Search results for: urban network space

Authors: Chinelle van der Westhuizen

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The introduction of cryptocurrencies as an alternative payment system have placed governments in a challenging position in relation to the regulatory status of cryptocurrencies and the money laundering activities associated with it. In April 2018, the Australian government amended its Anti-Money Laundering laws to regulate digital currency exchanges in an attempt to regulate money laundering activities and the introduction of ‘know-your-customer’ policies within the digital currency sector. Part one of this paper explores the use of cryptocurrencies for money laundering purposes and its significance to money launderers. Part two studies the efficacy of the current Australian Anti-Money Laundering laws and whether more can be done on a regulatory level. This paper will, therefore, highlight recent court decisions and legislation in terms of money laundering activities within these alternative payment systems in Australia and the United Kingdom. Part three of the paper will further analyze recent case studies by the Australian Transaction Reports and Analysis Centre and the Office for Professional Body Anti-Money Laundering Supervision in the United Kingdom as the regulatory bodies for money laundering activities. The case studies and research will explore the legal disputes and future regulation concerning the use of cryptocurrencies and money laundering on a national as well as international level. This paper intends to highlight that although cryptocurrency is viewed as an innovative global phenomenon and an alternative method of payment, there are a number of legal issues associated with its use that indicate the need for regulatory reform. It is recommended in this paper that the Financial Action Task Force, International Monetary Fund as well as concerned governments have ongoing discussions on these regulatory issues and how to address it appropriately, whether through legislation or universal guidelines. Therefore, the conclusion of this paper will emphasize the benefits of a regulatory regime for money laundering activities within the cryptocurrency space and that the lack of such a regime may be detrimental to countries.

Keywords: cryptocurrency, know-your-customer policy, money laundering, regulation

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Authors: Chaomeng Liu, Li Li, Xiao Wang, Li Ren, Qinge Zhang

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Late-life depression (LLD) is a prevalent mental disorder among the elderly, frequently accompanied by significant cognitive decline, and has emerged as a worldwide public health concern. Microglia, astrocytes, and peripheral immune cells play pivotal roles in regulating inflammatory responses within the central nervous system (CNS) across diverse cerebral disorders. This review commences with the clinical research findings and accentuates the recent advancements pertaining to microglia and astrocytes in the neuroinflammation process of LLD. The reciprocal communication network between the CNS and immune system is of paramount importance in the pathogenesis of depression and cognitive decline. Stress-induced downregulation of tight and gap junction proteins in the brain results in increased blood-brain barrier permeability and impaired astrocyte function. Concurrently, activated microglia release inflammatory mediators, initiating the kynurenine metabolic pathway and exacerbating the quinolinic acid/kynurenic acid imbalance. Moreover, the balance between Th17 and Treg cells is implicated in the preservation of immune homeostasis within the cerebral milieu of individuals suffering from LLD. The ultimate objective of this review is to present future strategies for the management and treatment of LLD, informed by the most recent advancements in research, with the aim of averting or postponing the onset of AD.

Keywords: neuroinflammation, late-life depression, microglia, astrocytes, central nervous system, blood-brain barrier, Kynurenine pathway

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Authors: Jieh-Jiuh Wang

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Disasters happen frequently due to the global climate changes today. The cultural heritage conservation should be considered from the perspectives of surrounding environments and large-scale disasters. Most current thoughts about the disaster prevention of cultural heritages in Taiwan are single-point thoughts emphasizing firefighting, decay prevention, and construction reinforcement and ignoring the whole concept of the environment. The traditional conservation cannot defend against more and more tremendous and frequent natural disasters caused by climate changes. More and more cultural heritages are confronting the high risk of disasters. This study adopts the perspective of risk identification and takes flood as the main disaster category. It analyzes the amount and categories of cultural heritages that might suffer from disasters with the geographic information system integrating the latest flooding potential data from National Fire Agency and Water Resources Agency and the basic data of cultural heritages. It examines the actual risk of cultural heritages confronting floods and serves as the accordance for future considerations of risk measures and preparation for reducing disasters. The result of the study finds the positive relationship between the disaster affected situation of national cultural heritages and the rainfall intensity. The order of impacted level by floods is historical buildings, historical sites indicated by municipalities and counties, and national historical sites and relics. However, traditional settlements and cultural landscapes are not impacted. It might be related to the taboo space in the traditional culture of site selection (concepts of disaster avoidance). As for the regional distribution on the other hand, cultural heritages in central and northern Taiwan suffer from more shocking floods, while the heritages in northern and eastern Taiwan suffer from more serious flooding depth.

Keywords: cultural heritage, flood, preventive conservation, risk management

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Authors: Redouane Larbi Boufeniza, Jing-Jia Luo

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This study assesses the suitability of deep learning (DL) for downscaling sea surface temperature (SST) over the Mediterranean Sea in the context of seasonal forecasting. We design a set of experiments that compare different DL configurations and deploy the best-performing architecture to downscale one-month lead forecasts of June–September (JJAS) SST from the Nanjing University of Information Science and Technology Climate Forecast System version 1.0 (NUIST-CFS1.0) for the period of 1982–2020. We have also introduced predictors over a larger area to include information about the main large-scale circulations that drive SST over the Mediterranean Sea region, which improves the downscaling results. Finally, we validate the raw model and downscaled forecasts in terms of both deterministic and probabilistic verification metrics, as well as their ability to reproduce the observed precipitation extreme and spell indicator indices. The results showed that the convolutional neural network (CNN)-based downscaling consistently improves the raw model forecasts, with lower bias and more accurate representations of the observed mean and extreme SST spatial patterns. Besides, the CNN-based downscaling yields a much more accurate forecast of extreme SST and spell indicators and reduces the significant relevant biases exhibited by the raw model predictions. Moreover, our results show that the CNN-based downscaling yields better skill scores than the raw model forecasts over most portions of the Mediterranean Sea. The results demonstrate the potential usefulness of CNN in downscaling seasonal SST predictions over the Mediterranean Sea, particularly in providing improved forecast products.

Keywords: Mediterranean Sea, sea surface temperature, seasonal forecasting, downscaling, deep learning

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Authors: Meng-Li Lin, Shang-Hsuan Chiu

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Taiwan is a country of diverse ethnic groups, the historical background of each ethnic group is different, and the conflict between them influence on each other, result in Taiwan's multi-culture. The Changhua County in Taiwan is the largest county of Hoklo-Hakka. Hakka people get along with Hoklo people for a long time. There are integration and conflict during that time and makes Hakka people gradually assimilated Hoklo-Hakka people. Today in Changhua Plain area, many Hoklo-Hakka people do not speak Hakka language. Therefore, it has been difficult to find information of Hakka from the Hakka language in the group of Hoklo-Hakka. But in the living space or culture to find relevant historical traces of life could be confirmed in Hakka Culture. In this paper, through the investigation of descent, life field, religion, language and other investigations of the Dacun, Changhua County residents to carry out the analysis of the process of assimilating Hoklo in living cultural landscape. First is through the local literature, the elderly and other oral history stories, to investigate the changes in Dacun field historical. Second, the comparison of collected traditional Hakka culture and the living cultural landscape of Hoklo-Haka are done to explore the differences between the living cultural landscape and the traditional Hakka culture. After analysis Hoklo-Hakka living cultural landscape, the significant differences, we proposed preservation strategy to provide recommendations to save the cultural life of Hoklo-Hakka landscape in future. Changhua Dacun traditional Hakka landscape is disappearing, in this study, we explore and investigate the data of Changhua Dacun Hoklo-Hakka living cultural landscape to analyze and to provide strategic advice to save. Here we have three study purposes. 1. Discuss the Hoklo-Hakka living cultural landscape of Changhua Dacun. 2. Investigate and record the Hoklo-Hakka living cultural landscape. 3. Propose a reserve strategy of the Hoklo-Hakka living cultural landscape in future.

Keywords: Hoklo-Hakka, Dacun, save policy, life Culture

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Authors: Yihunie Hibstie Asres, Manny Mathuthu

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Farmers may not be conscious for their farmland’s nutrients, soil organic matter, water and air because they simply concerned only for their labor availability and soil fertility losses. The composition and proportion of these components greatly influence soil physical properties, including texture, structure, and porosity, the fraction of pore space in a soil. The soil of this farmland must be able to supply adequate amount of plant nutrients, in forms which can be absorbed by the crop, within its lifespan. Deficiencies or imbalances in the supply of any of essential elements can compromise growth, affecting root development, cell division, crop quality, crop yield and resistance to disease and drought. This study was conducted to fill this knowledge gap in order to develop economically vital and environmentally accepted nutrient management strategies for the use of soils in agricultural lands. The objective of this study is to assess the elemental contents and concentration of soil samples collected from farmlands of ‘Yebrage’ using Neutron Activation Analysis (NAA) techniques regardless of oxidation state, chemical form or physical locations. NAA is used to determine the elemental composition and concentrations present in a soil. The macro/micronutrient and organic matter deficiencies have been verified in agricultural soils through increased use of soil testing and plant analysis. The challenge for agriculture over the coming decades will meet the world’s increasing demands for food in a sustainable way. Current issues and future challenges point out that as long as agriculture remains a soil-based industry, major decreases in productivity likely to be attained ensuring that plants do not have adequate and balanced supply of nutrients.

Keywords: NAA, Yebrage, Chemoga, macro/micronutrient

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Authors: Ananchai Ukaew, Choopong Chauypen

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Design concepts of real-time embedded system can be realized initially by introducing novel design approaches. In this literature, model based design approach and in-the-loop testing were employed early in the conceptual and preliminary phase to formulate design requirements and perform quick real-time verification. The design and analysis methodology includes simulation analysis, model based testing, and in-the-loop testing. The design of conceptual drive-by-wire, or DBW, algorithm for electronic control unit, or ECU, was presented to demonstrate the conceptual design process, analysis, and functionality evaluation. The concepts of DBW ECU function can be implemented in the vehicle system to improve electric vehicle, or EV, conversion drivability. However, within a new development process, conceptual ECU functions and parameters are needed to be evaluated. As a result, the testing system was employed to support conceptual DBW ECU functions evaluation. For the current setup, the system components were consisted of actual DBW ECU hardware, electric vehicle models, and control area network or CAN protocol. The vehicle models and CAN bus interface were both implemented as real-time applications where ECU and CAN protocol functionality were verified according to the design requirements. The proposed system could potentially benefit in performing rapid real-time analysis of design parameters for conceptual system or software algorithm development.

Keywords: drive-by-wire ECU, in-the-loop testing, model-based design, real-time embedded system

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Authors: Erich Gomes Schaitza, Antônio Francisco Savi, Glaucia Aparecida Prates

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The penetration of renewable energy into the electricity supply in Brazil is high, one of the highest in the World. Centralized hydroelectric generation is the main source of energy, followed by biomass and wind. Surprisingly, mini and micro-generation are negligible, with less than 2,000 connections to the national grid. In 2015, a new regulatory framework was put in place to change this situation. In the agricultural sector, the framework was complemented by the offer of low interest rate loans to in-farm renewable generation. Brazil proposed to more than double its area of planted forests as part of its INDC- Intended Nationally Determined Contributions to the UNFCCC-U.N. Framework Convention on Climate Change (UNFCCC). This is an ambitious target which will be achieved only if forests are attractive to farmers. Therefore, this paper analyses whether planting forests for in-farm energy generation with a with a woodchip gasifier is economically viable for microgeneration under the new framework and at if they could be an economic driver for forest plantation. At first, a static case was analyzed with data from Eucalyptus plantations in five farms. Then, a broader analysis developed with the use of Monte Carlo technique. Planting short rotation forests to generate energy could be a viable alternative and the low interest loans contribute to that. There are some barriers to such systems such as the inexistence of a mature market for small scale equipment and of a reference network of good practices and examples.

Keywords: biomass, distribuited generation, small-scale, Monte Carlo

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Authors: M. J. Zuroni, O. Syuhaily, M. A. Afida Mastura, M. S. Roslina, A. K. Nurul Aini

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The impact of country development has caused an increase of solid waste. The increase in population causes of excess usage thus effecting the sustainable environment. Zero waste management involves maximizing practices of recycling and minimizing residual waste. This paper seeks to analyze the relationship between knowledge, attitude, perceived behavior control, subjective norm and behavior of household solid waste towards household solid waste management among urban households in 8 states that have been implemented and enforced regulations under the Solid Waste Management and Public Cleansing Act 2007 (Act 672) in Malaysia. A total of respondents are 605 and we used a purposive sampling for location and simple sampling for sample size. Data collected by using self-administered questionnaire and were analyzed using SPSS software. The Pearson Correlation Test is to examine the relationship between four variables. Results show that knowledge scores are high because they have an awareness of the importance of managing solid waste. For attitude, perceived behavior control, subjective norm and behavioral scores at a moderate level in solid waste management activities. The findings show that there is a significant relationship between knowledge and behavior of household solid waste (r = 0.136 **, p = 0.001), there is a significant relationship between attitude and behavior (r = 0.238 **, p = 0.000), there is a significant relationship between perceived behavior control and behavior (r = 0.516 **, p = 0.000) and there is a significant relationship between subjective norm and behavior (r = 0.494 **, p = 0.000). The conclusion is that there is a relationship between knowledge, attitude, perceived behavior control and subjective norm toward the behavior of household solid waste management. Therefore, in the findings of the study, all parties including the government should work together to enhance the knowledge, attitude, perceived behavior control and behavior of household solid waste management in other states that have not implemented and enforced regulations under the Solid Waste and Public Cleansing Management Act 2007 (Act 672).

Keywords: solid waste management, knowledge, attitude, perceived behavior control, subjective norm, behavior

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Authors: Fall Abdourahmane, Lazrak Meryem, El Hsaini Houda, El Ammari Laila, Gamih Hasnae, Yahyane Abdelhakim, Benjouad Abdelaziz, Aguenaou Hassan, El Kari Khalid

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Introduction: The double burden of malnutrition (DBM), defined by the concurrent occurrence of undernutrition and overnutrition, represents a critical public health issue, particularly in low- and middle-income countries. In Morocco, 61.3% of women of reproductive age (WRA) are classified as overweight or obese, with 30.4% meeting the criteria for obesity. Furthermore, 34.4% of WRA are affected by anaemia, and 49.7% present with iron deficiency anaemia. Objective: The objective of this study is to assess the individual-level prevalence of the double burden of malnutrition (DBM) among Moroccan WRA, focusing on the simultaneous presence of iron deficiency anaemia and overweight/obesity. Methods: A national cross-sectional survey was carried out on a representative sample of 2090 Moroccan WRA. The data collected encompassed blood samples, anthropometric measurements and socio-economic factors. Haemoglobin levels were assessed using a Hemocue device, while ferritin and CRP levels were determined through immunoturbidimetric analysis. Results: The prevalence of overweight/obesity among WRA in Morocco was 60.2%, iron deficiency affected 30.6%, anaemia was found in 34.4%, and 50.0% had iron deficiency anaemia. The coexistence of overweight/obesity with anaemia was observed in 19.2% and with iron deficiency in 16.3%. Among overweight/obese women, 32.5% were anaemic, 28.4% had iron deficiency, and 47.6% had iron deficiency anaemia. The prevalence of DBM was higher in urban areas compared to rural settings. Conclusion: The DBM among women of WRA showed an emergent reality of the interconnection and the coexistence at individual level of the undernutrition and the overnutrition. Therefore, effective and dual actions that could simultaneously address the double dimension of the DBM have to be implemented for the policy solutions to be successful.

Keywords: the double burden of malnutrition, iron deficiency anemia, overweight, obesity

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Authors: Tabin Millo, Khoob Chand, Ashok Kumar Jaiswal

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Introduction: Various kinds of violence and offences are related to alcohol consumption by the offenders. The relationship between alcohol and violence is complex. But its study is important to achieve understanding of violence as well as alcohol related behavior. This study was done to know the blood alcohol concentration in people involved in various offences and its demographic pattern. The study was carried out in the forensic toxicology laboratory, department of Forensic Medicine, All India Institute of Medical Sciences, New Delhi, India. Material and methods: The blood samples were collected from the arrested people shortly after the commission of the offence by the emergency medical officers in the emergency department and forwarded to the forensic toxicology laboratory through the investigating officer. The blood samples were collected in EDTA vial with sodium fluoride preservative. The samples were analyzed by using gas chromatography with head space (GC-HS), which is ideal for alcohol estimation. The toxicology reports were given within a week. The data of seven years (2011-17) were analyzed for its alcohol concentration, associated crimes and its demographic pattern. Analysis and conclusion: Total 280 samples were analyzed in the period of 2011-2017. All were males except one female who was a bar dancer. The maximum cases were in the age group of 21-30 years (124 cases). The type of offences involved were road traffic accidents (RTA), assault cases, drunken driving, drinking in public place, drunk on duty, sexual offence, bestiality, eve teasing, fall etc. The maximum cases were of assault (75 cases) followed by RTA (64 cases). The maximum cases were in the alcohol concentration range of 101-150mg% (58 cases) followed by 51-100mg% (52 cases). The maximum blood alcohol level detected was 391.51 mg%, belonging to a security guard found unconscious. This study shows that alcohol consumption is associated with various kinds of violence and offences in society.

Keywords: alcohol, crime, toxicology, violence

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Authors: Duy Nguyen Do, Bart Julien Dewancker

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Many Soviet-style collective housing complexes (also known as KTT) were built since the 1960s in Hanoi to support the post-war population growth. Those low-rise buildings have created well-knitted, robust communities, so much to the point that in most complexes, all families in one housing block would know each other, occasionally interact and provide supports in need. To understand how the community of collective housing complexes have developed and maintained in order to adapt their advantages into modern housing designs, the study is executed on the site of Nguyen Cong Tru KTT. This is one of the oldest KTT in Hanoi, completed in 1954. The complex also has an unique characteristic that is closely related to its community: the symbiotic relationship with Hom – a flea market that has been co-developing with Nguyen Cong Tru KTT since its beginning. The research consists of three phases: the first phase is a sociological investigation with Nguyen Cong Tru KTT’s current residents and a site survey on the complex’s economic and architectural characteristics. In the second phase, the collected data is analyzed to find out people’s opinions with the KTT’s concerning their satisfaction with the current housing status, floor plan organization, community, the relationship between the KTT’s dedicated public spaces with the flea market and their usage. Simultaneously, the master plan and gathered information regarding current architectural characteristics of the complex are also inspected. On the third phase, the analyses’ results will provide information regarding the issues, positive trends and significant historical features of the complex’s architecture in order to generate suitable proposals for the redesigning project of Nguyen Cong Tru KTT, a design focused on vitalizing modern apartments’ communities.

Keywords: collective house community, collective house public space, community-focused, redesigning Nguyen Cong Tru KTT, sociological investigation

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Authors: Mario Isaza-Ruget, Claudia C. Colmenares-Mejia, Nancy Yomayusa, Camilo A. González, Andres Cely, Jossie Murcia

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Quantification of risks associated with complications development from chronic kidney disease (CKD) through accurate survival models can help with patient management. A retrospective cohort that included patients diagnosed with CKD from a primary care program and followed up between 2013 and 2018 was carried out. Time-dependent and static covariates associated with demographic, clinical, and laboratory factors were included. Deep Learning (DL) survival analyzes were developed for three CKD outcomes: CKD stage progression, >25% decrease in Estimated Glomerular Filtration Rate (eGFR), and Renal Replacement Therapy (RRT). Models were evaluated and compared with Random Survival Forest (RSF) based on concordance index (C-index) metric. 2.143 patients were included. Two models were developed for each outcome, Deep Neural Network (DNN) model reported C-index=0.9867 for CKD stage progression; C-index=0.9905 for reduction in eGFR; C-index=0.9867 for RRT. Regarding the RSF model, C-index=0.6650 was reached for CKD stage progression; decreased eGFR C-index=0.6759; RRT C-index=0.8926. DNN models applied in survival analysis context with considerations of longitudinal covariates at the start of follow-up can predict renal stage progression, a significant decrease in eGFR and RRT. The success of these survival models lies in the appropriate definition of survival times and the analysis of covariates, especially those that vary over time.

Keywords: artificial intelligence, chronic kidney disease, deep neural networks, survival analysis

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Authors: Mukesh Ravi Raushan

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Despite consideration of obesity as a deadly public health issue contributing 2.6 million deaths worldwide every year developing country like India is facing malnutrition and it is more common than in Sub-Saharan Africa. About one in every three malnourished children in the world lives in India. The paper assess the nutritional health among children using data from total number of 43737 infant and young children aged 0-59 months (µ = 29.54; SD = 17.21) of the selected households by National Family Health Survey, 2005-06. The wasting was measured by a Z-score of standardized weight-for-height according to the WHO child growth standards. The impact of education with place of residence was found to be significantly associated with the complementary food diversity score (CFDS) in India. The education of mother was positively associated with the CFDS but the degree of performance was lower in rural India than their counterpart from urban. The result of binary logistic regression on wasting with WHO seven types of recommended food for children in India suggest that child who consumed the milk product food (OR: 0.87, p<0.0001) were less likely to be malnourished than their counterparts who did not consume, whereas, in case of other food items as the child who consumed food product of seed (OR: 0.75, p<0.0001) were less likely to be malnourished than those who did not. The nutritional status among children were negatively associated with the protein containing complementary food given the child as those child who received pulse in last 24 hour were less likely to be wasted (OR: 0.87, p<0.00001) as compared to the reference categories. The frequency to feed the indexed child increases by 10 per cent the expected change in child health outcome in terms of wasting decreases by 2 per cent in India when place of residence, education, religion, and birth order were controlled. The index gets improved as the risk for malnutrition among children in India decreases.

Keywords: CFDS, food diversity index, India, logistic regression

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Authors: Etienne Mfoumou, Mo Shamma, Martin Tango, Michael Locke

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Water literacy is essential for addressing emerging water management challenges in southwest Nova Scotia (SWNS), where growing concerns over water scarcity and sustainability have highlighted the need for improved educational frameworks. Current approaches often fail to fully represent the complexity of water systems, focusing narrowly on the water cycle while neglecting critical aspects such as groundwater infiltration and the interconnectedness of surface and subsurface water systems. To address these gaps, this paper proposes a comprehensive framework for water literacy that integrates the physical dimensions of water systems with key aspects of understanding, including processes, energy, scale, and human dependency. Moreover, a suggested tool to enhance this framework is a real-time hydrometric data map supported by a network of water level monitoring devices deployed across the province. These devices, particularly for monitoring dug wells, would provide critical data on groundwater levels and trends, offering stakeholders actionable insights into water availability and sustainability. This real-time data would facilitate deeper understanding and engagement with local water issues, complementing the educational framework and empowering stakeholders to make informed decisions. By integrating this tool, the proposed framework offers a practical, interdisciplinary approach to improving water literacy and promoting sustainable water management in SWNS.

Keywords: water education, water literacy, water management, water systems, Southwest Nova Scotia

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Authors: Sanghamitra Acharya, Suwarna Datar

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Extensive use of digital and smart communication createsprolong expose of unwanted electromagnetic (EM) radiations. This harmful radiation creates not only malfunctioning of nearby electronic gadgets but also severely affects a human being. So, a suitable microwave absorbing material (MAM) becomes a necessary urge in the field of stealth and radar technology. Initially, Aluminum based hexa ferrite was prepared by sol-gel technique and for carbon derived composite was prepared by the simple one port chemical reduction method. Finally, composite films of Poly (Vinylidene) Fluoride (PVDF) are prepared by simple gel casting technique. Present work demands that aluminum-based hexaferrite phase conjugated with graphene in PVDF matrix becomes a suitable candidate both in commercially important X and Ku band. The structural and morphological nature was characterized by X-Ray diffraction (XRD), Field emission-scanning electron microscope (FESEM) and Raman spectra which conforms that 30-40 nm particles are well decorated over graphene sheet. Magnetic force microscopy (MFM) and conducting force microscopy (CFM) study further conforms the magnetic and conducting nature of composite. Finally, shielding effectiveness (SE) of the composite film was studied by using Vector network analyzer (VNA) both in X band and Ku band frequency range and found to be more than 30 dB and 40 dB, respectively. As prepared composite films are excellent microwave absorbers.

Keywords: carbon nanocomposite, microwave absorbing material, electromagnetic shielding, hexaferrite

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Authors: Yehjune Heo

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Fingerprint Anti-Spoofing approaches have been actively developed and applied in real-world applications. One of the main problems for Fingerprint Anti-Spoofing is not robust to unseen samples, especially in real-world scenarios. A possible solution will be to generate artificial, but realistic fingerprint samples and use them for training in order to achieve good generalization. This paper contains experimental and comparative results with currently popular GAN based methods and uses realistic synthesis of fingerprints in training in order to increase the performance. Among various GAN models, the most popular StyleGAN is used for the experiments. The CNN models were first trained with the dataset that did not contain generated fake images and the accuracy along with the mean average error rate were recorded. Then, the fake generated images (fake images of live fingerprints and fake images of spoof fingerprints) were each combined with the original images (real images of live fingerprints and real images of spoof fingerprints), and various CNN models were trained. The best performances for each CNN model, trained with the dataset of generated fake images and each time the accuracy and the mean average error rate, were recorded. We observe that current GAN based approaches need significant improvements for the Anti-Spoofing performance, although the overall quality of the synthesized fingerprints seems to be reasonable. We include the analysis of this performance degradation, especially with a small number of samples. In addition, we suggest several approaches towards improved generalization with a small number of samples, by focusing on what GAN based approaches should learn and should not learn.

Keywords: anti-spoofing, CNN, fingerprint recognition, GAN

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Authors: Sumaira Zafar, Arjumand Zaidi, Muhammad Arslan Hafeez

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Indus Basin Irrigation System (IBIS) is the largest contiguous irrigation system of the world comprising Indus River and its tributaries, canals, distributaries, and watercourses. A big challenge faced by IBIS is transmission losses through seepage and leaks that account to 41 percent of the total water derived from the river and about 40 percent of that is through watercourses. Irrigation system rehabilitation programs in Pakistan are focused on improvement of canal system at the watercourse level (tertiary channels). Under these irrigation system management programs more than 22,800 watercourses have been improved or lined out of 43,000 (12,900 Kilometers) watercourses. The evaluation of the improvement work is required at this stage to testify the success of the programs. In this paper, emerging technologies of GIS and satellite remote sensing are used for impact assessment of watercourse rehabilitation work in Sindh. To evaluate the efficiency of the improved watercourses, few parameters are selected like soil moisture along watercourses, availability of water at tail end and changes in cultivable command areas. Improved watercourses details and maps are acquired from National Program for Improvement of Watercourses (NPIW) and Space and Upper Atmospheric Research Commission (SUPARCO). High resolution satellite images of Google Earth for the year of 2004 to 2013 are used for digitizing command areas. Temporal maps of cultivable command areas show a noticeable increase in the cultivable land served by improved watercourses. Field visits are conducted to validate the results. Interviews with farmers and landowners also reveal their overall satisfaction in terms of availability of water at the tail end and increased crop production.

Keywords: geospatial, impact assessment, watercourses, GIS, remote sensing, seepage, canal lining

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Authors: Ali Riza Perçin, Eser Bingül

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Internet technologies have created opportunities with which people share their ideologies, thoughts and products. This virtual world, named social media has given the chance of gathering individual users and people from the world's remote locations and establishing an interaction between them. However, to an increasingly higher degree terrorist organizations today use the internet and most notably social-network media to create the effects they desire through a series of on-line activities. These activities, designed to support their activities, include information collection (intelligence), target selection, propaganda, fundraising and recruitment to name a few. Meanwhile, these have been used as the most important tool for recruitment especially from the different region of the world, especially disenfranchised youth, in the West in order to mobilize support and recruit “foreign fighters.” The recruits have obtained the statue, which is not accessible in their society and have preferred the style of life that is offered by the terrorist organizations instead of their current life. Like other terrorist groups, for a while now the terrorist organization Islamic State (IS) in Iraq and Syria has employed a social-media strategy in order to advance their strategic objectives. At the moment, however, IS seems to be more successful in their on-line activities than other similar organizations. IS uses social media strategically as part of its armed activities and for the sustainability of their military presence in Syria and Iraq. In this context, “Generation Y”, which could exist at the critical position and undertake active role, has been examined. Additionally, the explained characteristics of “Generation Y” have been put forward and the duties of families and society have been stated as well.

Keywords: social media, "generation Y", terrorist organization, islamic state IS

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Authors: Yitao Lei, Xingxiang Zhai, Burra Venkata Durga Kumar

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As the quantity and complexity of computing in large-scale software systems increase, distributed system computing becomes increasingly important. The distributed system realizes high-performance computing by collaboration between different computing resources. If there are no efficient resource scheduling resources, the abuse of distributed computing may cause resource waste and high costs. However, resource scheduling is usually an NP-hard problem, so we cannot find a general solution. However, some optimization algorithms exist like genetic algorithm, ant colony optimization, etc. The large scale of distributed systems makes this traditional optimization algorithm challenging to work with. Heuristic and machine learning algorithms are usually applied in this situation to ease the computing load. As a result, we do a review of traditional resource scheduling optimization algorithms and try to introduce a deep reinforcement learning method that utilizes the perceptual ability of neural networks and the decision-making ability of reinforcement learning. Using the machine learning method, we try to find important factors that influence the performance of distributed system computing and help the distributed system do an efficient computing resource scheduling. This paper surveys the application of deep reinforcement learning on distributed system computing resource scheduling proposes a deep reinforcement learning method that uses a recurrent neural network to optimize the resource scheduling, and proposes the challenges and improvement directions for DRL-based resource scheduling algorithms.

Keywords: resource scheduling, deep reinforcement learning, distributed system, artificial intelligence

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Authors: Richard Molyneux, Christopher Parrott, Kirill Horoshenkov

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This paper aims to demonstrate how various algorithms can be implemented within swarms of autonomous robots to provide continuous inspection within underground pipeline networks. Current methods of fault detection within pipes are costly, time consuming and inefficient. As such, solutions tend toward a more reactive approach, repairing faults, as opposed to proactively seeking leaks and blockages. The paper presents an efficient inspection method, showing that autonomous swarm robotics is a viable way of monitoring underground infrastructure. Tailored adaptations of various Vehicle Routing Problems (VRP) and path-planning algorithms provide a customised inspection procedure for complicated networks of underground pipes. The performance of multiple algorithms is compared to determine their effectiveness and feasibility. Notable inspirations come from ant colonies and stigmergy, graph theory, the k-Chinese Postman Problem ( -CPP) and traffic theory. Unlike most swarm behaviours which rely on fast communication between agents, underground pipe networks are a highly challenging communication environment with extremely limited communication ranges. This is due to the extreme variability in the pipe conditions and relatively high attenuation of acoustic and radio waves with which robots would usually communicate. This paper illustrates how to optimise the inspection process and how to increase the frequency with which the robots pass each other, without compromising the routes they are able to take to cover the whole network.

Keywords: autonomous inspection, buried pipes, stigmergy, swarm intelligence, vehicle routing problem

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Authors: Abobaker Mohammed Qasem Farhan, Shangming Yang, Mohammed Al-Nehari

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Pneumonia is a kind of lung disease that creates congestion in the chest. Such pneumonic conditions lead to loss of life of the severity of high congestion. Pneumonic lung disease is caused by viral pneumonia, bacterial pneumonia, or Covidi-19 induced pneumonia. The early prediction and classification of such lung diseases help to reduce the mortality rate. We propose the automatic Computer-Aided Diagnosis (CAD) system in this paper using the deep learning approach. The proposed CAD system takes input from raw computerized tomography (CT) scans of the patient's chest and automatically predicts disease classification. We designed the Hybrid Deep Learning Algorithm (HDLA) to improve accuracy and reduce processing requirements. The raw CT scans have pre-processed first to enhance their quality for further analysis. We then applied a hybrid model that consists of automatic feature extraction and classification. We propose the robust 2D Convolutional Neural Network (CNN) model to extract the automatic features from the pre-processed CT image. This CNN model assures feature learning with extremely effective 1D feature extraction for each input CT image. The outcome of the 2D CNN model is then normalized using the Min-Max technique. The second step of the proposed hybrid model is related to training and classification using different classifiers. The simulation outcomes using the publically available dataset prove the robustness and efficiency of the proposed model compared to state-of-art algorithms.

Keywords: CT scan, Covid-19, deep learning, image processing, lung disease classification

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Authors: H. Hakim, C. Kibert, C. Fabre, S. Monadizadeh

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Construction industry is an industry saddled with chronic problems of high waste generation. Waste management that is to ensure materials are utilized in an efficient manner would make a major contribution to mitigating the negative environmental impacts of construction waste including finite resources depletion and growing occupied landfill areas to name a few. Furthermore, ‘material resource efficiency’ has been found an economically smart approach specially when considered during the design phase. One effective strategy is to utilizing off-site construction process which includes a series of prefabricated systems such as mobile, modular, and HUD construction (Department of Housing and Urban Development manufactured buildings). These types of buildings are by nature material and resource-efficient. Despite conventional construction that is exposed to adverse weather conditions, manufactured construction production line is capable of creating repetitive units in a factory controlled environment. A factory can have several parallel projects underway with a high speed and in a timely manner which simplifies the storage of excess materials and re-allocating to the next projects. The literature reports that prefabricated construction significantly helps reduce errors, site theft, rework, and delayed problems and can ultimately lead to a considerable waste reduction. However, there is not sufficient data to quantify this reduction when it comes to a regular modular house in the U.S. Therefore, this manuscript aims to provide an analysis of waste originated from a manufactured factory trend. The analysis was made possible with several visits and data collection of Homes of Merits, a Florida Manufactured and Modular Homebuilder. The results quantify and verify a noticeable construction waste reduction.

Keywords: construction waste, modular construction, prefabricated buildings, waste management

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Authors: Emilee M. Cruz

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Teachers take part in short-term teaching fellowships abroad, and their preparation before, during, and after the experience is critical to affecting teachers’ feelings of success in the international classroom. A program evaluation of the teacher preparation within TALMA: The Israel Program for Excellence in English (TALMA) full-year teaching fellowship was conducted. A questionnaire was developed that examined professional development, deliberate reflection, and cultural and language immersion offered before, during, and after the short-term experience. The evaluation also surveyed teachers’ feelings of preparedness for the Israeli classroom and any recommendations they had for future teacher preparation within the fellowship program. The review suggests the TALMA program includes integrated professional learning communities between fellows and Israeli co-teachers, more opportunities for immersive Hebrew language learning, a broader professional network with Israelis, and opportunities for guided discussion with the TALMA community continued participation in TALMA events and learning following the full-year fellowship. Similar short-term international programs should consider the findings in the design of their participation preparation programs. The review also offers direction for future program evaluation of short-term participant preparation, including the need for frequent response item updates to match current offerings and evaluation of participant feelings of preparedness before, during, and after the full-year fellowship.

Keywords: educational program evaluation, international teaching, short-term teaching, teacher beliefs, teaching fellowship, teacher preparation

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Authors: Neda Seyyedi, Reza Berangi

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Voice over IP (VOIP) network, also known as Internet telephony, is growing increasingly having occupied a large part of the communications market. With the growth of each technology, the related security issues become of particular importance. Taking advantage of this technology in different environments with numerous features put at our disposal, there arises an increasing need to address the security threats. Being IP-based and playing a signaling role in VOIP networks, Session Initiation Protocol (SIP) lets the invaders use weaknesses of the protocol to disable VOIP service. One of the most important threats is denial of service attack, a branch of which in this article we have discussed as flooding attacks. These attacks make server resources wasted and deprive it from delivering service to authorized users. Distributed denial of service attacks and attacks with a low rate can mislead many attack detection mechanisms. In this paper, we introduce a mechanism which not only detects distributed denial of service attacks and low rate attacks, but can also identify the attackers accurately. We detect and prevent flooding attacks in SIP protocol using Shannon (FDP-S), Renyi (FDP-R) and Tsallis (FDP-T) entropy. We conducted an experiment to compare the percentage of detection and rate of false alarm messages using any of the Shannon, Renyi and Tsallis entropy as a measure of disorder. Implementation results show that, according to the parametric nature of the Renyi and Tsallis entropy, by changing the parameters, different detection percentages and false alarm rates will be gained with the possibility to adjust the sensitivity of the detection mechanism.

Keywords: VOIP networks, flooding attacks, entropy, computer networks

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Authors: Elron Fouten

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Recently, debates surrounding the social relevance of psychology in South Africa have focussed on how the growing neoliberal rationality within academia has again resulted in the discipline catering to the needs of powerful social groupings to protect its own economic interests, rather than producing socially relevant knowledge. Consequently, this study aimed to conduct a content analysis of the recent research output of psychology masters students, to establish whether it has produced research that addresses local and national psychosocial issues and as such deemed socially relevant knowledge. The study sampled clinical, counselling, and research psychology masters theses from 16 South African universities submitted between 1998 and 2017. Overall, 2001 theses were sampled, which were analysed using qualitative content analysis predominantly based on the descriptive categories identified in similar studies using published journal articles. Results indicated that empirical qualitative theses, using systems-oriented theory and post-modern frameworks were most prevalent. Further, traditional topics within psychology had relatively more weighting compared to more social topics. Although a significant number of theses recruited participants from working-class or poor backgrounds, there was an overreliance on participants from urban areas located in some of the country’s wealthiest provinces. Despite a strong adult-centric focus, trends regarding participants’ race and gender roughly resembled current population demographics. Overall, the results indicate that psychology in South Africa, at least at university-level, is to some extent trying to engage with national psychosocial concerns. However, there are still several key areas which need to be addressed to ensure the continued social relevance of the discipline.

Keywords: adult-centric, content analysis, relevance, psychosocial

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Authors: Nadia Allouache

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Solar radiation is by far the largest and the most world’s abundant, clean and permanent energy source. The amount of solar radiation intercepted by the Earth is much higher than annual global energy use. The energy available from the sun is greater than about 5200 times the global world’s need in 2006. In recent years, many promising technologies have been developed to harness the sun's energy. These technologies help in environmental protection, economizing energy, and sustainable development, which are the major issues of the world in the 21st century. One of these important technologies is the solar cooling systems that make use of either absorption or adsorption technologies. The solar adsorption cooling systems are good alternative since they operate with environmentally benign refrigerants that are natural, free from CFCs, and therefore they have a zero ozone depleting potential (ODP). A numerical analysis of thermal and solar performances of an adsorption solar refrigerating system using different adsorbent/adsorbate pairs such as activated carbon AC35 and activated carbon BPL/Ammoniac; is undertaken in this study. The modeling of the adsorption cooling machine requires the resolution of the equation describing the energy and mass transfer in the tubular adsorber that is the most important component of the machine. The Wilson and Dubinin- Astakhov models of the solid-adsorbat equilibrium are used to calculate the adsorbed quantity. The porous medium is contained in the annular space and the adsorber is heated by solar energy. Effect of key parameters on the adsorbed quantity and on the thermal and solar performances are analysed and discussed. The performances of the system that depends on the incident global irradiance during a whole day depends on the weather conditions: the condenser temperature and the evaporator temperature. The AC35/methanol pair is the best pair comparing to the BPL/Ammoniac in terms of system performances.

Keywords: activated carbon-methanol pair, activated carbon-ammoniac pair, adsorption, performance coefficients, numerical analysis, solar cooling system

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Authors: Parisa Göker, Hilal Kahveci, Özlem Candan Hergül

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Humans are generating culture while being in touch with nature. Along with skills, local knowledge based on experience, and many other subjects developed within this process, 'culture' offers humans a chance to survive. For this reason, culture forms the equipment for humans, which facilitates their survival in all ecosystems. Together with technology, quick consumption of natural sources and overuse culture of humans have brought up the eco-village concept. Ecovillages are ecologically, economically, socio-culturally, and spiritually sustainable settlement models. It is known that the eco-village approach is applying a proper methodology on behalf of integrative and versatile solution generation. Today, the eco-village approach, introducing a radical criticism to the understanding of civilization and consumption culture and deeming urban solutions inadequate as a spatial reflection to civilization and consumption culture, while making a difference about integrative solution offering with multidimensional features, along with the goal of creating self-sufficient communities, is creating solutions on the subject of both reducing the ecological footprint of humans and to provide social order and also to solve the injustice seen in terms of income and life standards. In this study, environmental issues, sustainable development, and environmental sustainability topics are examined within the context of eco-tourism and eco-village. Alongside this, the natural and cultural landscape values of Kurşunlu village which are located in Bilecik province’s Gölpazarı county, and a contextual frame is created for the facilitation of sustainability in the event of dynamizing the Kurşunlu village in terms of tourism-oriented activities.

Keywords: eco village, sustainability, rural landscape, cultural landscape

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Authors: Brian Bilich

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A typical global learning program is a two-week project based, culturally immersive and academically relevant experience built around a project with purpose and catered to student and business groups. Global Learning in Continuing Education at Austin Community College promotes global readiness through projects with purpose with special attention given to balancing learning, hospitality and travel. A recent project involved CommunityFirst! Village; a 51-acre planned community which provides affordable, permanent housing for men and women coming out of chronic homelessness. Global Learning students collaborated with residents and staff at the Community First! Village on a project to produce two-dimensional remodeling plans of residents’ tiny homes with a focus on but not limited to design improvements on elements related to accessibility, increased usability of living and storage space and esthetic upgrades to boost psychological and emotional appeal. The goal of project-based learning in the context of global learning in Continuing Educaiton at Austin Community Collegen general is two fold. One, in rapid fashion we develop a project which gives the learner a hands-on opportunity to exercise soft and technical skills, like creativity and communication and analytical thinking. Two, by basing projects on global social conflict issues, the project of purpose promotes the development of empathy for other people and fosters a sense of corporate social responsibility in future generations of business leadership. In the example provide above the project informed the student group on the topic of chronic homelessness and promoted awareness and empathy for this underserved segment of the community. Project-based global learning based on projects with purpose has the potential to cultivate global readiness by developing empathy and strengthening emotional intelligence for future generations.

Keywords: project-based learning, global learning, global readiness, globalization, international exchange, collaboration

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Authors: Dararat Tongdee, Surapong Chirarattananon, Somchai Maneewan, Chantana Punlek

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Recently, the Internet of Things (IoT) is the important technology that connects devices to the network and people can access real-time communication. This technology is used to report, collect, and analyze the big data for achieving a purpose. For a smart building, there are many IoT technologies that enable management and building operators to improve occupant thermal comfort, indoor air quality, and building energy efficiency. In this research, we propose monitoring and controlling performance of a smart dedicated outdoor air system (SDOAS) based on IoT platform. The SDOAS was specifically designed with the desiccant unit and thermoelectric module. The designed system was intended to monitor, notify, and control indoor environmental factors such as temperature, humidity, and carbon dioxide (CO₂) level. The SDOAS was tested under the American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE 62.2) and indoor air quality standard. The system will notify the user by Blynk notification when the status of the building is uncomfortable or tolerable limits are reached according to the conditions that were set. The user can then control the system via a Blynk application on a smartphone. The experimental result indicates that the temperature and humidity of indoor fresh air in the comfort zone are approximately 26 degree Celsius and 58% respectively. Furthermore, the CO₂ level was controlled lower than 1000 ppm by indoor air quality standard condition. Therefore, the proposed system can efficiently work and be easy to use for buildings.

Keywords: internet of things, indoor air quality, smart dedicated outdoor air system, thermal comfort

Procedia PDF Downloads 201