Operational Sustainability and Digital Leadership for Cybercrime Prevention

The digital world of work and social media, despite its challenges, is here to stay as an integrated part of our day-to-day operational norms. Therefore, we must make the best of it on a proactive basis before the private data of our employees and consumers becomes hacked remotely by criminals. Privacy violations and hacking of data cannot be sustained since they can be very costly and may even lead to bankruptcy. As such, today’s leaders, managers, and educators have the responsibility of preparing their future replacements for the modern digital economy, so their organizations’ operational processes can remain competitive, safe, and sustainable. Operational sustainability, in this paper, is proposed as a tripod or “three-legged stool” of environmental, social, and digital responsibility. With more employees and entrepreneurs accessing digital data remotely through vulnerable or unsecure online platforms, the opportunities for cybercrimes rise. Therefore, this article focuses more on the often-neglected digitalization element of operational sustainability. All leaders must be aware of the legal, social, and environmental expectations of a digital society by doing what is good for the world while also being efficient and safe from cybercriminals. The paper proposes that future leaders must be socialized with a sustainability mindset about data privacy and safety measures that are necessary for this fast-changing digital economy where hackers and artificial intelligence (AI) tools can make the process more challenging. With AI being used by some actors to generate false yet realistic content, companies will have to do more to make sure their brands are not defamed or tarnished. As such, this conceptual article discusses a model for operational sustainability, which includes the privacy and safety of data that can be used by managers, educators and other leaders for training and development purposes in today’s digital world of work.

AN ITERATIVE ALGORITHM FOR OPTIMAL DESIGN OF NON-FREQUENCY-SELECTIVE FIR DIGITAL FILTERS

This paper proposes a novel iterative algorithm for optimal design of non-frequency-selective Finite Impulse Response(FIR) digital filters based on the windowing method.Different from the traditional optimization concept of adjusting the window or the filter order in the windowing design of an FIR digital filter,the key idea of the algorithm is minimizing the approximation error by succes-sively modifying the design result through an iterative procedure under the condition of a fixed window length.In the iterative procedure,the known deviation of the designed frequency response in each iteration from the ideal frequency response is used as a reference for the next iteration.Because the approximation error can be specified variably,the algorithm is applicable for the design of FIR digital filters with different technical requirements in the frequency domain.A design example is employed to illustrate the efficiency of the algorithm.

Digital FIR filter design for bio-signal processing system

Recently,real-time processing systems for bio-signal of the muscles generated by the movement of the user have been developed.Finite impulse response(FIR)filter for bio-signal processing in bio-signal process systems is composed of multiple multiplier and adder of high-area.This makes the chip area increase significantly.To solve this problem,a low-area digital FIR filter is proposed in this paper,which can reduce the chip area.

Preliminary Analysis of the Relationship between the Magnitude Deviation of the Station and Site Response in the Fujian Digital Seismic Network

Using the records of 3,069 regional earthquake events from the Fujian Digital Seismic Network from October 2008 to December 2015,in which the magnitude of each of the events was measured by at least six stations,statistics are taken on the deviation between the magnitude of a single station and the average magnitude of the network. It is found that the magnitudes average deviation of each station is-0. 31-0. 68. Statistics are also taken for the period corresponding to the maximum amplitude of the record measured in each station for calculating the magnitude,and the dominant period gained is 0. 06s-0. 38s; site response of each seismic station is inverted using the Moya method,and it is found that the site response of 98 stations is in the bands of 1-20 Hz,suggesting that the site has an amplifying or suppressing effect on the signals in certain frequency bands;Considering the site response corresponding to the inherent 0. 8s period of the WoodAnderson pendulum seismograph,and comparing the magnitude deviation caused by the site response corresponding to the dominant period time of each station with the average magnitude deviation, we obtain that there is a good linear relationship between the magnitude deviation from the dominant period site response and the average deviation of the magnitude of each station,indicating that the magnitude deviation of a single station has a close relationship with the site response of the period corresponding to the maximum amplitude measured for calculating the magnitude.

Four optimal design approaches of high-order finite-impulse response filters based on neural network

Four optimal approaches of high-order finite-impulse response(FIR) digital filters were developed for designing four types filters using neural network algorithms. The solutions were presented as parallel algorithms to approximate the desired frequency response specification. Therefore, these methods avoid matrix inversion, and make a fast calculation of the filter’s coefficients possible. The convergence theorems of these proposed algorithms were presented and proved to illustrate them stable, and the implementation of these methods was described together with some design guidelines. The simulation results show that the ripples of the designed FIR filters are significantly little in the pass-band and stop-band, and the proposed algorithms are of fast convergence.

The Co-seismic Response of Underground Fluid in Yunnan to the Nepal MS8.1 Earthquake

In this paper,statistics are taken on the co-seismic response of underground fluid in Yunnan to the Nepal M_S8. 1 earthquake,and the co-seismic response characteristics of the water level and water temperature are analyzed and summarized with the digital data. The results show that the Nepal M_S8. 1 earthquake had greater impact on the Yunnan region,and the macro and micro dynamics of fluids showed significant co-seismic response. The earthquake recording capacity of water level and temperature measurement is significantly higher than that of water radon and water quality to this large earthquake; the maximum amplitude and duration of co-seismic response of water level and water temperature vary greatly in different wells. The changing forms are dominated by fluctuation and step rise in water level,and a rising or falling restoration in water temperature. From the records of the main shock and the maximum strong aftershock,we can see that the greater magnitude of earthquake,the higher ratio of the occurrence of co-seismic response,and in the same well,the larger the response amplitude,as well as the longer the duration. The amplitude and duration of co-seismic response recorded by different instruments in a same well are different. Water temperature co-seismic response almost occurred in wells with water level response,indicating that the well water level and water temperature are closely related in co-seismic response,and the well water temperature seismic response was caused mainly by well water level seismic response.

Digital imaging approaches for phenotyping whole plant nitrogen and phosphorus response in Brachypodium distachyon

This work evaluates the phenotypic response of the model grass （Brachypodium distacbyon （L.） P. Beauv.） to nitrogen and phosphorus nutrition using a combination of imaging techniques and destructive harvest of shoots and roots. Reference line Bd21-3 was grown in pots using 11 phosphorus and 11 nitrogen concentrations to establish a dose-response curve. Shoot biovolume and biomass, root length and biomass, and tissue phosphorus and nitrogen concentrations increased with nutrient concentration. Shoot biovolume, estimated by imaging, was highly correlated with dry weight （R2 〉 0.92） and both biovolume and growth rate responded strongly to nutrient availability. Higher nutrient supply increased nodal root length more than other root types. Photochemical efficiency was strongly reduced by low phosphorus concentrations as early as 1 week after germination, suggesting that this measurement may be suitable for high throughput screening of phosphorus response. In contrast, nitrogen concentration had little effect on photochemical efficiency. Changes in biovolume over time were used to compare growth rates of four accessions in response tonitrogen and phosphorus supply. We demonstrate that a time series image-based approach coupled with mathematical modeling provides higher resolution of genotypic response to nutrient supply than traditional destructive techniques and shows promise for high throughput screening and determina- tion of genomic regions associated with superior nutrient use efficiency.

An iterative re-weighted least-squares algorithm for the design of active absorbing wavemaker controller

In physical model tests for highly reflective structures, one often encounters a problem of multiple reflections between the reflective structures and the wavemaker. Absorbing wavemakers can cancel the re-reflective waves by adjusting the paddle motion. In this paper, we propose a method to design the controller of the 2-D absorbing wavemaker system in the wave flume. Based on the first-order wavemaker theory, a frequency domain absorption transfer function is derived. Its time realization can be obtained by de- signing an infinite impulse response （IIR） digital filter, which is expected to approximate the absorption transfer function in the least- squares sense. A commonly used approach to determine the parameters of the IIR filter is applying the Taylor expansion to linearize the filter formulation and solving the linear least-squares problem. However, the result is not optimal because the linearization cha- nges the original objective function. To improve the approximation performance, we propose an iterative reweighted least-squares （IRLS） algorithm and demonstrate that with the filters designed by this algorithm, the approximation errors can be reduced. Physical experiments are carried out with the designed controller. The results show that the system performs well for both regular and irregu- lar waves.