Search results for: sustainable tourism models

Authors: Sarah A. Tobin

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Social justice outcomes, derived from customer satisfaction, serve as a main pathway and conduit for achieving Sustainable Development Goals (SDGs) because they prompt democratizing and socially-inclusive effects that are consistent with Islamic economic values. This paper argues that achieving higher levels of social justice and the SGDs is possible only through the realization of Islamic banking and finance customer satisfaction that aligns with Islamic values in the tradition of the Shari`a (or Islamic law). Through this key manifestation of Shari`a in the banks, social justice aims of achieving SDGs become possible. This paper utilizes a case study of a large-scale survey (N=127) comparing customer satisfaction between a conventional and an Islamic bank in Amman, Jordan. Based on a series of linear regressions, the statistically-significant findings suggest that when overall customer satisfaction is high, customers are more likely to become empowered citizens demanding inclusive, quality services and corruption-free management, as well as attribute their experiences to the Islamic nature of the financial endeavors. Social justice interests and expectations increase (and SDGs are more likely met) when a customer has high levels of satisfaction. The paper concludes with policy recommendations for Islamic financial institutions that enhance customer service experiences for better achieving the social justice aims of the Islamic economy and SDGs, including transparency in transactions, exemplary customer service and follow up, and attending to Islamic values in the aesthetics of bank.

Keywords: customer satisfaction, Islamic economy, social justice, sustainable development goals

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Authors: Yu Fang Chen, Jeng Fung Hung

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This study aimed to develop a circular economy scale to assess the level of recognition among high-level executives in businesses regarding the circular economy. The circular economy is crucial for global ESG sustainable development and poses a challenge for corporate social responsibility. The aim of promoting the circular economy is to reduce resource consumption, move towards sustainable development, reduce environmental impact, maintain ecological balance, increase economic value, and promote employment. This study developed a 23-item Circular Economy Scale, which includes three subscales: "Understanding of Circular Economy by Enterprises" (8 items), "Attitudes" (9 items), and "Behaviors" (6 items). The Likert 5-point scale was used to measure responses, with higher scores indicating higher levels of agreement among senior executives with regard to the circular economy. The study tested 105 senior executives and used a structural equation model (SEM) as a measurement indicator to determine the extent to which potential variables were measured. The standard factor loading of the measurement indicator needs to be higher than 0.7, and the average variance explained (AVE) represents the index of convergent validity, which should be greater than 0.5 or at least 0.45 to be acceptable. Out of the 23 items, 12 did not meet the standard, so they were removed, leaving 5 items, 3 items, and 3 items for each of the three subscales, respectively, all with a factor loading greater than 0.7. The AVE for all three subscales was greater than 0.45, indicating good construct validity. The Cronbach's α reliability values for the three subscales were 0.887, 0.787, and 0.734, respectively, and the total scale was 0.860, all of which were higher than 0.7, indicating good reliability. The Circular Economy Scale developed in this study measures three conceptual components that align with the theoretical framework of the literature review and demonstrate good reliability and validity. It can serve as a measurement tool for evaluating the degree of acceptance of the circular economy among senior executives in enterprises. In the future, this scale can be used by senior executives in enterprises as an evaluation tool to further explore its impact on sustainable development and to promote circular economy and sustainable development based on the reference provided.

Keywords: circular economy, corporate social responsibility, scale development, structural equation model

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Authors: Dino Carpentras, Paul J. Maher, Caoimhe O'Reilly, Michael Quayle

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Opinion dynamics is a sub-field of agent-based modeling that focuses on people’s opinions and their evolutions over time. Despite the rapid increase in the number of publications in this field, it is still not clear how to apply these models to real-world scenarios. Indeed, there is no agreement on how people update their opinion while interacting. Furthermore, it is not clear if different topics will show the same dynamics (e.g., more polarized topics may behave differently). These problems are mostly due to the lack of experimental validation of the models. Some previous studies started bridging this gap in the literature by directly measuring people’s opinions before and after the interaction. However, these experiments force people to express their opinion as a number instead of using natural language (and then, eventually, encoding it as numbers). This is not the way people normally interact, and it may strongly alter the measured dynamics. Another limitation of these studies is that they usually average all the topics together, without checking if different topics may show different dynamics. In our work, we collected data from 200 participants on 5 unpolarized topics. Participants expressed their opinions in natural language (“agree” or “disagree”). We also measured the certainty of their answer, expressed as a number between 1 and 10. However, this value was not shown to other participants to keep the interaction based on natural language. We then showed the opinion (and not the certainty) of another participant and, after a distraction task, we repeated the measurement. To make the data compatible with opinion dynamics models, we multiplied opinion and certainty to obtain a new parameter (here called “continuous opinion”) ranging from -10 to +10 (using agree=1 and disagree=-1). We firstly checked the 5 topics individually, finding that all of them behaved in a similar way despite having different initial opinions distributions. This suggested that the same model could be applied for different unpolarized topics. We also observed that people tend to maintain similar levels of certainty, even when they changed their opinion. This is a strong violation of what is suggested from common models, where people starting at, for example, +8, will first move towards 0 instead of directly jumping to -8. We also observed social influence, meaning that people exposed with “agree” were more likely to move to higher levels of continuous opinion, while people exposed with “disagree” were more likely to move to lower levels. However, we also observed that the effect of influence was smaller than the effect of random fluctuations. Also, this configuration is different from standard models, where noise, when present, is usually much smaller than the effect of social influence. Starting from this, we built an opinion dynamics model that explains more than 80% of data variance. This model was also able to show the natural conversion of polarization from unpolarized states. This experimental approach offers a new way to build models grounded on experimental data. Furthermore, the model offers new insight into the fundamental terms of opinion dynamics models.

Keywords: experimental validation, micro-dynamics rule, opinion dynamics, update rule

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Authors: Mazifah Simis, Azahan Awang, Kadir Arifin

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The brownfield regeneration is being implemented in developped countries. However, as a group 1 developing country in the South East Asia, the rapid development and increasing number of urban population in Malaysia have urged the needs to incorporate the brownfield regeneration into its physical planning development. The increasing number of urban ex-landfills is seen as a new resource that could overcome the issues of inadequate urban green space provisions. With regards to the new development approach in urban planning, this perception study aims to identify the sustainable planning approach based on what the stakeholders have in mind. Respondents consist of 375 local communities within four urban ex-landfill areas and 61 landscape architect and town planner officers in the Malaysian Local Authorities. Three main objectives are set to be achieved, which are (i) to identify ex-landfill issues that need to be overcome prior to the ex-landfill redevelopment (ii) to identify the most suitable types of ex-landfill redevelopment, and (iii) to identify the priority function for ex-landfill redevelopment as the public parks. From the data gathered through the survey method, the order of priorities based on stakeholders' perception was produced. The results show different perception among the stakeholders, but they agreed to the development of the public park as the main development. Hence, this study attempts to produce an integrated approach as a model for sustainable ex-landfill redevelopment that could be accepted by the stakeholders as a beneficial future development that could change the image of 296 ex-landfills in Malaysia into the urban public parks by the year 2020.

Keywords: brownfield regeneration, ex-landfill redevelopment, integrated approach, stakeholders' perception

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Authors: David C. Ni

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Contemporary models for N-body systems are based on temporal, two-body, and mass point representation of Newtonian mechanics. Other mainstream models include 2D and 3D Ising models based on local neighborhood the lattice structures. In Quantum mechanics, the theories of collective modes are for superconductivity and for the long-range quantum entanglement. However, these models are still mainly for the specific phenomena with a set of designated parameters. We are therefore motivated to develop a new construction directly from the complex-variable N-body systems based on the extended Blaschke functions (EBF), which represent a non-temporal and nonlinear extension of Lorentz transformation on the complex plane – the normalized momentum spaces. A point on the complex plane represents a normalized state of particle momentums observed from a reference frame in the theory of special relativity. There are only two key parameters, normalized momentum and nonlinearity for modelling. An algorithm similar to Jenkins-Traub method is adopted for solving EBF iteratively. Through iteration, the solution sets show a form of σ + i [-t, t], where σ and t are the real numbers, and the [-t, t] shows various distributions, such as 1-peak, 2-peak, and 3-peak etc. distributions and some of them are analog to the canonical distributions. The results of the numerical analysis demonstrate continuum-to-discreteness transitions, evolutional invariance of distributions, phase transitions with conjugate symmetry, etc., which manifest the construction as a potential candidate for the unification of statistics. We hereby classify the observed distributions on the finite convergent domains. Continuous and discrete distributions both exist and are predictable for given partitions in different regions of parameter-pair. We further compare these distributions with canonical distributions and address the impacts on the existing applications.

Keywords: blaschke, lorentz transformation, complex variables, continuous, discrete, canonical, classification

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Authors: Navid Kaboudi, Ali Shayanfar

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Introduction: Feeding infants with safe milk from the beginning of their life is an important issue. Drugs which are used by mothers can affect the composition of milk in a way that is not only unsuitable, but also toxic for infants. Consuming permeable drugs during that sensitive period by mother could lead to serious side effects to the infant. Due to the ethical restrictions of drug testing on humans, especially women, during their lactation period, computational approaches based on structural parameters could be useful. The aim of this study is to develop mechanistic models to predict the M/P ratio of drugs during breastfeeding period based on their structural descriptors. Methods: Two hundred and nine different chemicals with their M/P ratio were used in this study. All drugs were categorized into two groups based on their M/P value as Malone classification: 1: Drugs with M/P>1, which are considered as high risk 2: Drugs with M/P>1, which are considered as low risk Thirty eight chemical descriptors were calculated by ACD/labs 6.00 and Data warrior software in order to assess the penetration during breastfeeding period. Later on, four specific models based on the number of hydrogen bond acceptors, polar surface area, total surface area, and number of acidic oxygen were established for the prediction. The mentioned descriptors can predict the penetration with an acceptable accuracy. For the remaining compounds (N= 147, 158, 160, and 174 for models 1 to 4, respectively) of each model binary regression with SPSS 21 was done in order to give us a model to predict the penetration ratio of compounds. Only structural descriptors with p-value<0.1 remained in the final model. Results and discussion: Four different models based on the number of hydrogen bond acceptors, polar surface area, and total surface area were obtained in order to predict the penetration of drugs into human milk during breastfeeding period About 3-4% of milk consists of lipids, and the amount of lipid after parturition increases. Lipid soluble drugs diffuse alongside with fats from plasma to mammary glands. lipophilicity plays a vital role in predicting the penetration class of drugs during lactation period. It was shown in the logistic regression models that compounds with number of hydrogen bond acceptors, PSA and TSA above 5, 90 and 25 respectively, are less permeable to milk because they are less soluble in the amount of fats in milk. The pH of milk is acidic and due to that, basic compounds tend to be concentrated in milk than plasma while acidic compounds may consist lower concentrations in milk than plasma. Conclusion: In this study, we developed four regression-based models to predict the penetration class of drugs during the lactation period. The obtained models can lead to a higher speed in drug development process, saving energy, and costs. Milk/plasma ratio assessment of drugs requires multiple steps of animal testing, which has its own ethical issues. QSAR modeling could help scientist to reduce the amount of animal testing, and our models are also eligible to do that.

Keywords: logistic regression, breastfeeding, descriptors, penetration

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Authors: Duduzile Dlamini-Boemah, Haretsebe Manwa, Lisebo Tseane-Gumbi

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The demands and expectations of twenty-first century tourists have changed, and they continue to have an impact on tour guiding in cultural and natural tourist attractions. The traditional communicative role of the tour guide as a mere presenter is not sufficient anymore; instead, there are expectations from the tourists of guides who provide effective interpretive guiding. It is always questionable if tour guides in South Africa are equipped with the skills for effective interpretation, yet limited research has been conducted to investigate the continuing professional education of tour guides in South Africa. Instead, much attention has been given to aspects of registration and certification of tour guides in South Africa. Concerns have been raised about tour guiding and have led to the development of a strategy by the Department of Tourism to professionalise tourists guiding that includes training. However, the necessity for tourism training in tour guiding in South Africa was raised as early as in the 1980s, the paper argues that there is a further need to emphasise continuing professional education in interpretive guiding in South Africa. In this study, continuing education and training are considered to involve the upgrading of the skills and knowledge of interpretation of those who are already working as tour guides at the cultural and natural attractions. The study is guided by the empowerment theory. The aim of this paper is to present issues of effective interpretive guiding and continuing professional education in interpretive guiding in South Africa. This study is based on the literature survey of secondary sources such as academic journal articles, government documents, and reports and books. The conclusions indicate that there is a need for training in interpretive delivery techniques in South Africa. The need for interpretive training in interpretive delivery techniques is attributed by the call to allow people to use indigenous knowledge, rather than formal education as a basis for becoming a field guide as well as affording the previously disadvantaged individuals to access training opportunities as tourist guides.

Keywords: continuing education, interpretive delivery skills, interpretive guiding, tour guide

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Authors: Chisomo Patrick Kumbuyo, Katsuyuki Shimizu, Hiroshi Yasuda, Yoshinobu Kitamura

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This study deals with a way of predicting Malawi rainfall from global sea surface temperature (SST) using a simple multiple regression model. Monthly rainfall data from nine stations in Malawi grouped into two zones on the basis of inter-station rainfall correlations were used in the study. Zone 1 consisted of Karonga and Nkhatabay stations, located in northern Malawi; and Zone 2 consisted of Bolero, located in northern Malawi; Kasungu, Dedza, Salima, located in central Malawi; Mangochi, Makoka and Ngabu stations located in southern Malawi. Links between Malawi rainfall and SST based on statistical correlations were evaluated and significant results selected as predictors for the regression models. The predictors for Zone 1 model were identified from the Atlantic, Indian and Pacific oceans while those for Zone 2 were identified from the Pacific Ocean. The correlation between the fit of predicted and observed rainfall values of the models were satisfactory with r=0.81 and 0.54 for Zone 1 and 2 respectively (significant at less than 99.99%). The results of the models are in agreement with other findings that suggest that SST anomalies in the Atlantic, Indian and Pacific oceans have an influence on the rainfall patterns of Southern Africa.

Keywords: Malawi rainfall, forecast model, predictors, SST

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Authors: Mohd Zaki Hamzah, Roslan Rani, Ahmad Bazli Razali, Satiful Bahri Mamat, Abdul Hadi Ripin, Mohd Harun Esa

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Ever since 1901, forest management and silviculture practices in Malaysia have been frequently reviewed and updated to take into account changes in forest conditions, markets, timber demand/supply and technical advances that can be achieved in industrial processes, logging and forest harvesting, and currently, the forest management system practiced in Peninsular Malaysia is the Selective Management System (SMS) which was introduced in 1978. This system requires the selection of management regime (felling) based on Pre-Felling Forest Inventory (Pre-F) data to ensure economical harvesting and also ensuring adequate standing stands for subsequent rounds of felling, while maintaining ecological balance and environmental quality. SMS regulates forest harvesting through area and volume controls, with the cutting cycle 30 years. Most of the forest management units (FMU) (in Peninsular Malaysia) implementing SMS have been certified by Forest Stewardship Council (FSC) and/or Program for Endorsement of Forest Certification (PEFC), and one such FMU belongs to Kumpulan Pengurusan Kayu Kayan Terengganu (KPKKT). KPKKT, a timber management subsidiary of Golden Pharos Berhad (GPB), adopts the SMS to manage its 108,900 ha of timber concessionary areas in its role as logs’ supplier for the consumption of three subsidiaries of GPB. KPKKT is also responsible for the sustainable development and management of its concession in accordance with the Sustainable Forest Management (SFM) standards to ensure that it addresses the loss of forest cover and forest degradation, forest-based economic, social and environmental benefits, and ecologically protecting forests while mobilising financial resources for the implementation of sustainable forest management planning, harvesting, monitoring and the marketing of products. This paper will detail out the management and harvesting guidelines imposed by the controlling government agency, and harvesting processes taken by KPKKT to comply with guidelines and eventually supplying timber to the relevant subsidiaries (downstream mills under GPB).

Keywords: sustainable forest management, silviculture, reduce impact logging, forest certification

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Authors: Hadi Badri Ahmadi, Xuping Wang

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Due to strict regulations and public awareness, corporations should develop policies to effectively decrease the negative environmental effects of their products and enhance their supply chain environmental sustainability. Assessment of environmental issues in the context of many industries has been studied in the previous literature. However, Iran cement industry has received less attention from researchers. Therefore, in this paper, we apply a Decision-Making Trial and Evaluation Laboratory (DEMATEL) approach to assess the relationships among green metrics of Iran cement industry supply chain under fuzzy environment. The study findings provide considerable insight for cement industry managers and experts in order to enhance the environmental sustainability of their supply chain and move towards sustainable development.

Keywords: green supply chain, DEMATEL, fuzzy set theory, environmental sustainability, sustainable development, cement industry

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Authors: Joanna Fidelus-Orzechowska, Dominika Wronska-Walach, Jaroslaw Cebulski

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Mountain areas are very often exposed to numerous transformations connected with the development of tourist infrastructure. In mountain areas in Poland ski tourism is very popular, so agricultural areas are often transformed into tourist areas. The construction of new ski runs can change the direction and rate of slope development. The main aim of this research was to determine geomorphological and hydrological changes within slopes caused by ski run constructions. The study was conducted in the Remiaszów catchment in the Inner Polish Carpathians (southern Poland). The mean elevation of the catchment is 859 m a.s.l. and the maximum is 946 m a.s.l. The surface area of the catchment is 1.16 km2, of which 16.8% is the area of the two studied ski runs. The studied ski runs were constructed in 2014 and 2015. In order to determine the relief transformations connected with new ski run construction high resolution LIDAR data was analyzed. The general relief changes in the studied catchment were determined on the basis of ALS (Airborne Laser Scanning ) data obtained before (2013) and after (2016) ski run construction. Based on the two sets of ALS data a digital elevation models of differences (DoDs) was created, which made it possible to determine the quantitative relief changes in the entire studied catchment. Additionally, cross and longitudinal profiles were calculated within slopes where new ski runs were built. Detailed data on relief changes within selected test surfaces was obtained based on TLS (Terrestrial Laser Scanning). Hydrological changes within the analyzed catchment were determined based on the convergence and divergence index. The study shows that the construction of the new ski runs caused significant geomorphological and hydrological changes in the entire studied catchment. However, the most important changes were identified within the ski slopes. After the construction of ski runs the entire catchment area lowered about 0.02 m. Hydrological changes in the studied catchment mainly led to the interruption of surface runoff pathways and changes in runoff direction and geometry.

Keywords: hydrological changes, mountain areas, relief transformations, ski run construction

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Authors: Ässia Boukhatmi, Roger Nyffenegger

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The expansion of solar energy as a means to address the climate crisis is undisputed, but the increasing number of new photovoltaic (PV) modules being put on the market is simultaneously leading to increased challenges in terms of managing the growing waste stream. Many of the discarded modules are still fully functional but are often damaged by improper handling after disassembly or not properly tested to be considered for a second life. In addition, the collection rate for dismantled PV modules in several European countries is only a fraction of previous projections, partly due to the increased number of illegal exports. The underlying problem for those market imperfections is an insufficient data exchange between the different actors along the PV value chain, as well as the limited traceability of PV panels during their lifetime. As part of the Horizon 2020 project CIRCUSOL, an asset database prototype was developed to tackle the described problems. In an iterative process applying the design science research methodology, different business models, as well as the technical implementation of the database, were established and evaluated. To explore the requirements of different stakeholders for the development of the database, surveys and in-depth interviews were conducted with various representatives of the solar industry. The proposed database prototype maps the entire value chain of PV modules, beginning with the digital product passport, which provides information about materials and components contained in every module. Product-related information can then be expanded with performance data of existing installations. This information forms the basis for the application of data analysis methods to forecast the appropriate end-of-life strategy, as well as the circular economy potential of PV modules, already before they arrive at the recycling facility. The database prototype could already be enriched with data from different data sources along the value chain. From a business model perspective, the database offers opportunities both in the area of reuse as well as with regard to the certification of sustainable modules. Here, participating actors have the opportunity to differentiate their business and exploit new revenue streams. Future research can apply this approach to further industry and product sectors, validate the database prototype in a practical context, and can serve as a basis for standardization efforts to strengthen the circular economy.

Keywords: business model, circular economy, database, design science research, solar industry

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Authors: Tarek Taha Kandil

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In higher education, the use of automated grading systems is on the rise, automating the assessment of students' work and providing practical feedback. Sustainable Grader Scope addresses the environmental impact of these computational tasks. This system uses an AI-powered algorithm and is designed to minimize grading process emissions. It reduces carbon emissions through energy-efficient computing and carbon-conscious scheduling. Students submit their computational workloads to the system, which evaluates submissions using containers and a distributed infrastructure. A carbon-conscious scheduler manages workloads across global campuses, optimizing emissions using real-time carbon intensity data. This ensures the university stays within government-set emission limits while tracking and reducing its carbon footprint.

Keywords: sustainability, green graders, digital sustainable grader scope, environmental responsibility; higher education.

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Authors: Yiorgos Hadjichristou

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The paper will focus on the hybrid living typologies which are brought about due to the Global Crisis. Mixing of the generations and the groups of people, mingling the functions of living with working and socializing, merging the act of living in synergy with the urban realm and its constituent elements will be the springboard of proposing an essential sustainable housing approach and the respective urban development. The thematic will be based on methodologies developed both on the academic, educational environment including participation of students’ research and on the practical aspect of architecture including case studies executed by the author in the island of Cyprus. Both paths of the research will deal with the explorative understanding of the hybrid ways of living, testing the limits of its autonomy. The evolution of the living typologies into substantial hybrid entities, will deal with the understanding of new ways of living which include among others: re-introduction of natural phenomena, accommodation of the activity of work and services in the living realm, interchange of public and private, injections of communal events into the individual living territories. The issues and the binary questions raised by what is natural and artificial, what is private and what public, what is ephemeral and what permanent and all the in-between conditions are eloquently traced in the everyday life in the island. Additionally, given the situation of Cyprus with the eminent scar of the dividing ‘Green line’ and the waiting of the ‘ghost city’ of Famagusta to be resurrected, the conventional way of understanding the limits and the definitions of the properties is irreversibly shaken. The situation is further aggravated by the unprecedented phenomenon of the crisis on the island. All these observations set the premises of reexamining the urban development and the respective sustainable housing in a synergy where their characteristics start exchanging positions, merge into each other, contemporarily emerge and vanish, changing from permanent to ephemeral. This fluidity of conditions will attempt to render a future of the built- and unbuilt realm where the main focusing point will be redirected to the human and the social. Weather and social ritual scenographies together with ‘spontaneous urban landscapes’ of ‘momentary relationships’ will suggest a recipe for emerging urban environments and sustainable living. Thus, the paper will aim at opening a discourse on the future of the sustainable living merged in a sustainable urban development in relation to the imminent solution of the division of island, where the issue of property became the main obstacle to be overcome. At the same time, it will attempt to link this approach to the global need for a sustainable evolution of the urban and living realms.

Keywords: social ritual scenographies, spontaneous urban landscapes, substantial hybrid entities, re-introduction of natural phenomena

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Authors: Samir Dekali, David Crouzier

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Due to their new physico-chemical properties engineered nanoparticles (ENPs) are increasingly employed in numerous industrial sectors (such as electronics, textile, aerospace, cosmetics, pharmaceuticals, food industry, etc). These new physico-chemical properties can also represent a threat for the human health. Consumers can notably be exposed involuntarily by different routes such as inhalation, ingestion or through the skin. Several studies recently reported a possible biodistribution of these ENPs on the blood-brain barrier (BBB). Consequently, there is a great need for developing BBB in vitro models representative of the in vivo situation and capable of rapidly and accurately assessing ENPs toxic effects and their potential translocation through this barrier. In this study, several in vitro models established with micro-endothelial brain cell lines of different origins (bEnd.3 mouse cell line or a new human cell line) co-cultivated or not with astrocytic cells (C6 rat or C8-B4 mouse cell lines) on Transwells® were compared using different endpoints: trans-endothelial resistance, permeability of the Lucifer yellow and protein junction labeling. Impact of NIST diesel exhaust particles on BBB cell viability is also discussed.

Keywords: nanoparticles, blood-brain barrier, diesel exhaust particles, toxicology

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Authors: R. Manjula, Kaustav Bagchi, Sushant Ramesh, Anush Baskaran

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In the past century, the emergence of information technology has had a significant positive impact on human life. While companies tend to be more involved in the completion of projects, the turn of the century has seen importance being given to investment in information security policies. These policies are essential to protect important data from adversaries, and thus following these policies has become one of the most important attributes revolving around information security models. In this research, we have focussed on the factors affecting information security policy compliance in two models : The theory of planned behaviour and the integration of the social bond theory and the involvement theory into a single model. Finally, we have given a proposal of where these theories would be successful.

Keywords: information technology, information security, involvement theory, policies, social bond theory

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Authors: A. Kourou, M. Panoutsopoulou

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Nowadays, disaster risk reduction requires innovative ways of working collaboratively, monitoring tools, management methods, risk communication, and knowledge, as key factors for decision-making actors. Experience has shown that the assessment of seismic risk and its effective management is still an important challenge. In Greece, Ionian Islands region is characterized as the most seismic area of the country and one of the most active worldwide. It is well known that in case of a disastrous earthquake the local authorities need to assess the situation in the affected area and coordinate the disaster response. In particular, the main outcomes of 'Telemachus' project are the development of an innovative operational system that hosts the needed data of seismic risk management in the Ionian Islands and the implementation of educational actions for the involved target groups. This project is funded in the Priority Axis 'Environmental Protection and Sustainable Development' of Operational Plan 'Ionian Islands 2014-2020'. EPPO is one of the partners of the project and it is responsible, among others, for the development of proper training material. This paper presents the training material of 'Telemachus' and its usage as a helpful, managerial tool in case of earthquake emergency. This material is addressed to different target groups, such as civil protection staff, people that involved with the tourism industry, educators of disabled people, etc. Very positive aspect of the project is the involvement of end-users that should evaluate the training products; test standards; clarify the personnel’s roles and responsibilities; improve interagency coordination; identify gaps in resources; improve individual performance; and identify opportunities for improvement. It is worth mentioning that even though the abovementioned material developed is useful for the training of specific target groups on emergency management issues within Ionian Islands Region, it could be used throughout Greece and other countries too.

Keywords: education of civil protection staff, Ionian Islands Region of Greece, seismic risk, training material

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Authors: Yanshuang Zhang, Byungho Jeong

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There exists some time lag between the consumption of inputs and the production of outputs. This time lag effect should be considered in calculating efficiency of decision making units (DMU). Recently, a couple of DEA models were developed for considering time lag effect in efficiency evaluation of research activities. However, these models can’t discriminate efficient DMUs because of the nature of basic DEA model in which efficiency scores are limited to ‘1’. This problem can be resolved a super-efficiency model. However, a super efficiency model sometimes causes infeasibility problem. This paper suggests an output oriented super-efficiency model for efficiency evaluation under the consideration of time lag effect. A case example using a long term research project is given to compare the suggested model with the MpO model

Keywords: DEA, Super-efficiency, Time Lag, research activities

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Authors: Maria Krambia-Kapardis, Andreas Kapardis

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The relevant literature has been inundated with arguments for ethics, moral values, honesty, resilience, trust in leadership as well as responsible leadership. In many countries around the globe, and as shown by some recent reports, many political leaders are not role models and do not show best practices by being ethical, responsible, compassionate, and resilient. Journalists, whistleblowers, WikiLeaks, Al Jazeera, and the International Consortium of Investigative Journalists (ICIJ) have been brought out from the shadow of political leaders who lack the virtues/attributes outlined above by the UN Global Compact. A number of political leaders who lack ethical and responsible leadership skills will continue to find loopholes to enrich themselves and their close friends and relatives. Some researchers use the Millon Inventory of Diagnostic; however, this test, while it provides helpful and useful insights into the personality of a person who leads or inspire his/her people but does not show if that person is ethical, motivating, and empowers his people with trust and honesty. Thus, it is recommended that political leaders ought to undergo training that encompasses Aristotelian Ethics by embedding the appropriate values and behaviours in their strategies, policies, and decisions, enhancing the change factors that will help in the implementation of a more sustainable development model. Finally, there is a need to develop a pedagogy and a curriculum which enables the development of responsible political leaders.

Keywords: political leaders, corruption, anti-corruption, political corruption

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Authors: Genady Grabarnik, Serge Yaskolko

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Generative Artificial Intelligence (AI) has significantly expanded its applicability with the incorporation of Large Language Models (LLMs) and become a technology with promise to automate some areas that were very difficult to automate before. The paper describes the introduction of generative Artificial Intelligence into Introductory Computer and Data Science courses and analysis of effect of such introduction. The generative Artificial Intelligence is incorporated in the educational process two-fold: For the instructors, we create templates of prompts for generation of tasks, and grading of the students work, including feedback on the submitted assignments. For the students, we introduce them to basic prompt engineering, which in turn will be used for generation of test cases based on description of the problems, generating code snippets for the single block complexity programming, and partitioning into such blocks of an average size complexity programming. The above-mentioned classes are run using Large Language Models, and feedback from instructors and students and courses’ outcomes are collected. The analysis shows statistically significant positive effect and preference of both stakeholders.

Keywords: introductory computer and data science education, generative AI, large language models, application of LLMS to computer and data science education

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Authors: N. Fuad, M. N. Taib, R. Jailani, M. E. Marwan

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This paper discusses on power spectral density (PSD) characteristics which are extracted from three-dimensional (3D) electroencephalogram (EEG) models. The EEG signal recording was conducted on 150 healthy subjects. Development of 3D EEG models involves pre-processing of raw EEG signals and construction of spectrogram images. Then, the values of maximum PSD were extracted as features from the model. These features are analysed using mean relative power (MRP) and different mean relative power (DMRP) technique to observe the pattern among different brain balancing indexes. The results showed that by implementing these techniques, the pattern of brain balancing indexes can be clearly observed. Some patterns are indicates between index 1 to index 5 for left frontal (LF) and right frontal (RF).

Keywords: power spectral density, 3D EEG model, brain balancing, mean relative power, different mean relative power

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Authors: Kumari Sweta, Ajanta Goswami, Abhilasha Dixit

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Landslide is a geomorphic process that plays an essential role in the evolution of the hill-slope and long-term landscape evolution. But its abrupt nature and the associated catastrophic forces of the process can have undesirable socio-economic impacts, like substantial economic losses, fatalities, ecosystem, geomorphologic and infrastructure disturbances. The estimated fatality rate is approximately 1person /100 sq. Km and the average economic loss is more than 550 crores/year in the Himalayan belt due to landslides. This study presents a comparative performance of a statistical bivariate method and a machine learning technique for landslide susceptibility mapping in and around Dharamshala, Himachal Pradesh. The final produced landslide susceptibility maps (LSMs) with better accuracy could be used for land-use planning to prevent future losses. Dharamshala, a part of North-western Himalaya, is one of the fastest-growing tourism hubs with a total population of 30,764 according to the 2011 census and is amongst one of the hundred Indian cities to be developed as a smart city under PM’s Smart Cities Mission. A total of 209 landslide locations were identified in using high-resolution linear imaging self-scanning (LISS IV) data. The thematic maps of parameters influencing landslide occurrence were generated using remote sensing and other ancillary data in the GIS environment. The landslide causative parameters used in the study are slope angle, slope aspect, elevation, curvature, topographic wetness index, relative relief, distance from lineaments, land use land cover, and geology. LSMs were prepared using information value (Info Val), and Fuzzy Expert System (FES) models. Info Val is a statistical bivariate method, in which information values were calculated as the ratio of the landslide pixels per factor class (Si/Ni) to the total landslide pixel per parameter (S/N). Using this information values all parameters were reclassified and then summed in GIS to obtain the landslide susceptibility index (LSI) map. The FES method is a machine learning technique based on ‘mean and neighbour’ strategy for the construction of fuzzifier (input) and defuzzifier (output) membership function (MF) structure, and the FR method is used for formulating if-then rules. Two types of membership structures were utilized for membership function Bell-Gaussian (BG) and Trapezoidal-Triangular (TT). LSI for BG and TT were obtained applying membership function and if-then rules in MATLAB. The final LSMs were spatially and statistically validated. The validation results showed that in terms of accuracy, Info Val (83.4%) is better than BG (83.0%) and TT (82.6%), whereas, in terms of spatial distribution, BG is best. Hence, considering both statistical and spatial accuracy, BG is the most accurate one.

Keywords: bivariate statistical techniques, BG and TT membership structure, fuzzy expert system, information value method, machine learning technique

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Authors: Ahmadi, Iriansyah, Raihana Yahman

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The giant freshwater prawn (Macrobrachium rosenbergii de Man, 1879) is a valuable species for fisheries and aquaculture, especially in Southeast Asia, including Indonesia due to their high market demand and potential for export. The growing demand for prawns is straining the sustainability of the Banjar Regency fishery. To ensure the long-term sustainability and economic viability of the prawn fishing in this region, it is imperative to implement evidence-based management practices. This requires comprehensive data on the Catch per Unit Effort (CPUE), Maximum Sustainable Yield (MSY) and the current rate of prawn resource exploitation. it analyzed five years of prawn catch data (2019-2023) obtained from South Kalimantan Marine and Fisheries Services. Fishing gears (e.g. hook & line and cast net) were first standardized with Fishing Power Index, and then calculated effort and MSY. The intercept (a) and the slope (b) values of regression curve were used to estimate the catch-maximum sustainable yield (CMSY) and optimal fishing effort (Fopt) levels within the framework of the Surplus Production Model. The estimated rates of resource utilization were then compared to the criteria of The National Commission of Marine Fish Stock Assessment. The findings showed that the CPUE value peaked in 2019 at 33.48 kg/trip, while the lowest value observed in 2022 at 5.12 kg/trip. The CMSY value was estimated to be 17,396 kg/year, corresponding to the Fopt level of 1,636 trips/year. The highest utilization rate was 56.90% recorded in 2020, while the lowest rate was observed in 2021 at 46.16%. The annual utilization rates were classified as “medium”, suggesting that increasing fishing effort by 45% could potentially maximize prawn catches at an optimum level. These findings provide a baseline for sustainable fisheries management in the region.

Keywords: giant prawns, CPUE, fishing power index, sustainable potential, utilization rate

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Authors: Bharatendra Rai

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Cutting tools are widely used in manufacturing processes and drilling is the most commonly used machining process. Although drill-bits used in drilling may not be expensive, their breakage can cause damage to expensive work piece being drilled and at the same time has major impact on productivity. Predicting drill-bit breakage, therefore, is important in reducing cost and improving productivity. This study uses twenty features extracted from two degradation signals viz., thrust force and torque. The methodology used involves developing and comparing decision tree, random forest, and multinomial logistic regression models for classifying and predicting drill-bit breakage using degradation signals.

Keywords: degradation signal, drill-bit breakage, random forest, multinomial logistic regression

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Authors: Muhammad Abdullah, Muhammad Atiq Ur Rehman Tariq, Faraz Ul Haq

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In developed countries, sustainability measures are widely accepted and acknowledged as crucial for addressing environmental concerns. Hydroponics, a soilless cultivation technique, has emerged as a potentially sustainable solution as it can reduce water consumption, land use, and environmental impacts. However, hydroponics may not be economically viable, especially when using reclaimed water, which may entail additional costs and risks. This study aims to address the critical question of whether hydroponics using reclaimed water can achieve a balance between sustainability and financial viability. Life Cycle Assessment (LCA) and Life Cycle Cost (LCC) will be integrated to assess the potential of hydroponics whether it is environmentally sustainable and economically viable. Life cycle assessment, or LCA, is a methodology for assessing environmental impacts associated with all the stages of the life cycle of a commercial product, process, or service. While Life Cycle Cost (LCC) is an approach that assesses the total cost of an asset over its life cycle, including initial capital costs and maintenance costs. The expected benefits of this study include supporting evidence-based decision-making for policymakers, farmers, and stakeholders involved in agriculture. By quantifying environmental impacts and economic costs, this research will facilitate informed choices regarding the adoption of hydroponics with reclaimed water. It is believed that the outcomes of this research work will help to achieve a sustainable approach to agricultural production, aligning with sustainability goals while considering economic factors by adopting hydroponic technique.

Keywords: hydroponic, life cycle assessment, life cycle cost, sustainability

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Authors: Kumar Shashvat, Amol P. Bhondekar

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In the midst of the five senses, odor is the most reminiscent and least understood. Odor testing has been mysterious and odor data fabled to most practitioners. The delinquent of recognition and classification of odor is important to achieve. The facility to smell and predict whether the artifact is of further use or it has become undesirable for consumption; the imitation of this problem hooked on a model is of consideration. The general industrial standard for this classification is color based anyhow; odor can be improved classifier than color based classification and if incorporated in machine will be awfully constructive. For cataloging of odor for peas, trees and cashews various discriminative approaches have been used Discriminative approaches offer good prognostic performance and have been widely used in many applications but are incapable to make effectual use of the unlabeled information. In such scenarios, generative approaches have better applicability, as they are able to knob glitches, such as in set-ups where variability in the series of possible input vectors is enormous. Generative models are integrated in machine learning for either modeling data directly or as a transitional step to form an indeterminate probability density function. The algorithms or models Linear Discriminant Analysis and Naive Bayes Classifier have been used for classification of the odor of cashews. Linear Discriminant Analysis is a method used in data classification, pattern recognition, and machine learning to discover a linear combination of features that typifies or divides two or more classes of objects or procedures. The Naive Bayes algorithm is a classification approach base on Bayes rule and a set of qualified independence theory. Naive Bayes classifiers are highly scalable, requiring a number of restraints linear in the number of variables (features/predictors) in a learning predicament. The main recompenses of using the generative models are generally a Generative Models make stronger assumptions about the data, specifically, about the distribution of predictors given the response variables. The Electronic instrument which is used for artificial odor sensing and classification is an electronic nose. This device is designed to imitate the anthropological sense of odor by providing an analysis of individual chemicals or chemical mixtures. The experimental results have been evaluated in the form of the performance measures i.e. are accuracy, precision and recall. The investigational results have proven that the overall performance of the Linear Discriminant Analysis was better in assessment to the Naive Bayes Classifier on cashew dataset.

Keywords: odor classification, generative models, naive bayes, linear discriminant analysis

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Authors: Adiyasa Muda Zannatan

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Cassava (Manihot esculenta) is a plant originating from Brazil. Cassava plants categorized as sixth major food in the world after wheat, rice, corn and potatoes. It has been cultivated on hilly land for 97 years since 1918 at Cireundeu village, West Java Province, Indonesia. Cireundeu traditional village located in the mountain valleys and has a hilly slope up to 38%. Cassava is used as the primary food in that area. Uniquely, Cassava productivity is stable and continues until now. The assessment of soil quality is taking soil samples in the area and analysis the soil in laboratory. The result of analysis that soil in the area is not degraded because it has optimum nutrient, organic matter, and high value of cation exchange capacity in soil even though it has been cultivated in scarp with high slope. Commonly, soil on scarp with high slope has a high rate erosion and poor nutrient. It proved that cassava is able to be an alternative technique of soil conservation in the areas that have a high slope. Beside that, cassava can be utilized as a plant food, feed, fertilizer, and energy. With the utilization of Cassava, the target of Sustainable Development Goals (SDG's) will be achieved with consideration three important components include economy, social, and environment. In economy, Cassava can to be the commercial product like processed food, feed, and alternative energy. In social, it will increase social welfare and will be hereditary. And for environment, Cassava prevents soil from erosion and keeps soil quality.

Keywords: Cassava, local wisdom, conservation, soil quality, sustainable

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Authors: Shahbaz Abbas, Lin Han Chiang Hsieh

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The significant population growth and climate change issues have contributed to the natural resources depletion and their sustainability in the future. Manufacturing industries have a substantial impact on every country’s economy, but the sustainability of the industrial resources is challenging, and the policymakers have been developing the possible solutions to manage the sustainability of industrial resources such as raw material, energy, water, and industrial supply chain. In order to address these challenges, nexus approach is one of the optimization and modelling techniques in the recent sustainable environmental research. The interactions between the nexus components acknowledge that all components are dependent upon each other, and they are interrelated; therefore, their sustainability is also associated with each other. In addition, the nexus concept does not only provide the resources sustainability but also environmental sustainability can be achieved through nexus approach by utilizing the industrial waste as a resource for the industrial processes. Based on energy-water nexus, this study has developed a resource-energy-water for the sugar industry to understand the interactions between sugarcane, energy, and water towards the sustainable sugar industry. In particular, the focus of the research is the Taiwanese sugar industry; however, the same approach can be adapted worldwide to optimize the sustainability of sugar industries. It has been concluded that there are significant interactions between sugarcane, energy consumption, and water consumption in the sugar industry to manage the scarcity of resources in the future. The interactions between sugarcane and energy also deliver a mechanism to reuse the sugar industrial waste as a source of energy, consequently validating industrial and environmental sustainability. The desired outcomes from the nexus can be achieved with the modifications in the policy and regulations of Taiwanese industrial sector.

Keywords: energy-water nexus, environmental sustainability, industrial sustainability, natural resource management

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Authors: Ourvashi Bissoon

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Sub-Saharan Africa in addition to being resource rich is increasingly being seen as having a huge growth potential and as a result, is increasingly attracting MNEs on its soil. To empirically assess the effectiveness of GDP in tracking sustainable resource use and the role played by MNEs in Sub-Saharan Africa, a panel data analysis has been undertaken for 32 countries over thirty-five years. The time horizon spans the period 1980-2014 to reflect the evolution from before the publication of the pioneering Brundtland report on sustainable development to date. Multinationals’ presence is proxied by the level of FDI stocks. The empirical investigation first focuses on the impact of trade openness and MNE presence on the traditional measure of economic growth namely the GDP growth rate, and then on the genuine savings (GS) rate, a measure of weak sustainability developed by the World Bank, which assumes the substitutability between different forms of capital and finally, the impact on the adjusted Net National Income (aNNI), a measure of green growth which caters for the depletion of natural resources is examined. For countries with significant exhaustible natural resources and important foreign investor presence, the adjusted net national income (aNNI) can be a better indicator of economic performance than GDP growth (World Bank, 2010). The issue of potential endogeneity and reverse causality is also addressed in addition to robustness tests. The findings indicate that FDI and openness contribute significantly and positively to the GDP growth of the countries in the sample; however there is a threshold level of institutional quality below which FDI has a negative impact on growth. When the GDP growth rate is substituted for the GS rate, a natural resource curse becomes evident. The rents being generated from the exploitation of natural resources are not being re-invested into other forms of capital namely human and physical capital. FDI and trade patterns may be setting the economies in the sample on a unsustainable path of resource depletion. The resource curse is confirmed when utilising the aNNI as well, thus implying that GDP growth measure may not be a reliable to capture sustainable development.

Keywords: FDI, sustainable development, genuine savings, sub-Saharan Africa

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Authors: Dahiru Bawa Muhammad

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Mathematics is accorded a prime position in basic education curriculum because it is envisaged to be an important tool in preparing children for life after school as well as equipping them with skills needed for secondary and higher education. As a result of this, the subject is made compulsory from primary through secondary school and candidates are expected to offer it and pass before fulfilling the requirement for higher education. Against this backdrop, this paper overviewed the basic education programme, context of teaching and learning mathematics at basic education level in Katsina State of Nigeria, relevance of the subject to different fields of human endeavours, challenges threatening the utility of the subject as a tool for the achievement of the goals of basic education programme and concluded by recommending how teaching and learning of mathematics can be improved for even development of citizens within nation states and enhanced/mutual sustainable development of nations in the global village.

Keywords: basic education, junior secondary school education, mathematical centre

Procedia PDF Downloads 461