd dynamics is being able to predict crowd flows at a particular location based on past/present flows from another location. There are several existing methods and models used to predict and manage crowd flow. In this paper, we introduce a novel method for short-term crowd flow prediction and show that it decreases the prediction error by 13% as compared to existing methods. The model is based on ensemble learning where we demonstrate that a combination of complementary methods with different a-priory assumptions can create better estimations. Utilizing a unique data set derived from CCTV camera recordings of pilgrims that we collected during the Kumbh Mela 2016 festival, we tested different methods from artificial intelligence and computational modelling, such as simple shift of time-series (time-shift), agent-based modelling, machine learning methods, and show how combinations of these different methods as an ensemble provide synergy to obtain better predictions. Our results demonstrate that agent-based modelling, when combined with other models, provides better predictive power especially in complex scenarios. These results point to something fundamental about the information contained within and generated by these methods. We anticipate that our research could be a starting point for further research of informational synergetic aspects of models and predictors.