Search results for: post classification change detection

Authors: Vinu Elias Jacob, Manoj Kumar Kini

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Disasters of all types are occurring more frequently and are becoming more costly than ever due to various manmade factors including climate change. A better utilisation of the concept of governance and management within disaster risk reduction is inevitable and of utmost importance. There is a need to explore the role of pre- and post-disaster public policies. The role of urban planning/design in shaping the opportunities of households, individuals and collectively the settlements for achieving recovery has to be explored. Governance strategies that can better support the integration of disaster risk reduction and management has to be examined. The main aim is to thereby build the resilience of individuals and communities and thus, the states too. Resilience is a term that is usually linked to the fields of disaster management and mitigation, but today has become an integral part of planning and design of cities. Disaster resilience broadly describes the ability of an individual or community to 'bounce back' from disaster impacts, through improved mitigation, preparedness, response, and recovery. The growing population of the world has resulted in the inflow and use of resources, creating a pressure on the various natural systems and inequity in the distribution of resources. This makes cities vulnerable to multiple attacks by both natural and man-made disasters. Each urban area needs elaborate studies and study based strategies to proceed in the discussed direction. Cochin in Kerala is the fastest and largest growing city with a population of more than 26 lakhs. The main concern that has been looked into in this paper is making cities resilient by designing a framework of strategies based on urban design principles for an immediate response system especially focussing on the city of Cochin, Kerala, India. The paper discusses, understanding the spatial transformations due to disasters and the role of spatial planning in the context of significant disasters. The paper also aims in developing a model taking into consideration of various factors such as land use, open spaces, transportation networks, physical and social infrastructure, building design, and density and ecology that can be implemented in any city of any context. Guidelines are made for the smooth evacuation of people through hassle-free transport networks, protecting vulnerable areas in the city, providing adequate open spaces for shelters and gatherings, making available basic amenities to affected population within reachable distance, etc. by using the tool of urban design. Strategies at the city level and neighbourhood level have been developed with inferences from vulnerability analysis and case studies.

Keywords: disaster management, resilience, spatial planning, spatial transformations

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Authors: Juliza Hidayati, Sawarni Hasibuan

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PT. XYZ is a manufacturing company that produces Crude Palm Oil (CPO). The fierce competition in the global markets not only between companies but also a competition between supply chains. This research aims to analyze the supply chain and value chain of Crude Palm Oil (CPO) in the company. Data analysis method used is qualitative analysis and quantitative analysis. The qualitative analysis describes supply chain and value chain, while the quantitative analysis is used to find out value added and the establishment of the value chain. Based on the analysis, the value chain of crude palm oil (CPO) in the company consists of four main actors that are suppliers of raw materials, processing, distributor, and customer. The value chain analysis consists of two actors; those are palm oil plantation and palm oil processing plant. The palm oil plantation activities include nurseries, planting, plant maintenance, harvesting, and shipping. The palm oil processing plant activities include reception, sterilizing, thressing, pressing, and oil classification. The value added of palm oil plantations was 72.42% and the palm oil processing plant was 10.13%.

Keywords: palm oil, value chain, value added, supply chain

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Authors: Liang Zhou, Xiaojing Zhu, Yin Lu

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Danshen can induce the angiogenesis in advanced ischemic heart disease while inhibiting the angiogenesis in cancer. Additionally, Danshen mainly contains two groups of ingredients: the hydrophilic phenolic acids (danshensu, caffeic acid and salvianolic acid B), and the lipophilic tanshinones (dihydrotanshinone I, tanshinone II A, and cryptotanshinone). The lipophilic tanshinones reduced the VEGF- and bFGF-induced proliferation of HUVECs in dose-dependent manner, but cannot perform in others. Conversely, caffeic acid and salvianolic acid B had the opposite effect. Danshensu inhibited the VEGF- and bFGF-induced migration of HUVECs, and others were not. Most of them interrupted the forming capillary-like structures of HUVECs, except the danshensu and caffeic acid. Oppositely, caffeic acid enhanced the ability of forming capillary-like structures of HUVECs. Ultimately, the lipophilic tanshinones, danshensu and salvianolic acid B inhibited the angiogenesis, whereas the caffeic acid induced the angiogenesis. These data provide useful information for the classification of ingredients of Danshen for angiogenesis.

Keywords: angiogenesis, Danshen, HUVECs, ingredients

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Authors: Khalil Aryanfar, Shahrzad Sanjari, Elmira Hafez, Pariya Gholipor

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The aim of this study was to Evaluate and compare the male and female students’ life skills of theoretical, technical-vocational and Job and Knowledge branches of secondary high school period. The research method is descriptive - survey Research population was 5892 students from three high schools in Tehran, sample size was determined 342 patients according to Morgan’s table and by stratified random sampling. The data collection tool was a questionnaire designed by the researchers that the reliability was more than 85/0 respectively. Data was anglicized by Kryskal Wallis and Mann-Whitney U-test. In three branches of theoretical, technical-vocational and Job and Knowledge The variables of academic achievement, the importance of organization, problem solving, seeking knowledge, good habits, mental and physical self-concept, family orientation and future orientation was not significant differences, in the variables of cooperative behavior, and ready for change was but significant differences. Variables such as academic achievement, seek knowledge, good habits, mental and physical, seeking direction to future cooperative behavior between boys and girls with the confidence of at least 95/0 and the variable ready for change among boys and girls by ensuring 0932 / There was an However, the importance of variables, problem solving, self-concept and family orientation was not significantly different.

Keywords: life skills, high school, theoretical, technical-vocational, job and knowledge

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Authors: Mark Linden, Michael Brown, Lynne Marsh, Maria Truesdale, Stuart Todd, Nathan Hughes, Trisha Forbes, Rachel Leonard

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Background: The COVID-19 pandemic exacerbated the already significant strain placed on family carers of people with profound and multiple intellectual disabilities (PMID), given the withdrawal of many services during lockdown. The aim of this study was to explore the experiences of family carers of people with PMID during the COVID-19 pandemic. Methods: Online focus groups were conducted with family carers (n=126) from across the UK and the Republic of Ireland. Participants were asked about their experiences of the COVID-19 pandemic, coping strategies, and challenges faced. Focus groups were audio recorded, transcribed verbatim and analyzed through thematic analysis. Findings: Three themes emerged from our analysis of the data: (i) COVID-19 as a double-edged sword, (ii) The struggle for support (iii) the Constant nature of caring. These included 11 subthemes: (i) ‘COVID-19 as a catalyst for change’, ‘Challenges during COVID-19: dealing with change’, ‘Challenges during COVID-19: fear of COVID-19’, ‘The online environment: the new normal’ (ii) ‘Invisibility of male carers’, ‘Carers supporting carers’, ‘The only service you get is lip service: non-existent services’, ‘Knowing your rights’ (iii) ‘Emotional response to the caring role: Feeling devalued’, ‘Emotional response to the caring role: Desperation of caring’, ‘Multiple demands of the caring role.’ Conclusions: Poor or inconsistent access to services and support has been an ongoing difficulty for many family carers. The COVID-19 pandemic has only further intensified these difficulties, increasing family carers' stress. There is an urgent need to design services, such as online support programs, in partnership with family carers that adequately address their needs.

Keywords: intellectual disabilities, family carer, COVID-19, disability

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Authors: Kazi Enamul Hoque

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Initiatives on sustainable development are currently aggressively pursued throughout the world. The Malaysian government has developed key policies and strategies for over 30 years to achieve the nation’s policy objectives which are designed to mitigate the issues of security, energy efficiency and environmental impact to meet the rising energy demand. Malaysia’s current focus is on developing effective policies on renewable energy (RE) in order to reduce dependency on fossil fuel and contribute towards mitigating the effects of climate change. In this light mass awareness should be considered as the highest priority to protect the environment and to escape disaster due to climate change. Schools can be the reliable and effective foundation to prepare students to get familiar with environmental issues such as renewable and non-renewable energy sources. Teachers can play a vital role to create awareness among students about the advantages and disadvantages of using different renewable and nonrenewable energy resources. Thus, this study aims to investigate teachers’ knowledge, perceptions and attitudes towards renewable energy through a survey aiming a sustainable energy future. Five hundred sets of questionnaires were distributed to the school teachers in Malaysia. Total 420 questionnaires were returned of which 410 were complete to analyze. Finding shows that teachers are very familiar with the renewable energy like solar, wind and also geothermal. Most teachers were not sure about the Photovoltaics and biodiesel. Furthermore, teachers are also aware that primary energy in Malaysia is imported fossil fuels. Most teachers heard about the renewable energy in Malaysia and only few claims that they did not hear of such things and the others said that they never heard of it. The outcomes of the study will assist the energy policy makers to use teachers to create mass awareness of energy usages for future planning.

Keywords: Malaysia, non-renewable energy, renewable energy, school teacher

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Authors: Jin Liang, Q. Li, Yue Qi, Liying Wang, Wenhua Yu, Xun Liu

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Fertility is very important for women. The gender role of women gives them the fertility ability. Giving birth to a boy or a girl might have effect on the mother’s life in the past in China. However, with the shifting of traditional attitudes and views, the women's social status and living situation have been transformed. Although the pregnancy and childbirth can still bring them a major impact on their lives, the form and content of the impact have changed. So we investigated the rural women of Hebei province after birth to reflect their living situation changes before and after birth and the differences of their living situation from women in the past by using a self-made rural women life situation change questionnaire, the index of well-being, and the index of general effect questionnaire. It has shown that women’s living situation after babybirth in Hebei province is well in general, and their mind and body, as well as their interpersonal relationships and social status, were all enhanced. The women’s living situation after babybirth was positively related to and could anticipate subjective happiness, and specifically, the rural women’s mind and body, their interpersonal relationship and social status in rural women life situation change questionnaire are the main predicted factors to subjective happiness. Furthermore, the women’s self-identification on female roles was influenced by the children’s gender. Specifically, women with only one daughter had highest self-identification on female roles, consisting with their families' concept about children’s gender, which indicated family values have a great effect on women’s self-identification on female roles in rural. Moreover, the women’s living situation and subjective happiness are both impacted by home incomes.

Keywords: rural women, parturition, well-being, life quality

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Authors: Bahareh Ansari

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Background: The Open Government Data (OGD) movement in the last decade has encouraged many government organizations around the world to make their data publicly available to advance democratic processes. But current open data platforms have not yet reached to their full potential in supporting all interested parties. To make the data useful and understandable for everyone, scholars suggested that opening the data should be supplemented by visualization. However, different visualizations of the same information can dramatically change an individual’s cognitive and emotional experience in working with the data. This study reviews the data visualization literature to create a list of the methods empirically tested to enhance users’ performance and experience in working with a visualization tool. This list can be used in evaluating the OGD visualization practices and informing the future open data initiatives. Methods: Previous reviews of visualization literature categorized the visualization outcomes into four categories including recall/memorability, insight/comprehension, engagement, and enjoyment. To identify the papers, a search for these outcomes was conducted in the abstract of the publications of top-tier visualization venues including IEEE Transactions for Visualization and Computer Graphics, Computer Graphics, and proceedings of the CHI Conference on Human Factors in Computing Systems. The search results are complemented with a search in the references of the identified articles, and a search for 'open data visualization,' and 'visualization evaluation' keywords in the IEEE explore and ACM digital libraries. Articles are included if they provide empirical evidence through conducting controlled user experiments, or provide a review of these empirical studies. The qualitative synthesis of the studies focuses on identification and classifying the methods, and the conditions under which they are examined to positively affect the visualization outcomes. Findings: The keyword search yields 760 studies, of which 30 are included after the title/abstract review. The classification of the included articles shows five distinct methods: interactive design, aesthetic (artistic) style, storytelling, decorative elements that do not provide extra information including text, image, and embellishment on the graphs), and animation. Studies on decorative elements show consistency on the positive effects of these elements on user engagement and recall but are less consistent in their examination of the user performance. This inconsistency could be attributable to the particular data type or specific design method used in each study. The interactive design studies are consistent in their findings of the positive effect on the outcomes. Storytelling studies show some inconsistencies regarding the design effect on user engagement, enjoyment, recall, and performance, which could be indicative of the specific conditions required for the use of this method. Last two methods, aesthetics and animation, have been less frequent in the included articles, and provide consistent positive results on some of the outcomes. Implications for e-government: Review of the visualization best-practice methods show that each of these methods is beneficial under specific conditions. By using these methods in a potentially beneficial condition, OGD practices can promote a wide range of individuals to involve and work with the government data and ultimately engage in government policy-making procedures.

Keywords: best practices, data visualization, literature review, open government data

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Authors: Mina Ganji Morad, Maziar Azadisoleimanieh, Sina Ganji Morad

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A green roof is formed by green plants alive and has many positive impacts in the regional climatic, as well as indoor. Green roof system to prevent solar radiation plays a role in the cooling space. The cooling is done by reducing thermal fluctuations on the exterior of the roof and by increasing the roof heat capacity which cause to keep the space under the roof cool in the summer and heating rate increases during the winter. A roof garden is one of the recommended ways to reduce energy consumption in large cities. Despite the scale of the city green roofs have effective functions, such as beautiful view of city and decontaminating the urban landscape and reduce mental stress, and in an exchange of energy and heat from outside to inside spaces. This article is based on a review of 20 articles and 10 books and valid survey results on the positive effects of green roofs to prevent energy waste in the building. According to these publications, three of the conventional roof, green roof typical and green roof with certain administrative details (layers of glass) and the use of resistant plants and shrubs have been analyzed and compared their heat transfer. The results of these studies showed that one of the best green roof systems for mountainous climate is tree and shrub system that in addition to being resistant to climate change in mountainous regions, will benefit from the other advantages of green roof. Due to the severity of climate change in mountainous areas it is essential to prevent the waste of buildings heating and cooling energy. Proper climate design can greatly help to reduce energy.

Keywords: green roof, heat transfer, reducing energy consumption, mountainous areas, sustainable architecture

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Authors: Ryan Chalk, G. M. Shafiullah

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Climate change is a pertinent issue facing governments and societies around the world. The industrial revolution has resulted in a steady increase in the average global temperature. The mining and energy production industries have been significant contributors to this change prompting government to intervene by promoting low emission technology within these sectors. This paper initially reviews the energy problem in Australia and the mining sector with a focus on the energy requirements and production methods utilised in Western Australia (WA). Renewable energy in the form of utility-scale solar photovoltaics (PV) provides a solution to these problems by providing emission-free energy which can be used to supplement the existing natural gas turbines in operation at the proposed site. This research presents a custom renewable solution for the mining site considering the specific township network, local weather conditions, and seasonal load profiles. A summary of the required PV output is presented to supply slightly over 50% of the towns power requirements during the peak (summer) period, resulting in close to full coverage in the trench (winter) period. Dig Silent Power Factory Software has been used to simulate the characteristics of the existing infrastructure and produces results of integrating PV. Large scale PV penetration in the network introduce technical challenges, that includes; voltage deviation, increased harmonic distortion, increased available fault current and power factor. Results also show that cloud cover has a dramatic and unpredictable effect on the output of a PV system. The preliminary analyses conclude that mitigation strategies are needed to overcome voltage deviations, unacceptable levels of harmonics, excessive fault current and low power factor. Mitigation strategies are proposed to control these issues predominantly through the use of high quality, made for purpose inverters. Results show that use of inverters with harmonic filtering reduces the level of harmonic injections to an acceptable level according to Australian standards. Furthermore, the configuration of inverters to supply active and reactive power assist in mitigating low power factor problems. Use of FACTS devices; SVC and STATCOM also reduces the harmonics and improve the power factor of the network, and finally, energy storage helps to smooth the power supply.

Keywords: climate change, mitigation strategies, photovoltaic (PV), power quality

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Authors: Laura Victoria Vigoya Morales, David Rolando Suarez Mora

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The problem of detecting enterococcus faecalis is receiving considerable attention with the new cases of beachgoers infected with the bacteria, which can be found in fecal matter. The process detection of this kind of bacteria would be taking a long time, which waste time and money as a result of closing recreation place, like beach or pools. Hence, new methods for automating the process of detecting and recognition of this bacteria has become in a challenge. This article describes a novel approach to detect the enterococcus faecalis bacteria in water by using an octave algorithm, which embody a network neural. This document shows result of performance, quality and integrity of the algorithm.

Keywords: Enterococcus faecalis, image treatment, octave and network neuronal

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Authors: Mahboobeh Eghtesad, Reza Mohseni

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We develop methods for detecting a target for orthogonal frequency division multiplexing (OFDM) based radars. As a preliminary step we introduce the target and Gaussian noise models in discrete–time form. Then, resorting to match filter (MF) we derive a detector for two different scenarios: a non-fluctuating target and a Rayleigh fluctuating target. It will be shown that a MF is not suitable for Rayleigh fluctuating targets. In this paper we propose a reduced-complexity method based on fast Fourier transfrom (FFT) for such a situation. The proposed method has better detection performance.

Keywords: constant false alarm rate (CFAR), match filter (MF), fast Fourier transform (FFT), OFDM radars, Rayleigh fluctuating target

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Authors: Emanuele Bonamente, Andrea Aquino

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This study presents an innovative design for geothermal heat pumps with the goal of maximizing the system efficiency (COP - Coefficient of Performance), reducing the soil use (e.g. length/depth of geothermal boreholes) and initial investment costs. Based on experimental data obtained from a two-year monitoring of a working prototype implemented for a commercial building in the city of Perugia, Italy, an upgrade of the system is proposed and the performance is evaluated via CFD simulations. The prototype was designed to include a thermal heat storage (i.e. water), positioned between the boreholes and the heat pump, acting as a flywheel. Results from the monitoring campaign show that the system is still capable of providing the required heating and cooling energy with a reduced geothermal installation (approx. 30% of the standard length). In this paper, an optimization of the system is proposed, re-designing the heat storage to include phase change materials (PCMs). Two stacks of PCMs, characterized by melting temperatures equal to those needed to maximize the system COP for heating and cooling, are disposed within the storage. During the working cycle, the latent heat of the PCMs is used to heat (cool) the water used by the heat pump while the boreholes independently cool (heat) the storage. The new storage is approximately 10 times smaller and can be easily placed close to the heat pump in the technical room. First, a validation of the CFD simulation of the storage is performed against experimental data. The simulation is then used to test possible alternatives of the original design and it is finally exploited to evaluate the PCM-storage performance for two different configurations (i.e. single- and double-loop systems).

Keywords: geothermal heat pump, phase change materials (PCM), energy storage, renewable energies

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Authors: Earleen Jane Fuentes, Regeene Melarese Lim, Franklin Benjamin Tapia, Alexis Pantola

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Mobile Ad-hoc Network (MANET) is an infrastructure-less network of mobile devices, also known as nodes. These nodes heavily rely on each other’s resources such as memory, computing power, and energy. Thus, some nodes may become selective in forwarding packets so as to conserve their resources. These nodes are called misleading nodes. Several reputation-based techniques (e.g. CORE, CONFIDANT, LARS, SORI, OCEAN) and acknowledgment-based techniques (e.g. TWOACK, S-TWOACK, EAACK) have been proposed to detect such nodes. These techniques do not appropriately punish misleading nodes. Hence, this paper addresses the limitations of these techniques using a system called MINDRA.

Keywords: acknowledgment-based techniques, mobile ad-hoc network, selfish nodes, reputation-based techniques

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Authors: Emma Van Schie

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The purpose of this study is to use mixed methods research to create typologies of the performance of firms in the cotton-to-clothing value chain in Zimbabwe, and to use these typologies to achieve the objective of adding to the small pool of studies on Sub-Saharan African value chains performing in the context of economic liberalisation and achieving development. The uptake of economic liberalisation measures across Sub-Saharan Africa has led to the restructuring of many value chains. While this action has resulted in some African economies positively reintegrating into global commodity chains, it has also been deeply problematic for the development impacts of the majority of others. Over and above this, these nations have been placed at a disadvantage due to the fact that there is little scholarly and policy research on approaches for managing economic liberalisation and value chain development in the unique African context. As such, the central question facing these less successful cases is how they can integrate into the world economy whilst still fostering their development. This paper draws from quantitative questionnaires and qualitative interviews with 28 stakeholders in the cotton-to-clothing value chain in Zimbabwe. This paper examines the performance of firms in the value chain, and the subsequent local socio-economic development impacts that are affected by the revival of the cotton-to-clothing value chain following its collapse in the wake of Zimbabwe’s uptake of economic liberalisation measures. Firstly, the paper finds the relatively undocumented characteristics and structures of firms in the value chain in the post-economic liberalisation era. As well as this, it finds typologies of the status of firms as either being in operation, closed down, or being placed under judicial management and the common characteristics that these typologies hold. The key findings show how a mixture of macro and local level aspects, such as value chain governance and the management structure of a business, leads to the most successful typology that is able to add value to the chain in the context of economic liberalisation, and thus unlock its socioeconomic development potential. These typologies are used in making industry and policy recommendations on achieving this balance between the macro and the local level, as well as recommendations for further academic research for more typologies and models on the case of cotton value chains in Sub-Saharan Africa. In doing so, this study adds to the small collection of academic evidence and policy recommendations for the challenges that African nations face when trying to incorporate into global commodity chains in attempts to benefit from their associated socioeconomic development opportunities.

Keywords: cotton-to-clothing value chain, economic liberalisation, restructuring value chain, typologies of firms, value chain governance, Zimbabwe

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Authors: Srinivas Nerella

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This study explores the significance of patent protection for artificial intelligence (AI) innovations in the pharmaceutical sector, emphasizing applications in drug discovery, personalized medicine, and clinical trial optimization. The challenges of patenting AI-driven inventions are outlined, focusing on the classification of algorithms as abstract ideas, meeting the non-obviousness standard, and issues around defining inventorship. The methodology includes examining case studies and existing patents, with an emphasis on how companies like Benevolent AI and Insilico Medicine have successfully secured patent rights. Findings demonstrate that a strategic approach to patent protection is essential, with particular attention to showcasing AI’s technical contributions to pharmaceutical advancements. Conclusively, the study underscores the critical role of understanding patent law and innovation strategies in leveraging intellectual property rights in the rapidly advancing field of AI-driven pharmaceuticals.

Keywords: artificial intelligence, pharmaceutical industry, patent protection, drug discovery, personalized medicine, clinical trials, intellectual property, non-obviousness

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Authors: Deniz Peksen

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This thesis aims to predict trend movement of closing price of stock and to maximize portfolio by utilizing the predictions. In this context, the study aims to define a stock portfolio strategy from models created by using Logistic Regression, Gradient Boosting and Random Forest. Recently, predicting the trend of stock price has gained a significance role in making buy and sell decisions and generating returns with investment strategies formed by machine learning basis decisions. There are plenty of studies in the literature on the prediction of stock prices in capital markets using machine learning methods but most of them focus on closing prices instead of the direction of price trend. Our study differs from literature in terms of target definition. Ours is a classification problem which is focusing on the market trend in next 20 trading days. To predict trend direction, fourteen years of data were used for training. Following three years were used for validation. Finally, last three years were used for testing. Training data are between 2002-06-18 and 2016-12-30 Validation data are between 2017-01-02 and 2019-12-31 Testing data are between 2020-01-02 and 2022-03-17 We determine Hold Stock Portfolio, Best Stock Portfolio and USD-TRY Exchange rate as benchmarks which we should outperform. We compared our machine learning basis portfolio return on test data with return of Hold Stock Portfolio, Best Stock Portfolio and USD-TRY Exchange rate. We assessed our model performance with the help of roc-auc score and lift charts. We use logistic regression, Gradient Boosting and Random Forest with grid search approach to fine-tune hyper-parameters. As a result of the empirical study, the existence of uptrend and downtrend of five stocks could not be predicted by the models. When we use these predictions to define buy and sell decisions in order to generate model-based-portfolio, model-based-portfolio fails in test dataset. It was found that Model-based buy and sell decisions generated a stock portfolio strategy whose returns can not outperform non-model portfolio strategies on test dataset. We found that any effort for predicting the trend which is formulated on stock price is a challenge. We found same results as Random Walk Theory claims which says that stock price or price changes are unpredictable. Our model iterations failed on test dataset. Although, we built up several good models on validation dataset, we failed on test dataset. We implemented Random Forest, Gradient Boosting and Logistic Regression. We discovered that complex models did not provide advantage or additional performance while comparing them with Logistic Regression. More complexity did not lead us to reach better performance. Using a complex model is not an answer to figure out the stock-related prediction problem. Our approach was to predict the trend instead of the price. This approach converted our problem into classification. However, this label approach does not lead us to solve the stock prediction problem and deny or refute the accuracy of the Random Walk Theory for the stock price.

Keywords: stock prediction, portfolio optimization, data science, machine learning

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Authors: Hangsik Shin

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The purpose of this research is to restore the feature location of under-sampled photoplethysmogram using spline interpolation and to investigate feasibility for feature shape restoration. We obtained 10 kHz-sampled photoplethysmogram and decimated it to generate under-sampled dataset. Decimated dataset has 5 kHz, 2.5 k Hz, 1 kHz, 500 Hz, 250 Hz, 25 Hz and 10 Hz sampling frequency. To investigate the restoration performance, we interpolated under-sampled signals with 10 kHz, then compared feature locations with feature locations of 10 kHz sampled photoplethysmogram. Features were upper and lower peak of photplethysmography waveform. Result showed that time differences were dramatically decreased by interpolation. Location error was lesser than 1 ms in both feature types. In 10 Hz sampled cases, location error was also deceased a lot, however, they were still over 10 ms.

Keywords: peak detection, photoplethysmography, sampling, signal reconstruction

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Authors: Mustafa M. Bob, Norhan Rahman, Abdalla Elamin, Saud Taher

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The objective of this study was to assess the suitability of Madinah city groundwater for irrigation purposes. Of the twenty three wells that were drilled in different locations in the city for the purposes of this study, twenty wells were sampled for water quality analyses. The United States Department of Agriculture (USDA) classification of irrigation water that is based on Sodium hazard (SAR) and salinity hazard was used for suitability assessment. In addition, the residual sodium carbonate (RSC) was calculated for all samples and also used for irrigation suitability assessment. Results showed that all groundwater samples are in the acceptable quality range for irrigation based on RSC values. When SAR and salinity hazard were assessed, results showed that while all groundwater samples (except one) fell in the acceptable range of SAR, they were either in the high or very high salinity zone which indicates that care should be taken regarding the type of soil and crops in the study area.

Keywords: irrigation suitability, TDS, salinity, SAR

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Authors: Antonella Falanga, Armando Cartenì

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Today, an unprecedented amount of data coming from several sources, including mobile devices, sensors, tracking systems, and online platforms, characterizes our lives. The term “big data” not only refers to the quantity of data but also to the variety and speed of data generation. These data hold valuable insights that, when extracted and analyzed, facilitate informed decision-making. The 4Vs of big data - velocity, volume, variety, and value - highlight essential aspects, showcasing the rapid generation, vast quantities, diverse sources, and potential value addition of these kinds of data. This surge of information has revolutionized many sectors, such as business for improving decision-making processes, healthcare for clinical record analysis and medical research, education for enhancing teaching methodologies, agriculture for optimizing crop management, finance for risk assessment and fraud detection, media and entertainment for personalized content recommendations, emergency for a real-time response during crisis/events, and also mobility for the urban planning and for the design/management of public and private transport services. Big data's pervasive impact enhances societal aspects, elevating the quality of life, service efficiency, and problem-solving capacities. However, during this transformative era, new challenges arise, including data quality, privacy, data security, cybersecurity, interoperability, the need for advanced infrastructures, and staff training. Within the transportation sector (the one investigated in this research), applications span planning, designing, and managing systems and mobility services. Among the most common big data applications within the transport sector are, for example, real-time traffic monitoring, bus/freight vehicle route optimization, vehicle maintenance, road safety and all the autonomous and connected vehicles applications. Benefits include a reduction in travel times, road accidents and pollutant emissions. Within these issues, the proper transport demand estimation is crucial for sustainable transportation planning. Evaluating the impact of sustainable mobility policies starts with a quantitative analysis of travel demand. Achieving transportation decarbonization goals hinges on precise estimations of demand for individual transport modes. Emerging technologies, offering substantial big data at lower costs than traditional methods, play a pivotal role in this context. Starting from these considerations, this study explores the usefulness impact of big data within transport demand estimation. This research focuses on leveraging (big) data collected during the COVID-19 pandemic to estimate the evolution of the mobility demand in Italy. Estimation results reveal in the post-COVID-19 era, more than 96 million national daily trips, about 2.6 trips per capita, with a mobile population of more than 37.6 million Italian travelers per day. Overall, this research allows us to conclude that big data better enhances rational decision-making for mobility demand estimation, which is imperative for adeptly planning and allocating investments in transportation infrastructures and services.

Keywords: big data, cloud computing, decision-making, mobility demand, transportation

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Authors: Mónica Arroyo

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South America shows increasing decline in regional export values in the last years, after a strong growth of trade flows especially with China up to 2013. This change is due to the end of the commodity price boom, the slowing of the Chinese economy and the effects of the 2008 economic crisis. This paper examines the integration of regional economies in this context, particularly the situation in Brazil and Argentina. Based on transformations over the last two decades, the analysis is focused on the spatial circuits of production linked to foreign markets, contributing to the understanding of the different uses of territory and the within-country inequality. The South American regional exports, consisting basically of raw materials, are concentrated in a few companies. Large areas are intended for the production of agriculture and mining commodities, under the command of major economic groups, both domestic and foreign, relegating the local population to less productive places or, in most cases, forcing them to change their activity and to migrate to other regions in search of some source of income. On the other hand, the dynamics of these commodities’ spatial circuits of production print requirements in territories in terms of infrastructure and regulation. Capturing this movement requires understanding businesses and government’s role in territorial regulation, and consequently how regional systems are changing – for instance, economic specialisation, growing role of services, investment in roads, railways, ports, and airports. This paper aims to highlight topics for discussion on regional economic dynamics and their different degrees of internationalisation. The intention is to contribute to the debate about the relations between trade, globalization, and development.

Keywords: regional inequality, international trade, developing world, South America

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Authors: Monika Chuchro

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This paper presents a preliminary attempt to apply classification of time series using meta-clusters in order to improve the quality of regression models. In this case, clustering was performed as a method to obtain a subgroups of time series data with normal distribution from inflow into waste water treatment plant data which Composed of several groups differing by mean value. Two simple algorithms: K-mean and EM were chosen as a clustering method. The rand index was used to measure the similarity. After simple meta-clustering, regression model was performed for each subgroups. The final model was a sum of subgroups models. The quality of obtained model was compared with the regression model made using the same explanatory variables but with no clustering of data. Results were compared by determination coefficient (R2), measure of prediction accuracy mean absolute percentage error (MAPE) and comparison on linear chart. Preliminary results allows to foresee the potential of the presented technique.

Keywords: clustering, data analysis, data mining, predictive models

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Authors: Jiahua Zhang, Qing Chang, Fengmei Yao

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Studying on the response of vegetation phenology to climate change at different temporal and spatial scales is important for understanding and predicting future terrestrial ecosystem dynamics andthe adaptation of ecosystems to global change. In this study, the Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) dataset and climate data were used to analyze the dynamics of grassland phenology as well as their correlation with climatic factors in different eco-geographic regions and elevation units across the Tibetan Plateau. The results showed that during 2003–2012, the start of the grassland greening season (SOS) appeared later while the end of the growing season (EOS) appeared earlier following the plateau’s precipitation and heat gradients from southeast to northwest. The multi-year mean value of SOS showed differences between various eco-geographic regions and was significantly impacted by average elevation and regional average precipitation during spring. Regional mean differences for EOS were mainly regulated by mean temperature during autumn. Changes in trends of SOS in the central and eastern eco-geographic regions were coupled to the mean temperature during spring, advancing by about 7d/°C. However, in the two southwestern eco-geographic regions, SOS was delayed significantly due to the impact of spring precipitation. The results also showed that the SOS occurred later with increasing elevation, as expected, with a delay rate of 0.66 d/100m. For 2003–2012, SOS showed an advancing trend in low-elevation areas, but a delayed trend in high-elevation areas, while EOS was delayed in low-elevation areas, but advanced in high-elevation areas. Grassland SOS and EOS changes may be influenced by a variety of other environmental factors in each eco-geographic region.

Keywords: grassland, phenology, MODIS, eco-geographic regions, elevation, climatic factors, Tibetan Plateau

Procedia PDF Downloads 323

Authors: Mustafa Kucukoduk, Evren Yildiztugay, A. Hediye Sekmen, Ismail Turkan, Yavuz Bagci

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In this study, physiological and biochemical responses of Centaurea tuzgoluensis, a Turkish endemic halophyte, to salinity were studied. Therefore, the changes in shoot growth, leaf relative water content (RWC), ion concentrations, lipid peroxidation, hydroxyl (OH.) radical scavenging activity, proline (Pro) content, and antioxidant system [superoxide dismutase (SOD), catalase (CAT), ascorbate peroxidase (APX) and glutathione reductase (GR)] were investigated. The 60 days (d) old C. tuzgoluensis seedlings were subjected to 0, 150 and 300 mM NaCl for 7 d and 14 d. The relative shoot growth was generally did not change in the 150 mM NaCl, but reduced with 300 mM NaCl stress at 7 d and 14 d. RWC was higher in 150 mM NaCl-treated leaves than that of 300 mM NaCl. Salinity decreased K+/Na+ ratio, but increased Na+, Cl, Ca+2 and Na+/Cl ratio in the leaves. On the other hand, it did not change or increase the K+ content at 150 and 300 mM NaCl, respectively. MDA content in the 150 and 300 mM NaCl-treated leaves remained close to control at 7 d. This was related to enhanced activities of SOD, CAT, APX and GR enzymes, and their isoenzymes especially Fe-SOD in the leaves. On the other hand, the higher sensitivity to 300 mM NaCl at 14 d was associated with inadequate increase in antioxidant enzymes and the decreased OH radical scavenging activity. All these results suggest that C. tuzgoluensis has different antioxidant metabolisms between short- (7 d) and long-term (14 d) salt treatments and salinity tolerance of C. tuzgoluensis might be closely related to increased capacity of antioxidative system to scavenge reactive oxygen species (ROS) and accumulation of osmoprotectant proline under salinity conditions.

Keywords: antioxidant enzymes, endemic halophyte, ion exchange, lipid peroxidation, antioxidant, enzymes, endemic halophyte, ion exchange, lipid peroxidation, proline, Centaurea tuzgoluensis

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Authors: Vladimir Smirnov, Roman Tominov, Vadim Avilov, Oleg Ageev

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The creation of a new generation micro- and nanoelectronics elements opens up unlimited possibilities for electronic devices parameters improving, as well as developing neuromorphic computing systems. Interest in the latter is growing up every year, which is explained by the need to solve problems related to the unstructured classification of data, the construction of self-adaptive systems, and pattern recognition. However, for its technical implementation, it is necessary to fulfill a number of conditions for the basic parameters of electronic memory, such as the presence of non-volatility, the presence of multi-bitness, high integration density, and low power consumption. Several types of memory are presented in the electronics industry (MRAM, FeRAM, PRAM, ReRAM), among which non-volatile resistive memory (ReRAM) is especially distinguished due to the presence of multi-bit property, which is necessary for neuromorphic systems manufacturing. ReRAM is based on the effect of resistive switching – a change in the resistance of the oxide film between low-resistance state (LRS) and high-resistance state (HRS) under an applied electric field. One of the methods for the technical implementation of neuromorphic systems is cross-bar structures, which are ReRAM cells, interconnected by cross data buses. Such a structure imitates the architecture of the biological brain, which contains a low power computing elements - neurons, connected by special channels - synapses. The choice of the ReRAM oxide film material is an important task that determines the characteristics of the future neuromorphic system. An analysis of literature showed that many metal oxides (TiO2, ZnO, NiO, ZrO2, HfO2) have a resistive switching effect. It is worth noting that the manufacture of nanocomposites based on these materials allows highlighting the advantages and hiding the disadvantages of each material. Therefore, as a basis for the neuromorphic structures manufacturing, it was decided to use ZnₓTiᵧHfzOᵢ nanocomposite. It is also worth noting that the ZnₓTiᵧHfzOᵢ nanocomposite does not need an electroforming, which degrades the parameters of the formed ReRAM elements. Currently, this material is not well studied, therefore, the study of the effect of resistive switching in forming-free ZnₓTiᵧHfzOᵢ nanocomposite is an important task and the goal of this work. Forming-free nanocomposite ZnₓTiᵧHfzOᵢ thin film was grown by pulsed laser deposition (Pioneer 180, Neocera Co., USA) on the SiO2/TiN (40 nm) substrate. Electrical measurements were carried out using a semiconductor characterization system (Keithley 4200-SCS, USA) with W probes. During measurements, TiN film was grounded. The analysis of the obtained current-voltage characteristics showed a resistive switching from HRS to LRS resistance states at +1.87±0.12 V, and from LRS to HRS at -2.71±0.28 V. Endurance test shown that HRS was 283.21±32.12 kΩ, LRS was 1.32±0.21 kΩ during 100 measurements. It was shown that HRS/LRS ratio was about 214.55 at reading voltage of 0.6 V. The results can be useful for forming-free nanocomposite ZnₓTiᵧHfzOᵢ films in neuromorphic systems manufacturing. This work was supported by RFBR, according to the research project № 19-29-03041 mk. The results were obtained using the equipment of the Research and Education Center «Nanotechnologies» of Southern Federal University.

Keywords: nanotechnology, nanocomposites, neuromorphic systems, RRAM, pulsed laser deposition, resistive switching effect

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Authors: Tolulope A. Olukunle

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Plastic waste management has emerged as one of the greatest challenges facing developing countries. This paper describes the design of various components of a plastic shredder. This machine is widely used in industries and recycling plants. The introduction of plastic shredder machine will promote reduction of post-consumer plastic waste accumulation and serves as a system for wealth creation and empowerment through conversion of waste into economically viable products. In this design research, a 10 kW electric motor with a rotational speed of 500 rpm was chosen to drive the shredder. A pulley size of 400 mm is mounted on the electric motor at a distance of 1000 mm away from the shredder pulley. The shredder rotational speed is 300 rpm.

Keywords: design, machine, plastic waste, recycling

Procedia PDF Downloads 326

Authors: M. Y. Lee, D. H. Shin, S. H. Park, W.C. Ham, S.K. Ko, C. G. Song

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Photoacoustic Tomography (PAT) is a promising medical imaging modality that combines optical imaging contrast with the spatial resolution of ultrasound imaging. It can also distinguish the changes in biological features. But, real-time PAT system should be confirmed due to photoacoustic effect for tissue. Thus, we have developed a real-time PAT system using a custom-developed data acquisition board and ultrasound linear probe. To evaluate performance of our system, phantom test was performed. As a result of those experiments, the system showed satisfactory performance and its usefulness has been confirmed. We monitored the degradation of inflammation which induced on the rat’s kidney using real-time PAT.

Keywords: photoacoustic tomography, inflammation detection, rat, kidney, contrast agent, ultrasound

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Authors: Kailash Chandra, Devanshu Gupta

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The Himalayan Mountains of India fall under two biogeographic zones Trans Himalaya (TH) and Himalaya and seven biotic provinces (TH-Ladakh Mountains, TH-Tibetan Plateau, TH-Sikkim, North-West Himalaya, West Himalaya, Central Himalaya, and East Himalaya). Because of the extreme environment and altitudinal variations, unique physiography, varied ecological conditions, and different vegetations, the Himalaya exhibit a rich assemblage of life, both flora, and fauna, further subjected to the impacts of climate change. To the authors’ best knowledge, there is no comprehensive account except for sporadic faunal investigations, to assess or interpret the insect diversity and their biogeographic distribution in Indian Himalaya (IH), one of the biodiversity hotspots. Therefore, in this paper, a compelling review of the extensive knowledge of insect diversity of IH is presented for the first time to the best of our knowledge. The inventory of the known insect species of IH was compiled from the exploration cum faunal-study data ready with the zoological survey of India, Kolkata as well as from the information published in the scientific literature till date. The species were listed with their valid names with their distribution in seven biotic provinces of IH. The insect fauna of IH represents about 38% of the identified insect diversity of India. The interpretation of data provided significant information in detecting possible gap areas in the taxonomic representation of different insect orders. Archaeognatha, Zygentoma, Ephemeroptera, Phasmida, Embioptera, Psocoptera, Phthiraptera, Strepsiptera, Megaloptera, Raphidioptera, Siphonaptera, and Mecoptera need revisions, and it is required to collect more samples from remote areas of the region. Scope for finding new taxa even in the most diverse orders, Coleoptera, Lepidoptera, Hymenoptera, Diptera, and Hemiptera cannot be overlooked. Exploration of cold deserts of Trans Himalaya and East Himalaya (Arunachal Pradesh) may result in a good number of new species from these regions. The most notable data was that many of the species recorded from Himalaya are still known from their type localities only, so there is an urgency to revisit and resurvey those collection localities for the evaluation of the status of those species. It is also required to assess and monitor the impact of climate change on the diversity of insects inhabiting in the fragile Himalayan ecosystem. DNA barcoding especially pests and biological control agents to solve the problems of identification in species complexes is also the need of the hour. In a nutshell, it can be concluded that the inventory of insects of this region is extensive but is far from final as every year hundreds of new species are described.

Keywords: catalog, climate change, diversity, DNA barcoding

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Authors: Ines Gasmi, Salima Smiti, Makram Soui, Khaled Ghedira

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Credit risk is considered as one of the important issues for financial institutions. It provokes great losses for banks. To this objective, numerous methods for credit risk evaluation have been proposed. Many evaluation methods are black box models that cannot adequately reveal information hidden in the data. However, several works have focused on building transparent rules-based models. For credit risk assessment, generated rules must be not only highly accurate, but also highly interpretable. In this paper, we aim to build both, an accurate and transparent credit risk evaluation model which proposes a set of classification rules. In fact, we consider the credit risk evaluation as an optimization problem which uses a genetic programming (GP) algorithm, where the goal is to maximize the accuracy of generated rules. We evaluate our proposed approach on the base of German and Australian credit datasets. We compared our finding with some existing works; the result shows that the proposed GP outperforms the other models.

Keywords: credit risk assessment, rule generation, genetic programming, feature selection

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Authors: M. Jebali, M. Jemni

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This work is the part of vision based hand gesture recognition system for Natural Human Computer Interface. Hand tracking and segmentation are the primary steps for any hand gesture recognition system. The aim of this paper is to develop robust and efficient hand segmentation algorithm such as an input to another system which attempt to bring the HCI performance nearby the human-human interaction, by modeling an intelligent sign language recognition system based on prediction in the context of dialogue between the system (avatar) and the interlocutor. For the purpose of hand segmentation, an overcoming occlusion approach has been proposed for superior results for detection of hand from an image.

Keywords: HCI, sign language recognition, object tracking, hand segmentation

Procedia PDF Downloads 415