Search results for: learning strategies

Authors: Asanka Bulathwatta

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This Study tries to figure out the role of emotional Intelligence for developing coping strategies among adolescents who face traumatic events. Late adolescence students who have enrolled into the University education (Bachelor students/first-year students) would be selected as the sample. University education is an important stage of students’ academic life. Therefore, all students need to develop their competencies to attain the goal of passing examinations and also to developing their wisdom related to the scientific knowledge they gathered through their academic life. Study to be conducted in a cross-cultural manner and it will be taking place in Germany and Sri Lanka. The sample will be consisting of 200 students from each country. Late adolescence is a critical period of the human being as it is foot step in their life which acquiring the emotional and social qualities in their social life. There are many adolescents who have affected by aggression related traumatic events during their lifespan but have not been identified or treated. More specifically, there are numerous burning issues within the first year of the university students namely, ragging done by seniors to juniors, bulling, invalidation and issues raise based on attitudes changes and orientation issues. Those factors can be traumatic for both their academic and day to day lifestyle. Identifying the students who are with emotional damages and their resiliency afterward the aggression related traumas and effective rehabilitation from the traumatic events is immensely needed in order to facilitate university students for their academic achievements and social life within the University education. Research findings in Germany show that students shows more interpersonal traumas, life-threatening illnesses and death of someone related are common in German sample.

Keywords: emotional intelligence, agression, trauma, coping

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Authors: Poom Thiparapkul, Tanat Jiravansirikul, Pakpoom Thongsari

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This study explores the design of electric vehicle (EV) dashboards with a focus on user interaction. Findings from a Thai sample reveal a preference for physical buttons over touch interfaces due to their immediate feedback. Touchscreens lack this assurance, leading to potential uncertainty. Users' smartphone experiences create a learning curve that doesn't translate well to in-car touch systems. Gender-wise, females exhibit slightly longer decision times. Designing EV dashboards should consider these factors, prioritizing user experience while avoiding overreliance on smartphone principles. A successful example is Subaru XV's design, which calculates screen angles and button positions for targeted users. In summary, EV dashboards should be intuitive, minimize touch dependency, and accommodate user habits. Balancing modernity with functionality can enhance driving experiences while ensuring safety. A user-centered approach, acknowledging gender differences, will yield efficient and safe driving environments.

Keywords: user experience design, user experience, electric vehicle, dashboard design, Thailand driver.

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Authors: Khaled M. Alhawiti

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Reading capability is a major segment of language competency. On the other hand, discovering topical writings at a fitting level for outside and second language learners is a test for educators. We address this issue utilizing natural language preparing innovation to survey reading level and streamline content. In the connection of outside and second-language learning, existing measures of reading level are not appropriate to this errand. Related work has demonstrated the profit of utilizing measurable language preparing procedures; we expand these thoughts and incorporate other potential peculiarities to measure intelligibility. In the first piece of this examination, we join characteristics from measurable language models, customary reading level measures and other language preparing apparatuses to deliver a finer technique for recognizing reading level. We examine the execution of human annotators and assess results for our finders concerning human appraisals. A key commitment is that our identifiers are trainable; with preparing and test information from the same space, our finders beat more general reading level instruments (Flesch-Kincaid and Lexile). Trainability will permit execution to be tuned to address the needs of specific gatherings or understudies.

Keywords: natural language processing, trainability, syntactic simplification tools, education

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Authors: Mthiyane Pretty, Mitsui Toshiake, Aycan Murat, Nagano Hirohiko

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Methane (CH₄) is one of the most dangerous greenhouse gases (GHG) emitted into the atmosphere by terrestrial ecosystems, with a global warming potential (GWP) 25-34 times that of CO2 on a centennial scale. Paddy rice cultivations are a major source of methane emission and is the major driving force for climate change. Thus, it is necessary to find out GHG emissions mitigation strategies from rice cultivation. A study was conducted at Niigata University. And the prime objective of this research was to determine the effects of rice varieties CH4 lowland (NU1, YNU, Nipponbare, Koshihikari) and upland (Norin 1, Norin 24, Hitachihatamochi) japonica rice varieties using different growth media which was paddy field soil and artificial soil. The treatments were laid out in a split plot design. The soil moisture was kept at 40-50% and 70%, respectively. The CH₄ emission rates were determined by collecting air samples using the closed chamber technique and measuring CH₄ concentrations using a gas chromatograph. CH₄ emission rates varied with the growth, growth media type and development of the rice varieties. The soil moisture was monitored at a soil depth of 5–10 cm with an HydraGO portable soil sensor system every three days for each pot, and temperatures were be recorded by a sensitive thermometer. The lowest cumulative CH4 emission rate was observed in Norin 24, particularly under 40 to 50% soil moisture. Across the rice genotypes, 40-50% significantly reduced the cumulative CH4 , followed by irrigation of 70% soil moisture. During the tillering stage, no significant variation in tillering and plant height was observed between and 70% soil moisture. This study suggests that the cultivation of Norin 24 and Norin 1 under 70% soil irrigation could be effective at reducing the CH4 in rice fields.

Keywords: methane, paddy fields, rice varieties, soil moisture

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Authors: Promise Ekpo Osaine, Daniel Melesse

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Image captioning is an active area of research in the multi-modal artificial intelligence (AI) community as it connects vision and language understanding, especially in settings where it is required that a model understands the content shown in an image and generates semantically and grammatically correct descriptions. In this project, we followed a standard approach to a deep learning-based image captioning model, injecting architecture for the encoder-decoder setup, where the encoder extracts image features, and the decoder generates a sequence of words that represents the image content. As such, we investigated image encoders, which are ResNet101, InceptionResNetV2, EfficientNetB7, EfficientNetV2M, and CLIP. As a caption generation structure, we explored long short-term memory (LSTM). The CLIP-LSTM model demonstrated superior performance compared to the encoder-decoder models, achieving a BLEU-1 score of 0.904 and a BLEU-4 score of 0.640. Additionally, among the CNN-LSTM models, EfficientNetV2M-LSTM exhibited the highest performance with a BLEU-1 score of 0.896 and a BLEU-4 score of 0.586 while using a single-layer LSTM.

Keywords: multi-modal AI systems, image captioning, encoder, decoder, BLUE score

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Authors: Asli Yagmur Akbulut

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Despite a robust and growing job market and lucrative salaries, there is a global shortage of Information Technology (IT) professionals. To make matters worse, women continue to be underrepresented in the IT workforce and among IT degree holders. In today’s knowledge based economy and society, it is extremely important to increase the presence of women in the IT field. In order to do so, it is necessary to reduce entry barriers and attract more women to pursue degrees in various IT fields including the field of Management Information Systems (MIS). Even though MIS is considered to have a more feminine nature, women still tend to avoid majoring in this field. Unfortunately, there is a lack of research that investigates the specific factors that may deter women from pursuing a degree in MIS. To address this research gap, this study examined a set of key environmental barriers that might prevent women from pursuing an MIS degree and explored whether there were any gender differences between female and male students in terms of these key barriers. Based on a survey of 280 students enrolled in an introductory level MIS course, the study empirically confirmed that there were significant differences between male and female students in terms of the key contextual barriers perceived. Female students demonstrated major concerns about gender discrimination related barriers, whereas male students were more concerned about negative social influences. Both male and female students were equally concerned about not being able to fit in well with other MIS majors. The findings have important implications for MIS programs, as the information gained can be used to design and implement specific intervention strategies to overcome the barriers and attract larger pools of women to the MIS discipline. The paper concludes with a discussion of the findings, implications, and future research directions.

Keywords: gender differences, MIS major, underrepresentation, women in IT

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Authors: Watcharapong Yaowarat, Thanee Kaewthummanukul, Waruntorn Jongrungrotsakul

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Noise-induced hearing loss, the most significant occupational and safety problem among the working population, can be effectively prevented through hearing protection devices (HPDs) use. This study aimed to examine whether the following factors, perceived benefits, perceived barriers, perceived self-efficacy, and interpersonal and situational influences about using hearing protection could predict HPD use among 132 qualified workers in production lines at Kaolin Mineral Dressing factories, Uttaradit and Lampang provinces. Data collection was undertaken from August to September 2020 according to the interview form developed by Yaruang et al. (2010), which was assured by a panel of experts and its reliability value was at an acceptable level. Data analysis was performed using logistic regression analysis. The results revealed that only the situational factor of using hearing protection could predict HPD use, which accounted for 21.80 percent of the total variance for HPD use. It was also found that the study sample who had a score for the situational factors on using hearing protection greater than or equal to the median was 4.16 times more likely to use HPDs than those who had lower median scores. (OR = 4.16, p < .05). The results, thus, indicate that organization policies addressing worker health along with enhancing a supportive environment for HPD use, in particular, the provision of various HPDs, are of great importance. Therefore, occupational health nurses and related health teams should enhance workers’ use of HPDs effectively through knowledge dissemination by adopting strategies appropriate to the workplace context leading to an achievement of worker health policy focusing on work safety.

Keywords: predicting factors, hearing protection device, factors predicting hearing protection device use, kaolin mineral dressing factories

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Authors: Engku Haliza Engku Ibrahim, Isarji Sarudin, Ainon Jariah Muhamad

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It is generally agreed that many factors contribute to one’s reading comprehension and there is consensus that vocabulary size one of the main factors. This study explores the relationship between second language learners’ vocabulary size and their reading comprehension scores. 130 Malay pre-university students of a public university participated in this study. They were students of an intensive English language programme doing preparatory English courses to pursue bachelors degree in English. A quantitative research method was employed based on the Vocabulary Levels Test by Nation (1990) and the reading comprehension score of the in-house English Proficiency Test. A review of the literature indicates that a somewhat positive correlation is to be expected though findings of this study can only be explicated once the final analysis has been carried out. This is an ongoing study and it is anticipated that results of this research will be finalized in the near future. The findings will help provide beneficial implications for the prediction of reading comprehension performance. It also has implications for the teaching of vocabulary in the ESL context. A better understanding of the relationship between vocabulary size and reading comprehension scores will enhance teachers’ and students’ awareness of the importance of vocabulary acquisition in the L2 classroom.

Keywords: vocabulary size, vocabulary learning, reading comprehension, ESL

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Authors: K. Nagaz, F. El Mokh, M. Masmoudi, N. Ben Mechlia, M. O. Baba Sy, G. Ghiglieri

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Field experiments on deficit irrigation (DI) were performed in Médenine, Tunisia on drip-irrigated olive, orange and grapevine orchards during 2013 and 2014. Four irrigation treatments were compared: full irrigation (FI), which was irrigated at 100% of ETc for the whole season; two deficit irrigation (DI) strategies -DI75 and DI50- which received, respectively, 25 and 50% less water than FI; and traditional farming management (FM) - with water input much less than actually needed. The traditional farming (FM) applied 11, 18, 30 and 33% less water than the FI treatment, respectively, in orange, grapevine and table and oil olive orchards, indicating that the farmers practices represent a form of unintended deficit irrigation. Yield was reduced when deficit irrigation was applied and there were significant differences between DI75, DI50 and FM treatments. Significant differences were not observed between DI50 and FM treatments even though numerically smaller yield was observed in the former (DI50) as compared to the latter (FM). The irrigation water productivity (IWP) was significantly affected by irrigation treatments. The smallest IWP was recorded under the FI treatment, while the largest IWP was obtained under the deficit irrigation treatment (DI50). The DI50 and FM treatments reduced the economic return compared to the full treatment (FI), while the DI75 treatment resulted in a better economic return in respect to DI50 and FM. Full irrigation (FI) could be recommended for olive, orange and grapevine irrigation under the arid climate of Tunisia. Nevertheless, the treatment DI75 can be applied as a strategy under water scarcity conditions in commercial olive, orange and grapevine orchards allowing water savings up to 25% but with some reduction in yield and net return. The results would be helpful in adopting deficit irrigation in ways that enhance net financial returns.

Keywords: water productivity, deficit irrigation, drip irrigation, orchards

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Authors: Li Qingjian, Li Ke, He Chun, Huang Yong

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In this paper, the method of combining the Pohl Seidman's deep belief network with the self-organizing neural network is proposed to classify the target. This method is mainly aimed at the high nonlinearity of the hyperspectral image, the high sample dimension and the difficulty in designing the classifier. The main feature of original data is extracted by deep belief network. In the process of extracting features, adding known labels samples to fine tune the network, enriching the main characteristics. Then, the extracted feature vectors are classified into the self-organizing neural network. This method can effectively reduce the dimensions of data in the spectrum dimension in the preservation of large amounts of raw data information, to solve the traditional clustering and the long training time when labeled samples less deep learning algorithm for training problems, improve the classification accuracy and robustness. Through the data simulation, the results show that the proposed network structure can get a higher classification precision in the case of a small number of known label samples.

Keywords: DBN, SOM, pattern classification, hyperspectral, data compression

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Authors: K. Shimola, M. Krishnaveni

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This paper examines vulnerability assessment of water resources in a semi-arid basin using the 4-step approach. The vulnerability assessment framework is developed to study the water resources vulnerability which includes the creation of GIS-based vulnerability maps. These maps represent the spatial variability of the vulnerability index. This paper introduces the 4-step approach to assess vulnerability that incorporates a new set of indicators. The approach is demonstrated using a framework composed of a precipitation data for (1975–2010) period, temperature data for (1965–2010) period, hydrological model outputs and the water resources GIS data base. The vulnerability assessment is a function of three components such as exposure, sensitivity and adaptive capacity. The current water resources vulnerability is assessed using GIS based spatio-temporal information. Rainfall Coefficient of Variation, monsoon onset and end date, rainy days, seasonality indices, temperature are selected for the criterion ‘exposure’. Water yield, ground water recharge, evapotranspiration (ET) are selected for the criterion ‘sensitivity’. Type of irrigation and storage structures are selected for the criterion ‘Adaptive capacity’. These indicators were mapped and integrated in GIS environment using overlay analysis. The five sub-basins, namely Arjunanadhi, Kousiganadhi, Sindapalli-Uppodai and Vallampatti Odai, fall under medium vulnerability profile, which indicates that the basin is under moderate stress of water resources. The paper also explores prioritization of sub-basinwise adaptation strategies to climate change based on the vulnerability indices.

Keywords: adaptive capacity, exposure, overlay analysis, sensitivity, vulnerability

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Authors: Hameed Ullah, Karim Elakabawi, Han KE, Najeeb Ullah, Habib Ullah, Sardar Ali Shah, Hamad Haider Khan, Muhammad Asad Khan, Ning Guo, Zuyi Yuan

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Background: Predictors of decreased fractional flow reserve at left circumflex coronary artery after left main (LM) crossover stenting are still lacking. The objectives of the present study were to provide the predictors for low Fractional flow reserve (FFR) at coronary artery (LCx) and the possible treatment strategies for the compromised LCx-together with their long term outcomes. Methods: A total of 563 included patients out of 1974 patients admitted to our hospital from February 2015 to November 2020 with significant distal LM-bifurcation lesions. The enrolled patients underwent single-stent cross-over PCI under IVUS guidance with further LCx intervention as indicated by measured FFR. Results: The included patients showed angiographic significant LCx ostial affection after LM-stenting, but only 116 (20.6%) patients had FFR <0.8. The 3-year composite MACE rates were comparable between the high and low FFR groups (16.8% vs. 15.5%, respectively; P=0.744). In a multivariable analysis, a low FFR in the LCx was associated with post-stenting MLA of the LCx (OR: 0.032, P <0.001), post-stenting LCx-plaque burden (OR: 1.166, P <0.001), post-stenting LM-MLA (OR: 0.821, P =0.038) and pre-stenting LCx-MLA (OR: 0.371, P =0.044). In patients with low FFR, management of compromised LCx with DEB had the lowest 3-year MACE rate (8.1%) as compared to either KBI (17.5%) or stenting group (20.5%), P =0.299. Conclusion: FFR-guided LCx intervention can avoid unnecessary LCx intervention. The post-stenting predictors of low FFR include post-stenting MLA and plaque burden of the LCx and MV stent length. The 3-year MACE rates were comparable between high FFR patients and patients who had low FFR and were adequately managed.

Keywords: fractional flow reserve, left main stem, percutaneous coronary interventions, intravascular ultrasound

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Authors: Iván García-Magariño, Javier Bravo-Agapito, Marta López-Fernández

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Online judges have proven their utility in partial auto-evaluation of programming short exercises in the last decades. UnitJudge online judge has the advantage of facilitating the evaluation of separate units to provide more segregate and meaningful feedback to students in complex exercises and practices. This paper discusses the use of UnitUdge in advanced Java object-oriented programming exercises and web development practices. This later usage has been proposed by means of the Selenium Java library and classes to provide the web address. Consequently, UnitJudge is an online judge system that can be applied in several subjects, and therefore, many other students would take advantage of self-testing their exercises. This paper presents the experiments with a Java programming exercise for learning Java object-oriented classes with a generic type. Considering 10 students who voluntarily used UnitJudge, 80% successfully learned this concept, passing the judge exercise with correct results.

Keywords: online judges, programming skills, computer science education, auto-evaluation

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Authors: Solomon Sisay, Belete Mengistu, Woldargay Erku, Desalegne Woldeyohannes

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Background: Tuberculosis is still the leading cause of illness in the world which accounted for 2.5% of the global burden of disease, and 25% of all avoidable deaths in developing countries. Objectives: The aim of study was to assess impact of DOTS strategy on tuberculosis case finding and treatment outcome in Gambella Regional State, Ethiopia from 2003 up to 2012 and from 2002 up to 2011, respectively. Methods: Health facility-based retrospective study was conducted. Data were collected and reported in quarterly basis using WHO reporting format for TB case finding and treatment outcome from all DOTS implementing health facilities in all zones of the region to Federal Ministry of Health. Results: A total of 10024 all form of TB cases had been registered between the periods from 2003 up to 2012. Of them, 4100 (40.9%) were smear-positive pulmonary TB, 3164 (31.6%) were smear-negative pulmonary TB and 2760 (27.5%) had extra-pulmonary TB. Case detection rate of smear-positive pulmonary TB had increased from 31.7% to 46.5% from the total TB cases and treatment success rate increased from 13% to 92% with average mean value of being 40.9% (SD= 0.1) and 55.7% (SD=0.28), respectively for the specified year periods. Moreover, the average values of treatment defaulter and treatment failure rates were 4.2% and 0.3%, respectively. Conclusion: It is possible to achieve the recommended WHO target which is 70% of CDR for smear-positive pulmonary TB, and 85% of TSR as it was already been fulfilled the targets for treatments more than 85% from 2009 up to 2011 in the region. However, it requires strong efforts to enhance case detection rate of 40.9% for smear-positive pulmonary TB through implementing alternative case finding strategies.

Keywords: Gambella Region, case detection rate, directly observed treatment short-course, treatment success rate, tuberculosis

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Authors: P. S. Jagadeesh Kumar, Tracy Lin Huan, Rebecca K. Rossi, Yanmin Yuan, Xianpei Li

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The fiscal growth of any country hinges on the prudent administration of water resources. The river Yamuna and Ganga are measured as the life line of India as it affords the needs for life to endure. Earth observation over remote sensing images permits the precise description and identification of ingredients on the superficial from space and airborne platforms. Multiple and heterogeneous image sources are accessible for the same geographical section; multispectral, hyperspectral, radar, multitemporal, and multiangular images. In this paper, a taxonomical learning of the fluvial geomorphological features of river Yamuna and Ganga over doon valley using color fusion of multispectral remote sensing images was performed. Experimental results exhibited that the segmentation based colorization technique stranded on pattern recognition, and color mapping fashioned more colorful and truthful colorized images for geomorphological feature extraction.

Keywords: color fusion, geomorphology, fluvial processes, multispectral images, pattern recognition

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Authors: Krish Batra

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The advent of open banking has revolutionized the financial services industry by fostering innovation, enhancing customer experience, and promoting competition. However, this paradigm shift towards more open and interconnected banking ecosystems has introduced complex cybersecurity challenges. This research paper delves into the multifaceted cybersecurity landscape of open banking, highlighting the vulnerabilities and threats inherent in sharing financial data across a network of banks and third-party providers. Through a detailed analysis of recent data breaches, phishing attacks, and other cyber incidents, the paper assesses the current state of cybersecurity within the open banking framework. It examines the effectiveness of existing security measures, such as encryption, API security protocols, and authentication mechanisms, in protecting sensitive financial information. Furthermore, the paper explores the regulatory response to these challenges, including the implementation of standards such as PSD2 in Europe and similar initiatives globally. By identifying gaps in current cybersecurity practices, the research aims to propose a set of robust, forward-looking strategies that can enhance the security and resilience of open banking systems. This includes recommendations for banks, third-party providers, regulators, and consumers on how to mitigate risks and ensure a secure open banking environment. The ultimate goal is to provide stakeholders with a comprehensive understanding of the cybersecurity implications of open banking and to outline actionable steps for safeguarding the financial ecosystem in an increasingly interconnected world.

Keywords: open banking, financial services industry, cybersecurity challenges, data breaches, phishing attacks, encryption, API security protocols, authentication mechanisms, regulatory response, PSD2, cybersecurity practices

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Authors: Wei-Jong Yang, Wei-Hau Du, Pau-Choo Chang, Jar-Ferr Yang, Pi-Hsia Hung

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The demands of smart visual thing recognition in various devices have been increased rapidly for daily smart production, living and learning systems in recent years. This paper proposed a visual thing recognition system, which combines binary scale-invariant feature transform (SIFT), bag of words model (BoW), and support vector machine (SVM) by using color information. Since the traditional SIFT features and SVM classifiers only use the gray information, color information is still an important feature for visual thing recognition. With color-based SIFT features and SVM, we can discard unreliable matching pairs and increase the robustness of matching tasks. The experimental results show that the proposed object recognition system with color-assistant SIFT SVM classifier achieves higher recognition rate than that with the traditional gray SIFT and SVM classification in various situations.

Keywords: color moments, visual thing recognition system, SIFT, color SIFT

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Authors: Amanda Burrell, Tonia Gary, David Wright, Kumara Ward

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This paper explores the concept of academic identity as it relates to the lecture, in particular, the digitized lecture delivered to a camera, in the absence of a student audience. Many academics have the performance aspect of the role thrust upon them with little or no training. For the purpose of this study, we look at the performance of the academic identity and examine tailored film presence coaching for its contributions toward academic identity, specifically in relation to feelings of self-confidence and diminishment of discomfort or stage fright. The case is articulated through the lens of scholar-practitioners, using expert facilitated participatory action research. It demonstrates in our sample of experienced academics, all reported some feelings of uncertainty about presenting lectures to camera prior to coaching. We share how power poses and reframing fear, produced improvements in the ease and competency of all participants. We share exactly how this insight could be adapted for self-coaching by any academic when called to present to a camera and consider the relationship between this and academic identity.

Keywords: academic identity, digitized lecture, embodied learning, performance coaching

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Authors: Xiaolei Hu, Enrico Ferrera, Riccardo Tomasi, Claudio Pastrone

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Load Forecasting plays a key role in making today's and future's Smart Energy Grids sustainable and reliable. Accurate power consumption prediction allows utilities to organize in advance their resources or to execute Demand Response strategies more effectively, which enables several features such as higher sustainability, better quality of service, and affordable electricity tariffs. It is easy yet effective to apply Load Forecasting at larger geographic scale, i.e. Smart Micro Grids, wherein the lower available grid flexibility makes accurate prediction more critical in Demand Response applications. This paper analyses the application of short-term load forecasting in a concrete scenario, proposed within the EU-funded GreenCom project, which collect load data from single loads and households belonging to a Smart Micro Grid. Three short-term load forecasting techniques, i.e. linear regression, artificial neural networks, and radial basis function network, are considered, compared, and evaluated through absolute forecast errors and training time. The influence of weather conditions in Load Forecasting is also evaluated. A new definition of Gain is introduced in this paper, which innovatively serves as an indicator of short-term prediction capabilities of time spam consistency. Two models, 24- and 1-hour-ahead forecasting, are built to comprehensively compare these three techniques.

Keywords: short-term load forecasting, smart micro grid, linear regression, artificial neural networks, radial basis function network, gain

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Authors: Shu-Pin Huang, Pai-Chi Teng, Hao-Han Chang, Chia-Hsin Liu, Yung-Lun Lin, Shu-Chi Wang, Hsin-Chih Yeh, Chih-Pin Chuu, Jiun-Hung Geng, Li-Hsin Chang, Wei-Chung Cheng, Chia-Yang Li

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The emergence of immune checkpoint inhibitors (ICIs) targeting proteins like PD-1 and PD-L1 has changed the treatment paradigm of bladder cancer. However, not all patients benefit from ICIs, with some experiencing early death. There's a significant need for biomarkers associated with the PD-1 pathway in bladder cancer. Current biomarkers focus on tumor PD-L1 expression, but a more comprehensive understanding of PD-1-related biology is needed. Our study has developed a seven-gene risk score panel, employing a comprehensive bioinformatics strategy, which could serve as a potential prognostic and predictive biomarker for bladder cancer. This panel incorporates the FYN, GRAP2, TRIB3, MAP3K8, AKT3, CD274, and CD80 genes. Additionally, we examined the relationship between this panel and immune cell function, utilizing validated tools such as ESTIMATE, TIDE, and CIBERSORT. Our seven-genes panel has been found to be significantly associated with bladder cancer survival in two independent cohorts. The panel was also significantly correlated with tumor infiltration lymphocytes, immune scores, and tumor purity. These factors have been previously reported to have clinical implications on ICIs. The findings suggest the potential of a PD-1 pathway-based transcriptomic panel as a prognostic and predictive biomarker in bladder cancer, which could help optimize treatment strategies and improve patient outcomes.

Keywords: bladder cancer, programmed cell death protein 1, prognostic biomarker, immune checkpoint inhibitors, predictive biomarker

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Authors: Madhu Babu Cherukuri, Tamoghna Ghosh

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Factory supply chain management spends billions of dollars every year to procure and manage equipment spare parts. Due to technology -and processes changes some of these spares become obsolete/dead inventory. Factories have huge dead inventory worth millions of dollars accumulating over time. This is due to lack of a scientific methodology to identify them and send the inventory back to the suppliers on a timely basis. The standard approach followed across industries to deal with this is: if a part is not used for a set pre-defined period of time it is declared dead. This leads to accumulation of dead parts over time and these parts cannot be sold back to the suppliers as it is too late as per contract agreement. Our main idea is the time period for identifying a part as dead cannot be a fixed pre-defined duration across all parts. Rather, it should depend on various properties of the part like historical consumption pattern, type of part, how many machines it is being used in, whether it- is a preventive maintenance part etc. We have designed a predictive algorithm which predicts part obsolescence well in advance with reasonable accuracy and which can help save millions.

Keywords: obsolete inventory, machine learning, big data, supply chain analytics, dead inventory

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Authors: Mohd Aderi Che Noh, Tuan Rahayu Tuan Lasan

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Higher order thinking skills (HOTS) is an important skill in the Malaysian education system to produce a knowledgeable generation, able to think critically and creatively in order to face the challenges in the future. Educational challenges of the 21st century require that all students to have the HOTS. Therefore, this study aims to identify the level of knowledge, attitude and readiness of students towards HOTS. The respondents were 127 form four students from schools in the Federal Territory of Putrajaya. This study is quantitative survey using a questionnaire to collect data. Data were analyzed using Statistical Package for the Social Sciences (SPSS) 23.0. The results showed that knowledge, attitudes and readiness of students towards HOTS lam were at a high level. Inferential analysis showed that there was a significant relationship between knowledge with attitude and readiness towards HOTS. This study provides information to the schools and teachers to improve the teaching and learning to increase students HOTS and fulfilling the hope of Ministry of Education to produce human capital who can be globally competitive.

Keywords: high order thinking skills, teaching, education, Malaysia

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Authors: Amanat Ali, Muhammad S. Al-Siyabi, Mostafa I. Waly, Hashem Al-Kilani

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In a cross-sectional research design, we assessed the nutrient intake, nutritional status, nutritional knowledge and dietary habits of Sultan Qaboos University (SQU) student athletes. A total of 71 (49 male and 22 female) student athletes with a mean age of 21.0 ± 1.81 and 19.32 ± 0.72 years and body mass index (BMI) of 22.51 ± 1.98 and 20.34 ± 2.97 kg/m2 for male and female respectively, participated in this study. A study questionnaire consisting of 2 sections was distributed to the participants. Section I included 18 questions regarding the demographic information, whereas the Section II consisted of 20 questions regarding the nutrition knowledge. The dietary intake of participants was collected by using a 7-days food diary identifying the frequency as well as the variety of food consumption. Significant differences (P < 0.05) were observed in the main sources of nutrition information used by the male and female athletes. Male athletes mainly had most of the nutrition information from friends (17%) whereas female athletes relied mainly on the family (20%). More female athletes (20%) were using TV as a source of nutrition information as compared to male athletes (15%). Both male and female athletes had the minimum nutrition information from dietitians and physicians. Significant (P < 0.05) differences were also observed in the nutritional knowledge and dietary habits scores of male and female athletes, which were 57 % and 49 %, respectively. Male athletes were classified to have fair nutritional knowledge and dietary habits, whereas the female athletes had poor nutritional knowledge and dietary habits. The average daily energy intake of male athletes was 2595 ± 358 kcal/day. Carbohydrate, fat, and protein contributed 64%, 22%, and 14%, of the total energy intake for the male athletes, respectively. The energy and macronutrients intake of male athletes was within the recommended dietary intake. The results indicated some gaps in the nutritional knowledge of SQU student athletes and suggest that there is a need for developing strategies in counseling and teaching the athletes to improve their nutritional knowledge and dietary habits.

Keywords: nutrient assessment, nutritional knowledge, dietary habits, Omani University athletes

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Authors: Hadjer Didouh, Izzaddine Sameut Bouhaik, Mohammed Hadj Meliani

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This research delves into the intricate dynamics of biofilm adhesion on surfaces, particularly focusing on the widely employed X52 surface in oil and gas industry pipelines. Biofilms, characterized by microorganisms within a self-produced matrix, pose significant challenges due to their detrimental impact on surfaces. Our study integrates advanced molecular techniques and cutting-edge microscopy, such as scanning electron microscopy (SEM), to identify microbial communities and visually assess biofilm adhesion. Simultaneously, we concentrate on the X52 surface, utilizing impedance spectroscopy and potentiodynamic polarization to gather electrochemical responses under various conditions. In conjunction with the broader investigation, we propose a novel approach to mitigate biofilm-induced corrosion challenges. This involves environmentally friendly inhibitors derived from plants, offering a sustainable alternative to conventional chemical treatments. Our inquiry screens and selects inhibitors based on their efficacy in hindering biofilm formation and reducing corrosion rates on the X52 surface. This study contributes valuable insights into the interplay between electrochemical processes and biofilm attachment on the X52 surface. Furthermore, the outcomes of this research have broader implications for the oil and gas industry, where biofilm-related corrosion is a persistent concern. The exploration of eco-friendly inhibitors not only holds promise for corrosion control but also aligns with environmental considerations and sustainability goals. The comprehensive nature of this research aims to enhance our understanding of biofilm dynamics, provide effective strategies for corrosion mitigation, and contribute to sustainable practices in pipeline management within the oil and gas sector.

Keywords: bio-corrosion, biofilm, attachment, X52, metal/bacteria interface

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Authors: Jane A. Luke

Abstract:

Persistent pressure passed on to manufacturers from escalating consumer expectations and the ever growing global competitiveness have produced a rapidly increasing interest in the development of various manufacturing strategy models. Academic and industrial circles are taking keen interest in the field of manufacturing strategy. Many manufacturing strategies are currently centered on the traditional concepts of focused manufacturing capabilities such as quality, cost, dependability and innovation. Process capability indices was conducted assuming that the process under study is in statistical control and independent observations are generated over time. However, in practice, it is very common to come across processes which, due to their inherent natures, generate autocorrelated observations. The degree of autocorrelation affects the behavior of patterns on control charts. Even, small levels of autocorrelation between successive observations can have considerable effects on the statistical properties of conventional control charts. When observations are autocorrelated the classical control charts exhibit nonrandom patterns and lack of control. Many authors have considered the effect of autocorrelation on the performance of statistical process control charts. In this paper, the effect of autocorrelation on confidence intervals for different PCIs was included. Stationary Gaussian processes is explained. Effect of autocorrelation on PCIs is described in detail. Confidence intervals for Cp and Cpk are constructed for PCIs when data are both independent and autocorrelated. Confidence intervals for Cp and Cpk are computed. Approximate lower confidence limits for various Cpk are computed assuming AR(1) model for the data. Simulation studies and industrial examples are considered to demonstrate the results.

Keywords: autocorrelation, AR(1) model, Bissell’s approximation, confidence intervals, statistical process control, specification limits, stationary Gaussian processes

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Authors: Amina R. Issae, Godfrey C. Katusi, Beda J. Mwang’Onde, Ladslaus L. Mnyone, Allen L. Malisa

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Background: The fluctuating composition of mosquito species over time, driven by ecological changes in specific regions, plays a pivotal role in the transmission of malaria. Grasping these dynamics is fundamental for establishing a baseline understanding and is crucial for identifying transmission patterns. This knowledge is essential in devising effective strategies for managing and controlling vector populations. Our study focused on examining the species composition and Plasmodium infection rates of malaria vectors, aiming to enhance the health and well-being of communities affected by malaria. Methods: Species composition was determined through a cross-sectional collection of mosquitoes, conducted once in the village, in four selected villages of Kilosa district, Tanzania. Mosquitoes were collected indoors and outdoors using CDC light traps. A sub-sample of all collected mosquitoes was subjected to PCR identification and assayed for Plasmodium porozoites. Results: A total of 6493 female Anophelines mosquitoes were collected, of which eight species were identified as Anopheles gambiaes.l., An. funestus group, An. coustani, An. pharoensis, An. squamosus, and An. rufipes. The abundance of the Anopheles gambiaes.s.and An. funestuss.s. varied with location and village. A total of 5 sporozoite-positive mosquitoes were found, of which 4 were An. funestuss.s. and 1 was An. gambiaes.s. Conclusions: Anopheles gambiaes.s.and An. funestuss.s. were identified as the most abundant malaria vectors, respectively. Sporozoite analysis indicated this for An. funestuss.s. contribute to most of the malaria transmission in the area. Further studies are required to assess the role of seasonal shifts in vector abundance, insecticide resistance and malaria transmission of the vectors.

Keywords: mosquito, composition, malaria, sporozoites

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Authors: Mark Linden, Michael Brown, Lynne Marsh, Maria Truesdale, Stuart Todd, Nathan Hughes, Trisha Forbes, Rachel Leonard

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Background: The COVID-19 pandemic exacerbated the already significant strain placed on family carers of people with profound and multiple intellectual disabilities (PMID), given the withdrawal of many services during lockdown. The aim of this study was to explore the experiences of family carers of people with PMID during the COVID-19 pandemic. Methods: Online focus groups were conducted with family carers (n=126) from across the UK and the Republic of Ireland. Participants were asked about their experiences of the COVID-19 pandemic, coping strategies, and challenges faced. Focus groups were audio recorded, transcribed verbatim and analyzed through thematic analysis. Findings: Three themes emerged from our analysis of the data: (i) COVID-19 as a double-edged sword, (ii) The struggle for support (iii) the Constant nature of caring. These included 11 subthemes: (i) ‘COVID-19 as a catalyst for change’, ‘Challenges during COVID-19: dealing with change’, ‘Challenges during COVID-19: fear of COVID-19’, ‘The online environment: the new normal’ (ii) ‘Invisibility of male carers’, ‘Carers supporting carers’, ‘The only service you get is lip service: non-existent services’, ‘Knowing your rights’ (iii) ‘Emotional response to the caring role: Feeling devalued’, ‘Emotional response to the caring role: Desperation of caring’, ‘Multiple demands of the caring role.’ Conclusions: Poor or inconsistent access to services and support has been an ongoing difficulty for many family carers. The COVID-19 pandemic has only further intensified these difficulties, increasing family carers' stress. There is an urgent need to design services, such as online support programs, in partnership with family carers that adequately address their needs.

Keywords: intellectual disabilities, family carer, COVID-19, disability

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Authors: Kazi Enamul Hoque

Abstract:

Initiatives on sustainable development are currently aggressively pursued throughout the world. The Malaysian government has developed key policies and strategies for over 30 years to achieve the nation’s policy objectives which are designed to mitigate the issues of security, energy efficiency and environmental impact to meet the rising energy demand. Malaysia’s current focus is on developing effective policies on renewable energy (RE) in order to reduce dependency on fossil fuel and contribute towards mitigating the effects of climate change. In this light mass awareness should be considered as the highest priority to protect the environment and to escape disaster due to climate change. Schools can be the reliable and effective foundation to prepare students to get familiar with environmental issues such as renewable and non-renewable energy sources. Teachers can play a vital role to create awareness among students about the advantages and disadvantages of using different renewable and nonrenewable energy resources. Thus, this study aims to investigate teachers’ knowledge, perceptions and attitudes towards renewable energy through a survey aiming a sustainable energy future. Five hundred sets of questionnaires were distributed to the school teachers in Malaysia. Total 420 questionnaires were returned of which 410 were complete to analyze. Finding shows that teachers are very familiar with the renewable energy like solar, wind and also geothermal. Most teachers were not sure about the Photovoltaics and biodiesel. Furthermore, teachers are also aware that primary energy in Malaysia is imported fossil fuels. Most teachers heard about the renewable energy in Malaysia and only few claims that they did not hear of such things and the others said that they never heard of it. The outcomes of the study will assist the energy policy makers to use teachers to create mass awareness of energy usages for future planning.

Keywords: Malaysia, non-renewable energy, renewable energy, school teacher

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Authors: Marc Solé, Francesc Giné, Magda Valls, Nina Bijedic

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What people say on social media has turned into a rich source of information to understand social behavior. Specifically, the growing use of Twitter social media for political communication has arisen high opportunities to know the opinion of large numbers of politically active individuals in real time and predict the global political tendencies of a specific country. It has led to an increasing body of research on this topic. The majority of these studies have been focused on polarized political contexts characterized by only two alternatives. Unlike them, this paper tackles the challenge of forecasting Spanish political trends, characterized by multiple political parties, by means of analyzing the Twitters Users political tendency. According to this, a new strategy, named Tweets Analysis Strategy (TAS), is proposed. This is based on analyzing the users tweets by means of discovering its sentiment (positive, negative or neutral) and classifying them according to the political party they support. From this individual political tendency, the global political prediction for each political party is calculated. In order to do this, two different strategies for analyzing the sentiment analysis are proposed: one is based on Positive and Negative words Matching (PNM) and the second one is based on a Neural Networks Strategy (NNS). The complete TAS strategy has been performed in a Big-Data environment. The experimental results presented in this paper reveal that NNS strategy performs much better than PNM strategy to analyze the tweet sentiment. In addition, this research analyzes the viability of the TAS strategy to obtain the global trend in a political context make up by multiple parties with an error lower than 23%.

Keywords: political tendency, prediction, sentiment analysis, Twitter

Procedia PDF Downloads 230

Authors: Hong Geng, Zaiyu Fan

Abstract:

With the acceleration of urbanization and motorization in China, the scale of cities and the travel distance of residents are constantly expanding, and the number of cars is continuously increasing, so the urban traffic problem is more and more serious. Traffic congestion, environmental pollution, energy consumption, travel safety and direct interference between traffic and other urban activities are increasingly prominent problems brought about by motorized development. This not only has a serious impact on the lives of the residents but also has a major impact on the healthy development of the city. The paper found that, in order to solve the development of motorization, a number of problems will arise; urban planning and traffic planning and design in residential planning often take into account the development of motorized traffic but neglects the demand for street life. This kind of planning has resulted in the destruction of the traditional communication space of the residential area, the pollution of noise and exhaust gas, and the potential safety risks of the residential area, which has disturbed the previously quiet and comfortable life of the residential area, resulting in the inconvenience of residents' life and the loss of street vitality. Based on these facts, this paper takes a residential area in Wuhan as the research object, through the actual investigation and research, from the perspective of micro-transformation analysis, combined with the concept of traffic micro-reconstruction governance. And research puts forward the residential traffic optimization strategies such as strengthening the interaction and connection between the residential area and the urban street system, street traffic classification and organization.

Keywords: micro-transformation, residential traffic, residents demand, traffic microcirculation

Procedia PDF Downloads 111