Search results for: artificial neuron network

Authors: Emmanouil Papavasileiou, Nikos Bozionelos, Liza Howe-Walsh, Sarah Turnbull

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Purpose: The research focuses on women academics’ insecure identity at work and examines its link with generational identity. The aim is to enrich understanding of identities at work as a crucial attribute of managing academics in the context of the proliferation of managerialist controls of audit, accountability, monitoring, and performativity. Methodology: Positivist quantitative methodology was utilized. Data were collected from the Scientific Women's Academic Network (SWAN) Charter. Responses from 155 women academics based in the British Higher Education system were analysed. Findings: Analysis showed high prevalence of strong imposter feelings among participants, suggesting high insecurity at work among women academics in the United Kingdom. Generational identity was related to imposter feelings. In particular, Millennials scored significantly higher than the other generational groups. Research implications: The study shows that imposter feelings are variously manifested among the prevalent generations of women academics, while generational identity is a significant antecedent of such feelings. Research limitations: Caution should be exercised in generalizing the findings to national cultural contexts beyond the United Kingdom. Practical and social implications: Contrary to popular depictions of Millennials as self-centered, narcissistic, materialistic and demanding, women academics who are members of this generational group appear significantly more insecure than the preceding generations. Value: The study provides insightful understandings into women academics’ identity at work as a function of generational identity, and provides a fruitful avenue for further research within and beyond this gender group and profession.

Keywords: academics, generational diversity, imposter feelings, United Kingdom, women, work identity

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Authors: Shveta Puri, Shiv Jyoti Pandey, G. M. Bhat, Neha Raina

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TheJammu and Kashmir region of the Northwest Himalaya had witnessed many devastating earthquakes in the recent past and has remained unexplored for any kind of seismic investigations except scanty records of the earthquakes that occurred in this region in the past. In this study, we have used local seismic data of year 2013 that was recorded by the network of Broadband Seismographs in J&K. During this period, our seismic stations recorded about 207 earthquakes including two moderate events of Mw 5.7 on 1st May, 2013 and Mw 5.1 of 2nd August, 2013.We analyzed the events of Mw 3-4.6 and the main events only (for minimizing the error) for source parameters, b value and sense of movement through waveform modeling for understanding seismotectonic and seismic hazard of the region. It has been observed that most of the events are bounded between 32.9° N – 33.3° N latitude and 75.4° E – 76.1° E longitudes, Moment Magnitude (Mw) ranges from Mw 3 to 5.7, Source radius (r), from 0.21 to 3.5 km, stress drop, from 1.90 bars to 71.1 bars and Corner frequency, from 0.39 – 6.06 Hz. The b-value for this region was found to be 0.83±0 from these events which are lower than the normal value (b=1), indicating the area is under high stress. The travel time inversion and waveform inversion method suggest focal depth up to 10 km probably above the detachment depth of the Himalayan region. Moment tensor solution of the (Mw 5.1, 02:32:47 UTC) main event of 2ndAugust suggested that the source fault is striking at 295° with dip of 33° and rake value of 85°. It was found that these events form intense clustering of small to moderate events within a narrow zone between Panjal Thrust and Kishtwar Window. Moment tensor solution of the main events and their aftershocks indicating thrust type of movement is occurring in this region.

Keywords: b-value, moment tensor, seismotectonics, source parameters

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Authors: Broto Seno

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This study aims to describe and examine more in the implementation of educational partnerships for undergraduate students at Yogyakarta State University (YSU), which is more focused on educational partnerships abroad. This study used descriptive qualitative approach. The study subjects consisted of a vice-rector, two staff education partnerships, four vice-dean, nine undergraduate students and three foreign students. Techniques of data collection using interviews and document review. Validity test of the data source using triangulation. Data analysis using flow models Miles and Huberman, namely data reduction, data display, and conclusion. Results of this study showed that the implementation of educational partnerships abroad for undergraduate students at YSU meets six of the nine indicators of the success of strategic partnerships. Six indicators are long-term, strategic, mutual trust, sustainable competitive advantages, mutual benefit for all the partners, and the separate and positive impact. The indicator has not been achieved is cooperative development, successful, and world class / best practice. These results were obtained based on the discussion of the four formulation of the problem, namely: 1) Implementation and development of educational partnerships abroad has been running good enough, but not maximized. 2) Benefits of the implementation of educational partnerships abroad is providing learning experiences for students, institutions of experience in comparison to each faculty, and improving the network of educational partnerships for YSU toward World Class University. 3) The sustainability of educational partnerships abroad is pursuing a strategy of development through improved management of the partnership. 4) Supporting factors of educational partnerships abroad is the support of YSU, YSU’s partner and society. Inhibiting factors of educational partnerships abroad is not running optimally management.

Keywords: partnership, education, YSU, institutions and faculties

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Authors: Rinyu Shei Mercy

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Protected areas are the potential areas for the development of ecotourism because of their biodiversity, landscapes, waterfalls, lakes, caves, salt lick and cultural heritage of local or indigenous people. These potentials have not yet been valorized, so this study will enable to investigate the evaluation and possibilities of valorization of ecotourism potentials in the Mbam and Djerem National Park. Hence, this was done by employing a combination of field observations, examination, data collection and evaluation, using a SWOT analysis. The SWOT provides an analysis to determine the strengths, weaknesses, opportunities and threats, and strategic suggestions for ecological planning. The study helps to determine an ecotouristic inventory and mapping of ecotourism potentials of the park, evaluate the degree of valorization of these potentials and the possibilities of valorization. Finally, the study has proven that the park has much natural potentials such as rivers, salt licks, waterfall and rapids, lakes, caves and rocks, etc. Also, from the study, it was realized that as concerns the degree of valorization of these ecotourism potentials, 50% of the population visit the salt lick of Pkayere because it’s a biodiversity hotspot and rich in mineral salt attracting a lot of animals and the least is the lake Miyere with 1% due to the fact that it is sacred. Moreover, from the results, there are possibilities that these potentials can be valorized and put into use because of their attractive nature such as creating good roads and bridges, good infrastructural facilities, good communication network etc. So, the study recommends that, in this process, MINTOUR, WCS, tour operators must interact sufficiently in order to develop the potential interest to ecotourism, ecocultural tourism and scientific tourism.

Keywords: ecotourism, national park Mbam and Djerem, valorization of biodiversity, protected areas of Cameroon

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Authors: Shoury Gupta

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Chatbots are a rapidly growing technological trend that has revolutionized the way businesses interact with their customers. With the advancements in artificial intelligence, chatbots can now mimic human-like conversations and provide instant and efficient responses to customer inquiries. In this research paper, we aim to explore the implications of chatbots on the future of globalization for both businesses and consumers. The paper begins by providing an overview of the current state of chatbots in the global market and their growth potential in the future. The focus is on how chatbots have become a valuable tool for businesses looking to expand their global reach, especially in areas with high population density and language barriers. With chatbots, businesses can engage with customers in different languages and provide 24/7 customer service support, creating a more accessible and convenient customer experience. The paper then examines the impact of chatbots on cross-cultural communication and how they can help bridge communication gaps between businesses and consumers from different cultural backgrounds. Chatbots can potentially facilitate cross-cultural communication by offering real-time translations, voice recognition, and other innovative features that can help users communicate effectively across different languages and cultures. By providing more accessible and inclusive communication channels, chatbots can help businesses reach new markets and expand their customer base, making them more competitive in the global market. However, the paper also acknowledges that there are potential drawbacks associated with chatbots. For instance, chatbots may not be able to address complex customer inquiries that require human input. Additionally, chatbots may perpetuate biases if they are programmed with certain stereotypes or assumptions about different cultures. These drawbacks may have significant implications for businesses and consumers alike. To explore the implications of chatbots on the future of globalization in greater detail, the paper provides a thorough review of existing literature and case studies. The review covers topics such as the benefits of chatbots for businesses and consumers, the potential drawbacks of chatbots, and how businesses can mitigate any risks associated with chatbot use. The paper also discusses the ethical considerations associated with chatbot use, such as privacy concerns and the need to ensure that chatbots do not discriminate against certain groups of people. The ethical implications of chatbots are particularly important given the potential for chatbots to be used in sensitive areas such as healthcare and financial services. Overall, this research paper provides a comprehensive analysis of chatbots and their implications for the future of globalization. By exploring both the potential benefits and drawbacks of chatbot use, the paper aims to provide insights into how businesses and consumers can leverage this technology to achieve greater global reach and improve cross-cultural communication. Ultimately, the paper concludes that chatbots have the potential to be a powerful tool for businesses looking to expand their global footprint and improve their customer experience, but that care must be taken to mitigate any risks associated with their use.

Keywords: chatbots, conversational AI, globalization, businesses

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Authors: Peter. M. Kusen, Georg Wandrey, Christopher Probst, Dietrich Kohlheyer, Jochen Buchs, Jorg Pietruszkau

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Light as a stimulus provides the capability to develop regulation techniques for customizable gene expression. A great advantage is the extremely flexible and accurate dosing that can be performed in a non invasive and sterile manner even for high throughput technologies. Therefore, light regulation in a multiwell microbioreactor system was realized providing the opportunity to control gene expression with outstanding complexity. A light-regulated gene expression system in Saccharomyces cerevisiae was designed applying the strategy of caged compounds. These compounds are photo-labile protected and therefore biologically inactive regulator molecules which can be reactivated by irradiation with certain light conditions. The “caging” of a repressor molecule which is consumed after deprotection was essential to create a flexible expression system. Thereby, gene expression could be temporally repressed by irradiation and subsequent release of the active repressor molecule. Afterwards, the repressor molecule is consumed by the yeast cells leading to reactivation of gene expression. A yeast strain harboring a construct with the corresponding repressible promoter in combination with a fluorescent marker protein was applied in a Photo-BioLector platform which allows individual irradiation as well as online fluorescence and growth detection. This device was used to precisely control the repression duration by adjusting the amount of released repressor via different irradiation times. With the presented screening platform the regulation of complex expression procedures was achieved by combination of several repression/derepression intervals. In particular, a stepwise increase of temporally-constant expression levels was demonstrated which could be used to study concentration dependent effects on cell functions. Also linear expression rates with variable slopes could be shown representing a possible solution for challenging protein productions, whereby excessive production rates lead to misfolding or intoxication. Finally, the very flexible regulation enabled accurate control over the expression induction, although we used a repressible promoter. Summing up, the continuous online regulation of gene expression has the potential to synchronize gene expression levels to optimize metabolic flux, artificial enzyme cascades, growth rates for co cultivations and many other applications addicted to complex expression regulation. The developed light-regulated expression platform represents an innovative screening approach to find optimization potential for production processes.

Keywords: caged-compounds, gene expression regulation, optogenetics, photo-labile protecting group

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Authors: Emanuel Teixeira, Anderson Ramos, Marisa Lourenço, Fernando J. Velez, Jon M. Peha

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This article discusses the benefit cost analysis aspects of millimetre wavebands (mmWaves) and Super High Frequency (SHF). The devaluation along the distance of the carrier-to-noise-plus-interference ratio with the coverage distance is assessed by considering two different path loss models, the two-slope urban micro Line-of-Sight (UMiLoS) for the SHF band and the modified Friis propagation model, for frequencies above 24 GHz. The equivalent supported throughput is estimated at the 5.62, 28, 38, 60 and 73 GHz frequency bands and the influence of carrier-to-noise-plus-interference ratio in the radio and network optimization process is explored. Mostly owing to the lessening caused by the behaviour of the two-slope propagation model for SHF band, the supported throughput at this band is higher than at the millimetre wavebands only for the longest cell lengths. The benefit cost analysis of these pico-cellular networks was analysed for regular cellular topologies, by considering the unlicensed spectrum. For shortest distances, we can distinguish an optimal of the revenue in percentage terms for values of the cell length, R ≈ 10 m for the millimeter wavebands and for longest distances an optimal of the revenue can be observed at R ≈ 550 m for the 5.62 GHz. It is possible to observe that, for the 5.62 GHz band, the profit is slightly inferior than for millimetre wavebands, for the shortest Rs, and starts to increase for cell lengths approximately equal to the ratio between the break-point distance and the co-channel reuse factor, achieving a maximum for values of R approximately equal to 550 m.

Keywords: millimetre wavebands, SHF band, SINR, cost benefit analysis, 5G

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Authors: Kenan Morani, Esra Kaya Ayana

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This study aimed to develop a novel pipeline for COVID-19 detection using a large and rigorously annotated database of computed tomography (CT) images. The pipeline consists of UNet-based segmentation, lung extraction, and a classification part, with the addition of optional slice removal techniques following the segmentation part. In this work, a batch normalization was added to the original UNet model to produce lighter and better localization, which is then utilized to build a full pipeline for COVID-19 diagnosis. To evaluate the effectiveness of the proposed pipeline, various segmentation methods were compared in terms of their performance and complexity. The proposed segmentation method with batch normalization outperformed traditional methods and other alternatives, resulting in a higher dice score on a publicly available dataset. Moreover, at the slice level, the proposed pipeline demonstrated high validation accuracy, indicating the efficiency of predicting 2D slices. At the patient level, the full approach exhibited higher validation accuracy and macro F1 score compared to other alternatives, surpassing the baseline. The classification component of the proposed pipeline utilizes a convolutional neural network (CNN) to make final diagnosis decisions. The COV19-CT-DB dataset, which contains a large number of CT scans with various types of slices and rigorously annotated for COVID-19 detection, was utilized for classification. The proposed pipeline outperformed many other alternatives on the dataset.

Keywords: classification, computed tomography, lung extraction, macro F1 score, UNet segmentation

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Authors: Viral Nagori, Preeti Shroff, Prathana Dodia

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The paper presents the study on women entrepreneurship over the last decade in Indian and Global Context. This research study has its basis primarily in the literature review. The research methodology classifies the literature review paper based on different parameters of women entrepreneurship. The literature review relies on research papers in journals, articles in periodicals, and books published on women entrepreneurship. To accomplish this, the criteria included finding the most relevant, recent, and cited studies on women entrepreneurship over the last decade. It aims to evaluate the issues and challenges faced by women entrepreneurs. The finding suggested that there are several common obstacles, which hinders the pathway to success towards being a successful woman entrepreneur. The paper also describes such common obstacles like the level of education, family responsibilities, lack of business information, religious and cultural constraints, limited mobility, exposure, lack of working capital, and more. The in-depth analysis of literature review indicates that despite the numerous barriers, the arrival of social media has played a crucial role in enabling women to start and scale up their enterprises. Further, technology innovation has given them access to have relevant market information, increase reach and network with the customers. It enabled them to achieve work life balance and pursuing entrepreneur in them. The paper also describes the Government and Nongovernmental initiatives for promotion of women entrepreneurship. At the end, the study provides insights into the changing dynamics of women entrepreneurship in the current scenario and future prospects.

Keywords: changing dynamics, government initiatives, literature review, social media, technology innovation, women entrepreneurship

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Authors: Filomena Lopes, Miguel Magalhaes, Carla Santos Pereira, Natercia Durao, Cristina Costa-Lobo

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The option to implement curricular internships with undergraduate students is a pedagogical option with some good results perceived by academic staff, employers, and among graduates in general and IT (Information Technology) in particular. Knowing that this type of exercise has never been so relevant, as one tries to give meaning to the future in a landscape of rapid and deep changes. We have as an example the potential disruptive impact on the jobs of advances in robotics, artificial intelligence and 3-D printing, which is a focus of fierce debate. It is in this context that more and more students and employers engage in the pursuit of career-promoting responses and business development, making their investment decisions of training and hiring. Three decades of experience and research in computer science degree and in information systems technologies degree at the Portucalense University, Portuguese private university, has provided strong evidence of its advantages. The Human Interaction Skills development as well as the attractiveness of such experiences for students are topics assumed as core in the Ccnception and management of the activities implemented in these study cycles. The objective of this paper is to gather evidence of the Human Interaction Skills explained and valued within the curriculum internship experiences of IT students employability. Data collection was based on the application of questionnaire to intern counselors and to students who have completed internships in these undergraduate courses in the last decade. The trainee supervisor, responsible for monitoring the performance of IT students in the evolution of traineeship activities, evaluates the following Human Interaction Skills: Motivation and interest in the activities developed, interpersonal relationship, cooperation in company activities, assiduity, ease of knowledge apprehension, Compliance with norms, insertion in the work environment, productivity, initiative, ability to take responsibility, creativity in proposing solutions, and self-confidence. The results show that these undergraduate courses promote the development of Human Interaction Skills and that these students, once they finish their degree, are able to initiate remunerated work functions, mainly by invitation of the institutions in which they perform curricular internships. Findings obtained from the present study contribute to widen the analysis of its effectiveness in terms of future research and actions in regard to the transition from Higher Education pathways to the Labour Market.

Keywords: human interaction skills, employability, internships, information technology, higher education

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Authors: Ifeanyichukwu Valerie Oguafor

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Women generally have been categorized and placed under the chain of business industry, sometimes highly regarded and other times merely. The social construction of womanhood does not in all sense support a woman going into business, let alone succeed in it because it is believed that it a man’s world. In a typical patriarchal setting, a woman is expected to know nothing more domestic roles. For some women, this is not the case as they have been able to break these barriers to excel in business amidst these social setting and stereotypes. This study examines media representation of Nigerians business women, using content analysis of TV interviews as media text, framing analysis as an approach in qualitative methodology, The study further aims to analyse media frames of two Nigerian business women: FolorunshoAlakija, a business woman in the petroleum industry with current net worth 1.1 billion U.S dollars, emerging as the richest black women in the world 2014. MosunmolaAbudu, a media magnate in Nigeria who launched the first Africa’s global black entertainment and lifestyle network in 2013. This study used six predefined frames: the business woman, the myth of business women, the non-traditional woman, women in leading roles, the family woman, the religious woman, and the philanthropist woman to analyse the representation of Nigerian business women in the media. The analysis of the aforementioned frames on TV interviews with these women reveals that the media perpetually reproduces existing gender stereotype and do not challenge patriarchy. Women face challenges in trying to succeed in business while trying to keep their homes stable. This study concludes that the media represent and reproduce gender stereotypes in spite of the expectation of empowering women. The media reduces these women’s success insignificant rather than a role model for women in society.

Keywords: representation of business women in the media, business women in Nigeria, framing in the media, patriarchy, women's subordination

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Authors: Sani M. Lawal, Idris Musa, Aliyu D. Usman

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The Pareto approach of optimal solutions in a search space that evolved in multi-objective optimization problems is adopted in this paper, which stands for a set of solutions in the search space. This paper aims at presenting an optimal placement of Distributed Generation (DG) in radial distribution networks with an optimal size for minimization of power loss and voltage deviation as well as maximizing voltage profile of the networks. And these problems are formulated using particle swarm optimization (PSO) as a constraint nonlinear optimization problem with both locations and sizes of DG being continuous. The objective functions adopted are the total active power loss function and voltage deviation function. The multiple nature of the problem, made it necessary to form a multi-objective function in search of the solution that consists of both the DG location and size. The proposed PSO algorithm is used to determine optimal placement and size of DG in a distribution network. The output indicates that PSO algorithm technique shows an edge over other types of search methods due to its effectiveness and computational efficiency. The proposed method is tested on the standard IEEE 34-bus and validated with 33-bus test systems distribution networks. Results indicate that the sizing and location of DG are system dependent and should be optimally selected before installing the distributed generators in the system and also an improvement in the voltage profile and power loss reduction have been achieved.

Keywords: distributed generation, pareto, particle swarm optimization, power loss, voltage deviation

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Authors: Monica Plechero

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Many firms belonging to Italian industrial districts faced a crisis starting from 2000 and upsurging during 2008-2014. To remain competitive in the global market, these firms and their local systems need to renovate their traditional competitive advantages, strengthen their link with global flows of knowledge. This may be particularly relevant in sectors such as the mechatronics, that combine traditional knowledge domain with new knowledge domains (e.g. mechanics, electronics, and informatics). This sector is nowadays one of the key sectors within the so-called ‘smart specialization strategy’ that can lead part of the Italian traditional industry towards new economic developmental opportunities. This paper, by investigating the mechatronics district of the Veneto region, wants to shed new light on how firms of a local system can gain from the globalization of innovation and innovation networks. Methodologically, the paper relies on primary data collected through a survey targeting firms of the local system, as well as on a number of qualitative case studies. The relevant role of medium size companies in the district emerges as evident, as they have wider opportunities to be involved in different processes of globalization of innovation. Indeed, with respect to small companies, the size of medium firms allows them to exploit strategically international markets and globally distributed knowledge. Supporting medium firms’ global innovation strategies, and incentivizing their role as district gatekeepers, may strengthen the competitive capability of the local system and provide new opportunities to positively face global competition.

Keywords: global innovation network, industrial district, internationalization, innovation, mechatronics, Veneto region

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Authors: Philip Semaha, Zhongfang Lei, Ziwen Zhao, Sen Liu, Zhenya Zhang, Kazuya Shimizu

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The increasing generation of saline wastewater through various industrial activities is becoming a global concern for activated sludge (AS) based biological treatment which is widely applied in wastewater treatment plants (WWTPs). As for the AS process, an increase in wastewater salinity has negative impact on its overall performance. The advent of conventional aerobic granular sludge (AGS) or bacterial AGS biotechnology has gained much attention because of its superior performance. The development of algal-bacterial AGS could enhance better nutrients removal, potentially reduce aeration cost through symbiotic algae-bacterial activity, and thus, can also reduce overall treatment cost. Nonetheless, the potential of salt stress to decrease biomass growth, microbial activity and nutrient removal exist. Up to the present, little information is available on saline wastewater treatment by algal-bacterial AGS. To the authors’ best knowledge, a comparison of the two AGS systems has not been done to evaluate nutrients removal capacity in the context of salinity increase. This study sought to figure out the impact of salinity on the algal-bacterial AGS system in comparison to bacterial AGS one, contributing to the application of AGS technology in the real world of saline wastewater treatment. In this study, the salt concentrations tested were 0 g/L, 1 g/L, 5 g/L, 10 g/L and 15 g/L of NaCl with 24-hr artificial illuminance of approximately 97.2 µmol m¯²s¯¹, and mature bacterial and algal-bacterial AGS were used for the operation of two identical sequencing batch reactors (SBRs) with a working volume of 0.9 L each, respectively. The results showed that salinity increase caused no apparent change in the color of bacterial AGS; while for algal-bacterial AGS, its color was progressively changed from green to dark green. A consequent increase in granule diameter and fluffiness was observed in the bacterial AGS reactor with the increase of salinity in comparison to a decrease in algal-bacterial AGS diameter. However, nitrite accumulation peaked from 1.0 mg/L and 0.4 mg/L at 1 g/L NaCl in the bacterial and algal-bacterial AGS systems, respectively to 9.8 mg/L in both systems when NaCl concentration varied from 5 g/L to 15 g/L. Almost no ammonia nitrogen was detected in the effluent except at 10 g/L NaCl concentration, where it averaged 4.2 mg/L and 2.4 mg/L, respectively, in the bacterial and algal-bacterial AGS systems. Nutrients removal in the algal-bacterial system was relatively higher than the bacterial AGS in terms of nitrogen and phosphorus removals. Nonetheless, the nutrient removal rate was almost 50% or lower. Results show that algal-bacterial AGS is more adaptable to salinity increase and could be more suitable for saline wastewater treatment. Optimization of operation conditions for algal-bacterial AGS system would be important to ensure its stably high efficiency in practice.

Keywords: algal-bacterial aerobic granular sludge, bacterial aerobic granular sludge, Nutrients removal, saline wastewater, sequencing batch reactor

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Authors: Veriko Jeladze, Besarion Partsvania, Levan Shoshiashvili

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This paper addresses a very topical issue today. The frequency range 2.5-100 GHz contains frequencies that have already been used or will be used in modern 5G technologies. The wavelengths used in 5G systems will be close to the body dimensions of small size biological objects, particularly insects. Because the body and body parts dimensions of insects at these frequencies are comparable with the wavelength, the high absorption of EMF energy in the body tissues can occur(body resonance) and therefore can cause harmful effects, possibly the extinction of some of them. An investigation into the impact of radio-frequency nonionizing electromagnetic field (EMF) utilized in the future 5G on insects is of great importance as a very high number of 5G network components will increase the total EMF exposure in the environment. All ecosystems of the earth are interconnected. If one component of an ecosystem is disrupted, the whole system will be affected (which could cause cascading effects). The study of these problems is an important challenge for scientists today because the existing studies are incomplete and insufficient. Consequently, the purpose of this proposed research is to investigate the possible hazardous impact of RF-EMFs (including 5G EMFs) on insects. The project will study the effects of these EMFs on various insects that have different body sizes through computer modeling at frequencies from 2.5 to 100 GHz. The selected insects are honey bee, wasp, and ladybug. For this purpose, the detailed 3D discrete models of insects are created for EM and thermal modeling through FDTD and will be evaluated whole-body Specific Absorption Rates (SAR) at selected frequencies. All these studies represent a novelty. The proposed study will promote new investigations about the bio-effects of 5G-EMFs and will contribute to the harmonization of safe exposure levels and frequencies of 5G-EMFs'.

Keywords: electromagnetic field, insect, FDTD, specific absorption rate (SAR)

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Authors: Mohammad Ghiasvand, Babak Khorsandi, Morteza Kolahdoozan

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Under the influence of waves, oil in the sea is subject to vertical scattering in the water column. Scientists' knowledge of how oil is dispersed in the water column is one of the lowest levels of knowledge among other processes affecting oil in the marine environment, which highlights the need for research and study in this field. Therefore, this study investigates the distribution of oil in the water column in a turbulent environment with zero velocity characteristics. Lack of laboratory results to analyze the distribution of petroleum pollutants in deep water for information Phenomenon physics on the one hand and using them to calibrate numerical models on the other hand led to the development of laboratory models in research. According to the aim of the present study, which is to investigate the distribution of oil in homogeneous and isotropic turbulence caused by the oscillating Grid, after reaching the ideal conditions, the crude oil flow was poured onto the water surface and oil was distributed in deep water due to turbulence was investigated. In this study, all experimental processes have been implemented and used for the first time in Iran, and the study of oil diffusion in the water column was considered one of the key aspects of pollutant diffusion in the oscillating Grid environment. Finally, the required oscillation velocities were taken at depths of 10, 15, 20, and 25 cm from the water surface and used in the analysis of oil diffusion due to turbulence parameters. The results showed that with the characteristics of the present system in two static modes and network motion with a frequency of 0.8 Hz, the results of oil diffusion in the four mentioned depths at a frequency of 0.8 Hz compared to the static mode from top to bottom at 26.18, 57 31.5, 37.5 and 50% more. Also, after 2.5 minutes of the oil spill at a frequency of 0.8 Hz, oil distribution at the mentioned depths increased by 49, 61.5, 85, and 146.1%, respectively, compared to the base (static) state.

Keywords: homogeneous and isotropic turbulence, oil distribution, oscillating grid, oil spill

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Authors: Nasser S. Shebka

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Fuzzy logic is used in complex adaptive systems where classical tools of representing knowledge are unproductive. Nevertheless, the incorporation of fuzzy logic, as it’s the case with all artificial intelligence tools, raised some inconsistencies and limitations in dealing with increased complexity systems and rules that apply to real-life situations and hinders the ability of the inference process of such systems, but it also faces some inconsistencies between inferences generated fuzzy rules of complex or imprecise knowledge-based systems. The use of fuzzy logic enhanced the capability of knowledge representation in such applications that requires fuzzy representation of truth values or similar multi-value constant parameters derived from multi-valued logic, which set the basis for the three t-norms and their based connectives which are actually continuous functions and any other continuous t-norm can be described as an ordinal sum of these three basic ones. However, some of the attempts to solve this dilemma were an alteration to fuzzy logic by means of non-monotonic logic, which is used to deal with the defeasible inference of expert systems reasoning, for example, to allow for inference retraction upon additional data. However, even the introduction of non-monotonic fuzzy reasoning faces a major issue of conflict resolution for which many principles were introduced, such as; the specificity principle and the weakest link principle. The aim of our work is to improve the logical representation and functional modelling of AI systems by presenting a method of resolving existing and potential rule conflicts by representing temporal modalities within defeasible inference rule-based systems. Our paper investigates the possibility of resolving fuzzy rules conflict in a non-monotonic fuzzy reasoning-based system by introducing temporal modalities and Kripke's general weak modal logic operators in order to expand its knowledge representation capabilities by means of flexibility in classifying newly generated rules, and hence, resolving potential conflicts between these fuzzy rules. We were able to address the aforementioned problem of our investigation by restructuring the inference process of the fuzzy rule-based system. This is achieved by using time-branching temporal logic in combination with restricted first-order logic quantifiers, as well as propositional logic to represent classical temporal modality operators. The resulting findings not only enhance the flexibility of complex rule-base systems inference process but contributes to the fundamental methods of building rule bases in such a manner that will allow for a wider range of applicable real-life situations derived from a quantitative and qualitative knowledge representational perspective.

Keywords: fuzzy rule-based systems, fuzzy tense inference, intelligent systems, temporal modalities

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Authors: Saikiran Subbagari, Avinash Malladhi

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Anti Money Laundering (AML) regulations are designed to prevent money laundering and terrorist financing activities worldwide. Financial institutions around the world are legally obligated to identify, assess and mitigate the risks associated with money laundering and report any suspicious transactions to governing authorities. With increasing volumes of data to analyze, financial institutions seek to automate their AML processes. In the rise of financial crimes, optical character recognition (OCR), in combination with machine learning (ML) algorithms, serves as a crucial tool for automating AML processes by extracting the data from documents and identifying suspicious transactions. In this paper, we examine the utilization of OCR for AML and delve into various OCR techniques employed in AML processes. These techniques encompass template-based, feature-based, neural network-based, natural language processing (NLP), hidden markov models (HMMs), conditional random fields (CRFs), binarizations, pattern matching and stroke width transform (SWT). We evaluate each technique, discussing their strengths and constraints. Also, we emphasize on how OCR can improve the accuracy of customer identity verification by comparing the extracted text with the office of foreign assets control (OFAC) watchlist. We will also discuss how OCR helps to overcome language barriers in AML compliance. We also address the implementation challenges that OCR-based AML systems may face and offer recommendations for financial institutions based on the data from previous research studies, which illustrate the effectiveness of OCR-based AML.

Keywords: anti-money laundering, compliance, financial crimes, fraud detection, machine learning, optical character recognition

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Authors: Xuan Zheng

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China is home to one of the world’s largest Deaf and Hard of Hearing (DHH) populations. In the 1980s, the concept of inclusive education was introduced, giving rise to a unique “learning in regular class (随班就读)” model tailored to local contexts. China’s inclusive education for DHH students is diversifying with innovative models like special education classes at regular schools, regular classes at regular schools, resource classrooms, satellite classes, and bilingual-bimodal projects. The scope extends to preschool and higher education programs. However, the inclusive development of DHH students faces challenges. The prevailing pathological viewpoint on disabilities persists, emphasizing the necessity for favorable auditory and speech rehabilitation outcomes before DHH students can integrate into regular classes. In addition, inadequate support systems in inclusive schools result in poor academic performance and increased psychological disorders among the group, prompting a notable return to special education schools. Looking ahead, China’s inclusive education for DHH students needs a substantial shift from “learning in regular class” to “sharing equal regular education.” Particular attention should be devoted to the effective integration of DHH students who employ sign language into mainstream educational settings. It is crucial to strengthen regulatory frameworks and institutional safeguards, advance the professional development of educators specializing in inclusive education for DHH students, and consistently enhance resources tailored to this demographic. Furthermore, the establishment of a robust, multidimensional, and collaborative support network, engaging both families and educational institutions, is also a pivotal facet.

Keywords: deaf, hard of hearing, inclusive education, China

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Authors: Berna Yaylalı, Isin Can Traunmüller

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This paper explores the emergent bottom-up practices in the fields of architecture and urban design within comparative perspectives of two cities. As a temporary, easily affordable intervention that gives the possibility of transforming neglected spaces into vibrant public spaces, tactical urbanism, together with creative place-making strategies, presents alternative ways of creating sustainable developments in derelict and underused areas. This study examines the potential of social and physical developments through a reading of case studies of two creative spatial practices: a pop-up garden transformed from an unused derelict space in Favoriten, Vienna, and an urban community garden in Kuzguncuk, Istanbul. Two cities are chosen according to their multicultural population and diversity. Istanbul was selected as a design city by UNESCO Creative Cities Network in 2017, and Vienna was declared an open and livable city by its local government. This research will use media archives and reports, interviews with locals and local governments, site observations, and visual recordings as methods to provide a critical reading on creative public spaces from the view of local users in these neighborhoods. Reflecting on these emergent ways, this study aims at discussing the production process of tactile urbanism with the practices of locals and the decision-making process with cases from İstanbul and Vienna. The comparison between their place-making strategies in tactical urbanism will give important insights for future developments.

Keywords: creative city, tactical urbanism, neglected area, public space

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Authors: Xingyue Yang

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This study focused on Chinese social media stars and the relationship between their level of fame on the social media platform Sina Weibo and their sales revenue on the E-commerce platform Taobao/Tmall.com. This was viewed from the perspective of Adler’s superstardom theory and Rosen and MacDonald’s theories examining the economics of celebrities who build their audience using digital, rather than traditional platforms. Theory and empirical research support the assertion that stars of traditional media achieve popular success due to a combination of talent and market concentration, as well as a range of other factors. These factors are also generally considered relevant to the popularisation of social media stars. However, success across digital media platforms also involves other variables - for example, upload strategies, cross-platform promotions, which often have no direct corollary in traditional media. These factors were the focus of our study, which investigated the relationship between popularity, promotional strategy and sales revenue for 15 social media stars who specialised in culinary topics on the Chinese social media platform Sina Weibo. In 2019, these food bloggers made a total of 2076 Sina Weibo posts, and these were compiled alongside calculations made to determine each food blogger’s sales revenue on the eCommerce platforms Taobao/Tmall. Quantitative analysis was then performed on this data, which determined that certain upload strategies on Weibo - such as upload time, posting format and length of video - have an important impact on the success of sales revenue on Taobao/Tmall.com.

Keywords: attention economics, digital media, network effect, social media stars

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Authors: Masoud Sheidai

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Biologists with a special field of population genetics and phylogeny have different research tasks such as populations’ genetic variability and divergence, species relatedness, the evolution of genetic and morphological characters, and identification of DNA SNPs with adaptive potential. To tackle these problems and reach a concise conclusion, they must use the proper and efficient statistical and bioinformatic methods as well as suitable genetic and morphological characteristics. In recent years application of different bioinformatic and statistical methods, which are based on various well-documented assumptions, are the proper analytical tools in the hands of researchers. The species delineation is usually carried out with the use of different clustering methods like K-means clustering based on proper distance measures according to the studied features of organisms. A well-defined species are assumed to be separated from the other taxa by molecular barcodes. The species relationships are studied by using molecular markers, which are analyzed by different analytical methods like multidimensional scaling (MDS) and principal coordinate analysis (PCoA). The species population structuring and genetic divergence are usually investigated by PCoA and PCA methods and a network diagram. These are based on bootstrapping of data. The Association of different genes and DNA sequences to ecological and geographical variables is determined by LFMM (Latent factor mixed model) and redundancy analysis (RDA), which are based on Bayesian and distance methods. Molecular and morphological differentiating characters in the studied species may be identified by linear discriminant analysis (DA) and discriminant analysis of principal components (DAPC). We shall illustrate these methods and related conclusions by giving examples from different edible and medicinal plant species.

Keywords: GWAS analysis, K-Means clustering, LFMM, multidimensional scaling, redundancy analysis

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Authors: Robin Molinier

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Industrial symbiosis (I.S) deals with both substitution synergies (exchange of waste materials, fatal energy and utilities as resources for production) and infrastructure/service sharing synergies. The latter is based on the intensification of use of an asset and thus requires to balance capital costs increments with snowball effects (network externalities) for its implementation. Initial investors must specify ex-ante arrangements (cost sharing and pricing schedule) to commit toward investments in capacities and transactions. Our model investigate the decision of 2 actors trying to choose cooperatively a level of infrastructure capacity oversizing to set a plug-and-play offer to a potential entrant whose capacity requirement is randomly distributed while satisficing their own requirements. Capacity cost exhibits sub-additive property so that there is room for profitable overcapacity setting in the first period. The entrant’s willingness-to-pay for the access to the infrastructure is dependent upon its standalone cost and the capacity gap that it must complete in case the available capacity is insufficient ex-post (the complement cost). Since initial capacity choices are driven by ex-ante (expected) yield extractible from the entrant we derive the expected complement cost function which helps us defining the investors’ objective function. We first show that this curve is decreasing and convex in the capacity increments and that it is shaped by the distribution function of the potential entrant’s requirements. We then derive the general form of solutions and solve the model for uniform and triangular distributions. Depending on requirements volumes and cost assumptions different equilibria occurs. We finally analyze the effect of a per-unit subsidy a public actor would apply to foster such sharing synergies.

Keywords: capacity, cooperation, industrial symbiosis, pricing

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Authors: Mukunda Upreti, Jill Storry, Rafael Björk, Emilie Louvet, Johan Normark, Sven Bergström

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Borrelia duttonii and most other relapsing fever species are Gram-negative bacteria which cause a blood borne infection characterized by the binding of bacterium to erythrocytes. The bacteria associate with two or more erythrocytes to form clusters of cells into rosettes. Rosetting is a major virulence factor and the mechanism is believed to facilitate persistence of bacteria in the circulatory system and the avoidance of host immune cells through masking or steric hindrance effects. However, the molecular mechanisms of rosette formation are still poorly understood. This study aims at determining the molecules involved in the rosette formation phenomenon. Fractionated serum, using different affinity purification methods, was investigated as a rosetting agent and IgG and at least one other serum components were needed for rosettes to form. An IgG titration curve demonstrated that IgG alone is not enough to restore rosette formation level to the level whole serum gives. IgG hydrolysis by IdeS ( Immunoglobulin G-degrading enzyme of Streptococcus pyogenes) and deglycosylation using N-Glycanase proved that the whole IgG molecule regardless of saccharide moieties is critical for Borrelia induced rosetting. Complement components C3 and C4 were also important serum molecules necessary to maintain optimum rosetting rates. The deactivation of complement network and serum depletion with C3 and C4 significantly reduced the rosette formation rate. The dependency of IgG and complement components also implied involvement of the complement receptor (CR1). Rosette formation test with Knops null RBC and sCR1 confirmed that CR1 is also part of Borrelia induced rosette formation.

Keywords: complement components C3 and C4, complement receptor 1, Immunoglobulin G, Knops null, Rosetting

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Authors: S. Agheb, G. Ledwich, G.Walker, Z.Tong

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Frequency control has become more of concern for reliable operation of interconnected power systems due to the integration of low inertia renewable energy sources to the grid and their volatility. Also, in case of a sudden fault, the system has less time to recover before widespread blackouts. Electric Vehicles (EV)s have the potential to cooperate in the Emergency Frequency Regulation (EFR) by a nonlinear control of the power system in case of large disturbances. The time is not adequate to communicate with each individual EV on emergency cases, and thus, an aggregate model is necessary for a quick response to prevent from much frequency deviation and the occurrence of any blackout. In this work, an aggregate of EVs is modelled as a big virtual battery in each area considering various aspects of uncertainty such as the number of connected EVs and their initial State of Charge (SOC) as stochastic variables. A control law was proposed and applied to the aggregate model using Lyapunov energy function to maximize the rate of reduction of total kinetic energy in a two-area network after the occurrence of a fault. The control methods are primarily based on the charging/ discharging control of available EVs as shunt capacity in the distribution system. Three different cases were studied considering the locational aspect of the model with the virtual EV either in the center of the two areas or in the corners. The simulation results showed that EVs could help the generator lose its kinetic energy in a short time after a contingency. Earlier estimation of possible contributions of EVs can help the supervisory control level to transmit a prompt control signal to the subsystems such as the aggregator agents and the grid. Thus, the percentage of EVs contribution for EFR will be characterized in the future as the goal of this study.

Keywords: emergency frequency regulation, electric vehicle, EV, aggregation, Lyapunov energy function

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Authors: M. Karimpour, L. Hitihamillage, N. Elkhoury, S. Moridpour, R. Hesami

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Rail transport authorities around the world have been facing a significant challenge when predicting rail infrastructure maintenance work for a long period of time. Generally, maintenance monitoring and prediction is conducted manually. With the restrictions in economy, the rail transport authorities are in pursuit of improved modern methods, which can provide precise prediction of rail maintenance time and location. The expectation from such a method is to develop models to minimize the human error that is strongly related to manual prediction. Such models will help them in understanding how the track degradation occurs overtime under the change in different conditions (e.g. rail load, rail type, rail profile). They need a well-structured technique to identify the precise time that rail tracks fail in order to minimize the maintenance cost/time and secure the vehicles. The rail track characteristics that have been collected over the years will be used in developing rail track degradation prediction models. Since these data have been collected in large volumes and the data collection is done both electronically and manually, it is possible to have some errors. Sometimes these errors make it impossible to use them in prediction model development. This is one of the major drawbacks in rail track degradation prediction. An accurate model can play a key role in the estimation of the long-term behavior of rail tracks. Accurate models increase the track safety and decrease the cost of maintenance in long term. In this research, a short review of rail track degradation prediction models has been discussed before estimating rail track degradation for the curve sections of Melbourne tram track system using Adaptive Network-based Fuzzy Inference System (ANFIS) model.

Keywords: ANFIS, MGT, prediction modeling, rail track degradation

Procedia PDF Downloads 335

Authors: Keiko Shimazu, Yasuhiro Maida, Tetsuya Sugata, Daisuke Tamakoshi, Kenji Makabe, Haruki Suzuki

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In this paper, we report how to acquire serious victims’ locations in the Acute Stage of Large-scale Disasters, in an Emergency Information Network System designed by us. The background of our concept is based on the Great East Japan Earthquake occurred on March 11^th, 2011. Through many experiences of national crises caused by earthquakes and tsunamis, we have established advanced communication systems and advanced disaster medical response systems. However, Japan was devastated by huge tsunamis swept a vast area of Tohoku causing a complete breakdown of all the infrastructures including telecommunications. Therefore, we noticed that we need interdisciplinary collaboration between science of disaster medicine, regional administrative sociology, satellite communication technology and systems engineering experts. Communication of emergency information was limited causing a serious delay in the initial rescue and medical operation. For the emergency rescue and medical operations, the most important thing is to identify the number of casualties, their locations and status and to dispatch doctors and rescue workers from multiple organizations. In the case of the Tohoku earthquake, the dispatching mechanism and/or decision support system did not exist to allocate the appropriate number of doctors and locate disaster victims. Even though the doctors and rescue workers from multiple government organizations have their own dedicated communication system, the systems are not interoperable.

Keywords: crisis management, disaster mitigation, messing, MGRS, military grid reference system, satellite communication system

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Authors: Paolo Grazioli

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In this paper, we present the main results achieved during an eight-week international design project on Colorado Future Sustainable Mobilitycarried out at Metropolitan State University of Denver. The project was born with the intention to seize the opportunity created by the Colorado government’s plan to promote e-bikes mobility by creating a large network of dedicated tracks. The project was supported by local entrepreneurs who offered financial and professional support. The main goal of the project was to engage design students with the skills to design a user-centered, original vehicle that would satisfy the unarticulated practical and emotional needs of “Gen Z” users by creating a fun, useful, and reliablelife companion that would helps users carry out their everyday tasks in a practical and enjoyable way. The project was carried out with the intention of proving the importance of the combination of creative methods with practical design methodologies towards the creation of an innovative yet immediately manufacturable product for a more sustainable future. The final results demonstrate the students' capability to create innovative and yet manufacturable products and, especially, their ability to create a new design paradigm for future sustainable mobility products. The design solutions explored n the project include collaborative learning and human-interaction design for future mobility. The findings of the research led students to the fabrication of two working prototypes that will be tested in Colorado and developed for manufacturing in the year 2024. The project showed that collaborative design and project-based teaching improve the quality of the outcome and can lead to the creation of real life, innovative products directly from the classroom to the market.

Keywords: sustainable transportation design, interface design, collaborative design, user -centered design research, design prototyping

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Authors: Mahshid Arabi

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In recent years, remarkable advancements in the fields of artificial intelligence and machine learning have led to the development of facial recognition technologies. These technologies are now employed in a wide range of applications, including security, surveillance, healthcare, and education. In the field of education, the identification of university entrance exam candidates has been one of the fundamental challenges. Traditional methods such as using ID cards and handwritten signatures are not only inefficient and prone to fraud but also susceptible to errors. In this context, utilizing advanced technologies like facial recognition can be an effective and efficient solution to increase the accuracy and reliability of identity verification in entrance exams. This article examines the use of FaceMatch software for recognizing the faces of university entrance exam candidates in Iran. The main objective of this research is to evaluate the efficiency and accuracy of FaceMatch software in identifying university entrance exam candidates to prevent fraud and ensure the authenticity of individuals' identities. Additionally, this research investigates the advantages and challenges of using this technology in Iran's educational systems. This research was conducted using an experimental method and random sampling. In this study, 1000 university entrance exam candidates in Iran were selected as samples. The facial images of these candidates were processed and analyzed using FaceMatch software. The software's accuracy and efficiency were evaluated using various metrics, including accuracy rate, error rate, and processing time. The research results indicated that FaceMatch software could accurately identify candidates with a precision of 98.5%. The software's error rate was less than 1.5%, demonstrating its high efficiency in facial recognition. Additionally, the average processing time for each candidate's image was less than 2 seconds, indicating the software's high efficiency. Statistical evaluation of the results using precise statistical tests, including analysis of variance (ANOVA) and t-test, showed that the observed differences were significant, and the software's accuracy in identity verification is high. The findings of this research suggest that FaceMatch software can be effectively used as a tool for identifying university entrance exam candidates in Iran. This technology not only enhances security and prevents fraud but also simplifies and streamlines the exam administration process. However, challenges such as preserving candidates' privacy and the costs of implementation must also be considered. The use of facial recognition technology with FaceMatch software in Iran's educational systems can be an effective solution for preventing fraud and ensuring the authenticity of university entrance exam candidates' identities. Given the promising results of this research, it is recommended that this technology be more widely implemented and utilized in the country's educational systems.

Keywords: facial recognition, FaceMatch software, Iran, university entrance exam

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Authors: Gizem Eser Erdek

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This study is research on predicting the remaining life of industrial cutting tools used in the industrial production process with deep learning methods. When the life of cutting tools decreases, they cause destruction to the raw material they are processing. This study it is aimed to predict the remaining life of the cutting tool based on the damage caused by the cutting tools to the raw material. For this, hole photos were collected from the hole-drilling machine for 8 months. Photos were labeled in 5 classes according to hole quality. In this way, the problem was transformed into a classification problem. Using the prepared data set, a model was created with convolutional neural networks, which is a deep learning method. In addition, VGGNet and ResNet architectures, which have been successful in the literature, have been tested on the data set. A hybrid model using convolutional neural networks and support vector machines is also used for comparison. When all models are compared, it has been determined that the model in which convolutional neural networks are used gives successful results of a %74 accuracy rate. In the preliminary studies, the data set was arranged to include only the best and worst classes, and the study gave ~93% accuracy when the binary classification model was applied. The results of this study showed that the remaining life of the cutting tools could be predicted by deep learning methods based on the damage to the raw material. Experiments have proven that deep learning methods can be used as an alternative for cutting tool life estimation.

Keywords: classification, convolutional neural network, deep learning, remaining life of industrial cutting tools, ResNet, support vector machine, VggNet

Procedia PDF Downloads 76