Search results for: noise sensing circuit

Authors: Ajit Brindhaban

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Background and Purpose: Computed Tomography (CT) scans have become the largest source of radiation in radiological imaging. The purpose of this study was to compare the quality of pediatric Computed Tomography (CT) images reconstructed using Filtered Back Projection (FBP) with images reconstructed using different strengths of Iterative Reconstruction (IR) technique, and to perform a feasibility study to assess the use of IR techniques as a dose reduction tool. Materials and Methods: An anthropomorphic phantom representing a 5-year old child was scanned, in two stages, using a Siemens Somatom CT unit. In stage one, scans of the head, chest and abdomen were performed using standard protocols recommended by the scanner manufacturer. Images were reconstructed using FBP and 5 different strengths of IR. Contrast-to-Noise Ratios (CNR) were calculated from average CT number and its standard deviation measured in regions of interest created in the lungs, bone, and soft tissues regions of the phantom. Paired t-test and the one-way ANOVA were used to compare the CNR from FBP images with IR images, at p = 0.05 level. The lowest strength value of IR that produced the highest CNR was identified. In the second stage, scans of the head was performed with decreased mA(s) values relative to the increase in CNR compared to the standard FBP protocol. CNR values were compared in this stage using Paired t-test at p = 0.05 level. Results: Images reconstructed using IR technique had higher CNR values (p < 0.01.) in all regions compared to the FBP images, at all strengths of IR. The CNR increased with increasing IR strength of up to 3, in the head and chest images. Increases beyond this strength were insignificant. In abdomen images, CNR continued to increase up to strength 5. The results also indicated that, IR techniques improve CNR by a up to factor of 1.5. Based on the CNR values at strength 3 of IR images and CNR values of FBP images, a reduction in mA(s) of about 20% was identified. The images of the head acquired at 20% reduced mA(s) and reconstructed using IR at strength 3, had similar CNR as FBP images at standard mA(s). In the head scans of the phantom used in this study, it was demonstrated that similar CNR can be achieved even when the mA(s) is reduced by about 20% if IR technique with strength of 3 is used for reconstruction. Conclusions: The IR technique produced better image quality at all strengths of IR in comparison to FBP. IR technique can provide approximately 20% dose reduction in pediatric head CT while maintaining the same image quality as FBP technique.

Keywords: filtered back projection, image quality, iterative reconstruction, pediatric computed tomography imaging

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Authors: Masauso Moses Phiri

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Frequent glucose monitoring is essential to the management of diabetes. Plasmonic enzyme-based glucose biosensors have the advantages of greater specificity, simplicity and rapidity. The aim of this study was to develop a rapid plasmonic colorimetric glucose biosensor based on biocatalytic enlargement of AuNS guided by GOx. Gold nanoparticles of 18 nm in diameter were synthesized using the citrate method. Using these as seeds, a modified seeded method for the synthesis of monodispersed gold nanostars was followed. Both the spherical and star-shaped nanoparticles were characterized using ultra-violet visible spectroscopy, agarose gel electrophoresis, dynamic light scattering, high-resolution transmission electron microscopy and energy-dispersive X-ray spectroscopy. The feasibility of a plasmonic colorimetric assay through growth of AuNS by silver coating in the presence of hydrogen peroxide was investigated by several control and optimization experiments. Conditions for excellent sensing such as the concentration of the detection solution in the presence of 20 µL AuNS, 10 mM of 2-(N-morpholino) ethanesulfonic acid (MES), ammonia and hydrogen peroxide were optimized. Using the optimized conditions, the glucose assay was developed by adding 5mM of GOx to the solution and varying concentrations of glucose to it. Kinetic readings, as well as color changes, were observed. The results showed that the absorbance values of the AuNS were blue shifting and increasing as the concentration of glucose was elevated. Control experiments indicated no growth of AuNS in the absence of GOx, glucose or molecular O₂. Increased glucose concentration led to an enhanced growth of AuNS. The detection of glucose was also done by naked-eye. The color development was near complete in ± 10 minutes. The kinetic readings which were monitored at 450 and 560 nm showed that the assay could discriminate between different concentrations of glucose by ± 50 seconds and near complete at ± 120 seconds. A calibration curve for the qualitative measurement of glucose was derived. The magnitude of wavelength shifts and absorbance values increased concomitantly with glucose concentrations until 90 µg/mL. Beyond that, it leveled off. The lowest amount of glucose that could produce a blue shift in the localized surface plasmon resonance (LSPR) absorption maxima was found to be 10 – 90 µg/mL. The limit of detection was 0.12 µg/mL. This enabled the construction of a direct sensitivity plasmonic colorimetric detection of glucose using AuNS that was rapid, sensitive and cost-effective with naked-eye detection. It has great potential for transfer of technology for point-of-care devices.

Keywords: colorimetric, gold nanostars, glucose, glucose oxidase, plasmonic

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Authors: Mari A. Virtanen, Elina Haavisto, Eeva Liikanen, Maria Kääriäinen

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Rapid technological development and digitalization has affected also on higher education. During last twenty years multiple of electronic and mobile learning (e-learning, m-learning) platforms have been developed and have become prevalent in many universities and in the all fields of education. Ubiquitous learning (u-learning) is not that widely known or used. Ubiquitous learning environments (ULE) are the new era of computer-assisted learning. They are based on ubiquitous technology and computing that fuses the learner seamlessly into learning process by using sensing technology as tags, badges or barcodes and smart devices like smartphones and tablets. ULE combines real-life learning situations into virtual aspects and can be flexible used in anytime and anyplace. The aim of this study was to assess the effects of ubiquitous 360 o learning environment on higher education students’ clinical histotechnology competence. A quasi-experimental study design was used. 57 students in biomedical laboratory science degree program was assigned voluntarily to experiment (n=29) and to control group (n=28). Experimental group studied via ubiquitous 360o learning environment and control group via traditional web-based learning environment (WLE) in a 8-week educational intervention. Ubiquitous 360o learning environment (ULE) combined authentic learning environment (histotechnology laboratory), digital environment (virtual laboratory), virtual microscope, multimedia learning content, interactive communication tools, electronic library and quick response barcodes placed into authentic laboratory. Web-based learning environment contained equal content and components with the exception of the use of mobile device, interactive communication tools and quick response barcodes. Competence of clinical histotechnology was assessed by using knowledge test and self-report developed for this study. Data was collected electronically before and after clinical histotechnology course and analysed by using descriptive statistics. Differences among groups were identified by using Wilcoxon test and differences between groups by using Mann-Whitney U-test. Statistically significant differences among groups were identified in both groups (p<0.001). Competence scores in post-test were higher in both groups, than in pre-test. Differences between groups were very small and not statistically significant. In this study the learning environment have developed based on 360o technology and successfully implemented into higher education context. And students’ competence increases when ubiquitous learning environment were used. In the future, ULE can be used as a learning management system for any learning situation in health sciences. More studies are needed to show differences between ULE and WLE.

Keywords: competence, higher education, histotechnology, ubiquitous learning, u-learning, 360o

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Authors: Ali H. Daraji, Ye Jianqiao

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The micro electrical devices of the wireless sensor network are continuously developed and become very small and compact with low electric power requirements using limited period life conventional batteries. The low power requirement for these devices, cost of conventional batteries and its replacement have encouraged researcher to find alternative power supply represented by energy harvesting system to provide an electric power supply with infinite period life. In the last few years, the investigation of energy harvesting for structure health monitoring has increased to powering wireless sensor network by converting waste mechanical vibration into electricity using piezoelectric sensors. Optimisation of energy harvesting is an important research topic to ensure a flowing of efficient electric power from structural vibration. The harvesting power is mainly based on the properties of piezoelectric material, dimensions of piezoelectric sensor, its position on a structure and value of an external electric load connected between sensor electrodes. Larger surface area of sensor is not granted larger power harvesting when the sensor area is covered positive and negative mechanical strain at the same time. Thus lead to reduction or cancellation of piezoelectric output power. Optimisation of energy harvesting is achieved by locating these sensors precisely and efficiently on the structure. Limited published work has investigated the energy harvesting for aircraft wing. However, most of the published studies have simplified the aircraft wing structure by a cantilever flat plate or beam. In these studies, the optimisation of energy harvesting was investigated by determination optimal value of an external electric load connected between sensor electrode terminals or by an external electric circuit or by randomly splitting piezoelectric sensor to two segments. However, the aircraft wing structures are complex than beam or flat plate and mostly constructed from flat and curved skins stiffened by stringers and ribs with more complex mechanical strain induced on the wing surfaces. This aircraft wing structure bonded with discrete macro fibre composite sensors was modelled using multiphysics finite element to optimise the energy harvesting by determination of the optimal number of sensors, location and the output resistance load. The optimal number and location of macro fibre sensors were determined based on the maximization of the open and close loop sensor output voltage using frequency response analysis. It was found different optimal distribution, locations and number of sensors bounded on the top and the bottom surfaces of the aircraft wing.

Keywords: energy harvesting, optimisation, sensor, wing

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Authors: Lito M. Amit, Venecio U. Ultra, Young-Woong Song

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The business process outsourcing (BPO) in the Philippines is expanding rapidly attracting more than 2% of total employment. Currently, the BPO industry is confronted with several issues pertaining to sustainable productivity such as meeting the staffing gap, high rate of employees’ turnover and workforce retention, and the occupational health and safety (OHS) of call center agents. We conducted a survey of OHS programs and health concerns among call center agents in the Philippines and determined the sociocultural factors that affect the vulnerability of call center agents to occupational health risks and hazards. The majority of the agents affirmed that OHS are implemented and OHS orientation and emergency procedures were conducted at employment initiations, perceived favorable and convenient working environment except for occasional noise disturbances and acoustic shock, visual, and voice fatigues. Male agents can easily adjust to the demands and changes in their work environment and flexible work schedules than female agents. Female agents have a higher tendency to be pressured and humiliated by low work performance, experience a higher incidence of emotional abuse, psychological abuse, and experience more physical stress than male agents. The majority of the call center agents had a night-shift schedule and regardless of other factors, night shift work brings higher stress to agents. While working in a call center, higher incidence of headaches and insomnia, burnout, suppressed anger, anxiety, and depressions were experienced by female, younger (21-25 years old) and those at night shift than their counterpart. Most common musculoskeletal disorders include body pain in the neck, shoulders and back; and hand and wrist disorders and these are commonly experienced by female and younger workers. About 30% experienced symptoms of cardiovascular and gastrointestinal disorders and weakened immune systems. Overall, these findings have shown the variable vulnerability by a different subpopulation of call center agents and are important in the occupational health risk prevention and management towards a sustainable human resource for BPO industry in the Philippines.

Keywords: business process outsourcing industry, health risk of call center agents, socio-cultural determinants, Philippines

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Authors: Krisala Joshi, Sayanta Ghosh, Renu Lata, Jagdish C. Kuniyal

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Throughout the world, monitoring and estimating the changing pattern of forests across diverse landscapes through remote sensing is instrumental in understanding the interactions of human activities and the ecological environment with the changing climate. Forest change detection using satellite imageries has emerged as an important means to gather information on a regional scale. Kullu valley in Himachal Pradesh, India is situated in a transitional zone between the lesser and the greater Himalayas. Thus, it presents a typical rugged mountainous terrain with moderate to high altitude which varies from 1200 meters to over 6000 meters. Due to changes in agricultural cropping patterns, urbanization, industrialization, hydropower generation, climate change, tourism, and anthropogenic forest fire, it has undergone a tremendous transformation in forest cover in the past three decades. The loss and degradation of forest cover results in soil erosion, loss of biodiversity including damage to wildlife habitats, and degradation of watershed areas, and deterioration of the overall quality of nature and life. The supervised classification of LANDSAT satellite data was performed to assess the changes in forest cover in Kullu valley over the years 2000 to 2020. Normalized Burn Ratio (NBR) was calculated to discriminate between burned and unburned areas of the forest. Our study reveals that in Kullu valley, the increasing number of forest fire incidents specifically, those due to anthropogenic activities has been on a rise, each subsequent year. The main objective of the present study is, therefore, to estimate the change in the forest cover of Kullu valley and to address the various social aspects responsible for the anthropogenic forest fires. Also, to assess its impact on the significant changes in the regional climatic factors, specifically, temperature, humidity, and precipitation over three decades, with the help of satellite imageries and ground data. The main outcome of the paper, we believe, will be helpful for the administration for making a quantitative assessment of the forest cover area changes due to anthropogenic activities and devising long-term measures for creating awareness among the local people of the area.

Keywords: Anthropogenic Activities, Forest Change Detection, Normalized Burn Ratio (NBR), Supervised Classification

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Authors: Mona Rashidirad, Hamid Salimian

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Dynamic capabilities, as the most considerable capabilities of firms in the current fast-moving economy may not be sufficient for performance improvement, but their contribution to performance is undeniable. While much of the extant literature investigates the impact of dynamic capabilities on organisational performance, little attention has been devoted to understand whether and how dynamic capabilities create value. Dynamic capabilities as the mirror of competitive strategies should enable firms to search and seize new ideas, integrate and coordinate the firm’s resources and capabilities in order to create value. A careful investigation to the existing knowledge base remains us puzzled regarding the relationship among competitive strategies, dynamic capabilities and value creation. This study thus attempts to fill in this gap by empirically investigating the impact of dynamic capabilities on value creation and the mediating impact of competitive strategy on this relationship. We aim to contribute to dynamic capability view (DCV), in both theoretical and empirical senses, by exploring the impact of dynamic capabilities on firms’ value creation and whether competitive strategy can play any role in strengthening/weakening this relationship. Using a sample of 491 firms in the UK telecommunications market, the results demonstrate that dynamic sensing, learning, integrating and coordinating capabilities play a significant role in firm’s value creation, and competitive strategy mediates the impact of dynamic capabilities on value creation. Adopting DCV, this study investigates whether the value generating from dynamic capabilities depends on firms’ competitive strategy. This study argues a firm’s competitive strategy can mediate its ability to derive value from its dynamic capabilities and it explains the extent a firm’s competitive strategy may influence its value generation. The results of the dynamic capabilities-value relationships support our expectations and justify the non-financial value added of the four dynamic capability processes in a highly turbulent market, such as UK telecommunications. Our analytical findings of the relationship among dynamic capabilities, competitive strategy and value creation provide further evidence of the undeniable role of competitive strategy in deriving value from dynamic capabilities. The results reinforce the argument for the need to consider the mediating impact of organisational contextual factors, such as firm’s competitive strategy to examine how they interact with dynamic capabilities to deliver value. The findings of this study provide significant contributions to theory. Unlike some previous studies which conceptualise dynamic capabilities as a unidimensional construct, this study demonstrates the benefits of understanding the details of the link among the four types of dynamic capabilities, competitive strategy and value creation. In terms of contributions to managerial practices, this research draws attention to the importance of competitive strategy in conjunction with development and deployment of dynamic capabilities to create value. Managers are now equipped with solid empirical evidence which explains why DCV has become essential to firms in today’s business world.

Keywords: dynamic capabilities, resource based theory, value creation, competitive strategy

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Authors: Md. Kausar Alam, Ramin Motamed

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The damaging effects of liquefaction-induced ground movements have been frequently observed in past earthquakes, such as the 2010-2011 Canterbury Earthquake Sequence (CES) in New Zealand and the 2011 Tohoku earthquake in Japan. To reduce the consequences of soil liquefaction at shallow depths, various ground improvement techniques have been utilized in engineering practice, among which this research is focused on experimentally evaluating the press-in sheet piling technique. The press-in sheet pile technique eliminates the vibration, hammering, and noise pollution associated with dynamic sheet pile installation methods. Unfortunately, there are limited experimental studies on the press-in sheet piling technique for liquefaction mitigation using 1g shake table tests in which all the controlling mechanisms of liquefaction-induced foundation settlement, including sand ejecta, can be realistically reproduced. In this study, a series of moderate scale 1g shake table experiments were conducted at the University of Nevada, Reno, to evaluate the performance of this technique in liquefiable soil layers. First, a 1/5 size model was developed based on a recent UC San Diego shaking table experiment. The scaled model has a density of 50% for the top crust, 40% for the intermediate liquefiable layer, and 85% for the bottom dense layer. Second, a shallow foundation is seated atop an unsaturated sandy soil crust. Third, in a series of tests, a sheet pile with variable embedment depth is inserted into the liquefiable soil using the press-in technique surrounding the shallow foundations. The scaled models are subjected to harmonic input motions with amplitude and dominant frequency properly scaled based on the large-scale shake table test. This study assesses the performance of the press-in sheet piling technique in terms of reductions in the foundation movements (settlement and tilt) and generated excess pore water pressures. In addition, this paper discusses the cost-effectiveness and carbon footprint features of the studied mitigation measures.

Keywords: excess pore water pressure, foundation settlement, press-in sheet pile, soil liquefaction

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Authors: Tomasz Grzes, Maciej Kopczynski, Jaroslaw Stepaniuk

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The rough sets theory developed by Prof. Z. Pawlak is one of the tools that can be used in the intelligent systems for data analysis and processing. Banking, medicine, image recognition and security are among the possible fields of utilization. In all these fields, the amount of the collected data is increasing quickly, but with the increase of the data, the computation speed becomes the critical factor. Data reduction is one of the solutions to this problem. Removing the redundancy in the rough sets can be achieved with the reduct. A lot of algorithms of generating the reduct were developed, but most of them are only software implementations, therefore have many limitations. Microprocessor uses the fixed word length, consumes a lot of time for either fetching as well as processing of the instruction and data; consequently, the software based implementations are relatively slow. Hardware systems don’t have these limitations and can process the data faster than a software. Reduct is the subset of the decision attributes that provides the discernibility of the objects. For the given decision table there can be more than one reduct. Core is the set of all indispensable condition attributes. None of its elements can be removed without affecting the classification power of all condition attributes. Moreover, every reduct consists of all the attributes from the core. In this paper, the hardware implementation of the two-stage greedy algorithm to find the one reduct is presented. The decision table is used as an input. Output of the algorithm is the superreduct which is the reduct with some additional removable attributes. First stage of the algorithm is calculating the core using the discernibility matrix. Second stage is generating the superreduct by enriching the core with the most common attributes, i.e., attributes that are more frequent in the decision table. Described above algorithm has two disadvantages: i) generating the superreduct instead of reduct, ii) additional first stage may be unnecessary if the core is empty. But for the systems focused on the fast computation of the reduct the first disadvantage is not the key problem. The core calculation can be achieved with a combinational logic block, and thus add respectively little time to the whole process. Algorithm presented in this paper was implemented in Field Programmable Gate Array (FPGA) as a digital device consisting of blocks that process the data in a single step. Calculating the core is done by the comparators connected to the block called 'singleton detector', which detects if the input word contains only single 'one'. Calculating the number of occurrences of the attribute is performed in the combinational block made up of the cascade of the adders. The superreduct generation process is iterative and thus needs the sequential circuit for controlling the calculations. For the research purpose, the algorithm was also implemented in C language and run on a PC. The times of execution of the reduct calculation in a hardware and software were considered. Results show increase in the speed of data processing.

Keywords: data reduction, digital systems design, field programmable gate array (FPGA), reduct, rough set

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Authors: Ali Hamza

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Accurate segmentation of breast ultrasound images is of paramount importance in enhancing the diagnostic capabilities of breast cancer detection. This study presents an approach utilizing the U-Net architecture for segmenting breast ultrasound images aimed at improving the accuracy and reliability of mass identification within the breast tissue. The proposed method encompasses a multi-stage process. Initially, preprocessing techniques are employed to refine image quality and diminish noise interference. Subsequently, the U-Net architecture, a deep learning convolutional neural network (CNN), is employed for pixel-wise segmentation of regions of interest corresponding to potential breast masses. The U-Net's distinctive architecture, characterized by a contracting and expansive pathway, enables accurate boundary delineation and detailed feature extraction. To evaluate the effectiveness of the proposed approach, an extensive dataset of breast ultrasound images is employed, encompassing diverse cases. Quantitative performance metrics such as the Dice coefficient, Jaccard index, sensitivity, specificity, and Hausdorff distance are employed to comprehensively assess the segmentation accuracy. Comparative analyses against traditional segmentation methods showcase the superiority of the U-Net architecture in capturing intricate details and accurately segmenting breast masses. The outcomes of this study emphasize the potential of the U-Net-based segmentation approach in bolstering breast ultrasound image analysis. The method's ability to reliably pinpoint mass boundaries holds promise for aiding radiologists in precise diagnosis and treatment planning. However, further validation and integration within clinical workflows are necessary to ascertain their practical clinical utility and facilitate seamless adoption by healthcare professionals. In conclusion, leveraging the U-Net architecture for breast ultrasound image segmentation showcases a robust framework that can significantly enhance diagnostic accuracy and advance the field of breast cancer detection. This approach represents a pivotal step towards empowering medical professionals with a more potent tool for early and accurate breast cancer diagnosis.

Keywords: mage segmentation, U-Net, deep learning, breast cancer detection, diagnostic accuracy, mass identification, convolutional neural network

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Authors: John E. Foley, Martin Miele, Raul Fonda, Jon Jacobson

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This paper presents development and implementation of new and innovative data collection and analysis methodologies based on deployment of total field magnetometer arrays. Our research has focused on the development of a vertically-integrated suite of platforms all utilizing common data acquisition, data processing and analysis tools. These survey platforms include low-altitude helicopters and ground-based vehicles, including robots, for terrestrial mapping applications. For marine settings the sensor arrays are deployed from either a hydrodynamic bottom-following wing towed from a surface vessel or from a towed floating platform for shallow-water settings. Additionally, sensor arrays are deployed from tethered remotely operated vehicles (ROVs) for underwater settings where high maneuverability is required. While the primary application of these systems is the detection and mapping of unexploded ordnance (UXO), these system are also used for various infrastructure mapping and geologic investigations. For each application, success is driven by the integration of magnetometer arrays, accurate geo-positioning, system noise mitigation, and stable deployment of the system in appropriate proximity of expected targets or features. Each of the systems collects geo-registered data compatible with a web-enabled data management system providing immediate access of data and meta-data for remote processing, analysis and delivery of results. This approach allows highly sophisticated magnetic processing methods, including classification based on dipole modeling and remanent magnetization, to be efficiently applied to many projects. This paper also briefly describes the initial development of magnetometer-based detection systems deployed from low-altitude helicopter platforms and the subsequent successful transition of this technology to the marine environment. Additionally, we present examples from a range of terrestrial and marine settings as well as ongoing research efforts related to sensor miniaturization for unmanned aerial vehicle (UAV) magnetic field mapping applications.

Keywords: dipole modeling, magnetometer mapping systems, sub-surface infrastructure mapping, unexploded ordnance detection

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Authors: Darshini Mahadevia, Kanika Gounder, Saumya Lathia

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Cities, an outcome of natural growth and migration, are ever-expanding due to urban sprawl. In the Global South, urban areas are experiencing a switch from public transport to private vehicles, coupled with intensified urban agglomeration, leading to frequent longer commutes by automobiles. This increase in travel distance and motorized vehicle kilometres lead to unsustainable cities. To achieve the nationally pledged GHG emission mitigation goal, the government is prioritizing a modal shift to low-carbon transport modes like mass transit and paratransit. Mixed land-use and urban densification are crucial for the economic viability of these projects. Informed by desktop assessment of mobility plans and in-person primary surveys, the paper explores the challenges around urban densification and travel patterns in two Indian cities of contrasting nature- Surat, a metropolitan industrial city with a 5.9 million population and a very compact urban form, and Udaipur, a heritage city attracting large international tourists’ footfall, with limited scope for further densification. Dense, mixed-use urban areas often improve access to basic services and economic opportunities by reducing distances and enabling people who don't own personal vehicles to reach them on foot/ cycle. But residents travelling on different modes end up contributing to similar trip lengths, highlighting the non-uniform distribution of land-uses and lack of planned transport infrastructure in the city and the urban-peri urban networks. Additionally, it is imperative to manage these densities to reduce negative externalities like congestion, air/noise pollution, lack of public spaces, loss of livelihood, etc. The study presents a comparison of the relationship between transport systems with the built form in both cities. The paper concludes with recommendations for managing densities in urban areas along with promoting low-carbon transport choices like improved non-motorized transport and public transport infrastructure and minimizing personal vehicle usage in the Global South.

Keywords: India, low-carbon transport, travel behaviour, trip length, urban densification

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Authors: Kathryn McMillan

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A recent study of 8500 adult Australians aged 16 and over revealed 62% had experienced childhood maltreatment. In response to multiple recommendations by bodies such as the Australian Law Reform Commission, parliamentary reports and stakeholder input, a number of key initiatives have been developed to grapple with the difficulties of a federal-state system and to screen and triage high-risk families navigating their way through the court system. The Lighthouse Project (LHP) is a world-first initiative of the Federal Circuit and Family Courts in Australia (FCFOCA) to screen family law litigants for major risk factors, including family violence, child abuse, alcohol or substance abuse and mental ill-health at the point of filing in all applications that seek parenting orders. It commenced on 7 December 2020 on a pilot basis but has now been expanded to 15 registries across the country. A specialist risk screen, Family DOORS, Triage has been developed – focused on improving the safety and wellbeing of families involved in the family law system safety planning and service referral, and ¬ differentiated case management based on risk level, with the Evatt List specifically designed to manage the highest risk cases. Early signs are that this approach is meeting the needs of families with multiple risks moving through the Court system. Before the LHP, there was no data available about the prevalence of risk factors experienced by litigants entering the family courts and it was often assumed that it was the litigation process that was fueling family violence and other risks such as suicidality. Data from the 2022 FCFCOA annual report indicated that in parenting proceedings, 70% alleged a child had been or was at risk of abuse, 80% alleged a party had experienced Family Violence, 74 % of children had been exposed to Family Violence, 53% alleged through substance misuse by party children had caused or was at risk of causing harm to children and 58% of matters allege mental health issues of a party had caused or placed a child at risk of harm. Those figures reveal the significant overlap between child protection and family violence, both of which are under the responsibility of state and territory governments. Since 2020, a further key initiative has been the co-location of child protection and police officials amongst a number of registries of the FCFOCA. The ability to access in a time-effective way details of family violence or child protection orders, weapons licenses, criminal convictions or proceedings is key to managing issues across the state and federal divide. It ensures a more cohesive and effective response to family law, family violence and child protection systems.

Keywords: child protection, family violence, parenting, risk screening, triage.

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Authors: Kai-Chieh Lin, Chih-Fu Wu, Hsiang Ling Hsu, Yung-Hsiang Tu, Chia-Chen Wu

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With the rapid development of computer technology, the design of computers and keyboards moves towards a trend of slimness. The change of mobile input devices directly influences users’ behavior. Although multi-touch applications allow entering texts through a virtual keyboard, the performance, feedback, and comfortableness of the technology is inferior to traditional keyboard, and while manufacturers launch mobile touch keyboards and projection keyboards, the performance has not been satisfying. Therefore, this study discussed the design factors of slim pressure-sensitive keyboards. The factors were evaluated with an objective (accuracy and speed) and a subjective evaluation (operability, recognition, feedback, and difficulty) depending on the shape (circle, rectangle, and L-shaped), thickness (flat, 3mm, and 6mm), and force (35±10g, 60±10g, and 85±10g) of the keyboard. Moreover, MANOVA and Taguchi methods (regarding signal-to-noise ratios) were conducted to find the optimal level of each design factor. The research participants, by their typing speed (30 words/ minute), were divided in two groups. Considering the multitude of variables and levels, the experiments were implemented using the fractional factorial design. A representative model of the research samples were established for input task testing. The findings of this study showed that participants with low typing speed primarily relied on vision to recognize the keys, and those with high typing speed relied on tactile feedback that was affected by the thickness and force of the keys. In the objective and subjective evaluation, a combination of keyboard design factors that might result in higher performance and satisfaction was identified (L-shaped, 3mm, and 60±10g) as the optimal combination. The learning curve was analyzed to make a comparison with a traditional standard keyboard to investigate the influence of user experience on keyboard operation. The research results indicated the optimal combination provided input performance to inferior to a standard keyboard. The results could serve as a reference for the development of related products in industry and for applying comprehensively to touch devices and input interfaces which are interacted with people.

Keywords: input performance, mobile device, slim keyboard, tactile feedback

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Authors: Alicia Yanadira Nava Fuentes, Ilse Cervantes Camacho, Amadeo José Argüelles Cruz, Ana María Balboa Verduzco

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Augmented reality promises being present in future driving, with its immersive technology let to show directions and maps to identify important places indicating with graphic elements when the car driver requires the information. On the other side, driving is considered a multitasking activity and, for some people, a complex activity where different situations commonly occur that require the immediate attention of the car driver to make decisions that contribute to avoid accidents; therefore, the main aim of the project is the instrumentation of a platform with biometric sensors that allows evaluating the performance in driving vehicles with the influence of augmented reality devices to detect the level of attention in drivers, since it is important to know the effect that it produces. In this study, the physiological sensors EPOC X (EEG), ECG06 PRO and EMG Myoware are joined in the driving test platform with a Logitech G29 steering wheel and the simulation software City Car Driving in which the level of traffic can be controlled, as well as the number of pedestrians that exist within the simulation obtaining a driver interaction in real mode and through a MSP430 microcontroller achieves the acquisition of data for storage. The sensors bring a continuous analog signal in time that needs signal conditioning, at this point, a signal amplifier is incorporated due to the acquired signals having a sensitive range of 1.25 mm/mV, also filtering that consists in eliminating the frequency bands of the signal in order to be interpretative and without noise to convert it from an analog signal into a digital signal to analyze the physiological signals of the drivers, these values are stored in a database. Based on this compilation, we work on the extraction of signal features and implement K-NN (k-nearest neighbor) classification methods and decision trees (unsupervised learning) that enable the study of data for the identification of patterns and determine by classification methods different effects of augmented reality on drivers. The expected results of this project include are a test platform instrumented with biometric sensors for data acquisition during driving and a database with the required variables to determine the effect caused by augmented reality on people in simulated driving.

Keywords: augmented reality, driving, physiological signals, test platform

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Authors: Hachul Jung, Ahee Kim, Sanghoon Lee, Dahye Kwon, Songwoo Yoon, Jinhee Moon

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We fabricated a wearable patch device including novel patch type flexible dry electrode based on carbon nanofibers (CNFs) and silicone-based elastomer (MED 6215) for real-time ECG monitoring. There are many methods to make flexible conductive polymer by mixing metal or carbon-based nanoparticles. In this study, CNFs are selected for conductive nanoparticles because carbon nanotubes (CNTs) are difficult to disperse uniformly in elastomer compare with CNFs and silver nanowires are relatively high cost and easily oxidized in the air. Wearable patch is composed of 2 parts that dry electrode parts for recording bio signal and sticky patch parts for mounting on the skin. Dry electrode parts were made by vortexer and baking in prepared mold. To optimize electrical performance and diffusion degree of uniformity, we developed unique mixing and baking process. Secondly, sticky patch parts were made by patterning and detaching from smooth surface substrate after spin-coating soft skin adhesive. In this process, attachable and detachable strengths of sticky patch are measured and optimized for them, using a monitoring system. Assembled patch is flexible, stretchable, easily skin mountable and connectable directly with the system. To evaluate the performance of electrical characteristics and ECG (Electrocardiography) recording, wearable patch was tested by changing concentrations of CNFs and thickness of the dry electrode. In these results, the CNF concentration and thickness of dry electrodes were important variables to obtain high-quality ECG signals without incidental distractions. Cytotoxicity test is conducted to prove biocompatibility, and long-term wearing test showed no skin reactions such as itching or erythema. To minimize noises from motion artifacts and line noise, we make the customized wireless, light-weight data acquisition system. Measured ECG Signals from this system are stable and successfully monitored simultaneously. To sum up, we could fully utilize fabricated wearable patch devices for real-time ECG monitoring easily.

Keywords: carbon nanofibers, ECG monitoring, flexible dry electrode, wearable patch

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Authors: Cezarina da Conceição Santinho Maurício, José Duque Vicente

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Established in 1987, the Erasmus Programme is a program for the exchange of higher education students. Its purposes are several. The mobility developed has contributed to the promotion of multiple learning, the internalization the feeling of belonging to a community, and the consolidation of cooperation between entities or universities. It also allows the experience of a European experience, considering multilingualism one of the bases of the European project and vehicle to achieve the union in diversity. The program has progressed and introduced changes Erasmus+ currently offers a wide range of opportunities for higher education, vocational education and training, school education, adult education, youth, and sport. These opportunities are open to students and other stakeholders, such as teachers. Portugal was one of the countries that readily adhered to this program, assuming itself as an instrument of internationalization of polytechnic and university higher education. Students and social work teachers have been involved in this mobility of learning and multicultural interactions. The presence and activation of this program was made possible by Portugal's joining the European Union. This event was reflected in the field of portuguese social work and contributes to its approach to the reality of european social work. Historically, the Portuguese social work has built a close connection with the Latin American world and, in particular, with Brazil. There are several examples that can be identified in the different historical stages. This is the case of the post-revolution period of 1974 and the presence of the reconceptualization movement, the struggle for enrollment in the higher education circuit, the process of winning a bachelor's degree, and postgraduate training (the first doctorates of social work were carried out in Brazilian universities). This influence is also found in the scope of the authors and the theoretical references used. This study examines the participation of graduates and students of social work in the Erasmus program. The following specific goals were outlined: to identify the host countries and universities; to investigate the dimension and type of mobility made, understand the learning and experiences acquired, identify the difficulties felt, capture their perspectives on social work and the contribution of this experience in training. In the methodological field, the option fell on a qualitative methodology, with the application of semi-structured interviews to graduates and students of social work with Erasmus mobility experience. Once the graduates agreed, the interviews were recorded and transcribed, analyzed according to the previously defined analysis categories. The findings emphasize the importance of this experience for students and graduates in informal and formal learning. The authors conclude with recommendations to reinforce this mobility, either at the individual level or as a project built for the group or collective.

Keywords: erasmus programme, graduates and students of social work, participation, social work

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Authors: Iris Vogeler, Rogerio Cichota, Armin Werner

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Dairy farms are under pressure to increase productivity while reducing environmental impacts. Effective fertiliser management practices are critical to achieve this. Determination of optimum nitrogen (N) fertilisation rates which maximise pasture growth and minimise N losses is challenging due to variability in plant requirements and likely near-future supply of N by the soil. Remote sensing can be used for mapping N nutrition status of plants and to rapidly assess the spatial variability within a field. An algorithm is, however, lacking which relates the N status of the plants to the expected yield response to additions of N. The aim of this simulation study was to develop a multi-variate model for determining N fertilisation rate for a target percentage of the maximum achievable yield based on the pasture N concentration (ii) use of an algorithm for guiding fertilisation rates, and (iii) evaluation of the model regarding pasture yield and N losses, including N leaching, denitrification and volatilisation. A simulation study was carried out using the Agricultural Production Systems Simulator (APSIM). The simulations were done for an irrigated ryegrass pasture in the Canterbury region of New Zealand. A multi-variate model was developed and used to determine monthly required N fertilisation rates based on pasture N content prior to fertilisation and targets of 50, 75, 90 and 100% of the potential monthly yield. These monthly optimised fertilisation rules were evaluated by running APSIM for a ten-year period to provide yield and N loss estimates from both nonurine and urine affected areas. Comparison with typical fertilisation rates of 150 and 400 kg N/ha/year was also done. Assessment of pasture yield and leaching from fertiliser and urine patches indicated a large reduction in N losses when N fertilisation rates were controlled by the multi-variate model. However, the reduction in leaching losses was much smaller when taking into account the effects of urine patches. The proposed approach based on biophysical modelling to develop a multi-variate model for determining optimum N fertilisation rates dependent on pasture N content is very promising. Further analysis, under different environmental conditions and validation is required before the approach can be used to help adjust fertiliser management practices to temporal and spatial N demand based on the nitrogen status of the pasture.

Keywords: APSIM modelling, optimum N fertilization rate, pasture N content, ryegrass pasture, three dimensional surface response function.

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Authors: Mehrnaz Mostafavi, Jalaledin Ghanavi

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This research investigates the production of nanoring structures through a chemical reduction approach, exploring gradual reduction processes assisted by reductant agents, leading to the formation of these specialized nanorings. The study focuses on the controlled reduction of metal atoms within these agents, crucial for shaping these nanoring structures over time. The paper commences by highlighting the wide-ranging applications of metal nanostructures across fields like Nanomedicine, Nanobiotechnology, and advanced spectroscopy methods such as Surface Enhanced Raman Spectroscopy (SERS) and Surface Enhanced Infrared Absorption Spectroscopy (SEIRA). Particularly, gold nanoparticles, especially in the nanoring configuration, have gained significant attention due to their distinctive properties, offering accessible spaces suitable for sensing and spectroscopic applications. The methodology involves utilizing human serum albumin as a reducing agent to create gold nanoparticles through a chemical reduction process. This process involves the transfer of electrons from albumin's carboxylic groups, converting them into carbonyl, while AuCl4− acquires electrons to form gold nanoparticles. Various characterization techniques like Ultraviolet–visible spectroscopy (UV-Vis), Atomic-force microscopy (AFM), and Transmission electron microscopy (TEM) were employed to examine and validate the creation and properties of the gold nanoparticles and nanorings. The findings suggest that precise and gradual reduction processes, in conjunction with optimal pH conditions, play a pivotal role in generating nanoring structures. Experiments manipulating optical properties revealed distinct responses in the visible and infrared spectrums, demonstrating the tunability of these nanorings. Detailed examinations of the morphology confirmed the formation of gold nanorings, elucidating their size, distribution, and structural characteristics. These nanorings, characterized by an empty volume enclosed by uniform walls, exhibit promising potential in the realms of Nanomedicine and Nanobiotechnology. In summary, this study presents a chemical synthesis approach using organic reducing agents to produce gold nanorings. The results underscore the significance of controlled and gradual reduction processes in crafting nanoring structures with unique optical traits, offering considerable value across diverse nanotechnological applications.

Keywords: nanoring structures, chemical reduction approach, gold nanoparticles, spectroscopy methods, nano medicine applications

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Authors: Paola Causin, Andrea Aspri, Alessandro Benfenati

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Diffuse Optical Tomography (DOT) is an emergent medical imaging technique which employs NIR light to estimate the spatial distribution of optical coefficients in biological tissues for diagnostic purposes, in a noninvasive and non-ionizing manner. DOT reconstruction is a severely ill-conditioned problem due to prevalent scattering of light in the tissue. In this contribution, we present our research in adopting hybrid knowledgedriven/data-driven approaches which exploit the existence of well assessed physical models and build upon them neural networks integrating the availability of data. Namely, since in this context regularization procedures are mandatory to obtain a reasonable reconstruction [1], we explore the use of neural networks as tools to include prior information on the solution. 2. Materials and Methods The idea underlying our approach is to leverage neural networks to solve PDE-constrained inverse problems of the form 𝒒 ∗ = 𝒂𝒓𝒈 𝒎𝒊𝒏𝒒 𝐃(𝒚, 𝒚̃), (1) where D is a loss function which typically contains a discrepancy measure (or data fidelity) term plus other possible ad-hoc designed terms enforcing specific constraints. In the context of inverse problems like (1), one seeks the optimal set of physical parameters q, given the set of observations y. Moreover, 𝑦̃ is the computable approximation of y, which may be as well obtained from a neural network but also in a classic way via the resolution of a PDE with given input coefficients (forward problem, Fig.1 box ). Due to the severe ill conditioning of the reconstruction problem, we adopt a two-fold approach: i) we restrict the solutions (optical coefficients) to lie in a lower-dimensional subspace generated by auto-decoder type networks. This procedure forms priors of the solution (Fig.1 box ); ii) we use regularization procedures of type 𝒒̂ ∗ = 𝒂𝒓𝒈𝒎𝒊𝒏𝒒 𝐃(𝒚, 𝒚̃)+ 𝑹(𝒒), where 𝑹(𝒒) is a regularization functional depending on regularization parameters which can be fixed a-priori or learned via a neural network in a data-driven modality. To further improve the generalizability of the proposed framework, we also infuse physics knowledge via soft penalty constraints (Fig.1 box ) in the overall optimization procedure (Fig.1 box ). 3. Discussion and Conclusion DOT reconstruction is severely hindered by ill-conditioning. The combined use of data-driven and knowledgedriven elements is beneficial and allows to obtain improved results, especially with a restricted dataset and in presence of variable sources of noise.

Keywords: inverse problem in tomography, deep learning, diffuse optical tomography, regularization

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Authors: Chen-Chang Lee, Po-Chou Chen, Jo-Chi Jao, Chun-Chung Lui, Leung-Chit Tsang, Lain-Chyr Hwang

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Fetal Magnetic Resonance Imaging (MRI) is a challenge task because the fetal movements could cause motion artifact in MR images. The remedy to overcome this problem is to use fast scanning pulse sequences. The Single-Shot Fast Spin-Echo (SSFSE) T2-weighted imaging technique is routinely performed and often used as a gold standard in clinical examinations. Fast spoiled gradient-echo (FSPGR) T1-Weighted Imaging (T1WI) is often used to identify fat, calcification and hemorrhage. Fast Imaging Employing Steady-State Acquisition (FIESTA) is commonly used to identify fetal structures as well as the heart and vessels. The contrast of FIESTA image is related to T1/T2 and is different from that of SSFSE. The advantages and disadvantages of these two scanning sequences for fetal imaging have not been clearly demonstrated yet. This study aimed to compare these three rapid MRI techniques (SSFSE, FIESTA, and FSPGR) for fetal MRI examinations. The image qualities and influencing factors among these three techniques were explored. A 1.5T GE Discovery 450 clinical MR scanner with an eight-channel high-resolution abdominal coil was used in this study. Twenty-five pregnant women were recruited to enroll fetal MRI examination with SSFSE, FIESTA and FSPGR scanning. Multi-oriented and multi-slice images were acquired. Afterwards, MR images were interpreted and scored by two senior radiologists. The results showed that both SSFSE and T2W-FIESTA can provide good image quality among these three rapid imaging techniques. Vessel signals on FIESTA images are higher than those on SSFSE images. The Specific Absorption Rate (SAR) of FIESTA is lower than that of the others two techniques, but it is prone to cause banding artifacts. FSPGR-T1WI renders lower Signal-to-Noise Ratio (SNR) because it severely suffers from the impact of maternal and fetal movements. The scan times for these three scanning sequences were 25 sec (T2W-SSFSE), 20 sec (FIESTA) and 18 sec (FSPGR). In conclusion, all these three rapid MR scanning sequences can produce high contrast and high spatial resolution images. The scan time can be shortened by incorporating parallel imaging techniques so that the motion artifacts caused by fetal movements can be reduced. Having good understanding of the characteristics of these three rapid MRI techniques is helpful for technologists to obtain reproducible fetal anatomy images with high quality for prenatal diagnosis.

Keywords: fetal MRI, FIESTA, FSPGR, motion artifact, SSFSE

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Authors: Jonathan Turner, Julie Doyle, Laura O’Philbin, Dympna O’Sullivan

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People living with dementia should be at the centre of decision-making regarding goals for daily living. These goals include basic activities (dressing, hygiene, and mobility), advanced activities (finances, transportation, and shopping), and meaningful activities that promote well-being (pastimes and intellectual pursuits). However, there is limited involvement of people living with dementia in the design of technology to support their goals. A project is described that is co-designing intelligent computer-based support for, and with, people affected by dementia and their carers. The technology will support self-management, empower participation in shared decision-making with carers and help people living with dementia remain healthy and independent in their homes for longer. It includes information from the patient’s care plan, which documents medications, contacts, and the patient's wishes on end-of-life care. Importantly for this work, the plan can outline activities that should be maintained or worked towards, such as exercise or social contact. The authors discuss how to integrate care goal information from such a care plan with data collected from passive sensors in the patient’s home in order to deliver individualized planning and interventions for persons with dementia. A number of scientific challenges are addressed: First, to co-design with dementia patients and their carers computerized support for shared decision-making about their care while allowing the patient to share the care plan. Second, to develop a new and open monitoring framework with which to configure sensor technologies to collect data about whether goals and actions specified for a person in their care plan are being achieved. This is developed top-down by associating care quality types and metrics elicited from the co-design activities with types of data that can be collected within the home, from passive and active sensors, and from the patient’s feedback collected through a simple co-designed interface. These activities and data will be mapped to appropriate sensors and technological infrastructure with which to collect the data. Third, the application of machine learning models to analyze data collected via the sensing devices in order to investigate whether and to what extent activities outlined via the care plan are being achieved. The models will capture longitudinal data to track disease progression over time; as the disease progresses and captured data show that activities outlined in the care plan are not being achieved, the care plan may recommend alternative activities. Disease progression may also require care changes, and a data-driven approach can capture changes in a condition more quickly and allow care plans to evolve and be updated.

Keywords: care goals, decision-making, dementia, self-care, sensors

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Authors: Kenza Benali

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Over the past decade, a number of remarkable projects in urban brownfield reconversion emerged across Canada, including the reconversion of former military bases owned by the Canada Lands Company (CLC) into sustainable communities. However, unlike other developments, the regeneration project of the former Canadian Forces Base Rockcliffe in Ottawa – which was announced as one of the most ambitious Smart growth projects in Canada – faced serious obstacles in terms of social acceptance by the local community, particularly urban minorities composed of Francophones, Indigenous and vulnerable groups who live near or on the Base. This turn of events led to the project being postponed and even reconsidered. Through an analysis of its press coverage, this research aims to understand the causes of this urban conflict which lasted for nearly ten years. The findings reveal that the conflict is not limited to the “standard” issues common to most conflicts related to urban mega-projects in the world – e.g., proximity issues (threads to the quality of the surrounding neighbourhoods; noise, traffic, pollution, New-build gentrification) often associated with NIMBY phenomena. In this case, the local actors questioned the purpose of the project (for whom and for what types of uses is it conceived?), its local implementation (to what extent are the local history and existing environment taken into account?), and the degree of implication of the local population in the decision-making process (with whom is the project built?). Moreover, the interests of the local actors have “jumped scales” and transcend the micro-territorial level of their daily life to take on a national and even international dimension. They defined an alternative view of how this project, considered strategic by his location in the nation’s capital, should be a reference as well as an international showcase of Canadian ambition and achievement in terms of urban sustainability. This vision promoted, actually, a territorial and national identity approach - in which some cultural values are highly significant (respect of social justice, inclusivity, ethnical diversity, cultural heritage, etc.)- as a counterweight to planners’ vision which is criticized as a normative/ universalist logic that ignore the territorial peculiarities.

Keywords: smart growth, brownfield reconversion, sustainable neighborhoods, Canada Lands Company, Canadian Forces Base Rockcliffe, urban conflicts

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Authors: Gulnara Galeeva, Yulia Kasperskaya

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The study deals with the relevant problem related to the formation of the efficient investment portfolio of an enterprise. The structure of the investment portfolio is connected to the degree of influence of intangible assets on the enterprise’s income. This determines the importance of research on the content of intangible assets. However, intangible assets studies do not take into consideration how the enterprise state can affect the content and the importance of intangible assets for the enterprise`s income. This affects accurateness of the calculations. In order to study this problem, the research was divided into several stages. In the first stage, intangible assets were classified based on their synergies as the underlying intangibles and the additional intangibles. In the second stage, this classification was applied. It showed that the lifecycle model and the theory of abrupt development of the enterprise, that are taken into account while designing investment projects, constitute limit cases of a more general theory of bifurcations. The research identified that the qualitative content of intangible assets significant depends on how close the enterprise is to being in crisis. In the third stage, the author developed and applied the Wide Pairwise Comparison Matrix method. This allowed to establish that using the ratio of the standard deviation to the mean value of the elements of the vector of priority of intangible assets makes it possible to estimate the probability of a full-blown crisis of the enterprise. The author has identified a criterion, which allows making fundamental decisions on investment feasibility. The study also developed an additional rapid method of assessing the enterprise overall status based on using the questionnaire survey with its Director. The questionnaire consists only of two questions. The research specifically focused on the fundamental role of stochastic resonance in the emergence of bifurcation (crisis) in the economic development of the enterprise. The synergetic approach made it possible to describe the mechanism of the crisis start in details and also to identify a range of universal ways of overcoming the crisis. It was outlined that the structure of intangible assets transforms into a more organized state with the strengthened synchronization of all processes as a result of the impact of the sporadic (white) noise. Obtained results offer managers and business owners a simple and an affordable method of investment portfolio optimization, which takes into account how close the enterprise is to a state of a full-blown crisis.

Keywords: analytic hierarchy process, bifurcation, investment portfolio, intangible assets, wide matrix

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Authors: Anderson Braga Mendes, Wallington Felipe de Almeida, Cicero Medeiros da Silva

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This study aimed to assess the lifespan of the fish transposition system of the Itaipu Power Plant (Brazil/Paraguay) by using 3D hydrodynamic modeling and Churchill trapping effiency in order to identify the sedimentological equilibrium configuration in the main pond of the Piracema Channel, which is part of a 10 km hydraulic circuit that enables fish migration from downstream to upstream (and vice-versa) the Itaipu Dam, overcoming a 120 m water drop. For that, bottom data from 2002 (its opening year) and 2015 were collected and analyzed, besides bed material at 12 stations to the purpose of identifying their granulometric profiles. The Shields and Yalin and Karahan diagrams for initiation of motion of bed material were used to determine the critical bed shear stress for the sedimentological equilibrium state based on the sort of sediment (grain size) to be found at the bottom once the balance is reached. Such granulometry was inferred by analyzing the grosser material (fine and medium sands) which inflows the pond and deposits in its backwater zone, being adopted a range of diameters within the upper and lower limits of that sand stratification. The software Delft 3D was used in an attempt to compute the bed shear stress at every station under analysis. By modifying the input bathymetry of the main pond of the Piracema Channel so as to the computed bed shear stress at each station fell within the intervals of acceptable critical stresses simultaneously, it was possible to foresee the bed configuration of the main pond when the sedimentological equilibrium is reached. Under such condition, 97% of the whole pond capacity will be silted, and a shallow water course with depths ranging from 0.2 m to 1.5 m will be formed; in 2002, depths ranged from 2 m to 10 m. Out of that water path, the new bottom will be practically flat and covered by a layer of water 0.05 m thick. Thus, in the future the main pond of the Piracema Channel will lack its purpose of providing a resting place for migrating fish species, added to the fact that it may become an insurmountable barrier for medium and large sized specimens. Everything considered, it was estimated that its lifespan, from the year of its opening to the moment of the sedimentological equilibrium configuration, will be approximately 95 years–almost half of the computed lifespan of Itaipu Power Plant itself. However, it is worth mentioning that drawbacks concerning the silting in the main pond will start being noticed much earlier than such time interval owing to the reasons previously mentioned.

Keywords: 3D hydrodynamic modeling, Churchill trapping efficiency, fish crossing system, Itaipu power plant, lifespan, sedimentological equilibrium

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Authors: Meshal M. Abdullah, Rusty A. Feagin, Layla Musawi

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When humans mismanage arid landscapes, soil erosion can become a primary mechanism that leads to desertification. This study focuses on applying soil erosion models to a disturbed landscape in Umm Nigga, Kuwait, and identifying its predicted change under restoration plans, The northern portion of Umm Nigga, containing both coastal and desert ecosystems, falls within the boundaries of the Demilitarized Zone (DMZ) adjacent to Iraq, and has been fenced off to restrict public access since 1994. The central objective of this project was to utilize GIS and remote sensing to compare the MPSIAC (Modified Pacific South West Inter Agency Committee), EMP (Erosion Potential Method), and USLE (Universal Soil Loss Equation) soil erosion models and determine their applicability for arid regions such as Kuwait. Spatial analysis was used to develop the necessary datasets for factors such as soil characteristics, vegetation cover, runoff, climate, and topography. Results showed that the MPSIAC and EMP models produced a similar spatial distribution of erosion, though the MPSIAC had more variability. For the MPSIAC model, approximately 45% of the land surface ranged from moderate to high soil loss, while 35% ranged from moderate to high for the EMP model. The USLE model had contrasting results and a different spatial distribution of the soil loss, with 25% of area ranging from moderate to high erosion, and 75% ranging from low to very low. We concluded that MPSIAC and EMP were the most suitable models for arid regions in general, with the MPSIAC model best. We then applied the MPSIAC model to identify the amount of soil loss between coastal and desert areas, and fenced and unfenced sites. In the desert area, soil loss was different between fenced and unfenced sites. In these desert fenced sites, 88% of the surface was covered with vegetation and soil loss was very low, while at the desert unfenced sites it was 3% and correspondingly higher. In the coastal areas, the amount of soil loss was nearly similar between fenced and unfenced sites. These results implied that vegetation cover played an important role in reducing soil erosion, and that fencing is much more important in the desert ecosystems to protect against overgrazing. When applying the MPSIAC model predictively, we found that vegetation cover could be increased from 3% to 37% in unfenced areas, and soil erosion could then decrease by 39%. We conclude that the MPSIAC model is best to predict soil erosion for arid regions such as Kuwait.

Keywords: soil erosion, GIS, modified pacific South west inter agency committee model (MPSIAC), erosion potential method (EMP), Universal soil loss equation (USLE)

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Authors: Jeh Patel, Chandrahas Paidi, Ahmed Hambaba

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Traditional methods for analyzing athlete movement often lack the detail and immediacy required for optimal training. This project aims to address this limitation by developing a Real-time human pose estimation system specifically designed to enhance athlete training across various sports. This system leverages the power of convolutional neural networks (CNNs) to provide a comprehensive and immediate analysis of an athlete’s movement patterns during training sessions. The core architecture utilizes dilated convolutions to capture crucial long-range dependencies within video frames. Combining this with the robust encoder-decoder architecture to further refine pose estimation accuracy. This capability is essential for precise joint localization across the diverse range of athletic poses encountered in different sports. Furthermore, by quantifying movement efficiency, power output, and range of motion, the system provides data-driven insights that can be used to optimize training programs. Pose estimation data analysis can also be used to develop personalized training plans that target specific weaknesses identified in an athlete’s movement patterns. To overcome the limitations posed by outdoor environments, the project employs strategies such as multi-camera configurations or depth sensing techniques. These approaches can enhance pose estimation accuracy in challenging lighting and occlusion scenarios, where pose estimation accuracy in challenging lighting and occlusion scenarios. A dataset is collected From the labs of Martin Luther King at San Jose State University. The system is evaluated through a series of tests that measure its efficiency and accuracy in real-world scenarios. Results indicate a high level of precision in recognizing different poses, substantiating the potential of this technology in practical applications. Challenges such as enhancing the system’s ability to operate in varied environmental conditions and further expanding the dataset for training were identified and discussed. Future work will refine the model’s adaptability and incorporate haptic feedback to enhance the interactivity and richness of the user experience. This project demonstrates the feasibility of an advanced pose detection model and lays the groundwork for future innovations in assistive enhancement technologies.

Keywords: computer vision, deep learning, human pose estimation, U-NET, CNN

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Authors: Andrea Giacomelli, Luciano Massetti, Elena Maggi, Antonio Raschi

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The presentation will report the activities managed during the Summer of 2017 by a team composed by staff from a University Department, a National Research Council Institute, and an outreach NGO, collecting measurements of night sky brightness and other information on artificial lighting, in order to characterize light pollution issues on portions of the Tuscan coast, in Central Italy. These activities combine measurements collected by the principal scientists, citizen science observations led by students, and outreach events targeting a broad audience. This campaign aggregates the efforts of three actors: the BuioMetria Partecipativa project, which started collecting light pollution data on a national scale in 2008 with an environmental engineering and free/open source GIS core team; the Institute of Biometeorology from the National Research Council, with ongoing studies on light and urban vegetation and a consolidated track record in environmental education and citizen science; the Department of Biology from the University of Pisa, which started experiments to assess the impact of light pollution in coastal environments in 2015. While the core of the activities concerns in situ data, the campaign will account also for remote sensing data, thus considering heterogeneous data sources. The aim of the campaign is twofold: (1) To test actions of citizen and student engagement in monitoring sky brightness (2) To collect night sky brightness data and test a protocol for applications to studies on the ecological impact of light pollution, with a special focus on marine coastal ecosystems. The collaboration of an interdisciplinary team in the study of artificial lighting issues is not a common case in Italy, and the possibility of undertaking the campaign in Tuscany has the added value of operating in one of the territories where it is possible to observe both sites with extremely high lighting levels, and areas with extremely low light pollution, especially in the Southern part of the region. Combining environmental monitoring and communication actions in the context of the campaign, this effort will contribute to the promotion of night skies with a good quality as an important asset for the sustainability of coastal ecosystems, as well as to increase citizen awareness through star gazing, night photography and actively participating in field campaign measurements.

Keywords: citizen science, light pollution, marine coastal biodiversity, environmental education

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Authors: Bencherif Kada

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In the forest management practice, landscape and Mediterranean forest are never posed as linked objects. But sustainable forestry requires the valorization of the forest landscape, and this aim involves assessing the spatial distribution of biodiversity by mapping forest landscaped units and subunits and by monitoring the environmental trends. This contribution aims to highlight, through object-oriented classifications, the landscaped biodiversity of the National Park of Tlemcen (Algeria). The methodology used is based on ground data and on the basic processing units of object-oriented classification, that are segments, so-called image-objects, representing a relatively homogenous units on the ground. The classification of Landsat Enhanced Thematic Mapper plus (ETM+) imagery is performed on image objects and not on pixels. Advantages of object-oriented classification are to make full use of meaningful statistic and texture calculation, uncorrelated shape information (e.g., length-to-width ratio, direction, and area of an object, etc.), and topological features (neighbor, super-object, etc.), and the close relation between real-world objects and image objects. The results show that per object classification using the k-nearest neighbor’s method is more efficient than per pixel one. It permits to simplify of the content of the image while preserving spectrally and spatially homogeneous types of land covers such as Aleppo pine stands, cork oak groves, mixed groves of cork oak, holm oak, and zen oak, mixed groves of holm oak and thuja, water plan, dense and open shrub-lands of oaks, vegetable crops or orchard, herbaceous plants, and bare soils. Texture attributes seem to provide no useful information, while spatial attributes of shape and compactness seem to be performant for all the dominant features, such as pure stands of Aleppo pine and/or cork oak and bare soils. Landscaped sub-units are individualized while conserving the spatial information. Continuously dominant dense stands over a large area were formed into a single class, such as dense, fragmented stands with clear stands. Low shrublands formations and high wooded shrublands are well individualized but with some confusion with enclaves for the former. Overall, a visual evaluation of the classification shows that the classification reflects the actual spatial state of the study area at the landscape level.

Keywords: forest, oaks, remote sensing, diversity, shrublands

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Authors: Varis Ransibrahmanakul, Doug Pirhalla, Scott Sheridan, Cameron Lee

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U.S. coastal areas and ecosystems are facing multiple sea level rise threats and effects: heavy rain events, cyclones, and changing wind and weather patterns all influence coastal flooding, sedimentation, and erosion along critical barrier islands and can strongly impact habitat resiliency and water quality in protected habitats. These impacts are increasing over time and have accelerated the need for new tracking techniques, models and tools of flood risk to support enhanced preparedness for coastal management and mitigation. To address this issue, NOAA National Ocean Service (NOS) evaluated new metrics from satellite altimetry AVISO/Copernicus and MODIS IR flood extents to isolate nodes atmospheric variability indicative of elevated sea level and nuisance flood events. Using de-trended time series of cross-shelf sea surface heights (SSH), we identified specific Self Organizing Maps (SOM) nodes and transitions having a strongest regional association with oceanic spatial patterns (e.g., heightened downwelling favorable wind-stress and enhanced southward coastal transport) indicative of elevated coastal sea levels. Results show the impacts of the inverted barometer effect as well as the effects of surface wind forcing; Ekman-induced transport along broad expanses of the U.S. eastern coastline. Higher sea levels and corresponding localized flooding are associated with either pattern indicative of enhanced on-shore flow, deepening cyclones, or local- scale winds, generally coupled with an increased local to regional precipitation. These findings will support an integration of satellite products and will inform seasonal outlook model development supported through NOAAs Climate Program Office and NOS office of Center for Operational Oceanographic Products and Services (CO-OPS). Overall results will prioritize ecological areas and coastal lab facilities at risk based on numbers of nuisance flood projected and inform coastal management of flood risk around low lying areas subjected to bank erosion.

Keywords: AVISO satellite altimetry SSHA, MODIS IR flood map, nuisance flood, remote sensing of flood

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