Search results for: subtle change detection and quantification

Authors: Monish Sengupta, Benjamin Heydecker, Daniel Woodland

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New train control systems rely mainly on Automatic Train Protection (ATP) and Automatic Train Operation (ATO) dynamically to control the speed and hence performance. The ATP and the ATO form the vital element within the CBTC (Communication Based Train Control) and within the ERTMS (European Rail Traffic Management System) system architectures. Reliable and accurate measurement of train location, speed and acceleration are vital to the operation of train control systems. In the past, all CBTC and ERTMS system have deployed a balise or equivalent to correct the uncertainty element of the train location. Typically a CBTC train is allowed to miss only one balise on the track, after which the Automatic Train Protection (ATP) system applies emergency brake to halt the service. This is because the location uncertainty, which grows within the train control system, cannot tolerate missing more than one balise. Balises contribute a significant amount towards wayside maintenance and studies have shown that balises on the track also forms a constraint for future track layout change and change in speed profile.This paper investigates the causes of the location uncertainty that is currently experienced and considers whether it is possible to identify an effective filter to ascertain, in conjunction with appropriate sensors, more accurate speed, distance and location for a CBTC driven train without the need of any external balises. An appropriate sensor fusion algorithm and intelligent sensor selection methodology will be deployed to ascertain the railway location and speed measurement at its highest precision. Similar techniques are already in use in aviation, satellite, submarine and other navigation systems. Developing a model for the speed control and the use of Kalman filter is a key element in this research. This paper will summarize the research undertaken and its significant findings, highlighting the potential for introducing alternative approaches to train positioning that would enable removal of all trackside location correction balises, leading to huge reduction in maintenances and more flexibility in future track design.

Keywords: ERTMS, CBTC, ATP, ATO

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Authors: Albert Kwabena Osei Konadu

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Pterocarpus erinaceus, also known as Rosewood, is tropical wood, endemic in forest savannah transition zones within the middle and northern portion of Ghana. Its economic viability has made it increasingly popular and in high demand, leading to widespread conservation concerns. Ghana’s forest resource management regime for these ecozones is mainly on conservation and very little on resource utilization. Consequently, commercial logging management standards are at teething stage and not fully developed, leading to a deficiency in the monitoring of logging operations and quantification of harvested trees volumes. Tree information form (TIF); a volume estimation and tracking regime, has proven to be an effective, sustainable management tool for regulating timber resource extraction in the high forest zones of the country. This work aims to generate TIF that can track and capture requisite parameters to accurately estimate the volume of harvested rosewood within forest savannah transition zones. Tree information forms were created on three scenarios of individual billets, stacked billets and conveying vessel basis. These TIFs were field-tested to deduce the most viable option for the tracking and estimation of harvested volumes of rosewood using the smallian and cubic volume estimation formula. Overall, four districts were covered with individual billets, stacked billets and conveying vessel scenarios registering mean volumes of 25.83m3,45.08m3 and 32.6m3, respectively. These adduced volumes were validated by benchmarking to assigned volumes of the Forestry Commission of Ghana and known standard volumes of conveying vessels. The results did indicate an underestimation of extracted volumes under the quotas regime, a situation that could lead to unintended overexploitation of the species. The research revealed conveying vessels route is the most viable volume estimation and tracking regime for the sustainable management of the Pterocarpous erinaceus species as it provided a more practical volume estimate and data extraction protocol.

Keywords: convention on international trade in endangered species, cubic volume formula, forest transition savannah zones, pterocarpus erinaceus, smallian’s volume formula, tree information form

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Authors: Darius Jakimavicius

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Artificial intelligence is the subject of intense debate in the international arena, identified both as a technological breakthrough and as a component of the strategic stability effect. Both the kinetic and non-kinetic development of AI and its application in the national strategies of the great powers may trigger a change in the security situation. Artificial intelligence is generally faster, more capable and more efficient than humans, and there is a temptation to transfer decision-making and control responsibilities to artificial intelligence. Artificial intelligence, which, once activated, can select and act on targets without further intervention by a human operator, blurs the boundary between human or robot (machine) warfare, or perhaps human and robot together. Artificial intelligence acts as a force multiplier that speeds up decision-making and reaction times on the battlefield. The role of humans is increasingly moving away from direct decision-making and away from command and control processes involving the use of force. It is worth noting that the autonomy and precision of AI systems make the process of strategic stability more complex. Deterrence theory is currently in a phase of development in which deterrence is undergoing further strain and crisis due to the complexity of the evolving models enabled by artificial intelligence. Based on the concept of strategic stability and deterrence theory, it is appropriate to develop further research on the development and impact of AI in order to assess AI from both a scientific and technical perspective: to capture a new niche in the scientific literature and academic terminology, to clarify the conditions for deterrence, and to identify the potential uses, impacts and possibly quantities of AI. The research problem is the impact of artificial intelligence developed by great powers on strategic stability. This thesis seeks to assess the impact of AI on strategic stability and deterrence principles, with human exclusion from the decision-making and control loop as a key axis. The interaction between AI and human actions and interests can determine fundamental changes in great powers' defense and deterrence, and the development and application of AI-based great powers strategies can lead to a change in strategic stability.

Keywords: artificial inteligence, strategic stability, deterrence theory, decision making loop

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Authors: Kwangmin Joo

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Automatic detection of lumbar vertebrae and classification method is proposed for evaluating the degree of disc narrowing. Prior to classification, deep learning based segmentation is applied to detect individual lumbar vertebra. M-net is applied to segment five lumbar vertebrae and fine-tuning segmentation is employed to improve the accuracy of segmentation. Using the features extracted from previous step, clustering technique, k-means clustering, is applied to estimate the degree of disc space narrowing under four grade scoring system. As preliminary study, techniques proposed in this research could help building an automatic scoring system to diagnose the severity of disc narrowing from X-ray images.

Keywords: Disc space narrowing, Degenerative disc disorders, Deep learning based segmentation, Clustering technique

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Authors: Rohit T. P., Sahil Athrij, Sasi Gopalan

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Currently, the content entertainment industry is dominated by mobile devices. As the trends slowly shift towards Augmented/Virtual Reality applications the computational demands on these devices are increasing exponentially and we are already reaching the limits of hardware optimizations. This paper proposes a software solution to this problem. By leveraging the capabilities of cloud computing we can offload the work from mobile devices to dedicated rendering servers that are way more powerful. But this introduces the problem of latency. This paper introduces a protocol that can achieve high-performance low latency Augmented/Virtual Reality experience. There are two parts to the protocol, 1) In-flight compression The main cause of latency in the system is the time required to transmit the camera frame from client to server. The round trip time is directly proportional to the amount of data transmitted. This can therefore be reduced by compressing the frames before sending. Using some standard compression algorithms like JPEG can result in minor size reduction only. Since the images to be compressed are consecutive camera frames there won't be a lot of changes between two consecutive images. So inter-frame compression is preferred. Inter-frame compression can be implemented efficiently using WebGL but the implementation of WebGL limits the precision of floating point numbers to 16bit in most devices. This can introduce noise to the image due to rounding errors, which will add up eventually. This can be solved using an improved interframe compression algorithm. The algorithm detects changes between frames and reuses unchanged pixels from the previous frame. This eliminates the need for floating point subtraction thereby cutting down on noise. The change detection is also improved drastically by taking the weighted average difference of pixels instead of the absolute difference. The kernel weights for this comparison can be fine-tuned to match the type of image to be compressed. 2) Dynamic Load distribution Conventional cloud computing architectures work by offloading as much work as possible to the servers, but this approach can cause a hit on bandwidth and server costs. The most optimal solution is obtained when the device utilizes 100% of its resources and the rest is done by the server. The protocol balances the load between the server and the client by doing a fraction of the computing on the device depending on the power of the device and network conditions. The protocol will be responsible for dynamically partitioning the tasks. Special flags will be used to communicate the workload fraction between the client and the server and will be updated in a constant interval of time ( or frames ). The whole of the protocol is designed so that it can be client agnostic. Flags are available to the client for resetting the frame, indicating latency, switching mode, etc. The server can react to client-side changes on the fly and adapt accordingly by switching to different pipelines. The server is designed to effectively spread the load and thereby scale horizontally. This is achieved by isolating client connections into different processes.

Keywords: 2D kernelling, augmented reality, cloud computing, dynamic load distribution, immersive experience, mobile computing, motion tracking, protocols, real-time systems, web-based augmented reality application

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Authors: Karina Zaccari, Ernesto Cordeiro Marujo

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This paper presents a Machine Learning (ML) approach to support Meningitis diagnosis in patients at a children’s hospital in Sao Paulo, Brazil. The aim is to use ML techniques to reduce the use of invasive procedures, such as cerebrospinal fluid (CSF) collection, as much as possible. In this study, we focus on predicting the probability of Meningitis given the results of a blood and urine laboratory tests, together with the analysis of pain or other complaints from the patient. We tested a number of different ML algorithms, including: Adaptative Boosting (AdaBoost), Decision Tree, Gradient Boosting, K-Nearest Neighbors (KNN), Logistic Regression, Random Forest and Support Vector Machines (SVM). Decision Tree algorithm performed best, with 94.56% and 96.18% accuracy for training and testing data, respectively. These results represent a significant aid to doctors in diagnosing Meningitis as early as possible and in preventing expensive and painful procedures on some children.

Keywords: machine learning, medical diagnosis, meningitis detection, pediatric research

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Authors: Zahra Khoshnood, Mehdi Kazaie, Sajedeh Neisi

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In 2013, 24 fish samples were taken from two fishery regions in the north of Persian Gulf near the Iranian coastal lines. The two flatfishes were Yellofin seabream (Acanthopagrus latus) and Longtail tuna (Thannus tonggol). We analyzed total Hg concentration of liver and muscle tissues by Mercury Analyzer (model LECO AMA 254). The average concentration of total Hg in edible Muscle tissue of deep-Flounder was measured in Bandar-Abbas and was found to be 18.92 and it was 10.19 µg.g-1 in Bandar-Lengeh. The corresponding values for Oriental sole were 8.47 and 0.08 µg.g-1. The average concentration of Hg in liver tissue of deep-Flounder, in Bandar-Abbas was 25.49 and that in Bandar-Lengeh was 12.52 µg.g-1.the values for Oriental sole were 11.88 and 3.2 µg.g-1 in Bandar-Abbas and Bandar-Lengeh, respectively.

Keywords: mercury, Acanthopagrus latus, Thannus tonggol, Persian Gulf

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Authors: Magdy Danial Riad

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Introduction: The ability of our world to support the expanding population after 2050 is at risk due to the food system's global role in poor health, climate change, and resource depletion. Healthy, equitable, and sustainable food systems must be achieved from the point of production through consumption in order to meet several of the sustainable development goals (SDG) targets. There is evidence that changing the local food environment can effectively change dietary habits in a community. The purpose of this article is to outline the policy initiatives taken by local governments to support environmentally friendly eating habits. Methods: Five databases were searched for peer-reviewed articles that described local government authorities' implementation of environmentally sustainable eating habits, were located in cities that had signed the Milan Urban Food Policy Pact, were published after 2015, were available in English, and described policy interventions. Data extraction was a two-step approach that started with extracting information from the included study and ended with locating information unique to policies in the grey literature. Results: 45 papers that described a variety of policy initiatives from low-, middle-, and high-income countries met the inclusion criteria. A variety of desired dietary behaviors were the focus of policy action, including reducing food waste, procuring food locally and in season, boosting breastfeeding, avoiding overconsumption, and consuming more plant-based meals and fewer items derived from animals. Conclusions: In order to achieve SDG targets, local governments are under pressure to implement evidence-based interventions. This study can help direct local governments toward evidence-based policy measures to improve regional food systems and support ecologically friendly eating habits.

Keywords: meals, planet, poor health, eating habits

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Authors: Lidija R. Jevrić, Sanja O. Podunavac-Kuzmanović, Strahinja Z. Kovačević

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This study considers the selection of the most suitable in silico molecular descriptors that could be used for s-triazine pesticides characterization. Suitable descriptors among topological, geometrical and physicochemical are used for quantitative structure-retention relationships (QSRR) model establishment. Established models were obtained using linear regression (LR) and multiple linear regression (MLR) analysis. In this paper, MLR models were established avoiding multicollinearity among the selected molecular descriptors. Statistical quality of established models was evaluated by standard and cross-validation statistical parameters. For detection of similarity or dissimilarity among investigated s-triazine pesticides and their classification, principal component analysis (PCA) and hierarchical cluster analysis (HCA) were used and gave similar grouping. This study is financially supported by COST action TD1305.

Keywords: chemometrics, classification analysis, molecular descriptors, pesticides, regression analysis

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Authors: Akbar Gharbali, Ali Abbasian Ardekani, Afshin Mohammadi

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Introduction: Thyroid nodules have an incidence of 33-68% in the general population. More than 5-15% of these nodules are malignant. Early detection and treatment of thyroid nodules increase the cure rate and provide optimal treatment. Between the medical imaging methods, Ultrasound is the chosen imaging technique for assessment of thyroid nodules. The confirming of the diagnosis usually demands repeated fine-needle aspiration biopsy (FNAB). So, current management has morbidity and non-zero mortality. Objective: To explore diagnostic potential of automatic texture analysis (TA) methods in differentiation benign and malignant thyroid nodules by ultrasound imaging in order to help for reliable diagnosis and monitoring of the thyroid nodules in their early stages with no need biopsy. Material and Methods: The thyroid US image database consists of 70 patients (26 benign and 44 malignant) which were reported by Radiologist and proven by the biopsy. Two slices per patient were loaded in Mazda Software version 4.6 for automatic texture analysis. Regions of interests (ROIs) were defined within the abnormal part of the thyroid nodules ultrasound images. Gray levels within an ROI normalized according to three normalization schemes: N1: default or original gray levels, N2: +/- 3 Sigma or dynamic intensity limited to µ+/- 3σ, and N3: present intensity limited to 1% - 99%. Up to 270 multiscale texture features parameters per ROIs per each normalization schemes were computed from well-known statistical methods employed in Mazda software. From the statistical point of view, all calculated texture features parameters are not useful for texture analysis. So, the features based on maximum Fisher coefficient and the minimum probability of classification error and average correlation coefficients (POE+ACC) eliminated to 10 best and most effective features per normalization schemes. We analyze this feature under two standardization states (standard (S) and non-standard (NS)) with Principle Component Analysis (PCA), Linear Discriminant Analysis (LDA) and Non-Linear Discriminant Analysis (NDA). The 1NN classifier was performed to distinguish between benign and malignant tumors. The confusion matrix and Receiver operating characteristic (ROC) curve analysis were used for the formulation of more reliable criteria of the performance of employed texture analysis methods. Results: The results demonstrated the influence of the normalization schemes and reduction methods on the effectiveness of the obtained features as a descriptor on discrimination power and classification results. The selected subset features under 1%-99% normalization, POE+ACC reduction and NDA texture analysis yielded a high discrimination performance with the area under the ROC curve (Az) of 0.9722, in distinguishing Benign from Malignant Thyroid Nodules which correspond to sensitivity of 94.45%, specificity of 100%, and accuracy of 97.14%. Conclusions: Our results indicate computer-aided diagnosis is a reliable method, and can provide useful information to help radiologists in the detection and classification of benign and malignant thyroid nodules.

Keywords: ultrasound imaging, thyroid nodules, computer aided diagnosis, texture analysis, PCA, LDA, NDA

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Authors: Lorenzo Gontrani, Marilena Carbone, Domenica Tommasa Donia, Elvira Maria Bauer, Pietro Tagliatesta

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One of the fields where DES shows remarkable added values is the synthesis Of inorganic materials, in particular nanoparticles. In this field, the higher- ent and highly-tunable nano-homogeneities of DES structure give origin to a marked templating effect, a precious role that has led to the recent bloom of a vast number of studies exploiting these new synthesis media to prepare Nanomaterials and composite structures of various kinds. In this contribution, the most recent developments in the field will be reviewed, and some ex-citing examples of novel metal oxide nanoparticles syntheses using non-toxic type-IV Deep Eutectic Solvents will be described. The prepared materials possess nanometric dimensions and show flower-like shapes. The use of the pre- pared nanoparticles as fluorescent materials for the detection of various contaminants is under development.

Keywords: metal deep eutectic solvents, nanoparticles, inorganic synthesis, type IV DES, lamellar

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Authors: Krzysztof Pomorski

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In the given work we present universal mathematical framework for modeling of cattle farm system that can set and validate various hypothesis that can be tested against experimental data. The presented work is preliminary but it is expected to be valid tool for future deeper analysis that can result in new class of prediction methods allowing early detection of cow dieseaes as well as cow performance. Therefore the presented work shall have its meaning in agriculture models and in machine learning as well. It also opens the possibilities for incorporation of certain class of biological models necessary in modeling of cow behavior and farm performance that might include the impact of environment on the farm system. Particular attention is paid to the model of coupled oscillators that it the basic building hypothesis that can construct the model showing certain periodic or quasiperiodic behavior.

Keywords: coupled ordinary differential equations, cattle farm system, numerical methods, stochastic differential equations

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Authors: Eszter Repasi, Akos Koller

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Our genetic information determines our look, physiology, sports performance and all our features. Maximizing the performances of athletes have adopted a science-based approach to the nutritional support. Nowadays genetics studies have blended with nutritional sciences, and a dynamically evolving, new research field have appeared. Nutritional genomics is needed to be used by nutritional experts. This is a recent field of nutritional science, which can provide a solution to reach the best sport performance using correlations between the athlete’s genome, nutritions, molecules, included human microbiome (links between food, microbiome and epigenetics), nutrigenomics and nutrigenetics. Nutritional genomics has a tremendous potential to change the future of dietary guidelines and personal recommendations. Experts need to use new technology to get information about the athletes, like nutritional genomics profile (included the determination of the oral and gut microbiome and DNA coded reaction for food components), which can modify the preparation term and sports performance. The influence of nutrients on the genes expression is called Nutrigenomics. The heterogeneous response of gene variants to nutrients, dietary components is called Nutrigenetics. The human microbiome plays a critical role in the state of health and well-being, and there are more links between food or nutrition and the human microbiome composition, which can develop diseases and epigenetic changes as well. A nutritional genomics-based profile of athletes can be the best technic for a dietitian to make a unique sports nutrition diet plan. Using functional food and the right food components can be effected on health state, thus sports performance. Scientists need to determine the best response, due to the effect of nutrients on health, through altering genome promote metabolites and result changes in physiology. Nutritional biochemistry explains why polymorphisms in genes for the absorption, circulation, or metabolism of essential nutrients (such as n-3 polyunsaturated fatty acids or epigallocatechin-3-gallate), would affect the efficacy of that nutrient. Controlled nutritional deficiencies and failures, prevented the change of health state or a newly discovered food intolerance are observed by a proper medical team, can support better sports performance. It is important that the dietetics profession informed on gene-diet interactions, that may be leading to optimal health, reduced risk of injury or disease. A special medical application for documentation and monitoring of data of health state and risk factors can uphold and warn the medical team for an early action and help to be able to do a proper health service in time. This model can set up a personalized nutrition advice from the status control, through the recovery, to the monitoring. But more studies are needed to understand the mechanisms and to be able to change the composition of the microbiome, environmental and genetic risk factors in cases of athletes.

Keywords: gene-diet interaction, multidisciplinary team, microbiome, diet plan

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Authors: Janaina Camile Pasqual Lofhagen, David Savarese, Veronika Vazhnik

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The urgency of the climate crisis requires both innovation and practicality. The energy transition framework allows industry to deliver resilient cities, enhance adaptability to change, pursue energy objectives such as growth or efficiencies, and increase renewable energy. This paper investigates a real-world application perspective for the use of biogas in Brazil and the U.S.. It will examine interventions to provide a foundation of infrastructure, as well as the tangible benefits for policy-makers crafting law and providing incentives.

Keywords: resilience, vulnerability, risks, biogas, sustainability.

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Authors: Massimo Ferrari, Maria Sole Pagliari

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Pollution is a classic example of economic externality: agents who produce it do not face direct costs from emissions. Therefore, there are no direct economic incentives for reducing pollution. One way to address this market failure would be directly taxing emissions. However, because emissions are global, governments might as well find it optimal to wait let foreign countries to tax emissions so that they can enjoy the benefits of lower pollution without facing its direct costs. In this paper, we first document the empirical relation between pollution and economic output with static and dynamic regression methods. We show that there is a negative relation between aggregate output and the stock of pollution (measured as the stock of CO₂ emissions). This relationship is also highly non-linear, increasing at an exponential rate. In the second part of the paper, we develop and estimate a two-country, two-sector model for the US and the euro area. With this model, we aim at analyzing how the public sector should respond to higher emissions and what are the direct costs that these policies might have. In the model, there are two types of firms, brown firms (which produce a polluting technology) and green firms. Brown firms also produce an externality, CO₂ emissions, which has detrimental effects on aggregate output. As brown firms do not face direct costs from polluting, they do not have incentives to reduce emissions. Notably, emissions in our model are global: the stock of CO₂ in the economy affects all countries, independently from where it is produced. This simplified economy captures the main trade-off between emissions and production, generating a classic market failure. According to our results, the current level of emission reduces output by between 0.4 and 0.75%. Notably, these estimates lay in the upper bound of the distribution of those delivered by studies in the early 2000s. To address market failure, governments should step in introducing taxes on emissions. With the tax, brown firms pay a cost for polluting hence facing the incentive to move to green technologies. Governments, however, might also adopt a beggar-thy-neighbour strategy. Reducing emissions is costly, as moves production away from the 'optimal' production mix of brown and green technology. Because emissions are global, a government could just wait for the other country to tackle climate change, ripping the benefits without facing any costs. We study how this strategic game unfolds and show three important results: first, cooperation is first-best optimal from a global prospective; second, countries face incentives to deviate from the cooperating equilibria; third, tariffs on imported brown goods (the only retaliation policy in case of deviation from the cooperation equilibrium) are ineffective because the exchange rate would move to compensate. We finally study monetary policy under when costs for climate change rise and show that the monetary authority should react stronger to deviations of inflation from its target.

Keywords: climate change, general equilibrium, optimal taxation, monetary policy

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Authors: O. M. Lemine

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The effect of milling parameters on the structural and magnetic properties of nickel powder was investigated. The samples were characterized by X-ray powder diffraction and vibrating sample magnetometer (VSM). The results did not reveal any phase change of nickel during the milling. The average crystallite size decreases with a prolongation of milling times, whereas the lattice parameters increase. The hysteresis loop reveals the intrinsic magnetic behaviour. It was observed an increase in the magnetization which can be correlated to the volume expansion showed by XRD results.

Keywords: nickel powders, nanocrystallines, XRD, VSM

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Authors: Sajidullah Khan, Najeeb Ullah, Wang Yin Chai, Chai Soo See

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In this paper, we propose an approach to remove impulse and Poisson noise from X-ray images. Many filters have been used for impulse noise removal from color and gray scale images with their own strengths and weaknesses but X-ray images contain Poisson noise and unfortunately there is no intelligent filter which can detect impulse and Poisson noise from X-ray images. Our proposed filter uses the upgraded layer discrimination approach to detect both Impulse and Poisson noise corrupted pixels in X-ray images and then restores only those detected pixels with a simple efficient and reliable one line equation. Our Proposed algorithms are very effective and much more efficient than all existing filters used only for Impulse noise removal. The proposed method uses a new powerful and efficient noise detection method to determine whether the pixel under observation is corrupted or noise free. Results from computer simulations are used to demonstrate pleasing performance of our proposed method.

Keywords: X-ray image de-noising, impulse noise, poisson noise, PRWF

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Authors: Launcelot McGrath

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The Coronavirus disease 2019 (COVID-19) has spread rapidly around the world, resulting in high mortality rates and very large numbers of people requiring medical treatment in ICU. Management of patient hospitalisation is a critical aspect to control this disease and reduce chaos in the healthcare systems. Remote monitoring provides a solution to protect vulnerable and elderly high-risk patients. Continuous remote monitoring of oxygen saturation, respiratory rate, heart rate, and temperature, etc., provides medical systems with up-to-the-minute information about their patients' statuses. Remote monitoring also limits the spread of infection by reducing hospital overcrowding. This paper examines the potential of remote monitoring for Covid-19 to assist in the rapid identification of patients at risk, facilitate the detection of patient deterioration, and enable early interventions.

Keywords: remote monitoring, patient care, oxygen saturation, Covid-19, hospital management

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Authors: Etleva Hamzaraj, Eva Kica, Anila Paparisto, Pranvera Lazo

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Worldwide demographic developments of recent decades have been associated with negative environmental consequences. For this reason, there is a growing interest in assessing the state of natural ecosystems or assessing human impact on them. In this respect, this study aims to evaluate the change in water quality of the Mat River for a period of about ten years to highlight human impact. In one year, period of study, several biological and environmental parameters are determined to evaluate river water quality, and the data collected are compared with those of a similar study in 2007. Samples are collected every month in five stations evenly distributed along the river. Total coliform bacteria, the number of heterotrophic bacteria in water, and benthic macroinvertebrates are used as biological parameters of water quality. The most probable number index is used for evaluation of total coliform bacteria in water, while the number of heterotrophic bacteria is determined by counting colonies on plates with Plate Count Agar, cultivated with 0.1 ml sample after series dilutions. Benthic macroinvertebrates are analyzed by the number of individuals per taxa, the value of biotic index, EPT Richness Index value and tolerance value. Environmental parameters like pH, temperature, and electrical conductivity are measured onsite. As expected, the bacterial load was higher near urban areas, and the pollution increased with the course of the river. The maximum concentration of fecal coliforms was 1100 MPN/100 ml in summer and near the most urbanized area of the river. The data collected during this study show that after about ten years, there is a change in water quality of Mat River. According to a similar study carried out in 2007, the water of Mat River was of ‘excellent’ quality. But, according to this study, the water was classified as of ‘excellent’ quality only in one sampling site, near river source, while in all other stations was of ‘good’ quality. This result is based on biological and environmental parameters measured. The human impact on the quality of water of Mat River is more than evident.

Keywords: water quality, coliform bacteria, MPN index, benthic macroinvertebrates, biotic index

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Authors: Mandana Karimi, Martha McMahon

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One of the most important consequences of water scarcity worldwide is the increase in conflicts over water issues, reduced access to clean water, food shortages, energy shortages, and reduced economic development. The extreme weather conditions in British Columbia are because of climate change, which is leading to water scarcity becoming a serious issue affecting British Columbians, aquatic ecosystems, the BC water policy, agriculture, and the economy. In light of climate change and water stress, the British Columbia government introduced a new water legislation in 2016 named the Water Sustainability Act to manage water resources in British Columbia. So, this study aimed to present a deep understanding emanating from the political and social dimensions of the new water policy in BC in the agriculture sector and which sociological paradigm governs the current water policy (WSA) in BC. Policy analysis based on the water problem representation approach was used to present the problem and solutions identified by the water policy in the agricultural sector in BC. The results of the policy analysis highlighted that the Water Sustainability Act is governed by a positivist and modernist approach because the groundwater license is the measurable situation to access the adequate quantity of water for the farmers. In addition, by the positivist paradigm water resources are conceptualized as a commodity to be bought and sold. Under the positivist approach, the measurable parameter of groundwater is also applied based on the top-down approach for water management to show the use of water resources for economic development. In addition, the findings of the policy analysis suggest that alternative paradigms, such as relational ontology, ecofeminism, and indigenous knowledge, could be applied in introducing water policies to shift from the positivist or modernist paradigm. These new paradigms present the potential for environmental policies like the Water Sustainability Act, based on partnership, and collaboration and with an explicit emphasis on protecting water for nature.

Keywords: water governance, Water Sustainability Act, water policy, small-scale farmer, policy analysis

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Authors: Clemencia Gomez

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Geology is currently absent from Colombia's education system, leading to a lack of geological awareness that hinders essential scientific training about Earth and its spatial and temporal dimensions. Understanding geological concepts is crucial for tackling challenges like climate change, sustainable resource management, geological risk mitigation, and groundwater management. Citizens have the right to receive a comprehensive scientific education that enhances their critical thinking regarding social, environmental, and economic issues. Geological sciences are vital in this context, as they enable the sustainable use of the planet's resources and effective management of human impacts. Additionally, geoethics should be integral to every citizen's education, highlighting the necessity of responsibly utilizing natural resources found in the Earth's surface and subsurface, which are fundamental to many everyday products. The Colombian associations of Geology aims to address these gaps by advocating for the appointment of geologists in municipalities. These professionals would assist in reviewing technical aspects of urban planning, identifying geological risks, pinpointing water supply opportunities, supporting sustainable mineral-energy projects, and promoting geological education in schools. The role of a professional in Earth sciences is crucial for municipalities for several reasons: Natural Resource Management: Earth scientists help in managing and conserving natural resources such as water, minerals, and soil. Their expertise ensures sustainable use and helps prevent depletion. Environmental Protection: They assess environmental impacts and advise on policies to protect ecosystems and biodiversity. This is vital for maintaining the health of local environments. Disaster Preparedness and Response: Professionals in this field analyze geological hazards like earthquakes, floods, and landslides. They contribute to developing early warning systems and emergency response plans, which can save lives and property. Climate Change Mitigation: Earth scientists study climate patterns and contribute to strategies for mitigating climate change impacts. This includes advising on land use planning and developing resilience strategies for communities. Urban Planning and Development: Their expertise is essential in urban planning, ensuring that infrastructure development considers geological and environmental factors. This helps prevent construction in hazardous areas and promotes sustainable development. Public Education and Awareness: They play a vital role in educating the public about Earth-related issues, fostering greater community engagement in environmental conservation and disaster preparedness. In summary, professionals in Earth sciences significantly contribute to the sustainability, safety, and well-being of municipalities and their residents.

Keywords: social geology, safety, sustainability, municipalities

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Authors: Neera Kapoor

Abstract:

Background: Knockdown Resistance (KDR) is one of the mechanisms of insecticide resistance in insects caused by the reduced target site sensitivity i.e. voltage gated sodium channel (VGSC) rendering it less sensitive to the toxic effects of DDT and pyrethroids. In this study, we evaluated insecticide susceptibility and its underlying KDR mechanism in eight Ae. aegypti and five Ae. albopictus field populations. Methodology: Field population was collected from four different geographical regions of India covering 18 districts of ten states. For genotyping of twelve KDR alleles in Ae. aegypti field populations, three PCR based assays were used; with DNA sequencing; ASPCR; PCR-RFLP. Genomic DNA was isolated, and three partial domains (II, III, and IV) of VGSC were amplified and sequenced. Results: Molecular screening for common KDR mutations, revealed the presence of five mutations viz. S989P, V1016G, T1520I, F1534C/L. Two novel mutations were observed, first at T1520 (ACC) residue where a C > T substitution at the second position of codon results in amino acid change to Isoleucine (ATC). Second mutation was an alternative point mutation at F1534 (TTC) residue where a substitution of T > C at the first position of codon results in an amino acid change to Leucine (CTC). ASPCRs were not accurate, so three PCR-RFLP assays were developed for genotyping of five KDR alleles in Ae. aegypti; viz. T1520I, F1534C/L. Representative samples of all genotypes (n=200) were sequenced to validate the newly developed PCR based assays for Ae. aegypti. Genotyping results showed that 989P is linked to 1016G and novel mutation 1520I was always found with 1534C allele. Conclusion: Present study confirmed the presence of DDT and pyrethroid resistance among Ae. aegypti populations in India and for the first time reported KDR mutations in this species from India including two novel mutations. Results of present study lead us to infer that, at least five KDR mutations (S989P, V1016G, T1530I, F1534C, and F1534L) can be seen as a potential marker for DDT/pyrethroid resistance.

Keywords: F1534C, F1534L, S989P, T1530I, V1016G

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Authors: Suin Seo, Sung-Il Cho

Abstract:

Background: The use of mobile apps for smoking cessation has grown exponentially in recent years. Yet, there were limited researches which evaluated the quality of smoking cessation apps to our knowledge. In most cases, a clinical practice guideline which is focused on clinical physician was used as an evaluation tool. Objective: The objective of this study was to develop a user-centered measure for quality of mobile smoking cessation apps. Methods: A literature search was conducted to identify articles containing explicit smoking cessation guideline for smoker published until January 2018. WHO’s guide for tobacco users to quit was adopted for evaluation tool which assesses smoker-oriented contents of smoking cessation apps. Compared to the clinical practice guideline, WHO guideline was designed for smokers (non-specialist). On the basis of existing criteria which was developed based on 2008 clinical practice guideline for Treating Tobacco Use and Dependence, evaluation tool was modified and developed by an expert panel. Results: There were five broad categories of criteria that were identified including five objective quality scales: enhancing motivation, assistance with a planning and making quit attempts, preparation for relapse, self-efficacy, connection to smoking. Enhancing motivation and assistance with planning and making quit attempts were similar to contents of clinical practice guideline, but preparation for relapse, self-efficacy and connection to smoking (environment or habit which reminds of smoking) only existed on WHO guideline. WHO guideline had more user-centered elements than clinical guideline. Especially, self-efficacy is the most important determinant of behavior change in accordance with many health behavior change models. With the WHO guideline, it is now possible to analyze the content of the app in the light of a health participant, not a provider. Conclusion: The WHO guideline evaluation tool is a simple, reliable and smoker-centered tool for assessing the quality of mobile smoking cessation apps. It can also be used to provide a checklist for the development of new high-quality smoking cessation apps.

Keywords: smoking cessation, evaluation, mobile application, WHO, guideline

Procedia PDF Downloads 193

Authors: Ejaz Ashraf, Raheel Babar, Muhammad Yaseen, Hafiz Khurram Shurjeel, Nosheen Fatima

Abstract:

Main purpose of this study was to assess adoption level of farmers for quinoa cultivation after they had been taught through training and visit extension approach. At this time of the 21^st century, population structure, climate change, food requirements and eating habits of people are changing rapidly. In this scenario, farmers must play their key role in sustainable crop development and production through adoption of new crops that may also be helpful to overcome the issue of food insecurity as well as reducing poverty in rural areas. Its cultivation in Pakistan is at the early stages and there is a need to raise awareness among farmers to grow quinoa crops. In the middle of the 2015, a training and visit extension approach was used to raise awareness and convince farmers to grow quinoa in the area. During training and visit extension program, 80 farmers were randomly selected for the training of quinoa cultivation. Later on, these farmers trained 60 more farmers living into their neighborhood. After six months, a survey was conducted with all 140 farmers to assess the impact of the training and visit program on adoption level of respondents for the quinoa crop. The survey instrument was developed with the help of literature review and other experts of the crop. Validity and reliability of the instrument were checked before complete data collection. The data were analyzed by using SPSS. Multiple regression analysis was used for interpretation of the results from the survey, which indicated that factors like information/ training, change in agronomic and plant protection practices play a key role in the adoption of quinoa cultivation by respondents. In addition, the model explains more than 50% of variation in the adoption level of respondents. It is concluded that farmers need timely information for improved knowledge of agronomic and plant protection practices to adopt cultivation of the quinoa crop in the area.

Keywords: farmers, quinoa, adoption, contact, training and visit

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Authors: M. Ghosh, A. Miroux, L. A. I. Kestens

Abstract:

At molecular or micrometre scale, practically all materials are neither homogeneous nor isotropic. The concept of texture is used to identify the structural features that cause the properties of a material to be anisotropic. For metallic materials, the anisotropy of the mechanical behaviour originates from the crystallographic nature of plastic deformation, and is therefore controlled by the crystallographic texture. Anisotropy in mechanical properties often constitutes a disadvantage in the application of materials, as it is often illustrated by the earing phenomena during drawing. However, advantages may also be attained when considering other properties (e.g. optimization of magnetic behaviour to a specific direction) by controlling texture through thermo-mechanical processing). Nevertheless, in order to have better control over the final properties it is essential to relate texture with materials processing route and subsequently optimise their performance. However, up to date, few studies have been reported about the evolution of texture in 6061 aluminium alloy during warm processing (from room temperature to 250ºC). In present investigation, recrystallized 6061 aluminium alloy samples were subjected to tensile and plane strain compression (PSC) at room and warm temperatures. The gradual change of texture following both deformation modes were measured and discussed. Tensile tests demonstrate the mechanism at low strain while PSC does the same at high strain and eventually simulate the condition of rolling. Cube dominated texture of the initial rolled and recrystallized AA6061 sheets were replaced by domination of S and R components after PSC at room temperature, warm temperature (250ºC) though did not reflect any noticeable deviation from room temperature observation. It was also noticed that temperature has no significant effect on the evolution of grain morphology during PSC. The band contrast map revealed that after 30% deformation the substructure inside the grain is mainly made of series of parallel bands. A tendency for decrease of Cube and increase of Goss was noticed after tensile deformation compared to as-received material. Like PSC, texture does not change after deformation at warm temperature though. n-fibre was noticed for all the three textures from Goss to Cube.

Keywords: AA 6061, deformation, temperature, tensile, PSC, texture

Procedia PDF Downloads 487

Authors: Seyed Mahdi Jameii

Abstract:

Underwater wireless sensor networks have been attracting the interest of many ‎researchers lately, and the past three decades have beheld the rapid progress of ‎underwater acoustic communication. One of the major problems in underwater wireless ‎sensor networks is how to transfer data from the moving node to the base stations and ‎choose the optimized route for data transmission. Secure routing in underwater ‎wireless sensor network (UWCNs) is necessary for packet delivery. Some routing ‎protocols are proposed for underwater wireless sensor networks. However, a few ‎researches have been done on secure routing in underwater sensor networks. In this ‎article, a secure routing protocol is provided to resist against wormhole and sybil ‎attacks. The results indicated acceptable performance in terms of increasing the packet ‎delivery ratio with regards to the attacks, increasing network lifetime by creating ‎balance in the network energy consumption, high detection rates against the attacks, ‎and low-end to end delay.‎

Keywords: attacks, routing, security, underwater wireless sensor networks

Procedia PDF Downloads 423

Authors: Baha Eddine Aissou, Aichouche Belhadj Aissa

Abstract:

Light detection and ranging (LiDAR) is an active remote sensing technology used for several applications. Airborne LiDAR is becoming an important technology for the acquisition of a highly accurate dense point cloud. A classification of airborne laser scanning (ALS) point cloud is a very important task that still remains a real challenge for many scientists. Support vector machine (SVM) is one of the most used statistical learning algorithms based on kernels. SVM is a non-parametric method, and it is recommended to be used in cases where the data distribution cannot be well modeled by a standard parametric probability density function. Using a kernel, it performs a robust non-linear classification of samples. Often, the data are rarely linearly separable. SVMs are able to map the data into a higher-dimensional space to become linearly separable, which allows performing all the computations in the original space. This is one of the main reasons that SVMs are well suited for high-dimensional classification problems. Only a few training samples, called support vectors, are required. SVM has also shown its potential to cope with uncertainty in data caused by noise and fluctuation, and it is computationally efficient as compared to several other methods. Such properties are particularly suited for remote sensing classification problems and explain their recent adoption. In this poster, the SVM classification of ALS LiDAR data is proposed. Firstly, connected component analysis is applied for clustering the point cloud. Secondly, the resulting clusters are incorporated in the SVM classifier. Radial basic function (RFB) kernel is used due to the few numbers of parameters (C and γ) that needs to be chosen, which decreases the computation time. In order to optimize the classification rates, the parameters selection is explored. It consists to find the parameters (C and γ) leading to the best overall accuracy using grid search and 5-fold cross-validation. The exploited LiDAR point cloud is provided by the German Society for Photogrammetry, Remote Sensing, and Geoinformation. The ALS data used is characterized by a low density (4-6 points/m²) and is covering an urban area located in residential parts of the city Vaihingen in southern Germany. The class ground and three other classes belonging to roof superstructures are considered, i.e., a total of 4 classes. The training and test sets are selected randomly several times. The obtained results demonstrated that a parameters selection can orient the selection in a restricted interval of (C and γ) that can be further explored but does not systematically lead to the optimal rates. The SVM classifier with hyper-parameters is compared with the most used classifiers in literature for LiDAR data, random forest, AdaBoost, and decision tree. The comparison showed the superiority of the SVM classifier using parameters selection for LiDAR data compared to other classifiers.

Keywords: classification, airborne LiDAR, parameters selection, support vector machine

Procedia PDF Downloads 151

Authors: Luvindran Sugumaran, Mohd Nashrul Mohd Zubir, Kazi Md Salim Newaz, Tuan Zaharinie Tuan Zahari, Suazlan Mt Aznam, Aiman Mohd Halil

Abstract:

With reference to Energy Roadmap 2050, the minimization of greenhouse gas emissions and the enhancement of energy efficiency are the two key factors that could facilitate a radical change in the world's energy infrastructure. However, the energy demands of electronic devices skyrocketed with the advent of the digital age. Currently, the two-phase cooling technique based on phase change pool boiling heat transfer has received a lot of attention because of its potential to fully utilize the latent heat of the fluid and produce a highly effective heat dissipation capacity while keeping the equipment's operating temperature within an acceptable range. There are numerous strategies available for the alteration of heating surfaces, but finding the best, simplest, and most dependable one remains a challenge. Lately, surface texturing via laser ablation has been used in a variety of investigations, demonstrating its significant potential for enhancing the pool boiling heat transfer performance. In this research, the nucleate pool boiling heat transfer performance of laser-structured copper surfaces of different patterns was investigated. The bare copper surface serves as a reference to compare the performance of laser-structured surfaces. It was observed that the heat transfer coefficients were increased with the increase of surface area ratio and the ratio of the peak-to-valley height of the microstructure. Laser machined grain structure produced extra nucleation sites, which ultimately caused the improved pool boiling performance. Due to an increase in nucleation site density and surface area, the enhanced nucleate boiling served as the primary heat transfer mechanism. The pool boiling performance of the laser-structured copper surfaces is superior to the bare copper surface in all aspects.

Keywords: heat transfer coefficient, laser structuring, micro structured surface, pool boiling

Procedia PDF Downloads 89

Authors: Luvindran Sugumaran, Mohd Nashrul Mohd Zubir, Kazi Md Salim Newaz, Tuan Zaharinie Tuan Zahari, Suazlan Mt Aznam, Aiman Mohd Halil

Abstract:

With reference to Energy Roadmap 2050, the minimization of greenhouse gas emissions, and the enhancement of energy efficiency are the two key factors that could facilitate a radical change in the world's energy infrastructure. However, the energy demands of electronic devices skyrocketed with the advent of the digital age. Currently, the two-phase cooling technique based on phase change pool boiling heat transfer has received a lot of attention because of its potential to fully utilize the latent heat of the fluid and produce a highly effective heat dissipation capacity while keeping the equipment's operating temperature within an acceptable range. There are numerous strategies available for the alteration of heating surfaces, but to find the best, simplest, and most dependable one remains a challenge. Lately, surface texturing via laser ablation has been used in a variety of investigations, demonstrating its significant potential for enhancing the pool boiling heat transfer performance. In this research, the nucleate pool boiling heat transfer performance of laser-structured copper surfaces of different patterns was investigated. The bare copper surface serves as a reference to compare the performance of laser-structured surfaces. It was observed that the heat transfer coefficients were increased with the increase of surface area ratio and the ratio of the peak-to-valley height of the microstructure. Laser machined grain structure produced extra nucleation sites, which ultimately caused the improved pool boiling performance. Due to an increase in nucleation site density and surface area, the enhanced nucleate boiling served as the primary heat transfer mechanism. The pool boiling performance of the laser-structured copper surfaces is superior to the bare copper surface in all aspects.

Keywords: heat transfer coefficient, laser structuring, micro structured surface, pool boiling

Procedia PDF Downloads 86

Authors: Luvindran Sugumaran, Mohd Nashrul Mohd Zubir, Kazi Md. Salim Newaz, Tuan Zaharinie Tuan Zahari, Suazlan Mt Aznam, Aiman Mohd Halil

Abstract:

With reference to Energy Roadmap 2050, the minimization of greenhouse gas emissions and the enhancement of energy efficiency are the two key factors that could facilitate a radical change in the world's energy infrastructure. However, the energy demands of electronic devices skyrocketed with the advent of the digital age. Currently, the two-phase cooling technique based on phase change pool boiling heat transfer has received a lot of attention because of its potential to fully utilize the latent heat of the fluid and produce a highly effective heat dissipation capacity while keeping the equipment's operating temperature within an acceptable range. There are numerous strategies available for the alteration of heating surfaces, but to find the best, simplest, and most dependable one remains a challenge. Lately, surface texturing via laser ablation has been used in a variety of investigations, demonstrating its significant potential for enhancing the pool boiling heat transfer performance. In this research, the nucleate pool boiling heat transfer performance of laser-structured copper surfaces of different patterns was investigated. The bare copper surface serves as a reference to compare the performance of laser-structured surfaces. It was observed that the heat transfer coefficients were increased with the increase of surface area ratio and the ratio of the peak-to-valley height of the microstructure. Laser-machined grain structure produced extra nucleation sites, which ultimately caused the improved pool boiling performance. Due to an increase in nucleation site density and surface area, the enhanced nucleate boiling served as the primary heat transfer mechanism. The pool boiling performance of the laser-structured copper surfaces is superior to the bare copper surface in all aspects.

Keywords: heat transfer coefficient, laser structuring, micro structured surface, pool boiling

Procedia PDF Downloads 88