Crop diversification strategies for minor irrigation schemes: Proceedings of the workshop organized by the Irrigation Research Management Unit, Irrigation Department and the Sri Lanka National Program, International Irrigation Management Institute, held at the Irrigation Department, Colombo, Sri Lanka on 20 February 1996

Irrigation programs / Irrigation management / Small scale systems / Crops / Diversification / Rice / Cropping systems / Constraints / Social aspects / Economic aspects / Field crops / Crop production / Labor / Farmers' attitudes / Water management / Groundwater / Sri Lanka

Identifying Users with Wearable Sensors based on Activity Patterns

We live in a world where ubiquitous systems surround us in the form of automated homes, smart appliances and wearable devices. These ubiquitous systems not only enhance productivity but can also provide assistance given a variety of different scenarios. However, these systems are vulnerable to the risk of unauthorized access, hence the ability to authenticate the end-user seamlessly and securely is important. This paper presents an approach for user identification given the physical activity patterns captured using on-body wearable sensors, such as accelerometer, gyroscope, and magnetometer. Three machine learning classifiers have been used to discover the activity patterns of users given the data captured from wearable sensors. The recognition results prove that the proposed scheme can effectively recognize a user’s identity based on his/her daily living physical activity patterns

Oscillator strength measurements of the 5s6s 1S0→5snp 1P1 Rydberg transitions of strontium

We report the experimentally determined oscillator strengths for the 5s6s 1S0→5snp 1P1 Rydberg transitions of strontium using two-step excitation in conjunction with a thermionic diode ion detector. The absolute photoionization cross section from the 5s6s 1S0 excited state has been determined by adjusting the polarization vector of the ionizing laser beam parallel, perpendicular, and at the magic angle with respect to that of the exciting dye laser. The measured absolute value of the photoionization cross section 0.9±0.2 Mb at the 5s threshold is used to extract the f values of the 5s6s 1S0→5snp 1P1 (26≤n≤73) Rydberg transitions. The oscillator strength in the discrete region merges smoothly to the oscillator strength density at the ionization threshold

Detecting fake news and disinformation using artificial intelligence and machine learning to avoid supply chain disruptions

Fake news and disinformation (FNaD) are increasingly being circulated through various online and social networking platforms, causing widespread disruptions and influencing decision-making perceptions. Despite the growing importance of detecting fake news in politics, relatively limited research efforts have been made to develop artificial intelligence (AI) and machine learning (ML) oriented FNaD detection models suited to minimize supply chain disruptions (SCDs). Using a combination of AI and ML, and case studies based on data collected from Indonesia, Malaysia, and Pakistan, we developed a FNaD detection model aimed at preventing SCDs. This model based on multiple data sources has shown evidence of its effectiveness in managerial decision-making. Our study further contributes to the supply chain and AI-ML literature, provides practical insights, and points to future research directions

First principles study of structural, electronic and optical properties of half-heusler alloys LIMGN, NaMGN and KMGN

In this study, we performed our calculations using the full-potential linearized-augmented plane wave (FP-LAPW) method as implemented in the WIEN2k code based on DFT. The generalized gradient functional with the Wu-Cohen (WC) parameterization was used to evaluate the structural, electronic, optical and thermoelectric properties of the materials under this study. We have calculated the structural parameters and our obtained results are in good agreement with available experimental and previous theory calculations. The density of states and band structure figures have been calculated and analyzed. The optical properties that covered by dielectric function, absorption coefficient, refractive index, extinction coefficient, reflectivity and energy-loss function have been calculated and analyzed in a range energy from 0eV to 30eV

Minimization of total harmonic distortions of cascaded H-bridge multilevel inverter by utilizing bio inspired AI algorithm

Minimizing total harmonic distortion (THD) with less system complexity and computation time is a stringent constraint for many power systems. The multilevel inverter can have low THD when switching angles are selected at the fundamental frequency. For low-order harmonic minimization, selective harmonic elimination (SHE) is the most adopted and proficient technique but it involves the non-linear transcendental equations which are very difficult to solve analytically and numerically. This paper proposes a genetic algorithm (GA)-based optimization technique to minimize the THD of cascaded H-bridge multilevel inverter. The GA is the finest approach for solving such complex equations by obtaining optimized switching angles. The switching angles are calculated by the genetic algorithm by solving the nonlinear transcendental equations. This paper has modeled and simulated a five-level inverter in MATLAB Simulink. The THD comparison is carried out between step modulation method and optimization method. The results reveal that THD has been reduced from 17.88 to 16.74% while third and fifth harmonics have been reduced from 3.24%, 3.7% to 0.84% and 3.3%, respectively. The optimization method along with LC filter significantly improves the power quality providing a complete sinusoidal signal for varying load