Search results for: passive solar architecture

Authors: Dejen Alemu, Murray E. Jennex, Temtim Assefa

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This paper is investigated to understand the design, the use, and the consequence of Knowledge Management System (KMS) for knowledge systems sharing and integration. A KMS for knowledge systems sharing and integration is designed to meet the challenges raised by knowledge management researchers and practitioners: the technical, the human, and social factors. Agricultural KMS involves various members coming from different Communities of Practice (CoPs) who possess their own knowledge of multiple practices which need to be combined in the system development. However, the current development of the technology ignored the indigenous knowledge of the local communities, which is the key success factor for agriculture. This research employed the multi-methodological approach to KMS research in action research perspective which consists of four strategies: theory building, experimentation, observation, and system development. Using the KMS development practice of Ethiopian agricultural transformation agency as a case study, this research employed an interpretive analysis using primary qualitative data acquired through in-depth semi-structured interviews and participant observations. The Orlikowski's structuration model of technology has been used to understand the design, the use, and the consequence of the KMS. As a result, the research identified three basic components for the architecture of the shared KMS, namely, the people, the resources, and the implementation subsystems. The KMS were developed using web 2.0 tools to promote knowledge sharing and integration among diverse groups of users in a distributed environment. The use of a shared KMS allows users to access diverse knowledge from a number of users in different groups of participants, enhances the exchange of different forms of knowledge and experience, and creates high interaction and collaboration among participants. The consequences of a shared KMS on the social system includes, the elimination of hierarchical structure, enhance participation, collaboration, and negotiation among users from different CoPs having common interest, knowledge and skill development, integration of diverse knowledge resources, and the requirement of policy and guideline. The research contributes methodologically for the application of system development action research for understanding a conceptual framework for KMS development and use. The research have also theoretical contribution in extending structuration model of technology for the incorporation of variety of knowledge and practical implications to provide management understanding in developing strategies for the potential of web 2.0 tools for sharing and integration of indigenous knowledge.

Keywords: communities of practice, indigenous knowledge, participation, structuration model of technology, Web 2.0 tools

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Authors: Maria Campos, Alain Massart, Hugo Sarmento

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The Meter Matters Erasmus Sport European Project (ID: 101050372) explores the field of social inclusion in and through sports with the aim of a) proposing appropriate criteria for co-funding sports programs involving people with intellectual and developmental disabilities and other more vulnerable people, primarily in mainstream sports organizations and b) proposing a model for co-funding social inclusion in and through sports at the national level. This European project (2022-2024) involves 6 partners from 3 countries: Univerza V Ljubljani – coordinator and Drustvo Specialna Olimpiada Slovenije (Slovenia); Magyar Specialis Olimpia Szovetseg and Magyar Testnevelesi Es Sporttudomanyi Egyetem (Hungary) and APPDA Coimbra - Associação Portuguesa para as Perturbações do Desenvolvimento e Autismo and Universidade De Coimbra, Faculty of Sport Sciences and Physical Education (Portugal). Equal involvement of all people in sports activities is, in terms of national and international guidelines, enshrined in some conventions and strategies in the field of sports, as well as human rights, social security, physical and mental health, architecture, environment and public administration. However, there is a gap between the practice and EU guidelines in terms of sustainable support for socially inclusive sports programs in the form of co-funding by state and local (municipal) resources. We observe considerable opacity in the regulation of the field. Given that there are both relevant programs and inclusive legislation and policies, we believe that the reason for the missing article is reflected in the undeveloped criteria for measuring social inclusion in sports. Major sports programs are usually co-funded based on crowds (number of involved athletes) and performance (sports score). In the field of social inclusion in sports, the criteria cannot be the same, as it is a smaller population. Therefore, the goals of inclusion in sports should not be the focused on competitive results but on opening equal opportunities for all, regardless of their psychophysical abilities. In the Meter Matters program, we are searching for criteria for co-funding social inclusion in sports through focus groups with coaches, social workers, psychologists and others professionals involved in inclusive sports programs in regular sports clubs and with athletes and their parents or guardians. Moreover, experts in the field of social inclusion in sports were also interviewed. Based on the proposals for measuring social inclusion in sports, we developed a model for co-funding socially inclusive sports programs.

Keywords: European project, meter matters, inclusion, sport

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Authors: Jarot Mahendra

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The primary objective of this paper is to provide a view in the interpretation of the revitalization of heritage buildings. This objective is achieved by analyzing the concept of interpretation that is oriented in the perspective of law, urban spatial planning, and stakeholder perspective, and then develops the theoretical framework of interpretation in the cultural resources management through issues of identity, heritage as a process, and authenticity in heritage. The revitalization of heritage buildings with the interpretation of these three issues is that interpretation can be used as a communication process to express the meaning and relation of heritage to the community so as to avoid the conflict that will arise and develop as a result of different perspectives of stakeholders. Using case studies in Indonesia, this study focuses on the revitalization of heritage sites in the National Gallery of Indonesia (GNI). GNI is a cultural institution that uses several historical buildings that have been designated as heritage and have not been designated as a heritage according to the regulations applicable in Indonesia, in carrying out its function as the center of Indonesian art development and art museums. The revitalization of heritage buildings is taken as a step to meet space needs in running the current GNI function. In the revitalization master plan, there are physical interventions on the building of heritage and the removal of some historic buildings which will then be built new buildings at that location. The research matrix was used to map out the main elements of the study (the concept of GNI revitalization, heritage as identity, heritage as a process, and authenticity in the heritage). Expert interviews and document studies are the main tools used in collecting data. Qualitative data is then analyzed through content analysis and template analysis. This study identifies the significance of historic buildings (heritage buildings and buildings not defined as heritage) as an important value of history, architecture, education, and culture. The significance becomes the basis for revisiting the revitalization master plan which is then reviewed according to applicable regulations and the spatial layout of Jakarta. The interpretation that is built is (1) GNI is one of the elements of the embodiment of the National Cultural Center in the context of the region, where there are National Monument, National Museum and National Library in the same area, so the heritage not only gives identity to the past culture but the culture of current community; (2) The heritage should be seen as a dynamic cultural process towards the cultural change of community, where heritage must develop along with the urban development, so that the heritage buildings can remain alive and side by side with modern buildings but still observe the principles of preservation of heritage; (3) The authenticity of heritage should be able to balance the cultural heritage conservation approach with urban development, where authenticity can serve as a 'Value Transmitter' so that authenticity can be used to evaluate, preserve and manage heritage buildings by considering tangible and intangible aspects.

Keywords: authenticity, culture process, identity, interpretation, revitalization

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Authors: Cristóbal Moënne-Loccoz, Rodrigo C. Vergara, Vladimir López, Domingo Mery, Diego Cosmelli

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Our daily interaction with computational interfaces is plagued of situations in which we go from inexperienced users to experts through self-motivated exploration of the same task. In many of these interactions, we must learn to find our way through a sequence of decisions and actions before obtaining the desired result. For instance, when drawing cash from an ATM machine, choices are presented in a step-by-step fashion so that a specific sequence of actions must be performed in order to produce the expected outcome. But, as they become experts in the use of such interfaces, do users adopt specific search and learning strategies? Moreover, if so, can we use this information to follow the process of expertise development and, eventually, predict future actions? This would be a critical step towards building truly adaptive interfaces that can facilitate interaction at different moments of the learning curve. Furthermore, it could provide a window into potential mechanisms underlying decision-making behavior in real world scenarios. Here we tackle this question using a simple game interface that instantiates a 4-level binary decision tree (BDT) sequential decision-making task. Participants have to explore the interface and discover an underlying concept-icon mapping in order to complete the game. We develop a Hidden Markov Model (HMM)-based approach whereby a set of stereotyped, hierarchically related search behaviors act as hidden states. Using this model, we are able to track the decision-making process as participants explore, learn and develop expertise in the use of the interface. Our results show that partitioning the problem space into such stereotyped strategies is sufficient to capture a host of exploratory and learning behaviors. Moreover, using the modular architecture of stereotyped strategies as a Mixture of Experts, we are able to simultaneously ask the experts about the user's most probable future actions. We show that for those participants that learn the task, it becomes possible to predict their next decision, above chance, approximately halfway through the game. Our long-term goal is, on the basis of a better understanding of real-world decision-making processes, to inform the construction of interfaces that can establish dynamic conversations with their users in order to facilitate the development of expertise.

Keywords: behavioral modeling, expertise acquisition, hidden markov models, sequential decision-making

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Authors: Chang Hsueh-Sheng, Chen Tzu-Ling

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Earthquake is an unpredictable natural disaster and intensive earthquakes have caused serious impacts on social-economic system, environmental and social resilience, and further increase vulnerability. Due to earthquakes do not kill people, buildings do. When buildings located nearby earthquake-prone areas and constructed upon poorer soil areas might result in earthquake-induced ground damage. In addition, many existing buildings built before any improved seismic provisions began to be required in building codes and inappropriate land usage with highly dense population might result in much serious earthquake disaster. Indeed, not only do earthquake disaster impact seriously on urban environment, but urban growth might increase the vulnerability. Since 1980s, ‘Cutting down risks and vulnerability’ has been brought up in both urban planning and architecture and such concept has way beyond retrofitting of seismic damages, seismic resistance, and better anti-seismic structures, and become the key action on disaster mitigation. Land use planning and zoning are two critical non-structural measures on controlling physical development while it is difficult for zoning boards and governing bodies restrict development of questionable lands to uses compatible with the hazard without credible earthquake loss projection. Therefore, identifying potential earthquake exposure, vulnerability people and places, and urban development areas might become strongly supported information for decision makers. Taiwan locates on the Pacific Ring of Fire where a seismically active zone is. Some of the active faults have been found close by densely populated and highly developed built environment in the cities. Therefore, this study attempts to base on the perspective of carrying capacity and draft out micro-zonation according to both vulnerability index and urban growth index while considering spatial variances of multi factors via geographical weighted principle components (GWPCA). The purpose in this study is to construct supported information for decision makers on revising existing zoning in high-risk areas for a more compatible use and the public on managing risks.

Keywords: earthquake disaster, vulnerability, urban growth, carrying capacity, /geographical weighted principle components (GWPCA), bivariate spatial association statistic

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Authors: Zainab Olabisi Tairu

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The human species is facing some of the most challenging issues encountered as civilization and development occurs. The most salient factors threatening all species globally are habitats loss and degradation, overexploitation, competition with unwanted invasive species, pollution, global climate and various individual lifestyles of indigenous species. In order to avoid or minimize the effect of our actions on the environment and to balance employee work life with their private life, Green Human Resource is important and must be practiced in every organization including Higher Learning Institutions. This study addressed Green HRM from an institutional perspective, University systems are involved in numerous and complex social, educational and extra-curricular activities. The University community must be challenged to rethink and re-construct their environmental policies and practices in order to contribute to sustainable development. Many institutions only look at sustainability from the technology improvement aspect and waste management. People are the principal actors for sustainability development at the institutional level. The aim of the study is to explore the concept of Green Human Resource Management at a case site. Divine Word University (DWU) an Institution of Higher Education that embraced the ‘Printing & Paper use Policy’, also commonly referred to as the ‘paperless policy’, the use of solar as an alternative source of energy, water conservation and improvement in internet technology (IT) with the aim of becoming a green institution in effort to help save the environment. This study used Participatory Action Research as the Overarching methodological framework and Egg of sustainability and Wellbeing as the theoretical perspective in analyzing the data, engaging Case study strategy and a mixed method design at DWU. Focus group interview were conducted with three departments at the University, semi-structure interviews with the senior managers, survey questionnaire administered to students and staff with a sample size of 176 participants, in addition, policy documents were also exploited as extra source of data. Waste management including e-waste appeared to be one of the main concerns at DWU. A vast majority of DWU staff and students expressed the need for their institution to do more on sustainability education. The findings revealed that members of the community are not fully integrated like the Egg of sustainability and wellbeing in order to achieve sustainable development goal. The concept of Green Human Resource Management in Universities lies with the idea that Universities must bear profound responsibilities to manage its stakeholders in an environmental friendly way. Human resource management can help local institutions to recognize the need for changes of lifestyle, production, consumption as well as the end product in order to combat or at least reduce human Induced which produce or aggravate it.

Keywords: sustainability, environmental management, higher education institutions, green human resource management

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Authors: Filip Varga, Nina Jeran, Martina Biosic, Zlatko Satovic, Martina Grdisa

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Dalmatian pyrethrum (Tanacetum cinerariifolium /Trevir./ Sch. Bip.), a species endemic to the eastern Adriatic coastline, is the source of natural insecticide pyrethrin. Pyrethrin is a mixture of six compounds (pyrethrin I and II, cinerin I and II, jasmolin I and II) that exhibits high insecticidal activity with no detrimental effects to the environment. A recently optimized matrix-solid phase dispersion method (MSPD), using florisil as the sorbent, acetone-ethyl acetate (1:1, v/v) as the elution solvent, and sodium sulfate anhydrous as the drying agent was utilized to extract the pyrethrins from 10 wild populations (20 individuals per population) distributed along the Croatian coast. All six components in the extracts were qualitatively and quantitatively determined by high-performance liquid chromatography with a diode array detector (HPLC-DAD). Pearson’s correlation index was calculated between pyrethrin compounds, and differences between the populations using the analysis of variance were tested. Additionally, the correlation of each pyrethrin component with spatio-ecological variables (bioclimate, soil properties, elevation, solar radiation, and distance from the coastline) was calculated. Total pyrethrin content ranged from 0.10% to 1.35% of dry flower weight, averaging 0.58% across all individuals. Analysis of variance revealed significant differences between populations based on all six pyrethrin compounds and total pyrethrin content. On average, the lowest total pyrethrin content was found in the population from Pelješac peninsula (0.22% of dry flower weight) in which total pyrethrin content lower than 0.18% was detected in 55% of the individuals. The highest average total pyrethrin content was observed in the population from island Zlarin (0.87% of dry flower weight), in which total pyrethrin content higher than 1.00% was recorded in only 30% of the individuals. Pyrethrin I/pyrethrin II ratio as a measure of extract quality ranged from 0.21 (population from the island Čiovo) to 5.88 (population from island Mali Lošinj) with an average of 1.77 across all individuals. By far, the lowest quality of extracts was found in the population from Mt. Biokovo (pyrethrin I/II ratio lower than 0.72 in 40% of individuals) due to the high pyrethrin II content typical for this population. Pearson’s correlation index revealed a highly significant positive correlation between pyrethrin I content and total pyrethrin content and a strong negative correlation between pyrethrin I and pyrethrin II. The results of this research clearly indicate high intra- and interpopulation diversity of Dalmatian pyrethrum with regards to pyrethrin content and composition. The information obtained has potential use in plant genetic resources conservation and biodiversity monitoring. Possibly the largest potential lies in designing breeding programs aimed at increasing pyrethrin content in commercial breeding lines and reintroduction in agriculture in Croatia. Acknowledgment: This work has been fully supported by the Croatian Science Foundation under the project ‘Genetic background of Dalmatian pyrethrum (Tanacetum cinerariifolium /Trevir/ Sch. Bip.) insecticidal potential’ - (PyrDiv) (IP-06-2016-9034).

Keywords: Dalmatian pyrethrum, HPLC, MSPD, pyrethrin

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Authors: Mario Hanna Louis Hanna

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The use of CAD (pc Aided layout) generation is ubiquitous inside the structure, engineering and construction (AEC) industry. This has led to its inclusion in the curriculum of structure faculties in Nigeria as an important part of the training module. This newsletter examines the moral troubles involved in implementing CAD (pc Aided layout) content into the architectural training curriculum. Using current literature, this study begins with the advantages of integrating CAD into architectural education and the responsibilities of various stakeholders in the implementation process. It also examines issues related to the terrible use of records generation and the perceived bad effect of CAD use on design creativity. The use of a survey technique, information from the architecture department of Chukwuemeka Odumegwu Ojukwu Uli college changed into accumulated to serve as a case observe on how the problems raised have been being addressed. The object draws conclusions on what guarantees a hit moral implementation. Tens of millions of human beings around the sector suffer from hepatitis C, one of the international's deadliest sicknesses. Interferon (IFN) is a remedy alternative for patients with hepatitis C, but these treatments have their aspect outcomes. Our research targeted growing an oral small molecule drug that goals hepatitis C virus (HCV) proteins and has fewer facet effects. Our contemporary study targets to broaden a drug primarily based on a small molecule antiviral drug precise for the hepatitis C virus (HCV). Drug improvement and the use of laboratory experiments isn't always best high-priced, however also time-eating to behavior those experiments. instead, on this in silicon have a look at, we used computational strategies to recommend a particular antiviral drug for the protein domain names of discovered in the hepatitis C virus. This examines used homology modeling and abs initio modeling to generate the 3-D shape of the proteins, then figuring out pockets within the proteins. Proper lagans for pocket pills were advanced the usage of the de novo drug design method. Pocket geometry is taken into consideration while designing ligands. A few of the various lagans generated, a different for each of the HCV protein domains has been proposed.

Keywords: drug design, anti-viral drug, in-silicon drug design, Hepatitis C virus (HCV) CAD (Computer Aided Design), CAD education, education improvement, small-size contractor automatic pharmacy, PLC, control system, management system, communication.

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Authors: Yohann R. J. Thomas, Sébastien Solan

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Conventional battery technology includes the assembly of electrode/separator/electrode by standard techniques such as stacking or winding, depending on the format size. In that type of batteries, coating or pasting techniques are only used for the electrode process. The processes are suited for large scale production of batteries and perfectly adapted to plenty of application requirements. Nevertheless, as the demand for both easier and cost-efficient production modes, flexible, custom-shaped and efficient small sized batteries is rising. Thin-film, printable batteries are one of the key areas for printed electronics. In the frame of European BASMATI project, we are investigating the feasibility of a new design of lithium-ion battery: interdigitated planar core design. Polymer substrate is used to produce bendable and flexible rechargeable accumulators. Direct fully printed batteries lead to interconnect the accumulator with other electronic functions for example organic solar cells (harvesting function), printed sensors (autonomous sensors) or RFID (communication function) on a common substrate to produce fully integrated, thin and flexible new devices. To fulfill those specifications, a high resolution printing process have been selected: Aerosol jet printing. In order to fit with this process parameters, we worked on nanomaterials formulation for current collectors and electrodes. In addition, an advanced printed polymer-electrolyte is developed to be implemented directly in the printing process in order to avoid the liquid electrolyte filling step and to improve safety and flexibility. Results: Three different current collectors has been studied and printed successfully. An ink of commercial copper nanoparticles has been formulated and printed, then a flash sintering was applied to the interdigitated design. A gold ink was also printed, the resulting material was partially self-sintered and did not require any high temperature post treatment. Finally, carbon nanotubes were also printed with a high resolution and well defined patterns. Different electrode materials were formulated and printed according to the interdigitated design. For cathodes, NMC and LFP were efficaciously printed. For anodes, LTO and graphite have shown to be good candidates for the fully printed battery. The electrochemical performances of those materials have been evaluated in a standard coin cell with lithium-metal counter electrode and the results are similar with those of a traditional ink formulation and process. A jellified plastic crystal solid state electrolyte has been developed and showed comparable performances to classical liquid carbonate electrolytes with two different materials. In our future developments, focus will be put on several tasks. In a first place, we will synthesize and formulate new specific nano-materials based on metal-oxyde. Then a fully printed device will be produced and its electrochemical performance will be evaluated.

Keywords: high resolution digital printing, lithium-ion battery, nanomaterials, solid-state electrolytes

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Authors: Zunaira Zaman, David Bohannon

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This study explores the application of machine learning (ML) for detecting security vulnerabilities in source code. The research aims to assist organizations with large application portfolios and limited security testing capabilities in prioritizing security activities. ML-based approaches offer benefits such as increased confidence scores, false positives and negatives tuning, and automated feedback. The initial approach using natural language processing techniques to extract features achieved 86% accuracy during the training phase but suffered from overfitting and performed poorly on unseen datasets during testing. To address these issues, the study proposes using the abstract syntax tree (AST) for Java and C++ codebases to capture code semantics and structure and generate path-context representations for each function. The Code2Vec model architecture is used to learn distributed representations of source code snippets for training a machine-learning classifier for vulnerability prediction. The study evaluates the performance of the proposed methodology using two datasets and compares the results with existing approaches. The Devign dataset yielded 60% accuracy in predicting vulnerable code snippets and helped resist overfitting, while the Juliet Test Suite predicted specific vulnerabilities such as OS-Command Injection, Cryptographic, and Cross-Site Scripting vulnerabilities. The Code2Vec model achieved 75% accuracy and a 98% recall rate in predicting OS-Command Injection vulnerabilities. The study concludes that even partial AST representations of source code can be useful for vulnerability prediction. The approach has the potential for automated intelligent analysis of source code, including vulnerability prediction on unseen source code. State-of-the-art models using natural language processing techniques and CNN models with ensemble modelling techniques did not generalize well on unseen data and faced overfitting issues. However, predicting vulnerabilities in source code using machine learning poses challenges such as high dimensionality and complexity of source code, imbalanced datasets, and identifying specific types of vulnerabilities. Future work will address these challenges and expand the scope of the research.

Keywords: code embeddings, neural networks, natural language processing, OS command injection, software security, code properties

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Authors: Mohammad Abu-Shaira, Weishi Shi

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Adaptive learning, a commonly employed solution to drift, involves updating predictive models online during their operation to react to concept drifts, thereby serving as a critical component and natural extension for online learning systems that learn incrementally from each example. This paper introduces LSTM-SCCM “Long Short-Term Memory Stream Cruise Control Method”, a drift adaptation-as-a-service framework for online learning. LSTM-SCCM automates drift adaptation through prompt detection, drift magnitude quantification, dynamic hyperparameter tuning, performing shortterm optimization and model recalibration for immediate adjustments, and, when necessary, conducting long-term model recalibration to ensure deeper enhancements in model performance. LSTM-SCCM is incorporated into a suite of cutting-edge online regression models, assessing their performance across various types of concept drift using diverse datasets with varying characteristics. The findings demonstrate that LSTM-SCCM represents a notable advancement in both model performance and efficacy in handling concept drift occurrences. LSTM-SCCM stands out as the sole framework adept at effectively tackling concept drifts within regression scenarios. Its proactive approach to drift adaptation distinguishes it from conventional reactive methods, which typically rely on retraining after significant degradation to model performance caused by drifts. Additionally, LSTM-SCCM employs an in-memory approach combined with the Self-Adjusting Memory (SAM) architecture to enhance real-time processing and adaptability. The framework incorporates variable thresholding techniques and does not assume any particular data distribution, making it an ideal choice for managing high-dimensional datasets and efficiently handling large-scale data. Our experiments, which include abrupt, incremental, and gradual drifts across both low- and high-dimensional datasets with varying noise levels, and applied to four state-of-the-art online regression models, demonstrate that LSTM-SCCM is versatile and effective, rendering it a valuable solution for online regression models to address concept drift.

Keywords: automated drift detection and adaptation, concept drift, hyperparameters optimization, online and adaptive learning, regression

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Authors: Gideon Nyuimbe Gasu

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Sub Saharan Africa is at a critical point, experiencing rapid population growth, particularly in urban areas and young growing force. At the same time, the growing risk of catastrophic global climate change threatens to weaken food production system, increase intensity and frequency of drought, flood, and fires and undermine gains on development and poverty reduction. Although the region has the lowest per capital greenhouse gas emission level in the world, it will need to join global efforts to address climate change, including action to avoid significant increases and to encourage a green economy. Thus, there is a need for the concept of 'greening the economy' as was prescribed at Rio Summit of 1992. Renewable energy is one of the criterions to achieve this laudable goal of maintaining a green economy. There is need to address climate change while facilitating continued economic growth and social progress as energy today is critical to economic growth. Fossil fuels remain the major contributor of greenhouse gas emission. Thus, cleaner technologies such as carbon capture storage, renewable energy have emerged to be commercially competitive. This paper sets out to examine how to achieve a low carbon economy with minimal emission of carbon dioxide and other greenhouse gases which is one of the outcomes of implementing a green economy. Also, the paper examines the different renewable energy sources such as nuclear, wind, hydro, biofuel, and solar voltaic as a panacea to the looming climate change menace. Finally, the paper assesses the different renewable energy and energy efficiency as a propeller to generating new sources of income and jobs and in turn reduces carbon emission. The research shall engage qualitative, evaluative and comparative methods. The research will employ both primary and secondary sources of information. The primary sources of information shall be drawn from the sub Saharan African region and the global environmental organizations, energy legislation, policies and related industries and the judicial processes. The secondary sources will be made up of some books, journal articles, commentaries, discussions, observations, explanations, expositions, suggestions, prescriptions and other material sourced from the internet on renewable energy as a panacea to climate change. All information obtained from these sources will be subject to content analysis. The research result will show that the entire planet is warming as a result of the activities of mankind which is clear evidence that the current development is fundamentally unsustainable. Equally, the study will reveal that a low carbon development pathway in the sub Saharan African region should be embraced to minimize emission of greenhouse gases such as using renewable energy rather than coal, oil, and gas. The study concludes that until adequate strategies are devised towards the use of renewable energy the region will continue to add and worsen the current climate change menace and other adverse environmental conditions.

Keywords: carbon dioxide, climate change, legislation/law, renewable energy

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Authors: Asiye Nisa Kartal

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An attempt to recognize the undiscovered bounds of Istiklal Street in Istanbul between its sensory experiences (intangible qualities) and physical setting (tangible qualities) could be taken as the first inspiration point for this study. ‘The dramatic physical changes’ and ‘their current impacts on sensory attributions’ of Istiklal Street have directed this study to consider the role of changing the physical layout on sensory dimensions which have a subtle but important role in the examination of urban places. The public places have always been subject to transformation, so in the last years, the changing socio-cultural structure, economic and political movements, law and city regulations, innovative transportation and communication activities have resulted in a controversial modification of Istanbul. And, as the culture, entertainment, tourism, and shopping focus of Istanbul, Istiklal Street has witnessed different changing stages within the last years. In this process, because of the projects being implemented, many buildings such as cinemas, theatres, and bookstores have restored, moved, converted, closed and demolished which have been significant elements in terms of the qualitative value of this area. And, the multi-layered socio-cultural, and architectural structure of Istiklal Street has been changing in a dramatical and controversial way. But importantly, while the physical setting of Istiklal Street has changed, the transformation has not been spatial, socio-cultural, economic; avoidably the sensory dimensions of Istiklal Street which have great importance in terms of intangible qualities of this area have begun to lose their distinctive features. This has created the challenge of this research. As the main hypothesis, this study claims that the physical transformations have led to change in the sensory characteristic of Istiklal Street, therefore the Sensescape of Istiklal Street deserve to be recorded, decoded and promoted as expeditiously as possible to observe the sensory reflections of physical transformations in this area. With the help of the method of ‘Sensewalking’ which is an efficient research tool to generate knowledge on sensory dimensions of an urban settlement, this study suggests way of ‘mapping’ to understand how do ‘changes of physical setting’ play role on ‘sensory qualities’ of Istiklal Street which have been changed or lost over time. Basically, this research focuses on the sensory mapping of Istiklal Street from the 1990s until today to picture, interpret, criticize the ‘sensory mapping of Istiklal Street in present’ and the ‘sensory mapping of Istiklal Street in past’. Through the sensory mapping of Istiklal Street, this study intends to increase the awareness about the distinctive sensory qualities of places. It is worthwhile for further studies that consider the sensory dimensions of places especially in the field of architecture.

Keywords: Istiklal street, sense, sensewalking, sensory mapping

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Authors: Francesco Lubrano, Fabrizio Bertone, Federico Stirano

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Modern societies strongly depend on Critical Infrastructures (CI). Hospitals, power supplies, water supplies, telecommunications are just few examples of CIs that provide vital functions to societies. CIs like hospitals are very complex environments, characterized by a huge number of cyber and physical systems that are becoming increasingly integrated. Ensuring a high level of security within such critical infrastructure requires a deep knowledge of vulnerabilities, threats, and potential attacks that may occur, as well as defence and prevention or mitigation strategies. The possibility to remotely monitor and control almost everything is pushing the adoption of network-connected devices. This implicitly introduces new threats and potential vulnerabilities, posing a risk, especially to those devices connected to the Internet. Modern medical devices used in hospitals are not an exception and are more and more being connected to enhance their functionalities and easing the management. Moreover, hospitals are environments with high flows of people, that are difficult to monitor and can somehow easily have access to the same places used by the staff, potentially creating damages. It is therefore clear that physical and cyber threats should be considered, analysed, and treated together as cyber-physical threats. This means that an integrated approach is required. SAFECARE, an integrated cyber-physical security solution, tries to respond to the presented issues within healthcare infrastructures. The challenge is to bring together the most advanced technologies from the physical and cyber security spheres, to achieve a global optimum for systemic security and for the management of combined cyber and physical threats and incidents and their interconnections. Moreover, potential impacts and cascading effects are evaluated through impact propagation models that rely on modular ontologies and a rule-based engine. Indeed, SAFECARE architecture foresees i) a macroblock related to cyber security field, where innovative tools are deployed to monitor network traffic, systems and medical devices; ii) a physical security macroblock, where video management systems are coupled with access control management, building management systems and innovative AI algorithms to detect behavior anomalies; iii) an integration system that collects all the incoming incidents, simulating their potential cascading effects, providing alerts and updated information regarding assets availability.

Keywords: cyber security, defence strategies, impact propagation, integrated security, physical security

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Authors: Adel Edwar Waheeb Louka

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Purpose AI-driven solutions are at the forefront of many pathology and medical imaging methods. Using algorithms designed to better the experience of medical professionals within their respective fields, the efficiency and accuracy of diagnosis can improve. In particular, X-rays are a fast and relatively inexpensive test that can diagnose diseases. In recent years, X-rays have not been widely used to detect and diagnose COVID-19. The under use of Xrays is mainly due to the low diagnostic accuracy and confounding with pneumonia, another respiratory disease. However, research in this field has expressed a possibility that artificial neural networks can successfully diagnose COVID-19 with high accuracy. Models and Data The dataset used is the COVID-19 Radiography Database. This dataset includes images and masks of chest X-rays under the labels of COVID-19, normal, and pneumonia. The classification model developed uses an autoencoder and a pre-trained convolutional neural network (DenseNet201) to provide transfer learning to the model. The model then uses a deep neural network to finalize the feature extraction and predict the diagnosis for the input image. This model was trained on 4035 images and validated on 807 separate images from the ones used for training. The images used to train the classification model include an important feature: the pictures are cropped beforehand to eliminate distractions when training the model. The image segmentation model uses an improved U-Net architecture. This model is used to extract the lung mask from the chest X-ray image. The model is trained on 8577 images and validated on a validation split of 20%. These models are calculated using the external dataset for validation. The models’ accuracy, precision, recall, f1-score, IOU, and loss are calculated. Results The classification model achieved an accuracy of 97.65% and a loss of 0.1234 when differentiating COVID19-infected, pneumonia-infected, and normal lung X-rays. The segmentation model achieved an accuracy of 97.31% and an IOU of 0.928. Conclusion The models proposed can detect COVID-19, pneumonia, and normal lungs with high accuracy and derive the lung mask from a chest X-ray with similarly high accuracy. The hope is for these models to elevate the experience of medical professionals and provide insight into the future of the methods used.

Keywords: artificial intelligence, convolutional neural networks, deeplearning, image processing, machine learningSarapin, intraarticular, chronic knee pain, osteoarthritisFNS, trauma, hip, neck femur fracture, minimally invasive surgery

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Authors: Natarajan Ramasamy, Gurulingamurthy Haralur, Ramesh Nivarthu, Nikhil Kumar Singha

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Elastomers are polymeric materials with varied backbone architectures ranging from linear to dendrimeric structures and wide varieties of monomeric repeat units. These elastomers show strongly viscous and weakly elastic when it is not cross-linked. But when crosslinked, based on the extent the properties of these elastomers can range from highly flexible to highly stiff nature. Lightly cross-linked systems are well studied and reported. Understanding the nature of highly cross-linked rubber based upon chemical structure and architecture is critical for varieties of applications. One of the critical parameters is cross-link density. In the current work, we have studied the highly cross-linked state of linear, lightly branched to star-shaped branched elastomers and determined the cross-linked density by using different models. Change in hardness, shift in Tg, change in modulus and swelling behavior were measured experimentally as a function of the extent of curing. These properties were analyzed using varied models to determine cross-link density. We used hardness measurements to examine cure time. Hardness to the extent of curing relationship is determined. It is well known that micromechanical transitions like Tg and storage modulus are related to the extent of crosslinking. The Tg of the elastomer in different crosslinked state was determined by DMA, and based on plateau modulus the crosslink density is estimated by using Nielsen’s model. Usually for lightly crosslinked systems, based on equilibrium swelling ratio in solvent the cross link density is estimated by using Flory–Rhener model. When it comes to highly crosslinked system, Flory-Rhener model is not valid because of smaller chain length. So models based on the assumption of polymer as a Non-Gaussian chain like 1) Helmis–Heinrich–Straube (HHS) model, 2) Gloria M.gusler and Yoram Cohen Model, 3) Barbara D. Barr-Howell and Nikolaos A. Peppas model is used for estimating crosslink density. In this work, correction factors are determined to the existing models and based upon it structure-property relationship of highly crosslinked elastomers was studied.

Keywords: dynamic mechanical analysis, glass transition temperature, parts per hundred grams of rubber, crosslink density, number of networks per unit volume of elastomer

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Authors: Guido Lorenzi, Massimo Santarelli, Carlos Augusto Santos Silva

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The growth of non-dispatchable renewable energy sources in the European electricity generation mix is promoting the research of technically feasible and cost-effective solutions to make use of the excess energy, produced when the demand is low. The increasing intermittent renewable capacity is becoming a challenge to face especially in Europe, where some countries have shares of wind and solar on the total electricity produced in 2015 higher than 20%, with Denmark around 40%. However, other consumption sectors (mainly transportation) are still considerably relying on fossil fuels, with a slow transition to other forms of energy. Among the opportunities for different mobility concepts, electric (EV) and biofuel-powered vehicles (BPV) are the options that currently appear more promising. The EVs are targeting mainly the light duty users because of their zero (Full electric) or reduced (Hybrid) local emissions, while the BPVs encourage the use of alternative resources with the same technologies (thermal engines) used so far. The batteries which are applied to EVs are based on ions of Lithium because of their overall good performance in energy density, safety, cost and temperature performance. Biofuels, instead, can be various and the major difference is in their physical state (liquid or gaseous). In this study gaseous biofuels are considered and, more specifically, Synthetic Natural Gas (SNG) produced through a process of Power-to-Gas consisting in an electrochemical upgrade (with Solid Oxide Electrolyzers) of biogas with CO2 recycling. The latter process combines a first stage of electrolysis, where syngas is produced, and a second stage of methanation in which the product gas is turned into methane and then made available for consumption. A techno-economic comparison between the two alternatives is possible, but it does not capture all the different aspects involved in the two routes for the promotion of a more sustainable mobility. For this reason, a more comprehensive methodology, i.e. Life Cycle Assessment, is adopted to describe the environmental implications of using excess electricity (directly or indirectly) for new vehicle fleets. The functional unit of the study is 1 km and the two options are compared in terms of overall CO2 emissions, both considering Cradle to Gate and Cradle to Grave boundaries. Showing how production and disposal of materials affect the environmental performance of the analyzed routes is useful to broaden the perspective on the impacts that different technologies produce, in addition to what is emitted during the operational life. In particular, this applies to batteries for which the decommissioning phase has a larger impact on the environmental balance compared to electrolyzers. The lower (more than one order of magnitude) energy density of Li-ion batteries compared to SNG implies that for the same amount of energy used, more material resources are needed to obtain the same effect. The comparison is performed in an energy system that simulates the Western European one, in order to assess which of the two solutions is more suitable to lead the de-fossilization of the transport sector with the least resource depletion and the mildest consequences for the ecosystem.

Keywords: electrical energy storage, electric vehicles, power-to-gas, life cycle assessment

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Authors: Chitresh Prasad, Arvind Ramesh, Aditya Virkar, Karan Dholkaria, Vinayak Malhotra

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Solid Propellant Rocket is a rocket that utilises a combination of a solid Oxidizer and a solid Fuel. Success in Solid Rocket Motor design and development depends significantly on knowledge of burning rate behaviour of the selected solid propellant under all motor operating conditions and design limit conditions. Most Solid Motor Rockets consist of the Main Engine, along with multiple Boosters that provide an additional thrust to the space-bound vehicle. Though widely used, they have been eclipsed by Liquid Propellant Rockets, because of their better performance characteristics. The addition of a catalyst such as Iron Oxide, on the other hand, can drastically enhance the performance of a Solid Rocket. This scientific investigation tries to emulate the working of a Solid Rocket using Sparklers and Energized Candles, with a central Energized Candle acting as the Main Engine and surrounding Sparklers acting as the Booster. The Energized Candle is made of Paraffin Wax, with Magnesium filings embedded in it’s wick. The Sparkler is made up of 45% Barium Nitrate, 35% Iron, 9% Aluminium, 10% Dextrin and the remaining composition consists of Boric Acid. The Magnesium in the Energized Candle, and the combination of Iron and Aluminium in the Sparkler, act as catalysts and enhance the burn rates of both materials. This combustion of Metallized Propellants has an influence over the regression rate of the subject candle. The experimental parameters explored here are Separation Distance, Systematically varying Configuration and Layout Symmetry. The major performance parameter under observation is the Regression Rate of the Energized Candle. The rate of regression is significantly affected by the orientation and configuration of the sparklers, which usually act as heat sources for the energized candle. The Overall Efficiency of any engine is factorised by the thermal and propulsive efficiencies. Numerous efforts have been made to improve one or the other. This investigation focuses on the Orientation of Rocket Motor Design to maximize their Overall Efficiency. The primary objective is to analyse the Flame Spread Rate variations of the energized candle, which resembles the solid rocket propellant used in the first stage of rocket operation thereby affecting the Specific Impulse values in a Rocket, which in turn have a deciding impact on their Time of Flight. Another objective of this research venture is to determine the effectiveness of the key controlling parameters explored. This investigation also emulates the exhaust gas interactions of the Solid Rocket through concurrent ignition of the Energized Candle and Sparklers, and their behaviour is analysed. Modern space programmes intend to explore the universe outside our solar system. To accomplish these goals, it is necessary to design a launch vehicle which is capable of providing incessant propulsion along with better efficiency for vast durations. The main motivation of this study is to enhance Rocket performance and their Overall Efficiency through better designing and optimization techniques, which will play a crucial role in this human conquest for knowledge.

Keywords: design modifications, improving overall efficiency, metallized combustion, regression rate variations

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Authors: Muhammad Khairi bin Sulaiman

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The utilization of Building Information Modelling (BIM) in the construction industry has provided an opportunity for designers in the Architecture, Engineering and Construction (AEC) industry to proceed from the conventional method of using manual drafting to a way that creates alternative designs quickly, produces more accurate, reliable and consistent outputs. By using BIM Software, designers can create digital content that manipulates the use of data using the parametric model of BIM. With BIM software, more alternative designs can be created quickly and design problems can be explored further to produce a better design faster than conventional design methods. Generally, BIM is used as a documentation mechanism and has not been fully explored and utilised its capabilities as a design tool. Relative to the current issue, Modular Coordination (MC) design as a sustainable design practice is encouraged since MC design will reduce material wastage through standard dimensioning, pre-fabrication, repetitive, modular construction and components. However, MC design involves a complex process of rules and dimensions. Therefore, a tool is needed to make this process easier. Since the parameters in BIM can easily be manipulated to follow MC rules and dimensioning, thus, the integration of BIM software with MC design is proposed for architects during the design stage. With this tool, there will be an improvement in acceptance and practice in the application of MC design effectively. Consequently, this study will analyse and explore the function and customization of BIM objects and the capability of BIM software to expedite the application of MC design during the design stage for architects. With this application, architects will be able to create building models and locate objects within reference modular grids that adhere to MC rules and dimensions. The parametric modeling capabilities of BIM will also act as a visual tool that will further enhance the automation of the 3-Dimensional space planning modeling process. (Method) The study will first analyze and explore the parametric modeling capabilities of rule-based BIM objects, which eventually customize a reference grid within the rules and dimensioning of MC. Eventually, the approach will further enhance the architect's overall design process and enable architects to automate complex modeling, which was nearly impossible before. A prototype using a residential quarter will be modeled. A set of reference grids guided by specific MC rules and dimensions will be used to develop a variety of space planning and configuration. With the use of the design, the tool will expedite the design process and encourage the use of MC Design in the construction industry.

Keywords: building information modeling, modular coordination, space planning, customization, BIM application, MC space planning

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Authors: Tsang K. L. V., Lewis L. A., Griffith S., Tucker P.

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Background:  Many children with high incidence disabilities, such as autism spectrum disorder (ASD), struggle to participate in the community in a socially acceptable manner. There are limitations for clinical settings to provide natural, real-life scenarios for them to practice the life skills needed to meet their real-life challenges. Virtual reality (VR) offers potential solutions to resolve the existing limitations faced by clinicians to create simulated natural environments for their clients to generalize the facilitated skills. Research design: The research aimed to develop a prototype of an interactive VR system to provide realistic and immersive environments for clients to practice skills. The descriptive qualitative methodology is employed to design and develop the Artificial Interactive Reality Unified System (AIRUS) prototype, which provided insights on how to use advanced VR technology to create simulated real-life social scenarios and enable users to interact with the objects and people inside the virtual environment using natural eye-gazes, hand and body movements. The eye tracking (e.g., selective or joint attention), hand- or body-tracking (e.g., repetitive stimming or fidgeting), and facial tracking (e.g., emotion recognition) functions allowed behavioral data to be captured and managed in the AIRUS architecture. Impact of project: Instead of using external controllers or sensors, hand tracking software enabled the users to interact naturally with the simulated environment using daily life behavior such as handshaking and waving to control and interact with the virtual objects and people. The AIRUS protocol offers opportunities for breakthroughs in future VR-based psychosocial assessment and intervention in occupational therapy. Implications for future projects: AI technology can allow more efficient data capturing and interpretation of object identification and human facial emotion recognition at any given moment. The data points captured can be used to pinpoint our users’ focus and where their interests lie. AI can further help advance the data interpretation system.

Keywords: occupational therapy, psychosocial assessment and intervention, simulated interactive environment, virtual reality

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Authors: Hamda M. Al-Ali

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The ultimate aim of space exploration has been centralized around the possibility of life on other planets in the solar system. This aim is driven by the detrimental effects that climate change could potentially have on human survival on Earth in the future. This drives humans to search for feasible solutions to increase environmental and economical sustainability on Earth and to evaluate and explore the ability of human survival on other planets such as Mars. To do that, frequent space missions are required to meet the ambitious human goals. This means that reliable and affordable access to space is required, which could be largely achieved through the use of reusable spacecrafts. Therefore, materials and resources must be used wisely to meet the increasing demand. Space missions are currently extremely expensive to operate. However, reusing materials hence spacecrafts, can potentially reduce overall mission costs as well as the negative impact on both space and Earth environments. This is because reusing materials leads to less waste generated per mission, and therefore fewer landfill sites are required. Reusing materials reduces resource consumption, material production, and the need for processing new and replacement spacecraft and launch vehicle parts. Consequently, this will ease and facilitate human access to outer space as it will reduce the demand for scarce resources, which will boost material efficiency in the space industry. Material efficiency expresses the extent to which resources are consumed in the production cycle and how the waste produced by the industrial process is minimized. The strategies proposed in this paper to boost material efficiency in the space sector are the introduction of key performance indicators that are able to measure material efficiency as well as the introduction of clearly defined policies and legislation that can be easily implemented within the general practices in the space industry. Another strategy to improve material efficiency is by amplifying energy and resource efficiency through reusing materials. The circularity of various spacecraft materials such as Kevlar, steel, and aluminum alloys could be maximized through reusing them directly or after galvanizing them with another layer of material to act as a protective coat. This research paper has an aim to investigate and discuss how to improve material efficiency in space missions considering circular economy concepts so that space and Earth become more economically and environmentally sustainable. The circular economy is a transition from a make-use-waste linear model to a closed-loop socio-economic model, which is regenerative and restorative in nature. The implementation of a circular economy will reduce waste and pollution through maximizing material efficiency, ensuring that businesses can thrive and sustain. Further research into the extent to which reusable launch vehicles reduce space mission costs have been discussed, along with the environmental and economic implications it could have on the space sector and the environment. This has been examined through research and in-depth literature review of published reports, books, scientific articles, and journals. Keywords such as material efficiency, circular economy, reusable launch vehicles and spacecraft materials were used to search for relevant literature.

Keywords: circular economy, key performance indicator, material efficiency, reusable launch vehicles, spacecraft materials

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Authors: Aliaksandr Shuba, Max Welch Guerra, Martin Pekar

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The research is dedicated to the Historiography of European urbanism in the 20th century with its critical analysis of transnational oriented sources in Slavic languages. The goal of this research was to give an overview of Slavic sources on this subject. In the research, historians, who wrote in influential historiographies on architecture and urbanism in the 20th century history in Slavic languages from Eastern, Central and South-eastern Europe, are analysed. The analysis of historiographies in Slavic languages includes diverse sources from around Europe with authors, who examined European Urbanism in the 20th century through a global prism of or their own perspectives. The main publications are from the second half of the 20th century and the early 21st century with Soviet and Post-Soviet discourses. The necessity to analyse Slavic sources was a result of historiography of urbanism establishment as a discipline in the 20th century and by the USSR, Czechslovak, and Yugoslavian academics, who created strong historiographic bases for a development of their urban historiographic schools for wide studies and analysis of architectural and urban ideas and projects with their history in the early 1970s. That is analyzed in this research within Slavic publications, which often have different perspectives and discourses to Anglo-Saxon, and these bibliographic sources can bring a diversity of new ideas in contemporary academic discourse of the European urban historiography. The publications in Slavic languages are analyzed according to the following aspects: where, when, which types, by whom, and to whom the sources were written. The critical analysis of essential sources on the Historiography of European urbanism in the 20th century with an accomplishment through their comparison and interpretation. The authors’ autonomy is analysed as a central point, along with the influence of the Communist Party and state control on the interpretation of the history of urbanism in Central, Eastern and South-eastern Europe with the main dominant topics and ideas from the second half of the 20th century. Cross-national Slavic Historiographic sources and their perspectives are compared to the main transnational Anglo-Saxon Historiographic topics as some of the dominant subjects are hypothetically similar and others have more local or national oriented directions. Some of the dominant subjects, topics, and subtopics are hypothetically similar, while the others have more local or national oriented directions because of the authors’ autonomy and influences of the Communist Party with the state control in Slavic Socialists countries that were illustrated in this research.

Keywords: European urbanism, historiography, different perspectives, 20th century

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Authors: Masoud Fathi Kazerouni, Jens Schlemper, Klaus-Dieter Kuhnert

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Green planet is one of the Earth’s names which is known as a terrestrial planet and also can be named the fifth largest planet of the solar system as another scientific interpretation. Plants do not have a constant and steady distribution all around the world, and even plant species’ variations are not the same in one specific region. Presence of plants is not only limited to one field like botany; they exist in different fields such as literature and mythology and they hold useful and inestimable historical records. No one can imagine the world without oxygen which is produced mostly by plants. Their influences become more manifest since no other live species can exist on earth without plants as they form the basic food staples too. Regulation of water cycle and oxygen production are the other roles of plants. The roles affect environment and climate. Plants are the main components of agricultural activities. Many countries benefit from these activities. Therefore, plants have impacts on political and economic situations and future of countries. Due to importance of plants and their roles, study of plants is essential in various fields. Consideration of their different applications leads to focus on details of them too. Automatic recognition of plants is a novel field to contribute other researches and future of studies. Moreover, plants can survive their life in different places and regions by means of adaptations. Therefore, adaptations are their special factors to help them in hard life situations. Weather condition is one of the parameters which affect plants life and their existence in one area. Recognition of plants in different weather conditions is a new window of research in the field. Only natural images are usable to consider weather conditions as new factors. Thus, it will be a generalized and useful system. In order to have a general system, distance from the camera to plants is considered as another factor. The other considered factor is change of light intensity in environment as it changes during the day. Adding these factors leads to a huge challenge to invent an accurate and secure system. Development of an efficient plant recognition system is essential and effective. One important component of plant is leaf which can be used to implement automatic systems for plant recognition without any human interface and interaction. Due to the nature of used images, characteristic investigation of plants is done. Leaves of plants are the first characteristics to select as trusty parts. Four different plant species are specified for the goal to classify them with an accurate system. The current paper is devoted to principal directions of the proposed methods and implemented system, image dataset, and results. The procedure of algorithm and classification is explained in details. First steps, feature detection and description of visual information, are outperformed by using Scale invariant feature transform (SIFT), HARRIS-SIFT, and FAST-SIFT methods. The accuracy of the implemented methods is computed. In addition to comparison, robustness and efficiency of results in different conditions are investigated and explained.

Keywords: SIFT combination, feature extraction, feature detection, natural images, natural plant recognition, HARRIS-SIFT, FAST-SIFT

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Authors: Volker Landersheim, Daria Manushyna, Thinh Pham, Dai-Duong Tran, Thomas Geury, Omar Hegazy, Steven Wilkins

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Air pollution is one of the emerging problems in our society. Targets of reduction of CO₂ emissions address low-carbon and resource-efficient transport. (Plug-in) hybrid electric propulsion concepts offer the possibility to reduce total cost of ownership (TCO) and emissions for public transport vehicles (e.g., bus application). In this context, typically, diesel engines are used to form the hybrid propulsion system of the vehicle. Though the technological development of diesel engines experience major advantages, some challenges such as the high amount of particle emissions remain relevant. Gaseous fuels (i.e., compressed natural gases (CNGs) or liquefied petroleum gases (LPGs) represent an attractive alternative to diesel because of their composition. In the framework of the research project 'Optimised Real-world Cost-Competitive Modular Hybrid Architecture' (ORCA), which was funded by the EU, two different hybrid-electric propulsion concepts have been investigated: one using a diesel engine as internal combustion engine and one using CNG as fuel. The aim of the current study is to analyze specific benefits for the aforementioned hybrid propulsion systems for predefined driving scenarios with regard to emissions and total cost of ownership in bus application. Engine models based on experimental data for diesel and CNG were developed. For the purpose of designing optimal energy management strategies for each propulsion system, maps-driven or quasi-static models for specific engine types are used in the simulation framework. An analogous modelling approach has been chosen to represent emissions. This paper compares the two concepts regarding their CO₂ and NOx emissions. This comparison is performed for relevant bus missions (urban, suburban, with and without zero-emission zone) and with different energy management strategies. In addition to the emissions, also the downsizing potential of the combustion engine has been analysed to minimize the powertrain TCO (pTCO) for plug-in hybrid electric buses. The results of the performed analyses show that the hybrid vehicle concept using the CNG engine shows advantages both with respect to emissions as well as to pTCO. The pTCO is 10% lower, CO₂ emissions are 13% lower, and the NOx emissions are more than 50% lower than with the diesel combustion engine. These results are consistent across all usage profiles under investigation.

Keywords: bus transport, emissions, hybrid propulsion, pTCO, CNG

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Authors: Christina Drosou, Konstantina E. Kyriakopoulou, Andreas Bimpilas, Dimitrios Tsimogiannis, Magdalini C. Krokida

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Rationale: Agiorgitiko is one of the most widely-grown and commercially well-established red wine varieties in Greece. Each year viticulture industry produces a large amount of waste consisting of grape skins and seeds (pomace) during a short period. Grapes contain polyphenolic compounds which are partially transferred to wine during winemaking. Therefore, winery wastes could be an alternative cheap source for obtaining such compounds with important antioxidant activity. Specifically, red grape waste contains anthocyanins and flavonols which are characterized by multiple biological activities, including cardioprotective, anti-inflammatory, anti-carcinogenic, antiviral and antibacterial properties attributed mainly to their antioxidant activity. Ultrasound assisted extraction (UAE) is considered an effective way to recover phenolic compounds, since it combines the advantage of mechanical effect with low temperature. Moreover, green solvents can be used in order to recover extracts intended for used in the food and nutraceutical industry. Apart from the extraction, pre-treatment process like drying can play an important role on the preservation of the grape pomace and the enhancement of its antioxidant capacity. Objective: The aim of this study is to recover natural extracts from winery waste with high antioxidant capacity using green solvents so they can be exploited and utilized as enhancers in food or nutraceuticals. Methods: Agiorgitiko grape pomace was dehydrated by air drying (AD) and accelerated solar drying (ASD) in order to explore the effect of the pre-treatment on the recovery of bioactive compounds. UAE was applied in untreated and dried samples using water and water: ethanol (1:1) as solvents. The total antioxidant potential and phenolic content of the extracts was determined using the 1,1-diphenyl-2-picrylhydrazyl (DPPH) radical scavenging assay and Folin-Ciocalteu method, respectively. Finally, the profile of anthocyanins and flavonols was specified using HPLC-DAD analysis. The efficiency of processes was determined in terms of extraction yield, antioxidant activity, phenolic content and the anthocyanins and flavovols profile. Results & Discussion: The experiments indicated that the pre-treatment was essential for the recovery of highly nutritious compounds from the pomace as long as the extracts samples showed higher phenolic content and antioxidant capacity. Water: ethanol (1:1) was considered a more effective solvent on the recovery of phenolic compounds. Moreover, ASD grape pomace extracted with the solvent system exhibited the highest antioxidant activity (IC50=0.36±0.01mg/mL) and phenolic content (TPC=172.68±0.01mgGAE/g dry extract), followed by AD and untreated pomace. The major compounds recovered were malvidin3-O-glucoside and quercetin3-O-glucoside according to the HPLC analysis. Conclusions: Winery waste can be exploited for the recovery of nutritious compounds using green solvents such as water or ethanol. The pretreatment of the pomace can significantly affect the concentration of phenolic compounds, while UAE is considered a highly effective extraction process.

Keywords: agiorgitico grape pomace, antioxidants, phenolic compounds, ultrasound assisted extraction

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Authors: Andrei Bejan, Luminita Marin, Dalila Belei

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Phenothiazine with electron-rich nitrogen and sulfur heteroatoms has a high electron-donating ability which promotes a good conjugation and therefore low band-gap with consequences upon charge carrier mobility improving and shifting of light emission in visible domain. Moreover, its non-planar butterfly conformation inhibits molecular aggregation and thus preserves quite well the fluorescence quantum yield in solid state compared to solution. Therefore phenothiazine and its derivatives are promising hole transport materials for use in organic electronic and optoelectronic devices as light emitting diodes, photovoltaic cells, integrated circuit sensors or driving circuits for large area display devices. The objective of this paper was to obtain a series of new phenothiazine derivatives by introduction of different electron withdrawing substituents as formyl, carboxyl and cyanoacryl units in order to create a push pull system which has potential to improve the electronic and optical properties. Bromine atom was used as electrono-donor moiety to extend furthermore the existing conjugation. The understudy compounds were structural characterized by FTIR and 1H-NMR spectroscopy and single crystal X-ray diffraction. Besides, the single crystal X-ray diffraction brought information regarding the supramolecular architecture of the compounds. Photophysical properties were monitored by UV-vis and photoluminescence spectroscopy, while the electrochemical behavior was established by cyclic voltammetry. The absorption maxima of the studied compounds vary in a large range (322-455 nm), reflecting the different electronic delocalization degree, depending by the substituent nature. In a similar manner, the emission spectra reveal different color of emitted light, a red shift being evident for the groups with higher electron withdrawing ability. The emitted light is pure and saturated for the compounds containing strong withdrawing formyl or cyanoacryl units and reach the highest quantum yield of 71% for the compound containing bromine and cyanoacrilic units. Electrochemical study show reversible oxidative and reduction processes for all the compounds and a close correlation of the HOMO-LUMO band gap with substituent nature. All these findings suggest the obtained compounds as promising materials for optoelectronic devices.

Keywords: electrochemical properties, phenothiazine derivatives, photoluminescence, quantum yield

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Authors: Domenica Bona

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Colin Chant and David Goodman argue that historians of Chinese pre-industrial cities tend to underestimate revolutions and overestimate cyclic patterns: periods of peace and prosperity in the earl part of each d nast , followed b peasants’ rebellions and upheavals. Boyd described these cyclic patterns as part of the background of Chinese town planning and architecture. Thus old ideals of city planning-square plan, southward orientation and a palace along the central axis - are revived again and again in the ascendant phases of several d nastic c cles (e.g. Chang’an, Kaifen, and Beijing). Along this line of thought, m paper questions the relationship between the “magic square rule” and modern Chinese urban- planning. As a matter of fact, the classical theme of “cosmic Taoist urbanism” is still a reference for planning cities and new urban developments, whenever there is the intention to express nationalist ideals and “cultural straightforwardness.” Besides, some case studies can be related to “modern d nasties”: the first Republic under the Kuo Min Tang, the red People’s Republic and the post-Maoist open country of Deng Xiao Ping. Considering the project for the new capital of Nanjing in the Thirties, Beijing’s Tianan Men area in the ifties, and Shenzhen’s utian CBD in late 20th century, I argue that cyclic patterns are still in place, though with deformations related to westernization, private interests and lack of spirituality. How far new Chinese cities are - or simply seem to be - westernized? Symbolism, invisible frameworks, repeating features and behavioural patterns make urban China just “superficiall” western. This can be well noticed in cities previousl occupied b foreigners, like Hong Kong, or in newly founded ones, like Shenzhen, where both Asians and non-Asian people can feel the gender-shift from New-York-like landscapes to something else. Current planning in main metropolitan areas shows a blurred relationship between public policies and private investments: two levels of decisions and actions, one addressing the larger scale and infrastructures, the other concerning the micro scale and development of single plots. While zoning is instrumental in this process, master plans are often laid out over a very poor cartography, so much that any relation between the formal characters of new cities and the centuries-old structure of the related territory gets lost.

Keywords: China, contemporary cities, cultural heritage, shenzhen, urban planning

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Authors: Esshili Awatef, Manitz Marie-Pierre, Eßlinger Manuela, Gerhardt Alexandra, Plümper Jennifer, Wachholz Simone, Friebe Astrid, Juckel Georg

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Maternal immune activation (MIA) resulting from maternal viral infection during pregnancy is a known risk factor for schizophrenia. The neural mechanisms by which maternal infections increase the risk for schizophrenia remain unknown, although the prevailing hypothesis argues that an activation of the maternal immune system induces changes in the maternal-fetal environment that might interact with fetal brain development. It may lead to an activation of fetal microglia inducing long-lasting functional changes of these cells. Based on post-mortem analysis showing an increased number of activated microglial cells in patients with schizophrenia, it can be hypothesized that these cells contribute to disease pathogenesis and may actively be involved in gray matter loss observed in such patients. In the present study, we hypothesize that prenatal treatment with the inflammatory agent Poly(I:C) during embryogenesis at contributes to microglial activation in the offspring, which may, therefore, represent a contributing factor to the pathogenesis of schizophrenia and underlines the need for new pharmacological treatment options. Pregnant rats were treated with intraperitoneal injections a single dose of Poly(I:C) or saline on gestation day 17. Brains of control and Poly(I:C) offspring, were removed and into 20-μm-thick coronal sections were cut by using a Cryostat. Brain slices were fixed and immunostained with ba1 antibody. Subsequently, Iba1-immunoreactivity was detected using a secondary antibody, goat anti-rabbit. The sections were viewed and photographed under microscope. The immunohistochemical analysis revealed increases in microglia cell number in the prefrontal cortex, in offspring of poly(I:C) treated-rats as compared to the controls injected with NaCl. However, no significant differences were observed in microglia activation in the cerebellum among the groups. Prenatal immune challenge with Poly(I:C) was able to induce long-lasting changes in the offspring brains. This lead to a higher activation of microglia cells in the prefrontal cortex, a brain region critical for many higher brain functions, including working memory and cognitive flexibility. which might be implicated in possible changes in cortical neuropil architecture in schizophrenia. Further studies will be needed to clarify the association between microglial cells activation and schizophrenia-related behavioral alterations.

Keywords: Microglia, neuroinflammation, PolyI:C, schizophrenia

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Authors: Eiman Kattan, Hong Wei

Abstract:

In using Convolutional Neural Network (CNN) for classification, there is a set of hyperparameters available for the configuration purpose. This study aims to evaluate the impact of a range of parameters in CNN architecture i.e. AlexNet on land cover classification based on four remotely sensed datasets. The evaluation tests the influence of a set of hyperparameters on the classification performance. The parameters concerned are epoch values, batch size, and convolutional filter size against input image size. Thus, a set of experiments were conducted to specify the effectiveness of the selected parameters using two implementing approaches, named pertained and fine-tuned. We first explore the number of epochs under several selected batch size values (32, 64, 128 and 200). The impact of kernel size of convolutional filters (1, 3, 5, 7, 10, 15, 20, 25 and 30) was evaluated against the image size under testing (64, 96, 128, 180 and 224), which gave us insight of the relationship between the size of convolutional filters and image size. To generalise the validation, four remote sensing datasets, AID, RSD, UCMerced and RSCCN, which have different land covers and are publicly available, were used in the experiments. These datasets have a wide diversity of input data, such as number of classes, amount of labelled data, and texture patterns. A specifically designed interactive deep learning GPU training platform for image classification (Nvidia Digit) was employed in the experiments. It has shown efficiency in both training and testing. The results have shown that increasing the number of epochs leads to a higher accuracy rate, as expected. However, the convergence state is highly related to datasets. For the batch size evaluation, it has shown that a larger batch size slightly decreases the classification accuracy compared to a small batch size. For example, selecting the value 32 as the batch size on the RSCCN dataset achieves the accuracy rate of 90.34 % at the 11th epoch while decreasing the epoch value to one makes the accuracy rate drop to 74%. On the other extreme, setting an increased value of batch size to 200 decreases the accuracy rate at the 11th epoch is 86.5%, and 63% when using one epoch only. On the other hand, selecting the kernel size is loosely related to data set. From a practical point of view, the filter size 20 produces 70.4286%. The last performed image size experiment shows a dependency in the accuracy improvement. However, an expensive performance gain had been noticed. The represented conclusion opens the opportunities toward a better classification performance in various applications such as planetary remote sensing.

Keywords: CNNs, hyperparamters, remote sensing, land cover, land use

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Authors: M. Kharrat, G. Moreau, Z. Aboura

Abstract:

The latest advances in the weaving industry, combined with increasingly sophisticated means of materials processing, have made it possible to produce complex 3D composite structures. Mainly used in aeronautics, composite materials with 3D architecture offer better mechanical properties than 2D reinforced composites. Nevertheless, these materials require a good understanding of their behavior. Because of the complexity of such materials, the damage mechanisms are multiple, and the scenario of their appearance and evolution depends on the nature of the exerted solicitations. The AE technique is a well-established tool for discriminating between the damage mechanisms. Suitable sensors are used during the mechanical test to monitor the structural health of the material. Relevant AE-features are then extracted from the recorded signals, followed by a data analysis using pattern recognition techniques. In order to better understand the damage scenarios of interlock composite materials, a multi-instrumentation was set-up in this work for tracking damage initiation and development, especially in the vicinity of the first significant damage, called macro-damage. The deployed instrumentation includes video-microscopy, Digital Image Correlation, Acoustic Emission (AE) and micro-tomography. In this study, a multi-variable AE data analysis approach was developed for the discrimination between the different signal classes representing the different emission sources during testing. An unsupervised classification technique was adopted to perform AE data clustering without a priori knowledge. The multi-instrumentation and the clustered data served to label the different signal families and to build a learning database. This latter is useful to construct a supervised classifier that can be used for automatic recognition of the AE signals. Several materials with different ingredients were tested under various solicitations in order to feed and enrich the learning database. The methodology presented in this work was useful to refine the damage threshold for the new generation materials. The damage mechanisms around this threshold were highlighted. The obtained signal classes were assigned to the different mechanisms. The isolation of a 'noise' class makes it possible to discriminate between the signals emitted by damages without resorting to spatial filtering or increasing the AE detection threshold. The approach was validated on different material configurations. For the same material and the same type of solicitation, the identified classes are reproducible and little disturbed. The supervised classifier constructed based on the learning database was able to predict the labels of the classified signals.

Keywords: acoustic emission, classifier, damage mechanisms, first damage threshold, interlock composite materials, pattern recognition

Procedia PDF Downloads 155