Search results for: real estate price prediction

Authors: Rossella Resi

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This paper describes a project carried out in an Italian school with English learning pupils combining three didactic tools which are attested to be relevant for the success of young learner’s language curriculum: the use of technology, the intralingual and interlingual mediation (according to CEFR) and the cultural dimension. Aim of this project was to test a technological hands-on translation activity like subtitling in a formal teaching context and to exploit its potential as motivational tool for developing listening and writing, translation and cross-cultural skills among language learners. The activities proposed involved the use of professional subtitling software called Aegisub and culture-specific films. The workshop was optional so motivation was entirely based on the pleasure of engaging in the use of a realistic subtitling program and on the challenge of meeting the constraints that a real life/work situation might involve. Twelve pupils in the age between 16 and 18 have attended the afternoon workshop. The workshop was organized in three parts: (i) An introduction where the learners were opened up to the concept and constraints of subtitling and provided with few basic rules on spotting and segmentation. During this session learners had also the time to familiarize with the main software features. (ii) The second part involved three subtitling activities in plenum or in groups. In the first activity the learners experienced the technical dimensions of subtitling. They were provided with a short video segment together with its transcription to be segmented and time-spotted. The second activity involved also oral comprehension. Learners had to understand and transcribe a video segment before subtitling it. The third activity embedded a translation activity of a provided transcription including segmentation and spotting of subtitles. (iii) The workshop ended with a small final project. At this point learners were able to master a short subtitling assignment (transcription, translation, segmenting and spotting) on their own with a similar video interview. The results of these assignments were above expectations since the learners were highly motivated by the authentic and original nature of the assignment. The subtitled videos were evaluated and watched in the regular classroom together with other students who did not take part to the workshop.

Keywords: ICT, L2, language learning, language mediation, subtitling

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Authors: Muhammet Şahal, Oğuz Köklü

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As statistical thinking and problem-solving processes have become increasingly important, teachers need to be more rigorously prepared with statistical knowledge to teach their students effectively. This study examined preservice mathematics teachers' development of statistical investigation projects using data and exploratory data analysis tools, following a design-based research perspective and statistical investigation cycle. A total of 26 pre-service senior mathematics teachers from a public university in Turkiye participated in the study. They formed groups of 3-4 members voluntarily and worked on their statistical investigation projects for six weeks. The data sources were audio recordings of pre-service teachers' group discussions while working on their projects in class, whole-class video recordings, and each group’s weekly and final reports. As part of the study, we reviewed weekly reports, provided timely feedback specific to each group, and revised the following week's class work based on the groups’ needs and development in their project. We used content analysis to analyze groups’ audio and classroom video recordings. The participants encountered several difficulties, which included formulating a meaningful statistical question in the early phase of the investigation, securing the most suitable data collection strategy, and deciding on the data analysis method appropriate for their statistical questions. The data collection and organization processes were challenging for some groups and revealed the importance of comprehensive planning. Overall, preservice senior mathematics teachers were able to work on a statistical project that contained the formulation of a statistical question, planning, data collection, analysis, and reaching a conclusion holistically, even though they faced challenges because of their lack of experience. The study suggests that preservice senior mathematics teachers have the potential to apply statistical knowledge and techniques in a real-world context, and they could proceed with the project with the support of the researchers. We provided implications for the statistical education of teachers and future research.

Keywords: design-based study, pre-service mathematics teachers, statistical investigation projects, statistical model

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Authors: Rolivhuwa Bishop Ramagoma1*, Lynn Cairncross1, , Saartjie Roux1

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According to the world health organisation, colon cancer is among the most common cancers diagnosed in both men and women. Specifically, it is the second leading cause of cancer related deaths accounting for over 860 000 deaths worldwide in 2018. Currently, chemotherapy has become an essential component of most cancer treatments. Despite progress in cancer drug development over the previous years, traditional chemotherapeutic drugs still have low selectivity for targeting tumour tissues and are frequently constrained by dose-limiting toxicity. The creation of nanoscale delivery vehicles capable of directly directing treatment into cancer cells has recently caught the interest of researchers. Herein, the development of peptide-functionalized polyethylene glycol gold nanoparticles (Peptide-PEG-AuNPs) as a cellular probe and delivery agent is described, with the higher aim to develop a specific diagnostic prototype and assess their specificity not only against cell lines but primary human cells as well. Gold nanoparticles (AuNPs) were synthesized and stabilized through chemical conjugation. The synthesized AuNPs were characterized, stability in physiological solutions was assessed, their cytotoxicity against colon carcinoma and non-carcinoma skin fibroblasts was also studied. Furthermore, genetic effect through real-time polymerase chain reaction (RT-PCR), localization and uptake, peptide specificity were also determined. In this study, different peptide-AuNPs were found to have preferential toxicity at higher concentrations, as revealed by cell viability assays, however, all AuNPs presented immaculate stability for over 3 months following the method of synthesis. The final obtained peptide-PEG-AuNP conjugates showed good biocompatibility in the presence of high ionic solutions and biological media and good cellular uptake. Formulation of colon cancer specific targeting peptide was successful, additionally, the genes/pathways affected by the treatments were determined through RT-PCR. Primary cells study is still on going with promising results thus far.

Keywords: nanotechnology, cancer, diagnosis, therapeutics, gold nanoparticles.

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Authors: Mustapha Ouardouz, Mina Amharref, Abdessamed Bernoussi

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The future energy, for limited energy resources countries, goes through renewable energies (solar, wind etc.). The renewable energies constitute a major component of the energy strategy to cover a substantial part of the growing needs and contribute to environmental protection by replacing fossil fuels. Indeed, sustainable development involves the promotion of renewable energy and the preservation of the environment by the use of clean energy technologies to limit emissions of greenhouse gases and reducing the pressure exerted on the forest cover. So the impact studies, of the energy use on the environment and farm-related risks are necessary. For that, a global approach integrating all the various sectors involved in such project seems to be the best approach. In this paper we present an approach based on the multi criteria analysis and the realization of one pilot to achieve the development of an innovative geo-intelligent environmental platform. An implementation of this platform will collect, process, analyze and manage environmental data in connection with the nature of used energy in the studied region. As an application we consider a region in the north of Morocco characterized by intense agricultural and industrials activities and using diverse renewable energy. The strategic goals of this platform are; the decision support for better governance, improving the responsiveness of public and private companies connected by providing them in real time with reliable data, modeling and simulation possibilities of energy scenarios, the identification of socio-technical solutions to introduce renewable energies and estimate technical and implantable potential by socio-economic analyzes and the assessment of infrastructure for the region and the communities, the preservation and enhancement of natural resources for better citizenship governance through democratization of access to environmental information, the tool will also perform simulations integrating environmental impacts of natural disasters, particularly those linked to climate change. Indeed extreme cases such as floods, droughts and storms will be no longer rare and therefore should be integrated into such projects.

Keywords: renewable energies, decision aided tool, environment, simulation

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Authors: Ahlem Bouziri, Chiraz Latiri, Eric Gaussier

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The steady growth in the size of textual document collections is a key progress-driver for modern information retrieval techniques whose effectiveness and efficiency are constantly challenged. Given a user query, the number of retrieved documents can be overwhelmingly large, hampering their efficient exploitation by the user. In addition, retaining only relevant documents in a query answer is of paramount importance for an effective meeting of the user needs. In this situation, the query expansion technique offers an interesting solution for obtaining a complete answer while preserving the quality of retained documents. This mainly relies on an accurate choice of the added terms to an initial query. Interestingly enough, query expansion takes advantage of large text volumes by extracting statistical information about index terms co-occurrences and using it to make user queries better fit the real information needs. In this respect, a promising track consists in the application of data mining methods to extract dependencies between terms, namely a generic basis of association rules between terms. The key feature of our approach is a better trade off between the size of the mining result and the conveyed knowledge. Thus, face to the huge number of derived association rules and in order to select the optimal combination of query terms from the generic basis, we propose to model the problem as a classification problem and solve it using a supervised learning algorithm such as SVM or k-means. For this purpose, we first generate a training set using a genetic algorithm based approach that explores the association rules space in order to find an optimal set of expansion terms, improving the MAP of the search results. The experiments were performed on SDA 95 collection, a data collection for information retrieval. It was found that the results were better in both terms of MAP and NDCG. The main observation is that the hybridization of text mining techniques and query expansion in an intelligent way allows us to incorporate the good features of all of them. As this is a preliminary attempt in this direction, there is a large scope for enhancing the proposed method.

Keywords: supervised leaning, classification, query expansion, association rules

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Authors: I. Hakki Eraslan, Birol Ozturk, Istemi Comlekci

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This paper begins by defining what is meant by “globalization” in finance and by identifying the sources of value-added in the internationally-competitive financial services sector origination, trading and distribution of debt and equity capital market instruments and their derivatives, foreign exchange trading and securities brokerage, management of market risk and credit risk, loan syndication and structured bank financings, corporate finance and advisory services, and asset management. These activities are considered in terms of a “value-chain” one that ultimately gives rise to the real economic gains attributable to financial-center operations. The research presents available evidence as to where the relevant value-added activities usually take place. It then examines the “centrifugal” and “centripetal” forces that determine the concentration or dispersal of value-added activity in financial intermediation, both interregionally and internationally. Next, the research assesses the factors, which appear to underlie the locational pattern of international financial centers that has evolved. In preparing this paper, also it is examined the current position and the main opportunities and challenges facing world major financial services sector, and attempted to lay out a potential vision and strategies. It is conducted extensive research, including many internal research materials and publications. It is also engaged closely with the academia, industry practitioners and regulators, and consulted market experts from major world financial centers. More than 60 in‐depth consultative sessions were conducted in the past two years which provided insightful suggestions and innovative ideas on how to further financial industry’s position as an international financial centre. The paper concludes with the outlook for the future pattern of financial centers in the global competitive environment. The ideas and advice gathered are condensed into this paper that recommends to the strategic decision leaders a vision and a strategy for financial services sector to move forward amid a highly competitive environment.

Keywords: financial centers, competitiveness, financial services industry, economics

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Authors: Manpreet Kaur, Cheol-Hong Min

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The increasing advancement in the robotics equipped with machine vision sensors applied to precision agriculture is a demanding solution for various problems in the agricultural farms. An important issue related with the machine vision system concerns crop row and weed detection. This paper proposes an automatic furrow detection system based on real-time processing for identifying crop rows in maize fields in the presence of weed. This vision system is designed to be installed on the farming vehicles, that is, submitted to gyros, vibration and other undesired movements. The images are captured under image perspective, being affected by above undesired effects. The goal is to identify crop rows for vehicle navigation which includes weed removal, where weeds are identified as plants outside the crop rows. The images quality is affected by different lighting conditions and gaps along the crop rows due to lack of germination and wrong plantation. The proposed image processing method consists of four different processes. First, image segmentation based on HSV (Hue, Saturation, Value) decision tree. The proposed algorithm used HSV color space to discriminate crops, weeds and soil. The region of interest is defined by filtering each of the HSV channels between maximum and minimum threshold values. Then the noises in the images were eliminated by the means of hybrid median filter. Further, mathematical morphological processes, i.e., erosion to remove smaller objects followed by dilation to gradually enlarge the boundaries of regions of foreground pixels was applied. It enhances the image contrast. To accurately detect the position of crop rows, the region of interest is defined by creating a binary mask. The edge detection and Hough transform were applied to detect lines represented in polar coordinates and furrow directions as accumulations on the angle axis in the Hough space. The experimental results show that the method is effective.

Keywords: furrow detection, morphological, HSV, Hough transform

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Authors: Auwal Abubakar, Shazril Imran Shaukat, Noor Khairiah A. Karim, Mohammed Zakir Kassim, Gokula Kumar Appalanaido, Hafiz Mohd Zin

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Background: Voluntary deep inspiration breath-hold radiotherapy (vDIBH-RT) is an effective cardiac dose reduction technique during left breast radiotherapy. This study aimed to assess the accuracy of the implementation of the vDIBH technique among left breast cancer patients without the use of a special device such as a surface-guided imaging system. Methods: The vDIBH-RT technique was implemented among thirteen (13) left breast cancer patients at the Advanced Medical and Dental Institute (AMDI), Universiti Sains Malaysia. Breath-hold monitoring was performed based on breath-hold skin marks and laser light congruence observed on zoomed CCTV images from the control console during each delivery. The initial setup was verified using cone beam computed tomography (CBCT) during breath-hold. Each field was delivered using multiple beam segments to allow a delivery time of 20 seconds, which can be tolerated by patients in breath-hold. The data were analysed using an in-house developed MATLAB algorithm. PTV margin was computed based on van Herk's margin recipe. Results: The setup error analysed from CBCT shows that the population systematic error in lateral (x), longitudinal (y), and vertical (z) axes was 2.28 mm, 3.35 mm, and 3.10 mm, respectively. Based on the CBCT image guidance, the Planning target volume (PTV) margin that would be required for vDIBH-RT using CCTV/Laser monitoring technique is 7.77 mm, 10.85 mm, and 10.93 mm in x, y, and z axes, respectively. Conclusion: It is feasible to safely implement vDIBH-RT among left breast cancer patients without special equipment. The breath-hold monitoring technique is cost-effective, radiation-free, easy to implement, and allows real-time breath-hold monitoring.

Keywords: vDIBH, cone beam computed tomography, radiotherapy, left breast cancer

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Authors: Poonam Sharma, Ankur Srivastav

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Cities are complex and dynamic systems that constitute a significant challenge to urban planning. The increasing size of the built-up area owing to growing population pressure and economic growth have lead to massive Landuse/Landcover change resulted in the loss of natural habitat and thus reducing the green covers in urban areas. Urban environmental quality is influenced by several aspects, including its geographical configuration, the scale, and nature of human activities occurring and environmental impacts generated. Cities have transformed into complex and dynamic systems that constitute a significant challenge to urban planning. Cities and their sustainability are often discussed together as the cities stand confronted with numerous environmental concerns as the world becoming increasingly urbanized, and the cities are situated in the mesh of global networks in multiple senses. A rapid transformed urban setting plays a crucial role to change the green area of natural habitats. To examine the pattern of urban growth and to measure the Landuse/Landcover change in Gurgoan in Haryana, India through the integration of Geospatial technique is attempted in the research paper. Satellite images are used to measure the spatiotemporal changes that have occurred in the land use and land cover resulting into a new cityscape. It has been observed from the analysis that drastically evident changes in land use has occurred with the massive rise in built up areas and the decrease in green cover and therefore causing the sustainability of the city an important area of concern. The massive increase in built-up area has influenced the localised temperatures and heat concentration. To enhance the decision-making process in urban planning, a detailed and real world depiction of these urban spaces is the need of the hour. Monitoring indicators of key processes in land use and economic development are essential for evaluating policy measures.

Keywords: cityscape, geospatial techniques, green cover index, urban environmental quality, urban planning

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Authors: Afsha Shaikh, Mohammed Azizur Rahman, Ibrahim Hassan, Mayur Pal

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Student engagement in learning is instantly affected by the sources of learning methods available for them, such as videos showing the applications of the concept or showing a practical demonstration. Specific to the engineering discipline, there exist enormous challenging concepts that can be simplified when they are connected to real-world scenarios. For this study, the concept of heat exchangers was used as it is a part of multidisciplinary engineering fields. To make the learning experience enjoyable and impactful, 3-D printed heat exchanger models were created for students to use while working on in-class activities and assignments. Students were encouraged to use the 3-D printed heat exchanger models to enhance their understanding of theoretical concepts associated with its applications. To assess the effectiveness of the method, feedback was received by students pursuing undergraduate engineering via an anonymous electronic survey. To make the feedback more realistic, unbiased, and genuine, students spent nearly two to three weeks using the models in their in-class assignments. The impact of these tools on their learning was assessed through their performance in their ungraded assignments as well as their interactive discussions with peers. ‘Having to apply the theory learned in class whilst discussing with peers on a class assignment creates a relaxed and stress-free learning environment in classrooms’; this feedback was received by more than half the students who took the survey and found 3-D models of heat exchanger very easy to use. Amongst many ways to enhance learning and make students more engaged through interactive models, this study sheds light on the importance of physical tools that help create a lasting mental representation in the minds of students. Moreover, in this technologically enhanced era, the concept of augmented reality was considered in this research. E-drawings application was recommended to enhance the vision of engineering students so they can see multiple views of the detailed 3-D models and cut through its different sides and angles to visualize it properly. E-drawings could be the next tool to implement in classrooms to enhance students’ understanding of engineering concepts.

Keywords: student engagement, life-long-learning, visual demonstration, 3-D printed models, engineering education

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Authors: Meenakshi Barsaul Chauhan, Aastha Chauhan, Shilpa Hurmade, Rajeev Sen, Jyotsna Sen, Monika Dalal

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Introduction: Ovarian masses are common forms of neoplasm in women and represent 2/3rd of gynaecological malignancies. A pre-operative suggestion of malignancy can guide the gynecologist to refer women with suspected pelvic mass to a gynecological oncologist for appropriate therapy and optimized treatment, which can improve survival. In the younger age group preoperative differentiation into benign or malignant pathology can decide for conservative or radical surgery. Imaging modalities have a definite role in establishing the diagnosis. By using International Ovarian Tumor Analysis (IOTA) classification with sonography, costly radiological methods like Magnetic Resonance Imaging (MRI) / computed tomography (CT) scan can be reduced, especially in developing countries like India. Thus, this study is being undertaken to evaluate the role of clinical methods and sonography for diagnosis of the nature of the ovarian tumor. Material And Methods: This prospective observational study was conducted on 40 patients presenting with ovarian masses, in the Department of Obstetrics and Gynaecology, at a tertiary care center in northern India. Functional cysts were excluded. Ultrasonography and color Doppler were performed on all the cases.IOTA rules were applied, which take into account locularity, size, presence of solid components, acoustic shadow, dopper flow etc . Magnetic Resonance Imaging (MRI) / computed tomography (CT) scans abdomen and pelvis were done in cases where sonography was inconclusive. In inoperable cases, Fine needle aspiration cytology (FNAC) was done. The histopathology report after surgery and cytology report after FNAC was correlated statistically with the pre-operative diagnosis made clinically and sonographically using IOTA rules. Statistical Analysis: Descriptive measures were analyzed by using mean and standard deviation and the Student t-test was applied and the proportion was analyzed by applying the chi-square test. Inferential measures were analyzed by sensitivity, specificity, negative predictive value, and positive predictive value. Results: Provisional diagnosis of the benign tumor was made in 16(42.5%) and of the malignant tumor was made in 24(57.5%) patients on the basis of clinical findings. With IOTA simple rules on sonography, 15(37.5%) were found to be benign, while 23 (57.5%) were found to be malignant and findings were inconclusive in 2 patients (5%). FNAC/Histopathology reported that benign ovarian tumors were 14 (35%) and 26(65%) were malignant, which was taken as the gold standard. The clinical finding alone was found to have a sensitivity of 66.6% and a specificity of 90.9%. USG alone had a sensitivity of 86% and a specificity of 80%. When clinical findings and IOTA simple rules of sonography were combined (excluding inconclusive masses), the sensitivity and specificity were 83.3% and 92.3%, respectively. While including inconclusive masses, sensitivity came out to be 91.6% and specificity was 89.2. Conclusion: IOTA's simple sonography rules are highly sensitive and specific in the prediction of ovarian malignancy and also easy to use and easily reproducible. Thus, combining clinical examination with USG will help in the better management of patients in terms of time, cost and better prognosis. This will also avoid the need for costlier modalities like CT, and MRI.

Keywords: benign, international ovarian tumor analysis classification, malignant, ovarian tumours, sonography

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Authors: Jonas Sanon

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The valorization of research is becoming a transversal instrument linking different sectors (academic, public and industrial). The practice of valorization seems to impact innovation techniques within companies where, there is often the implementation of industrial conventions of training through research (CIFRE), continuous training programs for employees, collaborations and partnerships around joint research and R&D laboratories focused on the needs of companies to improve or develop more efficient innovations. Furthermore, many public initiatives to support innovation and technology transfer have been developed at the international, European and national levels, with significant budget allocations. Thus, in the context of this work, we tried to analyze the way in which research transfer structures are evaluated within the Saclay ecosystem. In fact, the University-Paris-Saclay is one of the best French universities; it is made up of 10 university components, more than 275 laboratories and is in partnership with the largest French research centers This work mainly focused on how evaluations affected research transfer structures, how evaluations were conducted, and what the managers of research transfer structures thought about assessments. Thus, with the aid of the conducted interviews, it appears that the evaluations do not have a significant impact on the qualitative aspect of research and innovation, but is rather present a directive aspect to allow the structures to benefit or not from the financial resources to develop certain research work, sometimes directed and influenced by the market, some researchers might try to accentuate their research and experimentation work on themes that are not necessarily their areas of interest, but just to comply with the calls for proposed thematic projects. The field studies also outline the primary indicators used to assess the effectiveness of valorization structures as "the number of start-ups generated, the license agreements signed, the structure's patent portfolio, and the innovations of items developed from public research.". Finally, after mapping the actors, it became clear that the ecosystem of the University of Paris-Saclay benefits from a richness allowing it to better value its research in relation to the three categories of actors it has (internal, external and transversal), united and linked by a relationship of proximity of sharing and endowed with a real opportunity to innovate openly.

Keywords: research valorization, technology transfer, innovation, evaluation, impacts and performances, innovation policy

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Authors: George N. Prodromidis, Frank A. Coutelieris

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Biogas can be currently considered as an alternative option for electricity production, mainly due to its high energy content (hydrocarbon-rich source), its renewable status and its relatively low utilization cost. Solid Oxide Fuel Cell (SOFC) stacks convert fuel’s chemical energy to electricity with high efficiencies and reveal significant advantages on fuel flexibility combined with lower emissions rate, especially when utilize biogas. Electricity production by biogas constitutes a composite problem which incorporates an extensive parametric analysis on numerous dynamic variables. The main scope of the presented study is to propose a detailed thermodynamic model on the optimization of SOFC-based power plants’ operation based on fundamental thermodynamics, energy and exergy balances. This model named THERMAS (THERmodynamic MAthematical Simulation model) incorporates each individual process, during electricity production, mathematically simulated for different case studies that represent real life operational conditions. Also, THERMAS offers the opportunity to choose a great variety of different values for each operational parameter individually, thus allowing for studies within unexplored and experimentally impossible operational ranges. Finally, THERMAS innovatively incorporates a specific criterion concluded by the extensive energy analysis to identify the most optimal scenario per simulated system in exergy terms. Therefore, several dynamical parameters as well as several biogas mixture compositions have been taken into account, to cover all the possible incidents. Towards the optimization process in terms of an innovative OPF (OPtimization Factor), presented here, this research study reveals that systems supplied by low methane fuels can be comparable to these supplied by pure methane. To conclude, such an innovative simulation model indicates a perspective on the optimal design of a SOFC stack based system, in the direction of the commercialization of systems utilizing biogas.

Keywords: biogas, exergy, efficiency, optimization

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Authors: Si-Jie Ji, Santhanamoorthi Nachimuthu, Jyh-Chiang Jiang

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With the rapid development of industrialization and urbanization, air pollution poses significant global environmental challenges, contributing to acid rain, global warming, and adverse health effects. Therefore, it is necessary to monitor the concentration of toxic gases in the atmospheric environment in real-time and to deploy cost-effective gas sensors capable of detecting their emissions. In this study, we systematically investigated the sensing capabilities of the two-dimensional MoSe₂ for seven key environmental gases (NO, NO₂, CO, CO₂, SO₂, SO₃, and O₂) using density functional theory (DFT) and non-equilibrium Green’s function (NEGF) calculations. We also investigated the impact of H₂O as an interfering gas. Our results indicate that the MoSe₂ monolayer is thermodynamically stable and exhibits strong gas-sensing capabilities. The calculated adsorption energies indicate that these gases can stably adsorb on MoSe₂, with SO₃ exhibiting the strongest adsorption energy (-0.63 eV). Electronic structure analysis, including projected density of states (PDOS) and Bader charge analysis, demonstrates significant changes in the electronic properties of MoSe₂ upon gas adsorption, affecting its conductivity and sensing performance. We find that oxygen (O₂) adsorption notably influenced the deformation of MoSe₂. To comprehensively understand the potential of MoSe₂ as a gas sensor, we used the NEGF method to assess the electronic transport properties of MoSe₂ under gas adsorption, evaluating current-voltage (I-V), resistance-voltage (R-V) characteristics, and transmission spectra to determine sensitivity, selectivity, and recovery time compared to pristine MoSe₂. Sensitivity, selectivity, and recovery time are analyzed at a bias voltage of 1.7V, showing excellent performance of MoSe₂ in detecting SO₃, among other gases. The pronounced changes in electronic transport behavior induced by SO₃ adsorption confirm MoSe₂’s strong potential as a high-performance gas-sensing material. Overall, this theoretical study provides new insights into the development of high-performance gas sensors, demonstrating the potential of MoSe₂ as a gas-sensing material, particularly for gases like SO₃.

Keywords: density functional theory, gas sensing, MoSe₂, non-equilibrium Green’s function, SO

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Authors: Bendes Ákos

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Digital evidence will be the most widely used type of evidence in the future. With the development of the modern world, more and more new types of crimes have evolved and transformed. For this reason, it is extremely important to examine these types of crimes in order to get a comprehensive picture of them, with which we can help the authorities work. In 1865, with early technologies, people were able to forge a picture of a quality that is not even recognized today. With the help of today's technology, authorities receive a lot of false evidence. Officials are not able to process such a large amount of data, nor do they have the necessary technical knowledge to get a real picture of the authenticity of the given evidence. The digital world has many dangers. Unfortunately, we live in an age where we must protect everything digitally: our phones, our computers, our cars, and all the smart devices that are present in our personal lives and this is not only a burden on us, since companies, state and public utilities institutions are also forced to do so. The training of specialists and experts is essential so that the authorities can manage the incoming digital evidence at some level. When analyzing evidence, it is important to be able to examine it from the moment it is created. Establishing authenticity is a very important issue during official procedures. After the proper acquisition of the evidence, it is essential to store it safely and use it professionally. After the proper acquisition of the evidence, it is essential to store it safely and use it professionally. Otherwise, they will not have sufficient probative value and in case of doubt, the court will always decide in favor of the defendant. One of the most common problems in the world of digital data and evidence is doubt, which is why it is extremely important to examine the above-mentioned problems. The most effective way to avoid digital crimes is to prevent them, for which proper education and knowledge are essential. The aim is to present the dangers inherent in the digital world and the new types of digital crimes. After the comparison of the Hungarian investigative techniques with international practice, modernizing proposals will be given. A sufficiently stable yet flexible legislation is needed that can monitor the rapid changes in the world and not regulate afterward but rather provide an appropriate framework. It is also important to be able to distinguish between digital and digitalized evidence, as the degree of probative force differs greatly. The aim of the research is to promote effective international cooperation and uniform legal regulation in the world of digital crimes.

Keywords: digital crime, digital law, cyber crime, international cooperation, new crimes, skepticism

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Authors: Varvara Roubtsova, Mohamed Chekired

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Recent studies on the numerical simulation of geotechnical problems show the importance of considering the soil micro-structure. At this scale, soil is a discrete particle medium where the particles can interact with each other and with water flow under external forces, structure loads or natural events. This paper presents research conducted in a virtual laboratory named SiGran, developed at IREQ (Institut de recherche d’Hydro-Quebec) for the purpose of investigating a broad range of problems encountered in geotechnics. Using Discrete Element Method (DEM), SiGran simulated granular materials directly by applying Newton’s laws to each particle. The water flow was simulated by using Marker and Cell method (MAC) to solve the full form of Navier-Stokes’s equation for non-compressible viscous liquid. In this paper, examples of numerical simulation and their comparisons with real experiments have been selected to show the complexity of geotechnical research at the micro level. These examples describe transient flows into a porous medium, interaction of particles in a viscous flow, compacting of saturated and unsaturated soils and the phenomenon of liquefaction under seismic load. They also provide an opportunity to present SiGran’s capacity to compute the distribution and evolution of energy by type (particle kinetic energy, particle internal elastic energy, energy dissipated by friction or as a result of viscous interaction into flow, and so on). This work also includes the first attempts to apply micro discrete results on a macro continuum level where the Smoothed Particle Hydrodynamics (SPH) method was used to resolve the system of governing equations. The material behavior equation is based on the results of simulations carried out at a micro level. The possibility of combining three methods (DEM, MAC and SPH) is discussed.

Keywords: discrete element method, marker and cell method, numerical simulation, multi-scale simulations, smoothed particle hydrodynamics

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Authors: Jordan Gallant

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In the compound word processing literature, much attention has been paid to the relationship between a compound’s denotational meaning and that of its morphological whole-word constituents, which is referred to as ‘semantic transparency’. However, the parallel relationship between a compound’s connotation and that of its constituents has not been addressed at all. For instance, while a compound like ‘painkiller’ might be semantically transparent, it is not ‘affectively transparent’. That is, both constituents have primarily negative connotations, while the whole compound has a positive one. This paper investigates the role of affective transparency on compound processing using two methodologies commonly employed in this field: a lexical decision task and a typing task. The critical stimuli used were 112 English bi-constituent compounds that differed in terms of the effective transparency of their constituents. Of these, 36 stimuli contained constituents with similar connotations to the compound (e.g., ‘dreamland’), 36 contained constituents with more positive connotations (e.g. ‘bedpan’), and 36 contained constituents with more negative connotations (e.g. ‘painkiller’). Connotation of whole-word constituents and compounds were operationalized via valence ratings taken from an off-line ratings database. In Experiment 1, compound stimuli and matched non-word controls were presented visually to participants, who were then asked to indicate whether it was a real word in English. Response times and accuracy were recorded. In Experiment 2, participants typed compound stimuli presented to them visually. Individual keystroke response times and typing accuracy were recorded. The results of both experiments provided positive evidence that compound processing is influenced by effective transparency. In Experiment 1, compounds in which both constituents had more negative connotations than the compound itself were responded to significantly more slowly than compounds in which the constituents had similar or more positive connotations. Typed responses from Experiment 2 showed that inter-keystroke intervals at the morphological constituent boundary were significantly longer when the connotation of the head constituent was either more positive or more negative than that of the compound. The interpretation of this finding is discussed in the context of previous compound typing research. Taken together, these findings suggest that affective transparency plays a role in the recognition, storage, and production of English compound words. This study provides a promising first step in a new direction for research on compound words.

Keywords: compound processing, semantic transparency, typed production, valence

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Authors: Alfredo Fortunato, Carmelofrancesco Origlia, Sara Laurita, Rossella Nicoletti

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In the post-pandemic recovery phase of tourism, the role of a Destination Management Organization (DMO) as a coordinated management system of all the elements that make up a destination (attractions, access, marketing, human resources, brand, pricing, etc.) is also becoming relevant for local territories. The objective of a DMO is to maximize the visitor's perception of value and quality while ensuring the competitiveness and sustainability of the destination, as well as the long-term preservation of its natural and cultural assets, and to catalyze benefits for the local economy and residents. In carrying out the multiple functions to which it is called, the DMO can leverage a collective intelligence that comes from the ability to pool information, explicit and tacit knowledge, and relationships of the various stakeholders: policymakers, public managers and officials, entrepreneurs in the tourism supply chain, researchers, data journalists, schools, associations and committees, citizens, etc. The DMO potentially has at its disposal large volumes of data and many of them at low cost, that need to be properly processed to produce value. Based on these assumptions, the paper presents a conceptual framework for building an information system to support the DMO in the intelligent management of a tourist destination tested in an area of southern Italy. The approach adopted is data-informed and consists of four phases: (1) formulation of the knowledge problem (analysis of policy documents and industry reports; focus groups and co-design with stakeholders; definition of information needs and key questions); (2) research and metadatation of relevant sources (reconnaissance of official sources, administrative archives and internal DMO sources); (3) gap analysis and identification of unconventional information sources (evaluation of traditional sources with respect to the level of consistency with information needs, the freshness of information and granularity of data; enrichment of the information base by identifying and studying web sources such as Wikipedia, Google Trends, Booking.com, Tripadvisor, websites of accommodation facilities and online newspapers); (4) definition of the set of indicators and construction of the information base (specific definition of indicators and procedures for data acquisition, transformation, and analysis). The framework derived consists of 6 thematic areas (accommodation supply, cultural heritage, flows, value, sustainability, and enabling factors), each of which is divided into three domains that gather a specific information need to be represented by a scheme of questions to be answered through the analysis of available indicators. The framework is characterized by a high degree of flexibility in the European context, given that it can be customized for each destination by adapting the part related to internal sources. Application to the case study led to the creation of a decision support system that allows: •integration of data from heterogeneous sources, including through the execution of automated web crawling procedures for data ingestion of social and web information; •reading and interpretation of data and metadata through guided navigation paths in the key of digital story-telling; •implementation of complex analysis capabilities through the use of data mining algorithms such as for the prediction of tourist flows.

Keywords: collective intelligence, data framework, destination management, smart tourism

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Authors: Lily Ingsrisawang, Tasanee Nacharoen

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Introduction: The problems of unbalanced data sets generally appear in real world applications. Due to unequal class distribution, many research papers found that the performance of existing classifier tends to be biased towards the majority class. The k -nearest neighbors’ nonparametric discriminant analysis is one method that was proposed for classifying unbalanced classes with good performance. Hence, the methods of discriminant analysis are of interest to us in investigating misclassification error rates for class-imbalanced data of three diabetes risk groups. Objective: The purpose of this study was to compare the classification performance between parametric discriminant analysis and nonparametric discriminant analysis in a three-class classification application of class-imbalanced data of diabetes risk groups. Methods: Data from a healthy project for 599 staffs in a government hospital in Bangkok were obtained for the classification problem. The staffs were diagnosed into one of three diabetes risk groups: non-risk (90%), risk (5%), and diabetic (5%). The original data along with the variables; diabetes risk group, age, gender, cholesterol, and BMI was analyzed and bootstrapped up to 50 and 100 samples, 599 observations per sample, for additional estimation of misclassification error rate. Each data set was explored for the departure of multivariate normality and the equality of covariance matrices of the three risk groups. Both the original data and the bootstrap samples show non-normality and unequal covariance matrices. The parametric linear discriminant function, quadratic discriminant function, and the nonparametric k-nearest neighbors’ discriminant function were performed over 50 and 100 bootstrap samples and applied to the original data. In finding the optimal classification rule, the choices of prior probabilities were set up for both equal proportions (0.33: 0.33: 0.33) and unequal proportions with three choices of (0.90:0.05:0.05), (0.80: 0.10: 0.10) or (0.70, 0.15, 0.15). Results: The results from 50 and 100 bootstrap samples indicated that the k-nearest neighbors approach when k = 3 or k = 4 and the prior probabilities of {non-risk:risk:diabetic} as {0.90:0.05:0.05} or {0.80:0.10:0.10} gave the smallest error rate of misclassification. Conclusion: The k-nearest neighbors approach would be suggested for classifying a three-class-imbalanced data of diabetes risk groups.

Keywords: error rate, bootstrap, diabetes risk groups, k-nearest neighbors

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Authors: Rachel Goh, Alexander McNab, Brent Alsop, David O'Hare

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In a busy airport, the decision whether to take passengers aside and search their luggage for dangerous items can have important consequences. If an officer fails to search and stop a bag containing a dangerous object, a life-threatening incident might occur. But stopping a bag unnecessarily means that the officer might lose time searching the bag and face an angry passenger. Passengers’ bags, however, are often cluttered with personal belongings of varying shapes and sizes. It can be difficult to determine what is dangerous or not, especially if the decisions must be made quickly in cases of busy flight schedules. Additionally, the decision to search bags is often made with input from the surrounding officers on duty. This scenario raises several questions: 1) Past findings suggest that humans are more reliant on an automated aid when under time pressure in a visual search task, but does this translate to human-human reliance? 2) Are humans more likely to agree with another person if the person is assumed to be an expert or a novice in these ambiguous situations? In the present study, forty-one participants performed a simulated luggage-screening task. They were partnered with an advisor of two different statuses (expert vs. novice), but of equal accuracy (90% correct). Participants made two choices each trial: their first choice with no advisor input, and their second choice after advisor input. The second choice was made within either 2 seconds or 8 seconds; failure to do so resulted in a long time-out period. Under the 2-second time pressure, participants were more likely to disagree with their own first choice and agree with the expert advisor, regardless of whether the expert was right or wrong, but especially when the expert suggested that the bag was safe. The findings indicate a tendency for people to assume less responsibility for their decisions and defer to their partner, especially when a quick decision is required. This over-reliance on others’ opinions might have negative consequences in real life, particularly when relying on fallible human judgments. More awareness is needed regarding how a stressful environment may influence reliance on other’s opinions, and how better techniques are needed to make the best decisions under high stress and time pressure.

Keywords: advisors, decision-making, time pressure, trust

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Authors: Nami Matsumoto

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This study explores the experiences of cross-linguistic medical encounters by patients, and their views of receiving language support therein, with a particular focus on Japanese-English cases. The aim of this study is to investigate the reason for the frequent use of a spouse as a communication mediator from a Japanese perspective, through a comparison with that of English speakers. This study conducts an empirical qualitative analysis of the accounts of informants. A total of 31 informants who have experienced Japanese-English cross-linguistic medical encounters were recruited in Australia and Japan for semi-structured in-depth interviews. A breakdown of informants is 15 English speakers and 16 Japanese speakers. In order to obtain a further insight into collected data, additional interviews were held with 4 Australian doctors who are familiar with using interpreters. This study was approved by the Australian National University Human Research Ethics Committee, and written consent to participate in this study was obtained from all participants. The interviews lasted up to over one hour. They were audio-recorded and subsequently transcribed by the author. Japanese transcriptions were translated into English by the author. An analysis of interview data found that patients value relationship in communication. Particularly, Japanese informants, who have an English-speaking spouse, value trust-based communication interventions by their spouse, regardless of the language proficiency of the spouse. In Australia, health care interpreters are required to abide by the national code of ethics for interpreters. The Code defines the role of an interpreter exclusively to be language rendition and enshrines the tenets of accuracy, confidentiality and professional role boundaries. However, the analysis found that an interpreter who strictly complies with the Code sometimes fails to render the real intentions of the patient and their doctor. Findings from the study suggest that an interpreter should not be detached from the context and should be more engaged in the needs of patients. Their needs are not always communicated by an interpreter when they simply follow a professional code of ethics. The concept of relationship-centred care should be incorporated in the professional practice of health care interpreters.

Keywords: health care, Japanese-English medical encounters, language barriers, trust

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Authors: Pinzhe Zhao

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This study focuses on predicting university students' cheating tendencies using psychological traits and machine learning techniques. Academic dishonesty is a significant issue that compromises the integrity and fairness of educational institutions. While much research has been dedicated to detecting cheating behaviors after they have occurred, there is limited work on predicting such tendencies before they manifest. The aim of this research is to develop a model that can identify students who are at higher risk of engaging in academic misconduct, allowing for earlier interventions to prevent such behavior. Psychological factors are known to influence students' likelihood of cheating. Research shows that traits such as test anxiety, moral reasoning, self-efficacy, and achievement motivation are strongly linked to academic dishonesty. High levels of anxiety may lead students to cheat as a way to cope with pressure. Those with lower self-efficacy are less confident in their academic abilities, which can push them toward dishonest behaviors to secure better outcomes. Students with weaker moral judgment may also justify cheating more easily, believing it to be less wrong under certain conditions. Achievement motivation also plays a role, as students driven primarily by external rewards, such as grades, are more likely to cheat compared to those motivated by intrinsic learning goals. In this study, data on students’ psychological traits is collected through validated assessments, including scales for anxiety, moral reasoning, self-efficacy, and motivation. Additional data on academic performance, attendance, and engagement in class are also gathered to create a more comprehensive profile. Using machine learning algorithms such as Random Forest, Support Vector Machines (SVM), and Long Short-Term Memory (LSTM) networks, the research builds models that can predict students’ cheating tendencies. These models are trained and evaluated using metrics like accuracy, precision, recall, and F1 scores to ensure they provide reliable predictions. The findings demonstrate that combining psychological traits with machine learning provides a powerful method for identifying students at risk of cheating. This approach allows for early detection and intervention, enabling educational institutions to take proactive steps in promoting academic integrity. The predictive model can be used to inform targeted interventions, such as counseling for students with high test anxiety or workshops aimed at strengthening moral reasoning. By addressing the underlying factors that contribute to cheating behavior, educational institutions can reduce the occurrence of academic dishonesty and foster a culture of integrity. In conclusion, this research contributes to the growing body of literature on predictive analytics in education. It offers a approach by integrating psychological assessments with machine learning to predict cheating tendencies. This method has the potential to significantly improve how academic institutions address academic dishonesty, shifting the focus from punishment after the fact to prevention before it occurs. By identifying high-risk students and providing them with the necessary support, educators can help maintain the fairness and integrity of the academic environment.

Keywords: academic dishonesty, cheating prediction, intervention strategies, machine learning, psychological traits, academic integrity

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Authors: Biback Das

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New Public Management, a phenomenal tool, which is used to enforcing in public administration in different country’s to enhance the capacities. Since the 1980s, New Public Management (NPM) is primarily focusing to modernize the public sector. From the initial period, many developed countries such as UK, New Zealand, Australia, and the USA are applied in their administration to modernize. Almost 1990s, it has been applied in many developing countries. This study can describe the real situations of NPM based administration. Bangladesh Government has taken many projects to reform the public sector under NPM. Even many Development Agencies like UN, UNDP, World Bank, Asian Development Bank and so on, along with many developed countries also invested and prescribed to take NPM based reform that can to restructure the public sector so that it can maximize the efforts to provide the better service. This study examines using many factors that effects work on Public Administration in Bangladesh and also assessing its endeavor to adopt in it. Although Government has taken such initiatives to implement NPM originated reform, it’s not effectively been implemented to bring positive change about as per NPM objectives. This study mainly examines some initiatives in Bangladesh that have the influence of NPM as well as some drawbacks that can’t help the satisfaction of these initiatives. This article help to identify the efforts of many development agencies providing a fund to enhance the NPM based projects with their specific conditions that are prescribed by them helping to get fund. Therefore, to establish effective public management or to follow NPM model, Bangladesh need having an institutional framework, sound rule of law, proper structure, effective civil service system, appropriate checks, and balances to restructure the public sector help along with donor agencies ad implement in it. Bangladesh Government has applied its recent days to enhance the capabilities in its Public Administration. Moreover, this study mainly identifies how the designing strategies, program formulating, its implementation in various sector such as education, health sector etc. and how to reduce the backdrop the during problem by smooth functioning. This paper is also assessing the influence of many projects like PPP (Public-Private and Partnership) to work along with private organizations for smooth service delivery. Accordingly, this paper briefly reviews how it applies in a global context following the taken many initiatives and the consequences of Bangladesh context.

Keywords: new public management, capacity building, conditionalities, service delivery, public-private-partnership

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Authors: E. Samain, T. Aussenac, D. van Tuinen, S. Selim

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Plant growth promoting rhizobacteria are known as potential biofertilizers and plant resistance inducers. The present work aims to study the durability of the resistance induced as a response to wheat seeds inoculation with PB2 and its influence by Z. tritici strains. The internal and external roots colonization have been determined in vitro, seven days post inoculation, by measuring the colony forming unit (CFU). In planta experimentations were done under controlled conditions included four wheat cultivars with different levels of resistance against Septoria Leaf Blotch (SLB) and four Z. tritici strains with high aggressiveness and resistance levels to fungicides. Plantlets were inoculated with PB2 at sowing and infected with Z. tritici at 3 leaves or tillering growth stages. The infection level with SLB was evaluated at 17 days post inoculation using real-time quantitative polymerase chain reaction (PCR). Results showed that PB2 has a high potential of wheat root external colonization (> 10⁶ CFU/g of root). However, the internal colonization seems to be cultivar dependent. Indeed, PB2 has not been observed as endophytic for one cultivar but has a high level of internal colonization with more than 104 CFU/g of root concerning the three others. Two wheat cultivars (susceptible and moderated resistant) were used to investigate PB2-induced resistance (PB2-IR). After the first infection with Z. tritici, results showed that PB2-IR has conferred a high protection efficiency (40-90%) against SLB in the two tested cultivars. Whereas the PB2-IR was effective against all tested strains with the moderate resistant cultivar, it was higher with the susceptible cultivar (> 64%) but against three of the four tested strains. Concerning the durability of the PB2-IR, after the second infection timing, it has been observed a significant decrease (10-59%) depending strains in the moderate resistant cultivar. Contrarily, the susceptible cultivar showed a stable and high protection level (76-84%) but against three of the four tested strains and interestingly, the strain that overcame PB2-IR was not the same as that of the first infection timing. To conclude, PB2 induces a high and durable resistance against Z. tritici. The PB2-IR is pathogen strain, plant growth stage and genotype dependent. These results may explain the loss of the induced resistance effectiveness under field conditions.

Keywords: induced resistance, Paenibacillus sp. strain B2, wheat genotypes, Zymoseptoria tritici

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Authors: Ahsan Ali, Mayank Ostwal, Nikhil Agarwal

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Abstract—According to a World Bank report, millions of people across the globe still do not have access to improved water services. With uninterrupted growth of cities and urban inhabitants, there is a mounting need to safeguard the sustainable expansion of cities. Efficient functioning of the urban components and high living standards of the residents are needed to be ensured. The water and sanitation network of an urban development is one of its most essential parts of its critical infrastructure. The growth in urban population is leading towards increased water demand, and thus, the local water resources are severely strained. 'Smart water' is referred to water and waste water infrastructure that is able to manage the limited resources and the energy used to transport it. It enables the sustainable consumption of water resources through co-ordinate water management system, by integrating Information Communication Technology (ICT) solutions, intended at maximizing the socioeconomic benefits without compromising the environmental values. This paper presents a case study from a medium sized city in North-western Pakistan. Currently, water is getting contaminated due to the proximity between water and sewer pipelines in the study area, leading to public health issues. Due to unsafe grey water infiltration, the scarce ground water is also getting polluted. This research takes into account the design of smart urban water network by integrating ICT (Information and Communication Technology) with urban water network. The proximity between the existing water supply network and sewage network is analyzed and a design of new water supply system is proposed. Real time mapping of the existing urban utility networks will be projected with the help of GIS applications. The issue of grey water infiltration is addressed by providing sustainable solutions with the help of locally available materials, keeping in mind the economic condition of the area. To deal with the current growth of urban population, it is vital to develop new water resources. Hence, distinctive and cost effective procedures to harness rain water would be suggested as a part of the research study experiment.

Keywords: GIS, smart water, sustainability, urban water management

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Authors: Baljit Soroya

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Transnational communities are as a consequence of greater mobility of people, globalization and digitization have had a major impact on international relations and diasporas in the context of external conflicts. To a significant extent conflicts are becoming deterritorialised and informed by both internal (state politics) and external (foreign policy) players such as in Iraq and Syria leading to forced migration of unprecedented levels within the last two decades. The situation of forced migrants has, it is suggested, worsened as a consequence of the neo-liberal policies and requirements of organizations such as the European Bank. A case example of this being that of Greece, and the exacerbation of insecurity for Greek nationals and the demonization of refugees seeking sanctuary. This has been as a consequence, in part, of the neoliberal dogma of the European Bank. The article analyses the complex intersection of the real and perceived threats of international terrorism and the manner in which UK migration policy and Practice is unfolding. The policy and practice developments are explored in the context of the shift in politics in both the UK and wider Europe to the far right and the drift of main stream political parties to the right. In many cases, the mainstream political groupings, have co-opted the fears as presented by far right organization for political their own political gains, such as in the UK and France In its analysis it will be argued that, whilst international terrorism is an issue of concern, however in the context of the UK it is not of the same scale as the effects of climate change or indeed domestic violence. Given that, the question has to be asked why the threat of international terrorism is having such an impact on UK migration policy and practice and, specifically refugees. Furthermore, it is argued that this policy and practice are being formulated within a narrative that portrays migrants as the problem both in relation to terrorism and the disenfranchisement of ‘ordinary white communities’. The intersectionality of social, economic inequalities, fear of international terrorism, increase in conflicts and the political climate have contributed to a lack of trust of political establishments that have in turn sought to impress the public with their anti-immigrant rhetoric and policy agendas. The article ends by suggesting that whilst politics and political affiliations have become fractured there are nevertheless spaces for collective action, particularly in relation to issues of refugees.

Keywords: international terrorism, migration policy, conflict, media, community, politics

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Authors: Adkham Paiziev, Fikrat Kerimov

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Near Infrared Spectroscopy (NIRS) is one of the biophotonic techniques which can be used to monitor oxygenation and hemodynamics in a variety of human tissues, including skeletal muscle. In the present work, we are offering tissue oximetry (OxyPrem) to measure hemodynamic parameters of skeletal muscles in rest and exercise. Purpose: - To elaborate the new wireless, portable, noninvasive, wearable NIRS device to measure skeletal muscle oxygenation during exercise. - To test this device on brachioradialis muscle of wrestler volunteers by using combined method of arterial occlusion (AO) and NIRS (AO+NIRS). Methods: Oxyprem NIRS device has been used together with AO test. AO test and Isometric brachioradialis muscle contraction experiments have been performed on one group of wrestler volunteers. ‘Accu- Measure’ caliper (USA) to measure skinfold thickness (SFT) has been used. Results: Elaborated device consists on power supply box, a sensor head and installed ‘Tubis’ software for data acquisition and to compute deoxyhemoglobin ([HHb), oxyhemoglobin ([O2Hb]), tissue oxygenation (StO2) and muscle tissue oxygen consumption (mVO2). Sensor head consists on four light sources with three light emitting diodes with nominal wavelengths of 760 nm, 805 nm, and 870 nm, and two detectors. AO and isometric voluntary forearm muscle contraction (IVFMC) on five healthy male subjects (23,2±0.84 in age, 0.43±0.05cm of SFT ) and four female subjects (22.0±1.0 in age and 0.24±0.04 cm SFT) has been measured. mVO2 for control group has been calculated (-0.65%/sec±0.07) for male and -0.69%/±0.19 for female subjects). Tissue oxygenation index for wrestlers in average about 75% whereas for control group StO2 =63%. Second experiment was connected with quality monitoring muscle activity during IVFMC at 10%,30% and 50% of MVC. It has been shown, that the concentration changes of HbO2 and HHb positively correlated to the contraction intensity. Conclusion: We have presented a portable multi-channel wireless NIRS device for real-time monitoring of muscle activity. The miniaturized NIRS sensor and the usage of wireless communication make the whole device have a compact-size, thus can be used in muscle monitoring.

Keywords: skeletal muscle, oxygenation, instrumentation, near infrared spectroscopy

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Authors: Lintang Putra Sadewa, Ilham Prasetya Budhi

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Slope monitoring program has now become a mandatory campaign for any open pit mines around the world to operate safely. Utilizing various slope monitoring instruments and strategies, miners are now able to deliver precise decisions in mitigating the risk of slope failures which can be catastrophic. Currently, the most sophisticated slope monitoring technology available is the Slope Stability Radar (SSR), whichcan measure wall deformation in submillimeter accuracy. One of its eminent features is that SSRcan provide a timely warning by automatically raise an alarm when a predetermined rate-of-movement threshold is reached. However, establishing proper alarm thresholds is arguably one of the onerous challenges faced in any slope monitoring program. The difficulty mainly lies in the number of considerations that must be taken when generating a threshold becausean alarm must be effectivethat it should limit the occurrences of false alarms while alsobeing able to capture any real wall deformations. In this sense, experience shows that a site-specific alarm thresholdtendsto produce more reliable results because it considers site distinctive variables. This study will attempt to determinealarming thresholds for safety-critical monitoring based on an empirical model of slope deformation behaviour that is defined statistically fromdeformation data captured by the Slope Stability Radar (SSR). The study area comprises of upright-dipping highwall setting in a coal mining area with intense mining activities, andthe deformation data used for the study were recorded by the SSR throughout the year 2022. The model is site-specific in nature thus, valuable information extracted from the model (e.g., time-to-failure, onset-of-acceleration, and velocity) will be applicable in setting up site-specific alarm thresholds and will give a clear understanding of how deformation trends evolve over the area.

Keywords: safety-critical monitoring, alarming strategy, slope deformation behaviour model, coal mining

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Authors: Moshe Wasserblat, Jonathan Mamou, Oren Pereg

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Natural Language Processing (NLP) has made a major leap in the last few years, in practical integration into medical solutions; for example, extracting clinical concepts from medical texts such as medical condition, medication, treatment, and symptoms. However, training and deploying those models in real environments still demands a large amount of annotated data and NLP/Machine Learning (ML) expertise, which makes this process costly and time-consuming. We present a practical and efficient method for clinical concept extraction that does not require costly labeled data nor ML expertise. The method includes three steps: Step 1- the user injects a large in-domain text corpus (e.g., PubMed). Then, the system builds a contextual model containing vector representations of concepts in the corpus, in an unsupervised manner (e.g., Phrase2Vec). Step 2- the user provides a seed set of terms representing a specific medical concept (e.g., for the concept of the symptoms, the user may provide: ‘dry mouth,’ ‘itchy skin,’ and ‘blurred vision’). Then, the system matches the seed set against the contextual model and extracts the most semantically similar terms (e.g., additional symptoms). The result is a complete set of terms related to the medical concept. Step 3 –in production, there is a need to extract medical concepts from the unseen medical text. The system extracts key-phrases from the new text, then matches them against the complete set of terms from step 2, and the most semantically similar will be annotated with the same medical concept category. As an example, the seed symptom concepts would result in the following annotation: “The patient complaints on fatigue [symptom], dry skin [symptom], and Weight loss [symptom], which can be an early sign for Diabetes.” Our evaluations show promising results for extracting concepts from medical corpora. The method allows medical analysts to easily and efficiently build taxonomies (in step 2) representing their domain-specific concepts, and automatically annotate a large number of texts (in step 3) for classification/summarization of medical reports.

Keywords: clinical concepts, concept expansion, medical records annotation, medical records summarization

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Authors: Luca Indovina, Carmela Coppola, Carlo Altucci, Riccardo Barberi, Rocco Romano

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In this paper a real court case, held in Italy at the Court of Nola, in which a correct physical description, conducted with both a Monte Carlo and biophysical analysis, would have been sufficient to arrive at conclusions confirmed by documentary evidence, is considered. This will be an example of how forensic physics can be useful in confirming documentary evidence in order to reach hardly questionable conclusions. This was a libel trial in which the defendant, Mr. DS (Defendant for Slander), had falsely accused one of his neighbors, Mr. OP (Offended Person), of having caused him some damages. The damages would have been caused by an external plaster piece that would have detached from the neighbor’s property and would have hit Mr DS while he was in his garden, much more than a meter far away from the facade of the building from which the plaster piece would have detached. In the trial, Mr. DS claimed to have suffered a scratch on his forehead, but he never showed the plaster that had hit him, nor was able to tell from where the plaster would have arrived. Furthermore, Mr. DS presented a medical certificate with a diagnosis of contusion of the cerebral cortex. On the contrary, the images of Mr. OP’s security cameras do not show any movement in the garden of Mr. DS in a long interval of time (about 2 hours) around the time of the alleged accident, nor do they show any people entering or coming out from the house of Mr. DS in the same interval of time. Biophysical analysis shows that both the diagnosis of the medical certificate and the wound declared by the defendant, already in conflict with each other, are not compatible with the fall of external plaster pieces too small to be found. The wind was at a level 1 of the Beaufort scale, that is, unable to raise even dust (level 4 of the Beaufort scale). Therefore, the motion of the plaster pieces can be described as a projectile motion, whereas collisions with the building cornice can be treated using Newtons law of coefficients of restitution. Numerous numerical Monte Carlo simulations show that the pieces of plaster would not have been able to reach even the garden of Mr. DS, let alone a distance over 1.30 meters. Results agree with the documentary evidence (images of Mr. OP’s security cameras) that Mr. DS could not have been hit by plaster pieces coming from Mr. OP’s property.

Keywords: biophysics analysis, Monte Carlo simulations, Newton’s law of restitution, projectile motion

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