Search results for: regional features

Authors: Siriraks Khawchaimaha, Sangwian Boonto

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Sport Authority of Thailand (SAT) is the state enterprise, promotes and supports all sports kind both professional and athletes for competitions, and administer under government policy and government officers and therefore, all financial supports whether cash inflows and cash outflows are strictly committed to government budget and limited to the planned projects at least 12 to 16 months ahead of reality, as results of ineffective in sport events, administration and competitions. In order to retain in the sports challenges around the world, SAT need to has its own sports business services model by each stadium, region and athletes’ competencies. Based on the HMK model of Khawchaimaha, S. (2007), this research study is formalized into each 10 regional stadiums to details into the characteristics root of fans, athletes, coaches, equipments and facilities, and stadiums. The research designed is firstly the evaluation of external factors: hardware whereby competition or practice of stadiums, playground, facilities, and equipments. Secondly, to understand the software of the organization structure, staffs and management, administrative model, rules and practices. In addition, budget allocation and budget administration with operating plan and expenditure plan. As results for the third step, issues and limitations which require action plan for further development and support, or to cease that unskilled sports kind. The final step, based on the HMK model and modeling canvas by Alexander O and Yves P (2010) are those of template generating Sports Business Services Model for each 10 SAT’s regional stadiums.

Keywords: HMK model, not for profit organization, sport business model, sport services model

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Authors: Jozef Mindas, Jaroslav Skvarenina, Jana Skvareninova

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Study of the effects of climate change on Norway Spruce (Picea abies) forests has mainly focused on the diversity of tree species diversity of tree species as a result of the ability of species to tolerate temperature and moisture changes as well as some effects of disturbance regime changes. The tree species’ diversity changes in spruce forests due to climate change have been analyzed via gap model. Forest gap model is a dynamic model for calculation basic characteristics of individual forest trees. Input ecological data for model calculations have been taken from the permanent research plots located in primeval forests in mountainous regions in Slovakia. The results of regional scenarios of the climatic change for the territory of Slovakia have been used, from which the values are according to the CGCM3.1 (global) model, KNMI and MPI (regional) models. Model results for conditions of the climate change scenarios suggest a shift of the upper forest limit to the region of the present subalpine zone, in supramontane zone. N. spruce representation will decrease at the expense of beech and precious broadleaved species (Acer sp., Sorbus sp., Fraxinus sp.). The most significant tree species diversity changes have been identified for the upper tree line and current belt of dwarf pine (Pinus mugo) occurrence. The results have been also discussed in relation to most important disturbances (wind storms, snow and ice storms) and phenological changes which consequences are little known. Special discussion is focused on biomass production changes in relation to carbon storage diversity in different carbon pools.

Keywords: biodiversity, climate change, Norway spruce forests, gap model

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Authors: Fedili Benamar, Beloulou Mohamed Lamine, Ouahes Hassane, Ghattas Samir

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 Background and aims: Peripheral regional anesthesia has been integrated into most analgesia protocols for total knee arthroplasty which considered among the most painful surgeries with a huge potential for chronicization. The adductor canal block (ACB) has gained popularity. Similarly, the IPACK block has been described to provide analgesia of the posterior knee capsule. This study aimed to evaluate the analgesic efficacy of this block in patients undergoing primary PTG. Methods: 90 patients were randomized to receive either an IPACK, an anterior sciatic block, or a sham block (30 patients in each group + multimodal analgesia and a catheter in the KCA adductor canal). GROUP 1 KCA GROUP 2 KCA+BSA GROUP 3 KCA+IPACK The analgesic blocks were done under echo-guidance preoperatively respecting the safety rules, the dose administered was 20 cc of ropivacaine 0.25% was used. We were to assess posterior knee pain 6 hours after surgery. Other endpoints included quality of recovery after surgery, pain scores, opioid requirements (PCA morphine)(EPI info 7.2 analysis). Results: -groups were matched -A predominance of women (4F/1H). -average age: 68 +/-7 years -the average BMI =31.75 kg/m2 +/- 4. -70% of patients ASA2 ,20% ASA3. -The average duration of the intervention: 89 +/- 19 minutes. -Morphine consumption (PCA) significantly higher in group 1 (16mg) & group 2 (8mg) group 3 (4mg) - The groups were matched . -There was a correlation between the use of the ipack block and postoperative pain Conclusions :In a multimodal analgesic protocol, the addition of IPACK block decreased pain scores and morphine consumption ,

Keywords: regional anesthesia, analgesia, total knee arthroplasty, the adductor canal block (acb), the ipack block, pain

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Authors: P. S. Jagadeesh Kumar, Mingmin Pan, Xianpei Li, Yanmin Yuan, Tracy Lin Huan

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Researchers are doing enchanting research into the inherited features of Alzheimer’s disease and probable consistent therapies. In Alzheimer’s, memories are extinct in reverse order; memories formed lately are more transitory than those from formerly. Reminiscence therapy includes the conversation of past actions, trials and knowledges with another individual or set of people, frequently with the help of perceptible reminders such as photos, household and other acquainted matters from the past, music and collection of tapes. In this manuscript, the competence of reminiscence therapy for Alzheimer’s disease is measured using logistic regression based linear bootstrap aggregating. Logistic regression is used to envisage the experiential features of the patient’s memory through various therapies. Linear bootstrap aggregating shows better stability and accuracy of reminiscence therapy used in statistical classification and regression of memories related to validation therapy, supportive psychotherapy, sensory integration and simulated presence therapy.

Keywords: Alzheimer’s disease, linear bootstrap aggregating, logistic regression, reminiscence therapy

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Authors: W. F. Ribeiro, J. L. N. Góes

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The industrial process adds to engineering wood products features absent in solid wood, with homogeneous structure and reduced defects, improved physical and mechanical properties, bio-deterioration, resistance and better dimensional stability, improving quality and increasing the reliability of structures wood. These features combined with using fast-growing trees, make them environmentally ecological products, ensuring a strong consumer market. The wood I-joists are manufactured by the industrial profiles bonding flange and web, an important aspect of the production of wooden I-beams is the adhesive joint that bonds the web to the flange. Adhesives can effectively transfer and distribute stresses, thereby increasing the strength and stiffness of the composite. The objective of this study is to evaluate different resins in a shear strain specimens with the aim of analyzing the most efficient resin and possibility of using national products, reducing the manufacturing cost. First was conducted a literature review, where established the geometry and materials generally used, then established and analyzed 8 national resins and produced six specimens for each.

Keywords: engineered wood products, structural resin, wood i-joist, Pinus taeda

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Authors: Yufeng Li, Yinan Ma, Jing Wu, Chengnian Long

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Infrared object detection aims at separating small and dim target from clutter background and its capabilities extend beyond the limits of visible light, making it invaluable in a wide range of applications such as improving safety, security, efficiency, and functionality. However, existing methods are usually sensitive to the noise of the input infrared image, leading to a decrease in target detection accuracy and an increase in the false alarm rate in high-noise environments. To address this issue, an infrared small target detection algorithm called YOLO-IR is proposed in this paper to improve the robustness to high infrared noise. To address the problem that high noise significantly reduces the clarity and reliability of target features in infrared images, we design a soft-threshold coordinate attention mechanism to improve the model’s ability to extract target features and its robustness to noise. Since the noise may overwhelm the local details of the target, resulting in the loss of small target features during depth down-sampling, we propose a deep and shallow feature fusion neck to improve the detection accuracy. In addition, because the generalized Intersection over Union (IoU)-based loss functions may be sensitive to noise and lead to unstable training in high-noise environments, we introduce a Wasserstein-distance based loss function to improve the training of the model. The experimental results show that YOLO-IR achieves a 5.0% improvement in recall and a 6.6% improvement in F1-score over existing state-of-art model.

Keywords: infrared small target detection, high noise, robustness, soft-threshold coordinate attention, feature fusion

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Authors: Ahmed M. Gad, Ahmed S. Hweidi

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Background: Defects of the little finger and adjacent areas are not uncommon. It could be a traumatic, post-burn, or after contracture release. Different options could be used for resurfacing these defect, including skin grafts, local or regional flaps. Ulnar para-metacarpal flap described by Bakhach in 1995 based on the distal division of the dorsal branch of the ulnar artery considered a good option for that. In this work, we applied the concept of propeller flap for better mobilization and in-setting of the ulnar para-metacarpal flap. Methods: The study included 15 cases with 4 females and 11 male patients. 10 of the patients had severe post-burn contractures of little finger, and 5 had post-traumatic little finger defects. Contractures were released and resulting soft tissue defects were reconstructed with propeller ulnar para-metacarpal artery flap. The flap based on two main perforators communicating with the palmar system, it was raised based on one of them depending on the extent of the defect and rotated 180 degrees after judicious dissection of the perforator. Results: 13 flaps survived completely, one of the cases developed partial skin loss, which healed by dressing, another flap was completely lost and covered later by a full-thickness skin graft. Conclusion: Ulnar para-metacarpal flap is a reliable option to resurface the little finger as well as adjacent areas. The application of the propeller flap concept based on whether the proximal or distal communicating branch makes the rotation and in-setting of the flap easier.

Keywords: little finger defects, propeller flap, regional hand defects, ulnar parametacarpal flap

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Authors: Ewa Bednorz, Marek Polrolniczak, Bartosz Czernecki, Arkadiusz Marek Tomczyk

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This study is meant as a contribution to the research of the upwelling phenomenon, which is one of the most pronounced examples of the sea-atmosphere coupling. The aim is to confirm the atmospheric forcing of the sea waters circulation and sea surface temperature along the variously oriented Baltic Sea coasts and to find out macroscale and regional circulation patterns triggering upwelling along different sections of this relatively small and semi-closed sea basin. The mean daily sea surface temperature data from the summer seasons (June–August) of the years 1982–2017 made the basis for the detection of upwelling cases. For the atmospheric part of the analysis, monthly indices of the Northern Hemisphere macroscale circulation patterns were used. Besides, in order to identify the local direction of airflow, the daily zonal and meridional regional circulation indices were constructed and introduced to the analysis. Finally, daily regional circulation patterns over the Baltic Sea region were distinguished by applying the principal component analysis to the gridded mean daily sea level pressure data. Within the Baltic Sea, upwelling is the most frequent along the zonally oriented northern coast of the Gulf of Finland, southern coasts of Sweden, and along the middle part of the western Gulf of Bothnia coast. Among the macroscale circulation patterns, the Scandinavian type (SCAND), with a primary circulation center located over Scandinavia, has the strongest impact on the horizontal flow of surface sea waters in the Baltic Sea, which triggers upwelling. An anticyclone center over Scandinavia in the positive phase of SCAND enhances the eastern airflow, which increases upwelling frequency along southeastern Baltic coasts. It was proved in the study that the zonal circulation has a stronger impact on upwelling occurrence than the meridional one, and it could increase/decrease a chance of upwelling formation by more than 70% in some coastal sections. Positive and negative phases of six distinguished regional daily circulation patterns made 12 different synoptic situations which were analyzed in the terms of their influence on the upwelling formation. Each of them revealed some impact on the frequency of upwelling in some coastal section of the Baltic Sea; however, two kinds of synoptic situations seemed to have the strongest influence, namely, the first kind representing pressure patterns enhancing the zonal flow and the second kind representing synoptic patterns with a cyclone/anticyclone centers over southern Scandinavia. Upwelling occurrence appeared to be particularly strongly reliant on the atmospheric conditions in some specific coastal sections, namely: the Gulf of Finland, the south eastern Baltic coasts (Polish and Latvian-Lithuanian section), and the western part of the Gulf of Bothnia. Concluding, it can be stated that atmospheric conditions strongly control the occurrence of upwelling within the Baltic Sea basin. Both local and macroscale circulation patterns expressed by the location of the pressure centers influence the frequency of this phenomenon; however, the impact strength varies, depending on the coastal region. Acknowledgment: This research was funded by the National Science Centre, Poland, grant number 2016/21/B/ST10/01440.

Keywords: Baltic Sea, circulation patterns, coastal upwelling, synoptic conditions

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Authors: Sarah Jacqueline Saram, Diya Baker, Jaishree Gandhewar

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Named after the Slovakian microbiologist, Miroslav Kocur, the Kocuria spp. are an emerging cause of significant human infections. Their predilection for immunocompromised states, such as malignancy and metabolic disorders, is highlighted in the literature. The coagulase-negative, gram-positive cocci are commensals found in the skin and oropharynx of humans, and their growing presence as responsible organisms in ocular infections cannot be ignored. The severe, rapid, and unrelenting disease course associated with Kocuria keratitis is underlined in the literature. However, the clinical features are variable, which may impede making a diagnosis. Here, we describe a first account of an initial misdiagnosis due to reliance on subjective analysis features on a confocal microscope, which ultimately led to a delay in commencing the correct treatment. In documenting this, we hope to underline to clinicians the difficulties in recognising a Kocuria Rhizophilia keratitis due to its similar clinical presentation to an Acanthamoeba Keratitis, thus emphasizing the need for early investigations such as corneal scrapes to secure the correct diagnosis and prevent further harm and vision loss for the patient.

Keywords: keratitis, cornea, infection, rare, Kocuria

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Authors: L. S. Chathurika

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Early prediction of student performance is an important factor to be gained academic excellence. Whatever the study stream in secondary education, students lay the foundation for higher studies during the first year of their degree or diploma program in Sri Lanka. The information technology (IT) field has certain improvements in the education domain by selecting specialization areas to show the talents and skills of students. These specializations can be software engineering, network administration, database administration, multimedia design, etc. After completing the first-year, students attempt to select the best path by considering numerous factors. The purpose of this experiment is to predict the best study path using machine learning algorithms. Five classification algorithms: decision tree, support vector machine, artificial neural network, Naïve Bayes, and logistic regression are selected and tested. The support vector machine obtained the highest accuracy, 82.4%. Then affecting features are recognized to select the best study path.

Keywords: algorithm, classification, evaluation, features, testing, training

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Authors: Noura Al Akkari, Aurélie Foucquier, Sylvain Lespinats

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Load monitoring is a management process for energy consumption towards energy savings and energy efficiency. Non Intrusive Load Monitoring (NILM) is one method of load monitoring used for disaggregation purposes. NILM is a technique for identifying individual appliances based on the analysis of the whole residence data retrieved from the main power meter of the house. Our NILM framework starts with data acquisition, followed by data preprocessing, then event detection, feature extraction, then general appliance modeling and identification at the final stage. The event detection stage is a core component of NILM process since event detection techniques lead to the extraction of appliance features. Appliance features are required for the accurate identification of the household devices. In this research work, we aim at developing a new event detection methodology with accurate load disaggregation to extract appliance features. Time-domain features extracted are used for tuning general appliance models for appliance identification and classification steps. We use unsupervised algorithms such as Dynamic Time Warping (DTW). The proposed method relies on detecting areas of operation of each residential appliance based on the power demand. Then, detecting the time at which each selected appliance changes its states. In order to fit with practical existing smart meters capabilities, we work on low sampling data with a frequency of (1/60) Hz. The data is simulated on Load Profile Generator software (LPG), which was not previously taken into consideration for NILM purposes in the literature. LPG is a numerical software that uses behaviour simulation of people inside the house to generate residential energy consumption data. The proposed event detection method targets low consumption loads that are difficult to detect. Also, it facilitates the extraction of specific features used for general appliance modeling. In addition to this, the identification process includes unsupervised techniques such as DTW. To our best knowledge, there exist few unsupervised techniques employed with low sampling data in comparison to the many supervised techniques used for such cases. We extract a power interval at which falls the operation of the selected appliance along with a time vector for the values delimiting the state transitions of the appliance. After this, appliance signatures are formed from extracted power, geometrical and statistical features. Afterwards, those formed signatures are used to tune general model types for appliances identification using unsupervised algorithms. This method is evaluated using both simulated data on LPG and real-time Reference Energy Disaggregation Dataset (REDD). For that, we compute performance metrics using confusion matrix based metrics, considering accuracy, precision, recall and error-rate. The performance analysis of our methodology is then compared with other detection techniques previously used in the literature review, such as detection techniques based on statistical variations and abrupt changes (Variance Sliding Window and Cumulative Sum).

Keywords: electrical disaggregation, DTW, general appliance modeling, event detection

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Authors: Lin Li, P. G. R. N. I. Pussella

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When representing spatial data and their attributes on different types of maps, the scale plays a key role in the process of map generalization. The process is consisted with two main operators such as selection and omission. Once some data were selected, they would undergo of several geometrical changing processes such as elimination, simplification, smoothing, exaggeration, displacement, aggregation and size reduction. As a result of these operations at different levels of data, the geometry of the spatial features such as length, sinuosity, orientation, perimeter and area would be altered. This would be worst in the case of preparation of small scale maps, since the cartographer has not enough space to represent all the features on the map. What the GIS users do is when they wanted to analyze a set of spatial data; they retrieve a data set and does the analysis part without considering very important characteristics such as the scale, the purpose of the map and the degree of generalization. Further, the GIS users use and compare different maps with different degrees of generalization. Sometimes, GIS users are going beyond the scale of the source map using zoom in facility and violate the basic cartographic rule 'it is not suitable to create a larger scale map using a smaller scale map'. In the study, the effect of map generalization for GIS analysis would be discussed as the main objective. It was used three digital maps with different scales such as 1:10000, 1:50000 and 1:250000 which were prepared by the Survey Department of Sri Lanka, the National Mapping Agency of Sri Lanka. It was used common features which were on above three maps and an overlay analysis was done by repeating the data with different combinations. Road data, River data and Land use data sets were used for the study. A simple model, to find the best place for a wild life park, was used to identify the effects. The results show remarkable effects on different degrees of generalization processes. It can see that different locations with different geometries were received as the outputs from this analysis. The study suggests that there should be reasonable methods to overcome this effect. It can be recommended that, as a solution, it would be very reasonable to take all the data sets into a common scale and do the analysis part.

Keywords: generalization, GIS, scales, spatial analysis

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Authors: Keerti Kembhavi, M. R. Archana, V. Anjaneyappa

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Most asphalt pavement condition evaluation use rating frameworks in which asphalt pavement distress is estimated by type, extent, and severity. Rating is carried out by the pavement condition rating (PCR), which is tedious and expensive. This paper presents the development of a low-cost technique for image pavement distress analysis that permits the identification of pothole and cracks. The paper explores the application of image processing tools for the detection of potholes and cracks. Longitudinal cracking and pothole are detected using Fuzzy-C- Means (FCM) and proceeded with the Spectral Theory algorithm. The framework comprises three phases, including image acquisition, processing, and extraction of features. A digital camera (Gopro) with the holder is used to capture pavement distress images on a moving vehicle. FCM classifier and Spectral Theory algorithms are used to compute features and classify the longitudinal cracking and pothole. The Matlab2016Ra Image preparing tool kit utilizes performance analysis to identify the viability of pavement distress on selected urban stretches of Bengaluru city, India. The outcomes of image evaluation with the utilization semi-computerized image handling framework represented the features of longitudinal crack and pothole with an accuracy of about 80%. Further, the detected images are validated with the actual dimensions, and it is seen that dimension variability is about 0.46. The linear regression model y=1.171x-0.155 is obtained using the existing and experimental / image processing area. The R2 correlation square obtained from the best fit line is 0.807, which is considered in the linear regression model to be ‘large positive linear association’.

Keywords: crack detection, pothole detection, spectral clustering, fuzzy-c-means

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Authors: Sujay Kotwale, Ramasubba Reddy M.

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Electrocardiogram (ECG) is a non-invasive technique used to study and analyze various heart diseases. Cardiac arrhythmia is a serious heart disease which leads to death of the patients, when left untreated. An early-time detection of cardiac arrhythmia would help the doctors to do proper treatment of the heart. In the past, various algorithms and machine learning (ML) models were used to early-time detection of cardiac arrhythmia, but few of them have achieved better results. In order to improve the performance, this paper implements principal component analysis (PCA) along with XGBoost model. The PCA was implemented to the raw ECG signals which suppress redundancy information and extracted significant features. The obtained significant ECG features were fed into XGBoost model and the performance of the model was evaluated. In order to valid the proposed technique, raw ECG signals obtained from standard MIT-BIH database were employed for the analysis. The result shows that the performance of proposed method is superior to the several state-of-the-arts techniques.

Keywords: cardiac arrhythmia, electrocardiogram, principal component analysis, XGBoost

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Authors: Mais Khader, Xingjie Wei

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This research sheds light on female entrepreneurs by providing new insights on the survival predictions of companies led by females in the UK. This study aims to build a predictive machine learning model of the survival of female-led & co-led small & medium enterprises (SMEs) in the UK over the period 2000-2020. The predictive model built utilised a combination of financial and non-financial features related to both companies and their directors to predict SMEs' survival. These features were studied in terms of their contribution to the resultant predictive model. Five machine learning models are used in the modelling: Decision tree, AdaBoost, Naïve Bayes, Logistic regression and SVM. The AdaBoost model had the highest performance of the five models, with an accuracy of 73% and an AUC of 80%. The results show high feature importance in predicting companies' survival for company size, management experience, financial performance, industry, region, and females' percentage in management.

Keywords: company survival, entrepreneurship, females, machine learning, SMEs

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Authors: Ismail Celik, Ismail Sahin, Fetah Eren

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The computer, among the most important inventions of the twentieth century, has become an increasingly important component in our everyday lives. Computer games also have become increasingly popular among people day-by-day, owing to their features based on realistic virtual environments, audio and visual features, and the roles they offer players. In the present study, the metaphors students have for computer games are investigated, as well as an effort to fill the gap in the literature. Students were asked to complete the sentence—‘Computer game is like/similar to….because….’— to determine the middle school students’ metaphorical images of the concept for ‘computer game’. The metaphors created by the students were grouped in six categories, based on the source of the metaphor. These categories were ordered as ‘computer game as a means of entertainment’, ‘computer game as a beneficial means’, ‘computer game as a basic need’, ‘computer game as a source of evil’, ‘computer game as a means of withdrawal’, and ‘computer game as a source of addiction’, according to the number of metaphors they included.

Keywords: computer game, metaphor, middle school students, virtual environments

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Authors: Alagie Salieu Nankey

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Flood-resistant house is the key mechanism to withstand flood hazards in Ebo-Town. It emerged simple yet powerful way of mitigating flooding in the community of Ebo- Town. Even though there are different types of buildings, little is known yet how and why flood affects building severely. In this paper, we examine three different types of flood-resistant buildings that are suitable for Ebo Town. We gather content and contextual features from six (6) respondents and used this data set to identify factors that are significantly associated with the flood-resistant house. Moreover, we built a suitable design concept. We found that amongst all the theories studied in the literature study Slit or Elevated House is the most suitable building design in Ebo-Town and Pile foundation is the most appropriate foundation type in the study area. Amongst contextual features, local materials are the most economical materials for the proposed design. This research proposes a framework that explains the theoretical relationships between flood hazard zones and flood-resistant houses in Ebo Town. Moreover, this research informs the design of sense-making and analytics tools for the resistant house.

Keywords: flood-resistant, slit, flood hazard zone, pile foundation

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Authors: Liana Lortkipanidze, Nino Amirezashvili, Nino Javashvili

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The purpose of the grammatical dictionary is to provide information on the morphological and syntactic characteristics of the basic word in the dictionary entry. The electronic grammatical dictionaries are used as a tool of automated morphological analysis for texts processing. The Georgian Grammatical Dictionary should contain grammatical information for each word: part of speech, type of declension/conjugation, grammatical forms of the word (paradigm), alternative variants of basic word/lemma. In this paper, we present the system for compiling the Georgian Grammatical Dictionary automatically. We propose dictionary-based methods for extending grammatical lexicons. The input lexicon contains only a few number of words with identical grammatical features. The extension is based on similarity measures between features of words; more precisely, we add words to the extended lexicons, which are similar to those, which are already in the grammatical dictionary. Our dictionaries are corpora-based, and for the compiling, we introduce the method for lemmatization of unknown words, i.e., words of which neither full form nor lemma is in the grammatical dictionary.

Keywords: acquisition of lexicon, Georgian grammatical dictionary, lemmatization rules, morphological processor

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Authors: Daniel Murrant, Andrew Quinn, Lee Chapman

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A growing population has led to increasing global water and energy demand. This demand, combined with the effects of climate change and an increasing need to maintain and protect the natural environment, represents a potentially severe threat to many national infrastructure systems. This has resulted in a considerable quantity of published material on the interdependencies that exist between the supply of water and the thermal generation of electricity, often known as the water-energy nexus. Focusing specifically on the UK, there is a growing concern that the future availability of water may at times constrain thermal electricity generation, and therefore hinder the UK in meeting its increasing demand for a secure, and affordable supply of low carbon electricity. To provide further information on the threat the water-energy nexus may pose to the UK’s energy system, this paper models the regional water demand of UK thermal electricity generation in 2030 and 2050. It uses the strategically important Energy Systems Modelling Environment model developed by the Energy Technologies Institute. Unlike previous research, this paper was able to use abstraction and consumption factors specific to UK power stations. It finds that by 2050 the South East, Yorkshire and Humber, the West Midlands and North West regions are those with the greatest freshwater demand and therefore most likely to suffer from a lack of resource. However, it finds that by 2050 it is the East, South West and East Midlands regions with the greatest total water (fresh, estuarine and seawater) demand and the most likely to be constrained by environmental standards.

Keywords: climate change, power station cooling, UK water-energy nexus, water abstraction, water resources

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Authors: Mehtab Alam, Mudiarasan Kuppusamy

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Image branding is the prominent and well-guided phenomena of managing tourism destinations. It examines the image of cities forming as brand identity. Transformation of cities into tourist destinations is obligatory for the current management practices to be used for foreign policy. The research considers the features of perception, destination accommodation, destination quality, traveler revisit, destination information system, and behavioral image for tourism destination management. Using the quantitative and qualitative research methodology, the objective is to examine and investigate the opportunities for destination branding. It investigates the features and management of tourism destinations in Abbottabad city of Pakistan through SPSS and NVivo 12 software. The prospective outlook of the results and coding reflects the significant contribution of integrated destination management for image branding, where Abbottabad has the potential to become a destination city. The positive impact of branding integrates tourism management as it is fulfilling travelers’ requirements to influence the choice of destination for innovative foreign policy.

Keywords: image branding, destination management, tourism, foreign policy, innovative

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Authors: Tamar Arieli

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Cross-border cooperation has long been hailed as a means for stabilizing and normalizing relations between former enemies. Cooperation in problem-solving and realizing of local interests in post-conflict environments can indeed serve as a basis for developing dialogue and meaningful relations between neighbors across borders. Hence the potential for formerly sealed borders to serve as a basis for generating local and national perceptions of interdependence and as a buffer against the resume of conflict. Central questions which arise for policy-makers and third parties are how to facilitate cross-border cooperation and which areas of cooperation best serve to normalize post-conflict border regions. The Israel-Jordan border functions as a post-conflict border, in that it is a peaceful border since the 1994 Israel-Jordan peace treaty yet cross-border relations are defined but the highly securitized nature of the border region and the ongoing Arab-Israel regional conflict. This case study is based on long term qualitative research carried out in the border regions of both Israel and Jordan, which mapped and analyzed cross-border in a wide range of activities – social interactions sponsored by peace-facilitating NGOs, government sponsored agricultural cooperation, municipal initiated emergency planning in cross-border continuous urban settings, private cross-border business ventures and various environmental cooperative initiatives. These cooperative initiatives are evaluated through multiple interviews carried out with initiators and partners in cross-border cooperation as well as analysis of documentation, funding and media. These cooperative interactions are compared based on levels of cross-border local and official awareness and involvement as well as sustainability over time. This research identifies environmental cooperation as the most sustainable area of cross- border cooperation and as most conducive to generating perceptions of regional interdependence. This is a variation to the ‘New Middle East’ vision of business-based cooperation leading to conflict amelioration and regional stability. Environmental cooperation serving the public good rather than personal profit enjoys social legitimization even in the face of widespread anti-normalization sentiments common in the post-conflict environment. This insight is examined in light of philosophical and social aspects of the natural environment and its social perceptions. This research has theoretical implications for better understanding dynamics of cooperation and conflict, as well as practical ramifications for practitioners in border region policy and management.

Keywords: borders, cooperation, post-conflict, security

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Authors: Friba Haidari

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The aim of the study is to identify Russia's role in managing the Nagorno-Karabakh conflict betweenArmenia and Azerbaijan during the years 1990 to 2020. The Nagorno-Karabakh crisis can not be considered a mere territorial conflict but also a crossroads of interests of foreign actors. Geopolitical rivalries and the access to energy by regional and trans-regional actors have complicated the crisis and created a security challenge in the region, which is likely to escalate into a full-blown war between the parties involved. The geopolitical situation of Nagorno-Karabakh and its current situation have affected all peripheral states in some way. Russia, as one of the main actors in this scene, has been actively involved since the beginning of the crisis. The Russians have always sought to strengthen their influence and presence in the Nagorno-Karabakh crisis. Russia's efforts to weaken the role of the Minsk Group, The presence of Western actors, and the deployment of Russian forces in the disputed area can be assessed in this context. However, this study seeks to answer the question of what role did Russia play in managing the Nagorno-Karabakh conflict between Armenia and Azerbaijan between 1990 and 2020? The study hypothesizes that Russia has prevented the escalation of the Nagorno-Karabakh conflict through mediation and some coercion. This study is divided into four parts, including conflict management as a theoretical framework; Examining the competition and the role of actors in the Caucasus region, especially the role of the Minsk Group, and what approach or tools and methods Russia has used in its foreign policy in managing the conflict, and finally what are the relations between the countries involved and what will be Russia's role in the future? Was discussed. This study examines the analysis and transfer of ideas and information using authoritative international sources with an explanatory method and shares its results with everyone.

Keywords: Russia, conflict, nagorno-karabakh, management

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Authors: Sandeep J. Kumar

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Urbanisation is considered as the primary driver of land use and land cover change that has direct link to population and economic growth. In India, as well as in other developing countries, cities are urbanizing at an alarming rate. This unprecedented and uncontrolled urbanisation can result in urban sprawl. Due to a number of factors, urban sprawl is recognised to be a result of poor planning, inadequate policies, and poor governance. Urban sprawl may be seen as posing a threat to the development of sustainable cities. Hence, it is very essential to manage this. Planning for predicted future growth is critical to avoid the negative effects of urban growth at the local and regional levels. Thiruvananthapuram being the capital city of Kerala is a city of economic success, challenges, and opportunities. Urbanization trends in the city have paved way for Urban Sprawl. This thesis aims to formulate a framework to combat the emerging urban sprawl in the city of Thiruvananthapuram. For that, the first step was to quantify trends of urban growth in Thiruvananthapuram city using Geographical Information System(GIS) and remote sensing techniques. The technique and results obtained in the study are extremely valuable in analysing the land use changes. Secondly, these change in the trends were analysed through some of the critical factors that helped the study to understand the underlying issues of the existing city structure that has resulted in urban sprawl. Anticipating development trends can modify the current order. This can be productively resolved using regional and municipal planning and management strategies. Hence efficient strategies to curb the sprawl in Thiruvananthapuram city have been formulated in this study that can be considered as recommendations for future planning.

Keywords: urbanisation, urban sprawl, geographical information system(GIS), thiruvananthapuram

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Authors: Noura Al Akkari, Aurélie Foucquier, Sylvain Lespinats

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Load monitoring is a management process for energy consumption towards energy savings and energy efficiency. Non Intrusive Load Monitoring (NILM) is one method of load monitoring used for disaggregation purposes. NILM is a technique for identifying individual appliances based on the analysis of the whole residence data retrieved from the main power meter of the house. Our NILM framework starts with data acquisition, followed by data preprocessing, then event detection, feature extraction, then general appliance modeling and identification at the final stage. The event detection stage is a core component of NILM process since event detection techniques lead to the extraction of appliance features. Appliance features are required for the accurate identification of the household devices. In this research work, we aim at developing a new event detection methodology with accurate load disaggregation to extract appliance features. Time-domain features extracted are used for tuning general appliance models for appliance identification and classification steps. We use unsupervised algorithms such as Dynamic Time Warping (DTW). The proposed method relies on detecting areas of operation of each residential appliance based on the power demand. Then, detecting the time at which each selected appliance changes its states. In order to fit with practical existing smart meters capabilities, we work on low sampling data with a frequency of (1/60) Hz. The data is simulated on Load Profile Generator software (LPG), which was not previously taken into consideration for NILM purposes in the literature. LPG is a numerical software that uses behaviour simulation of people inside the house to generate residential energy consumption data. The proposed event detection method targets low consumption loads that are difficult to detect. Also, it facilitates the extraction of specific features used for general appliance modeling. In addition to this, the identification process includes unsupervised techniques such as DTW. To our best knowledge, there exist few unsupervised techniques employed with low sampling data in comparison to the many supervised techniques used for such cases. We extract a power interval at which falls the operation of the selected appliance along with a time vector for the values delimiting the state transitions of the appliance. After this, appliance signatures are formed from extracted power, geometrical and statistical features. Afterwards, those formed signatures are used to tune general model types for appliances identification using unsupervised algorithms. This method is evaluated using both simulated data on LPG and real-time Reference Energy Disaggregation Dataset (REDD). For that, we compute performance metrics using confusion matrix based metrics, considering accuracy, precision, recall and error-rate. The performance analysis of our methodology is then compared with other detection techniques previously used in the literature review, such as detection techniques based on statistical variations and abrupt changes (Variance Sliding Window and Cumulative Sum).

Keywords: general appliance model, non intrusive load monitoring, events detection, unsupervised techniques;

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Authors: Emery Jr. Coppola

Abstract:

Water resources are being depleted and degraded at an alarming and non-sustainable rate worldwide. In some areas, it is progressing more slowly. In other areas, irreversible damage has already occurred, rendering regions largely unsuitable for human existence with destruction of the environment and the economy. Today, 2.5 billion people or 36 percent of the world population live in water-stressed areas. The convergence of factors that created this global water crisis includes local, regional, and global failures. In this paper, a survey of some of these factors is presented. They include abuse of political power and regulatory acquiescence, improper planning and design, ignoring good science and models, systemic failures, and division between the powerful and the powerless. Increasing water demand imposed by exploding human populations and growing economies with short-falls exacerbated by climate change and continuing water quality degradation will accelerate this growing water crisis in many areas. Without regional measures to improve water efficiencies and protect dwindling and vulnerable water resources, environmental and economic displacement of populations and conflict over water resources will only grow. Perhaps more challenging, a global commitment is necessary to curtail if not reverse the devastating effects of climate change. Factors will be illustrated by real-world examples, followed by some partial solutions offered by water experts for helping to mitigate the growing water crisis. These solutions include more water efficient technologies, education and incentivization for water conservation, wastewater treatment for reuse, and improved data collection and utilization.

Keywords: climate change, water conservation, water crisis, water technologies

Procedia PDF Downloads 224

Authors: Abdelazeem Algammal, Reham Abouelmaatti, Xiaokun Li, Jisheng Ma, Eman Abdelnaby, Wael Elfeil

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Toll-like receptors (TLRs) are the best understood of the innate immune receptors that detect infections in vertebrates. However, the fish TLRs also exhibit very distinct features and a large diversity, which is likely derived from their diverse evolutionary history and the distinct environments that they occupy. Little is known about the fish immune system structure. Our work was aimed to identify and clone the Nile tilapiaTLR-3 as a model of freshwater fish species; we cloned the full-length cDNA sequence of Nile tilapia (Oreochromis niloticus) TLR-3 and according to our knowledge, it is the first report illustrating tilapia TLR-3. The complete cDNA sequence of Nile tilapia TLR-3 was 2736 pair base and it encodes a polypeptide of 912 amino acids. Analysis of the deduced amino acid sequence indicated that Nile tilapia TLR-3 has typical structural features and main components of proteins belonging to the TLR family. Our results illustrate a complete and functional Nile tilapia TLR-3 and it is considered an ortholog of the other vertebrate’s receptor.

Keywords: Nile tilapia, TLR-3, cloning, gene expression

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Authors: H. Zidoum, A. AlShareedah, S. Al Sawafi, A. Al-Ansari, B. Al Lawati

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Systemic lupus erythematosus (SLE) is an autoimmune disease with genetic and environmental components. SLE is characterized by a wide variability of clinical manifestations and a course frequently subject to unpredictable flares. Despite recent progress in classification tools, the early diagnosis of SLE is still an unmet need for many patients. This study proposes an interpretable disease classification model that combines the high and efficient predictive performance of CatBoost and the model-agnostic interpretation tools of Shapley Additive exPlanations (SHAP). The CatBoost model was trained on a local cohort of 219 Omani patients with SLE as well as other control diseases. Furthermore, the SHAP library was used to generate individual explanations of the model's decisions as well as rank clinical features by contribution. Overall, we achieved an AUC score of 0.945, F1-score of 0.92 and identified four clinical features (alopecia, renal disorders, cutaneous lupus, and hemolytic anemia) along with the patient's age that was shown to have the greatest contribution on the prediction.

Keywords: feature selection, classification, systemic lupus erythematosus, model interpretation, SHAP, Catboost

Procedia PDF Downloads 66

Authors: Sujata Kulkarni, Udhav Bhosle, Vijaykumar T.

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Due to the closeness between seismic signals and non-seismic signals, it is vital to detect earthquakes using conventional methods. In order to distinguish between seismic events and non-seismic events depending on their amplitude, our study processes the data that come from seismic sensors. The authors suggest a robust noise suppression technique that makes use of a bandpass filter, an IIR Wiener filter, recursive short-term average/long-term average (STA/LTA), and Carl short-term average (STA)/long-term average for event identification (LTA). The trigger ratio used in the proposed study to differentiate between seismic and non-seismic activity is determined. The proposed work focuses on significant feature extraction for machine learning-based seismic event detection. This serves as motivation for compiling a dataset of all features for the identification and forecasting of seismic signals. We place a focus on feature vector dimension reduction techniques due to the temporal complexity. The proposed notable features were experimentally tested using a machine learning model, and the results on unseen data are optimal. Finally, a presentation using a hybrid dataset (captured by different sensors) demonstrates how this model may also be employed in a real-time setting while lowering false alarm rates. The planned study is based on the examination of seismic signals obtained from both individual sensors and sensor networks (SN). A wideband seismic signal from BSVK and CUKG station sensors, respectively located near Basavakalyan, Karnataka, and the Central University of Karnataka, makes up the experimental dataset.

Keywords: Carl STA/LTA, features extraction, real time, dataset, machine learning, seismic detection

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Authors: S. D. Abdul, F. B. J. Sawa, D. Z. Andrawus, G. Dan'ilu

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Fresh leaves of twelve accessions of S. indicum were studied to examine their stomatal features, trichomes, epidermal cell shapes and anticlinal cell-wall patterns which may be used for the delimitation of the varieties. The twelve accessions of S. indicum studied have amphistomatic leaves, i.e. having stomata on both surfaces. Four types of stomatal complex types were observed namely, diacytic, anisocytic, tetracytic and anomocytic. Anisocytic type was the most common occurring on both surfaces of all the varieties and occurred 100% in varieties lale-duk, ex-sudan and ex-gombe 6. One-way ANOVA revealed that there was no significant difference between the stomatal densities of ex-gombe 6, ex-sudan, adawa-wula, adawa-ting, ex-gombe 4 and ex-gombe 2 . Accession adawa-ting (improved) has the smallest stomatal size (26.39µm) with highest stomatal density (79.08mm2) while variety adawa-wula possessed the largest stomatal size (74.31µm) with lowest stomatal density (29.60mm2), the exception was found in variety adawa-ting whose stomatal size is larger (64.03µm) but with higher stomatal density (71.54mm2). Wavy, curve or undulate anticlinal wall patterns with irregular and or isodiametric epidermal cell shapes were observed. These accessions were found to exhibit high degree of heterogeneity in their trichome features. Ten types of trichomes were observed: unicellular, glandular peltate, capitate glandular, long unbranched uniseriate, short unbranched uniseriate, scale, multicellular, multiseriate capitate glandular, branched uniseriate and stallate trichomes. The most frequent trichome type is short-unbranched uniseriate, followed by long-unbranched uniseriate (72.73% and 72.5%) respectively. The least frequent was multiseriate capitate glandular (11.5%). The high variation in trichome types and density coupled with the stomatal complex types suggest that these varieties of S. indicum probably have the capacity to conserve water. Furthermore, the leaf micromorphological features varied from one accession to another, hence, are found to be good diagnostic and additional tool in identification as well as nomenclature of the accessions of S. indicum.

Keywords: Sesamum indicum, stomata, trichomes, epidermal cells, taxonomy

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Authors: S. Vignesh, N. Vishnu, S. Vigneshwaran, M. Vishnu Anand, Dinesh Kumar Babu, V. R. Sanal Kumar

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The study of the primary flow velocity and the self impinging secondary jet flow mixing is important from both the fundamental research and the application point of view. Real industrial configurations are more complex than simple shear layers present in idealized numerical thrust-vectoring models due to the presence of combustion, swirl and confinement. Predicting the flow features of self impinging secondary jets in a supersonic primary flow is complex owing to the fact that there are a large number of parameters involved. Earlier studies have been highlighted several key features of self impinging jets, but an extensive characterization in terms of jet interaction between supersonic flow and self impinging secondary sonic jets is still an active research topic. In this paper numerical studies have been carried out using a validated two-dimensional k-omega standard turbulence model for the design optimization of a thrust vector control system using shock induced self impinging secondary flow sonic jets using non-reacting flows. Efforts have been taken for examining the flow features of TVC system with various secondary jets at different divergent locations and jet impinging angles with the same inlet jet pressure and mass flow ratio. The results from the parametric studies reveal that in addition to the primary to the secondary mass flow ratio the characteristics of the self impinging secondary jets having bearing on an efficient thrust vectoring. We concluded that the self impinging secondary jet nozzles are better than single jet nozzle with the same secondary mass flow rate owing to the fact fixing of the self impinging secondary jet nozzles with proper jet angle could facilitate better thrust vectoring for any supersonic aerospace vehicle.

Keywords: fluidic thrust vectoring, rocket steering, supersonic to sonic jet interaction, TVC in aerospace vehicles

Procedia PDF Downloads 576