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6 Accessible Facilities in Home Environment for Elderly Family Members in Sri Lanka
Authors: M. A. N. Rasanjalee Perera
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The world is facing several problems due to increasing elderly population. In Sri Lanka, along with the complexity of the modern society and structural and functional changes of the family, “caring for elders” seems as an emerging social problem. This situation may intensify as the county is moving into a middle income society. Seeking higher education and related career opportunities, and urban living in modern housing are new trends, through which several problems are generated. Among many issues related with elders, “lack of accessible and appropriate facilities in their houses as well as public buildings” can be identified as a major problem. This study argues that welfare facilities provided for the elderly people, particularly in the home environment, in the country are not adequate. Modern housing features such as bathrooms, pantries, lobbies, and leisure areas etc. are questionable as to whether they match with elders’ physical and mental needs. Consequently, elders have to face domestic accidents and many other difficulties within their living environments. Records of hospitals in the country also proved this fact. Therefore, this study tries to identify how far modern houses are suited with elders’ needs. The study further questioned whether “aging” is a considerable matter when people are buying, planning and renovating houses. A randomly selected sample of 50 houses were observed and 50 persons were interviewed around the Maharagama urban area in Colombo district to obtain primary data, while relevant secondary data and information were used to have a depth analysis. The study clearly found that none of the houses included to the sample are considering elders’ needs in planning, renovating, or arranging the home. Instead, most of the families were giving priority to the rich and elegant appearance and modern facilities of the houses. Particularly, to the bathrooms, pantry, large setting areas, balcony, parking slots for two vehicles, ad parapet walls with roller-gates are the main concerns. A significant factor found here is that even though, many children of the aged are in middle age and reaching their older years at present, they do not plan their future living within a safe and comfortable home, despite that they are hoping to spent the latter part of their lives in the their current homes. This fact highlights that not only the other responsible parts of the society, but also those who are reaching their older ages are ignoring the problems of the aged. At the same time, it was found that more than 80% of old parents do not like to stay at their children’s homes as the living environments in such modern homes are not familiar or convenient for them. Due to this context, the aged in Sri Lanka may have to be alone in their own homes due to current trend of society of migrating to urban living in modern houses. At the same time, current urban families who live in modern houses may have to face adding accessible facilities in their home environment, as current modern housing facilities may not be appropriate them for a better life in their latter part of life.
Keywords: Aging population, elderly care, home environment, housing facilities.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 8045 Modern Detection and Description Methods for Natural Plants Recognition
Authors: Masoud Fathi Kazerouni, Jens Schlemper, Klaus-Dieter Kuhnert
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Green planet is one of the Earth’s names which is known as a terrestrial planet and also can be named the fifth largest planet of the solar system as another scientific interpretation. Plants do not have a constant and steady distribution all around the world, and even plant species’ variations are not the same in one specific region. Presence of plants is not only limited to one field like botany; they exist in different fields such as literature and mythology and they hold useful and inestimable historical records. No one can imagine the world without oxygen which is produced mostly by plants. Their influences become more manifest since no other live species can exist on earth without plants as they form the basic food staples too. Regulation of water cycle and oxygen production are the other roles of plants. The roles affect environment and climate. Plants are the main components of agricultural activities. Many countries benefit from these activities. Therefore, plants have impacts on political and economic situations and future of countries. Due to importance of plants and their roles, study of plants is essential in various fields. Consideration of their different applications leads to focus on details of them too. Automatic recognition of plants is a novel field to contribute other researches and future of studies. Moreover, plants can survive their life in different places and regions by means of adaptations. Therefore, adaptations are their special factors to help them in hard life situations. Weather condition is one of the parameters which affect plants life and their existence in one area. Recognition of plants in different weather conditions is a new window of research in the field. Only natural images are usable to consider weather conditions as new factors. Thus, it will be a generalized and useful system. In order to have a general system, distance from the camera to plants is considered as another factor. The other considered factor is change of light intensity in environment as it changes during the day. Adding these factors leads to a huge challenge to invent an accurate and secure system. Development of an efficient plant recognition system is essential and effective. One important component of plant is leaf which can be used to implement automatic systems for plant recognition without any human interface and interaction. Due to the nature of used images, characteristic investigation of plants is done. Leaves of plants are the first characteristics to select as trusty parts. Four different plant species are specified for the goal to classify them with an accurate system. The current paper is devoted to principal directions of the proposed methods and implemented system, image dataset, and results. The procedure of algorithm and classification is explained in details. First steps, feature detection and description of visual information, are outperformed by using Scale invariant feature transform (SIFT), HARRIS-SIFT, and FAST-SIFT methods. The accuracy of the implemented methods is computed. In addition to comparison, robustness and efficiency of results in different conditions are investigated and explained.
Keywords: SIFT combination, feature extraction, feature detection, natural images, natural plant recognition, HARRIS-SIFT, FAST-SIFT.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 7294 An Online Space for Practitioners in the Water, Sanitation and Hygiene Sector
Authors: Olivier Mills, Bernard McDonell, Laura A. S. MacDonald
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The increasing availability and quality of internet access throughout the developing world provides an opportunity to utilize online spaces to disseminate water, sanitation and hygiene (WASH) knowledge to practitioners. Since 2001, CAWST has provided in-person education, training and consulting services to thousands of WASH practitioners all over the world, supporting them to start, troubleshoot, improve and expand their WASH projects. As CAWST continues to grow, the organization faces challenges in meeting demand from clients and in providing consistent, timely technical support. In 2012, CAWST began utilizing online spaces to expand its reach by developing a series of resources websites and webinars. CAWST has developed a WASH Education and Training resources website, a Biosand Filter (BSF) Knowledge Base, a Household Water Treatment and Safe Storage Knowledge Base, a mobile app for offline users, a live chat support tool, a WASH e-library, and a series of webinar-style online training sessions to complement its in-person capacity development services. In order to determine the preliminary outcomes of providing these online services, CAWST has monitored and analyzed registration to the online spaces, downloads of the educational materials, and webinar attendance; as well as conducted user surveys. The purpose of this analysis was to find out who was using the online spaces, where users came from, and how the resources were being used. CAWST’s WASH Resources website has served over 5,800 registered users from 3,000 organizations in 183 countries. Additionally, the BSF Knowledge Base has served over 1000 registered users from 68 countries, and over 540 people from 73 countries have attended CAWST’s online training sessions. This indicates that the online spaces are effectively reaching a large numbers of users, from a range of countries. A 2016 survey of the Biosand Filter Knowledge Base showed that approximately 61% of users are practitioners, and 39% are either researchers or students. Of the respondents, 46% reported using the BSF Knowledge Base to initiate a BSF project and 43% reported using the information to train BSF technicians. Finally, 61% indicated they would like even greater support from CAWST’s Technical Advisors going forward. The analysis has provided an encouraging indication that CAWST’s online spaces are contributing to its objective of engaging and supporting WASH practitioners to start, improve and expand their initiatives. CAWST has learned several lessons during the development of these online spaces, in particular related to the resources needed to create and maintain the spaces, and respond to the demand created. CAWST plans to continue expanding its online spaces, improving user experience of the sites, and involving new contributors and content types. Through the use of online spaces, CAWST has been able to increase its global reach and impact without significantly increasing its human resources by connecting WASH practitioners with the information they most need, in a practical and accessible manner. This paper presents on CAWST’s use of online spaces through the CAWST-developed platforms discussed above and the analysis of the use of these platforms.
Keywords: Education and training, knowledge sharing, online resources, water and sanitation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16833 Sickle Cell Disease: Review of Managements in Pregnancy and the Outcome in Ampang Hospital, Selangor
Authors: Z. Nurzaireena, K. Azalea, T. Azirawaty, S. Jameela, G. Muralitharan
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The aim of this study is the review of the management practices of sickle cell disease patients during pregnancy, as well as the maternal and neonatal outcome at Ampang Hospital, Selangor. The study consisted of a review of pregnant patients with sickle cell disease under follow up at the Hematology Clinic, Ampang Hospital over the last seven years to assess their management and maternal-fetal outcome. The results of the review show that Ampang Hospital is considered the public hematology centre for sickle cell disease and had successfully managed three pregnancies throughout the last seven years. Patients’ presentations, managements and maternal-fetal outcome were compared and reviewed for academic improvements. All three patients were seen very early in their pregnancy and had been given a regime of folic acid, antibiotics and thrombo-prophylactic drugs. Close monitoring of maternal and fetal well being was done by the hematologists and obstetricians. Among the patients, there were multiple admissions during the pregnancy for either a painful sickle cell bone crisis, haemolysis following an infection and anemia requiring phenotype- matched blood and exchange transfusions. Broad spectrum antibiotics coverage during and infection, hydration, pain management and venous-thrombolism prophylaxis were mandatory. The pregnancies managed to reach near term in the third trimester but all required emergency caesarean section for obstetric indications. All pregnancies resulted in live births with good fetal outcome. During post partum all were nursed closely in the high dependency units for further complications and were discharged well. Post partum follow up and contraception counseling was comprehensively given for future pregnancies. Sickle cell disease is uncommonly seen in the East, especially in the South East Asian region, yet more cases are seen in the current decade due to improved medical expertise and advance medical laboratory technologies. Pregnancy itself is a risk factor for sickle cell patients as increased thrombosis event and risk of infections can lead to multiple crisis, haemolysis, anemia and vaso-occlusive complications including eclampsia, cerebrovasular accidents and acute bone pain. Patients mostly require multiple blood product transfusions thus phenotype-matched blood is required to reduce the risk of alloimmunozation. Emphasizing the risks and complications in preconception counseling and establishing an ultimate pregnancy plan would probably reduce the risk of morbidity and mortality to the mother and unborn child. Early management for risk of infection, thromboembolic events and adequate hydration is mandatory. A holistic approach involving multidisciplinary team care between the hematologist, obstetricians, anesthetist, neonatologist and close nursing care for both mother and baby would ensure the best outcome. In conclusion, sickle cell disease by itself is a high risk medical condition and pregnancy would further amplify the risk. Thus, close monitoring with combine multidisciplinary care, counseling and educating the patients are crucial in achieving the safe outcome.Keywords: Anemia, haemoglobinopathies, pregnancy, sickle cell disease.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 12952 Species Profiling of White Grub Beetles and Evaluation of Pre and Post Sown Application of Insecticides against White Grub Infesting Soybean
Authors: Ajay Kumar Pandey, Mayank Kumar
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White grub (Coleoptera: Scarabaeidae) is a major destructive pest in western Himalayan region of Uttarakhand. Beetles feed on apple, apricot, plum, walnut etc. during night while, second and third instar grubs feed on live roots of cultivated as well as non-cultivated crops. Collection and identification of scarab beetles through light trap was carried out at Crop Research Centre, Govind Ballab Pant University Pantnagar, Udham Singh Nagar (Uttarakhand) during 2018. Field trials were also conducted in 2018 to evaluate pre and post sown application of different insecticides against the white grub infesting soybean. The insecticides like Carbofuran 3 Granule (G) (750 g a.i./ha), Clothianidin 50 Water Dispersal Granule (WG) (120 g a.i./ha), Fipronil 0.3 G (50 g a.i./ha), Thiamethoxam 25 WG (80 g a.i./ha), Imidacloprid 70 WG (300 g a.i./ha), Chlorantraniliprole 0.4% G(100 g a.i./ha) and mixture of Fipronil 40% and Imidacloprid 40% WG (300 g a.i./ha) were applied at the time of sowing in pre sown experiment while same dosage of insecticides were applied in standing soybean crop during (first fortnight of July). Commutative plant mortality data were recorded after 20, 40, 60 days intervals and compared with untreated control. Total 23 species of white grub beetles recorded on the light trap and Holotrichia serrata Fabricious (Coleoptera: Melolonthinae) was found to be predominant species by recording 20.6% relative abundance out of the total light trap catch (i.e. 1316 beetles) followed by Phyllognathus sp. (14.6% relative abundance). H. rosettae and Heteronychus lioderus occupied third and fourth rank with 11.85% and 9.65% relative abundance, respectively. The emergence of beetles of predominant species started from 15th March, 2018. In April, average light trap catch was 382 white grub beetles, however, peak emergence of most of the white grub species was observed from June to July, 2018 i.e. 336 beetles in June followed by 303 beetles in the July. On the basis of the emergence pattern of white grub beetles, it may be concluded that the Peak Emergence Period (PEP) for the beetles of H. serrata was second fortnight of April for the total period of 15 days. In May, June and July relatively low population of H. serrata was observed. A decreasing trend in light trap catch was observed and went on till September during the study. No single beetle of H. serrata was observed on light trap from September onwards. The cumulative plant mortality data in both the experiments revealed that all the insecticidal treatments were significantly superior in protection-wise (6.49-16.82% cumulative plant mortality) over untreated control where highest plant mortality was 17.28 to 39.65% during study. The mixture of Fipronil 40% and Imidacloprid 40% WG applied at the rate of 300 g a.i. per ha proved to be most effective having lowest plant mortality i.e. 9.29 and 10.94% in pre and post sown crop, followed by Clothianidin 50 WG (120 g a.i. per ha) where the plant mortality was 10.57 and 11.93% in pre and post sown treatments, respectively. Both treatments were found significantly at par among each other. Production-wise, all the insecticidal treatments were found statistically superior (15.00-24.66 q per ha grain yields) over untreated control where the grain yield was 8.25 & 9.13 q per ha. Treatment Fipronil 40% + Imidacloprid 40% WG applied at the rate of 300 g a.i. per ha proved to be most effective and significantly superior over Imidacloprid 70WG applied at the rate of 300 g a.i. per ha.
Keywords: Bio efficacy, insecticide, Holotrichia, soybean, white grub.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 6941 A Real-Time Bayesian Decision-Support System for Predicting Suspect Vehicle’s Intended Target Using a Sparse Camera Network
Authors: Payam Mousavi, Andrew L. Stewart, Huiwen You, Aryeh F. G. Fayerman
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We present a decision-support tool to assist an operator in the detection and tracking of a suspect vehicle traveling to an unknown target destination. Multiple data sources, such as traffic cameras, traffic information, weather, etc., are integrated and processed in real-time to infer a suspect’s intended destination chosen from a list of pre-determined high-value targets. Previously, we presented our work in the detection and tracking of vehicles using traffic and airborne cameras. Here, we focus on the fusion and processing of that information to predict a suspect’s behavior. The network of cameras is represented by a directional graph, where the edges correspond to direct road connections between the nodes and the edge weights are proportional to the average time it takes to travel from one node to another. For our experiments, we construct our graph based on the greater Los Angeles subset of the Caltrans’s “Performance Measurement System” (PeMS) dataset. We propose a Bayesian approach where a posterior probability for each target is continuously updated based on detections of the suspect in the live video feeds. Additionally, we introduce the concept of ‘soft interventions’, inspired by the field of Causal Inference. Soft interventions are herein defined as interventions that do not immediately interfere with the suspect’s movements; rather, a soft intervention may induce the suspect into making a new decision, ultimately making their intent more transparent. For example, a soft intervention could be temporarily closing a road a few blocks from the suspect’s current location, which may require the suspect to change their current course. The objective of these interventions is to gain the maximum amount of information about the suspect’s intent in the shortest possible time. Our system currently operates in a human-on-the-loop mode where at each step, a set of recommendations are presented to the operator to aid in decision-making. In principle, the system could operate autonomously, only prompting the operator for critical decisions, allowing the system to significantly scale up to larger areas and multiple suspects. Once the intended target is identified with sufficient confidence, the vehicle is reported to the authorities to take further action. Other recommendations include a selection of road closures, i.e., soft interventions, or to continue monitoring. We evaluate the performance of the proposed system using simulated scenarios where the suspect, starting at random locations, takes a noisy shortest path to their intended target. In all scenarios, the suspect’s intended target is unknown to our system. The decision thresholds are selected to maximize the chances of determining the suspect’s intended target in the minimum amount of time and with the smallest number of interventions. We conclude by discussing the limitations of our current approach to motivate a machine learning approach, based on reinforcement learning in order to relax some of the current limiting assumptions.
Keywords: Autonomous surveillance, Bayesian reasoning, decision-support, interventions, patterns-of-life, predictive analytics, predictive insights.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 540