216 research outputs found

    Exploring Users' Pointing Performance on Virtual and Physical Large Curved Displays

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    Large curved displays have emerged as a powerful platform for collaboration, data visualization, and entertainment. These displays provide highly immersive experiences, a wider field of view, and higher satisfaction levels. Yet, large curved displays are not commonly available due to their high costs. With the recent advancement of Head Mounted Displays (HMDs), large curved displays can be simulated in Virtual Reality (VR) with minimal cost and space requirements. However, to consider the virtual display as an alternative to the physical display, it is necessary to uncover user performance differences (e.g., pointing speed and accuracy) between these two platforms. In this paper, we explored users' pointing performance on both physical and virtual large curved displays. Specifically, with two studies, we investigate users' performance between the two platforms for standard pointing factors such as target width, target amplitude as well as users' position relative to the screen. Results from user studies reveal no significant difference in pointing performance between the two platforms when users are located at the same position relative to the screen. In addition, we observe users' pointing performance improves when they are located at the center of a semi-circular display compared to off-centered positions. We conclude by outlining design implications for pointing on large curved virtual displays. These findings show that large curved virtual displays are a viable alternative to physical displays for pointing tasks.Comment: In 29th ACM Symposium on Virtual Reality Software and Technology (VRST 2023

    Exploring Users Pointing Performance on Large Displays with Different Curvatures in Virtual Reality

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    Large curved displays inside Virtual Reality environments are becoming popular for visualizing high-resolution content during analytical tasks, gaming or entertainment. Prior research showed that such displays provide a wide field of view and offer users a high level of immersion. However, little is known about users' performance (e.g., pointing speed and accuracy) on them. We explore users' pointing performance on large virtual curved displays. We investigate standard pointing factors (e.g., target width and amplitude) in combination with relevant curve-related factors, namely display curvature and both linear and angular measures. Our results show that the less curved the display, the higher the performance, i.e., faster movement time. This result holds for pointing tasks controlled via their visual properties (linear widths and amplitudes) or their motor properties (angular widths and amplitudes). Additionally, display curvatures significantly affect the error rate for both linear and angular conditions. Furthermore, we observe that curved displays perform better or similar to flat displays based on throughput analysis. Finally, we discuss our results and provide suggestions regarding pointing tasks on large curved displays in VR.Comment: IEEE Transactions on Visualization and Computer Graphics (2023

    Seasonal variation in the abundance and species diversity of penaeid shrimps from the coastal area of Sonmiani Bay Lagoon, Balochistan, Pakistan

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    Shrimp communities of the coastal habitat of the Sonmiani Lagoon were shown to be dominated by family Penaeidae. Seasonal variation in the relative abundance and species diversity of penaeid shrimps was derived from sampling of 2554 individuals representing twelve species of three genera. The results showed that species of the genus Penaeus dominated over those of the other two genera of penaeid shrimps i.e. Metapenaeus and Parapenaeopsis. The most abundant species of penaeid shrimps were Penaeus indicus (67.50 %), Metapenaeus affinis (13.31 %), Penaeus merguiensis (12.02 %), Metapenaeus brevicornis (4.26 %) and Metapenaeus stebbingi (1.60 %), respectively. Relative abundance varied seasonally within the species and between the seasons. Highest species richness in the lagoon was observed in the period of SW monsoon and the lowest in pre-monsoon season, whereas Diversity (H') was found to be highest in post-monsoon, and appeared to be influenced by the equitability (J) of distribution of individuals among the species. Temperature, salinity and pH influenced both the abundance and the diversity of shrimp fauna in the lagoon

    Seasonal variation in the abundance and species diversity of penaeid shrimps from the coastal area of Sonmiani Bay Lagoon, Balochistan, Pakistan

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    228-235Shrimp communities of the coastal habitat of the Sonmiani Lagoon were shown to be dominated by family Penaeidae. Seasonal variation in the relative abundance and species diversity of penaeid shrimps was derived from sampling of 2554 individuals representing twelve species of three genera. The results showed that species of the genus Penaeus dominated over those of the other two genera of penaeid shrimps i.e. Metapenaeus and Parapenaeopsis. The most abundant species of penaeid shrimps were Penaeus indicus (67.50 %), Metapenaeus affinis (13.31 %), Penaeus merguiensis (12.02 %), Metapenaeus brevicornis (4.26 %) and Metapenaeus stebbingi (1.60 %), respectively. Relative abundance varied seasonally within the species and between the seasons. Highest species richness in the lagoon was observed in the period of SW monsoon and the lowest in pre-monsoon season, whereas Diversity (H') was found to be highest in post-monsoon, and appeared to be influenced by the equitability (J) of distribution of individuals among the species. Temperature, salinity and pH influenced both the abundance and the diversity of shrimp fauna in the lagoon

    Combining Machine Learning Classifiers for Stock Trading with Effective Feature Extraction

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    The unpredictability and volatility of the stock market render it challenging to make a substantial profit using any generalized scheme. This paper intends to discuss our machine learning model, which can make a significant amount of profit in the US stock market by performing live trading in the Quantopian platform while using resources free of cost. Our top approach was to use ensemble learning with four classifiers: Gaussian Naive Bayes, Decision Tree, Logistic Regression with L1 regularization and Stochastic Gradient Descent, to decide whether to go long or short on a particular stock. Our best model performed daily trade between July 2011 and January 2019, generating 54.35% profit. Finally, our work showcased that mixtures of weighted classifiers perform better than any individual predictor about making trading decisions in the stock market

    PROXIMATE AND PHYTOCHEMICAL COMPOSITION AND ANTIOXIDANT PROPERTIES OF INDIGENOUS LANDRACES OF OMANI FENUGREEK SEEDS

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    Background: Fenugreek (Trigonella foenum graecum L) is receiving global attention as a functional food due to its unique nutritional and medicinal properties as anti-diabetic, hypocholesterolemic, antipyretic, anti-carcinogenic and seasoning and flavoring agent. Materials and Methods: Seeds of indigenous fenugreek accessions were collected from three different ecological regions (Al-Dakhaliyah, Al¬Dhahirah, and Al-Batinah) of Sultanate of Oman. The samples were analyzed for proximate chemical composition, phytochemical contents and antioxidant properties. Results: Only significant (

    The effects of aerobic, resistance, and combined exercises on the plasma irisin levels, HOMA-IR, and lipid profiles in women with metabolic syndrome: A randomized controlled trial

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    Background/objective: Irisin is suggested to be an exercise beneficial effects mediator. This study aimed to examine the effects of the aerobic exercise (AE), resistance exercise (RE), and combined exercise (CE) on the plasma levels of irisin and some metabolic and anthropometric indices. Methods: Sixty overweight women with metabolic syndrome were assigned equally into four groups: AE, RE, CE, and control. The study variables were measured before and 24 h after the intervention period. Results: None of the study groups showed statistically significant changes in the serum irisin. However, muscle mass significantly increased in the RE and CE groups. Also, a significant decrease was observed in the body fat percentage in all groups. In addition, compared with the control group, the homeostatic model assessment of insulin resistance in the AE (p = 0.021), RE (p = 0.039), and in the CE (p = 0.003) groups reduced significantly. According to the analysis of indices� changes, serum irisin was significantly correlated with the body fat percentage (r = 0.532) and HOMA-IR (r = 0.424). Conclusions: The systematic exercise program for 8-weeks did not change circulating irisin and no statistically significant difference was observed between the exercise methods. Also, serum irisin seemed to be associated with the glycemic status, body fat and weight independent of exercise activity. RCT registration code: IRCT20180806040721N2. Registry name: Iranian Registry of Clinical Trials. © 2020 The Society of Chinese Scholars on Exercise Physiology and Fitnes

    Burden of rare variants in synaptic genes in patients with severe tinnitus: An exome based extreme phenotype study

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    Background: tinnitus is a heterogeneous condition associated with audiological and/or mental disorders. Chronic, severe tinnitus is reported in 1% of the population and it shows a relevant heritability, according to twins, adoptees and familial aggregation studies. The genetic contribution to severe tinnitus is unknown since large genomic studies include individuals with self-reported tinnitus and large heterogeneity in the phenotype. The aim of this study was to identify genes for severe tinnitus in patients with extreme phenotype. Methods: for this extreme phenotype study, we used three different cohorts with European ancestry (Spanish with Meniere disease (MD), Swedes tinnitus and European generalized epilepsy). In addition, four independent control datasets were also used for comparisons. Whole-exome sequencing was performed for the MD and epilepsy cohorts and whole-genome sequencing was carried out in Swedes with tinnitus. Findings: we found an enrichment of rare missense variants in 24 synaptic genes in a Spanish cohort, the most significant being PRUNE2, AKAP9, SORBS1, ITGAX, ANK2, KIF20B and TSC2 (p < 2E 04), when they were compared with reference datasets. This burden was replicated for ANK2 gene in a Swedish cohort with 97 tinnitus individuals, and in a subset of 34 Swedish patients with severe tinnitus for ANK2, AKAP9 and TSC2 genes (p < 2E 02). However, these associations were not significant in a third cohort of 701 generalized epilepsy individuals without tinnitus. Gene ontology (GO) and gene-set enrichment analyses revealed several pathways and biological processes involved in severe tinnitus, including membrane trafficking and cytoskeletal protein binding in neurons. Interpretation: a burden of rare variants in ANK2, AKAP9 and TSC2 is associated with severe tinnitus. ANK2, encodes a cytoskeleton scaffolding protein that coordinates the assembly of several proteins, drives axonal branching and influences connectivity in neurons
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