Search results for: intelligent nation

Authors: Ebenezer Joseph

Abstract:

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

Keywords: chess, intelligence, creativity, children

Procedia PDF Downloads 241

Authors: Moser Stephan, Lukasser Gerald, Weitlaner Robert

Abstract:

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

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

Procedia PDF Downloads 91

Authors: Aileen O'loughlin

Abstract:

‘Is Everybody Going WeLL?’ (IEGW?) is a 33-hour classroom-based initiative created to a) explore values and how they impact on well-being, b) encourage adolescents to connect with their community, and c) provide them with the education to encourage and maintain a lifetime love of physical activity (PA) to ensure beneficial effects on their personal well-being. This initiative is also aimed at achieving sustainable education and aligning with the United Nation’s Sustainable Development Goals numbers 3 and 4. The classroom is a unique setting in which adolescents’ PA participation can be positively influenced through fun PA policies and initiatives. The primary purpose of this research is to evaluate a range of psychosocial and PA outcomes following the 33-hour education programme. This research examined the impact of a PA and well-being programme consisting of either a 60minute or 80minute class, depending on the timetable structure of the school, delivered once a week. Participant outcomes were measured using validated questionnaires regarding Self-esteem, Mental Health Literacy (MHL) and Daily Physical Activity Participation. These questionnaires were administered at three separate time points; baseline, mid-intervention, and post intervention. Semi-structured interviews with participating teachers regarding adherence and participants’ attitudes were completed post-intervention. These teachers were randomly selected for interview. This perspective analytical cohort study included 235 post-primary school students between 11-13 years of age (100 boys and 135 girls) from five public Irish post-primary schools. Three schools received the intervention only; a 33hour interactive well-being learning unit, one school formed a control group and one school had participants in both the intervention and control group. Participating schools were a convenience sample. Data presented outlines baseline data collected pre-participation (0 hours completed). N = 18 junior certificate students returned all three questionnaires fully completed for a 56.3% return rate from 1 school, Intervention School #3. 94.4% (n = 17) of participants enjoy taking part in some form of PA, however only 5.5% (n = 1) of the participants took part in PA every day of the previous 7 days and only 5.5% (n = 1) of those surveyed participated in PA every day during a normal week. 55% (n = 11) had a low level of self-esteem, 50% (n = 9) fall within the normal range of self-esteem, and n = 0 surveyed demonstrated a high level of self-esteem. Female participants’ Mean score was higher than their male counterparts when MHL was compared. Correlation analyses revealed a small association between Self-esteem and Happiness (r = 0.549). Positive correlations were also revealed between MHL and Happiness, MHL and Self-esteem and Self-esteem and 60+ minutes of PA completed daily. IEGW? is a classroom-based with simple methods easy to implement, replicate and financially viable to both public and private schools. It’s unique dataset will allow for the evaluation of a societal approach to the psycho-social well-being and PA participation levels of adolescents. This research is a work in progress and future work is required to learn how to best support the implementation of ‘Is Everybody Going WeLL?’ as part of the school curriculum.

Keywords: education, life-long learning, physical activity, psychosocial well-being

Procedia PDF Downloads 101

Authors: Muna Shafiq

Abstract:

Growth in international immigration is a reflection of increased migration patterns in Canada and in other parts of the world. Canada continues to promote itself as a bilingual country, yet the bilingual French and English population numbers do not reflect this platform. Each province’s integration policies focus only on second language learning of either English or French. Moreover, since English Canadians outnumber French Canadians, maintaining, much less increasing, English-French bilingualism appears unrealistic. One solution to increasing Canadian bilingualism requires creating intercultural communication initiatives between youth in Quebec and the rest of Canada. Specifically, the focus is on active, experiential learning, where intercultural competencies develop outside traditional classroom settings. The target groups are Generation Y Millennials and Generation Z Linksters, the next generations in the career and parenthood lines. Today, Canada’s education system, like many others, must continually renegotiate lines between programs it offers its immigrant and native communities. While some purists or right-wing nationalists would disagree, the survival of bilingualism in Canada has little to do with reducing immigration. Children and youth immigrants play a valuable role in increasing Canada’s French and English speaking communities. For instance, a focus on more immersion, over core French education programs for immigrant children and youth would not only increase bilingual rates; it would develop meaningful intercultural attachments between Canadians. Moreover, a vigilant increase of funding in French immersion programs is critical, as are new initiatives that focus on experiential language learning for students in French and English language programs. A favorable argument supports the premise that other than French-speaking students in Québec and elsewhere in Canada, second and third generation immigrant students are excellent ambassadors to promote bilingualism in Canada. Most already speak another language at home and understand the value of speaking more than one language in their adopted communities. Their dialogue and participation in experiential language exchange workshops are necessary. If the proposed exchanges take place inter-provincially, the momentum to increase collective regional voices increases. This regional collectivity can unite Canadians differently than nation-targeted initiatives. The results from an experiential youth exchange organized in 2017 between students at the crossroads of Generation Y and Generation Z in Vancouver and Quebec City respectively offer a promising starting point in assessing the strength of bringing together different regional voices to promote bilingualism. Code-switching between standard, international French Vancouver students, learn in the classroom versus more regional forms of Quebec French spoken locally created regional connectivity between students. The exchange was equally rewarding for both groups. Increasing their appreciation for each other’s regional differences allowed them to contribute actively to their social and emotional development. Within a sociolinguistic frame, this proposed model of experiential learning does not focus on hands-on work experience. However, the benefits of such exchanges are as valuable as work experience initiatives developed in experiential education. Students who actively code switch between French and English in real, not simulated contexts appreciate bilingualism more meaningfully and experience its value in concrete terms.

Keywords: experiential learning, intercultural communication, social and emotional learning, sociolinguistic code-switching

Procedia PDF Downloads 120

Authors: John Mark King

Abstract:

Beginning on Feb. 7, 2019, the luxury brand, Gucci, was met with a firestorm on social media over fashion runway images of its black balaclava sweater, which covered the bottom half of the face and featured large, shiny bright red lips surrounding the mouth cutout. Many observers on social media and in the news media noted the garment resembled racist “blackface.” This study aimed to measure how items were framed across multiple media platforms. The unit of analysis was any headline or lead paragraph published using the search terms “Gucci” and “sweater” or “jumper” or “balaclava” during the one-year timeframe of Feb. 7, 2019, to Feb. 6, 2020. Limitations included headlines and lead paragraphs published in English and indexed in the Lexis/Nexis database. Independent variables were the nation in which the item was published and the platform (newspapers, blogs, web-based publications, newswires, magazines, or broadcast news). Dependent variables were tone toward Gucci (negative, neutral or positive) and frame (blackface/racism/racist, boycott/celebrity boycott, sweater/balaclava/jumper/fashion, apology/pulling the product/diversity initiatives by Gucci or frames unrelated to the controversy but still involving Gucci sweaters) and word count. Two coders achieved 100% agreement on all variables except tone (94.2%) and frame (96.3%). The search yielded 276 items published from 155 sources in 18 nations. The tone toward Gucci during this period was negative (69.9%). Items that were neutral (16.3%) or positive (13.8%) toward the brand were overwhelmingly related to items about other Gucci sweaters worn by celebrities or fashion reviews of other Gucci sweaters. The most frequent frame was apology/pulling the product/diversity initiatives by Gucci (35.5%). The tone was most frequently negative across all continents, including the Middle East (83.3% negative), Asia (81.8%), North America (76.6%), Australia/New Zealand (66.7%), and Europe (59.8%). Newspapers/magazines/newswires/broadcast news transcripts (72.4%) were more negative than blogs/web-based publications (63.6%). The most frequent frames used by newspapers/magazines/newswires/broadcast news transcripts were apology/pulling the product/diversity initiatives by Gucci (38.7%) and blackface/racism/racist (26.1%). Blogs/web-based publications most frequently used frames unrelated to the controversial garment, but about other Gucci sweaters (42.9%) and apology/pulling the product/diversity initiatives by Gucci (27.3%). Sources in Western nations (34.7%) and Eastern nations (47.1%) most frequently used the frame of apology/pulling the product/diversity initiatives by Gucci. Mean word count was higher for negative items (583.58) than positive items (404.76). Items framed as blackface/racism/racist or boycott/celebrity boycott had higher mean word count (668.97) than items framed as sweater/balaclava/jumper/fashion or apology/pulling the product/diversity initiatives by Gucci (498.22). The author concluded that during the year-long period, Gucci’s image was likely damaged by the release of the garment at the center of the controversy due to near-universally negative items published, but Gucci’s apology/pulling the product off the market/diversity initiatives by Gucci and items about other Gucci sweaters worn by celebrities or fashion reviews of other Gucci sweaters were the most common frames across multiple media platforms, which may have mitigated the damage to the brand.

Keywords: Blackface, branding, Gucci, media framing

Procedia PDF Downloads 132

Authors: Hari K. Adhikari, Keshab Sharma, K. C. Apil

Abstract:

The Gorkha Nepal earthquake of moment magnitude (Mw) 7.8 hit the central region of Nepal on April 25, 2015; with the epicenter about 77 km northwest of Kathmandu Valley. This paper aims to explore challenges of reconstruction in the rural earthquake-stricken areas of Nepal. The Gorkha earthquake on April 25, 2015, has significantly affected the livelihood of people and overall economy in Nepal, causing severe damage and destruction in central Nepal including nation’s capital. A larger part of the earthquake affected area is difficult to access with rugged terrain and scattered settlements, which posed unique challenges and efforts on a massive scale reconstruction and rehabilitation. 800 thousand buildings were affected leaving 8 million people homeless. Challenge of reconstruction of optimum 800 thousand houses is arduous for Nepal in the background of its turmoil political scenario and weak governance. With significant actors involved in the reconstruction process, no appreciable relief has reached to the ground, which is reflected over the frustration of affected people. The 2015 Gorkha earthquake is one of most devastating disasters in the modern history of Nepal. Best of our knowledge, there is no comprehensive study on reconstruction after disasters in modern Nepal, which integrates the necessary information to deal with challenges and opportunities of reconstructions. The study was conducted using qualitative content analysis method. Thirty engineers and ten social mobilizes working for reconstruction and more than hundreds local social workers, local party leaders, and earthquake victims were selected arbitrarily. Information was collected through semi-structured interviews and open-ended questions, focus group discussions, and field notes, with no previous assumption. Author also reviewed literature and document reviews covering academic and practitioner studies on challenges of reconstruction after earthquake in developing countries such as 2001 Gujarat earthquake, 2005 Kashmir earthquake, 2003 Bam earthquake and 2010 Haiti earthquake; which have very similar building typologies, economic, political, geographical, and geological conditions with Nepal. Secondary data was collected from reports, action plans, and reflection papers of governmental entities, non-governmental organizations, private sector businesses, and the online news. This study concludes that inaccessibility, absence of local government, weak governance, weak infrastructures, lack of preparedness, knowledge gap and manpower shortage, etc. are the key challenges of the reconstruction after 2015 earthquake in Nepal. After scrutinizing different challenges and issues, study counsels that good governance, integrated information, addressing technical issues, public participation along with short term and long term strategies to tackle with technical issues are some crucial factors for timely and quality reconstruction in context of Nepal. Sample collected for this study is relatively small sample size and may not be fully representative of the stakeholders involved in reconstruction. However, the key findings of this study are ones that need to be recognized by academics, governments, and implementation agencies, and considered in the implementation of post-disaster reconstruction program in developing countries.

Keywords: Gorkha earthquake, reconstruction, challenges, policy

Procedia PDF Downloads 387

Authors: Getaneh Berie Tarekegn, Li-Chia Tai

Abstract:

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

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

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

Abstract:

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

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

Procedia PDF Downloads 58

Authors: Joy Chiu, Colin Hemez, Emma Ryan, Jia Sun, Robert Dubrow, Michael Pascucilla

Abstract:

The popularity of recreational boating is on the rise in the United States, which raises numerous national-level challenges in the management of air and water pollution, aquatic habitat destruction, and waterway access. The need to control sewage discharge from recreational vessels underlies all of these challenges. The release of raw human waste into aquatic environments can lead to eutrophication and algal blooms; can increase human exposure to pathogenic viruses, bacteria, and parasites; can financially impact commercial shellfish harvest/fisheries and marine bathing areas; and can negatively affect access to recreational and/or commercial waterways to the detriment of local economies. Because of the damage that unregulated sewage discharge can do to environments and human health/marine life, recreational vessels in the United States are required by law to 'pump-out' sewage from their holding tanks into sewage treatment systems in all designated 'no discharge areas'. Many pump-out boats, which transfer waste out of recreational vessels, are operated and maintained using funds allocated through the Federal Clean Vessel Act (CVA). The East Shore District Health Department of Branford, Connecticut is protecting this estuary by pioneering the design and construction of the first-in-the-nation zero-emissions, the solar-electric pump-out boat of its size to replace one of its older traditional gasoline-powered models through a Connecticut Department of Energy and Environmental Protection CVA Grant. This study, conducted in collaboration with the East Shore District Health Department, the Connecticut Department of Energy and Environmental Protection, States Organization for Boating Access and Connecticut’s CVA program coordinators, had two aims: (1) To perform a national assessment of pump-out boat programs, supplemented by a limited international assessment, to establish best pump-out boat practices (regardless of how the boat is powered); and (2) to estimate the cost, greenhouse gas emissions, and environmental and public health impacts of solar-electric versus traditional gasoline-powered pump-out boats. A national survey was conducted of all CVA-funded pump-out program managers and selected pump-out boat operators to gauge best practices; costs associated with gasoline-powered pump-out boat operation and management; and the regional, cultural, and policy-related issues that might arise from the adoption of solar-electric pump-out boat technology. We also conducted life-cycle analyses of gasoline-powered and solar-electric pump-out boats to compare their greenhouse gas emissions; production of air, soil and water pollution; and impacts on human health. This work comprises the most comprehensive study into pump-out boating practices in the United States to date, in which information obtained at local, state, national, and international levels is synthesized. This study aims to enable CVA programs to make informed recommendations for sustainable pump-out boating practices and identifies the challenges and opportunities that remain for the wide adoption of solar-electric pump-out boat technology.

Keywords: pump-out boat, marine water, solar-electric, zero emissions

Procedia PDF Downloads 111

Authors: Iordana Neamtu, Aurica P. Chiriac, Loredana E. Nita, Mihai Asandulesa, Elena Butnaru, Nita Tudorachi, Alina Diaconu

Abstract:

In the last decade, the attention of many researchers is focused on the synthesis of innovative “intelligent” copolymer structures with great potential for different uses. This considerable scientific interest is stimulated by possibility of the significant improvements in physical, mechanical, thermal and other important specific properties of these materials. Functionalization of polymer in synthesis by designing a suitable composition with the desired properties and applications is recognized as a valuable tool. In this work is presented a comparative study of the properties of the new copolymers poly(maleic anhydride maleic-co-3,9-divinyl-2,4,8,10-tetraoxaspiro[5.5]undecane) and poly(itaconic-anhydride-co-3,9-divinyl-2,4,8,10-tetraoxaspiro[5.5]undecane) obtained by radical polymerization in dioxane, using 2,2′-azobis(2-methylpropionitrile) as free-radical initiator. The comonomers are able for generating special effects as for example network formation, biodegradability and biocompatibility, gel formation capacity, binding properties, amphiphilicity, good oxidative and thermal stability, good film formers, and temperature and pH sensitivity. Maleic anhydride (MA) and also the isostructural analog itaconic anhydride (ITA) as polyfunctional monomers are widely used in the synthesis of reactive macromolecules with linear, hyperbranched and self & assembled structures to prepare high performance engineering, bioengineering and nano engineering materials. The incorporation of spiroacetal groups in polymer structures improves the solubility and the adhesive properties, induce good oxidative and thermal stability, are formers of good fiber or films with good flexibility and tensile strength. Also, the spiroacetal rings induce interactions on ether oxygen such as hydrogen bonds or coordinate bonds with other functional groups determining bulkiness and stiffness. The synthesized copolymers are analyzed by DSC, oscillatory and rotational rheological measurements and dielectric spectroscopy with the aim of underlying the heating behavior, solution viscosity as a function of shear rate and temperature and to investigate the relaxation processes and the motion of functional groups present in side chain around the main chain or bonds of the side chain. Acknowledgments This work was financially supported by the grant of the Romanian National Authority for Scientific Research, CNCS-UEFISCDI, project number PN-II-132/2014 “Magnetic biomimetic supports as alternative strategy for bone tissue engineering and repair’’ (MAGBIOTISS).

Keywords: Poly(maleic anhydride-co-3, 9-divinyl-2, 4, 8, 10-tetraoxaspiro (5.5)undecane); Poly(itaconic anhydride-co-3, 9-divinyl-2, 4, 8, 10-tetraoxaspiro (5.5)undecane); DSC; oscillatory and rotational rheological analysis; dielectric spectroscopy

Procedia PDF Downloads 215

Authors: Getaneh Berie Tarekegn, Li-Chia Tai

Abstract:

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

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

Procedia PDF Downloads 23

Authors: Chris Fersterer, Col Fay, Tobias Danielmeier, Kat Achterberg, Scott Willis

Abstract:

New Zealand, an island nation, has an extensive coastline peppered with small communities of iconic buildings known as Bachs. Post WWII, these modest buildings were constructed by their owners as retreats and generally were small, low cost, often using recycled material and often they fell below current acceptable building standards. In the latter part of the 20^th century, real estate prices in many of these communities remained low and these areas became permanent residences for people attracted to this affordable lifestyle choice. The Blueskin Resilient Communities Trust (BRCT) is an organisation that recognises the vulnerability of communities in low lying settlements as now being prone to increased flood threat brought about by climate change and sea level rise. Some of the inhabitants of Blueskin Bay, Otago, NZ have already found their properties to be un-insurable because of increased frequency of flood events and property values have slumped accordingly. Territorial authorities also acknowledge this increased risk and have created additional compliance measures for new buildings that are less than 2 m above tidal peaks. Community resilience becomes an additional concern where inhabitants are attracted to a lifestyle associated with a specific location and its people when this lifestyle is unable to be met in a suburban or city context. Traditional models of social housing fail to provide the sense of community connectedness and identity enjoyed by the current residents of Blueskin Bay. BRCT have partnered with the Otago Polytechnic Design School to design a new form of community housing that can react to this environmental change. It is a longitudinal project incorporating participatory approaches as a means of getting people ‘on board’, to understand complex systems and co-develop solutions. In the first period, they are seeking industry support and funding to develop a transportable and fully self-contained housing model that exploits current technologies. BRCT also hope that the building will become an educational tool to highlight climate change issues facing us today. This paper uses the Climate Safe House (CSH) as a case study for education in architectural sustainability through experiential learning offered as part of the Otago Polytechnics Bachelor of Design. Students engage with the project with research methodologies, including site surveys, resident interviews, data sourced from government agencies and physical modelling. The process involves collaboration across design disciplines including product and interior design but also includes connections with industry, both within the education institution and stakeholder industries introduced through BRCT. This project offers a rich learning environment where students become engaged through project based learning within a community of practice, including architecture, construction, energy and other related fields. The design outcomes are expressed in a series of public exhibitions and forums where community input is sought in a truly participatory process.

Keywords: community resilience, problem based learning, project based learning, case study

Procedia PDF Downloads 268

Authors: Seung Ah Lee, Sunghyun Cho, Kyong Mee Chung

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Rapid population aging became a worldwide demographic phenomenon due to rising life expectancy and declining fertility rates. Considering the current increasing rate of population aging, it is assumed that Korean society enters into a ‘super-aged’ society in 10 years, in which people aged 65 years or older account for more than 20% of entire population. In line with this trend, ICT services aimed to help elderly people to improve the quality of life have been suggested. However, existing ICT services mainly focus on supporting health or nursing care and are somewhat limited to meet a variety of specialized needs and challenges of this population. It is pointed out that the majority of services have been driven by technology-push policies. Given that the usage of ICT services greatly vary on individuals’ socio-economic status (SES), physical and psychosocial needs, this study systematically categorized elderly population into sub-groups and identified their needs and characteristics related to ICT usage in detail. First, three assessment criteria (demographic variables including SES, cognitive functioning level, and emotional functioning level) were identified based on previous literature, experts’ opinions, and focus group interview. Second, survey questions for needs assessment were developed based on the criteria and administered to 600 respondents from a national probability sample. The questionnaire consisted of 67 items concerning demographic information, experience on ICT services and information technology (IT) devices, quality of life and cognitive functioning, etc. As the result of survey, age (60s, 70s, 80s), education level (college graduates or more, middle and high school, less than primary school) and cognitive functioning level (above the cut-off, below the cut-off) were considered the most relevant factors for categorization and 18 sub-groups were identified. Finally, 18 sub-groups were clustered into 3 groups according to following similarities; computer usage rate, difficulties in using ICT, and familiarity with current or previous job. Group 1 (‘active users’) included those who with high cognitive function and educational level in their 60s and 70s. They showed favorable and familiar attitudes toward ICT services and used the services for ‘joyful life’, ‘intelligent living’ and ‘relationship management’. Group 2 (‘potential users’), ranged from age of 60s to 80s with high level of cognitive function and mostly middle to high school graduates, reported some difficulties in using ICT and their expectations were lower than in group 1 despite they were similar to group 1 in areas of needs. Group 3 (‘limited users’) consisted of people with the lowest education level or cognitive function, and 90% of group reported difficulties in using ICT. However, group 3 did not differ from group 2 regarding the level of expectation for ICT services and their main purpose of using ICT was ‘safe living’. This study developed a systematic needs assessment tool and identified three sub-groups of elderly ICT users based on multi-criteria. It is implied that current cognitive function plays an important role in using ICT and determining needs among the elderly population. Implications and limitations were further discussed.

Keywords: elderly population, ICT, needs assessment, population aging

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Authors: Junqi Zou

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As one of the world’s most tech-ready countries, Singapore has initiated the Smart Nation plan to harness the full power and potential of digital technologies to transform the way people live and work, through the more efficient government and business processes, to make the economy more productive. The key evolutions of digital technology transformation in healthcare and the increasing deployment of Internet of Things (IoTs), Big Data, AI/cognitive, Robotic Process Automation (RPA), Electronic Health Record Systems (EHR), Electronic Medical Record Systems (EMR), Warehouse Management System (WMS in the most recent decade have significantly stepped up the move towards an information-driven healthcare ecosystem. The advances in information technology not only bring benefits to patients but also act as a key force in changing management accounting in healthcare sector. The aim of this study is to investigate the impacts of digital technology transformation on Singapore’s healthcare sector from a management accounting perspective. Adopting a Balanced Scorecard (BSC) analysis approach, this paper conducted an exploratory case study of a newly launched Singapore public hospital, which has been recognized as amongst the most digitally advanced healthcare facilities in Asia-Pacific region. Specifically, this study gains insights on how the new technology is changing healthcare organizations’ management accounting from four perspectives under the Balanced Scorecard approach, 1) Financial Perspective, 2) Customer (Patient) Perspective, 3) Internal Processes Perspective, and 4) Learning and Growth Perspective. Based on a thorough review of archival records from the government and public, and the interview reports with the hospital’s CIO, this study finds the improvements from all the four perspectives under the Balanced Scorecard framework as follows: 1) Learning and Growth Perspective: The Government (Ministry of Health) works with the hospital to open up multiple training pathways to health professionals that upgrade and develops new IT skills among the healthcare workforce to support the transformation of healthcare services. 2) Internal Process Perspective: The hospital achieved digital transformation through Project OneCare to integrate clinical, operational, and administrative information systems (e.g., EHR, EMR, WMS, EPIB, RTLS) that enable the seamless flow of data and the implementation of JIT system to help the hospital operate more effectively and efficiently. 3) Customer Perspective: The fully integrated EMR suite enhances the patient’s experiences by achieving the 5 Rights (Right Patient, Right Data, Right Device, Right Entry and Right Time). 4) Financial Perspective: Cost savings are achieved from improved inventory management and effective supply chain management. The use of process automation also results in a reduction of manpower costs and logistics cost. To summarize, these improvements identified under the Balanced Scorecard framework confirm the success of utilizing the integration of advanced ICT to enhance healthcare organization’s customer service, productivity efficiency, and cost savings. Moreover, the Big Data generated from this integrated EMR system can be particularly useful in aiding management control system to optimize decision making and strategic planning. To conclude, the new digital technology transformation has moved the usefulness of management accounting to both financial and non-financial dimensions with new heights in the area of healthcare management.

Keywords: balanced scorecard, digital technology transformation, healthcare ecosystem, integrated information system

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Authors: Satya Narayan

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India, a rapidly growing economy with a burgeoning population, grapples with the dual challenge of meeting rising energy demands and reducing its carbon footprint. Geothermal energy, an often overlooked and underutilized renewable source, holds immense potential for addressing this challenge. Geothermal resources offer a valuable, consistent, and sustainable energy source, and may significantly contribute to India's energy. This paper discusses the importance of geothermal exploration in India, emphasizing its role in achieving sustainable energy production while mitigating environmental impacts. It also delves into the methodology employed to assess geothermal resource feasibility, including geophysical surveys and borehole drilling. The results and discussion sections highlight promising geothermal sites across India, illuminating the nation's vast geothermal potential. It detects potential geothermal reservoirs, characterizes subsurface structures, maps temperature gradients, monitors fluid flow, and estimates key reservoir parameters. Globally, geothermal energy falls into high and low enthalpy categories, with India mainly having low enthalpy resources, especially in hot springs. The northwestern Himalayan region boasts high-temperature geothermal resources due to geological factors. Promising sites, like Puga Valley, Chhumthang, and others, feature hot springs suitable for various applications. The Son-Narmada-Tapti lineament intersects regions rich in geological history, contributing to geothermal resources. Southern India, including the Godavari Valley, has thermal springs suitable for power generation. The Andaman-Nicobar region, linked to subduction and volcanic activity, holds high-temperature geothermal potential. Geophysical surveys, utilizing gravity, magnetic, seismic, magnetotelluric, and electrical resistivity techniques, offer vital information on subsurface conditions essential for detecting, evaluating, and exploiting geothermal resources. The gravity and magnetic methods map the depth of the mantle boundary (high-temperature) and later accurately determine the Curie depth. Electrical methods indicate the presence of subsurface fluids. Seismic surveys create detailed sub-surface images, revealing faults and fractures and establishing possible connections to aquifers. Borehole drilling is crucial for assessing geothermal parameters at different depths. Detailed geochemical analysis and geophysical surveys in Dholera, Gujarat, reveal untapped geothermal potential in India, aligning with renewable energy goals. In conclusion, geophysical surveys and borehole drilling play a pivotal role in economically viable geothermal site selection and feasibility assessments. With ongoing exploration and innovative technology, these surveys effectively minimize drilling risks, optimize borehole placement, aid in environmental impact evaluations, and facilitate remote resource exploration. Their cost-effectiveness informs decisions regarding geothermal resource location and extent, ultimately promoting sustainable energy and reducing India's reliance on conventional fossil fuels.

Keywords: geothermal resources, geophysical methods, exploration, exploitation

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Authors: Yixin Zhu, Lishengsa Yue, Jian Sun, Lanyue Tang

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Modeling driving distraction in microscopic traffic simulation is crucial for enhancing simulation accuracy. Current driving distraction models are mainly derived from physical motion constraints under distracted states, in which distraction-related error terms are added to existing microscopic driver models. However, the model accuracy is not very satisfying, due to a lack of modeling the cognitive mechanism underlying the distraction. This study models driving distraction based on the Queueing Network Human Processor model (QN-MHP). This study utilizes the queuing structure of the model to perform task invocation and switching for distracted operation and control of the vehicle under driver distraction. Based on the assumption of the QN-MHP model about the cognitive sub-network, server F is a structural bottleneck. The latter information must wait for the previous information to leave server F before it can be processed in server F. Therefore, the waiting time for task switching needs to be calculated. Since the QN-MHP model has different information processing paths for auditory information and visual information, this study divides driving distraction into two types: auditory distraction and visual distraction. For visual distraction, both the visual distraction task and the driving task need to go through the visual perception sub-network, and the stimuli of the two are asynchronous, which is called stimulus on asynchrony (SOA), so when calculating the waiting time for switching tasks, it is necessary to consider it. In the case of auditory distraction, the auditory distraction task and the driving task do not need to compete for the server resources of the perceptual sub-network, and their stimuli can be synchronized without considering the time difference in receiving the stimuli. According to the Theory of Planned Behavior for drivers (TPB), this study uses risk entropy as the decision criterion for driver task switching. A logistic regression model is used with risk entropy as the independent variable to determine whether the driver performs a distraction task, to explain the relationship between perceived risk and distraction. Furthermore, to model a driver’s perception characteristics, a neurophysiological model of visual distraction tasks is incorporated into the QN-MHP, and executes the classical Intelligent Driver Model. The proposed driving distraction model integrates the psychological cognitive process of a driver with the physical motion characteristics, resulting in both high accuracy and interpretability. This paper uses 773 segments of distracted car-following in Shanghai Naturalistic Driving Study data (SH-NDS) to classify the patterns of distracted behavior on different road facilities and obtains three types of distraction patterns: numbness, delay, and aggressiveness. The model was calibrated and verified by simulation. The results indicate that the model can effectively simulate the distracted car-following behavior of different patterns on various roadway facilities, and its performance is better than the traditional IDM model with distraction-related error terms. The proposed model overcomes the limitations of physical-constraints-based models in replicating dangerous driving behaviors, and internal characteristics of an individual. Moreover, the model is demonstrated to effectively generate more dangerous distracted driving scenarios, which can be used to construct high-value automated driving test scenarios.

Keywords: computational cognitive model, driving distraction, microscopic traffic simulation, psychological-physical constraints

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Authors: Ajay Ivan

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This paper focuses on the cultural politics of health-promotional and disease-preventive pedagogic practices in the context of the national tobacco control programme in India. Tobacco consumption is typically problematised as a paradox: tobacco poses objective health risks such as cancer and heart disease, but its production, sale and export contribute significantly to state revenue. A blanket ban on tobacco products, therefore, is infeasible though desirable. Instead, initiatives against tobacco use have prioritised awareness creation and behaviour change to reduce its demand. This paper argues that public health communication is not, as commonly assumed, an apolitical and neutral transmission of disease-preventive information. Drawing on Michel Foucault’s concept of governmentality, it examines such campaigns as techniques of disciplining people rather than coercing them to give up tobacco use, which would be both impractical and counter-productive. At the level of the population, these programmes constitute a security mechanism that reduces risks without eliminating them, so as to ensure an optimal level of public health without hampering the economy. Anti-tobacco pedagogy thus aligns with a contemporary paradigm of health that emphasises risk-assessment and lifestyle management as tools of governance, using pedagogic techniques to teach people how to be healthy. The paper analyses the pictorial health warnings on tobacco packets and anti-tobacco advertisements in movie theatres mandated by the state, along with awareness-creation messages circulated by anti-tobacco advocacy groups in India, to show how they discursively construct tobacco and its consumption as a health risk. Smoking is resignified from a pleasurable and sociable practice to a deadly addiction that jeopardises the health of those who smoke and those who passively inhale the smoke. While disseminating information about the health risks of tobacco, these initiatives employ emotional and affective techniques of persuasion to discipline tobacco users. They incite fear of death and of social ostracism to motivate behaviour change, complementing their appeals to reason. Tobacco is portrayed as a grave moral danger to the family and a detriment to the vitality of the nation, such that using it contradicts one’s duties as a parent or citizen. Awareness programmes reproduce prevailing societal assumptions about health and disease, normalcy and deviance, and proper and improper conduct. Pedagogy thus functions as an apparatus of public health governance, recruiting subjects as volunteers in their own regulation and aligning their personal goals and aspirations to the objectives of tobacco control. The paper links this calculated management of subjectivity and the self-responsibilisation of the pedagogic subject to a distinct mode of neoliberal civic governance in contemporary India. Health features prominently in this mode of governance that serves the biopolitical obligation of the state as laid down in Article 39 of the Constitution, which includes a duty to ensure the health of its citizens. Insofar as the health of individuals is concerned, the problem is how to balance this duty of the state with the fundamental right of the citizen to choose how to live. Public health pedagogy, by directing the citizen’s ‘free’ choice without unduly infringing upon it, offers a tactical solution.

Keywords: public health communication, pedagogic power, tobacco control, neoliberal governance

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Authors: Roshni Raha, Kavya P., Gayathri M.

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India, with a humongous population, remains the world's poorest developing nation in terms of nutritional status, with iron deficiency anaemia (IDA) affecting the population. Despite efforts over the past decades, India's anaemia prevalence has not been reduced. Researchers are interested in developing therapies that will minimize the typical side effects of oral iron and optimize iron salts-based treatment through delivery methods based on the physiology of hepcidin regulation. However, they need to come up with iron therapies that will prevent making the infection worse. This article explores using bio-nanotechnology as the alternative, promising substitution of providing iron supplements for the treatment of diarrhoea and gut inflammation in kids and pregnant women. This article is an exploratory study using a literature survey and secondary research from review papers. In the realm of biotechnology, nanoparticles have become extremely famous due to unexpected variations in surface characteristics caused by particle size. Particle size distribution and shape exhibit unusual, enhanced characteristics when reduced to nanoscale. The article attempts to develop a model for a nanotechnology based solution in iron fortification to combat the problems of diarrhoea and gut inflammation. Certain dimensions that have been considered in the model include the size, shape, source, and biosynthesis of the iron nanoparticles. Another area of investigation addressed in the article is the cost-effective biocompatible production of these iron nanoparticles. Studies have demonstrated that a substantial reduction of metal ions to form nanoparticles from the bulk metal occurs in plants because of the presence of a wide diversity of biomolecules. Using this concept, the paper investigates the effectiveness and impact of how similar sources can be used for the biological synthesis of iron nanoparticles. Results showed that iron particles, when prepared in nano-metre size, offer potential advantages. When the particle size of the iron compound decreases and attains nano configuration, its surface area increases, which further improves its solubility in the gastric acid, leading to higher absorption, higher bioavailability, and producing the least organoleptic changes in food. It has no negative effects and possesses a safe, effective profile to reduce IDA. Considering all the parameters, it has been concluded that iron particles in nano configuration serve as alternative iron supplements for the complete treatment of IDA. Nanoparticles of ferric phosphate, ferric pyrophosphate, and iron oxide are the choices of iron supplements. From a sourcing perspective, the paper concludes green sources are the primary sources for the biological synthesis of iron nanoparticles. It will also be a cost-effective strategy since our goal is to treat the target population in rural India. Bio-nanotechnology serves as an alternative and promising substitution for iron supplements due to its low cost, excellent bioavailability, and strong organoleptic properties. One area of future research can be to explore the type of size and shape of iron nanoparticles that would be suitable for the different age groups of pregnant women and children and whether it would be influenced based on the topography in certain areas.

Keywords: anemia, bio-nanotechnology, iron-fortification, nanoparticle

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Authors: Muhammad Ahnaf Zahin, Yaw Adu-Gyamfi

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Bus transit is a crucial component of transportation networks, especially in urban areas. Any intelligent transportation system must have accurate real-time information on bus travel times since it minimizes waiting times for passengers at different stations along a route, improves service reliability, and significantly optimizes travel patterns. Bus agencies must enhance the quality of their information service to serve their passengers better and draw in more travelers since people waiting at bus stops are frequently anxious about when the bus will arrive at their starting point and when it will reach their destination. For solving this issue, different models have been developed for predicting bus travel times recently, but most of them are focused on smaller road networks due to their relatively subpar performance in high-density urban areas on a vast network. This paper develops a deep learning-based architecture using a single-step multi-station forecasting approach to predict average bus travel times for numerous routes, stops, and trips on a large-scale network using heterogeneous bus transit data collected from the GTFS database. Over one week, data was gathered from multiple bus routes in Saint Louis, Missouri. In this study, Gated Recurrent Unit (GRU) neural network was followed to predict the mean vehicle travel times for different hours of the day for multiple stations along multiple routes. Historical time steps and prediction horizon were set up to 5 and 1, respectively, which means that five hours of historical average travel time data were used to predict average travel time for the following hour. The spatial and temporal information and the historical average travel times were captured from the dataset for model input parameters. As adjacency matrices for the spatial input parameters, the station distances and sequence numbers were used, and the time of day (hour) was considered for the temporal inputs. Other inputs, including volatility information such as standard deviation and variance of journey durations, were also included in the model to make it more robust. The model's performance was evaluated based on a metric called mean absolute percentage error (MAPE). The observed prediction errors for various routes, trips, and stations remained consistent throughout the day. The results showed that the developed model could predict travel times more accurately during peak traffic hours, having a MAPE of around 14%, and performed less accurately during the latter part of the day. In the context of a complicated transportation network in high-density urban areas, the model showed its applicability for real-time travel time prediction of public transportation and ensured the high quality of the predictions generated by the model.

Keywords: gated recurrent unit, mean absolute percentage error, single-step forecasting, travel time prediction.

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Authors: Jia Li, Xing Wei, Yuchen Hong, Yang Lu

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Detecting vehicle behavior has always been the focus of intelligent transportation, but with the explosive growth of the number of vehicles and the complexity of the road environment, the vehicle behavior videos captured by traditional surveillance have been unable to satisfy the study of vehicle behavior. The traditional method of manually labeling vehicle behavior is too time-consuming and labor-intensive, but the existing object detection and tracking algorithms have poor practicability and low behavioral location detection rate. This paper proposes a vehicle behavior detection algorithm based on the dual-stream convolution network and the multi-dimensional video dynamic detection network. In the videos, the straight-line behavior of the vehicle will default to the background behavior. The Changing lanes, turning and turning around are set as target behaviors. The purpose of this model is to automatically mark the target behavior of the vehicle from the untrimmed videos. First, the target behavior proposals in the long video are extracted through the dual-stream convolution network. The model uses a dual-stream convolutional network to generate a one-dimensional action score waveform, and then extract segments with scores above a given threshold M into preliminary vehicle behavior proposals. Second, the preliminary proposals are pruned and identified using the multi-dimensional video dynamic detection network. Referring to the hierarchical reinforcement learning, the multi-dimensional network includes a Timer module and a Spacer module, where the Timer module mines time information in the video stream and the Spacer module extracts spatial information in the video frame. The Timer and Spacer module are implemented by Long Short-Term Memory (LSTM) and start from an all-zero hidden state. The Timer module uses the Transformer mechanism to extract timing information from the video stream and extract features by linear mapping and other methods. Finally, the model fuses time information and spatial information and obtains the location and category of the behavior through the softmax layer. This paper uses recall and precision to measure the performance of the model. Extensive experiments show that based on the dataset of this paper, the proposed model has obvious advantages compared with the existing state-of-the-art behavior detection algorithms. When the Time Intersection over Union (TIoU) threshold is 0.5, the Average-Precision (MP) reaches 36.3% (the MP of baselines is 21.5%). In summary, this paper proposes a vehicle behavior detection model based on multi-dimensional dynamic detection network. This paper introduces spatial information and temporal information to extract vehicle behaviors in long videos. Experiments show that the proposed algorithm is advanced and accurate in-vehicle timing behavior detection. In the future, the focus will be on simultaneously detecting the timing behavior of multiple vehicles in complex traffic scenes (such as a busy street) while ensuring accuracy.

Keywords: vehicle behavior detection, convolutional neural network, long short-term memory, deep learning

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Authors: Àidan Higgins

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Higher education will be crucial in the coming decades in helping to make Ireland a nation is known for innovation, competitive enterprise, and ongoing academic success, as well as a desirable location to live and work with a high quality of life, vibrant culture, and inclusive social structures. Higher education institutions will actively connect with each student community, society, and business; they will help students develop a sense of place and identity in Ireland and provide the tools they need to contribute significantly to the global community. It will also serve as a catalyst for novel ideas through research, many of which will become the foundation for long-lasting inventive businesses in the future as part of the 2030 National Strategy on Education focuses on change and developing our education system with a focus on how we carry out Research. The emphasis is central to knowledge transfer and a consistent research framework with exploiting opportunities and having the necessary expertise. The newly formed Technological Universities (TU) in Ireland are based on a government initiative to create a new type of higher education institution that focuses on applied and industry-focused research and education. The basis of the TU is to bring together two or more existing institutes of technology to create a larger and more comprehensive institution that offers a wider range of programs and services to students and industry partners. The TU model aims to promote collaboration between academia, industry, and community organizations to foster innovation, research, and economic development. The TU model also aims to enhance the student experience by providing a more seamless pathway from undergraduate to postgraduate studies, as well as greater opportunities for work placements and engagement with industry partners. Additionally, the TUs are designed to provide a greater emphasis on applied research, technology transfer, and entrepreneurship, with the goal of fostering innovation and contributing to economic growth. A project is a collection of organised tasks carried out precisely to produce a singular output (product or service) within a given time frame. Project management is a set of activities that facilitates the successful implementation of a project. The significant differences between research and development projects are the (lack of) precise requirements and (the inability to) plan an outcome from the beginning of the project. The evaluation criteria for a research project must consider these and other "particularities" in works; for instance, proving something cannot be done may be a successful outcome. This study intends to explore how a newly established multi-campus technological university manages research projects effectively. The study will identify the potential and difficulties of managing research projects, the tools, resources and processes available in a multi-campus Technological University context and the methods and approaches employed to deal with these difficulties. Key stakeholders like project managers, academics, and administrators will be surveyed as part of the study, which will also involve an explorative investigation of current literature and data. The findings of this study will contribute significantly to creating best practices for project management in this setting and offer insightful information about the efficient management of research projects within a multi-campus technological university.

Keywords: project management, research and research-related projects, multi-campus technology university, processes

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Authors: Dila Ram Bhandari

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Throughout the 20th century, new governments were created where identities such as ethnic, religious, linguistic, caste, communal, tribal, and others played a part in the development of constitutions and the legal system of victim and criminal justice. Acute issues with extremism, poverty, environmental degradation, cybercrimes, human rights violations, crime against, and victimization of both individuals and groups have recently plagued South Asian nations. Everyday massive number of crimes are steadfast, these frequent crimes have made the lives of common citizens restless. Crimes are one of the major threats to society and also for civilization. Crime is a bone of contention that can create a societal disturbance. The old-style crime solving practices are unable to live up to the requirement of existing crime situations. Crime analysis is one of the most important activities of the majority of intelligent and law enforcement organizations all over the world. The South Asia region lacks such a regional coordination mechanism, unlike central Asia of Asia Pacific regions, to facilitate criminal intelligence sharing and operational coordination related to organized crime, including illicit drug trafficking and money laundering. There have been numerous conversations in recent years about using data mining technology to combat crime and terrorism. The Data Detective program from Sentient as a software company, uses data mining techniques to support the police (Sentient, 2017). The goals of this internship are to test out several predictive model solutions and choose the most effective and promising one. First, extensive literature reviews on data mining, crime analysis, and crime data mining were conducted. Sentient offered a 7-year archive of crime statistics that were daily aggregated to produce a univariate dataset. Moreover, a daily incidence type aggregation was performed to produce a multivariate dataset. Each solution's forecast period lasted seven days. Statistical models and neural network models were the two main groups into which the experiments were split. For the crime data, neural networks fared better than statistical models. This study gives a general review of the applied statistics and neural network models. A detailed image of each model's performance on the available data and generalizability is provided by a comparative analysis of all the models on a comparable dataset. Obviously, the studies demonstrated that, in comparison to other models, Gated Recurrent Units (GRU) produced greater prediction. The crime records of 2005-2019 which was collected from Nepal Police headquarter and analysed by R programming. In conclusion, gated recurrent unit implementation could give benefit to police in predicting crime. Hence, time series analysis using GRU could be a prospective additional feature in Data Detective.

Keywords: time series analysis, forecasting, ARIMA, machine learning

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Authors: Nahid Nariman

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The prosperity of any nation depends on its ability to use human potential, in particular, to offer an education that builds learners' competencies to become effective workforce participants and true citizens of the world. Ever since the Second World War, the United States has been a dominant player in the world politically, economically, socially, and culturally. The rapid rise of technological advancement and consumer technologies have made it clear that science, technology, engineering, and math (STEM) play a crucial role in today’s world economy. Exploring the top qualities demanded from new hires in the industry—i.e., problem-solving skills, teamwork, dependability, adaptability, technical and communication skills— sheds light on the kind of path that is needed for a successful educational system to effectively support STEM. The focus of 21st century education has been to build student competencies by preparing them to acquire and apply knowledge, to think critically and creatively, to competently use information, be able to work in teams, to demonstrate intellectual and moral values as well as cultural awareness, and to be able to communicate. Many educational reforms pinpoint various 'ideal' pathways toward STEM that educators, policy makers, and business leaders have identified for educating the workforce of tomorrow. This study will explore how problem-based learning (PBL), an instructional strategy developed in the medical field and adopted with many successful results in K-12 through higher education, is the proper approach to stimulate underrepresented high school students' interest in pursuing STEM careers. In the current study, the effect of a problem-based STEM model on students' attitudes and career interests was investigated using qualitative and quantitative methods. The participants were 71 low-income, native Hawaiian high school students who would be first-generation college students. They were attending a summer STEM camp developed as the result of a collaboration between the University of Hawaii and the Upward Bound Program. The project, funded by the National Science Foundation's Innovative Technology Experiences for Students and Teachers (ITEST) program, used PBL as an approach in challenging students to engage in solving hands-on, real-world problems in their communities. Pre-surveys were used before camp and post-surveys on the last day of the program to learn about the implementation of the PBL STEM model. A Career Interest Questionnaire provided a way to investigate students’ career interests. After the summer camp, a representative selection of students participated in focus group interviews to discuss their opinions about the PBL STEM camp. The findings revealed a significantly positive increase in students' attitudes towards STEM disciplines and STEM careers. The students' interview results also revealed that students identified PBL to be an effective form of instruction in their learning and in the development of their 21st-century skills. PBL was acknowledged for making the class more enjoyable and for raising students' interest in STEM careers, while also helping them develop teamwork and communication skills in addition to scientific knowledge. As a result, the integration of PBL and a STEM learning experience was shown to positively affect students’ interest in STEM careers.

Keywords: problem-based learning, science education, STEM, underrepresented students

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Authors: Gaurav Kumar Sinha

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In an era defined by the proliferation of data and the utilization of cloud computing environments, the efficient transfer and processing of big data workloads across multi-cloud platforms have emerged as critical challenges. This research paper embarks on a comprehensive exploration of the complexities associated with managing and optimizing big data in a multi-cloud ecosystem.The foundation of this study is rooted in the recognition that modern enterprises increasingly rely on multiple cloud providers to meet diverse business needs, enhance redundancy, and reduce vendor lock-in. As a consequence, managing data across these heterogeneous cloud environments has become intricate, necessitating innovative approaches to ensure data integrity, security, and performance.The primary objective of this research is to investigate strategies and techniques for enhancing the efficiency of data transfer and processing in multi-cloud scenarios. It recognizes that big data workloads are characterized by their sheer volume, variety, velocity, and complexity, making traditional data management solutions insufficient for harnessing the full potential of multi-cloud architectures.The study commences by elucidating the challenges posed by multi-cloud environments in the context of big data. These challenges encompass data fragmentation, latency, security concerns, and cost optimization. To address these challenges, the research explores a range of methodologies and solutions. One of the key areas of focus is data transfer optimization. The paper delves into techniques for minimizing data movement latency, optimizing bandwidth utilization, and ensuring secure data transmission between different cloud providers. It evaluates the applicability of dedicated data transfer protocols, intelligent data routing algorithms, and edge computing approaches in reducing transfer times.Furthermore, the study examines strategies for efficient data processing across multi-cloud environments. It acknowledges that big data processing requires distributed and parallel computing capabilities that span across cloud boundaries. The research investigates containerization and orchestration technologies, serverless computing models, and interoperability standards that facilitate seamless data processing workflows.Security and data governance are paramount concerns in multi-cloud environments. The paper explores methods for ensuring data security, access control, and compliance with regulatory frameworks. It considers encryption techniques, identity and access management, and auditing mechanisms as essential components of a robust multi-cloud data security strategy.The research also evaluates cost optimization strategies, recognizing that the dynamic nature of multi-cloud pricing models can impact the overall cost of data transfer and processing. It examines approaches for workload placement, resource allocation, and predictive cost modeling to minimize operational expenses while maximizing performance.Moreover, this study provides insights into real-world case studies and best practices adopted by organizations that have successfully navigated the challenges of multi-cloud big data management. It presents a comparative analysis of various multi-cloud management platforms and tools available in the market.

Keywords: multi-cloud environments, big data workloads, data transfer optimization, data processing strategies

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Authors: Justin Byrne, Jose Ramon Cobo

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The growing importance of cross- or intercultural competencies (used here interchangeably) for the business and management professionals is now a commonplace in both academic and professional literature. This reflects two parallel developments. On the one hand, it is a consequence of the increased attention paid to a whole range of 'soft skills', now seen as fundamental in both individuals' and corporate success. On the other hand, and more specifically, the increasing demand for interculturally competent professionals is a corollary of ongoing processes of globalization, which multiply and intensify encounters between individuals and companies from different cultural backgrounds. Business schools have, for some decades, responded to the needs of the job market and their own students by providing students with training in intercultural skills, as they are encouraged to do so by the major accreditation agencies on both sides of the Atlantic. Adapting Early and Ang's (2003) formulation of Cultural Intelligence (CQ), this paper aims to help fill the lagunae in the current literature on intercultural training in three main ways. First, it offers an in-depth analysis of the CQ of a little studied group: contemporary Millenial and 'Generation Z' Business School students. The level of analysis distinguishes between the four different dimensions of CQ, cognition, metacognition, motivation and behaviour, and thereby provides a detailed picture of the strengths and weaknesses in CQ of the group as a whole, as well as of different sub-groups and profiles of students. Secondly, by crossing these individual-level findings with respondents' socio-cultural and educational data, this paper also proposes and tests hypotheses regarding the relative impact and importance of four possible antecedents of intercultural skills identified in the literature: prior international experience; intercultural training, foreign language proficiency, and experience of cultural diversity in habitual country of residence. Third, we use this analysis to suggest data-based intercultural training priorities for today's management students. These conclusions are based on the statistical analysis of individual responses of some 300 Bachelor or Masters students in a major European Business School provided to two on-line surveys: Ang, Van Dyne, et al's (2007) standard 20-question self-reporting CQ Scale, and an original questionnaire designed by the authors to collate information on respondent's socio-demographic and educational profile relevant to our four hypotheses and explanatory variables. The data from both instruments was crossed in both descriptive statistical analysis and regression analysis. This research shows that there is no statistically significant and positive relationship between the four antecedents analyzed and overall CQ level. The exception in this respect is the statistically significant correlation between international experience, and the cognitive dimension of CQ. In contrast, the results show that the combination of international experience and foreign language skills acting together, does have a strong overall impact on CQ levels. These results suggest that selecting and/or training students with strong foreign language skills and providing them with international experience (through multinational programmes, academic exchanges or international internships) constitutes one effective way of training culturally intelligent managers of tomorrow.

Keywords: business school, cultural intelligence, millennial, training

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Authors: Roberta Mugellesi Dow

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As the climate crisis becomes unignorable, it is imperative that new services are developed addressing not only the needs of customers but also taking into account its impact on the environment. The Telecommunication and Integrated Application (TIA) Directorate of ESA is supporting the green transition with particular attention to the sustainable mobility.“Accelerating the shift to sustainable and smart mobility” is at the core of the European Green Deal strategy, which seeks a 90% reduction in related emissions by 2050 . Transforming the way that people and goods move is essential to increasing mobility while decreasing environmental impact, and transport must be considered holistically to produce a shared vision of green intermodal mobility. The use of space technologies, integrated with terrestrial technologies, is an enabler of smarter traffic management and increased transport efficiency for automated and connected multimodal mobility. Satellite connectivity, including future 5G networks, and digital technologies such as Digital Twin, AI, Machine Learning, and cloud-based applications are key enablers of sustainable mobility.SatCom is essential to ensure that connectivity is ubiquitously available, even in remote and rural areas, or in case of a failure, by the convergence of terrestrial and SatCom connectivity networks, This is especially crucial when there are risks of network failures or cyber-attacks targeting terrestrial communication. SatCom ensures communication network robustness and resilience. The combination of terrestrial and satellite communication networks is making possible intelligent and ubiquitous V2X systems and PNT services with significantly enhanced reliability and security, hyper-fast wireless access, as well as much seamless communication coverage. SatNav is essential in providing accurate tracking and tracing capabilities for automated vehicles and in guiding them to target locations. SatNav can also enable location-based services like car sharing applications, parking assistance, and fare payment. In addition to GNSS receivers, wireless connections, radar, lidar, and other installed sensors can enable automated vehicles to monitor surroundings, to ‘talk to each other’ and with infrastructure in real-time, and to respond to changes instantaneously. SatEO can be used to provide the maps required by the traffic management, as well as evaluate the conditions on the ground, assess changes and provide key data for monitoring and forecasting air pollution and other important parameters. Earth Observation derived data are used to provide meteorological information such as wind speed and direction, humidity, and others that must be considered into models contributing to traffic management services. The paper will provide examples of services and applications that have been developed aiming to identify innovative solutions and new business models that are allowed by new digital technologies engaging space and non space ecosystem together to deliver value and providing innovative, greener solutions in the mobility sector. Examples include Connected Autonomous Vehicles, electric vehicles, green logistics, and others. For the technologies relevant are the hybrid satcom and 5G providing ubiquitous coverage, IoT integration with non space technologies, as well as navigation, PNT technology, and other space data.

Keywords: sustainability, connectivity, mobility, satellites

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Authors: Caroline Atef Shoukry Tadros

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Massive Urbanization growth threatens the sustainability of cities and the quality of city life. This raised the need for an alternate model of sustainability, so we need to plan the future cities in a smarter way with smarter mobility. Smart Mobility planning applications are solutions that use digital technologies and infrastructure advances to improve the efficiency, sustainability, and inclusiveness of urban transportation systems. They can contribute to meeting the needs of Urbanization growth by addressing the challenges of traffic congestion, pollution, accessibility, and safety in cities. Some example of a Smart Mobility planning application are Mobility-as-a-service: This is a service that integrates different transport modes, such as public transport, shared mobility, and active mobility, into a single platform that allows users to plan, book, and pay for their trips. This can reduce the reliance on private cars, optimize the use of existing infrastructure, and provide more choices and convenience for travelers. MaaS Global is a company that offers mobility-as-a-service solutions in several cities around the world. Traffic flow optimization: This is a solution that uses data analytics, artificial intelligence, and sensors to monitor and manage traffic conditions in real-time. This can reduce congestion, emissions, and travel time, as well as improve road safety and user satisfaction. Waycare is a platform that leverages data from various sources, such as connected vehicles, mobile applications, and road cameras, to provide traffic management agencies with insights and recommendations to optimize traffic flow. Logistics optimization: This is a solution that uses smart algorithms, blockchain, and IoT to improve the efficiency and transparency of the delivery of goods and services in urban areas. This can reduce the costs, emissions, and delays associated with logistics, as well as enhance the customer experience and trust. ShipChain is a blockchain-based platform that connects shippers, carriers, and customers and provides end-to-end visibility and traceability of the shipments. Autonomous vehicles: This is a solution that uses advanced sensors, software, and communication systems to enable vehicles to operate without human intervention. This can improve the safety, accessibility, and productivity of transportation, as well as reduce the need for parking space and infrastructure maintenance. Waymo is a company that develops and operates autonomous vehicles for various purposes, such as ride-hailing, delivery, and trucking. These are some of the ways that Smart Mobility planning applications can contribute to meeting the needs of the Urbanization growth. However, there are also various opportunities and challenges related to the implementation and adoption of these solutions, such as the regulatory, ethical, social, and technical aspects. Therefore, it is important to consider the specific context and needs of each city and its stakeholders when designing and deploying Smart Mobility planning applications.

Keywords: smart mobility planning, smart mobility applications, smart mobility techniques, smart mobility tools, smart transportation, smart cities, urbanization growth, future smart cities, intelligent cities, ICT information and communications technologies, IoT internet of things, sensors, lidar, digital twin, ai artificial intelligence, AR augmented reality, VR virtual reality, robotics, cps cyber physical systems, citizens design science

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Authors: Alfredo Fortunato, Carmelofrancesco Origlia, Sara Laurita, Rossella Nicoletti

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In the post-pandemic recovery phase of tourism, the role of a Destination Management Organization (DMO) as a coordinated management system of all the elements that make up a destination (attractions, access, marketing, human resources, brand, pricing, etc.) is also becoming relevant for local territories. The objective of a DMO is to maximize the visitor's perception of value and quality while ensuring the competitiveness and sustainability of the destination, as well as the long-term preservation of its natural and cultural assets, and to catalyze benefits for the local economy and residents. In carrying out the multiple functions to which it is called, the DMO can leverage a collective intelligence that comes from the ability to pool information, explicit and tacit knowledge, and relationships of the various stakeholders: policymakers, public managers and officials, entrepreneurs in the tourism supply chain, researchers, data journalists, schools, associations and committees, citizens, etc. The DMO potentially has at its disposal large volumes of data and many of them at low cost, that need to be properly processed to produce value. Based on these assumptions, the paper presents a conceptual framework for building an information system to support the DMO in the intelligent management of a tourist destination tested in an area of southern Italy. The approach adopted is data-informed and consists of four phases: (1) formulation of the knowledge problem (analysis of policy documents and industry reports; focus groups and co-design with stakeholders; definition of information needs and key questions); (2) research and metadatation of relevant sources (reconnaissance of official sources, administrative archives and internal DMO sources); (3) gap analysis and identification of unconventional information sources (evaluation of traditional sources with respect to the level of consistency with information needs, the freshness of information and granularity of data; enrichment of the information base by identifying and studying web sources such as Wikipedia, Google Trends, Booking.com, Tripadvisor, websites of accommodation facilities and online newspapers); (4) definition of the set of indicators and construction of the information base (specific definition of indicators and procedures for data acquisition, transformation, and analysis). The framework derived consists of 6 thematic areas (accommodation supply, cultural heritage, flows, value, sustainability, and enabling factors), each of which is divided into three domains that gather a specific information need to be represented by a scheme of questions to be answered through the analysis of available indicators. The framework is characterized by a high degree of flexibility in the European context, given that it can be customized for each destination by adapting the part related to internal sources. Application to the case study led to the creation of a decision support system that allows: •integration of data from heterogeneous sources, including through the execution of automated web crawling procedures for data ingestion of social and web information; •reading and interpretation of data and metadata through guided navigation paths in the key of digital story-telling; •implementation of complex analysis capabilities through the use of data mining algorithms such as for the prediction of tourist flows.

Keywords: collective intelligence, data framework, destination management, smart tourism

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Authors: Richard McGregor, Carmen Reaiche, Stephen Boyle

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Cyber threats are a relatively recent phenomenon and offer cyber insurers a dynamic and intelligent peril. As individuals en mass become increasingly digitally dependent, Personal Cyber Insurance (PCI) offers an attractive option to mitigate cyber risk at a personal level. This abstract proposes a literature review that conceptualises a framework for siting Personal Cyber Insurance (PCI) within the context of cyberspace. The lack of empirical research within this domain demonstrates an immediate need to define the scope of PCI to allow cyber insurers to understand personal cyber risk threats and vectors, customer awareness, capabilities, and their associated needs. Additionally, this will allow cyber insurers to conceptualise appropriate frameworks allowing effective management and distribution of PCI products and services within a landscape often in-congruent with risk attributes commonly associated with traditional personal line insurance products. Cyberspace has provided significant improvement to the quality of social connectivity and productivity during past decades and allowed enormous capability uplift of information sharing and communication between people and communities. Conversely, personal digital dependency furnish ample opportunities for adverse cyber events such as data breaches and cyber-attacksthus introducing a continuous and insidious threat of omnipresent cyber risk–particularly since the advent of the COVID-19 pandemic and wide-spread adoption of ‘work-from-home’ practices. Recognition of escalating inter-dependencies, vulnerabilities and inadequate personal cyber behaviours have prompted efforts by businesses and individuals alike to investigate strategies and tactics to mitigate cyber risk – of which cyber insurance is a viable, cost-effective option. It is argued that, ceteris parabus, the nature of cyberspace intrinsically provides characteristic peculiarities that pose significant and bespoke challenges to cyber insurers, often in-congruent with risk attributes commonly associated with traditional personal line insurance products. These challenges include (inter alia) a paucity of historical claim/loss data for underwriting and pricing purposes, interdependencies of cyber architecture promoting high correlation of cyber risk, difficulties in evaluating cyber risk, intangibility of risk assets (such as data, reputation), lack of standardisation across the industry, high and undetermined tail risks, and moral hazard among others. This study proposes a thematic overview of the literature deemed necessary to conceptualise the challenges to issuing personal cyber coverage. There is an evident absence of empirical research appertaining to PCI and the design of operational business models for this business domain, especially qualitative initiatives that (1) attempt to define the scope of the peril, (2) secure an understanding of the needs of both cyber insurer and customer, and (3) to identify elements pivotal to effective management and profitable distribution of PCI - leading to an argument proposed by the author that postulates that the traditional general insurance customer journey and business model are ill-suited for the lineaments of cyberspace. The findings of the review confirm significant gaps in contemporary research within the domain of personal cyber insurance.

Keywords: cyberspace, personal cyber risk, personal cyber insurance, customer journey, business model

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Authors: Osman Adiguzel

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Shape-memory alloys are a new class of functional materials with a peculiar property known as shape memory effect. These alloys return to a previously defined shape on heating after deformation in low temperature product phase region and take place in a class of functional materials due to this property. The origin of this phenomenon lies in the fact that the material changes its internal crystalline structure with changing temperature. Shape memory effect is based on martensitic transitions, which govern the remarkable changes in internal crystalline structure of materials. Martensitic transformation, which is a solid state phase transformation, occurs in thermal manner in material on cooling from high temperature parent phase region. This transformation is governed by changes in the crystalline structure of the material. Shape memory alloys cycle between original and deformed shapes in bulk level on heating and cooling, and can be used as a thermal actuator or temperature-sensitive elements due to this property. Martensitic transformations usually occur with the cooperative movement of atoms by means of lattice invariant shears. The ordered parent phase structures turn into twinned structures with this movement in crystallographic manner in thermal induced case. The twinned martensites turn into the twinned or oriented martensite by stressing the material at low temperature martensitic phase condition. The detwinned martensite turns into the parent phase structure on first heating, first cycle, and parent phase structures turn into the twinned and detwinned structures respectively in irreversible and reversible memory cases. On the other hand, shape memory materials are very important and useful in many interdisciplinary fields such as medicine, pharmacy, bioengineering, metallurgy and many engineering fields. The choice of material as well as actuator and sensor to combine it with the host structure is very essential to develop main materials and structures. Copper based alloys exhibit this property in metastable beta-phase region, which has bcc-based structures at high temperature parent phase field, and these structures martensitically turn into layered complex structures with lattice twinning following two ordered reactions on cooling. Martensitic transition occurs as self-accommodated martensite with inhomogeneous shears, lattice invariant shears which occur in two opposite directions, <110 > -type directions on the {110}-type plane of austenite matrix which is basal plane of martensite. This kind of shear can be called as {110}<110> -type mode and gives rise to the formation of layered structures, like 3R, 9R or 18R depending on the stacking sequences on the close-packed planes of the ordered lattice. In the present contribution, x-ray diffraction and transmission electron microscopy (TEM) studies were carried out on two copper based alloys which have the chemical compositions in weight; Cu-26.1%Zn 4%Al and Cu-11%Al-6%Mn. X-ray diffraction profiles and electron diffraction patterns reveal that both alloys exhibit super lattice reflections inherited from parent phase due to the displacive character of martensitic transformation. X-ray diffractograms taken in a long time interval show that locations and intensities of diffraction peaks change with the aging time at room temperature. In particular, some of the successive peak pairs providing a special relation between Miller indices come close each other.

Keywords: Shape memory effect, martensite, twinning, detwinning, self-accommodation, layered structures

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