Search results for: decision based artificial neural network

Authors: A. El Kachani, E. Chakir, A. Ait Laachir, A. Niaaniaa, J. Zerouaoui

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This document presents an adaptive controller based on recursive parametric identification applied to a wind turbine based on the doubly-fed induction machine (DFIG), to compensate the faults and guarantee efficient of the DFIG. The proposed adaptive controller is based on the recursive least square algorithm which considers that the best estimator for the vector parameter is the vector x minimizing a quadratic criterion. Furthermore, this method can improve the rapidity and precision of the controller based on a model. The proposed controller is validated via simulation on a 5.5 kW DFIG-based wind turbine. The results obtained seem to be good. In addition, they show the advantages of an adaptive controller based on recursive least square algorithm.

Keywords: adaptive controller, recursive least squares algorithm, wind turbine, doubly fed induction generator

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Authors: Peiming Li

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This paper presents an innovative blockchain-based approach to enhance the reliability and efficiency of federated learning systems. By integrating a decentralized oracle consensus mechanism into the federated learning framework, we address key challenges of data and model integrity. Our approach utilizes a network of redundant oracles, functioning as independent validators within an epoch-based training system in the federated learning model. In federated learning, data is decentralized, residing on various participants' devices. This scenario often leads to concerns about data integrity and model quality. Our solution employs blockchain technology to establish a transparent and tamper-proof environment, ensuring secure data sharing and aggregation. The decentralized oracles, a concept borrowed from blockchain systems, act as unbiased validators. They assess the contributions of each participant using a Hidden Markov Model (HMM), which is crucial for evaluating the consistency of participant inputs and safeguarding against model poisoning and malicious activities. Our methodology's distinct feature is its epoch-based training. An epoch here refers to a specific training phase where data is updated and assessed for quality and relevance. The redundant oracles work in concert to validate data updates during these epochs, enhancing the system's resilience to security threats and data corruption. The effectiveness of this system was tested using the Mnist dataset, a standard in machine learning for benchmarking. Results demonstrate that our blockchain-oriented federated learning approach significantly boosts system resilience, addressing the common challenges of federated environments. This paper aims to make these advanced concepts accessible, even to those with a limited background in blockchain or federated learning. We provide a foundational understanding of how blockchain technology can revolutionize data integrity in decentralized systems and explain the role of oracles in maintaining model accuracy and reliability.

Keywords: federated learning system, block chain, decentralized oracles, hidden markov model

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Authors: Annika Stechemesser, Rachel Pounds, Emma Lucas, Chris Dawson, Julia Lipecki, Pavle Vrljicak, Jan Brosens, Sean Kehoe, Jason Yap, Lawrence Young, Sascha Ott

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Advances in technology make it now possible to retrieve the genetic information of thousands of single cancerous cells. One of the key challenges in single cell analysis of cancerous tissue is to determine the number of different cell types and their characteristic genes within the sample to better understand the tumors and their reaction to different treatments. For this analysis to be possible, it is crucial to filter out background noise as it can severely blur the downstream analysis and give misleading results. In-depth analysis of the state-of-the-art filtering methods for single cell data showed that they do, in some cases, not separate noisy and normal cells sufficiently. We introduced an algorithm that filters and clusters single cell data simultaneously without relying on certain genes or thresholds chosen by eye. It detects communities in a Shared Nearest Neighbor similarity network, which captures the similarities and dissimilarities of the cells by optimizing the modularity and then identifies and removes vertices with a weak clustering belonging. This strategy is based on the fact that noisy data instances are very likely to be similar to true cell types but do not match any of these wells. Once the clustering is complete, we apply a set of evaluation metrics on the cluster level and accept or reject clusters based on the outcome. The performance of our algorithm was tested on three datasets and led to convincing results. We were able to replicate the results on a Peripheral Blood Mononuclear Cells dataset. Furthermore, we applied the algorithm to two samples of ovarian cancer from the same patient before and after chemotherapy. Comparing the standard approach to our algorithm, we found a hidden cell type in the ovarian postchemotherapy data with interesting marker genes that are potentially relevant for medical research.

Keywords: cancer research, graph theory, machine learning, single cell analysis

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Authors: Rubens Duarte Coelho, Timóteo Herculino da Silva Barros, Jefferson de Olveira Costa

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Brazil has an electrical matrix of predominantly renewable origin, with emphasis on water sources, which account for 65.2%, biomass energy for 8.2%, wind for 6.8% and solar for 0.13% of the domestic supply. Among these sources, sugarcane cultivation stands out, aiming both at the production of bioethanol and biomass to supply “clean energy”. However, like all other crops, sugar cane demands a large volume of a natural resource that is increasingly “scarce” in quantity and quality: water. Adequate and strategic water management throughout the entire sugarcane cycle is of fundamental importance, and water productivity can be used to adjust irrigation planning and decision-making, increasing the productivity of stalks, bioethanol, biomass, and sugar. In this way, water productivity is a good indicator for analysis and decision-making considering the sustainability of cultivation, as it allows evaluation of the variation in the ratio between production and the amount of water used, suggesting values that maximize the use of this natural resource. In this context, studies that relate water demand, in this case, expressed by water productivity, with the energy production of this crop, in this case, expressed by the production of bioethanol, biomass and sugar, are fundamental to obtaining an efficient production of renewable energy, which aims at the rational use of natural resources, especially water. The objective of the present work was to evaluate the response of sugarcane varieties subjected to different water availability to obtain better sustainability in bioenergy production, presenting water productivity indices for Bioethanol, Sugar and Biomass. The variety that responded best was RB966928, with a bioethanol yield of 68.7 L Mg-1. Future research should focus on the water response under each of the sugarcane fractions in terms of their elemental composition so that the influence of water on the energy supply of this crop can be better understood.

Keywords: energy matrix, water use, water use efficiency, sustainability

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Authors: Umesh Kumar Singh, Abhishek Raghuvanshi, Suyash Kumar Singh

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As IoT networks gain popularity, they are more susceptible to security breaches. As a result, it is crucial to analyze the IoT platform as a whole from the standpoint of core security concepts. The Internet of Things relies heavily on wireless networks, which are well-known for being susceptible to a wide variety of attacks. This article provides an analysis of many techniques that may be used to identify vulnerabilities in the software and hardware associated with the Internet of Things (IoT). In the current investigation, an experimental setup is built with the assistance of server computers, client PCs, Internet of Things development boards, sensors, and cloud subscriptions. Through the use of network host scanning methods and vulnerability scanning tools, raw data relating to IoT-based applications and devices may be collected. Shodan is a tool that is used for scanning, and it is also used for effective vulnerability discovery in IoT devices as well as penetration testing. This article presents an efficient mitigation plan for encountering vulnerabilities in the Internet of Things.

Keywords: internet of things, security, privacy, vulnerability identification, mitigation plan

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Authors: Stefan Peters, Phillip Roetman

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The global loss of biodiversity is threatening the benefits nature provides to human populations and has become a more pressing issue than climate change and requires immediate attention. While there have been successful global agreements for environmental protection, such as the Montreal Protocol, these are rare, and we cannot rely on them solely. Thus, it is crucial to take national and local actions to support biodiversity. Australia is one of the 17 countries in the world with a high level of biodiversity, and its cities are vital habitats for endangered species, with more of them found in urban areas than in non-urban ones. However, the protection of biodiversity in metropolitan Adelaide has been inadequate, with over 130 species disappearing since European colonization in 1836. In this research project we conceptualized, developed and implemented a framework for wildlife Habitat Hotspots and Habitat Corridor modelling in an urban context using geographic data and GIS modelling and analysis. We used detailed topographic and other geographic data provided by a local council, including spatial and attributive properties of trees, parcels, water features, vegetated areas, roads, verges, traffic, and census data. Weighted factors considered in our raster-based Habitat Hotspot model include parcel size, parcel shape, population density, canopy cover, habitat quality and proximity to habitats and water features. Weighted factors considered in our raster-based Habitat Corridor model include habitat potential (resulting from the Habitat Hotspot model), verge size, road hierarchy, road widths, human density, and presence of remnant indigenous vegetation species. We developed a GIS model, using Python scripting and ArcGIS-Pro Model-Builder, to establish an automated reproducible and adjustable geoprocessing workflow, adaptable to any study area of interest. Our habitat hotspot and corridor modelling framework allow to determine and map existing habitat hotspots and wildlife habitat corridors. Our research had been applied to the study case of Burnside, a local council in Adelaide, Australia, which encompass an area of 30 km2. We applied end-user expertise-based category weightings to refine our models and optimize the use of our habitat map outputs towards informing local strategic decision-making.

Keywords: biodiversity, GIS modeling, habitat hotspot, wildlife corridor

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Authors: Nasser Koleini Mamaghani, Sara Mostowfi

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The complexity of public space design makes it difficult for designers to simultaneously consider all issues for thorough decision-making. Among public spaces, the public space around people’s house is the most prominent space that affects and impacts people’s daily life. Considering recreational public spaces in cities, their main purpose would be to design for experiences that enable a deep feeling of peace and a moment of being away from the hectic daily life. Respecting human emotions and restoring natural environments, although difficult and to some extent out of reach, are key issues for designing such spaces. In this paper we propose to analyse the structure of recreational public spaces and the related emotional impressions. Furthermore, we suggest investigating how these structures influence people’s choice for public spaces by using differential semantics. According to Kansei methodology, in order to evaluate a situation appropriately, the assessment variables must be adapted to the user’s mental scheme. This means that the first step would have to be the identification of a space’s conceptual scheme. In our case study, 32 Kansei words and 4 different locations, each with a different sensual experience, were selected. The 4 locations were all parks in the city of Tehran (Iran), each with a unique structure and artifacts such as a fountain, lighting, sculptures, and music. It should be noted that each of these parks has different combination and structure of environmental and artificial elements like: fountain, lightning, sculpture, music (sound) and so forth. The first one was park No.1, a park with natural environment, the selected space was a fountain with motion light and sculpture. The second park was park No.2, in which there are different styles of park construction: ways from different countries, the selected space was traditional Iranian architecture with a fountain and trees. The third one was park No.3, the park with modern environment and spaces, and included a fountain that moved according to music and lighting. The fourth park was park No.4, the park with combination of four elements: water, fire, earth, wind, the selected space was fountains squirting water from the ground up. 80 participant (55 males and 25 females) aged from 20-60 years participated in this experiment. Each person filled the questionnaire in the park he/she was in. Five-point semantic differential scale was considered to determine the relation between space details and adjectives (kansei words). Received data were analyzed by multivariate statistical technique (factor analysis using SPSS statics). Finally the results of this analysis are criteria as inspiration which can be used in future space designing for creating pleasant feeling in users.

Keywords: environmental design, differential semantics, Kansei engineering, subjective preferences, space

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Authors: Arun Dhakal, Geoff Cockfield, Tek Narayan Maraseni

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This paper attempts to fulfil the gap in measuring adoption in agroforestry studies. It explains the derivation of an index of adoption rate in a Nepalese context and examines the factors affecting adoption of agroforestry-based land management practice (AFLMP) in the Dhanusha District of Nepal. Data about the different farm practices and the factors (bio-physical, socio-economic) influencing adoption were collected during focus group discussion and from the randomly selected households using a household survey questionnaire, respectively. A multivariate regression model was used to determine the factors. The factors (variables) found to significantly affect adoption of AFLMP were: farm size, availability of irrigation water, education of household heads, agricultural labour force, frequency of visits by extension workers, expenditure on farm inputs purchase, household’s experience in agroforestry, and distance from home to government forest. The regression model explained about 75% of variation in adoption decision. The model rejected ‘erosion hazard’, ‘flood hazard’ and ‘gender’ as determinants of adoption, which in case of single agroforestry practice were major variables and played positive role. Out of eight variables, farm size played the most powerful role in explaining the variation in adoption, followed by availability of irrigation water and education of household heads. The results of this study suggest that policies to promote the provision of irrigation water, extension services and motivation to obtaining higher education would probably provide the incentive to adopt agroforestry elsewhere in the terai of Nepal.

Keywords: agroforestry, adoption index, determinants of adoption, step-wise linear regression, Nepal

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Authors: Caroline Atef Shoukry Tadros

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Massive Urbanization growth threatens the sustainability of cities and the quality of city life. This raised the need for an alternate model of sustainability, so we need to plan the future cities in a smarter way with smarter mobility. Smart Mobility planning applications are solutions that use digital technologies and infrastructure advances to improve the efficiency, sustainability, and inclusiveness of urban transportation systems. They can contribute to meeting the needs of Urbanization growth by addressing the challenges of traffic congestion, pollution, accessibility, and safety in cities. Some example of a Smart Mobility planning application are Mobility-as-a-service: This is a service that integrates different transport modes, such as public transport, shared mobility, and active mobility, into a single platform that allows users to plan, book, and pay for their trips. This can reduce the reliance on private cars, optimize the use of existing infrastructure, and provide more choices and convenience for travelers. MaaS Global is a company that offers mobility-as-a-service solutions in several cities around the world. Traffic flow optimization: This is a solution that uses data analytics, artificial intelligence, and sensors to monitor and manage traffic conditions in real-time. This can reduce congestion, emissions, and travel time, as well as improve road safety and user satisfaction. Waycare is a platform that leverages data from various sources, such as connected vehicles, mobile applications, and road cameras, to provide traffic management agencies with insights and recommendations to optimize traffic flow. Logistics optimization: This is a solution that uses smart algorithms, blockchain, and IoT to improve the efficiency and transparency of the delivery of goods and services in urban areas. This can reduce the costs, emissions, and delays associated with logistics, as well as enhance the customer experience and trust. ShipChain is a blockchain-based platform that connects shippers, carriers, and customers and provides end-to-end visibility and traceability of the shipments. Autonomous vehicles: This is a solution that uses advanced sensors, software, and communication systems to enable vehicles to operate without human intervention. This can improve the safety, accessibility, and productivity of transportation, as well as reduce the need for parking space and infrastructure maintenance. Waymo is a company that develops and operates autonomous vehicles for various purposes, such as ride-hailing, delivery, and trucking. These are some of the ways that Smart Mobility planning applications can contribute to meeting the needs of the Urbanization growth. However, there are also various opportunities and challenges related to the implementation and adoption of these solutions, such as the regulatory, ethical, social, and technical aspects. Therefore, it is important to consider the specific context and needs of each city and its stakeholders when designing and deploying Smart Mobility planning applications.

Keywords: smart mobility planning, smart mobility applications, smart mobility techniques, smart mobility tools, smart transportation, smart cities, urbanization growth, future smart cities, intelligent cities, ICT information and communications technologies, IoT internet of things, sensors, lidar, digital twin, ai artificial intelligence, AR augmented reality, VR virtual reality, robotics, cps cyber physical systems, citizens design science

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Authors: Alex Ellery

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Geoengineering approaches to climate change mitigation are unpopular and regarded with suspicion. Of these, space-based approaches are regarded as unworkable and enormously costly. Here, a space-based approach is presented that is modest in cost, fully controllable and reversible, and acts as a natural spur to the development of solar power satellites over the longer term as a clean source of energy. The low-cost approach exploits self-replication technology which it is proposed may be enabled by 3D printing technology. Self-replication of 3D printing platforms will enable mass production of simple spacecraft units. Key elements being developed are 3D-printable electric motors and 3D-printable vacuum tube-based electronics. The power of such technologies will open up enormous possibilities at low cost including space-based geoengineering.

Keywords: 3D printing, in-situ resource utilization, self-replication technology, space-based geoengineering

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Authors: Burcin Basyazici

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The history of urban regeneration in Istanbul dates to the 1980s and has been generated by various reasons, from political state-based decisions to cultural migrations and/or translocations and economical private sector-based reasons. However, one of the latest regeneration areas in Fikirtepe that have been still under construction for ten years becomes dissimilar to other regeneration areas in Istanbul. The region is located very close to Kadıkoy's downtown area but was still considered a slum due to its inhabitants -who mostly belong to lower-income immigrants. The process begun in 2011 with the decision of the government, and the settlement has been emptied and demolished also by the government -together with the investors and construction companies. Although there has been much research on the process of deconstruction and the relocation of landlords, there hasn’t been any research on what happened after the regeneration. While many high-rise luxurious gated communities were constructed and inhabited in five years, many constructions have stopped due to the latest economic devastation in Turkey. Then the region stayed as an unfinished construction area with its new upper-income and upper-middle-income residents and old low-income landlords. This situation has also changed the commercial activities in Fikirtepe. While some new retail facilities have been offered for new residents, some of the oldest ones have also survived in new-Fikirtepe. This study aims to investigate the urban everyday life of Fikirtepe with relation to its retail-based regeneration with the help of the theories of Bourdieu called cultural capital and cultural omnivorousness. To achieve this aim, after presenting the historical background of urban regeneration in Istanbul, Bourdieu’s conceptualism of cultural capital, habitus, and the consumption tendencies related to those are introduced and discussed within the scope of the Fikirtepe case. To represent the retail-based regeneration in the area, the current situation of retail premises is mapped by comparing to its pre-situation before urban gentrification. To better understand the change of cultural capital and the consumption tendencies of the new residents, eighteen semi-structured in-depth interviews have been conducted with twelve inhabitants from three different luxurious gated communities and six shop owners containing the new ones after regeneration and old ones before it. The interview questions have been structured to understand the motivation of change and/or inhibition of retail premises and the consumption tendencies of the new residents. In conclusion, the study shows that even though the cultural capital has been changed in Fikirtepe, the new residents also tend to act as culturally omnivorous by referring to Bourdieu's theories on multi-cultural tendencies of the upper-class and upper-middle-class societies, that should be questioned regarding the cultural regeneration in in-town urban regeneration areas in metropoles.

Keywords: bourdieu, cultural omnivorousness, fikirtepe, urban regeneration in istanbul

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Authors: P. H. Tee, S. M. Zamri, K. M. Kasim, S. K. Tiew

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This study evaluates the management of osteoporosis in a tertiary care government hospital in Malaysia. As the number of admitted patients having osteoporotic fractures is on the rise, osteoporotic medications are an increasing financial burden to government hospitals because they account for half of the orthopedic budget and expenditure. Comprehensive knowledge among practitioners is important to detect early and avoid this preventable disease and its serious complications. The purpose of this study is to evaluate the awareness, knowledge, and practices in managing osteoporosis among practitioners in Hospital Tengku Ampuan Rahimah (HTAR), Klang. A questionnaire from an overseas study in managing osteoporosis among primary care physicians is adapted to Malaysia’s Clinical Practice Guideline of Osteoporosis 2012 (revised 2015) and international guidelines were distributed to all orthopedic practitioners in HTAR Klang (including surgeons, orthopedic medical officers), endocrinologists, rheumatologists and geriatricians. The participants were evaluated on their expertise in the diagnosis, prevention, treatment decision and medications for osteoporosis. Collected data were analyzed for all descriptive and statistical analyses as appropriate. All 45 participants responded to the questionnaire. Participants scored highest on expertise in prevention, followed by diagnosis, treatment decision and lastly, medication. Most practitioners stated that own-initiated continuing professional education from articles and books was the most effective way to update their knowledge, followed by attendance in conferences on osteoporosis. This study confirms the importance of comprehensive training and education regarding osteoporosis among tertiary care physicians and surgeons, predominantly in pharmacotherapy, to deliver wholesome care for osteoporotic patients.

Keywords: awareness, knowledge, osteoporosis, practices

Procedia PDF Downloads 117

Authors: Jude Inwumoh, Adam P. R. Taylor, Kosala Gunawardane

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Modular multilevel converters (MMC) exhibit a highly scalable and modular characteristic with good voltage/power expansion, fault tolerance capability, low output harmonic content, good redundancy, and a flexible front-end configuration. Fault detection, location, and isolation, as well as maintaining fault ride-through (FRT), are major challenges to MMC reliability and power supply sustainability. Different papers have been reviewed to seek the best MMC configuration with fault capability. DC faults are the most common fault, while the probability that AC fault occurs in a modular multilevel converter (MCC) is low; though, AC faults consequence are severe. This paper reviews several MMC topologies and modulation techniques in tackling faults. These fault control strategies are compared based on cost, complexity, controllability, and power loss. A meshed network of half-bridge (HB) MMC topology was optimal in rendering fault ride through than any other MMC topologies but only when combined with DC circuit breakers (CBS), AC CBS, and fault current limiters (FCL).

Keywords: MMC-HVDC, DC faults, fault current limiters, control scheme

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Authors: Rosyidah Muhamad

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New media is facilitating collective action in ways never thought possible. Although the broader political climate may have a powerful influence on the success or failure of emerging social movement organizations, the Internet is enabling groups previously incapable of political action to find their voices Whether this shift is offering greater relative benefit to previously underrepresented or incumbent political fixtures is subject to debate, but it is clear that like-minded people are now able to better locate and converse with each other via many Internet. The recent social movement in Malaysia – the BERSIH Movement had attracted demonstrators from countries all over the world. The movement with an unforeseen mixture of nationalities became world news. Interestingly, the new media seemed to play a crucial role in the organization of the protests around the world. This article maps this movement via an analysis of their websites. It examines the contribution of these websites based on the collective identity, actual mobilization and a network of organizations. This research indicates signs of an integration of different organizations that contributed to an important role of the new media.

Keywords: Bersih Movement, Malaysian politics, new media, social movement

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Authors: Joanna Bajerska, Agata Chmurzyńska, Agata Muzsik, Patrycja Krzyżanowska, Klaudia Łochocka, Jarosław Walkowiak

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The Mediterranean diet (MED) is regarded as beneficial in the therapy of central obesity-associated metabolic abnormalities. However, in the traditional diet of the Central European countries, food items with positive nutritional profiles (rye bread, oats, buckwheat, herrings, linseed and rapeseed oil, berries, apples, plums, root vegetables etc.) are also used. We hypothesized that the Central European Diet (CED) may be comparatively effective in reducing symptoms of central obesity as MED. We tested the health effects of the CED, which is an environmentally friendly regional diet and the traditional MED diet in a group of postmenopausal centrally obese women. A total 58 with a mean age of 60 y (50-70y), body mass index (in kg/m(2)) of 33.4 (22.6-47.3), and waist circumference of 105 cm (87.5-137 cm) were randomly assigned to receive either the diet based on food items commonly used in Central Europe (the CED group; n = 29) or the Mediterranean diet (the MED group; n = 29) for 15 weeks. Body mass and body composition were measured with a Bod Pod (Cosmed, Italy). A non-elastic flexible measuring tape was used to measure waist circumference. Additionally, blood pressure, plasma lipid and glucose levels were assessed with the use of a biochemical analyzer. A total of 50 subjects [86% (CED 83%; MED 90%)] completed the intervention. A high dietary compliance for both described diets was achieved. The mean (±SEM) weight and waist circumference changes were -7.4 ± 0.7 kg; -8.3 ± 0.7 cm and -8.1 ± 0.5 kg; -7.1 ± 0.6 cm for the CED and MED groups, respectively. Moreover, there were no differences between the effectiveness of the diets used in terms of the influence on fat mass, blood pressure, and biochemical parameters. The preliminary data suggest that both described diets may be successfully used for improving central obesity-associated metabolic abnormalities. The project was financed by the National Science Centre awarded based on the number of decision DEC-013/09/B/NZ9/02365

Keywords: central european diet, central obesity, Mediterranean diet, metabolic abnormalities

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Authors: N. F. F. Ebecken, G. C. Pereira

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Although networks provide a powerful approach to the study of a wide variety of ecological systems, their formulation usually does not include various types of interactions, interactions that vary in space and time, and interconnected systems such as networks. The emerging field of 'multilayer networks' provides a natural framework for extending ecological systems analysis to include these multiple layers of complexity as it specifically allows for differentiation and modeling of intralayer and interlayer connectivity. The structure provides a set of concepts and tools that can be adapted and applied to the ecology, facilitating research in high dimensionality, heterogeneous systems in nature. Here, ecological multilayer networks are formally defined based on a review of prior and related approaches, illustrates their application and potential with existing data analyzes, and discusses limitations, challenges, and future applications. The integration of multilayer network theory into ecology offers a largely untapped potential to further address ecological complexity, to finally provide new theoretical and empirical insights into the architecture and dynamics of ecological systems.

Keywords: ecological networks, multilayered networks, sea ecology, Brazilian Coastal Area

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Authors: Mohamamd Shahjahan

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Background: Cybercrime is common phenomenon at present both developed and developing countries. Young generation, especially adolescents now engaged internet frequently and they commit cybercrime frequently in Bangladesh. Objective: In this regard, the present study on the pattern of cybercrime among youngers of Bangladesh has been conducted. Methods and tools: This study was a cross-sectional study, descriptive in nature. Non-probability accidental sampling technique has been applied to select the sample because of the nonfinite population and the sample size was 167. A printed semi-structured questionnaire was used to collect data. Results: The study shows that adolescents mainly do hacking (94.6%), pornography (88.6%), software piracy (85 %), cyber theft (82.6%), credit card fraud (81.4%), cyber defamation (75.6%), sweet heart swindling (social network) (65.9%) etc. as cybercrime. According to findings the major causes of cybercrime among the respondents in Bangladesh were- weak laws (88.0%), defective socialization (81.4%), peer group influence (80.2%), easy accessibility to internet (74.3%), corruption (62.9%), unemployment (58.7%), and poverty (24.6%) etc. It is evident from the study that 91.0% respondents used password cracker as the techniques of cyber criminality. About 76.6%, 72.5%, 71.9%, 68.3% and 60.5% respondents’ technique was key loggers, network sniffer, exploiting, vulnerability scanner and port scanner consecutively. Conclusion: The study concluded that pattern of cybercrimes is frequently changing and increasing dramatically. Finally, it is recommending that the private public partnership and execution of existing laws can be controlling this crime.

Keywords: cybercrime, adolescents, pattern, internet

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Authors: Yana Snegireva

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Carbonate reservoirs are known for their heterogeneity, resulting from various geological processes such as diagenesis and fracturing. These complexities may cause great challenges in understanding fluid flow behavior and predicting the production performance of naturally fractured reservoirs. The investigation of carbonate reservoirs is crucial, as many petroleum reservoirs are naturally fractured, which can be difficult due to the complexity of their fracture networks. This can lead to geological uncertainties, which are important for global petroleum reserves. The problem outlines the key challenges in carbonate reservoir modeling, including the accurate representation of fractures and their connectivity, as well as capturing the impact of fractures on fluid flow and production. Traditional reservoir modeling techniques often oversimplify fracture networks, leading to inaccurate predictions. Therefore, there is a need for a modern approach that can capture the complexities of carbonate reservoirs and provide reliable predictions for effective reservoir management and production optimization. The modern approach to carbonate reservoir modeling involves the utilization of the hybrid fracture modeling approach, including the discrete fracture network (DFN) method and implicit fracture network, which offer enhanced accuracy and reliability in characterizing complex fracture systems within these reservoirs. This study focuses on the application of the hybrid method in the Nepsko-Botuobinskaya anticline of the Eastern Siberia field, aiming to prove the appropriateness of this method in these geological conditions. The DFN method is adopted to model the fracture network within the carbonate reservoir. This method considers fractures as discrete entities, capturing their geometry, orientation, and connectivity. But the method has significant disadvantages since the number of fractures in the field can be very high. Due to limitations in the amount of main memory, it is very difficult to represent these fractures explicitly. By integrating data from image logs (formation micro imager), core data, and fracture density logs, a discrete fracture network (DFN) model can be constructed to represent fracture characteristics for hydraulically relevant fractures. The results obtained from the DFN modeling approaches provide valuable insights into the East Siberia field's carbonate reservoir behavior. The DFN model accurately captures the fracture system, allowing for a better understanding of fluid flow pathways, connectivity, and potential production zones. The analysis of simulation results enables the identification of zones of increased fracturing and optimization opportunities for reservoir development with the potential application of enhanced oil recovery techniques, which were considered in further simulations on the dual porosity and dual permeability models. This approach considers fractures as separate, interconnected flow paths within the reservoir matrix, allowing for the characterization of dual-porosity media. The case study of the East Siberia field demonstrates the effectiveness of the hybrid model method in accurately representing fracture systems and predicting reservoir behavior. The findings from this study contribute to improved reservoir management and production optimization in carbonate reservoirs with the use of enhanced and improved oil recovery methods.

Keywords: carbonate reservoir, discrete fracture network, fracture modeling, dual porosity, enhanced oil recovery, implicit fracture model, hybrid fracture model

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Authors: Bhim Kumar Dahal

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Transportation network development in the developing country is in rapid pace. The majority of the network belongs to railway and expressway which passes through diverse topography, landform and geological conditions despite the avoidance principle during route selection. Construction of such networks demand many low to high embankment which required improvement in the foundation soil. This paper is mainly focused on the various advanced ground improvement techniques used to improve the soft soil, modelling approach and its predictability for embankments construction. The ground improvement techniques can be broadly classified in to three groups i.e. densification group, drainage and consolidation group and reinforcement group which are discussed with some case studies.  Various methods were used in modelling of the embankments from simple 1-dimensional to complex 3-dimensional model using variety of constitutive models. However, the reliability of the predictions is not found systematically improved with the level of sophistication.  And sometimes the predictions are deviated more than 60% to the monitored value besides using same level of erudition. This deviation is found mainly due to the selection of constitutive model, assumptions made during different stages, deviation in the selection of model parameters and simplification during physical modelling of the ground condition. This deviation can be reduced by using optimization process, optimization tools and sensitivity analysis of the model parameters which will guide to select the appropriate model parameters.

Keywords: cement, improvement, physical properties, strength

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Authors: Fabio Fabris, Alex A. Freitas

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Hierarchical classification is a special type of classification task where the class labels are organised into a hierarchy, with more generic class labels being ancestors of more specific ones. Meta-learning for classification-algorithm recommendation consists of recommending to the user a classification algorithm, from a pool of candidate algorithms, for a dataset, based on the past performance of the candidate algorithms in other datasets. Meta-learning is normally used in conventional, non-hierarchical classification. By contrast, this paper proposes a meta-learning approach for more challenging task of hierarchical classification, and evaluates it in a large number of bioinformatics datasets. Hierarchical classification is especially relevant for bioinformatics problems, as protein and gene functions tend to be organised into a hierarchy of class labels. This work proposes meta-learning approach for recommending the best hierarchical classification algorithm to a hierarchical classification dataset. This work’s contributions are: 1) proposing an algorithm for splitting hierarchical datasets into new datasets to increase the number of meta-instances, 2) proposing meta-features for hierarchical classification, and 3) interpreting decision-tree meta-models for hierarchical classification algorithm recommendation.

Keywords: algorithm recommendation, meta-learning, bioinformatics, hierarchical classification

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Authors: Yanjun Chen, Chuanping Hu, Jie Shao, Lin Mei, Chongyang Zhang

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Traditional image classification is based on encoding scheme (e.g. Fisher Vector, Vector of Locally Aggregated Descriptor) with low-level image features (e.g. SIFT, HoG). Compared to these low-level local features, deep convolutional features obtained at the mid-level layer of convolutional neural networks (CNN) have richer information but lack of geometric invariance. For scene classification, there are scattered objects with different size, category, layout, number and so on. It is crucial to find the distinctive objects in scene as well as their co-occurrence relationship. In this paper, we propose a method to take advantage of both deep convolutional features and the traditional encoding scheme while taking object-centric and scene-centric information into consideration. First, to exploit the object-centric and scene-centric information, two CNNs that trained on ImageNet and Places dataset separately are used as the pre-trained models to extract deep convolutional features at multiple scales. This produces dense local activations. By analyzing the performance of different CNNs at multiple scales, it is found that each CNN works better in different scale ranges. A scale-wise CNN adaption is reasonable since objects in scene are at its own specific scale. Second, a fisher kernel is applied to aggregate a global representation at each scale and then to merge into a single vector by using a post-processing method called scale-wise normalization. The essence of Fisher Vector lies on the accumulation of the first and second order differences. Hence, the scale-wise normalization followed by average pooling would balance the influence of each scale since different amount of features are extracted. Third, the Fisher vector representation based on the deep convolutional features is followed by a linear Supported Vector Machine, which is a simple yet efficient way to classify the scene categories. Experimental results show that the scale-specific feature extraction and normalization with CNNs trained on object-centric and scene-centric datasets can boost the results from 74.03% up to 79.43% on MIT Indoor67 when only two scales are used (compared to results at single scale). The result is comparable to state-of-art performance which proves that the representation can be applied to other visual recognition tasks.

Keywords: deep convolutional features, Fisher Vector, multiple scales, scale-specific normalization

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Authors: Lin-Lin Liu, Song-Qi Hu, Yin Wang

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Paraffin-based fuels are regarded to be a promising fuel of hybrid rocked motor because of the high regression rate, low price, and environmental friendliness. Graphene Oxide (GO) is an attractive energetic material which is expected to be widely used in propellants, explosives, and some high energy fuels. Paraffin-based fuels with paraffin and GO as raw materials were prepared, and the oxidation process of the samples was investigated by thermogravimetric analysis differential scanning calorimetry (TG/DSC) under oxygen (O₂) and nitrous oxide (N₂O) atmospheres. The oxidation reaction kinetics of the fuels was estimated through the non-isothermal measurements and model-free isoconversional methods based on the experimental results of TGA. The results show that paraffin-based fuels are easier oxidized under O₂ rather than N₂O with atmospheres due to the lower activation energy; GO plays a catalytic role for the oxidation of paraffin-based fuels under the both atmospheres, and the activation energy of the oxidation process decreases with the increase of GO; catalytic effect of GO on the oxidation of paraffin-based fuels are more obvious under O₂ atmospheres than under N₂O atmospheres.

Keywords: graphene oxide, paraffin-based fuels, oxidation, activation energy, TGA

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Authors: Liang-Hsuan Chen, Sheng-Shing Nien

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This study aims to develop approaches to formulate intuitionistic fuzzy regression (IFR) models for many decision-making applications in the fuzzy environments using intuitionistic fuzzy observations. Intuitionistic fuzzy numbers (IFNs) are used to characterize the fuzzy input and output variables in the IFR formulation processes. A mathematical programming problem (MPP) is built up to optimally determine the IFR parameters. Each parameter in the MPP is defined as a couple of alternative numerical variables with opposite signs, and an intuitionistic fuzzy error term is added to the MPP to characterize the uncertainty of the model. The IFR model is formulated based on the distance measure to minimize the total distance errors between estimated and observed intuitionistic fuzzy responses in the MPP resolution processes. The proposed approaches are simple/efficient in the formulation/resolution processes, in which the sign of parameters can be determined so that the problem to predetermine the sign of parameters is avoided. Furthermore, the proposed approach has the advantage that the spread of the predicted IFN response will not be over-increased, since the parameters in the established IFR model are crisp. The performance of the obtained models is evaluated and compared with the existing approaches.

Keywords: fuzzy sets, intuitionistic fuzzy number, intuitionistic fuzzy regression, mathematical programming method

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Authors: S. Jayalakshmi, Gayathri S., Subiksa V., Nithyasri P., Agasthiya

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Paleochannels are the buried part of an active river system which was separated from the active river channel by the process of cutoff or abandonment during the dynamic evolution of the active river. Over time, they are filled by young unconsolidated or semi-consolidated sediments. Additionally, it is impacted by geo morphological influences, lineament alterations, and other factors. The primary goal of this study is to identify the paleochannels in Periyar river basin for the year 2023. Those channels has a high probability in the presence of natural resources, including gold, platinum,tin,an duranium. Numerous techniques are used to map the paleochannel. Using the optical data, Satellite images were collected from various sources, which comprises multispectral satellite images from which indices such as Normalized Difference Vegetation Index (NDVI),Normalized Difference Water Index (NDWI), Soil Adjusted Vegetative Index (SAVI) and thematic layers such as Lithology, Stream Network, Lineament were prepared. Weights are assigned to each layer based on its importance, and overlay analysis has done, which concluded that the northwest region of the area has shown some paleochannel patterns. The results were cross-verified using the results obtained using microwave data. Using Sentinel data, Synthetic Aperture Radar (SAR) Image was extracted from European Space Agency (ESA) portal, pre-processed it using SNAP 6.0. In addition to that, Polarimetric decomposition technique has incorporated to detect the paleochannels based on its scattering property. Further, Principal component analysis has done for enhanced output imagery. Results obtained from optical and microwave radar data were compared and the location of paleochannels were detected. It resulted six paleochannels in the study area out of which three paleochannels were validated with the existing data published by Department of Geology and Environmental Science, Kerala. The other three paleochannels were newly detected with the help of SAR image.

Keywords: paleochannels, optical data, SAR image, SNAP

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Authors: Abdullah Abu-Tineh, Hissa Sadiq, Fatma Al-Mutawah, Youmen Chaaban

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The past 20 years have seen a proliferation of empirical research into various licensure systems. Extensive quantitative work investigates these systems of appraisal from different countries, but there is far less research on the implementation of the Qatari licensure system and the adoption of professional standards. In this paper, we provided a quantitatively and qualitatively descriptive look at the process that moves educators from their point of entry into the profession through their certification as accomplished professionals. Specifically, we focused on the perceptions of teachers and school leaders on the licensure system currently adopted by Ministry of Education and Higher Education in Qatar. The paper aims to inform progress towards a system of reliable, valid, and nationally appropriate teacher and school leader evaluation procedures. Such a system can support decision-making based on a common, comprehensive set of standards that ensures the placement of only the most effective educators in Qatari schools. This paper was made possible by NPRP grant # (NPRP7-1224-5-178) from the Qatar national research fund (a member of Qatar foundation) to Abdullah M. Abu-Tineh. The statements made herein are solely the responsibility of the author.

Keywords: licensure system, professional standards, professional portfolio, educator voice

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Authors: Sade Ogundipe

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The private healthcare sector in the United Kingdom has experienced unprecedented challenges during times of crisis, necessitating effective leadership adaptability. This qualitative study delves into the dynamic landscape of leadership within the sector, particularly during crises, employing the lenses of complexity theory and institutional theory to unravel the intricate mechanisms at play. Through in-depth interviews with 25 various levels of leaders in the UK private healthcare sector, this research explores how leaders in UK private healthcare organizations navigate complex and often chaotic environments, shedding light on their adaptive strategies and decision-making processes during crises. Complexity theory is used to analyze the complicated, volatile nature of healthcare crises, emphasizing the need for adaptive leadership in such contexts. Institutional theory, on the other hand, provides insights into how external and internal institutional pressures influence leadership behavior. Findings from this study highlight the multifaceted nature of leadership adaptability, emphasizing the significance of leaders' abilities to embrace uncertainty, engage in sensemaking, and leverage the institutional environment to enact meaningful changes. Furthermore, this research sheds light on the challenges and opportunities that leaders face when adapting to crises within the UK private healthcare sector. The study's insights contribute to the growing body of literature on leadership in healthcare, offering practical implications for leaders, policymakers, and stakeholders within the UK private healthcare sector. By employing the dual perspectives of complexity theory and institutional theory, this research provides a holistic understanding of leadership adaptability in the face of crises, offering valuable guidance for enhancing the resilience and effectiveness of healthcare leadership within this vital sector.

Keywords: leadership, adaptability, decision-making, complexity, complexity theory, institutional theory, organizational complexity, complex adaptive system (CAS), crises, healthcare

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Authors: Haleema Sadia

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The study is aimed at exploring the identity construction of female British born Pakistani postgraduate student who shifted to Pakistan at the age of 12, stayed there for 8 years and re-shifted to UK for Higher Education. Research questions are: 1. What is the academic and socio-cultural background of the participant prior to joining the UoM as a postgrad student? 2. How the participant talk, see herself and act in relation to cultural and social norms and practices? Participant’ identity is explored through positioning theory of Holland et al. (1998), referring to the ways people understand and enact their social positions in the figured world. The research is a case study based on narrative interview of Shabana, a British-born Pakistani female postgraduate student, who has recently joined the university of Manchester. Shabana received her primary education in UK during the first twelve years of her life. She is the youngest among the three sisters, with only one brother younger to her. Her father, although not well educated is a successful entrepreneur, maintaining offices in UK and Pakistan. Her mother is a housewife with no formal education. Shabana’s elder sister got involved in a relationship with a Pakistani boy against cultural norms of arranged marriage. Resultantly the three sisters were shifted to Pakistan to be equated with socio-religious norms. Shabana termed her first year in Pakistan as disgusting and she hated her father for the decision. However after a year’s time and shifting from an orthodox city to the provincial capital Lahore, she developed liking for the Pakistani culture. She gradually developed a new socio-religious identity during her stay, which she expressed as a turning point in her life. After completing O level Shabana returned back to UK and joined the University of Hull as undergraduate Student. At Hull she remained isolated, missed the religious environment and relished the memories of Lahore. She would visit Pakistan almost three times a year. After obtaining her BSc degree from Hull she went back to Pakistan. Soon after she decided to improve her academic qualification. She came to UK to join her parents and got admission in the MSc chemistry program at UoM. Presently Shabana talks about the dominant role of male members in the family culture in decision-making. She strongly feels to struggle hard and attain equal status with males in education, employment, earning, authority and freedom. She sees herself in a position to share the authority with her (would be) husband in important family and other matters. Shabana has developed a new identity of a mix of both Pakistani and UK culture. She is appreciative of the socio-cultural values of UK while still regarding the cultural and religious values of Pakistan in high esteem.

Keywords: postgraduate students, identity construction, cultural shifts, female british pakistani student

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Authors: Cheng Li, Jie Shen, Yutian Tang

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Embracing the upcoming era of urbanization with the challenges of limitation of resources, disappearing cultural identities and conflicts among different groups of stakeholders, new integrated approaches are offered in our urban practice to help decision-makers and stakeholders frame and develop well-conceived, practical strategies for urban developing trajectories to approach urban-level sustainability in multiple social, cultural, ecological dimensions. Through bottom-up participation, we take advantage of tourism and leisure industries as driving forces for urbanization in China to promote integrated sustainable systems, with the hope of approaching both historical and ecological aspects of urban sustainability; and also thanks to top-down participation, we have codes, standards and rules established by the governments to strengthen the implementation of ecological urban sustainability. The results are monitored and evaluated experimentally and multidimensionally and the sustainable systems we constructed with local stakeholder groups turned out to be effective. The presentation of our selected projects would indicate our different focuses on urban sustainability.

Keywords: urban sustainability, integrated urban strategy, tourism and leisure industries, history, modern technology

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Authors: Chusit Apirumanekul, Chayanis Krittasudthacheewa, Ratchapat Ratanavaraha, Yanyong Inmuong

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Rapid economic development in the Lower Mekong region is leading to changes in water quantity and quality. Changes in land- and forest-use, infrastructure development, increasing urbanization, migration patterns and climate risks are increasing demands for water, within various sectors, placing pressure on scarce water resources. Appropriate policies, strategies, and planning are urgently needed for improved water resource management. Over the last decade, Thailand has experienced more frequent and intense drought situations, affecting the level of water storage in reservoirs along with insufficient water allocation for agriculture during the dry season. The Huay Saibat River Basin, one of the well-known water-scarce areas in the northeastern region of Thailand, is experiencing ongoing water scarcity that affects both farming livelihoods and household consumption. Drought management in Thailand mainly focuses on emergency responses, rather than advance preparation and mitigation for long-term solutions. Despite many efforts from local authorities to mitigate the drought situation, there is yet no long-term comprehensive water management strategy, that integrates climate risks alongside other uncertainties. This paper assesses the application in the Huay Saibat River Basin, of the Robust Decision Support framework, to explore the feasibility of multiple drought management policies; including a shift in cropping season, in crop changes, in infrastructural operations and in the use of groundwater, under a wide range of uncertainties, including climate and land-use change. A series of consultative meetings were organized with relevant agencies and experts at the local level, to understand and explore plausible water resources strategies and identify thresholds to evaluate the performance of those strategies. Three different climate conditions were identified (dry, normal and wet). Other non-climatic factors influencing water allocation were further identified, including changes from sugarcane to rubber, delaying rice planting, increasing natural retention storage and using groundwater to supply demands for household consumption and small-scale gardening. Water allocation and water use in various sectors, such as in agriculture, domestic, industry and the environment, were estimated by utilising the Water Evaluation And Planning (WEAP) system, under various scenarios developed from the combination of climatic and non-climatic factors mentioned earlier. Water coverage (i.e. percentage of water demand being successfully supplied) was defined as a threshold for water resource strategy assessment. Thresholds for different sectors (agriculture, domestic, industry, and environment) were specified during multi-stakeholder engagements. Plausible water strategies (e.g. increasing natural retention storage, change of crop type and use of groundwater as an alternative source) were evaluated based on specified thresholds in 4 sectors (agriculture, domestic, industry, and environment) under 3 climate conditions. 'Business as usual' was evaluated for comparison. The strategies considered robust, emerge when performance is assessed as successful, under a wide range of uncertainties across the river basin. Without adopting any strategy, the water scarcity situation is likely to escalate in the future. Among the strategies identified, the use of groundwater as an alternative source was considered a potential option in combating water scarcity for the basin. Further studies are needed to explore the feasibility for groundwater use as a potential sustainable source.

Keywords: climate change, robust decision support, scenarios, water resources management

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Authors: Manirath Wongsim

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Information technology management has become important for the achievement of organisations. An increase in the pace of technological change has revolutionised the way accountants perform their jobs. In response to this challenge, the identification of a new comprehensive set of information technology competencies combined with information technology skills and other skills (namely, soft skills) are necessary. Thus, this study aims to investigate IT competencies among professional accountants to enhance firm performance. This research was conducted with 42 respondents at ten organisations in Thailand. This research used qualitative, interpretive evidence.The results indicate that the factor IT competencies within the organizational issues defines19 factors. Specifically, these new factors, based on the research findings and the literature and unique to IT competences for professional accountants, include ERP software skills, BI software skills and accounting law and legal skills. The evidence in this study suggests that ERP software, spreadsheets, BI software and accounting software were ranked as much-needed skills to be acquired by accountants while communication skills were ranked as the most required skills, and delegation skills as the least required. The findings of the research’s empirical evidence suggest that organizations should understand appropriate into developing information technology related competencies for knowledge workers in general and professional accountants in particular and provide assistance in all processes of decision making.

Keywords: IT competencies, IT competencies for accountants, IT skills for accounting, soft skills for accountants

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