Search results for: intelligent classification

Authors: David Broussard

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This review article delves into the realm of marine conservation finance, addressing the inadequacies in current financial streams from the private sector and the underutilization of existing financing mechanisms. The study emphasizes the emerging field of “blue finance”, which contributes to economic growth, improved livelihoods, and marine ecosystem health. The financial burden of marine conservation projects typically falls on philanthropists and governments, contrary to the polluter-pays principle. However, the private sector’s increasing commitment to NetZero and growing environmental and social responsibility goals prompts the need for alternative funding sources for marine conservation initiatives like marine protected areas. The article explores the potential of utilizing several financing mechanisms like carbon credits and other forms of payment for ecosystem services in the marine context, providing a solution to the lack of private funding for marine conservation. The methodology employed involves a systematic and quantitative approach, combining traditional review methods and elements of meta-analysis. A comprehensive search of the years 2000 - 2023, using relevant keywords on the Scopus platform, resulted in a review of 252 articles. The temporal evolution of blue finance studies reveals a significant increase in annual articles from 2010 to 2022, with notable peaks in 2011 and 2022. Marine Policy, Ecosystem Services, and Frontiers in Marine Science are prominent journals in this field. While the majority of articles focus on payment for ecosystem services, there is a growing awareness of the need for holistic approaches in conservation finance. Utilizing bibliometric techniques, the article showcases the dominant share of payment for ecosystem services in the literature with a focus on blue carbon. The classification of articles based on various criteria, including financing mechanisms and conservation types, aids in categorizing and understanding the diversity of research objectives and perspectives in this complex field of marine conservation finance.

Keywords: biodiversity offsets, carbon credits, ecosystem services, impact investment, payment for ecosystem services

Procedia PDF Downloads 55

Authors: Ladda Her, Juntip Kanjanasilp, Ratree Sawangjit, Nathorn Chaiyakunapruk

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Cough is the common symptom of the respiratory tract infections or non-infections; the duration of cough indicates a classification and severity of disease. Herbal medicines can be used as the alternative to drugs for relief of cough symptoms from acute and chronic disease. Eucalyptus was used for reducing cough with evidences suggesting it has an active role in reduction of airway inflammation. The present study aims to evaluate efficacy and safety of eucalyptus for relief of cough symptom in respiratory disease. Method: The Cochrane Library, MEDLINE (PubMed), Scopus, CINAHL, Springer, Science direct, ProQuest, and THAILIS databases. From its inception until 01/02/2019 for randomized control trials. We follow for the efficacy and safety of eucalyptus for reducing cough. Methodological quality was evaluated by using the Cochrane risk of bias tool; two reviewers in our team screened eligibility and extracted data. Result: Six studies were included for the review and five studies were included in the meta-analysis, there were 1.911 persons including children (n: 1) and adult (n: 5) studies; for study in children and adult were between 1 and 80 years old, respectively. Eucalyptus was used as mono herb (n: 2) and in combination with other herbs form (n: 4). All of the studies with eucalyptus were compared for efficacy and safety with placebo or standard treatment, Eucalyptus dosage form in studies included capsules, spray, and syrup. Heterogeneity was 32.44 used random effect model (I² = 1.2%, χ² = 1.01; P-value = 0.314). The efficacy of eucalyptus was showed a reduced cough symptom statistically significant (n = 402, RR: 1.40, 95%CI [1.19, 1.65], P-value < 0.0001) when compared with placebo. Adverse events (AEs) were reported mild to moderate intensity with mostly gastrointestinal symptom. The methodological quality of the included trials was overall poor. Conclusion: Eucalyptus appears to be beneficial and safe for relieving in respiratory diseases focus on cough frequency. The evidence was inconclusive due to limited quality trial. Well-designed trials for evaluating the effectiveness in humans, the effectiveness for reducing cough symptom in human is needed. Eucalyptus had safety as monotherapy or in combination with other herbs.

Keywords: cough, eucalyptus, cineole, herbal medicine, systematic review, meta-analysis

Procedia PDF Downloads 133

Authors: Joseph Falzon, Margaret Nelson

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Background: Regeneration and re-use of abandoned historic buildings present a continuous challenge for policy makers and stakeholders in the tourism and leisure industry. Obsolete historic buildings provide great potential for tourism and leisure accommodation, presenting unique heritage experiences to travellers and host communities. Contemporary demands in the hospitality industry continuously require higher standards, some of which are in conflict with heritage conservation principles. Objective: The aim of this research paper is to critically discuss regeneration policies with stakeholders of the tourism and leisure industry and to examine current practices in policy development and the resultant impact of policies on the Maltese tourism and leisure industry. Research Design: Six semi-structured interviews with stakeholders involved in the tourism and leisure industry participated in the research. A number of measures were taken to reduce bias and thus improve trustworthiness. Clear statements of the purpose of the research study were provided at the start of each interview to reduce expectancy bias. The interviews were semi-structured to minimise interviewer bias. Interviewees were allowed to expand and elaborate as necessary, with only necessary probing questions, to allow free expression of opinion and practices. Interview guide was submitted to participants at least two weeks before the interview to allow participants to prepare for the interview and prevent recall bias during the interview as much as possible. Interview questions and probes contained both positive and negative aspects to prevent interviewer bias. Policy documents were available during the interview to prevent recall bias. Interview recordings were transcribed ‘intelligent’ verbatim. Analysis was carried out using thematic analysis with the coding frame developed independently by two researchers. All phases of the study were governed by research ethics. Findings: Findings were grouped in main themes: financing of regeneration, governance, legislation and policies. Other key issues included value of historic buildings and approaches for regeneration. Whist regeneration of historic buildings was noted, participants discussed a number of barriers that hindered regeneration. Stakeholders identified gaps in policies and gaps at policy implementation stages. European Union funding policies facilitated regeneration initiatives but funding criteria based on economic deliverables presented the intangible heritage gap. Stakeholders identified niche markets for heritage tourism accommodation. Lack of research-based policies was also identified. Conclusion: Potential of regeneration is hindered by inadequate legal framework that supports contemporary needs of the tourism industry. Policies should be developed by active stakeholder participation. Adequate funding schemes have to support the tangible and intangible components of the built heritage.

Keywords: governance, historic buildings, policy, tourism

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Authors: Camille Van Eupen, Dirk Maes, Marc Herremans, Kristijn R. R. Swinnen, Ben Somers, Stijn Luca

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In ecology, species distribution models are commonly implemented to study species-environment relationships. These models increasingly rely on opportunistic citizen science data when high-quality species records collected through standardized recording protocols are unavailable. While these opportunistic data are abundant, uncertainty is usually high, e.g., due to observer effects or a lack of metadata. Data quality filtering is often used to reduce these types of uncertainty in an attempt to increase the value of studies relying on opportunistic data. However, filtering should not be performed blindly. In this study, recommendations are built for data quality filtering of opportunistic species occurrence data that are used as input for species distribution models. Using an extensive database of 5.7 million citizen science records from 255 species in Flanders, the impact on model performance was quantified by applying three data quality filters, and these results were linked to species traits. More specifically, presence records were filtered based on record attributes that provide information on the observation process or post-entry data validation, and changes in the area under the receiver operating characteristic (AUC), sensitivity, and specificity were analyzed using the Maxent algorithm with and without filtering. Controlling for sample size enabled us to study the combined impact of data quality filtering, i.e., the simultaneous impact of an increase in data quality and a decrease in sample size. Further, the variation among species in their response to data quality filtering was explored by clustering species based on four traits often related to data quality: commonness, popularity, difficulty, and body size. Findings show that model performance is affected by i) the quality of the filtered data, ii) the proportional reduction in sample size caused by filtering and the remaining absolute sample size, and iii) a species ‘quality profile’, resulting from a species classification based on the four traits related to data quality. The findings resulted in recommendations on when and how to filter volunteer generated and opportunistically collected data. This study confirms that correctly processed citizen science data can make a valuable contribution to ecological research and species conservation.

Keywords: citizen science, data quality filtering, species distribution models, trait profiles

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Authors: Onyekachi Onwudike, Russell Lock, Iain Phillips

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The variability that exists across governments, her departments and the provisioning of services has been areas of concern in the E-Government domain. There is a need for reuse and integration across government departments which are accompanied by varying degrees of risks and threats. There is also the need for assessment, prevention, preparation, response and recovery when dealing with these risks or threats. The ability of a government to cope with the emerging changes that occur within it is known as resilience. In order to forge ahead with concerted efforts to manage reuse and integration induced risks or threats to governments, the ambiguities contained within resilience must be addressed. Enhancing resilience in the E-Government domain is synonymous with reducing risks governments face with provisioning of services as well as reuse of components across departments. Therefore, it can be said that resilience is responsible for the reduction in government’s vulnerability to changes. In this paper, we present the use of the ontology to measure the resilience of governments. This ontology is made up of a well-defined construct for the taxonomy of resilience. A specific class known as ‘Resilience Requirements’ is added to the ontology. This class embraces the concept of resilience into the E-Government domain ontology. Considering that the E-Government domain is a highly complex one made up of different departments offering different services, the reliability and resilience of the E-Government domain have become more complex and critical to understand. We present questions that can help a government access how prepared they are in the face of risks and what steps can be taken to recover from them. These questions can be asked with the use of queries. The ontology focuses on developing a case study section that is used to explore ways in which government departments can become resilient to the different kinds of risks and threats they may face. A collection of resilience tools and resources have been developed in our ontology to encourage governments to take steps to prepare for emergencies and risks that a government may face with the integration of departments and reuse of components across government departments. To achieve this, the ontology has been extended by rules. We present two tools for understanding resilience in the E-Government domain as a risk analysis target and the output of these tools when applied to resilience in the E-Government domain. We introduce the classification of resilience using the defined taxonomy and modelling of existent relationships based on the defined taxonomy. The ontology is constructed on formal theory and it provides a semantic reference framework for the concept of resilience. Key terms which fall under the purview of resilience with respect to E-Governments are defined. Terms are made explicit and the relationships that exist between risks and resilience are made explicit. The overall aim of the ontology is to use it within standards that would be followed by all governments for government-based resilience measures.

Keywords: E-Government, Ontology, Relationships, Resilience, Risks, Threats

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Authors: José Manuel Palma, Paula Pereira, Margarida Tomás

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Foreseen the future: Human factors integration in European Horizon Projects The development of new technology as artificial intelligence, smart sensing, robotics, cobotics or intelligent machinery must integrate human factors to address the need to optimize systems and processes, thereby contributing to the creation of a safe and accident-free work environment. Human Factors Integration (HFI) consistently pose a challenge for organizations when applied to daily operations. AGILEHAND and FORTIS projects are grounded in the development of cutting-edge technology - industry 4.0 and 5.0. AGILEHAND aims to create advanced technologies for autonomously sort, handle, and package soft and deformable products, whereas FORTIS focuses on developing a comprehensive Human-Robot Interaction (HRI) solution. Both projects employ different approaches to explore HFI. AGILEHAND is mainly empirical, involving a comparison between the current and future work conditions reality, coupled with an understanding of best practices and the enhancement of safety aspects, primarily through management. FORTIS applies HFI throughout the project, developing a human-centric approach that includes understanding human behavior, perceiving activities, and facilitating contextual human-robot information exchange. it intervention is holistic, merging technology with the physical and social contexts, based on a total safety culture model. In AGILEHAND we will identify safety emergent risks, challenges, their causes and how to overcome them by resorting to interviews, questionnaires, literature review and case studies. Findings and results will be presented in “Strategies for Workers’ Skills Development, Health and Safety, Communication and Engagement” Handbook. The FORTIS project will implement continuous monitoring and guidance of activities, with a critical focus on early detection and elimination (or mitigation) of risks associated with the new technology, as well as guidance to adhere correctly with European Union safety and privacy regulations, ensuring HFI, thereby contributing to an optimized safe work environment. To achieve this, we will embed safety by design, and apply questionnaires, perform site visits, provide risk assessments, and closely track progress while suggesting and recommending best practices. The outcomes of these measures will be compiled in the project deliverable titled “Human Safety and Privacy Measures”. These projects received funding from European Union’s Horizon 2020/Horizon Europe research and innovation program under grant agreement No101092043 (AGILEHAND) and No 101135707 (FORTIS).

Keywords: human factors integration, automation, digitalization, human robot interaction, industry 4.0 and 5.0

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Authors: Kambiz Rasoulkhani, Jeanne Cole, Sybil Sharvelle, Ali Mostafavi

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Dual water distribution systems have been proposed as solutions to enhance the sustainability and resilience of urban water systems by improving performance and decreasing energy consumption. The objective of this study was to evaluate the long-term resilience and robustness of dual water distribution systems versus singular water distribution systems under various stressors such as demand fluctuation, aging infrastructure, and funding constraints. To this end, the long-term dynamics of these infrastructure systems was captured using a simulation model that integrates institutional agency decision-making processes with physical infrastructure degradation to evaluate the long-term transformation of water infrastructure. A set of model parameters that varies for dual and singular distribution infrastructure based on the system attributes, such as pipes length and material, energy intensity, water demand, water price, average pressure and flow rate, as well as operational expenditures, were considered and input in the simulation model. Accordingly, the model was used to simulate various scenarios of demand changes, funding levels, water price growth, and renewal strategies. The long-term resilience and robustness of each distribution infrastructure were evaluated based on various performance measures including network average condition, break frequency, network leakage, and energy use. An ecologically-based resilience approach was used to examine regime shifts and tipping points in the long-term performance of the systems under different stressors. Also, Classification and Regression Tree analysis was adopted to assess the robustness of each system under various scenarios. Using data from the City of Fort Collins, the long-term resilience and robustness of the dual and singular water distribution systems were evaluated over a 100-year analysis horizon for various scenarios. The results of the analysis enabled: (i) comparison between dual and singular water distribution systems in terms of long-term performance, resilience, and robustness; (ii) identification of renewal strategies and decision factors that enhance the long-term resiliency and robustness of dual and singular water distribution systems under different stressors.

Keywords: complex systems, dual water distribution systems, long-term resilience performance, multi-agent modeling, sustainable and resilient water systems

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Authors: Faith Eweluegim Enahoro-Ofagbe, Alika Eke Joseph

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Information on genetic variation within a population is crucial for utilizing heterozygosity for breeding programs that aim to improve crop species. The study was conducted to ascertain the genotypic similarities among twelve sugarcane (Saccharum officinarum) varieties to group them for purposes of hybridizations for cane yield improvement. The experiment was conducted at the University of Benin, Faculty of Agriculture Teaching and Research Farm, Benin City. Twelve sugarcane varieties obtained from National Cereals Research Institute, Badeggi, Niger State, Nigeria, were planted in three replications in a randomized complete block design. Each variety was planted on a five-row plot of 5.0 m in length. Data were collected on 12 agronomic traits, including; the number of millable cane, cane girth, internode length, number of male and female flowers (fuss), days to flag leaf, days to flowering, brix%, cane yield, and others. There were significant differences, according to the findings among the twelve genotypes for the number of days to flag leaf, number of male and female flowers (fuss), and cane yield. The relationship between the twelve sugarcane varieties was expressed using hierarchical cluster analysis. The twelve genotypes were grouped into three major clusters based on hierarchical classification. Cluster I had five genotypes, cluster II had four, and cluster III had three. Cluster III was dominated by varieties characterized by higher cane yield, number of leaves, internode length, brix%, number of millable stalks, stalk/stool, cane girth, and cane length. Cluster II contained genotypes with early maturity characteristics, such as early flowering, early flag leaf development, growth rate, and the number of female and male flowers (fuss). The maximum inter-cluster distance between clusters III and I indicated higher genetic diversity between the two groups. Hybridization between the two groups could result in transgressive recombinants for agronomically important traits.

Keywords: sugarcane, Saccharum officinarum, genotype, cluster analysis, principal components analysis

Procedia PDF Downloads 63

Authors: Faruk Ortes, Derya Karabulut, Yunus Ziya Arslan

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Myoelectric features gathering from musculature environment are considered on a preferential basis to perceive muscle activation and control human arm prostheses according to recent experimental researches. EMG (electromyography) signal based human arm prostheses have shown a promising performance in terms of providing basic functional requirements of motions for the amputated people in recent years. However, these assistive devices for neurorehabilitation still have important limitations in enabling amputated people to perform rather sophisticated or functional movements. Surface electromyogram (EMG) is used as the control signal to command such devices. This kind of control consists of activating a motion in prosthetic arm using muscle activation for the same particular motion. Extraction of clear and certain neural information from EMG signals plays a major role especially in fine control of hand prosthesis movements. Many signal processing methods have been utilized for feature extraction from EMG signals. The specific objective of this study was to compare widely used time domain features of EMG signal including integrated EMG(IEMG), root mean square (RMS) and waveform length(WL) for prediction of externally applied forces to human hands. Obtained features were classified using artificial neural networks (ANN) to predict the forces. EMG signals supplied to process were recorded during only type of muscle contraction which is isometric and isotonic one. Experiments were performed by three healthy subjects who are right-handed and in a range of 25-35 year-old aging. EMG signals were collected from muscles of the proximal part of the upper body consisting of: biceps brachii, triceps brachii, pectorialis major and trapezius. The force prediction results obtained from the ANN were statistically analyzed and merits and pitfalls of the extracted features were discussed with detail. The obtained results are anticipated to contribute classification process of EMG signal and motion control of powered human arm prosthetics control.

Keywords: assistive devices for neurorehabilitation, electromyography, feature extraction, force estimation, human arm prosthesis

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Authors: Ahmed AlNouss, Salim Ahmed

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Process control refers to the techniques to control the variables in a process in order to maintain them at their desired values. Advanced process control (APC) is a broad term within the domain of control where it refers to different kinds of process control and control related tools, for example, model predictive control (MPC), statistical process control (SPC), fault detection and classification (FDC) and performance assessment. APC is often used for solving multivariable control problems and model predictive control (MPC) is one of only a few advanced control methods used successfully in industrial control applications. Advanced control is expected to bring many benefits to the plant operation; however, the extent of the benefits is plant specific and the application needs a large investment. This requires an analysis of the expected benefits before the implementation of the control. In a real plant simulation studies are carried out along with some experimentation to determine the improvement in the performance of the plant due to advanced control. In this research, such an exercise is undertaken to realize the needs of APC application. The main objectives of the paper are as follows: (1) To apply MPC to a number of simulations set up to realize the need of MPC by comparing its performance with that of proportional integral derivatives (PID) controllers. (2) To study the effect of controller parameters on control performance. (3) To develop appropriate performance index (PI) to compare the performance of different controller and develop novel idea to present tuning map of a controller. These objectives were achieved by applying PID controller and a special type of MPC which is dynamic matrix control (DMC) on the multi-tanks process simulated in loop-pro. Then the controller performance has been evaluated by changing the controller parameters. This performance was based on special indices related to the difference between set point and process variable in order to compare the both controllers. The same principle was applied for continuous stirred tank heater (CSTH) and continuous stirred tank reactor (CSTR) processes simulated in Matlab. However, in these processes some developed programs were written to evaluate the performance of the PID and MPC controllers. Finally these performance indices along with their controller parameters were plotted using special program called Sigmaplot. As a result, the improvement in the performance of the control loops was quantified using relevant indices to justify the need and importance of advanced process control. Also, it has been approved that, by using appropriate indices, predictive controller can improve the performance of the control loop significantly.

Keywords: advanced process control (APC), control loop, model predictive control (MPC), proportional integral derivatives (PID), performance indices (PI)

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Authors: G. Rajapakse, S. Jayasinghe, A. Fleming

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This paper aims to experimentally validate the control strategy used for electrical power converters in grid integrated oscillating water column (OWC) wave energy converter (WEC). The particular OWC’s unidirectional air turbine-generator output power results in discrete large power pulses. Therefore, the system requires power conditioning prior to integrating to the grid. This is achieved by using a back to back power converter with an energy storage system. A Li-Ion battery energy storage is connected to the dc-link of the back-to-back converter using a bidirectional dc-dc converter. This arrangement decouples the system dynamics and mitigates the mismatch between supply and demand powers. All three electrical power converters used in the arrangement are controlled using finite control set-model predictive control (FCS-MPC) strategy. The rectifier controller is to regulate the speed of the turbine at a set rotational speed to uphold the air turbine at a desirable speed range under varying wave conditions. The inverter controller is to maintain the output power to the grid adhering to grid codes. The dc-dc bidirectional converter controller is to set the dc-link voltage at its reference value. The software modeling of the OWC system and FCS-MPC is carried out in the MATLAB/Simulink software using actual data and parameters obtained from a prototype unidirectional air-turbine OWC developed at Australian Maritime College (AMC). The hardware development and experimental validations are being carried out at AMC Electronic laboratory. The designed FCS-MPC for the power converters are separately coded in Code Composer Studio V8 and downloaded into separate Texas Instrument’s TIVA C Series EK-TM4C123GXL Launchpad Evaluation Boards with TM4C123GH6PMI microcontrollers (real-time control processors). Each microcontroller is used to drive 2kW 3-phase STEVAL-IHM028V2 evaluation board with an intelligent power module (STGIPS20C60). The power module consists of a 3-phase inverter bridge with 600V insulated gate bipolar transistors. Delta standard (ASDA-B2 series) servo drive/motor coupled to a 2kW permanent magnet synchronous generator is served as the turbine-generator. This lab-scale setup is used to obtain experimental results. The validation of the FCS-MPC is done by comparing these experimental results to the results obtained by MATLAB/Simulink software results in similar scenarios. The results show that under the proposed control scheme, the regulated variables follow their references accurately. This research confirms that FCS-MPC fits well into the power converter control of the OWC-WEC system with a Li-Ion battery energy storage.

Keywords: dc-dc bidirectional converter, finite control set-model predictive control, Li-ion battery energy storage, oscillating water column, wave energy converter

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Authors: Andrea Gatti, Federica Coppotelli, Ma Primavera, Laura Palmieri, Umberto Tarantino

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Aim of study: Scientific literature is scarce of studies and reviews valuing the pros and cons of the paratricipital approach for the treatment of humeral shaft fractures; the lateral paratricipital approach is a valid alternative to the classical posterior approach to the humeral shaft as it preserves both the triceps muscle and the elbow extensor mechanisms; based on our experience, this retrospective analysis aims at analyzing outcome, risks and benefits of the lateral paratricipital approach for humeral shaft fractures. Methods: Our study includes 14 patients treated between 2018 and 2019 for unilateral humeral shaft fractures: 13 with a B1 or B2 and a patient with a C fracture type (according to the AO/ATO Classification); 6 of our patients identified as male while 8 as female; age average was 57.8 years old (range 21-73 years old). A lateral paratricipital approach was performed on all 14 patients, sparing the triceps muscle by avoiding the olecranon osteotomy and by assessing the integrity and the preservation of the radial nerve; the humeral shaft fracture osteosynthesis was performed by means of plates and screws. After surgery all patients have started elbow functional rehabilitation with acceptable pain management. Post-operative follow-up has been carried out by assessing radiographs, MEPS (Mayo Elbow Performance Score) and DASH (Disability of Arm Shoulder and Hand) functional assessment and ROM of the affected joint. Results: All 14 patients had an optimal post-operative follow-up with an adequate osteosynthesis and functional rehabilitations by entirely preserving the operated elbow joint; the mean elbow ROM was 0-118.6 degree (range of 0-130) while the average MEPS score was 86 (range75-100) and 79.9 for the DASH (range 21.7-86.1). Just 2 patients suffered of temporary radial nerve apraxia, healed in the subsequent follow-ups. CONCLUSION: The lateral paratricipital approach preserve both the integrity of the triceps muscle and the elbow biomechanism but we do strongly recommend additional studies to be carried out to highlight differences between it and the classical posterior approach in treating humeral shaft fractures.

Keywords: paratricepital approach, humerus shaft fracture, posterior approach humeral shaft, paratricipital postero-lateral approach

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Authors: M. R. Babaei, S. M. Hosseini, S. Rahmani, L. Moradi

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Today, the quality of education and training systems and the effectiveness of the education systems of most concern to stakeholders and decision-makers of our country's development in each country. In Iran this is a double issue of concern to numerous reasons; So that governments, over the past decade have hardly even paid the running costs of education. ICT is claiming it has the power to change the structure of a program for training, reduce costs and increase quality, and do education systems and products consistent with the needs of the community and take steps to practice education. Own of the areas that the introduction of information technology has fundamentally changed is the field of education. The aim of this research is process reengineering management in schools simultaneously has been using field studies to collect data in the form of interviews and a questionnaire survey. The statistical community of this research has been the country of Iran and smart schools under the education. Sampling was targeted. The data collection tool was a questionnaire composed of two parts. The questionnaire consists of 36 questions that each question designates one of effective factors on the management of smart schools. Also each question consists of two parts. The first part designates the operating position in the management process, which represents the domain's belonging to the management agent (planning, organizing, leading, controlling). According to the classification of Dabryn and in second part the factors affect the process of managing the smart schools were examined, that Likert scale is used to classify. Questions the validity of the group of experts and prominent university professors in the fields of information technology, management and reengineering of approved and Cronbach's alpha reliability and also with the use of the formula is evaluated and approved. To analyse the data, descriptive and inferential statistics were used to analyse the factors contributing to the rating of (Linkert scale) descriptive statistics (frequency table data, mean, median, mode) was used. To analyse the data using analysis of variance and nonparametric tests and Friedman test, the assumption was evaluated. The research conclusions show that the factors influencing the management process re-engineering smart schools in school performance is affected.

Keywords: re-engineering, management process, smart school, Iran's school

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Authors: Ebenezer Joseph

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Chess is a useful tool to enhance general and specific cognitive functioning in children. The present study aims to assess the impact of chess on cognitive in children and to measure the differential impact of socio-demographic factors like age and gender of the child on the effectiveness of the chess intervention.This research study used an experimental design to study the impact of the Training in Chess on the intelligence of children. The Pre-test Post-test Control Group Design was utilized. The research design involved two groups of children: an experimental group and a control group. The experimental group consisted of children who participated in the one-year Chess Training Intervention, while the control group participated in extra-curricular activities in school. The main independent variable was training in chess. Other independent variables were gender and age of the child. The dependent variable was the cognitive functioning of the child (as measured by IQ, working memory index, processing speed index, perceptual reasoning index, verbal comprehension index, numerical reasoning, verbal reasoning, non-verbal reasoning, social intelligence, language, conceptual thinking, memory, visual motor and creativity). The sample consisted of 200 children studying in Government and Private schools. Random sampling was utilized. The sample included both boys and girls falling in the age range 6 to 16 years. The experimental group consisted of 100 children (50 from Government schools and 50 from Private schools) with an equal representation of boys and girls. The control group similarly consisted of 100 children. The dependent variables were assessed using Binet-Kamat Test of Intelligence, Wechsler Intelligence Scale for Children - IV (India) and Wallach Kogan Creativity Test. The training methodology comprised Winning Moves Chess Learning Program - Episodes 1–22, lectures with the demonstration board, on-the-board playing and training, chess exercise through workbooks (Chess school 1A, Chess school 2, and tactics) and working with chess software. Further students games were mapped using chess software and the brain patterns of the child were understood. They were taught the ideas behind chess openings and exposure to classical games were also given. The children participated in mock as well as regular tournaments. Preliminary analysis carried out using independent t tests with 50 children indicates that chess training has led to significant increases in the intelligent quotient. Children in the experimental group have shown significant increases in composite scores like working memory and perceptual reasoning. Chess training has significantly enhanced the total creativity scores, line drawing and pattern meaning subscale scores. Systematically learning chess as part of school activities appears to have a broad spectrum of positive outcomes.

Keywords: chess, intelligence, creativity, children

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Authors: Yosep Chong, Yejin Kim, Jingyun Choi, Hwanjo Yu, Eun Jung Lee, Chang Suk Kang

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For the past decades, immunohistochemistry (IHC) has been playing an important role in the diagnosis of human neoplasms, by helping pathologists to make a clearer decision on differential diagnosis, subtyping, personalized treatment plan, and finally prognosis prediction. However, the IHC performed in various tumors of daily practice often shows conflicting and very challenging results to interpret. Even comprehensive diagnosis synthesizing clinical, histologic and immunohistochemical findings can be helpless in some twisted cases. Another important issue is that the IHC data is increasing exponentially and more and more information have to be taken into account. For this reason, we reached an idea to develop an expert supporting system to help pathologists to make a better decision in diagnosing human neoplasms with IHC results. We gave probabilistic decision tree algorithm and tested the algorithm with real case data of lymphoid neoplasms, in which the IHC profile is more important to make a proper diagnosis than other human neoplasms. We designed probabilistic decision tree based on Bayesian theorem, program computational process using MATLAB (The MathWorks, Inc., USA) and prepared IHC profile database (about 104 disease category and 88 IHC antibodies) based on WHO classification by reviewing the literature. The initial probability of each neoplasm was set with the epidemiologic data of lymphoid neoplasm in Korea. With the IHC results of 131 patients sequentially selected, top three presumptive diagnoses for each case were made and compared with the original diagnoses. After the review of the data, 124 out of 131 were used for final analysis. As a result, the presumptive diagnoses were concordant with the original diagnoses in 118 cases (93.7%). The major reason of discordant cases was that the similarity of the IHC profile between two or three different neoplasms. The expert supporting system algorithm presented in this study is in its elementary stage and need more optimization using more advanced technology such as deep-learning with data of real cases, especially in differentiating T-cell lymphomas. Although it needs more refinement, it may be used to aid pathological decision making in future. A further application to determine IHC antibodies for a certain subset of differential diagnoses might be possible in near future.

Keywords: database, expert supporting system, immunohistochemistry, probabilistic decision tree

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Authors: Lilian Bambirra De Assis, Patricia Albuquerque Gomes, Kamila Pagel De Oliveira, Deborah Oliveira Santos, Marcelo Esteves Chaves Campos

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This paper aimed to analyze how performance management occurs in the context of the modernization of the federal public sector in Chile and Portugal. To do so, the study was based on a theoretical framework that covers the modernization of public administration to performance management, passing on people management. The work consisted of qualitative-descriptive research in which 16 semi-structured interviews were applied in the countries of study and documents and legislation were used referring to the subject. Performance management, as well as other people management subsystems, is criticized for using private sector management tools, based on a results-driven logic. From this point of view, it is understood that certain practices of the private sector, regarding the measurement of performance, can not be simply inserted in the scenario of the public administration. Beyond this criticism, performance management can contribute to the achievement of the strategic objectives of the countries and its focus is upward, a trend that can be verified through the manuals produced; by the interest of consultants and professional organizations, both public and private; and OECD (Organization for Economic Cooperation and Development) evaluations. In Portugal, public administration reform was implemented during the Constitutional Government (2005-2009) and had as its objective the restructuring of human resources management, with an emphasis on its integration with budget management, which is an inclination of the OECD, while in Chile HRM (Human Resource Management) practices are directed to ministries to a lesser extent than the OECD average. The central human resources management sector, for the most part, coordinates policy but is also responsible for other issues, including payment and classification systems. Chile makes less use of strategic Human Resource Management practices than the average of OECD countries, and its prominence lies in the decentralization of public bodies, which may grant autonomy, but fragments the implementation of policies and practices in that country since they are not adopted by all organs. Through the analysis, it was possible to identify that Chile and Portugal have practices and personnel management policies that make reference to performance management, which is similar to other OECD countries. The study countries also have limitations to implement performance management and the results indicate that there are still processes to be perfected, such as performance appraisal and compensation.

Keywords: management of people in the public sector, modernization of public administration, performance management in the public sector, HRM, OECD

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Authors: Jemma Porrett

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Background: We present a literature review examining the research surrounding tick paralysis resulting in facial nerve palsy. A case of an intra-aural paralysis tick bite resulting in unilateral facial nerve palsy is also discussed. Methods: A novel case of otoacariasis with associated ipsilateral facial nerve involvement is presented. Additionally, we conducted a review of the literature, and we searched the MEDLINE and EMBASE databases for relevant literature published between 1915 and 2020. Utilising the following keywords; 'Ixodes', 'Facial paralysis', 'Tick bite', and 'Australia', 18 articles were deemed relevant to this study. Results: Eighteen articles included in the review comprised a total of 48 patients. Patients' ages ranged from one year to 84 years of age. Ten studies estimated the possible duration between a tick bite and facial nerve palsy, averaging 8.9 days. Forty-one patients presented with a single tick within the external auditory canal, three had a single tick located on the temple or forehead region, three had post-auricular ticks, and one patient had a remarkable 44 ticks removed from the face, scalp, neck, back, and limbs. A complete ipsilateral facial nerve palsy was present in 45 patients, notably, in 16 patients, this occurred following tick removal. House-Brackmann classification was utilised in 7 patients; four patients with grade 4, one patient with grade three, and two patients with grade 2 facial nerve palsy. Thirty-eight patients had complete recovery of facial palsy. Thirteen studies were analysed for time to recovery, with an average time of 19 days. Six patients had partial recovery at the time of follow-up. One article reported improvement in facial nerve palsy at 24 hours, but no further follow-up was reported. One patient was lost to follow up, and one article failed to mention any resolution of facial nerve palsy. One patient died from respiratory arrest following generalized paralysis. Conclusions: Tick paralysis is a severe but preventable disease. Careful examination of the face, scalp, and external auditory canal should be conducted in patients presenting with otalgia and facial nerve palsy, particularly in tropical areas, to exclude the possibility of tick infestation.

Keywords: facial nerve palsy, tick bite, intra-aural, Australia

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Authors: Murray Matarab Konzang

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Lae Port Development Project, Four Lane Highway and other development in the extraction industry which have direct road link to Lae City are predicted to have significant impact on its road network system. This paper evaluates Lae roads improvement program with forecast on planning, economic and the installation of bypasses to ease congestion, effective and convenient transport service for bulk goods and reduce travel time. Land-use transportation study and plans for local area traffic management scheme will be considered. City roads are faced with increased number of traffic and some inadequate road pavement width, poor transport plans, and facilities to meet this transportation demand. Lae also has drainage system which might not hold a 100 year flood. Proper evaluation, plan, design and intersection analysis is needed to evaluate road network system thus recommend improvement and estimate future growth. Repetitive and cyclic loading by heavy commercial vehicles with different axle configurations apply on the flexible pavement which weakens and tear the pavement surface thus small cracks occur. Rain water seeps through and overtime it creates potholes. Effective planning starts from experimental research and appropriate design standards to enable firm embankment, proper drains and quality pavement material. This paper will address traffic problems as well as road pavement, capacities of intersections, and pedestrian flow during peak hours. The outcome of this research will be to identify heavily trafficked road sections and recommend treatments to reduce traffic congestions, road classification, and proposal for bypass routes and improvement. First part of this study will describe transport or traffic related problems within the city. Second part would be to identify challenges imposed by traffic and road related problems and thirdly to recommend solutions after the analyzing traffic data that will indicate current capacities of road intersections and finally recommended treatment for improvement and future growth.

Keywords: Lae, road network, highway, vehicle traffic, planning

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Authors: Ella Tyuryumina, Alexey Neznanov

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This paper is devoted to mathematical modelling of the progression and stages of breast cancer. We propose Consolidated mathematical growth model of primary tumor and secondary distant metastases growth in patients with lymph nodes metastases (CoM-III) as a new research tool. We are interested in: 1) modelling the whole natural history of primary tumor and secondary distant metastases growth in patients with lymph nodes metastases; 2) developing adequate and precise CoM-III which reflects relations between primary tumor and secondary distant metastases; 3) analyzing the CoM-III scope of application; 4) implementing the model as a software tool. Firstly, the CoM-III includes exponential tumor growth model as a system of determinate nonlinear and linear equations. Secondly, mathematical model corresponds to TNM classification. It allows to calculate different growth periods of primary tumor and secondary distant metastases growth in patients with lymph nodes metastases: 1) ‘non-visible period’ for primary tumor; 2) ‘non-visible period’ for secondary distant metastases growth in patients with lymph nodes metastases; 3) ‘visible period’ for secondary distant metastases growth in patients with lymph nodes metastases. The new predictive tool: 1) is a solid foundation to develop future studies of breast cancer models; 2) does not require any expensive diagnostic tests; 3) is the first predictor which makes forecast using only current patient data, the others are based on the additional statistical data. Thus, the CoM-III model and predictive software: a) detect different growth periods of primary tumor and secondary distant metastases growth in patients with lymph nodes metastases; b) make forecast of the period of the distant metastases appearance in patients with lymph nodes metastases; c) have higher average prediction accuracy than the other tools; d) can improve forecasts on survival of breast cancer and facilitate optimization of diagnostic tests. The following are calculated by CoM-III: the number of doublings for ‘non-visible’ and ‘visible’ growth period of secondary distant metastases; tumor volume doubling time (days) for ‘non-visible’ and ‘visible’ growth period of secondary distant metastases. The CoM-III enables, for the first time, to predict the whole natural history of primary tumor and secondary distant metastases growth on each stage (pT1, pT2, pT3, pT4) relying only on primary tumor sizes. Summarizing: a) CoM-III describes correctly primary tumor and secondary distant metastases growth of IA, IIA, IIB, IIIB (T1-4N1-3M0) stages in patients with lymph nodes metastases (N1-3); b) facilitates the understanding of the appearance period and inception of secondary distant metastases.

Keywords: breast cancer, exponential growth model, mathematical model, primary tumor, secondary metastases, survival

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Authors: Moser Stephan, Lukasser Gerald, Weitlaner Robert

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Urban structures will be used more intensively in the future through redensification or new planned districts with high building densities. Especially, to achieve positive energy balances like requested for Positive Energy Districts (PED) the single use of roofs is not sufficient for dense urban areas. However, the increasing share of window significantly reduces the facade area available for use in PV generation. Through the use of PV technology at other building components, such as external venetian blinds, onsite generation can be maximized and standard functionalities of this product can be positively extended. While offering advantages in terms of infrastructure, sustainability in the use of resources and efficiency, these systems require an increased optimization in planning and control strategies of buildings. External venetian blinds with PV technology require an intelligent control concept to meet the required demands such as maximum power generation, glare prevention, high daylight autonomy, avoidance of summer overheating but also use of passive solar gains in wintertime. Today, geometric representation of outdoor spaces and at the building level, three-dimensional geometric information is available for planning with Building Information Modeling (BIM). In a research project, a web application which is called HELLA DECART was developed to provide this data structure to extract the data required for the simulation from the BIM models and to make it usable for the calculations and coupled simulations. The investigated object is uploaded as an IFC file to this web application and includes the object as well as the neighboring buildings and possible remote shading. This tool uses a ray tracing method to determine possible glare from solar reflections of a neighboring building as well as near and far shadows per window on the object. Subsequently, an annual estimate of the sunlight per window is calculated by taking weather data into account. This optimized daylight assessment per window provides the ability to calculate an estimation of the potential power generation at the integrated PV on the venetian blind but also for the daylight and solar entry. As a next step, these results of the calculations as well as all necessary parameters for the thermal simulation can be provided. The overall aim of this workflow is to advance the coordination between the BIM model and coupled building simulation with the resulting shading and daylighting system with the artificial lighting system and maximum power generation in a control system. In the research project Powershade, an AI based control concept for PV integrated façade elements with coupled simulation results is investigated. The developed automated workflow concept in this paper is tested by using an office living lab at the HELLA company.

Keywords: BIPV, building simulation, optimized control strategy, planning tool

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Authors: Desalegn Feyissa Desu

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Drug therapy problem is a significant challenge to provide high quality health care service for the patients. It is associated with morbidity, mortality, increased hospital stay, and reduced quality of life. Moreover, pediatric patients are quite susceptible to drug therapy problems. Thus this study aimed to assess drug therapy problem and its contributing factors among pediatric patients diagnosed with infectious disease admitted to pediatric ward of Jimma university medical center, from April 1 to June 30, 2018. Prospective observational study was conducted among pediatric patients with infectious disease admitted from April 01 to June 30, 2018. Drug therapy problems were identified by using Cipolle’s and strand’s drug related problem classification method. Patient’s written informed consent was obtained after explaining the purpose of the study. Patient’s specific data were collected using structured questionnaire. Data were entered into Epi data version 4.0.2 and then exported to statistical software package version 21.0 for analysis. To identify predictors of drug therapy problems occurrence, multiple stepwise backward logistic regression analysis was done. The 95% CI was used to show the accuracy of data analysis and statistical significance was considered at p-value < 0.05. A total of 304 pediatric patients were included in the study. Of these, 226(74.3%) patients had at least one drug therapy problem during their hospital stay. A total of 356 drug therapy problems were identified among two hundred twenty six patients. Non-compliance (28.65%) and dose too low (27.53%) were the most common type of drug related problems while disease comorbidity [AOR=3.39, 95% CI= (1.89-6.08)], Polypharmacy [AOR=3.16, 95% CI= (1.61-6.20)] and more than six days stay in hospital [AOR=3.37, 95% CI= (1.71-6.64) were independent predictors of drug therapy problem occurrence. Drug therapy problems were common in pediatric patients with infectious disease in the study area. Presence of comorbidity, polypharmacy and prolonged hospital stay were the predictors of drug therapy problem in study area. Therefore, to overcome the significant gaps in pediatric pharmaceutical care, clinical pharmacists, Pediatricians, and other health care professionals have to work in collaboration.

Keywords: drug therapy problem, pediatric, infectious disease, Ethiopia

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Authors: Dor Oppenheim, Yael Edan, Guy Shani

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This paper presents an image analysis algorithm to detect and count yellow tomato flowers in a greenhouse with uneven illumination conditions, complex growth conditions and different flower sizes. The algorithm is designed to be employed on a drone that flies in greenhouses to accomplish several tasks such as pollination and yield estimation. Detecting the flowers can provide useful information for the farmer, such as the number of flowers in a row, and the number of flowers that were pollinated since the last visit to the row. The developed algorithm is designed to handle the real world difficulties in a greenhouse which include varying lighting conditions, shadowing, and occlusion, while considering the computational limitations of the simple processor in the drone. The algorithm identifies flowers using an adaptive global threshold, segmentation over the HSV color space, and morphological cues. The adaptive threshold divides the images into darker and lighter images. Then, segmentation on the hue, saturation and volume is performed accordingly, and classification is done according to size and location of the flowers. 1069 images of greenhouse tomato flowers were acquired in a commercial greenhouse in Israel, using two different RGB Cameras – an LG G4 smartphone and a Canon PowerShot A590. The images were acquired from multiple angles and distances and were sampled manually at various periods along the day to obtain varying lighting conditions. Ground truth was created by manually tagging approximately 25,000 individual flowers in the images. Sensitivity analyses on the acquisition angle of the images, periods throughout the day, different cameras and thresholding types were performed. Precision, recall and their derived F1 score were calculated. Results indicate better performance for the view angle facing the flowers than any other angle. Acquiring images in the afternoon resulted with the best precision and recall results. Applying a global adaptive threshold improved the median F1 score by 3%. Results showed no difference between the two cameras used. Using hue values of 0.12-0.18 in the segmentation process provided the best results in precision and recall, and the best F1 score. The precision and recall average for all the images when using these values was 74% and 75% respectively with an F1 score of 0.73. Further analysis showed a 5% increase in precision and recall when analyzing images acquired in the afternoon and from the front viewpoint.

Keywords: agricultural engineering, image processing, computer vision, flower detection

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Authors: Roberto Rosenhaim, Marcos Antonio Crus Moreira, Robson da Cunha, Gerson Gomes Cunha

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This work provides details on the wind speed behavior within cities of Arraial do Cabo and São Pedro da Aldeia located in the Lakes Region of the State of Rio de Janeiro, Brazil. This region has one of the best potentials for wind power generation. In interurban layer, wind conditions are very complex and depend on physical geography, size and orientation of buildings and constructions around, population density, and land use. In the same context, the fundamental surface parameter that governs the production of flow turbulence in urban canyons is the surface roughness. Such factors can influence the potential for power generation from the wind within the cities. Moreover, the use of wind on a small scale is not fully utilized due to complexity of wind flow measurement inside the cities. It is difficult to accurately predict this type of resource. This study demonstrates how fuzzy logic can facilitate the assessment of the complexity of the wind potential inside the cities. It presents a decision support tool and its ability to deal with inaccurate information using linguistic variables created by the heuristic method. It relies on the already published studies about the variables that influence the wind speed in the urban environment. These variables were turned into the verbal expressions that are used in computer system, which facilitated the establishment of rules for fuzzy inference and integration with an application for smartphones used in the research. In the first part of the study, challenges of the sustainable development which are described are followed by incentive policies to the use of renewable energy in Brazil. The next chapter follows the study area characteristics and the concepts of fuzzy logic. Data were collected in field experiment by using qualitative and quantitative methods for assessment. As a result, a map of the various points is presented within the cities studied with its wind viability evaluated by a system of decision support using the method multivariate classification based on fuzzy logic.

Keywords: behavior of winds, wind power, fuzzy logic, sustainable development

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Authors: Cláudia Moço, Maria Santos, Carlos Arsénio, Débora Mendes, Miguel Oliveira. José Paulo Da Silva

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Construction industry generates large amounts of waste all over the world. About 450 million tons of construction and demolition wastes (C&DW) are produced annually in the European Union. C&DW are highly heterogeneous materials in size and composition, which imposes strong difficulties on their management. Directive n.º 2008/98/CE, of the European Parliament and of the Council of 6 November establishes that 70 % of the C&DW have to be recycled by 2020. To evaluate possible applications of these materials, a detailed physical, chemical and environmental characterization is necessary. Multi Triagem, Lda. is a company located in Algarve (Portugal) and was supported by the European Regional Development Fund (grant QREN 30307 Multivalor) to quantify and characterize the received C&DW, in order to evaluate their possible applications. This evaluation, performed in collaboration with the University of Algarve, involves a physical, chemical and environmental detailed characterization of the received C&DW. In this work we report on the amounts, trial procedures and properties of the C&DW received over a period of fifteen month. In this period the company received C&DW coming from 393 different origins. The total amount was 32.458 tons, mostly mixtures containing concrete, masonry/mortar and soil/rock. Most of C&DW came from demodulation constructions and diggings. The organic/inert component, namely metal, glass, wood and plastics, were screened first and account for about 3 % of the received materials. The remaining materials were screened and grouped according to their origin and contents, the latter evaluated by visual inspection. Twenty five samples were prepared and submitted to a detailed physical, chemical and environmental analysis. The C&DW aggregates show lower quality properties than natural aggregates for concrete preparation and unbound layers of road pavements. However, chemical analyzes indicated that most samples are environmentally safe. A continuous monitoring of the presence of heavy metals and organic compounds is needed in order to perform a proper screening of the C&DW. C&DW aggregates provide a good alternative to natural aggregates.

Keywords: construction and demolition wastes, waste classification, waste composition, waste screening

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Authors: Jiri Kysucan, Dusan Klos, Katherine Vomackova, Pavel Koranda, Martin Lovecek, Cestmir Neoral, Roman Havlik

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Aim: The prognosis of patients with pancreatic cancer is poor. The median of survival after establishing diagnosis is 3-11 months without surgical treatment, 13-20 months with surgical treatment depending on the disease stage, 5-year survival is less than 5%. Radical surgical resection remains the only hope of curing the disease. Early diagnosis with valid establishment of tumor resectability is, therefore, the most important aim for patients with pancreatic cancer. The aim of the work is to evaluate the contribution and define the role of 18F-FDG PET/CT in preoperative staging. Material and Methods: In 195 patients (103 males, 92 females, median age 66,7 years, 32-88 years) with a suspect pancreatic lesion, as part of the standard preoperative staging, in addition to standard examination methods (ultrasonography, contrast spiral CT, endoscopic ultrasonography, endoscopic ultrasonographic biopsy), a hybrid 18F-FDG PET/CT was performed. All PET/CT findings were subsequently compared with standard staging (CT, EUS, EUS FNA), with peroperative findings and definitive histology in the operated patients as reference standards. Interpretation defined the extent of the tumor according to TNM classification. Limitations of resectability were local advancement (T4) and presence of distant metastases (M1). Results: PET/CT was performed in a total of 195 patients with a suspect pancreatic lesion. In 153 patients, pancreatic carcinoma was confirmed and of these patients, 72 were not indicated for radical surgical procedure due to local inoperability or generalization of the disease. The sensitivity of PET/CT in detecting the primary lesion was 92.2%, specificity was 90.5%. A false negative finding in 12 patients, a false positive finding was seen in 4 cases, positive predictive value (PPV) 97.2%, negative predictive value (NPV) 76,0%. In evaluating regional lymph nodes, sensitivity was 51.9%, specificity 58.3%, PPV 58,3%, NPV 51.9%. In detecting distant metastases, PET/CT reached a sensitivity of 82.8%, specificity was 97.8%, PPV 96.9%, NPV 87.0%. PET/CT found distant metastases in 12 patients, which were not detected by standard methods. In 15 patients (15.6%) with potentially radically resectable findings, the procedure was contraindicated based on PET/CT findings and the treatment strategy was changed. Conclusion: PET/CT is a highly sensitive and specific method useful in preoperative staging of pancreatic cancer. It improves the selection of patients for radical surgical procedures, who can benefit from it and decreases the number of incorrectly indicated operations.

Keywords: cancer, PET/CT, staging, surgery

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Authors: Shantam Gupta

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The objective of this study is to address the critical need for automation in the domestic food processing sector and study its impact. Food is the one of the most basic physiological needs essential for the survival of a living being. Some of them have the capacity to prepare their own food (like most plants) and henceforth are designated as primary food producers; those who depend on these primary food producers for food form the primary consumers’ class (herbivores). Some of the organisms relying on the primary food are the secondary food consumers (carnivores). There is a third class of consumers called tertiary food consumers/apex food consumers that feed on both the primary and secondary food consumers. Humans form an essential part of the apex predators and are generally at the top of the food chain. But still further disintegration of the food habits of the modern human i.e. Homo sapiens, reveals that humans depend on other individuals for preparing their own food. The old notion of eating raw/brute food is long gone and food processing has become very trenchant in lives of modern human. This has led to an increase in dependence on other individuals for ‘processing’ the food before it can be actually consumed by the modern human. This has led to a further shift of humans in the classification of food chain of consumers. The effects of the shifts shall be systematically investigated in this paper. The processing of food has a direct impact on the economy of the individual (consumer). Also most individuals depend on other processing individuals for the preparation of food. This dependency leads to establishment of a vital link of dependency in the food web which when altered can adversely affect the food web and can have dire consequences on the health of the individual. This study investigates the challenges arising out due to this dependency and the impact of food processing on the economy of the individual. A comparison of Industrial food processing and processing at domestic platforms (households and restaurants) has been made to provide an idea about the present scenario of automation in the food processing sector. A lot of time and energy is also consumed while processing food at home for consumption. The high frequency of consumption of meals (greater than 2 times a day) makes it even more laborious. Through the medium of this study a pressing need for development of an automatic cooking machine is proposed with a mission to reduce the inter-dependency & human effort of individuals required for the preparation of food (by automation of the food preparation process) and make them more self-reliant The impact of development of this product has also further been profoundly discussed. Assumption used: The individuals those who process food also consume the food that they produce. (They are also termed as ‘independent’ or ‘self-reliant’ modern human beings.)

Keywords: automation, food processing, impact on economy, processing individual

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Authors: M. Amparo Núñez-Andrés, Felipe Buill, Albert Prades

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More and more frequently, geomatics techniques such as terrestrial laser scanning or digital photogrammetry, either terrestrial or from drones, are being used to obtain digital terrain models (DTM) used for the monitoring of geological phenomena that cause natural disasters, such as landslides, rockfalls, debris-flow. One of the main multitemporal analyses developed from these models is the quantification of volume changes in the slopes and hillsides, either caused by erosion, fall, or land movement in the source area or sedimentation in the deposition zone. To carry out this task, it is necessary to filter the point clouds of all those elements that do not belong to the slopes. Among these elements, vegetation stands out as it is the one we find with the greatest presence and its constant change, both seasonal and daily, as it is affected by factors such as wind. One of the best-known indexes to detect vegetation on the image is the NVDI (Normalized Difference Vegetation Index), which is obtained from the combination of the infrared and red channels. Therefore it is necessary to have a multispectral camera. These cameras are generally of lower resolution than conventional RGB cameras, while their cost is much higher. Therefore we have to look for alternative indices based on RGB. In this communication, we present the results obtained in Georisk project (PID2019‐103974RB‐I00/MCIN/AEI/10.13039/501100011033) by using the GLI (Green Leaf Index) and ExG (Excessive Greenness), as well as the change to the Hue-Saturation-Value (HSV) color space being the H coordinate the one that gives us the most information for vegetation filtering. These filters are applied both to the images, creating binary masks to be used when applying the SfM algorithms, and to the point cloud obtained directly by the photogrammetric process without any previous filter or the one obtained by TLS (Terrestrial Laser Scanning). In this last case, we have also tried to work with a Riegl VZ400i sensor that allows the reception, as in the aerial LiDAR, of several returns of the signal. Information to be used for the classification on the point cloud. After applying all the techniques in different locations, the results show that the color-based filters allow correct filtering in those areas where the presence of shadows is not excessive and there is a contrast between the color of the slope lithology and the vegetation. As we have advanced in the case of using the HSV color space, it is the H coordinate that responds best for this filtering. Finally, the use of the various returns of the TLS signal allows filtering with some limitations.

Keywords: RGB index, TLS, photogrammetry, multispectral camera, point cloud

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Authors: Leei Wong

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Changes in globalized contexts precipitate changing perceptions concerning linguistic politeness practices. Within these changing contexts, misunderstanding or stereotypification of politeness norms may lead to negative consequences such as hostility or even communication breakdown. With China’s rising influence, the country is offering a vast potential market for global economic development and diplomatic relations and opportunities for intercultural interaction, and many outside China are subsequently learning Chinese. These trends bring both opportunities and pitfalls for intercultural communication, including within the important field of politeness awareness. One internationally recognized benchmark for the study and classification of languages – the updated 2018 CEFR (Common European Framework of Reference for Language) Companion Volume New Descriptors (CEFR/CV) – classifies politeness as a B1 (or intermediate) level descriptor on the scale of Politeness Conventions. This provides some indication of the relevance of politeness awareness within new globalized contexts for fostering better intercultural communication. This study specifically examines Bald on record politeness strategies presented in current beginner TCAL textbooks used in Australian tertiary education through content-analysis. The investigation in this study involves the purposive sampling of commercial textbooks published in America and China followed by interpretive content analysis. The philosophical position of this study is therefore located within an interpretivist ontology, with a subjectivist epistemological perspective. It sets out with the aim to illuminate the characteristics of Chinese Bald on record strategies that are deemed significant in the present-world context through Chinese textbook writers and curriculum designers. The data reveals significant findings concerning politeness strategies in beginner stage curriculum, and also opens the way for further research on politeness strategies in intermediate and advanced level textbooks for additional language learners. This study will be useful for language teachers, and language teachers-in-training, by generating awareness and providing insights and advice into the teaching and learning of Bald on record politeness strategies. Authors of textbooks may also benefit from the findings of this study, as awareness is raised of the need to include reference to understanding politeness in language, and how this might be approached.

Keywords: linguistic politeness, higher education, Chinese language, additional language

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Authors: Getaneh Berie Tarekegn, Li-Chia Tai

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With the rapid advancement of artificial intelligence, low-power built-in sensors on Internet of Things devices, and communication technologies, location-aware services have become increasingly popular and have permeated every aspect of people’s lives. Global navigation satellite systems (GNSSs) are the default method of providing continuous positioning services for ground and aerial vehicles, as well as consumer devices (smartphones, watches, notepads, etc.). However, the environment affects satellite positioning systems, particularly indoors, in dense urban and suburban cities enclosed by skyscrapers, or when deep shadows obscure satellite signals. This is because (1) indoor environments are more complicated due to the presence of many objects surrounding them; (2) reflection within the building is highly dependent on the surrounding environment, including the positions of objects and human activity; and (3) satellite signals cannot be reached in an indoor environment, and GNSS doesn't have enough power to penetrate building walls. GPS is also highly power-hungry, which poses a severe challenge for battery-powered IoT devices. Due to these challenges, IoT applications are limited. Consequently, precise, seamless, and ubiquitous Positioning, Navigation and Timing (PNT) systems are crucial for many artificial intelligence Internet of Things (AI-IoT) applications in the era of smart cities. Their applications include traffic monitoring, emergency alarms, environmental monitoring, location-based advertising, intelligent transportation, and smart health care. This paper proposes a generative AI-based positioning scheme for large-scale wireless settings using fingerprinting techniques. In this article, we presented a semi-supervised deep convolutional generative adversarial network (S-DCGAN)-based radio map construction method for real-time device localization. We also employed a reliable signal fingerprint feature extraction method with t-distributed stochastic neighbor embedding (t-SNE), which extracts dominant features while eliminating noise from hybrid WLAN and long-term evolution (LTE) fingerprints. The proposed scheme reduced the workload of site surveying required to build the fingerprint database by up to 78.5% and significantly improved positioning accuracy. The results show that the average positioning error of GAILoc is less than 0.39 m, and more than 90% of the errors are less than 0.82 m. According to numerical results, SRCLoc improves positioning performance and reduces radio map construction costs significantly compared to traditional methods.

Keywords: location-aware services, feature extraction technique, generative adversarial network, long short-term memory, support vector machine

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Authors: Men An Pan, Hong Ren Chen, Chih Heng Shih, Hsing Yuan Yen

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Pingtung County is located in the southernmost region of Taiwan. During the winter season, pollutants due to insufficient dispersion caused by the downwash of the northeast monsoon lead to the poor air quality of the County. Through the implementation of various control methods, including the application of permits of air pollution, fee collection of air pollution, control oil fume of catering sectors, smoke detection of diesel vehicles, regular inspection of locomotives, and subsidies for low-polluting vehicles. Moreover, to further mitigate the air pollution, additional alternative controlling strategies are also carried out, such as construction site control, prohibition of open-air agricultural waste burning, improvement of river dust, and strengthening of road cleaning operations. The combined efforts have significantly reduced air pollutants in the County. However, in order to effectively and promptly monitor the ambient air quality, the County has subsequently deployed micro-sensors, with a total of 400 IoTs (Internet of Things) micro-sensors for PM2.5 and VOC detection and 3 air quality monitoring stations of the Environmental Protection Agency (EPA), covering 33 townships of the County. The covered area has more than 1,300 listed factories and 5 major industrial parks; thus forming an Internet of Things (IoTs) based multi-level air quality monitoring system. The results demonstrate that the IoTs multi-level air quality sensors combined with other strategies such as “sand and gravel dredging area technology monitoring”, “banning open burning”, “intelligent management of construction sites”, “real-time notification of activation response”, “nighthawk early bird plan with micro-sensors”, “unmanned aircraft (UAV) combined with land and air to monitor abnormal emissions”, and “animal husbandry odour detection service” etc. The satisfaction improvement rate of air control, through a 2021 public survey, reached a high percentage of 81%, an increase of 46% as compared to 2018. For the air pollution complaints for the whole year of 2021, the total number was 4213 in contrast to 7088 in 2020, a reduction rate reached almost 41%. Because of the spatial-temporal features of the air quality monitoring IoTs system by the application of microsensors, the system does assist and strengthen the effectiveness of the existing air quality monitoring network of the EPA and can provide real-time control of the air quality. Therefore, the hot spots and potential pollution locations can be timely determined for law enforcement. Hence, remarkable results were obtained for the two years. That is, both reduction of public complaints and better air quality are successfully achieved through the implementation of the present IoTs system for real-time air quality monitoring throughout Pingtung County.

Keywords: IoT, PM, air quality sensor, air pollution, environmental monitoring

Procedia PDF Downloads 53