Search results for: remote working

Authors: Iris Lavalle Acejo, Helen Sampson

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Drawing from the perspectives of female seafarers, this article offers an analysis of an empirical investigation of the mechanisms by which women are excluded from working on board cargo ships. Female seafarers currently make up about 1% of seafarers in the global cargo shipping industry. As female presence onboard continues to constitute a small proportion of the total crew, we consider their professional advancement in comparison with their male counterparts and the ways in which they are discouraged from entering, or remining within, the industry. With interactions at work severely constrained by the traditionally masculine working culture of the ship, the study hopes to provide insights on the mechanisms in which they face and navigate barriers as they both accommodate and resist gendered differences onboard.

Keywords: female seafarers, glasswalls, genderbarriers, genderedworkplaces

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Authors: Shabnam Etemadi

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Background: Infertility is one of the most important issues in any society due to its psychological, medical and economic consequences that can greatly influence overall health and life. This study aims to assess the relationship between inhalation or exposing workplace pollution and dysfunction of the male reproductive system. Semen samples are male employees in south of Iran who exposed to work environmental pollutants for long hours. Method: Due to descriptive-analytical, the analysis of all interviews of all male patients of Bu Ali Medical Center and Pasteur Laboratory are conducted within 6 months. Random sampling numbered and patients signed informed consent. To analyze the data, Miller's fertility motivation questionnaires and the Miller-Smith lifestyle assessment inventory are used and Working Conditions Survey is developed. For analyzing the collecting data SPSS is used. Findings: Although sperm motility and volume had no statistically significant relationship with any of the lifestyle components, the weak relationship between sperm movement and work environment conditions (P = 0.07) lead to other factors to be investigated. * Among the factors of Working Environment Condition, smoking, work in the open environment and presence of more than 6 hours in the work environment with sperm mobility, smoking, contact with chemicals and radioactive with sperm volume at a level less than 0.05 had a statistically significant relationship. Conclusion: Finding revealed the environment pollution is one of the important factors in male infertility and strengthens this hypothesis. Working Environmental pollutants in the field of metropolitan pollution should be considered as a unifying hypothesis, possibly could interfere with male reproductive function.

Keywords: infertility, lifestyle, workplace pollution, male infertility

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Authors: Yulia Chalri, E. T. P. Lussiana, Sarifuddin Madenda, Bambang Trisakti, Yuhilza Hanum

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Water is a natural resource needed by humans and other living creatures. The territorial water of Indonesia is 81% of the country area, consisting of inland waters and the sea. The research object is inland waters in the form of lakes and reservoirs, since 90% of inland waters are in them, therefore the water quality should be monitored. One of water quality parameters is Total Suspended Solid (TSS). Most of the earlier research did direct measurement by taking the water sample to get TSS values. This method takes a long time and needs special tools, resulting in significant cost. Remote sensing technology has solved a lot of problems, such as the mapping of watershed and sedimentation, monitoring disaster area, mapping coastline change, and weather analysis. The aim of this research is to estimate TSS of Rawa Pening lake in Central Java by using the Lansat 8 image. The result shows that the proposed method successfully estimates the Rawa Pening’s TSS. In situ TSS shows normal water quality range, and so does estimation result of segmentation method.

Keywords: total suspended solid (TSS), remote sensing, image segmentation, RGB value

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Authors: Zeinu Ahmed Rabba, Derek D Stretch

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Remote sensing contributes valuable information to streamflow estimates. Usually, stream flow is directly measured through ground-based hydrological monitoring station. However, in many developing countries like Ethiopia, ground-based hydrological monitoring networks are either sparse or nonexistent, which limits the manage water resources and hampers early flood-warning systems. In such cases, satellite remote sensing is an alternative means to acquire such information. This paper discusses the application of remotely sensed rainfall data for streamflow modeling in Gilgel Ghibe basin in Ethiopia. Ten years (2001-2010) of two satellite-based precipitation products (SBPP), TRMM and WaterBase, were used. These products were combined with the PyTOPKAPI hydrological model to generate daily stream flows. The results were compared with streamflow observations at Gilgel Ghibe Nr, Assendabo gauging station using four statistical tools (Bias, R², NS and RMSE). The statistical analysis indicates that the bias-adjusted SBPPs agree well with gauged rainfall compared to bias-unadjusted ones. The SBPPs with no bias-adjustment tend to overestimate (high Bias and high RMSE) the extreme precipitation events and the corresponding simulated streamflow outputs, particularly during wet months (June-September) and underestimate the streamflow prediction over few dry months (January and February). This shows that bias-adjustment can be important for improving the performance of the SBPPs in streamflow forecasting. We further conclude that the general streamflow patterns were well captured at daily time scales when using SBPPs after bias adjustment. However, the overall results demonstrate that the simulated streamflow using the gauged rainfall is superior to those obtained from remotely sensed rainfall products including bias-adjusted ones.

Keywords: Ethiopia, PyTOPKAPI model, remote sensing, streamflow, Tropical Rainfall Measuring Mission (TRMM), waterBase

Procedia PDF Downloads 284

Authors: Lawal Kado

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This paper investigates the perceptions of academic staff at Umaru Musa Yar’adua University regarding the influences of librarians and working colleagues on the awareness and use of electronic databases. The study aims to provide insights into the effectiveness of these influences and suggest strategies to improve the usage of electronic databases. Research aim: The aim of this study is to determine the perceptions of academic staff on the influence of librarians and working colleagues towards the awareness and use of electronic databases in Umaru Musa Yar’adua University, Katsina. Methodology: The study adopts a quantitative method and survey research design. The survey questionnaire is distributed to 110 respondents selected through simple random sampling from a population of 523 academic staff. The collected data is analyzed using the Statistical Package for Social Sciences (SPSS) version 23. Findings: The study reveals a high level of general awareness of electronic databases in the university, largely influenced by librarians and colleagues. Librarians have played a crucial role in making academic staff aware of the available databases. The sources of information for awareness include colleagues, social media, e-mails from the library, and internet searching. Theoretical importance: This study contributes to the literature by examining the perceptions of academic staff, which can inform policymakers and stakeholders in developing strategies to maximize the use of electronic databases. Data collection and analysis procedures: The data is collected through a survey questionnaire that utilizes the Likert scaling technique. The closed-ended questions are analyzed using SPSS 23. Question addressed: The paper addresses the question of how librarians and working colleagues influence the awareness and use of electronic databases among academic staff. Conclusion: The study concludes that the influence of librarians and working colleagues significantly contributes to the awareness and use of electronic databases among academic staff. The paper recommends the establishment of dedicated departments or units for marketing library resources to further promote the usage of electronic databases.

Keywords: awareness, electronic databases, academic staff, unified theory of acceptance and use of technology, social influence

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Authors: Lan Zhang, Cailing Zhang

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In recent years, many face anti-spoofing algorithms have high detection accuracy when detecting 2D face anti-spoofing or 3D mask face anti-spoofing alone in the field of face anti-spoofing, but their detection performance is greatly reduced in multidimensional and cross-datasets tests. The rPPG method used for face anti-spoofing uses the unique vital information of real face to judge real faces and face anti-spoofing, so rPPG method has strong stability compared with other methods, but its detection rate of 2D face anti-spoofing needs to be improved. Therefore, in this paper, we improve an rPPG(Remote Photoplethysmography) method(MrPPG) for face anti-spoofing which through color space fusion, using the correlation of pulse signals between real face regions and background regions, and introducing the cyclic neural network (LSTM) method to improve accuracy in 2D face anti-spoofing. Meanwhile, the MrPPG also has high accuracy and good stability in face anti-spoofing of multi-dimensional and cross-data datasets. The improved method was validated on Replay-Attack, CASIA-FASD, Siw and HKBU_MARs_V2 datasets, the experimental results show that the performance and stability of the improved algorithm proposed in this paper is superior to many advanced algorithms.

Keywords: face anti-spoofing, face presentation attack detection, remote photoplethysmography, MrPPG

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Authors: Constant Akama, Frank Kulor, Frederick Agyemang

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All over the world, due to increasing population, electric power distribution companies are looking for more efficient ways of reading electricity meters. In Ghana, the prepaid metering system was introduced in 2007 to replace the manual system of reading which was fraught with inefficiencies. However, the prepaid system in Ghana is not capable of integration with online systems such as e-commerce platforms and remote monitoring systems. In this paper, we present a design framework for an automatic metering system that can be integrated with e-commerce platforms and remote monitoring systems. The meter was designed using ADE 7755 which reads the energy consumption and the reading is processed by a microcontroller connected to Sim900 General Packet Radio Service module containing a GSM chip provisioned with an Access Point Name. The system also has a billing server and a management server located at the premises of the utility company which communicate with the meter over a Virtual Private Network and GPRS. With this system, customers can buy credit online and the credit will be transferred securely to the meter. Also, when a fault is reported, the utility company can log into the meter remotely through the management server to troubleshoot the problem.

Keywords: access point name, general packet radio service, GSM, virtual private network

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Authors: Dauda A. Oladosu, Kamorudeen A Olaiya, Abdurahman Bello

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The deployment of smart meters by utility providers to gather fine grained spatiotemporal consumption data has grossly influenced the consumers’ emotion and behavior towards energy utilization. The quest for reduction in power consumption is now a subject of concern and one the methods adopted by the consumers to achieve this is Non-intrusive Load (appliance) Monitoring. Hence, this work presents performance Analysis of Domotics System as a tool for load monitoring when integrated with Consumer Control Unit of residential building. The system was developed with basic elements which enhance remote sensing, DTMF (Dual Tone Multi-frequency) recognition and cryptic messaging when specific task was performed. To demonstrate its applicability and suitability, this prototype was used consistently for six months at different load demands and the utilities consumed were documented. The results obtained shows good response when phone dialed, and the packet delivery of feedback SMS was quite satisfactory, making the implemented system to be of good quality with affordable cost and performs the desired functions. Besides, comparative analysis showed notable reduction in energy consumption and invariably lessened electrical bill of the consumer.

Keywords: automation, domotics, energy, load, remote, schedule

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Authors: Sharda Kumari

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As the Covid-19 pandemic continues to leave its mark on the global business landscape, companies have had to adapt to new realities and find ways to sustain their operations amid social distancing measures, government restrictions, and heightened public health concerns. This unprecedented situation has placed considerable stress on both employees and employers, underscoring the need for innovative approaches to manage the risks associated with Covid-19 transmission in the workplace. In response to these challenges, the pandemic has accelerated the adoption of digital technologies, with an increasing preference for remote interactions and virtual collaboration. Customer relationship management (CRM) systems have risen to prominence as a vital resource for organizations navigating the post-pandemic world, providing a range of benefits that include acquiring new customers, generating insightful consumer data, enhancing customer relationships, and growing market share. In the context of pandemic management, CRM systems offer three primary advantages: (1) integration features that streamline operations and reduce the need for multiple, costly software systems; (2) worldwide accessibility from any internet-enabled device, facilitating efficient remote workforce management during a pandemic; and (3) the capacity for rapid adaptation to changing business conditions, given that most CRM platforms boast a wide array of remotely deployable business growth solutions, a critical attribute when dealing with a dispersed workforce in a pandemic-impacted environment. These advantages highlight the pivotal role of CRM systems in helping organizations remain resilient and adaptive in the face of ongoing global challenges.

Keywords: healthcare, CRM, customer relationship management, customer experience, digital transformation, pandemic response, patient monitoring, patient management, healthcare automation, electronic health record, patient billing, healthcare information systems, remote workforce, virtual collaboration, resilience, adaptable business models, integration features, CRM in healthcare, telehealth, pandemic management

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Authors: Chetna Tyagi. G. B. V. S. Lakshmi, Ambuj Tripathi, D. K. Avasthi

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Graphene oxide provides a good host matrix for preparing nanocomposites due to the different functional groups attached to its edges and planes. Being biocompatible, it is used in therapeutic applications. As enzyme-based biosensor requires complicated enzyme purification procedure, high fabrication cost and special storage conditions, we need enzyme-less biosensors for use even in a harsh environment like high temperature, varying pH, etc. In this work, we have prepared both enzyme-based and enzyme-less graphene oxide-based biosensors for glucose detection using glucose-oxidase as enzyme and gold nanoparticles, respectively. These samples were characterized using X-ray diffraction, UV-visible spectroscopy, scanning electron microscopy, and transmission electron microscopy to confirm the successful synthesis of the working electrodes. Electrochemical measurements were performed for both the working electrodes using a 3-electrode electrochemical cell. Cyclic voltammetry curves showed the homogeneous transfer of electron on the electrodes in the scan range between -0.2V to 0.6V. The sensing measurements were performed using differential pulse voltammetry for the glucose concentration varying from 0.01 mM to 20 mM, and sensing was improved towards glucose in the presence of gold nanoparticles. Gold nanoparticles in graphene oxide nanocomposite played an important role in sensing glucose in the absence of enzyme, glucose oxidase, as evident from these measurements. The selectivity was tested by measuring the current response of the working electrode towards glucose in the presence of the other common interfering agents like cholesterol, ascorbic acid, citric acid, and urea. The enzyme-less working electrode also showed storage stability for up to 15 weeks, making it a suitable glucose biosensor.

Keywords: electrochemical, enzyme-less, glucose, gold nanoparticles, graphene oxide, nanocomposite

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Authors: Marwa M. Ibrahim

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The objective of this research is to study the technical and economic performance of wind/diesel/battery (W/D/B) off-grid system supplying a small remote gathering of four families using the HOMER software package. The second objective is to study the effect of wind energy system on the cost of generated electricity considering the cost of reducing CO₂ emissions as external benefit of wind turbines, no pollutant emission through the operational phase. The system consists of a small wind turbine, battery storage, and diesel generator. The electrical energy is to cater to the basic needs for which the daily load pattern is estimated at 8 kW peak. Net Present Cost (NPC) and Cost of Energy (COE) are used as economic criteria, while the measure of performance is % of power shortage. Technical and economic parameters are defined to estimate the feasibility of the system under study. Optimum system configurations are estimated for the selected site in Egypt. Using HOMER software, the simulation results shows that W/D/B systems are economical for the assumed community site as the price of generated electricity is about 0.285 $/kWh, without taking external benefits into considerations and 0.221 if CO₂ emissions taken into consideration W/D/B systems are more economical than alone diesel system as the COE is 0.432 $/kWh for diesel alone.

Keywords: renewable energy, hybrid energy system, on-off grid system, simulation, optimization and environmental impacts

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Authors: Endalkachew Abebe Kebede, Bojin Bojinov, Andon Vasilev Andonov, Orhan Dengiz

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Remote sensing has a potential application in assessing and monitoring the plants' biophysical properties using the spectral responses of plants and soils within the electromagnetic spectrum. However, only a few reports compare the performance of different remote sensing sensors against in-situ field spectral measurement. The current study assessed the potential applications of open data source satellite images (Sentinel 2 and Landsat 9) in estimating the biophysical properties of the wheat crop on a study farm found in the village of OvchaMogila. A Landsat 9 (30 m resolution) and Sentinel-2 (10 m resolution) satellite images with less than 10% cloud cover have been extracted from the open data sources for the period of December 2021 to April 2022. An Unmanned Aerial Vehicle (UAV) has been used to capture the spectral response of plant leaves. In addition, SpectraVue 710s Leaf Spectrometer was used to measure the spectral response of the crop in April at five different locations within the same field. The ten most common vegetation indices have been selected and calculated based on the reflectance wavelength range of remote sensing tools used. The soil samples have been collected in eight different locations within the farm plot. The different physicochemical properties of the soil (pH, texture, N, P₂O₅, and K₂O) have been analyzed in the laboratory. The finer resolution images from the UAV and the Leaf Spectrometer have been used to validate the satellite images. The performance of different sensors has been compared based on the measured leaf spectral response and the extracted vegetation indices using the five sampling points. A scatter plot with the coefficient of determination (R2) and Root Mean Square Error (RMSE) and the correlation (r) matrix prepared using the corr and heatmap python libraries have been used for comparing the performance of Sentinel 2 and Landsat 9 VIs compared to the drone and SpectraVue 710s spectrophotometer. The soil analysis revealed the study farm plot is slightly alkaline (8.4 to 8.52). The soil texture of the study farm is dominantly Clay and Clay Loam.The vegetation indices (VIs) increased linearly with the growth of the plant. Both the scatter plot and the correlation matrix showed that Sentinel 2 vegetation indices have a relatively better correlation with the vegetation indices of the Buteo dronecompared to the Landsat 9. The Landsat 9 vegetation indices somewhat align better with the leaf spectrometer. Generally, the Sentinel 2 showed a better performance than the Landsat 9. Further study with enough field spectral sampling and repeated UAV imaging is required to improve the quality of the current study.

Keywords: landsat 9, leaf spectrometer, sentinel 2, UAV

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Authors: C. Asha Poorna, P. G. Vinod, A. R. R. Menon

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Currently increasing population and their activities like urbanization and industrialization generating the greatest environmental, issue called Waste. And the major problem in waste management is selection of an appropriate site for waste disposal. The selection of suitable site have constrains like environmental, economical and political considerations. In this paper we discuss the strategies to be followed while selecting a site for decentralized system for solid waste disposal, using Geographic Information System (GIS), the Analytical Hierarchy Process (AHP) and the remote sensing method for Thiruvananthapuram corporation area. It is located on the west coast of India near the extreme south of the mainland. It lies on the shores of Killiyar and Karamana River. Being on the basin the waste managements must be regulated with the water body. The different criteria considered for waste disposal site selection are lithology, surface water, aquifer, groundwater, land use, contours, aspect, elevation, slope, and distance to road, distance from settlement are examined in relation to land fill site selection. Each criterion was identified and weighted by AHP score and mapped using GIS technique and suitable map is prepared by overlay analysis.

Keywords: waste disposal, solid waste management, Geographic Information System (GIS), Analytical Hierarchy Process (AHP)

Procedia PDF Downloads 396

Authors: Kanchan Negi

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Background: Modern and urban occupational culture have driven demands for people to work long hours and weekends and take work to home at times. Research on the health effects of these exhaustive temporal work patterns is scant or contradictory. This study examines the relationship between work patterns and wellbeing in a sample of women living in the metropolitan hub of Delhi. Method: This study is based on the data collected from 360 currently married women between age 29 and 49 years, working in the urban capital hub of India, i.e., Delhi. The women interviewed were professionals from the education, health, banking and information and technology (IT) sector. Bivariate analysis was done to study the characteristics of the sample. Logistic regression analysis was used to estimate the physical and psychological wellbeing across occupational characteristics. Results: Most of the working women were below age 35 years; around 30% of women worked in the education sector, 23% in health, 21% in banking and 26% in the IT sector. Over 55% of women were employed in the private sector and only 36% were permanent employees. Nearly 30% of women worked for more than the standard 8 hours a day. The findings from logistic regression showed that compared to women working in the education sector, those who worked in the banking and IT sector more likely to have physical and psychological health issues (OR 2.07-4.37, CI 1.17-4.37); women who bear dual burden of responsibilities had higher odds of physical and psychological health issues than women who did not (OR 1.19-1.85 CI 0.96-2.92). Women who worked for more than 8 hours a day (OR 1.15, CI 1.01-1.30) and those who worked for more than five days a week (OR 1.25, CI 1.05-1.35) were more likely to have physical health issues than women who worked for 6-8 hours a day and five days e week, respectively. Also, not having flexible work timings and compensatory holidays increased the odds of having physical and psychological health issues among working women (OR 1.17-1.29, CI 1.01-1.47). Women who worked in the private sector, those employed temporarily and who worked in the non-conducive environments were more likely to have psychological health issues as compared to women in the public sector, permanent employees and those who worked in a conducive environment, respectively (OR 1.33-1.67, CI 1.09-2.91). Women who did not have poor work-life balance had reduced the odds of psychological health issues than women with poor work-life balance (OR 0.46, CI 0.25-0.84). Conclusion: Poor wellbeing significantly linked to strenuous and rigid work patterns, suggesting that modern and urban work culture may contribute to the poor wellbeing of working women. Noticing the recent decline in female workforce participation in Delhi, schemes like Flexi-timings, compensatory holidays, work-from-home and daycare facilities for young ones must be welcomed; these policies already exist in some private sector firms, and the public sectors companies should also adopt such changes to ease the dual burden as homemaker and career maker. This could encourage women in the urban areas to readily take up the jobs with less juggle to manage home and work.

Keywords: occupational characteristics, urban India, well-being, working women

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Authors: Dhanuj M. Gandikota

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Sensor-derived three-dimensional (3D) point clouds of trees are invaluable in remote sensing analysis for the accurate measurement of key structural metrics, bio-inventory values, spatial planning/visualization, and ecological modeling. Machine learning (ML) holds the potential in addressing the restrictive tradeoffs in cost, spatial coverage, resolution, and information gain that exist in current point cloud sensing methods. Terrestrial laser scanning (TLS) remains the highest fidelity source of both canopy and below-canopy structural features, but usage is limited in both coverage and cost, requiring manual deployment to map out large, forested areas. While aerial laser scanning (ALS) remains a reliable avenue of LIDAR active remote sensing, ALS is also cost-restrictive in deployment methods. Space-borne photogrammetry from high-resolution satellite constellations is an avenue of passive remote sensing with promising viability in research for the accurate construction of vegetation 3-D point clouds. It provides both the lowest comparative cost and the largest spatial coverage across remote sensing methods. However, both space-borne photogrammetry and ALS demonstrate technical limitations in the capture of valuable below-canopy point cloud data. Looking to minimize these tradeoffs, we explored a class of powerful ML algorithms called Deep Learning (DL) that show promise in recent research on 3-D point cloud reconstruction and interpolation. Our research details the efficacy of applying these DL techniques to reconstruct accurate below-canopy point clouds from space-borne and aerial remote sensing through learned patterns of tree species fractal symmetry properties and the supplementation of locally sourced bio-inventory metrics. From our dataset, consisting of tree point clouds obtained from TLS, we deconstructed the point clouds of each tree into those that would be obtained through ALS and satellite photogrammetry of varying resolutions. We fed this ALS/satellite point cloud dataset, along with the simulated local bio-inventory metrics, into the DL point cloud reconstruction architectures to generate the full 3-D tree point clouds (the truth values are denoted by the full TLS tree point clouds containing the below-canopy information). Point cloud reconstruction accuracy was validated both through the measurement of error from the original TLS point clouds as well as the error of extraction of key structural metrics, such as crown base height, diameter above root crown, and leaf/wood volume. The results of this research additionally demonstrate the supplemental performance gain of using minimum locally sourced bio-inventory metric information as an input in ML systems to reach specified accuracy thresholds of tree point cloud reconstruction. This research provides insight into methods for the rapid, cost-effective, and accurate construction of below-canopy tree 3-D point clouds, as well as the supported potential of ML and DL to learn complex, unmodeled patterns of fractal tree growth symmetry.

Keywords: deep learning, machine learning, satellite, photogrammetry, aerial laser scanning, terrestrial laser scanning, point cloud, fractal symmetry

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Authors: Yongqi Dong, Zuo Zhang, Rui Fu, Li Li

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The records generated by taxicabs which are equipped with GPS devices is of vital importance for studying human mobility behavior, however, here we are focusing on taxi drivers' operation strategies between workdays and weekends temporally and spatially. We identify a group of valuable characteristics through large scale drivers' behavior in a complex metropolis environment. Based on the daily operations of 31,000 taxi drivers in New York City, we classify drivers into top, ordinary and low-income groups according to their monthly working load, daily income, daily ranking and the variance of the daily rank. Then, we apply big data analysis and visualization methods to compare the different characteristics among top, ordinary and low income drivers in selecting of working time, working area as well as strategies between workdays and weekends. The results verify that top drivers do have special operation tactics to help themselves serve more passengers, travel faster thus make more money per unit time. This research provides new possibilities for fully utilizing the information obtained from urban taxicab data for estimating human behavior, which is not only very useful for individual taxicab driver but also to those policy-makers in city authorities.

Keywords: big data, operation strategies, comparison, revenue, temporal, spatial

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Authors: Chunyue Liu, Hongxing Jiang

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Traditional water depth survey of wetland habitats used by waterbirds needs intensive labor, time and money. The optical remote sensing image relies on passive multispectral scanner data has been widely employed to study estimate water depth. This paper presents an innovative method for developing the water depth model based on the characteristics of visible and thermal infrared spectra of Landsat ETM+ image, combing with 441 field water depth data at Etoupao shallow wetland. The wetland is located at Momoge National Nature Reserve of Northeast China, where the largest stopover habitat along the eastern flyway of globally, critically-endangered Siberian Cranes are. The cranes mainly feed on the tubers of emergent aquatic plants such as Scirpus planiculmis and S. nipponicus. The effective water control is a critical step for maintaining the production of tubers and food availability for this crane. The model employing multi-band approach can effectively simulate water depth for this shallow wetland. The model parameters of NDVI and GREEN indicated the vegetation growth and coverage affecting the reflectance from water column change are uneven. Combining with the field-observed water level at the same date of image acquisition, the digital elevation model (DEM) for the underwater terrain was generated. The wetland area and water volume of different water levels were then calculated from the DEM using the function of Area and Volume Statistics under the 3D Analyst of ArcGIS 10.0. The findings provide good references to effectively monitor changes in water level and water demand, develop practical plan for water level regulation and water management, and to create best foraging habitats for the cranes. The methods here can be adopted for the bottom topography simulation and water management in waterbirds’ habitats, especially in the shallow wetlands.

Keywords: remote sensing, water depth reversion, shallow wetland habitat management, siberian crane

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Authors: Bernard Kumi-Boateng, Issaka Yakubu

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Forest fire, which is, an uncontrolled fire occurring in nature has become a major concern for the Forestry Commission of Ghana (FCG). The forest fires in Ghana usually result in massive destruction and take a long time for the firefighting crews to gain control over the situation. In order to assess the effect of forest fire at local scale, it is important to consider the role fire plays in vegetation composition, biodiversity, soil erosion, and the hydrological cycle. The occurrence, frequency and behaviour of forest fires vary over time and space, primarily as a result of the complicated influences of changes in land use, vegetation composition, fire suppression efforts, and other indigenous factors. One of the forest zones in Ghana with a high level of vegetation stress is the Goaso forest area. The area has experienced changes in its traditional land use such as hunting, charcoal production, inefficient logging practices and rural abandonment patterns. These factors which were identified as major causes of forest fire, have recently modified the incidence of fire in the Goaso area. In spite of the incidence of forest fires in the Goaso forest area, most of the forest services do not provide a cartographic representation of the burned areas. This has resulted in significant amount of information being required by the firefighting unit of the FCG to understand fire risk factors and its spatial effects. This study uses Remote Sensing and Geographic Information System techniques to develop a fire risk hazard model using the Goaso Forest Area (GFA) as a case study. From the results of the study, natural forest, agricultural lands and plantation cover types were identified as the major fuel contributing loads. However, water bodies, roads and settlements were identified as minor fuel contributing loads. Based on the major and minor fuel contributing loads, a forest fire risk hazard model with a reasonable accuracy has been developed for the GFA to assist decision making.

Keywords: forest, GIS, remote sensing, Goaso

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Authors: Mohd Sarfaraz

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The objective of this study is to investigate the work-life balance and job satisfaction among women employees in a hospital in India. It is believed that balancing a successful career with a family life or personal life can be challenging. WLB impacts on persons' satisfaction in their work and personal life roles. For this purpose, a questionnaire is developed with 22 items. The data collected from women employees who are working in a hospital in Aligarh, India. The constructs considered in this study include WLB and job satisfaction. The demographic and organisational variables considered in the study are genders, age and tenure of the job. Factors of WLB are flexible working conditions, work-life balance programs, and employee intention to change/leave a job, work pressure/stress and long working hours. This paper examines the relationship between work-family conflict, policies, and job and life satisfaction. Appropriate statistical tool using SPSS will be applied to achieve the objective. The anxiety over work-life balance is progressively becoming a common talk, especially for female employees.Increasing demands from the work and family domains represent a high strain for employees which even lead to the health problems among employees. Although it is believed that work-family role strain is more common among women employees. Therefore, the study will focus on these issues of WLB and job satisfaction among female professionals.

Keywords: work-life balance, job satisfaction, work- family conflict, health

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Authors: Veronica Kah Jo Wong, Yoke Mui Lim, Nurul Sakina Mokhtar Azizi

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The impact on the construction industry in Malaysia is unprecedented, as the government implemented a lockdown to restrict human movement in an effort to stop COVID-19 from spreading. Quantity surveyor (QS), as one of the key construction professionals, found that the working practices and environments for quantity surveyors today have changed due to the current pandemic. The QS profession must deal not only with changes in project issues but also with a different working environment in which most people are required to work from home and follow the standard operating procedures. Therefore, QS should be flexible, agile, and have the capability to adapt to the current working practices by strengthening their competencies. Adapting to the current and recovering environment of COVID-19 may result in the emergence of a new competence such as skill and knowledge for QS in order to maintain the quality of performance in the delivery of their professional services. Thus, this paper's objective is to investigate the changes in knowledge and skills in quantity surveyors. The data will be collected through interviews with registered professional QS to gain better insights that are specific in this industry, and the findings will be verified using the Delphi method. It is hoped that new knowledge and skill will be found from the study and will not only contribute to the betterment of the professional QS but also in guiding higher learning institutions to incorporate the new competencies into their curriculum.

Keywords: competency, COVID-19 pandemic, Malaysia, quantity surveying

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Authors: Joshua Adan Valdez, Shawn Gallaher

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Global climate change has impacted atmospheric temperatures contributing to rising sea levels, decreasing sea ice, and increased freshening of high latitude oceans. This freshening has contributed to increased stratification inhibiting local mixing and nutrient transport, modifying regional circulations in polar oceans. In recent years, the Western Arctic has seen an increase in freshwater volume at an average rate of 397+-116km3/year across the Beaufort Gyre. The majority of the freshwater volume resides in the Beaufort Gyre surface lens driven by anticyclonic wind forcing, sea ice melt, and Arctic river runoff, and is typically defined as water fresher than 34.8. The near-isothermal nature of Arctic seawater and non-linearities in the equation of state for near-freezing waters result in a salinity-driven pycnocline as opposed to the temperature-driven density structure seen in the lower latitudes. In this study, we investigate the relationship between freshwater content and dynamic ocean topography (DOT). In situ measurements of freshwater content are useful in providing information on the freshening rate of the Beaufort Gyre; however, their collection is costly and time-consuming. Utilizing NASA’s ICESat-2’s DOT remote sensing capabilities and Air Expendable CTD (AXCTD) data from the Seasonal Ice Zone Reconnaissance Surveys (SIZRS), a linear regression model between DOT and freshwater content is determined along the 150° west meridian. Freshwater content is calculated by integrating the volume of water between the surface and a depth with a reference salinity of ~34.8. Using this model, we compare interannual variability in freshwater content within the gyre, which could provide a future predictive capability of freshwater volume changes in the Beaufort-Chukchi Sea using non-in situ methods. Successful employment of the ICESat-2’s DOT approximation of freshwater content could potentially demonstrate the value of remote sensing tools to reduce reliance on field deployment platforms to characterize physical ocean properties.

Keywords: Cryosphere, remote sensing, Arctic oceanography, climate modeling, Ekman transport

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Authors: Narendra Kumar

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In developing countries, the majority of people with diabetes are in the age range of 45-64 years and more women than men. As in many areas of the India, non-insulin dependent diabetes mellitus has become major problems. Now it is spreading among the middle class and poor at an alarming stage in India and Kerala is turning to be the world capital of diabetes. This study uses two round NSS data from the ‘National Sample Survey Organization, India’ to investigate the predictors of diabetes in Kerala. The overall estimates for diabetes prevalence among elderly show that higher in men than women, but there are more women with diabetes than men. Education of respondent has been found a significant characteristics, further respondent working status, caste/tribe have substantial impact on diabetes in Kerala. The disease is more common for people who are mostly physically inactive. This whole picture is very much prominent in the urban areas compared with the rural ones. Not working elderly have significantly higher with diabetes than for those working in elderly. Socioeconomic status was inversely associated with diabetes prevalence. For men and women, the prevalence of diabetes and hypertension were significantly higher in the urban population while smoking, smokeless tobacco consumption was more prevalent in the rural population. High alcohol intake increases diabetes risk among elderly. Finally these findings specified that an increase improve health care services and changing life style of elderly which should in turn raise diabetes patient survival and should decrease comorbidities due to diabetes in Kerala.

Keywords: elderly, diabetes, prevalence, Kerala

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Authors: Ahmad Sharif Ahmadi, Yoshitaka Kajita

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With massive population expansion and fast economic development in last decade, urban land has increasingly expanded and formed high informal development territory in Kabul city. This paper investigates integrated urbanization trends in Kabul city since the formation of the basic structure of the present city using GIS and remote sensing. This study explores the spatial and temporal difference of urban land expansion and land use categories among different time intervals, 1964-1978 and 1978-2008 from 1964 to 2008 in Kabul city. Furthermore, the goal of this paper is to understand the extent of urban land expansion and the factors driving urban land expansion in Kabul city. Many factors like population expansion, the return of refugees from neighboring countries and significant economic growth of the city affected urban land expansion. Across all the study area urban land expansion rate, population expansion rate and economic growth rate have been compared to analyze the relationship of driving forces with urban land expansion. Based on urban land change data detected by interpreting land use maps, it was found that in the entire study area the urban territory has been expanded by 14 times between 1964 and 2008.

Keywords: GIS, Kabul city, land use, urban land expansion, urbanization

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Authors: Berhanu Keno Terfa

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To understand the consequences of urbanization, accurate, and long-term representation of urban dynamics is essential. Remote sensing data from various multi-temporal satellite images viz., TM (1987), TM (1995), ETM+ (2005) and OLI (2017) were used. An integrated method, landscape metrics, built-up density, and urban growth type analysis were employed to analyze the pattern, process, and overall growth status in the city. The result showed that the built-up area had increased by 541.3% between 1987 and 2017, at an average annual increment of 8.9%. The area of urban expansion in a city has tripled during the 2005-2017 period as compared to 187- 1995. The major growth took place in the east and southeast directions during 1987–1995 period, whereas predominant built-up development was observed in south and southeast direction during 1995–2017 period. The analysis using landscape metrics and urban typologies showed that Hawassa experienced a fragmented and irregular spatiotemporal urban growth patterns, mostly by extension, suggesting a strong tendency towards sprawl in the past three decades.

Keywords: Hawassa, spatial patterns, remote sensing, multi-temporal, urban sprawl

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Authors: Uvais Qidwai, Mohamed Shakir

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This paper presents an initial study related to the use of robotic toys as teaching and therapeutic aid tools for teachers and care-givers as well as parents of children with various levels of autism spectrum disorder (ASD). Some of the most common features related to the behavior of a child with ASD are his/her social isolation, living in their own world, not being physically active, and not willing to learn new things. While the teachers, parents, and all other related care-givers do their best to improve the condition of these kids, it is usually quite an uphill task. However, one remarkable observation that has been reported by several teachers dealing with ASD children is the fact that the same children do get attracted to toys with lights and sounds. Hence, this project targets the development/modifications of such existing toys into appropriate behavior training tools which the care-givers can use as they would desire. Initially, the remote control is in hand of the trainer, but after some time, the child is entrusted with the control of the robotic toy to test for the level of interest. It has been found during the course of this study that children with quite low learning activity got extremely interested in the robot and even advanced to controlling the robot with the Electromyography (EMG). It has been observed that the children did show some hesitation in the beginning 5 minutes of the very first sessions of such interaction but were very comfortable afterwards which has been considered as a very strong indicator of the potential of this technique in teaching and rehabilitation of children with ASD or similar brain disorders.

Keywords: Autism Spectrum Disorder (ASD), robotic toys, IR control, electromyography, LabVIEW based remote control

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Authors: Zdzislaw Kaminski, Zbigniew Czyz, Krzysztof Skiba

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This paper discusses the CFD simulation of a flow around a rotor of a Vertical Axis Wind Turbine. Numerical simulation, unlike experiments, enables us to validate project assumptions when it is designed and avoid a costly preparation of a model or a prototype for a bench test. CFD simulation enables us to compare characteristics of aerodynamic forces acting on rotor working surfaces and define operational parameters like torque or power generated by a turbine assembly. This research focused on the rotor with the blades capable of modifying their working surfaces, i.e. absorbing wind kinetic energy. The operation of this rotor is based on adjusting angular aperture α of the top and bottom parts of the blades mounted on an axis. If this angular aperture α increases, the working surface which absorbs wind kinetic energy also increases. The operation of turbines is characterized by parameters like the angular aperture of blades, power, torque, speed for a given wind speed. These parameters have an impact on the efficiency of assemblies. The distribution of forces acting on the working surfaces in our turbine changes according to the angular velocity of the rotor. Moreover, the resultant force from the force acting on an advancing blade and retreating blade should be as high as possible. This paper is part of the research to improve an efficiency of a rotor assembly. Therefore, using simulation, the courses of the above parameters were studied in three full rotations individually for each of the blades for three angular apertures of blade working surfaces, i.e. 30 °, 60 °, 90 °, at three wind speeds, i.e. 4 m / s, 6 m / s, 8 m / s and rotor speeds ranging from 100 to 500 rpm. Finally, there were created the characteristics of torque coefficients and power as a function of time for each blade separately and for the entire rotor. Accordingly, the correlation between the turbine rotor power as a function of wind speed for varied values of rotor rotational speed. By processing this data, the correlation between the power of the turbine rotor and its rotational speed for each of the angular aperture of the working surfaces was specified. Finally, the optimal values, i.e. of the highest output power for given wind speeds were read. The research results in receiving the basic characteristics of turbine rotor power as a function of wind speed for the three angular apertures of the blades. Given the nature of rotor operation, the growth in the output turbine can be estimated if angular aperture of the blades increases. The controlled adjustment of angle α enables a smooth adjustment of power generated by a turbine rotor. If wind speed is significant, this type of adjustment enables this output power to remain at the same level (by reducing angle α) with no risk of damaging a construction. This work has been financed by the Polish Ministry of Science and Higher Education.

Keywords: computational fluid dynamics, numerical analysis, renewable energy, wind turbine

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Authors: Ali J. Ghandour, Houssam A. Krayem, Abedelkarim A. Jezzini

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High-resolution satellite images and remote sensing can provide global information in a fast way compared to traditional methods of data collection. Under such high resolution, a road is not a thin line anymore. Objects such as cars and trees are easily identifiable. Automatic vehicles enumeration can be considered one of the most important applications in traffic management. In this paper, autonomous vehicle detection and classification approach in highway environment is proposed. This approach consists mainly of three stages: (i) first, a set of preprocessing operations are applied including soil, vegetation, water suppression. (ii) Then, road networks detection and delineation is implemented using built-up area index, followed by several morphological operations. This step plays an important role in increasing the overall detection accuracy since vehicles candidates are objects contained within the road networks only. (iii) Multi-level Otsu segmentation is implemented in the last stage, resulting in vehicle detection and classification, where detected vehicles are classified into cars and trucks. Accuracy assessment analysis is conducted over different study areas to show the great efficiency of the proposed method, especially in highway environment.

Keywords: remote sensing, object identification, vehicle and road extraction, vehicle and road features-based classification

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Authors: Saad Algharib, Jay Lee

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Urbanization is a complex phenomenon that occurs during the city’s development from one form to another. In other words, it is the process when the activities in the land use/land cover change from rural to urban. Since the oil exploration, Kuwait City has been growing rapidly due to its urbanization and population growth by both natural growth and inward immigration. The main objective of this study is to detect changes in urban land use/land cover and to examine the changing spatial patterns of urban growth in and around Kuwait City between 1989 and 2001. In addition, this study also evaluates the spatial patterns of the changes detected and how they can be related to the spatial configuration of the city. Recently, the use of remote sensing and geographic information systems became very useful and important tools in urban studies because of the integration of them can allow and provide the analysts and planners to detect, monitor and analyze the urban growth in a region effectively. Moreover, both planners and users can predict the trends of the growth in urban areas in the future with remotely sensed and GIS data because they can be effectively updated with required precision levels. In order to identify the new urban areas between 1989 and 2001, the study uses satellite images of the study area and remote sensing technology for classifying these images. Unsupervised classification method was applied to classify images to land use and land cover data layers. After finishing the unsupervised classification method, GIS overlay function was applied to the classified images for detecting the locations and patterns of the new urban areas that developed during the study period. GIS was also utilized to evaluate the distribution of the spatial patterns. For example, Moran’s index was applied for all data inputs to examine the urban growth distribution. Furthermore, this study assesses if the spatial patterns and process of these changes take place in a random fashion or with certain identifiable trends. During the study period, the result of this study indicates that the urban growth has occurred and expanded 10% from 32.4% in 1989 to 42.4% in 2001. Also, the results revealed that the largest increase of the urban area occurred between the major highways after the forth ring road from the center of Kuwait City. Moreover, the spatial distribution of urban growth occurred in cluster manners.

Keywords: geographic information systems, remote sensing, urbanization, urban growth

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Authors: Rituparna Nath, Shawn J. Marshall

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Glaciers are one of the main sensitive climatic indicators, as they respond strongly to small climatic shifts. We develop a flow line model of glacier dynamics to simulate the past and future extent of glaciers in the Canadian Rocky Mountains, with the aim of coupling this model within larger scale regional climate models of glacier response to climate change. This paper will focus on glacier-climate modeling and reconstructions of glacier volume from the Little Ice Age (LIA) to present for Athabasca Glacier, Alberta, Canada. Glacier thickness, volume and mass change will be constructed using flow line modelling and examination of different climate scenarios that are able to give good reconstructions of LIA ice extent. With the availability of SPOT 5 imagery, Digital elevation models and GIS Arc Hydro tool, ice catchment properties-glacier width and LIA moraines have been extracted using automated procedures. Simulation of glacier mass change will inform estimates of meltwater run off over the historical period and model calibration from the LIA reconstruction will aid in future projections of the effects of climate change on glacier recession. Furthermore, the model developed will be effective for further future studies with ensembles of glaciers.

Keywords: flow line modeling, Athabasca Glacier, glacier mass balance, Remote Sensing, Arc hydro tool, little ice age

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Authors: Xudong Guan, Ainong Li, Gaohuan Liu, Chong Huang, Wei Zhao

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Due to the low spatial resolution of MODIS data, the accuracy of small-area plaque extraction with a high degree of landscape fragmentation is greatly limited. To this end, the study combines Landsat data with higher spatial resolution and MODIS data with higher temporal resolution for decision-level fusion. Considering the importance of the land heterogeneity factor in the fusion process, it is superimposed with the weighting factor, which is to linearly weight the Landsat classification result and the MOIDS classification result. Three levels were used to complete the process of data fusion, that is the pixel of MODIS data, the pixel of Landsat data, and objects level that connect between these two levels. The multilevel decision fusion scheme was tested in two sites of the lower Mekong basin. We put forth a comparison test, and it was proved that the classification accuracy was improved compared with the single data source classification results in terms of the overall accuracy. The method was also compared with the two-level combination results and a weighted sum decision rule-based approach. The decision fusion scheme is extensible to other multi-resolution data decision fusion applications.

Keywords: image classification, decision fusion, multi-temporal, remote sensing

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