Search results for: learning attitudes

Authors: Joanna Konstantinou

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The study is about the challenges faced by entrepreneurs in a crisis context and in turbulent economies. The scope is to determine which factors, if any, are related to the success of a new business venture, such as innovation, access to funding and capital, enhanced digital skills, employment relations and organizational culture as well as a company’s strategic orientation towards international markets. The crisis context has been recorded to have affected the number of SMEs in the Greek economy, the number of people employed as well as the volume of the output produced. Although not all SMEs have been equally impacted by the crisis, which has been identified to affect certain sectors more than others, and although research is not exhaustive in that end, employment relations and patterns, firm’s age, and innovation practices in relation to employees’ learning curve seem to have a positive correlation with the successful survival and resilience of the firm. The aim is to identify important factors that can contribute positively to the success of a startup business, and that will allow businesses to acquire resilience and survive economic adversities, and it will focus on businesses of the Greek economy, the country with the longer lasting economic crisis and the findings will be lessons to learn for other economies.

Keywords: entrepreneurship, innovation, crisis, challenges

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Authors: Mamta M. Barapatre, V. N. Sahare

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Since from long time two wheeled vehicle self-balancing has always been a back-breaking task for both human and robots. Leaning a bicycle driving is long time process and goes through building knowledge base for parameter decision making while balancing robots. In order to create this machine learning phase with embedded system the proposed system is designed. The system proposed aims to construct a bicycle automaton, power-driven by an electric motor, which could balance by itself and move along a specific path. This path could be wavy with bumps and varying widths. The key aim was to construct a cycle which self-balances itself by controlling its handle. In order to take a turn, the mass was transferred to the center. In order to maintain the stability, the bicycle bot automatically turned the handle and a turn. Some problems were faced by the team which were Speed, Steering mechanism through mass- distribution (leaning), Center of mass location and gyroscopic effect of its wheel. The idea proposed have potential applications in automation of transportation system and is most efficient.

Keywords: gyroscope-flywheel, accelerometer, servomotor-controller, self stability concept

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Authors: Shih-Yu Wang, Shun-Wen Hsiao

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In the field of cybersecurity, there exists many vendors giving malware samples classified results, namely naming after the label that contains some important information which is also called AV label. Lots of researchers relay on AV labels for research. Unfortunately, AV labels are too cluttered. They do not have a fixed format and fixed naming rules because the naming results were based on each classifiers' viewpoints. A way to fix the problem is taking a majority vote. However, voting can sometimes create problems of bias. Thus, we create a novel ensemble approach which does not rely on the cacophonous naming result but depend on group identification to aggregate everyone's opinion. To achieve this purpose, we develop an scoring system called Pairwise Consensus Score (PCS) to calculate result similarity. The entire method architecture combine Genetic Algorithm and PCS to find maximum consensus in the group. Experimental results revealed that our method outperformed the majority voting by 10% in term of the score.

Keywords: genetic algorithm, ensemble learning, malware family, malware labeling, AV labels

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Authors: Jennifer Buz, Alvin Spivey

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The most common greenhouse gas emitted through human activities, carbon dioxide (CO2), is naturally consumed by plants during photosynthesis. This process is actively being monetized by companies wishing to offset their carbon dioxide emissions. For example, companies are now able to purchase protections for vegetated land due-to-be clear cut or purchase barren land for reforestation. Therefore, by actively preventing the destruction/decay of plant matter or by introducing more plant matter (reforestation), a company can theoretically offset some of their emissions. One of the biggest issues in the carbon credit market is validating and verifying carbon offsets. There is a need for a system that can accurately and frequently ensure that the areas sold for carbon credits have the vegetation mass (and therefore for carbon offset capability) they claim. Traditional techniques for measuring vegetation mass and determining health are costly and require many person-hours. Orbital Sidekick offers an alternative approach that accurately quantifies carbon mass and assesses vegetation health through satellite hyperspectral imagery, a technique which enables us to remotely identify material composition (including plant species) and condition (e.g., health and growth stage). How much carbon a plant is capable of storing ultimately is tied to many factors, including material density (primarily species-dependent), plant size, and health (trees that are actively decaying are not effectively storing carbon). All of these factors are capable of being observed through satellite hyperspectral imagery. This abstract focuses on speciation. To build a species classification model, we matched pixels in our remote sensing imagery to plants on the ground for which we know the species. To accomplish this, we collaborated with the researchers at the Teakettle Experimental Forest. Our remote sensing data comes from our airborne “Kato” sensor, which flew over the study area and acquired hyperspectral imagery (400-2500 nm, 472 bands) at ~0.5 m/pixel resolution. Coverage of the entire teakettle experimental forest required capturing dozens of individual hyperspectral images. In order to combine these images into a mosaic, we accounted for potential variations of atmospheric conditions throughout the data collection. To do this, we ran an open source atmospheric correction routine called ISOFIT1 (Imaging Spectrometer Optiman FITting), which converted all of our remote sensing data from radiance to reflectance. A database of reflectance spectra for each of the tree species within the study area was acquired using the Teakettle stem map and the geo-referenced hyperspectral images. We found that a wide variety of machine learning classifiers were able to identify the species within our images with high (>95%) accuracy. For the most robust quantification of carbon mass and the best assessment of the health of a vegetated area, speciation is critical. Through the use of high resolution hyperspectral data, ground-truth databases, and complex analytical techniques, we are able to determine the species present within a pixel to a high degree of accuracy. These species identifications will feed directly into our carbon mass model.

Keywords: hyperspectral, satellite, carbon, imagery, python, machine learning, speciation

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Authors: Lystra Huggins

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The COVID-19 pandemic affected all facets of life, including pedagogical strategies and perceptual experiences for both instructors and students. While there have also been many challenges and advantages to the online teaching and learning environment, when students’ cameras are on, the daily experiences of students’ lives have been magnified during synchronous online instruction and have served to humanize them in the classroom. This means that students’ everyday experiences, now often on display on ZOOM, allow instructors to see the realities of students. They include children running, spouses walking by parents cooking or sitting on the sofa following the lecture, students at their place of employment or driving from work, or having their classroom engagement interrupted by a delivery. Students’ backgrounds and spaces create unique dynamics during synchronous instruction, which offers a holistic view of them outside academia. This research explores whether witnessing students’ daily experiences leads to empathy from their instructors and whether it results in a greater understanding of students’ challenges and circumstances. Ultimately, it will amplify instructors’ stance on the advantages of students having their cameras on during synchronous online classes to develop a connection with the instructor and a more cohesive classroom environment.

Keywords: instructor’s empathy, synchronous class, asynchronous class, online environment

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Authors: Rendani Mercy Makhwathana

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This paper intends to explore teachers' encounters when teaching English First Additional Language in rural public schools. Teachers are pillars of any education system around the globe. Educational transformations hinge on them as critical role players in the education system. Thus, teachers' encounters are worth consideration, for they impact learners' learning and the well-being of education in general. An exploratory qualitative approach was used in this paper. The population for this paper comprised all Foundation Phase teachers in the district. A purposive sample of 15 Foundation Phase teachers from five rural-based schools was used. Data were collected through classroom observation and individual face-to-face interviews. Data were categorized, analyzed, and interpreted. Amongst the revealed teachers' encounters are learners' inability to read and write and learners' lack of English language background and learners' lack of the vocabulary to express themselves. This paper recommends the provision of relevant resources and support to effectively teach English First Additional Language to enable learners' engagement and effective use of the English language.

Keywords: first additional language, english second language, medium of instruction, teacher professional development

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Authors: Shirley S. Ho, Alisius X. L. D. Leong, Jiemin Looi, Agnes S. F. Chuah

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Nuclear energy is a contentious technology that has attracted much public debate over the years. The prominence of nuclear energy in Southeast Asia (SEA) has burgeoned due to the surge of interest and plans for nuclear development in the region. Understanding public perceptions of nuclear energy in SEA is pertinent given the limited number of studies conducted. In particular, five SEA nations – Singapore, Malaysia, Indonesia, Thailand, and Vietnam are of immediate interest as that they are amongst the most economically developed or developing nations in the SEA region. High energy demands from economic development in these nations have led to considerations of adopting nuclear energy as an alternative source of energy. This study aims to explore whether differences in the nuclear developmental stage in each country affects public perceptions of nuclear energy. In addition, this study seeks to find out about the type and importance of communication credibility as a judgement heuristic in facilitating message acceptance across these five countries. Credibility of a communication channel is a crucial component influencing public perception, acceptance, and attitudes towards nuclear energy. Aside from simply identifying the frequently used communication channels, it is of greater significance to understand public perception of source and media credibility. Given the lack of studies conducted in SEA, this exploratory study adopts a qualitative approach to elicit a spectrum of opinions and insights regarding the key communication aspects influencing public perceptions of nuclear energy. Specifically, the capitals of each of the abovementioned countries - Kuala Lumpur, Bangkok, and Hanoi - were selected, with the exception of Singapore, an island city-state, and Yogyakarta, the most populous island of Indonesia to better understand public perception towards nuclear energy. Focus group discussions were utilized as the mode of data collection to elicit a wide variety of viewpoints held by the participants, which is well-suited for exploratory research. In total, 156 participants took part in the 13 focus group discussions. The participants were either local citizens or permanent residents aged between 18 and 69 years old. Each of the focus groups consists of 8-10 participants, including both male and female participants. The transcripts from each focus group were analysed using NVivo 10, and the text was organised according to the emerging themes or categories. The general public in all the countries was familiar but had no in-depth knowledge with nuclear energy. Four dimensions of nuclear energy communication were identified based on the focus group discussions: communication channels, perceived credibility of sources, circumstances for discussion, and discussion style. The first dimension, communication channels refers to the medium through which participants receive information about nuclear energy. Four types of media emerged from the discussions. They included online and social media, broadcast media, print media, and word-of- mouth (WOM). Collectively, across all five countries, participants were found to engage in different types of knowledge acquisition and information seeking behavior depending on the communication channels used.

Keywords: nuclear energy, public perception, communication, Southeast Asia, source credibility

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Authors: Ehsan K. Hazaveh

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This research project explores creative methods of storytelling through photography to portray a vulnerable and marginalised community: former refugees living in Wellington, New Zealand. The project explores photographic representational techniques that can not only empower and give voice to those communities but also challenge dominant stereotypes about refugees and support humanitarian actions. The aims of this study are to develop insights surrounding issues associated with the photographic representation of refugees and to explore the collaborative construction of possible counter-narratives that might lead to the formulation of a practice framework for representing refugees using photography. In other words, the goal of this study is to explore representational and narrative strategies that frame refugees as active community members and as individuals with specific histories and expertise. These counter-narratives will bring the diversity of refugees to the surface by offering personal stories, contextualising their experience, raising awareness about the plight and human rights of the refugee community in New Zealand, evoking empathy and, therefore, facilitating the process of social change. The study has designed a photographic narrative framework by determining effective methods of photo storytelling, framing, and aesthetic techniques, focusing on different ways of taking, selecting, editing and curating photographs. Photo elicitation interviews have been used to ‘explore’, ‘produce’ and ‘co-curate’ the counter-narrative along with participants. Photo elicitation is a qualitative research method that employs images to evoke data in order to find out how other people experience their world - the researcher shows photographs to the participant and asks open-ended questions to get them to talk about their life experiences and the world around them. The qualitative data have been collected and produced through interactions with four former refugees living in Wellington, New Zealand. In this way, this project offers a unique account of their conditions and basic knowledge about their living experience and their stories. The participants of this study have engaged with PhotoVoice, a photo elicitation methodology that employs photography and storytelling, to share activities, emotions, hopes, and aspects of their lived experiences. PhotoVoice was designed to empower members of marginalised populations. It involves a series of meeting sessions, in which participants share photographs they have taken and discuss stories about the photographs to identify, represent, and enhance the issues important to their lives and communities. Finally, the data provide a basis for systematically producing visual counter-narratives that highlight the experiences of former- refugees. By employing these methods, refugees can represent their world as well as interpret it. The process of developing this research framing has enabled the development of powerful counter-narratives that challenge prevailing stereotypical depictions which in turn have the potential to shape improved humanitarian outcomes, shifts in public attitudes and political perspectives in New Zealand.

Keywords: media, photography, refugees, photo-elicitation, storytelling

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Authors: Nien-Te Kuo, Yi-Sung Cheng, Kuo-Chien Chang

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Cultural festival tourism is now seen by many as an opportunity to facilitate community development because it has significant influences on the economic, social, cultural, and political aspects of local communities. The potential for tourist attraction has been recognized as a useful tool to strengthen local economies from governments. However, most community festivals in Taiwan are short-lived, often only lasting for a few years or occasionally not making it past a one-off event. Researchers suggested that most governments and other stakeholders do not recognize the importance of building a partnership with residents when developing community tourism. Thus, the sustainable community tourism development still remains a key issue in the existing literature. The success of community tourism is related to the attitudes and lifestyles of local residents. In order to maintain sustainable tourism, residents need to be seen as development partners. Residents’ support intention for tourism development not only helps to increase awareness of local culture, history, the natural environment, and infrastructure, but also improves the interactive relationship between the host community and tourists. Furthermore, researchers have identified the social capital theory as the core of sustainable community tourism development. The social capital of residents has been seen as a good way to solve issues of tourism governance, forecast the participation behavior and improve support intention of residents. In addition, previous studies have pointed out the role of community participation and place identity in increasing resident support intention for tourism development. A lack of place identity is one of the main reasons that community tourism has become a mere formality and is not sustainable. It refers to how much residents participate during tourism development and is mainly influenced by individual interest. Scholars believed that the place identity of residents is the soul of community festivals. It shows the community spirit to visitors and has significant impacts on tourism benefits and support intention of residents in community tourism development. Although the importance of community participation and place identity have been confirmed by both governmental and non-governmental organizations, real-life execution still needs to be improved. This study aimed to use social capital theory to investigate the social structure between community residents, participation levels in festival tourism, degrees of place identity, and resident support intention for future community tourism development, and the causal relationship that these factors have with cultural festival tourism. A quantitative research approach was employed to examine the proposed model. Structural equation model was used to test and verify the proposed hypotheses. This was a case study of the Kaohsiung Zuoying Wannian Folklore Festival. The festival was located in the Zuoying District of Kaohsiung City, Taiwan. The target population of this study was residents who attended the festival. The results reveal significant correlations among social capital, community participation, place identity and support intention. The results also confirm that impacts of social capital on support intention were significantly mediated by community participation and place identity. Practical suggestions were provided for tourism operators and policy makers. This work was supported by the Ministry of Science and Technology of Taiwan, Republic of China, under the grant MOST-105-2410-H-328-013.

Keywords: community participation, place identity, social capital, support intention

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Authors: B. Ozarisoy, E. Ampatzi, G. Z. Lancaster

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This research project is undertaken in the Turkish Republic of Northern Cyprus (T.R.N.C). The study focuses on identifying refurbishment activities capable of diagnosing and detecting the underlying problems alongside the challenges offered by the buildings’ typology in addition to identifying the correct construction materials in the refurbishment process which allow for the maximisation of expected energy savings. Attention is drawn to, the level of awareness and understanding of refurbishment activity that needs to be raised in the current construction process alongside factors that include the positive environmental impact and the saving of energy. The approach here is to look at buildings that have been built by private construction companies that have already been refurbished by occupants and to suggest additional control mechanisms for retrofitting that can further enhance the process of renewal. The objective of the research is to investigate the occupants’ behaviour and role in the refurbishment activity; to explore how and why occupants decide to change building components and to understand why and how occupants consider using energy-efficient materials. The present work is based on data from this researcher’s first-hand experience and incorporates the preliminary data collection on recent housing sector statistics, including the year in which housing estates were built, an examination of the characteristics that define the construction industry in the T.R.N.C., building typology and the demographic structure of house owners. The housing estates are chosen from 16 different projects in four different regions of the T.R.N.C. that include urban and suburban areas. There is, therefore, a broad representation of the common drivers in the property market, each with different levels of refurbishment activity and this is coupled with different samplings from different climatic regions within the T.R.N.C. The study is conducted through semi-structured interviews to identify occupants’ behaviour as it is associated with refurbishment activity. The interviews provide all the occupants’ demographic information, needs and intentions as they relate to various aspects of the refurbishment process. This research paper presents the results of semi-structured interviews with 70 homeowners in a selected group of 16 housing estates in five different parts of the T.R.N.C. The people who agreed to be interviewed in this study are all residents of single or multi-family housing units. Alongside the construction process and its impact on the environment, the results point out the need for control mechanisms in the housing sector to promote and support the adoption of retrofit strategies and minimize non-controlled refurbishment activities, in line with diagnostic information of the selected buildings. The expected solutions should be effective, environmentally acceptable and feasible given the type of housing projects under review, with due regard for their location, the climatic conditions within which they were undertaken, the socio-economic standing of the house owners and their attitudes, local resources and legislative constraints. Furthermore, the study goes on to insist on the practical and long-term economic benefits of refurbishment under the proper conditions and why this should be fully understood by the householders.

Keywords: construction process, energy-efficiency, refurbishment activity, retrofitting

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Authors: S. Biondi, V. Catania, R. Di Natale, A. R. Intilisano, D. Panno

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One of the major goals of Spoken Dialog Systems (SDS) is to understand what the user utters. In the SDS domain, the Spoken Language Understanding (SLU) Module classifies user utterances by means of a pre-definite conceptual knowledge. The SLU module is able to recognize only the meaning previously included in its knowledge base. Due the vastity of that knowledge, the information storing is a very expensive process. Updating and managing the knowledge base are time-consuming and error-prone processes because of the rapidly growing number of entities like proper nouns and domain-specific nouns. This paper proposes a solution to the problem of Name Entity Recognition (NER) applied to a SDS domain. The proposed solution attempts to automatically recognize the meaning associated with an utterance by using the PANKOW (Pattern based Annotation through Knowledge On the Web) method at runtime. The method being proposed extracts information from the Web to increase the SLU knowledge module and reduces the development effort. In particular, the Google Search Engine is used to extract information from the Facebook social network.

Keywords: spoken dialog system, spoken language understanding, web semantic, name entity recognition

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Authors: Yagya Raj Pandeya, Joonwhoan Lee

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The dynamic behavior of music and video makes it difficult to evaluate musical instrument playing in a video by computer system. Any television or film video clip with music information are rich sources for analyzing musical instruments using modern machine learning technologies. In this research, we integrate the audio and video information sources using convolutional neural network (CNN) and pass network learned features through recurrent neural network (RNN) to preserve the dynamic behaviors of audio and video. We use different pre-trained CNN for music and video feature extraction and then fine tune each model. The music network use 2D convolutional network and video network use 3D convolution (C3D). Finally, we concatenate each music and video feature by preserving the time varying features. The long short term memory (LSTM) network is used for long-term dynamic feature characterization and then use late fusion with generalized mean. The proposed network performs better performance to recognize the musical instrument using audio-video multimodal neural network.

Keywords: multimodal, 3D convolution, music-video feature extraction, generalized mean

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Authors: Manana Lobzhanidze

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The COVID-19 pandemic has made significant changes in migration processes, notably changes in the study migration process. The constraints caused by the COVID-19 pandemic led to changes in the studying process, which negatively affected its efficiency. The educational process has partially or completely shifted to distance learning; Both labor and study migration have increased significantly in the world. The employment and education market has become global and consequently, a number of challenges have arisen for employers, researchers, and businesses. The role of preparing qualified personnel in achieving high productivity is justified, the benefits for employers and employees are assessed on the one hand, and the role of study migration for the country’s development is examined on the other hand. Research methods. The research is based on methods of analysis and synthesis, quantitative and qualitative, groupings, relative and mean quantities, graphical representation, comparison, analysis and etc. In-depth interviews were conducted with experts to determine quantitative and qualitative indicators. Research findings. Factors affecting study migration are analysed in the paper and the environment that stimulates migration is explored. One of the driving forces of migration is considered to be the desire for receiving higher pay. Levels and indicators of study migration are studied by country. Comparative analysis has found that study migration rates are high in countries where the price of skilled labor is high. The productivity of individuals with low skills is low, which negatively affects the economic development of countries. It has been revealed that students leave the country to improve their skills during study migration. The process mentioned in the article is evaluated as a positive event for a developing country, as individuals are given the opportunity to share the technology of developed countries, gain knowledge, and then introduce it in their own country. The downside of study migration is the return of a small proportion of graduates from developed economies to their home countries. The article concludes that countries with emerging economies devote less resources to research and development, while this is a priority in developed countries, allowing highly skilled individuals to use their skills efficiently. The paper studies the national education system examines the level of competition in the education market and the indicators of educational migration. The level of competition in the education market and the indicators of educational migration are studied. The role of qualified personnel in achieving high productivity is substantiated, the benefits of employers and employees are assessed on the one hand, and the role of study migration in the development of the country is revealed on the other hand. The paper also analyzes the level of competition in the education and labor markets and identifies indicators of study migration. During the pandemic period, there was a great demand for the digital technologies. Open access to a variety of comprehensive platforms will significantly reduce study migration to other countries. As a forecast, it can be said that the intensity of the use of e-learning platforms will be increased significantly in the post-pandemic period. The paper analyzes the positive and negative effects of study migration on economic development, examines the challenges of study migration in light of the COVID-19 pandemic, suggests ways to avoid negative consequences, and develops recommendations for improving the study migration process in the post-pandemic period.

Keywords: study migration, COVID-19 pandemic, factors affecting migration, economic development, post-pandemic migration

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Authors: Angely Sim Jia Wun, Sasa Arsovski

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Numerous studies have been conducted on the segmentation of medical images. Segmenting the lungs is one of the common research topics in those studies. Our research stemmed from the lack of solutions for automatic bone, airway, and vessel segmentation, despite the existence of multiple lung segmentation techniques. Consequently, currently, available software tools used for medical image segmentation do not provide automatic lung, bone, airway, and vessel segmentation. This paper presents segmentation techniques along with an interactive software tool architecture for segmenting bone, lung, airway, and vessel tissues. Additionally, we propose a method for creating binary masks from automatically generated segments. The key contribution of our approach is the technique for automatic image thresholding using adjustable Hounsfield values and binary mask extraction. Generated binary masks can be successfully used as a training dataset for deep-learning solutions in medical image segmentation. In this paper, we also examine the current software tools used for medical image segmentation, discuss our approach, and identify its advantages.

Keywords: lung segmentation, binary masks, U-Net, medical software tools

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Authors: Scott N. Gerard, Aliza Heching, Susann M. Keohane, Samuel S. Adams

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The world-wide population of people over 60 years of age is growing rapidly. The explosion is placing increasingly onerous demands on individual families, multiple industries and entire countries. Current, human-intensive approaches to eldercare are not sustainable, but IoT and AI technologies can help. The Knowledge Reactor (KR) is a contextual, data fusion engine built to address this and other similar problems. It fuses and centralizes IoT and System of Record/Engagement data into a reactive knowledge graph. Cognitive applications and services are constructed with its multiagent architecture. The KR can scale-up and scaledown, because it exploits container-based, horizontally scalable services for graph store (JanusGraph) and pub-sub (Kafka) technologies. While the KR can be applied to many domains that require IoT and AI technologies, this paper describes how the KR specifically supports the challenging domain of cognitive eldercare. Rule- and machine learning-based analytics infer activities of daily living from IoT sensor readings. KR scalability, adaptability, flexibility and usability are demonstrated.

Keywords: ambient sensing, AI, artificial intelligence, eldercare, IoT, internet of things, knowledge graph

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Authors: Sezen Aslan, N. Aydan Sat

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The society of 21st century constantly faces with complex otherness that emerges in various forms and justifications. Otherness caused by class, race or ethnicity inevitably reflects to urban areas, and in this way, cities are diversified into totally self-centered and closed-off urban enclaves. One of the most important dynamics that creates otherness in contemporary society is migration. Immigration on an international scale is one of the most important events that have reshaped the world, and the number of immigrants in the world is increasing day by day. Forced migration and refugee statements constitute the major part of countries' immigration policies and practices. Domestic problems such as racism, violence, war, censorship and silencing, attitudes contrary to human rights, different cultural or religious identities cause populations to migrate. Immigration is one of the most important reasons for the formation of urban enclaves within cities. Turkey, which was used to face a higher rate of outward migration, has begun to host immigrant groups from foreign countries. 1980s is the breaking point about the issue as a result of internal disturbances in the Middle East. After Iranian, Iraqi and Afghan immigrants, Turkey faces the largest external migration in its story with Syrian population. Turkey has been hosting approximate three million Syrian people after Syrian Civil War which started in 2011. 92% of Syrian refugees are currently living in different urban areas in Turkey instead of camps. Syrian refugees are experiencing a spontaneous spatiality due to the lack of specific settlement and housing policies of the country. This spontaneity is one of the most important factors in the creation of urban enclaves. From this point of view, the aim of this study is to clarify processes that lead the creation of urban enclaves and to explain socio-spatial effects of these urban enclaves to the other parts of the cities. Ankara, which is one of the most registered Syrian hosting Province in Turkey, is selected as a case study area. About 55% of the total Syrian population lives in the Altındağ district in Ankara. They settled specifically in two neighborhoods in Altındağ district, named as Önder and Ulubey. These neighborhoods are old slum areas, and they were evacuated due to urban renewal on the same dates with the migration of the Syrians. Before demolition of these old slums, Syrians are settled into them as tenants. In the first part of the study, a brief explanation of the concept of urban enclave, its occurrence parameters and possible socio-spatial threats, examples from previous immigrant urban enclaves caused internal migration will be given. Emergence of slums, planning history and social processes in the case study area will be described in the second part of the study. The third part will be focused on the Syrian refugees and their socio-spatial relationship in the case study area and in-depth interviews with refugees and spatial analysis will be realized. Suggestions for the future of the case study area and recommendations to prevent immigrant groups from social and spatial exclusion will be discussed in the conclusion part of the study.

Keywords: migration, immigration, Syrian refugees, urban enclaves, Ankara

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Authors: Oluyemi Christianah Ojo

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This study seeks to investigate the quality of ICT provided in the new Caring Heart schools in Ondo State, Nigeria. The population for the study was all caring Heart Mega Schools in Ondo State, Nigeria. Research questions were generated; two instruments CCCMS and TQCUC were used to elicit information from the schools and the teachers. The study adopts descriptive survey approach. The studies revealed and concluded that ICT components were available and adequate in these schools, Charts showing ICT components and other forms of computer devices used as instructional materials were available but were not adequate; teachers teaching computer studies are competent in the delivery of instructions and in handling computer gadgets in the laboratory. The study recommended the provision of steady electricity, uninterrupted internet facilities and provision of adequate ICT components and charts for effective teaching delivery and learning.

Keywords: facilities, information communication technology, mega primary school, primary education

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Authors: Yan Li

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Purpose: There is a lack of suitable recommendation systems to assist engineering teaching. The existing traditional engineering pedagogies lack learning interests for postgraduate students. The knowledge graph-based recommender system aims to enhance postgraduate students’ programming skills, with a focus on programming courses. Design/methodology/approach: The case study will be used as a major research method, and the two case studies will be taken in both two teaching styles of the universities (Zhejiang University and the University of Nottingham Ningbo China), followed by the interviews. Quantitative and qualitative research methods will be combined in this study. Research limitations/implications: The case studies were only focused on two teaching styles universities, which is not comprehensive enough. The subject was limited to postgraduate students. Originality/value: The study collected and analyzed the data from two teaching styles of universities’ perspectives. It explored the challenges of Engineering education and tried to seek potential enhancement.

Keywords: knowledge graph and recommender system, engineering pedagogy, programming skills, postgraduate students

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Authors: M. Mokhtarzadeh, M. Taheri Qomi, M. Nikafrooz, A. Atashafrooz

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The purpose of the present study was to investigate the effectiveness of using motion graphics as a learning medium on training hearing aids maintenance skills to hearing-impaired children. The statistical population of this study consisted of all children with hearing loss in Ahvaz city, at age 4 to 7 years old. As the sample, 60, whom were selected by multistage random sampling, were randomly assigned to two groups; experimental (30 children) and control (30 children) groups. The research method was experimental and the design was pretest-posttest with the control group. The intervention consisted of a 2-minute motion graphics clip to train hearing aids maintenance skills. Data were collected using a 9-question researcher-made questionnaire. The data were analyzed by using one-way analysis of covariance. Results showed that the training of hearing aids maintenance skills with motion graphics was significantly effective for those children. The results of this study can be used by educators, teachers, professionals, and parents to train children with disabilities or normal students.

Keywords: hearing aids, hearing aids maintenance skill, hearing impaired children, motion graphics

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Authors: Fereshteh Nazeri Bahadori

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In today's competitive environment, any company that aims to operate in a market, whether industrial or consumer markets, must know that it cannot address all the tastes and demands of customers at once and serve them all. The study of consumer memory is considered an important subject in marketing research, and many companies have conducted studies on this subject and the factors affecting it due to its importance. Therefore, the current study tries to investigate the relationship between consumers' attention, literacy, and memory. Memory has a very close relationship with learning. Memory is the collection of all the information that we have understood and stored. One of the important subjects in consumer behavior is information processing by the consumer. One of the important factors in information processing is the mental involvement of the consumer, which has attracted a lot of attention in the past two decades. Since consumers are the turning point of all marketing activities, successful marketing begins with understanding why and how consumers behave. Therefore, in the current study, the role of executive attention and literacy on consumers' memory has been investigated. The results showed that executive attention and literacy would play a significant role in the long-term and short-term memory of consumers.

Keywords: literacy, consumer memory, executive attention, psychology of consumer behavior

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Authors: Ana B. Vivas, Antonia Ypsilanti, Aristea I. Ladas, Angeles F. Estevez

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Mild Cognitive Impairment (MCI) is considered an intermediate stage between normal and pathological aging, as a substantial percentage of people diagnosed with MCI converts later to dementia of the Alzheimer’s type. Memory is of the first cognitive processes to deteriorate in this condition. In the present study we employed the differential outcomes procedure (DOP) to improve visuospatial memory in a group of participants with MCI. The DOP requires the structure of a conditional discriminative learning task in which a correct choice response to a specific stimulus-stimulus association is reinforced with a particular reinforcer or outcome. A group of 10 participants with MCI, and a matched control group had to learn and keep in working memory four target locations out of eight possible locations where a shape could be presented. Results showed that participants with MCI had a statistically significant better terminal accuracy when a unique outcome was paired with a location (76% accuracy) as compared to a non differential outcome condition (64%). This finding suggests that the DOP is useful in improving working memory in MCI patients, which may delay their conversion to dementia.

Keywords: mild cognitive impairment, working memory, differential outcomes, cognitive process

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Authors: Hong Lu, Xiong Xiao

Abstract:

Shaft parts are widely used in machinery industry, however, bending deformation often occurred when this kind of parts is being heat treated. This parts needs to be straightened to meet the requirement of straightness. As for the pressure straightening process, a good straightening stroke algorithm is related to the precision and efficiency of straightening process. In this paper, the relationship between straightening load and deflection during the straightening process is analyzed, and the mathematical model of the straightening process has been established. By the mathematical model, the iterative method is used to solve the straightening stroke. Compared to the traditional straightening stroke algorithm, straightening stroke calculated by this method is much more precise; because it can adapt to the change of material performance parameters. Considering that the straightening method is widely used in the mass production of the shaft parts, knowledge base is used to store the data of the straightening process, and a straightening stroke algorithm based on empirical data is set up. In this paper, the straightening process control model which combine the straightening stroke method based on iteration and straightening stroke algorithm based on empirical data has been set up. Finally, an experiment has been designed to verify the straightening process control model.

Keywords: straightness, straightening stroke, deflection, shaft parts

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Authors: Bin Ji, Kai Xu, Shunyu Yao, Jingjing Liu, Ye Pan

Abstract:

Human pose estimation is a popular research area in computer vision for its important application in human-machine interface. In recent years, 2D human pose estimation based on convolution neural network has got great progress and development. However, in more and more practical applications, people often need to deal with tasks based on video. It’s not far-fetched for us to consider how to combine the spatial and temporal information together to achieve a balance between computing cost and accuracy. To address this issue, this study proposes a new spatiotemporal model, namely Spatiotemporal Net (STNet) to combine both temporal and spatial information more rationally. As a result, the predicted keypoints heatmap is potentially more accurate and spatially more precise. Under the condition of ensuring the recognition accuracy, the algorithm deal with spatiotemporal series in a decoupled way, which greatly reduces the computation of the model, thus reducing the resource consumption. This study demonstrate the effectiveness of our network over the Penn Action Dataset, and the results indicate superior performance of our network over the existing methods.

Keywords: convolutional long short-term memory, deep learning, human pose estimation, spatiotemporal series

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Authors: Zhifeng Kong

Abstract:

Over-parameterized neural networks have attracted a great deal of attention in recent deep learning theory research, as they challenge the classic perspective of over-fitting when the model has excessive parameters and have gained empirical success in various settings. While a number of theoretical works have been presented to demystify properties of such models, the convergence properties of such models are still far from being thoroughly understood. In this work, we study the convergence properties of training two-hidden-layer partially over-parameterized fully connected networks with the Rectified Linear Unit activation via gradient descent. To our knowledge, this is the first theoretical work to understand convergence properties of deep over-parameterized networks without the equally-wide-hidden-layer assumption and other unrealistic assumptions. We provide a probabilistic lower bound of the widths of hidden layers and proved linear convergence rate of gradient descent. We also conducted experiments on synthetic and real-world datasets to validate our theory.

Keywords: over-parameterization, rectified linear units ReLU, convergence, gradient descent, neural networks

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Authors: Aşina Gülerarslan, M. Faik Özdengül

Abstract:

The new economic, social and political world order has led to the emergence of a wide range of persuasion strategies and practices based on an ever expanding marketing axis that involves organizations, ideas and persons as well as products and services. It is seen that since the 1990's, a wide variety of competitive marketing ideas have been offered systematically to target audiences in the field of politics as in other fields. When the components of marketing are taken into consideration, all kinds of communication efforts involving “political leaders”, who are conceptualized as products in terms of political marketing, serve a process of social persuasion, which cannot be restricted to election periods only, and a manageable “image”. In this context, image, which is concerned with how the political product is perceived, involves not only the political discourses shared with the public but also all kinds of biographical information about the leader, the leader’s specific way of living and routines and his/her attitudes and behaviors in their private lives, and all these are regarded as components of the “product image”. While on the one hand the leader’s verbal or supra-verbal references serve the way the “spirit of the product” is perceived –just as in brand positioning- they also show their self-esteem levels, in other words how they perceive themselves on the other hand. Indeed, their self-esteem levels are evaluated in three fundamental categories in the “Functional Analysis”, namely parent, child and adult, and it is revealed that the words, tone of voice and body language a person uses makes it easy to understand at what self-esteem level that person is. In this context, words, tone of voice and body language, which provide important clues as to the “self” of the person, are also an indication of how political leaders evaluate both “themselves” and “the mass/audience” in the communication they establish with their audiences. When the matter is taken from the perspective of Turkey, the levels of self-esteem in the relationships that the political leaders establish with the masses are also important in revealing how our society is seen from the perspective of a specific leader. Since the leader is a part of the marketing strategy of a political party as a product, this evaluation is significant in terms of the forms of relationships between political institutions in our country with the society. In this study, the self-esteem level in the documentary entitled “Master’s Story”, where Recep Tayyip Erdoğan’s life history is told, is analyzed in the context of words, tone of voice and body language. Within the scope of the study, at what level of self-esteem Recep Tayyip Erdoğan was in the “Master’s Story”, a documentary broadcast on Beyaz TV, was investigated using the content analysis method. First, based on the Functional Analysis Literature, a transactional approach scale was created regarding parent, adult and child self-esteem levels. On the basis of this scale, the prime minister’s self-esteem level was determined in three basic groups, namely “tone of voice”, “the words he used” and “body language”. Descriptive analyses were made to the data within the framework of these criteria and at what self-esteem level the prime minister spoke throughout the documentary was revealed.

Keywords: political marketing, leader image, level of self-esteem, transactional approach

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Authors: Manar Amayri, Hussain Kazimi, Quoc-Dung Ngo, Stephane Ploix

Abstract:

A general approach is proposed to determine occupant behavior (occupancy and activity) in residential buildings and to use these estimates for improved energy management. Occupant behaviour is modelled with a Bayesian Network in an unsupervised manner. This algorithm makes use of domain knowledge gathered via questionnaires and recorded sensor data for motion detection, power, and hot water consumption as well as indoor CO₂ concentration. Two case studies are presented which show the real world applicability of estimating occupant behaviour in this way. Furthermore, experiments integrating occupancy estimation and hot water production control show that energy efficiency can be increased by roughly 5% over known optimal control techniques and more than 25% over rule-based control while maintaining the same occupant comfort standards. The efficiency gains are strongly correlated with occupant behaviour and accuracy of the occupancy estimates.

Keywords: energy, management, control, optimization, Bayesian methods, learning theory, sensor networks, knowledge modelling and knowledge based systems, artificial intelligence, buildings

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Authors: Yuan Liu, Hongyun Liu

Abstract:

Teacher-student relationship plays an important role on facilitating students’ learning behavior, school engagement, and academic outcomes. It is believed that good relationship will enhance the human agency—the intrinsic motivation—mainly through the strengthening of autonomic support, feeling of relatedness, and the individual’s competence to increase the academic outcomes. This is in line with self-determination theory (SDT), which generally views that the intrinsic motivation imbedded with human basic needs is one of the most important factors that would lead to better school engagement, academic outcomes, and well-being. Based on SDT, the present study explored the relation of among teacher-student relationship (teacher’s encouragement, respect), students’ motivation (extrinsic and intrinsic), and achievement outcomes. The study was based on a large scale academic assessment and questionnaire survey conducted by the Center for Assessment and Improvement of Basic Education Quality in Mainland China (2013) on Grade 8 students. The results indicated that intrinsic motivation mediated the relation between teacher-student relationship and academic achievement outcomes.

Keywords: teacher-student relationship, intrinsic motivation, academic achievement, mediation

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Authors: Blessing Dwumah Manu, Dawn Wallin

Abstract:

This study aims to explore school principal instructional leadership capabilities (Robinson, 2010) that support school performance in senior high schools in Ghana’s Northern Region. It explores the ways in which leaders (a) use deep leadership content knowledge to (b) solve complex school-based problems while (c) building relational trust with staff, parents, and students as they engage in the following instructional leadership dimensions: establishing goals and expectations; resourcing strategically; ensuring quality teaching; leading teacher learning and development and ensuring an orderly and safe environment (Patuawa et al, 2013). The proposed research utilizes a constructivist approach to explore the experiences of 18 school representatives (including principals, deputy principals, department heads, teachers, parents, and students) through an interview method.

Keywords: instructional leadership, leadership content knowledge, solving complex problems, building relational trust and school performance

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Authors: Dev Ras Pandey, Bharat Mishra, S. K. Tripathi

Abstract:

Cloud computing is ready to transform the structure of businesses and learning through supplying the real-time applications and provide an immediate help for small to medium sized businesses. The ability to run a hypervisor inside a virtual machine is important feature of virtualization and it is called nested virtualization. In today’s growing field of information technology, many of the virtualization models are available, that provide a convenient approach to implement, but decision for a single model selection is difficult. This paper explains the applications of operating system based virtualization in cloud computing with an appropriate/suitable model with their different specifications and user’s requirements. In the present paper, most popular models are selected, and the selection was based on container and hypervisor based virtualization. Selected models were compared with a wide range of user’s requirements as number of CPUs, memory size, nested virtualization supports, live migration and commercial supports, etc. and we identified a most suitable model of virtualization.

Keywords: virtualization, OS based virtualization, container based virtualization, hypervisor based virtualization

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Authors: Karen Chad, Louise Humbert, Kenzie Friesen, Dave Sandomirsky

Abstract:

Background: The pandemic of COVID-19 presented many historical challenges to the sporting community. For organizations and individuals, sport was put on hold resulting in social, economic, physical, and mental health consequences for all involved. High school sports are seen as an effective and accessible pathway for students to receive health, social, and academic benefits. Studies examining sport cessation due to COVID-19 found substantial negative outcomes on the physical and mental well-being of participants in the high school setting. However, the pandemic afforded an opportunity to examine sport participation and the value people place upon their engagement in high school sport. Study objectives: (1) Examine the experiences of students, parents, administrators, officials, and coaches during a year without high school sports; (2) Understand why participants are involved in high school sports; and (3) Learn what supports are needed for future involvement. Methodology: A mixed method design was used, including semi-structured interviews and a survey (SurveyMonkey software), which was disseminated electronically to high school students, coaches, school administrators, parents, and officials. Results: 1222 respondents completed the survey. Findings showed: (1) 100% of students participate in high school sports to improve their mental health, with >95% said it keeps them active and healthy, helps them make friends and teaches teamwork, builds confidence and positive self-perceptions, teaches resiliency, enhances connectivity to their school, and supports academic learning; (2) Top three reasons teachers coach is their desire to make a difference in the lives of students, enjoyment, and love of the sport, and to give back. Teachers said what they enjoy most is contributing to and watching athletes develop, direct involvement with student sport success, and the competitiveatmosphere; (3) 90% of parents believe playing sports is a valuable experience for their child, 95% said it enriches student academic learning and educational experiences, and 97% encouraged their child to play school sports; (4) Officials participate because of their enjoyment and love of the sport, experience, and expertise, desire to make a difference in the lives of children, the competitive/sporting atmosphere and growing the sport. 4% of officials said it was financially motivated; (5) 100% of administrators said high school sports are important for everyone. 80% believed the pandemic will decrease teachers coaching and increase student mental health and well-being. When there was no sport, many athletes got a part-time job and tried to stay active, with limited success. Coaches, officials, and parents spent more time with family. All participants did little physical activity, were bored; and struggled with mental health and poor physical health. Respondents recommended better communication, promotion, and branding of high school sport benefits, equitable funding for all sports, athlete development, compensation and recognition for coaching, and simple processes to strengthen the high school sport model. Conclusions: High school sport is an effective vehicle for athletes, parents, coaches, administrators, and officials to derive many positive outcomes. When it is taken away, serious consequences prevail. Paying attention to important success factors will be important for the effectiveness of high school sports.

Keywords: physical activity, high school, sports, pandemic

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