Analysis of Hand Segmentation in the Wild

A large number of works in egocentric vision have concentrated on action and object recognition. Detection and segmentation of hands in first-person videos, however, has less been explored. For many applications in this domain, it is necessary to accurately segment not only hands of the camera wearer but also the hands of others with whom he is interacting. Here, we take an in-depth look at the hand segmentation problem. In the quest for robust hand segmentation methods, we evaluated the performance of the state of the art semantic segmentation methods, off the shelf and fine-tuned, on existing datasets. We fine-tune RefineNet, a leading semantic segmentation method, for hand segmentation and find that it does much better than the best contenders. Existing hand segmentation datasets are collected in the laboratory settings. To overcome this limitation, we contribute by collecting two new datasets: a) EgoYouTubeHands including egocentric videos containing hands in the wild, and b) HandOverFace to analyze the performance of our models in presence of similar appearance occlusions. We further explore whether conditional random fields can help refine generated hand segmentations. To demonstrate the benefit of accurate hand maps, we train a CNN for hand-based activity recognition and achieve higher accuracy when a CNN was trained using hand maps produced by the fine-tuned RefineNet. Finally, we annotate a subset of the EgoHands dataset for fine-grained action recognition and show that an accuracy of 58.6% can be achieved by just looking at a single hand pose which is much better than the chance level (12.5%).Comment: Accepted at CVPR 201

Education Order in Punjab: A District Level Study.

This paper attempts to evaluate the status of education in the current districts of Punjab and compare this with the status of education attainment in 1998. The tool used for assessment and comparison is the Education Index (EI) for the districts of Punjab. The Education Index is a composite index which is calculated using enrollment at different education levels and literacy rates. The main data sources used are the Population Census 1998, Punjab Development Statistics 1998 and the Multiple Indicator Cluster Survey (MICS) 2008. Using data from these sources, robustness in the results is verified by comparing different weighting simulations of the EI. The EI results are found using the UNDP methodology and the Principal Component Analysis (PCA) method. Both methodologies of calculation lead us to ascertain the robustness of the EI calculation using the data. This testing allows an important conclusion to emerge that the different weighting schemes does not largely affect the ranking of districts. Further, by comparing the results for both years, considerable development in education status is observed; however, an unexpected result also appears. The relative pattern of education status across Punjab has hardly altered in the last ten years even with the considerable progress that has been witnessed. This shows that an unchanging relative ranking of districts seems to exist unless significant endorsement of education takes place within the lowest ranked districts. JEL classification: I2, O1 Keywords: Education, Development, Developing Countr

Optimizing Onion Crop Management: A Smart Agriculture Framework with IoT Sensors and Cloud Technology

Smart agriculture, fueled by the integration of Internet of Things (IoT) and cloud technology, has revolutionized modern farming practices. In this study, we propose a step-by-step framework for optimizing onion crop management using IoT sensors and cloud-based solutions. By deploying various IoT sensors, including soil moisture, temperature, humidity, and aerial drones, essential data about the onion crops is collected and transmitted to a central data hub. Optional edge computing devices enable real-time data processing, minimizing latency and bandwidth usage.The collected data is aggregated and stored securely on a cloud platform, which facilitates advanced data analysis and insights. Utilizing machine learning algorithms, the cloud platform can provide valuable information about the onion's growth patterns, health status, and growth trajectory. Farmers can easily access this information through a user-friendly dashboard, accessible via web or mobile applications.Automated alerts and notifications enable timely intervention, notifying farmers about any deviations from optimal conditions, such as low moisture levels or pest infestations. The system's predictive capabilities allow for precision irrigation and nutrient management, optimizing resource usage and improving crop health.The accumulated historical data offers a wealth of information, enabling the identification of trends and the prediction of growth patterns for future planting seasons. Throughout this process, data security and privacy measures are prioritized, with encrypted data transmission and storage to protect farmers' sensitive information.The integration of IoT and cloud technology provides an efficient and effective solution for monitoring onion crop growth. The proposed framework offers farmers valuable insights, improves productivity, and promotes sustainable agricultural practices

Effects of Salinity on Growth of Tomato

This research work reports effects of salinity on external and internal morphology of tomato (Lycopersicon esculentum. M.) Plants under salt stress conditions showed inhibition in root, shoot and leaf growth. Fresh and dry weight of roots and shoot was also reduced in plants treated with higher concentrations of NaCl. Leaves also showed yellowing and stunted growth which was further evaluated by estimating the chlorophyll content which was significantly reduced under higher concentrations of NaCl. Enzymatic activity like acid phosphatase and peroxidases was also altered in plants treated with higher concentration of salt, suggesting the sensitivity of tomato plants against saline conditions

Personalised learning materials based on dyslexia types: ontological approach

In recent years, e-learning systems have played an increasingly important role in higher education and, in particular, in enhancing learning experiences for individuals who have learning difficulties. However, it appears that many of the people involved in the development and implementation of e-learning tools overlook the needs of dyslexic students. As such, these students lack access to the resources on offer to other students and this leads to a disability divide. In order for educational initiatives to be effective, learning experiences need to be tailored to the individual needs of each student and the materials and tools employed should be aligned with the student’s needs, capabilities and learning objectives. The objective of this research was to propose an ontology that will facilitate the development of learning methods and technologies that are aligned with dyslexia types and symptoms. The paper commences with a discussion of domain ontology and examines how learning objectives that take into consideration a student’s capabilities and needs can be matched with appropriate assistive technology in order to deliver effective e-learning experiences and educational resources that can be consistently employed. The ontology employed within this study was developed using Ontology Web Language (OWL), an information processing system that allows applications to handle both the content and the presentation of the information available on the web. Two characteristics were employed within this research to describe each resource: dyslexia type and the features of assistive technologies that were deemed to be most appropriate for educational experiences targeted at each dyslexia type

Spontaneous bilateral tubal pregnancy

With the increase in incidence of ectopic pregnancy over the decades, bilateral ectopic pregnancy is also increasing. It is usually associated with assisted reproductive techniques (ART) but in recent years few cases of spontaneous bilateral ectopic pregnancy have been reported. Gynaecologists should be aware of this and that ultrasonography has limitations in diagnosis. In cases of ectopic pregnancy where contralateral adnexa is not clearly identified on ultrasound and fertility needs to be conserved, patient should be managed by experts in well equipped centres. A case of spontaneous bilateral tubal pregnancy that remained undiagnosed till laparotomy, is described

DAEL framework: a new adaptive e-learning framework for students with dyslexia

This paper reports on an extensive study conducted on the existing frameworks and relevant theories that lead to a better understanding of the requirements of an e-learning tool for people with dyslexia. The DAEL framework has been developed with respect to four different dimensions: presentation, hypermediality, acceptability and accessibility, and user experience. However, there has been no research on the different types of dyslexia and the dyslexic user’s viewpoint as they affect application design. Therefore, in this paper a framework is proposed which would conform to the standards of acceptability and accessibility for dyslexic students. We hypothesise that an e-learning application, which will adopt itself according to individuals’ dyslexia types, will advantage the dyslexics’ individuals in their learning process

Acute hypotensive and diuretic activities of Berberis vulgaris root bark aqueous extract in normal rats

The aim of this study is to investigate the effectiveness of intravenous administration of Berberis vulgaris root bark aqueous extract (BRBD) on the cardiovascular and renal functions of healthy normotensive rats. The different doses of BRBD 1, 10 and 20 mg/kg were administered intravenously (i.v) in normal rats. Blood pressure, diuretic activity and serum renal profile were analyzed. Intravenous injection of BRBD at the different doses of 1, 10 and 20 mg/kg showed a dose-dependent reduction in mean arterial blood pressure (

GA3 improves flower yield in some cucurbits treated with lead and mercury

Present study reveals florigenic effects of growth hormones (i.e. gibberellic acid, GA3) and heavy metals (i.e., Pb(NO3)2 and HgCl2) in Cucumis sativus L. and Momordica charantia L. Applied GA3 at 400 ppm caused precocious flowering, increasing the number of pistillate and staminate flowers in both plants. Application of Pb(NO3)2 and HgCl2 caused significant delay in flowering, consequently leading to reduction in number of flowers. However, when GA3 was applied with Pb(NO3)2 and HgCl2, there was less decrease in staminate and pistillate flowers, revealing the dominant effect of GA3. It can be concluded that inhibitory effects of heavy metals on flowering were partially restored by phytohormones.Keywords: Flowering, heavy metals, phytohormone

Healthcare equity in Pakistan_Observations from a summer visit

This summer, I had the chance to visit Pakistan after 8 years. Both my parents were born and raised there and had only come to Canada a year before I was born. Growing up with both of these nationalities, I spent a lot of my childhood in Karachi, Pakistan. From the climate to the infrastructure, I was always left stunned by how different life in Karachi is from the life I am familiar with, in Canada. This visit, as I returned to my motherland as a university student in a health sciences program, I couldn’t help but observe the state of healthcare and health equity in Karachi