Search results for: adopt a culture of continuous learning

Authors: Georg Brunnthaller, Sandra Stein, Wilfried Sihn

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Transportation service providers are facing increasing volatility concerning future transport demand. Short-term planning horizons and planning uncertainties lead to reduced capacity utilization and increasing empty mileage. To overcome these challenges, a model is proposed to continuously pre-plan future transportation capacity in order to redesign and adjust the intermodal fleet accordingly. It is expected that the model will enable logistics service providers to organize more economically and ecologically sustainable transport chains in a more flexible way. To further describe these planning aspects, this paper gives an overview on transportation planning problems in a structured way. The focus is on strategic and tactical planning levels, comprising relevant fleet-sizing, service-network-design and choice-of-carriers-problems. Models and their developed solution techniques are presented, and the literature review is concluded with an outlook to our future research directions.

Keywords: freight transportation planning, multimodal, fleet-sizing, service network design, choice of transportation mode, review

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Authors: Mojtaba Borhani

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By employing the unique characteristics of a region, its economy, climate, geography, and culture, rural communities can create distinctive products. This approach not only boosts economic opportunities but also promotes sustainable growth and preserves cultural heritage. A strategic focus on branding and intellectual property (IP) is essential. By developing strong brands, rural areas can differentiate their products, increase their market value, and build consumer loyalty. Moreover, IP protection safeguards the creative and innovative output of rural communities, incentivizing further development. Rural branding can serve as a cornerstone for community empowerment. It can help to prevent rural exodus by providing economic incentives and a strong sense of place. Additionally, by protecting traditional knowledge and cultural expressions, branding contributes to the long-term sustainability of rural livelihoods.

Keywords: intellectual property, regional branding, sustainable development, rural economy

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Authors: Kamna Solanki, Yudhvir Singh, Sandeep Dalal

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Software testing is a time and cost intensive process. A scrutiny of the code and rigorous testing is required to identify and rectify the putative bugs. The process of bug identification and its consequent correction is continuous in nature and often some of the bugs are removed after the software has been launched in the market. This process of code validation of the altered software during the maintenance phase is termed as Regression testing. Regression testing ubiquitously considers resource constraints; therefore, the deduction of an appropriate set of test cases, from the ensemble of the entire gamut of test cases, is a critical issue for regression test planning. This paper presents a novel method for designing a suitable prioritization process to optimize fault detection rate and performance of regression test on predefined constraints. The proposed method for test case prioritization m-ACO alters the food source selection criteria of natural ants and is basically a modified version of Ant Colony Optimization (ACO). The proposed m-ACO approach has been coded in 'Perl' language and results are validated using three examples by computation of Average Percentage of Faults Detected (APFD) metric.

Keywords: regression testing, software testing, test case prioritization, test suite optimization

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Authors: Ali Etemadi, Polat H. Gulkan

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The drift spectrum derived through the continuous shear-beam and wave propagation theory is known to be useful appliance to measure of the demand of pulse like near field ground motions on building structures. As regards, many of old frame buildings with poor or non-ductile column elements, pass the elastic limits and blurt the post yielding hysteresis degradation responses when subjected to such impulsive ground motions. The drift spectrum which, is based on a linear system cannot be predicted the overestimate drift demands arising from inelasticity in an elastic plastic systems. A simple procedure to estimate the drift demands in shear-type frames which, respond over the elastic limits is described and effect of hysteresis degradation behavior on seismic demands is clarified. Whereupon the modification factors are proposed to incorporate the hysteresis degradation effects parametrically. These factors are defined with respected to the linear systems. The method can be applicable for rapid assessment of existing poor detailed, non-ductile buildings.

Keywords: drift spectrum, shear-type frame, stiffness and strength degradation, pinching, smooth hysteretic model, quasi static analysis

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Authors: Zhenfeng Xie

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Acute gastroenteritis (AGE) is a common cause of morbidity and mortality in infants and young children worldwide, especially in developing countries. Enterovirus(EVs) have been identified in patients with AGE in many countries around the world, and some studies have revealed that EV infection is associated with gastrointestinal symptoms and plays a role in AGE. As a potential causative pathogen of AGE in humans, continuous detection and identification of EVs in pediatric patients with AGE is needed. In this study, we aimed to investigate the prevalence, seasonal distribution, and molecular characteristics of EVs circulating in pediatric patients with AGE in Thailand from 2019 to 2022. A total of 1422 stool specimens were collected for this study. RT-PCR amplification of the 5'UTR was used to screen for EV positive samples. EV genotyping was determined based on nucleotide sequence and phylogenetic analysis of the VP1 sequences. EV prevalence in pediatric AGE patients was 8.3% (118 out of 1,422). Among these, 35.6% of EV infection cases were caused by species A, followed by species C and B (33.1% and 30.5%, respectively). A total of 26 EV genotypes were identified in this study. Poliovirus 3 and coxsackievirus A2 were the predominant genotypes detected(14% and 13%, respectively). EV was detected all year round with higher prevalence between July and December. In summary, this study reports EV's prevalence and genotype diversity in pediatric patients with AGE in Thailand during 2019-2022.

Keywords: enterovirus, epidemiology, acute gastroenteritis, genotype

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Authors: J. Burlakovs, Y. Jani, L. Grinberga, M. Kriipsalu, O. Anne, I. Grinfelde, W. Hogland

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The worldwide future sustainable economies are oriented towards the sea: the maritime economy is becoming one of the strongest driving forces in many regions as population growth is the highest in coastal areas. For hundreds of years sea resources were depleted unsustainably by fishing, mining, transportation, tourism, and waste. European Sustainable Development Strategy is identifying and developing actions to enable the EU to achieve a continuous, long-term improvement of the quality of life through the creation of sustainable communities. The aim of this paper is to provide insight in Baltic Sea Region case studies on implemented actions on tourism industry waste and beach wrack management in coastal areas, hazardous contaminants and plastic flow treatment from waste, wastewaters and stormwaters. These projects mentioned in study promote successful prevention of contaminant flows to the sea environments and provide perspectives for creation of valuable new products from residuals for future circular economy are the step forward to green innovation winning streak.

Keywords: resilience, hazardous waste, phytoremediation, water management, circular economy

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Authors: Deyadeen Ali Alshibani

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In the literature, the multi-armed bandit problem as a statistical decision model of an agent trying to optimize his decisions while improving his information at the same time. There are several different algorithms models and their applications on this problem. In this paper, we evaluate the Regret-regression through comparing with Q-learning method. A simulation on determination of optimal treatment regime is presented in detail.

Keywords: optimal, bandit problem, optimization, dynamic programming

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Authors: Yu-Jia Jian, Emily Chia-Yu Su, Hui-Ling Hsu, Jian-Jhih Chen

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Coronary artery is the major supplier of myocardial blood flow. When fat and cholesterol are deposit in the coronary arterial wall, narrowing and stenosis of the artery occurs, which may lead to myocardial ischemia and eventually infarction. According to the World Health Organization (WHO), estimated 740 million people have died of coronary heart disease in 2015. According to Statistics from Ministry of Health and Welfare in Taiwan, heart disease (except for hypertensive diseases) ranked the second among the top 10 causes of death from 2013 to 2016, and it still shows a growing trend. According to American Heart Association (AHA), the risk factors for coronary heart disease including: age (> 65 years), sex (men to women with 2:1 ratio), obesity, diabetes, hypertension, hyperlipidemia, smoking, family history, lack of exercise and more. We have collected a dataset of 421 patients from a hospital located in northern Taiwan who received coronary computed tomography (CT) angiography. There were 300 males (71.26%) and 121 females (28.74%), with age ranging from 24 to 92 years, and a mean age of 56.3 years. Prior to coronary CT angiography, basic data of the patients, including age, gender, obesity index (BMI), diastolic blood pressure, systolic blood pressure, diabetes, hypertension, hyperlipidemia, smoking, family history of coronary heart disease and exercise habits, were collected and used as input variables. The output variable of the prediction module is the degree of coronary artery stenosis. The output variable of the prediction module is the narrow constriction of the coronary artery. In this study, the dataset was randomly divided into 80% as training set and 20% as test set. Four machine learning algorithms, including logistic regression, stepwise regression, neural network and decision tree, were incorporated to generate prediction results. We used area under curve (AUC) / accuracy (Acc.) to compare the four models, the best model is neural network, followed by stepwise logistic regression, decision tree, and logistic regression, with 0.68 / 79 %, 0.68 / 74%, 0.65 / 78%, and 0.65 / 74%, respectively. Sensitivity of neural network was 27.3%, specificity was 90.8%, stepwise Logistic regression sensitivity was 18.2%, specificity was 92.3%, decision tree sensitivity was 13.6%, specificity was 100%, logistic regression sensitivity was 27.3%, specificity 89.2%. From the result of this study, we hope to improve the accuracy by improving the module parameters or other methods in the future and we hope to solve the problem of low sensitivity by adjusting the imbalanced proportion of positive and negative data.

Keywords: decision support, computed tomography, coronary artery, machine learning

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Authors: Gayatri Mahajan

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Modern Construction Technology (CT) includes a broad range of advanced techniques and practices that bound the recent developments in material technology, design methods, quantity surveying, facility management, services, structural analysis and design, and other management education. Adoption of recent digital transformation technology is the need of today to speed up the business and is also the basis of construction improvement. Incorporating and practicing the technologies such as cloud-based communication and collaboration solution, Mobile Apps and 5G,3D printing, BIM and Digital Twins, CAD / CAM, AR/ VR, Big Data, IoT, Wearables, Blockchain, Modular Construction, Offsite Manifesting, Prefabrication, Robotic, Drones and GPS controlled equipment expedite the progress in the Construction industry (CI). Resources used are journaled research articles, web/net surfing, books, thesis, reports/surveys, magazines, etc. The outline of the research organization for this study is framed at four distinct levels in context to conceptualization, resources, innovative and emerging trends in CI, and better methods for completion of the construction projects. The present study conducted during 2020-2022 reveals that implementing these technologies improves the level of standards, planning, security, well-being, sustainability, and economics too. Application uses, benefits, impact, advantages/disadvantages, limitations and challenges, and policies are dealt with to provide information to architects and builders for smooth completion of the project. Results explain that construction technology trends vary from 4 to 15 for CI, and eventually, it reaches 27 for Civil Engineering (CE). The perspective of the most recent innovations, trends, tools, challenges, and solutions is highly embraced in the field of construction. The incorporation of the above said technologies in the pandemic Covid -19 and post-pandemic might lead to a focus on finding out effective ways to adopt new-age technologies for CI.

Keywords: BIM, drones, GPS, mobile apps, 5G, modular construction, robotics, 3D printing

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Authors: K. Kalieva, G. Ibraimova

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In literature, poetry stands as a profound genre that bridges the life experiences of everyday people, transcending language and culture to unite people through the universal language of emotion and human connection. This paper explores the collaborative efforts of translators in creating the anthology of post-Soviet Kyrgyz women’s poetry, a project spanning over ten years. This compelling anthology brings together the works of fifty prominent female poets from Kyrgyzstan during the post-Soviet era. It includes the original poems in Kyrgyz and provide English translations, sharing the rich and diverse voices of Kyrgyz women with a global audience and fostering a deep appreciation for the beauty of their words. The paper highlights the unique perspectives on life, love, and identity offered by each poet, and emphasizes the role of translation in making these voices accessible worldwide. Each poet's unique voice offers a glimpse into the rich cultural and literary landscape of Kyrgyzstan, highlighting themes that resonate universally. Methodology of the paper employs a combination of qualitative content analysis, semiotic analysis, and quantitative thematic analysis to examine the translation strategies, and the cultural and emotional peculiarities captured in the translations, as well as the themes explored by the poets in their poems. Through the art of translation, the paper explores the lyrical world of Kyrgyz women poets. Although Kyrgyz poets’ names and poems are unfamiliar to many, their words resonate with an emotional depth that is sure to leave a lasting impression. Kyrgyz women's poetry translated into English celebrates the distinctive voices of women in the contemporary world. It serves as a reminder that poetry possesses the power to transcend life's obstacles, foster mutual understanding, and inspire positive change. The poems created by Kyrgyz women are envisioned to serve as a source of inspiration for readers. The paper proposes a poetic journey created by Kyrgyz women, offering readers an opportunity to experience Kyrgyz landscapes, traditions, and universal human themes through their verses. The paper provides an in-depth analysis of the poem translations, exploring the beauty and depth of the poets' thoughts and feelings. Through these translations, readers are invited to explore the world of Kyrgyz women poets, enriching their understanding of the language, culture, and the profound human experiences conveyed in the poetry. The hypotheses of the paper is that analyzing these translations through translation studies theories and linguistic and semiotic frameworks will reveal the complexities and challenges involved in translating poetry across languages and cultures.

Keywords: Kyrgyz poetry, post-soviet literature, translation, women poets.

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Authors: Enyia James Diwa, Isaiah Thank-God Ebi, Dodeye Ina Igbong

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The privatization of utilities has brought about very strong competition in industries such as petrochemical and gas distribution among others, considering the continuous increase in cost of fuel. This has brought about the intense reason for gas turbine owners and operators to reduce and control performance degradation of the engine in other to minimize cost. The most common and very crucial problem of the gas turbine is the fouling of compressor, which is mostly caused by a reduction in flow capacity, compressor efficiency, and pressure ratio, this, in turn, lead to the engine compressor re-matching and output power and thermal efficiency reduction. The content of this paper encompasses a detailed presentation of the major causes, effects and control mechanism of fouling. The major emphasis is on compressor water washing to enable power augmentation. A modelled gas turbine similar to that of GE LM6000 is modelled for the current study, based on TURBOMATCH which is a Cranfield University software specifically made for gas turbine performance simulation and fouling detection. The compounded and intricate challenges of compressor online water washing of large output gas turbine are carried out. The treatment is applied to axial compressor used in the petrochemical and hydrocarbon industry.

Keywords: gas turbine, fouling, degradation, compressor washing

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Authors: Irem Ela Yildizeli

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Advertising today has become an indispensable phenomenon both for businesses and consumers. Due to the conditions of rapid changes in the market and growth of competitiveness, the success of many of firms that produce similar merchandise depends largely on how professionally and effective they use marketing communication elements which also must have some sense of shared values between the message provider and the receiver within cultural and global trend. This paper demonstrates how consumer behaviour and communication through cultural values evaluate advertising styles. Using samples of award-winning ads from both author's and other professional's creative works, the study reveals a significant correlation between the cultural elements and advertisement reception for language and cultural norms respectively. The findings of this study draw attention to the change of communication in the beginning of the 21st century which has shaped a new style of Participatory and Experience Design in advertising.

Keywords: advertising, advertising style, culture, experience design, participatory design

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Authors: Shashikant R. Kuchekar, Shivaji D. Pulate, Vishwas B. Gaikwad

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A simple and selective method is developed for solvent extraction spectrophotometric determination of antimony(III) using O-Methylphenyl Thiourea (OMPT) as a sensitive chromogenic chelating agent. The basis of proposed method is formation of antimony(III)-OMPT complex was extracted with 0.0025 M OMPT in chloroform from aqueous solution of antimony(III) in 1.0 M perchloric acid. The absorbance of this complex was measured at 297 nm against reagent blank. Beer’s law was obeyed up to 15µg mL-1 of antimony(III). The Molar absorptivity and Sandell’s sensitivity of the antimony(III)-OMPT complex in chloroform are 16.6730 × 103 L mol-1 cm-1 and 0.00730282 µg cm-2 respectively. The stoichiometry of antimony(III)-OMPT complex was established from slope ratio method, mole ratio method and Job’s continuous variation method was 1:2. The complex was stable for more than 48 h. The interfering effect of various foreign ions was studied and suitable masking agents are used wherever necessary to enhance selectivity of the method. The proposed method is successfully applied for determination of antimony(III) from real samples alloy and synthetic mixtures. Repetition of the method was checked by finding relative standard deviation (RSD) for 10 determinations which was 0.42%.

Keywords: solvent extraction, antimony, spectrophotometry, real sample analysis

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Authors: Sergio Andres Rojas, Julian Benavides Franco, Juan Tomas Sayago

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An increasing amount of research demonstrates how market mood affects financial markets, but their primary goal is to demonstrate how Trump's tweets impacted US interest rate volatility. Following that lead, this work evaluates the effect that Trump's tweets had during his presidency on local and international stock markets, considering not just volatility but the direction of the movement. Three indexes for Trump's tweets were created relating his activity with movements in the S&P500 using natural language analysis and machine learning algorithms. The indexes consider Trump's tweet activity and the positive or negative market sentiment they might inspire. The first explores the relationship between tweets generating negative movements in the S&P500; the second explores positive movements, while the third explores the difference between up and down movements. A pseudo-investment strategy using the indexes produced statistically significant above-average abnormal returns. The findings also showed that the pseudo strategy generated a higher return in the local market if applied to intraday data. However, only a negative market sentiment caused this effect on daily data. These results suggest that the market reacted primarily to a negative idea reflected in the negative index. In the international market, it is not possible to identify a pervasive effect. A rolling window regression model was also performed. The result shows that the impact on the local and international markets is heterogeneous, time-changing, and differentiated for the market sentiment. However, the negative sentiment was more prone to have a significant correlation most of the time.

Keywords: market sentiment, Twitter market sentiment, machine learning, natural dialect analysis

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Authors: Marcell Serra de Almeida Martins, Benedito de Souza Ribeiro Neto, Gerson Lima Serejo, Carlos Gustavo Resque Dos Santos

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Indoor positioning systems use sensors such as Bluetooth, ZigBee, and Wi-Fi, as well as cameras for image capture, which can be fixed or mobile. These computer vision-based positioning approaches are low-cost to implement, mainly when it uses a mobile camera. The present study aims to create a design of a fiducial marker for a low-cost indoor localization system. The marker is tape-shaped to perform a continuous reading employing two detection algorithms, one for greater distances and another for smaller distances. Therefore, the location service is always operational, even with variations in capture distance. A minimal localization and reading algorithm were implemented for the proposed marker design, aiming to validate it. The accuracy tests consider readings varying the capture distance between [0.5, 10] meters, comparing the proposed marker with others. The tests showed that the proposed marker has a broader capture range than the ArUco and QRCode, maintaining the same size. Therefore, reducing the visual pollution and maximizing the tracking since the ambient can be covered entirely.

Keywords: multiscale recognition, indoor localization, tape-shaped marker, fiducial marker

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Authors: Majed M. Mustafa, Abdulrahman A. Altassan

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In recent years, ensuring accessibility for all individuals, particularly those with mobility impairments, has gained significant attention in Saudi Arabia. This research aims to evaluate wheelchair accessibility in shopping centers, malls, and stores across the kingdom, highlighting its critical role in promoting inclusivity and equal access. The study will focus on the availability and quality of ramps, automatic doors, lifts, accessible restrooms, and overall ease of navigation for wheelchair users. Utilizing a mixed-methods approach, the research will employ site assessments, user surveys, and interviews with facility managers to gather comprehensive data. Preliminary findings indicate that while some facilities have made strides in accessibility, there are still numerous areas requiring improvement. The study will provide targeted recommendations to enhance accessibility, ensuring that all users can navigate shopping environments with ease and dignity. Conclusively, this research underscores the need for continuous efforts and policy enhancements to achieve universal design standards in public spaces within Saudi Arabia.

Keywords: automatic doors, equal access, ramp quality, wheelchair accessibility

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Authors: Omotoyosi Bilikies Ilori, Adekunle Saheed Ajisebiyawo

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After the Second World War, there was an emergence of a new stage of capitalist globalization with its Neo-liberal ideology. There were global economic and political restructurings that affected third-world countries like Nigeria. Neo-liberalism is the driving force of globalization, which is the latest manifestation of imperialism that engenders endemic poverty in Nigeria. Poverty is severe and widespread in Nigeria. Poverty entails a situation where a person lives on less than one dollar per day and has no access to basic necessities of life. Poverty is inhuman and a breach of human rights. The Nigerian government initiated some strategies in the past to help in poverty reduction. Neo-liberalism manifested in the Third World, such as Nigeria, through the privatization of public enterprises, trade liberalization, and the rollback of the state investments in providing important social services. These main ideas of Neo-liberalism produced poverty in Nigeria and also encouraged the abandonment of the social contract between the government and the people. There is thus a gap in the provision of social services and subsidies for the masses, all of which Neo-liberal ideological positions contradict. This paper is a qualitative study which draws data from secondary sources. The theoretical framework is anchored on the market theory of capitalist globalization and public choice theory. The objectives of this study are to (i) examine the impacts of Neo-liberalism on poverty in Nigeria as a typical example of a Third World country and (ii) find out the effects of Neo-liberalism on the provision of social services and subsidies and employment. The findings from this study revealed that (i) the adoption of the Neo-liberal ideology by the Nigerian government has led to increased poverty and poor provision of social services and employment in Nigeria; and (ii) there is an increase in foreign debts which compounds poverty situation in Nigeria. This study makes the following recommendations: (i) Government should adopt strategies that are pro-poor to eradicate poverty; (ii) The Trade Unions and the masses should develop strategies to challenge Neo-liberalism and reject Neo-liberal ideology.

Keywords: neo-liberalism, poverty, employment, poverty reduction, structural adjustment programme

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Authors: Yuta Nakano, Kozo Kajiwara, Atsushi Hori, Takeshi Fujita

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In association with the wave of electric vehicles (EV), low energy consumption systems have become more and more important. One of the key technologies to realize low energy consumption is a dynamic vision sensor (DVS), or we can call it an event sensor, neuromorphic vision sensor and so on. This sensor has several features, such as high temporal resolution, which can achieve 1 Mframe/s, and a high dynamic range (120 DB). However, the point that can contribute to low energy consumption the most is its sparsity; to be more specific, this sensor only captures the pixels that have intensity change. In other words, there is no signal in the area that does not have any intensity change. That is to say, this sensor is more energy efficient than conventional sensors such as RGB cameras because we can remove redundant data. On the other side of the advantages, it is difficult to handle the data because the data format is completely different from RGB image; for example, acquired signals are asynchronous and sparse, and each signal is composed of x-y coordinate, polarity (two values: +1 or -1) and time stamp, it does not include intensity such as RGB values. Therefore, as we cannot use existing algorithms straightforwardly, we have to design a new processing algorithm to cope with DVS data. In order to solve difficulties caused by data format differences, most of the prior arts make a frame data and feed it to deep learning such as Convolutional Neural Networks (CNN) for object detection and recognition purposes. However, even though we can feed the data, it is still difficult to achieve good performance due to a lack of intensity information. Although polarity is often used as intensity instead of RGB pixel value, it is apparent that polarity information is not rich enough. Considering this context, we proposed to use the timestamp information as a data representation that is fed to deep learning. Concretely, at first, we also make frame data divided by a certain time period, then give intensity value in response to the timestamp in each frame; for example, a high value is given on a recent signal. We expected that this data representation could capture the features, especially of moving objects, because timestamp represents the movement direction and speed. By using this proposal method, we made our own dataset by DVS fixed on a parked car to develop an application for a surveillance system that can detect persons around the car. We think DVS is one of the ideal sensors for surveillance purposes because this sensor can run for a long time with low energy consumption in a NOT dynamic situation. For comparison purposes, we reproduced state of the art method as a benchmark, which makes frames the same as us and feeds polarity information to CNN. Then, we measured the object detection performances of the benchmark and ours on the same dataset. As a result, our method achieved a maximum of 7 points greater than the benchmark in the F1 score.

Keywords: event camera, dynamic vision sensor, deep learning, data representation, object recognition, low energy consumption

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Authors: Martina I. Reinhold, Theresa Bacon-Baguley

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A core challenge of physician assistant education is preparing professionals for lifelong learning. While this conventionally has encompassed scientific advances, students must also embrace new care delivery models and technologies. Telemedicine, the provision of care via two-way audio and video, is an example of a technological advance reforming health care. During a three-semester sequence of Hospital Community Experiences, physician assistant students were assigned experiences with Answer Health on Demand, a telemedicine collaborative. Preceding the experiences, the agency lectured on the application of telemedicine. Students were then introduced to the technology and partnered with a provider. Prior to observing the patient-provider interaction, patient consent was obtained. Afterwards, students completed a reflection paper on lessons learned and the potential impact of telemedicine on their careers. Thematic analysis was completed on the students’ reflection papers (n=13). Preceding the lecture and experience, over 75% of students (10/13) were unaware of telemedicine. Several stated they were 'skeptical' about the effectiveness of 'impersonal' health care appointments. After the experience, all students remarked that telemedicine will play a large role in the future of healthcare and will provide benefits by improving access in rural areas, decreasing wait time, and saving cost. More importantly, 30% of students (4/13) commented that telemedicine is a technology they can see themselves using in their future practice. Initial results indicate that collaborative interaction between students and telemedicine providers enhanced student learning and exposed students to technological advances in the delivery of care. Further, results indicate that students perceived telemedicine more favorably as a viable delivery method after the experience.

Keywords: collaboration, physician assistant education, teaching innovative health care delivery method, telemedicine

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Authors: Emilie Zimet

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During our department meetings for teachers of children with learning disabilities and difficulties, we often discuss the best practices for supporting students who come to school with literacy difficulties. After completing Sounds Write and Writing Revolution courses, it seems there is a possibility to link approaches and still maintain fidelity to a program and provide individualised instruction to support students with such difficulties and disabilities. In this case study, the researcher has been focussing on how best to use the knowledge acquired to provide quality intervention that targets the varied areas of challenge that students require support in. Students present to school with a variety of co-occurring reading and writing deficits and with complementary approaches, such as The Writing Revolution and Sounds Write, it is possible to support students to improve their fundamental skills in these key areas. Over the next twelve weeks, the researcher will collect data on current students with whom this approach will be trialled and then compare growth with students from last year who received support using Sounds-Write only. Maintaining fidelity may be a potential challenge as each approach has been tested in a specific format for best results. The aim of this study is to determine if approaches can be combined, so the implementation will need to incorporate elements of both reading (from Sounds Write) and writing (from The Writing Revolution). A further challenge is the time length of each session (25 minutes), so the researcher will need to be creative in the use of time to ensure both writing and reading are targeted while ensuring the programs are implemented. The implementation will be documented using student work samples and planning documents. This work will include a display of findings using student learning samples to demonstrate the importance of co-targeting the reading and writing challenges students come to school with.

Keywords: literacy difficulties, intervention, individual differences, methods of provision

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Authors: Saleh Gorji, Sahil Gulati, Ana Pakzad

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Continuous electron diffraction tomography, also known as microcrystal electron diffraction (MicroED) or three-dimensional electron diffraction (3DED), is a powerful technique, which in combination with cryo-electron microscopy (cryo-ED), can provide atomic-scale 3D information about the crystal structure and composition of different classes of crystalline materials such as proteins, peptides, and small molecules. Unlike the well-established X-ray crystallography method, 3DED does not require large single crystals and can collect accurate electron diffraction data from crystals as small as 50 – 100 nm. This is a critical advantage as growing larger crystals, as required by X-ray crystallography methods, is often very difficult, time-consuming, and expensive. In most cases, specimens studied via 3DED method are electron beam sensitive, which means there is a limitation on the maximum amount of electron dose one can use to collect the required data for a high-resolution structure determination. Therefore, collecting data using a conventional scintillator-based fiber coupled camera brings additional challenges. This is because of the inherent noise introduced during the electron-to-photon conversion in the scintillator and transfer of light via the fibers to the sensor, which results in a poor signal-to-noise ratio and requires a relatively higher and commonly specimen-damaging electron dose rates, especially for protein crystals. As in other cryo-EM techniques, damage to the specimen can be mitigated if a direct detection camera is used which provides a high signal-to-noise ratio at low electron doses. In this work, we have used two classes of such detectors from Gatan, namely the K3® camera (a monolithic active pixel sensor) and Stela™ (that utilizes DECTRIS hybrid-pixel technology), to address this problem. The K3 is an electron counting detector optimized for low-dose applications (like structural biology cryo-EM), and Stela is also a counting electron detector but optimized for diffraction applications with high speed and high dynamic range. Lastly, data collection workflows, including crystal screening, microscope optics setup (for imaging and diffraction), stage height adjustment at each crystal position, and tomogram acquisition, can be one of the other challenges of the 3DED technique. Traditionally this has been all done manually or in a partly automated fashion using open-source software and scripting, requiring long hours on the microscope (extra cost) and extensive user interaction with the system. We have recently introduced Latitude® D in DigitalMicrograph® software, which is compatible with all pre- and post-energy-filter Gatan cameras and enables 3DED data acquisition in an automated and optimized fashion. Higher quality 3DED data enables structure determination with higher confidence, while automated workflows allow these to be completed considerably faster than before. Using multiple examples, this work will demonstrate how to direct detection electron counting cameras enhance 3DED results (3 to better than 1 Angstrom) for protein and small molecule structure determination. We will also show how Latitude D software facilitates collecting such data in an integrated and fully automated user interface.

Keywords: continuous electron diffraction tomography, direct detection, diffraction, Latitude D, Digitalmicrograph, proteins, small molecules

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Authors: Maryam Alkhalosi, Ahmad Naddaf, Rana Alani

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Qatar National Library has its main accounts on social media, which presents the general image of the library and its daily news. A paper will be presented based on a case study researching the outcome of having a separate Instagram account led by librarians, not the Communication Department of the library. The main purpose of the librarians-led account is to promote librarians’ services and events, such as research consultation, reference questions, community engagement programs, collection marketing, etc. all in the way that librarians think it reflects their role in the community. Librarians had several obstacles to help users understanding librarians' roles. As was noticed that Instagram is the most popular social media platform in Qatar, it was selected to promote how librarians can help users through a focused account to create a direct channel between librarians and users. Which helps librarians understand users’ needs and interests. This research will use a quantitative approach depending on the case study, librarians have used their case in the department of Research and learning to find out the best practices might help in promoting the librarians' services and reaching out to a bigger number of users. Through the descriptive method, this research will describe the changes observed in the numbers of community users who interact with the Instagram account and engaged in librarians’ events. Statistics of this study are based on three main sources: 1. The internal monthly statistics sheet of events and programs held by the Research and Learning Department. 2. The weekly tracking of the Instagram account statistics. 3. Instagram’s tools such as polls, quizzes, questions, etc. This study will show the direct effect of a librarian-led Instagram account on the number of community members who participate and engage in librarian-led programs and services. In addition to highlighting the librarians' role directly with the community members. The study will also show the best practices on Instagram, which helps reaching a wider community of users. This study is important because, in the region, there is a lack of studies focusing on librarianship, especially on contemporary problems and its solution. Besides, there is a lack of understanding of the role of a librarian in the Arab region. The research will also highlight how librarians can help the public and researchers as well. All of these benefits can come through one popular easy channel in social media. From another side, this paper is a chance to share the details of this experience starting from scratch, including the phase of setting the policy and guidelines of managing the social media account, until librarians reached to a point where the benefits of this experience are in reality. This experience had even added many skills to the librarians.

Keywords: librarian’s role, social media, instagram and libraries, promoting libraries’ services

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Authors: Grace D. Severo, Lopita U. Jung

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This study aimed to determine the educational philosophies and teaching styles of the college faculty of the University of Perpetual Help System DALTA in the campuses of Las-Piñas, Molino, and Calamba, south of Metro Manila. It sought to determine the relationships of educational philosophy and teaching styles of the college faculty vis-à-vis the university system’s educational philosophies and teaching style preferences. A hundred and five faculty members from the Colleges of Education, Arts and Sciences responded to the survey during the academic year 2014-2015. The Philosophy of Adult Education Inventory measured the faculty’s preferred educational philosophies. The Principles of Adult Learning Scale measured the faculty’s teaching style preference. Findings show that there is a similarity between the university system and the faculty members in using the progressive educational philosophy, however both contrasted in the preferred teaching style. Majority of the faculty held progressive educational philosophy but their preference for teacher-centered teaching style did not match. This implies that the majority are certain of having progressive educational philosophy but are not utilizing the learner-centered teaching styles; a high degree of support and commitment to practice a progressive and humanist philosophical orientation in education; and a high degree of support on teacher-centered teaching style promotion from the institution can strengthen a high degree of commitment for the faculty to enunciate their values and practice through these educational philosophies and teaching styles.

Keywords: educational philosophies, teaching styles, philosophy of adult education inventory, principles of adult learning scale

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Authors: Lina Martinez, Juan David Rivera Acevedo, Isabella Franco

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The informal economy plays a significant role in the job market in Colombia. Cali, the third largest city in the country, is characterized by a high percentage of socially and economically vulnerable population groups who take part in the urban informal economy, with street vending as their primary source of income. This paper studies the socio-economic dimensions of street vendors in Cali. In particular, it examines why they are unable to capitalize on their comparatively high earnings and are not likely to escape poverty even though they usually profit from government welfare and tax evasion due to the non-regulated character of informality. The analysis of an observational study and two surveys with 637 and 300 participants show that street vending is a cash-based day-to-day activity. Since most of the street vendors do not have access to formal banking systems, they depend on payday loans with incomparably high interest rates which absorb a large share of their income and maintain a continuous indebtedness. This is one of the main reasons why they are unable to improve their living conditions. However, the daily cash flow masks the high opportunity cost of loans and long-term deficits.

Keywords: Colombia, informal economy, payday loans, street vendors

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Authors: Jigg L. Pelayo, Ricardo G. Villar, Einstine M. Opiso

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The advances of aerial laser scanning in the Philippines has open-up entire fields of research in remote sensing and machine vision aspire to provide accurate timely information for the government and the public. Rapid mapping of polygonal roads and roof boundaries is one of its utilization offering application to disaster risk reduction, mitigation and development. The study uses low density LiDAR data and high resolution aerial imagery through object-oriented approach considering the theoretical concept of data analysis subjected to machine learning algorithm in minimizing the constraints of feature extraction. Since separating one class from another in distinct regions of a multi-dimensional feature-space, non-trivial computing for fitting distribution were implemented to formulate the learned ideal hyperplane. Generating customized hybrid feature which were then used in improving the classifier findings. Supplemental algorithms for filtering and reshaping object features are develop in the rule set for enhancing the final product. Several advantages in terms of simplicity, applicability, and process transferability is noticeable in the methodology. The algorithm was tested in the different random locations of Misamis Oriental province in the Philippines demonstrating robust performance in the overall accuracy with greater than 89% and potential to semi-automation. The extracted results will become a vital requirement for decision makers, urban planners and even the commercial sector in various assessment processes.

Keywords: feature extraction, machine learning, OBIA, remote sensing

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Authors: Jamil Lane, Jason Freeman

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Background: The role of interpersonal relationships is vital predictors of adolescents’ eating habits, exercise activity, and health problems including obesity. The effect of interpersonal relationships (i.e. family, friends, and intimate partners) on individual health behaviors and development have gained considerable attention during the past 10 years. Teenagers eating habits and exercise activities are established through a dynamic course involving internal and external factors such as food preferences, body weight perception, and parental and peer influence. When conceptualizing one’s interpersonal relationships, it is important to understand that how one relates to others is shaped by their culture. East-Asian culture has been characterized as collectivistic, which describes the significant role intergroup relationships play in their construction of the self. Cultures found in North America, on the other hand, can be characterized as individualistic, meaning that these cultures encourage individuals to prioritize their interest over the needs and want of their compatriots. Individuals from collectivistic cultures typically have stronger boundaries between in-group and out-group membership, whereas those from individualistic cultures see themselves as distinct and separate from strangers as well as family or friends. Objective: The purpose of this study is to examine the effect of collectivism and individualism on interpersonal relationships that shapes eating patterns and physical activity among Asian-American and European-American adolescents. Design/Methods: Analyses were based on data from the National Longitudinal Study of Adolescent Health, a nationally representative sample of adolescents in the United States who were surveyed from 1994 through 2008. This data will be used to examine interpersonal relationship factors that shape dietary intake and physical activity patterns within the Asian-American and European-American population in the United States. Factors relating to relationship strength, eating, and exercise behaviors were reported by participants in this first wave of data collection (1995). We plan to analyze our data using intragroup comparisons among those who identified as 'Asian-American' (n = 270) and 'White or European American' (n = 4,294) among the domains of positivity of peer influence and level of physical activity / healthy eating. Further, intergroup comparisons of these relationships will be made to extricate how the role positive peer influence in maintaining healthy eating and exercise habits differs with cultural variation. Results: We hypothesize that East-Asian participants with a higher degree of positivity in their peer and family relationships will experience a significantly greater rise in healthy eating and exercise behaviors than European-American participants with similar degrees of relationship positivity.

Keywords: interpersonal relationships, eating patterns, physical activity, adolescent health

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Authors: Violeta Kostadinova, Emilia Tsankova

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The purpose of this research is to explore and analyze the integration of the younger generation with Bulgarian folklore through various innovative forms, methods and approaches. A survey was conducted among students to evaluate its success. The results prove the relevance of the problem as well and the necessity of innovation to keep the national and promotion of Bulgarian folklore. Innovation in music education is a good way to create positive motivation and raise interest in folk art, which is especially pronounced when the folk songs have contemporary arrangement. Modern interpretation of Bulgarian folk music makes the music more approachable to young people and makes it more likely that folk music will become an integral part of our modern culture. The research would help the implementation of appropriate innovations for more effective training and upgrading for music students in all middle and high schools in the country.

Keywords: Bulgarian folklore, innovative forms, methods and approaches, motivation, music education

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Authors: Kaustav Kundu, Alberto Portioli Staudacher

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Construction industry plays a vital role in the economy of the world. But due to high uncertainty and variability in the industry, its performance is not as efficient in terms of quality, lead times, productivity and costs as of other industries. Moreover, there are continuous conflicts among the different actors in the construction supply chains in terms of profit sharing. Previous studies suggested partnership as an important approach to promote cooperation among the different actors in the construction supply chains and thereby it improves the overall performance. Construction practitioners tried to focus on partnership which can enhance the performance of construction supply chains but they are not fully aware of different approaches and techniques for improving partnership. In this research, a systematic review on partnership in relation to construction supply chains is carried out to understand different elements influencing the partnership. The research development of this domain is analyzed by reviewing selected articles published from 1996 to 2015. Based on the papers, three major elements influencing partnership in construction supply chains are identified: “Lean approach”, “Relationship building” and “E-commerce applications”. This study analyses the contributions in the areas within each element and provides suggestions for future developments of partnership in construction supply chains.

Keywords: partnership, construction, lean, SCM, supply chain management

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Authors: Teja Sai Puligadda

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Satellite images in detail can serve an important role in the geographic study. Quantitative and qualitative information provided by the satellite and remote sensing images minimizes the complexity of work and time. Data/images are captured at regular intervals by satellite remote sensing systems, and the amount of data collected is often enormous, and it expands rapidly as technology develops. Interpreting remote sensing images, geographic data mining, and researching distinct vegetation types such as agricultural and forests are all part of satellite image categorization. One of the biggest challenge data scientists faces while classifying satellite images is finding the best suitable classification algorithms based on the available that could able to classify images with utmost accuracy. In order to categorize satellite images, which is difficult due to the sheer volume of data, many academics are turning to deep learning machine algorithms. As, the CNN algorithm gives high accuracy in image recognition problems and automatically detects the important features without any human supervision and the ANN algorithm stores information on the entire network (Abhishek Gupta., 2020), these two deep learning algorithms have been used for satellite image classification. This project focuses on remote sensing through Deep Neural Networks i.e., ANN and CNN with Deep Sat (SAT-4) Airborne dataset for classifying images. Thus, in this project of classifying satellite images, the algorithms ANN and CNN are implemented, evaluated & compared and the performance is analyzed through evaluation metrics such as Accuracy and Loss. Additionally, the Neural Network algorithm which gives the lowest bias and lowest variance in solving multi-class satellite image classification is analyzed.

Keywords: artificial neural network, convolutional neural network, remote sensing, accuracy, loss

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Authors: Ramazan Bakir, Gizem Kayar

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It is known that Alzheimer and Dementia are the two most common types of Neurodegenerative diseases and their visibility is getting accelerated for the last couple of years. As the population sees older ages all over the world, researchers expect to see the rate of this acceleration much higher. However, unfortunately, there is no known pharmacological cure for both, although some help to reduce the rate of cognitive decline speed. This is why we encounter with non-pharmacological treatment and tracking methods more for the last five years. Many researchers, including well-known associations and hospitals, lean towards using non-pharmacological methods to support cognitive function and improve the patient’s life quality. As the dementia symptoms related to mind, learning, memory, speaking, problem-solving, social abilities and daily activities gradually worsen over the years, many researchers know that cognitive support should start from the very beginning of the symptoms in order to slow down the decline. At this point, life of a patient and caregiver can be improved with some daily activities and applications. These activities include but not limited to basic word puzzles, daily cleaning activities, taking notes. Later, these activities and their results should be observed carefully and it is only possible during patient/caregiver and M.D. in-person meetings in hospitals. These meetings can be quite time-consuming, exhausting and financially ineffective for hospitals, medical doctors, caregivers and especially for patients. On the other hand, digital support systems are showing positive results for all stakeholders of healthcare systems. This can be observed in countries that started Telemedicine systems. The biggest potential of our system is setting the inter-user communication up in the best possible way. In our project, we propose Machine Learning based digitalization of validated traditional cognitive tests (e.g. MOCA, Afazi, left-right hemisphere), their analyses for high-quality follow-up and communication systems for all stakeholders. R. Bakir and G. Kayar are with Gefeasoft, Inc, R&D – Software Development and Health Technologies company. Emails: ramazan, gizem @ gefeasoft.com This platform has a high potential not only for patient tracking but also for making all stakeholders feel safe through all stages. As the registered hospitals assign corresponding medical doctors to the system, these MDs are able to register their own patients and assign special tasks for each patient. With our integrated machine learning support, MDs are able to track the failure and success rates of each patient and also see general averages among similarly progressed patients. In addition, our platform also supports multi-player technology which helps patients play with their caregivers so that they feel much safer at any point they are uncomfortable. By also gamifying the daily household activities, the patients will be able to repeat their social tasks and we will provide non-pharmacological reminiscence therapy (RT – life review therapy). All collected data will be mined by our data scientists and analyzed meaningfully. In addition, we will also add gamification modules for caregivers based on Naomi Feil’s Validation Therapy. Both are behaving positively to the patient and keeping yourself mentally healthy is important for caregivers. We aim to provide a therapy system based on gamification for them, too. When this project accomplishes all the above-written tasks, patients will have the chance to do many tasks at home remotely and MDs will be able to follow them up very effectively. We propose a complete platform and the whole project is both time and cost-effective for supporting all stakeholders.

Keywords: alzheimer’s, dementia, cognitive functionality, cognitive tests, serious games, machine learning, artificial intelligence, digitalization, non-pharmacological, data analysis, telemedicine, e-health, health-tech, gamification

Procedia PDF Downloads 131