Seeking Optimum System Settings for Physical Activity Recognition on Smartwatches

Physical activity recognition (PAR) using wearable devices can provide valued information regarding an individual's degree of functional ability and lifestyle. In this regards, smartphone-based physical activity recognition is a well-studied area. Research on smartwatch-based PAR, on the other hand, is still in its infancy. Through a large-scale exploratory study, this work aims to investigate the smartwatch-based PAR domain. A detailed analysis of various feature banks and classification methods are carried out to find the optimum system settings for the best performance of any smartwatch-based PAR system for both personal and impersonal models. To further validate our hypothesis for both personal (The classifier is built using the data only from one specific user) and impersonal (The classifier is built using the data from every user except the one under study) models, we tested single subject validation process for smartwatch-based activity recognition.Comment: 15 pages, 2 figures, Accepted in CVC'1

Three-Dimensional Flow of a Second Grade Fluid along an Infinite Horizontal Plane Wall with Periodic Suction

In this paper, three-dimensional flow of a second grade fluid along a horizontal infinite plate which is subjected to a transverse sinusoidal suction velocity distribution is studied. Due to variable suction velocity distribution the flow becomes three-dimensional and for constant suction the problem becomes two-dimensional. The free stream velocity is uniform and for small perturbation approximation, analytic technique is applied to obtain the expressions for velocity field and components of skin friction. The effect of second-grade parameter, Reynolds number and suction parameter on the velocity in the direction of main flow and on the stress components is investigated with the help of graphs. The existence of backflow is observed and it is noted that the Reynolds number and suction parameter are controlling parameters for the backflow

Systematic Collective e-Cheating in a Saudi Arabian Higher Education Context: A Case Study

Objectives: The primary purpose was to investigate organized group cheating in a Middle Eastern institution during the shift to e-learning brought on by the COVID-19 pandemic in 2019. Method: The study explores the personal experiences of ten Saudi Arabian English as a Foreign Language program graduates in a higher education institution through in-depth interviews via qualitative interpretative phenomenological analysis. The study was guided by Ajzen’s theory of planned behavior. Results: A novel type of misconduct coined systematic collective e-cheating was identified and discussed. In addition, insights on the causes and types of e-cheating in a Middle Eastern context were provided. Conclusions: Academic misconduct was directly influenced by a rapid transition to e-learning, societal culture, and subjective norms, all of which jointly contributed to shifts in ethical perceptions leading to increased reports of cheating. Objectives: The primary purpose was to investigate organized group cheating in a Middle Eastern institution during the shift to e-learning brought on by the COVID-19 pandemic in 2019. Method: The study explores the personal experiences of ten Saudi Arabian English as a Foreign Language program graduates in a higher education institution through in-depth interviews via qualitative interpretative phenomenological analysis. The study was guided by Ajzen’s theory of planned behavior. Results: A novel type of misconduct coined systematic collective e-cheating was identified and discussed. In addition, insights on the causes and types of e-cheating in a Middle Eastern context were provided. Conclusions: Academic misconduct was directly influenced by a rapid transition to e-learning, societal culture, and subjective norms, all of which jointly contributed to shifts in ethical perceptions leading to increased reports of cheating. Implication for Theory and/or Practice: Education professionals need to be aware of underlying issues related to unethical behavior and encourage students to understand and address negative ideologies regarding ethics on a societal level. Efforts must also be made to raise instructor awareness of academic misconduct in e-learning through comprehensive professional development programs. Furthermore, with the increased use of technology in education, if the social, cultural, and perceptional factors are not addressed, educational systems will be impacted, affecting the credibility and value of academic degrees should cheating become the norm

Transcriptome profile of early responsive genes in susceptible barley during Rhynchosporium secalis infection

Scald caused by Rhynchosporium secalis, is an economically important disease found worldwide. In order to profile genes and pathways responding to R. seclais infection, leaf transcriptomes before and after fungus inoculation in susceptible barley were compared using cDNA-AFLP technique. Transcriptional changes of 144 expressed sequence tags (ESTs) were observed, of which 18 have no previously described function. Functional annotation of the transcripts revealed a wide range of pathways including cell wall fortification, cytoskeleton construction and metabolic processes at different time points. Furthermore, the results of RT-PCR analysis on candidate genes, ABC transporters and lycine-specific demethylase were consistent with the cDNA-AFLP data in their expression patterns. Taken together, our data suggest that susceptible barley reprograms metabolic and biological processes to initiate a suitable response R. secalis infection

Salicylic acid pathway changes in barley plants challenged with either a biotrophic or a necrotrophic pathogen

The biotrophic Blumeria graminis (Bg) and the necrotrophic Cochliobolus sativus; (Cs) are economically important fungal pathogens of barley globally. To better understand barley mechanisms to resist these pathogens, changes in salicylic acid (SA) and its responsive genes particularly the pathogenesis related PR1, PR2, PR3 and PR5 were evaluated using qRT-PCR across four time points post infection. Data showed that SA contents significantly increased (P = 0.001) in infected plants of both resistant and susceptible genotypes 24 h post inoculation in comparison with non-infected controls. In addition, time-course tests revealed a notable contradiction in the defense-related genes expression patterns between barley and Bg and Cs interactions, showing that expression patterns of the same defense-associated genes were altered in adaptation to different pathogens. PR1 and PR2 genes were highlyactivated inresistant plants infected with the necrotrophic pathogen Cs rather than of the biotrophic one. The uniformity in barley defense response mechanisms could be in convention with the well-accepted notion that these responses are high intense in the resistant genotype. Our work provides useful information on the expected role of SA pathways in barley towards biotrophic and necroptrophic pathogens with different lifestyles

Salicylic acid and hydrogen peroxide accumulation in relation to hydrolyte leakage in barley plants challenged with Cochliobolus sativus

Spot blotch (SB) caused by the hemibiotrophic fungal pathogen Cochliobolus sativus is a destructive disease of barley worldwide. To better understand the mechanisms of resistance to this disease, the involvements of salicylic acid (SA), hydrogen peroxide (H2O2) and ion fluxes during the interaction between resistant and susceptible barley seedlings and C. sativus were investigated. Early SA accumulation in leaf tissues was accompanied with an increase in H2O2 concentration in both compatible and incompatible interactions. The resistant cultivar constitutively contained higher levels of H2O2 and SA, as well as during the 72 h as compared with the un-infected control (0 h). However, levels increased rapidly upon infection in both cultivars. Moreover, a markedly greater increase in ion fluxes from the compatible material compared with the incompatible one was observed. Results suggest that SA and H2O2 accumulation are important during both compatible and incompatible barley- C. sativus interactions

Using Ensembles of Machine Learning Techniques to Predict Reference Evapotranspiration (ET0) Using Limited Meteorological Data

To maximize crop production, reference evapotranspiration (ET0) measurement is crucial for managing water resources and planning crop water needs. The FAO-PM56 method is recommended globally for estimating ET0 and evaluating alternative methods due to its extensive theoretical foundation. Numerous meteorological parameters, needed for ET0 estimation, are difficult to obtain in developing countries. Therefore, alternative ways to estimate ET0 using fewer climatic data are of critical importance. To estimate ET0 with alternative methods, difference climatic parameters of temperatures, relative humidity (maximum and minimum), sunshine hours, and wind speed for a period of 20 years from 1996 to 2015 were used in the study. The data were recorded by 11 meteorological observatories situated in various climatic regions of Pakistan. The significance of the climatic parameters used was evaluated using sensitivity analysis. The machine learning techniques of single decision tree (SDT), tree boost (TB) and decision tree forest (DTF) were used to perform sensitivity analysis. The outcomes indicated that DTF-based models estimated ET0 with higher accuracy and fewer climatic variables as compared to other ML techniques used in the study. The DTF technique, with Model 15 as input, outperformed other techniques for the most part of the performance metrics (i.e., NSE = 0.93, R-2 = 0.96 and RMSE = 0.48 mm/month). The results indicated that the DTF with fewer climatic variables of mean relative humidity, wind speed and minimum temperature could estimate ET0 accurately and outperformed other ML techniques. Additionally, a non-linear ensemble (NLE) of ML techniques was further used to estimate ET0 using the best input combination (i.e., Model 15). It was seen that the applied non-linear ensemble (NLE) approach enhanced modelling accuracy as compared to a stand-alone application of ML techniques (R-2 Multan = 0.97, R2 Skardu = 0.99, R-2 ISB = 0.98, R2 Bahawalpur = 0.98 etc.). The study results affirmed the use of an ensemble model for ET0 estimation and suggest applying it in other parts of the world to validate model performance