Search results for: streaming platforms

Authors: Sopio Totibadze

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Although the legal framework of Georgia reflects the main principles of gender equality and is in line with the international situation, Georgia remains a male-dominated society. This means that men prevail in many areas of social, economic, and political life, which frequently gives women a subordinate status in society and the family. According to the latest studies, “violence against women and girls in Georgia is also recognized as a public problem, and it is necessary to focus on it”. Moreover, the Public Defender's report (2019) reveals that “in the last five years, 151 women were killed in Georgia due to gender and family violence”. Unfortunately, there are frequent cases of crimes based on gender-based oppression in Georgia, which pose a threat not only to women but also to people of any gender whose desires and aspirations do not correspond to the gender norms and roles prevailing in society. It is well-known that language is often used as a tool for gender oppression. Therefore, feminist and gender studies in linguistics ultimately serve to represent the problem, reflect on it, and propose ways to solve it. Together with technical advancement in communication, a new form of discrimination has arisen- hate language against women in electronic media discourse. Due to the nature of social media and the internet, messages containing hate language can spread in seconds and reach millions of people. However, only a few know about the detrimental effects they may have on the addressee and society. This paper aims to analyse the hateful comments directed at women on various media platforms to determine the linguistic strategies used while attacking women and the reasons why women may fall victim to this type of hate language. The data have been collected over six months, and overall, 500 comments will be examined for the paper. Qualitative and quantitative analysis was chosen for the methodology of the study. The comments posted on various media platforms have been selected manually due to several reasons, the most important being the problem of identifying hate speech as it can disguise itself in different ways- humour, memes, etc. The comments on the articles, posts, pictures, and videos selected for sociolinguistic analysis depict a woman, a taboo topic, or a scandalous event centred on a woman that triggered hate language towards the person to whom the post/article was dedicated. The study has revealed that a woman can become a victim of hatred directed at them if they do something considered to be a deviation from a societal norm, namely, get a divorce, be sexually active, be vocal about feministic values, and talk about taboos. Interestingly, people who utilize hate language are not only men trying to “normalize” the prejudiced patriarchal values but also women who are equally active in bringing down a "strong" woman. The paper also aims to raise awareness about the hate language directed at women, as being knowledgeable about the issue at hand is the first step to tackling it.

Keywords: femicide, hate language, media discourse, sociolinguistics

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Authors: Yung-Chung Chuang

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Current situation and accumulated development of archaeological sites have very high impacts on the preservation value of the site. This research set 3 archaeological sites in Taiwan as study areas. Assessment of the degree of destruction of cultural layers due to land use change and geomorphological change were conducted with aerial photographs (1976-1978; 2016-2017) and digital aerial survey technology on 2D and 3D geographic information system platforms. The results showed that the archaeological sites were all seriously influenced due to the high land use intensity between 1976-2017. Geomorphological changes caused by human cultivation and engineering construction were main causes of site destruction, especially in private lands. Therefore, urban planning methods for land acquisition or land regulation are necessary.

Keywords: archaeological sites, accumulated development, destruction of cultural layers, geomorphological changes

Procedia PDF Downloads 182

Authors: Zhang Tianping, Jia Yanhui, Li Juan, Yang Le, Yang Hao, Yang Wei, Sun Xiaojing, Shi Kai, Li Xingda, Sun Yunkui

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Lanzhou Institute of Physics (LIP) is the major supplier of electric propulsion subsystems for Chinese satellite platforms. The development statuses of these electric propulsion subsystems were summarized including the LIPS-200 ion electric propulsion subsystem (IEPS) for DFH-3B platform, the LIPS-300 IEPS for DFH-5 and DFH-4SP platform, the LIPS-200+ IEPS for DFH-4E platform and near-earth asteroid exploration spacecraft, the LIPS-100 IEPS for small satellite platform, the LHT-100 hall electric propulsion subsystem (HEPS) for flight test on XY-2 satellite, the LHT-140 HEPS for large LEO spacecraft, the LIPS-400 IEPS for deep space exploration mission and other EPS for other Chinese spacecraft.

Keywords: ion electric propulsion, hall electric propulsion, satellite platform, LIP

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Authors: Alono Thorie, Ananya Mukhopadhyay

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Ooid bearing horizons of the Proterozoic Kunihar Formation, Simla Group, Lesser Himalaya have been addressed in the present work. The study is concentrated around the outskirts of Arki town, Solan district, Himachal Pradesh, India. Based on the sedimentary facies associations, the processes that promote the formation of ooids have been documented. The facies associations that have been recorded are: (i) Oolitic-Intraclastic grainstone (FA1), (ii) Oolitic grainstone (FA2), (iii) Boundstone (FA3), (iv) Dolomudstone (FA4) and (v) Rudstone (FA5). Oolitic-Intraclastic grainstone (FA1) mainly consists of well sorted ooids with concentric laminae and intraclasts. Large ooids with grain sizes more than 4 mm are characteristic of oolites throughout the area. Normally graded beds consisting of ooids and intraclasts are frequently documented in storm sediments in shelf environments and carbonate platforms. The well-sorted grainstone fabric indicates deposition in a high-energy shoal with tidal currents and storm reworking. FA2 comprises spherical to elliptical grains up to 8.5cm in size with concentric cortex and micritic nuclei. Peloids in FA2 are elliptical, rounded objects <0.3 mm in size. FA1 and FA2 have been recorded alongside boundstones (FA3) comprising stromatolites having columnar, wavy and domal morphology. Boundstones (FA3) reflect microbial growth in carbonate platforms and reefs. Dolomudstones (FA4) interbedded with cross laminated sandstones and erosional surfaces reflect sedimentation in storm dominated zones below fair-weather wave base. Rudstone (FA5) is composed of oolitic grainstone (FA2), boundstone (FA3) and dolomudstone (FA4). These clasts are few mm to more than 10 cm in length. Rudstones indicate deposition along a slope with intermittent influence of wave currents and storm activities. Most ooids from the Kunihar Formation are regular ooids with abundance of broken ooids. Compound and concentric ooids indicating medium to low energy environments are present but scarce. Ooids from high energy domains are more dominant than ooids developed from low energy environments. The unusually large size of the Kunihar ooids (more than 8.5 cm) is rare in the geological record. Development of carbonate deposits such as oolitic- intraclastic Grainstones (FA1), oolitic grainstones (FA2) and rudstones (FA5), and reflect deposition in an agitated beach environment with abundant microbial activity and high energy shallow marine waters influenced by tide, wave and storm currents. Occurrences of boundstone (FA4) or stromatolitic carbonate amongst oolitic facies (FA1 and FA2) and appearance of compound and concentric ooids indicate intervals of calm in between agitated phases of storm, wave and tidal activities.

Keywords: proterozoic, Simla Group, ooids, stromatolites

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Authors: Peter E. Egielewa

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Communication through the smartphone connects people globally. However, since the last 10 years, there has been an increasing shift from the social engagement in the family to the digital mediated communication aided by the smartphone. The traditional family communication had largely been oral and relational, which the smartphone is now digitally mediating. The study employs mixed research method of quantitative and qualitative research design and deploys questionnaire to elicit responses from both parents and children of 50 purposively selected families from five villages in Southern Nigeria that are very active with smartphone use. Based on the Theory of Family Systems, preliminary findings show that the smartphone is becoming an addiction among Nigerian family members and has shifted the dynamics of family communication from relational to digital culture. The research concludes that smartphone use affects family communication negatively and recommends the moderation of smartphone use in the family and the search for alternative platforms for family communication that minimises smartphone addiction.

Keywords: digital, distorted communication, family, Nigeria, smartphone

Procedia PDF Downloads 108

Authors: Elham Farahmand, Fatimah Ibrahim, Samira Hosseini, Ivan Djordjevic, Leo. H. Koole

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Compositions of different molar ratios of polymethylmethacrylate-co-methacrylic acid (PMMA-co-MAA) were synthesized via free- radical polymerization. Polymer coated surfaces have been produced on silicon wafers. Coated samples were analyzed by atomic force microscopy (AFM). The results have shown that the roughness of the surfaces have increased by increasing the molar ratio of monomer methacrylic acid (MAA). This study reveals that the gradual increase in surface roughness is due to the fact that carboxylic functional groups have been generated by MAA segments. Such surfaces can be desirable platforms for fabrication of the biosensors for detection of the viruses and diseases.

Keywords: polymethylmethacrylate-co-methacrylic acid (PMMA-co-MAA), polymeric material, atomic force microscopy, roughness, carboxylic functional groups

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Authors: Lam Hong Lan

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The textile industry is said to be the second-largest polluter, responsible for 92 million tonnes of waste annually. There is an urgent need to practice the circular economy to increase the use and reuse around the world. By its nature, the pre-owned fashion business is considered part of the circular economy as it helps to eliminate waste and circulate products. Second-hand clothes and accessories used to be associated with a ‘cheap image’ that carried ‘old energy’ in Vietnam. This perception has been shifted, especially amongst the younger generation. Vietnamese consumer is spending more on products and services that increase self-esteem. The same consumer is moving away from a collectivist social identity towards a ‘me, not we’ outlook as they look for a way to express their individual identity. And pre-owned fashion is one of their solutions as it values money, can create a unique personal style for the wearer and links with sustainability. The design of this study is based on the second-hand shopping motivation theory. A semi-structured online survey with 100 consumers from one pre-owned clothing community and one pre-owned e-commerce site in Vietnam. The findings show that in contrast with Vietnamese older consumers (55+yo) who, in the previous study, generally associated pre-owned fashion with ‘low-cost’, ‘cheap image’ that carried ‘old energy’, young customers (20-30 yo) were actively promoted their pre-owned fashion items to the public via outlet’s social platforms and their social media. This cultural shift comes from the impact of global and local discourse around sustainable fashion and the growth of digital platforms in the pre-owned fashion business in the last five years, which has generally supported wider interest in pre-owned fashion in Vietnam. It can be summarised in three areas: (1) global and local celebrity influencers. A number of celebrities have been photographed wearing vintage items in music videos, photoshoots or at red carpet events. (2) E-commerce and intermediaries. International e-commerce sites – e.g., Vinted, TheRealReal – and/or local apps – e.g., Re.Loved – can influence attitudes and behaviors towards pre-owned consumption. (3) Eco-awareness. The increased online coverage of climate change and environmental pollution has encouraged customers to adopt a more eco-friendly approach to their wardrobes. While sustainable biomaterials and designs are still navigating their way into sustainability, sustainable consumerism via pre-owned fashion seems to be an immediate solution to lengthen the clothes lifecycle. This study has found that young consumers are primarily seeking value for money and/or a unique personal style from pre-owned/vintage fashion while using these purchases to promote their own “eco-awareness” via their social media networks. This is a good indication for fashion designers to keep in mind in their design process and for fashion enterprises in their business model’s choice to not overproduce fashion items.

Keywords: cultural shift, pre-owned fashion, sustainable consumption, sustainable fashion.

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Authors: A. Nagaletchimee Annamalai

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The study investigated on how a small group of pre-service teachers and lecturers used social media to interact and collaborate to complete their tasks. The study is a qualitative case study that explored the lecturers’ reflections and pre-service teachers’ interviews. The lecturers were given the option to choose Facebook or any other social media as their teaching and learning platforms. However, certain guidelines based on were given to lecturers to conduct their teaching and learning activities. The findings revealed that although Facebook was a popular social networking site, it was not a preferred educational platform. Lecturers preferred to use WhatsApp, Canvas, and email. The focus group interview found positive and negative experiences of the pre-service teachers. The study suggested several pedagogical implications and importantly highlighted the need for changes in curriculum to ensure lecturers leverage the potential of technology in education.

Keywords: social media, interactions, collaboration, online learning environment

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Authors: Rattakorn Poonsuph

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Technological innovation plays a crucial role in virtual healthcare services. A growing number of telehealth platforms are concentrating on using digital tools to improve the quality and availability of care. As a result, telehealth represents an opportunity to redesign the way health services are delivered. The research objective is to discover a new business model for digital health services and related industries to participate with telehealth solutions. The business opportunity is valuable for healthcare investors as a startup company to further investigations or implement the telehealth platform. The paper presents a digital healthcare business model and business opportunities to related industries. These include digital healthcare services extending from a traditional business model and use cases of business opportunities to related industries. Although there are enormous business opportunities, telehealth is still challenging due to the patient adaption and digital transformation process within a healthcare organization.

Keywords: telehealth, Internet hospital, HealthTech, InsurTech

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Authors: Amon Olimov, Umarov Jamshid, Dae-Ho Kim, Chol-U Lee, Ryum-Duck Oh

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This paper proposes IoT virtualization platform based incident information system. IoT information based environment is the platform that was developed for the purpose of collecting a variety of data by managing regionally scattered IoT devices easily and conveniently in addition to analyzing data collected from roads. Moreover, this paper configured the platform for the purpose of providing incident information based on sensed data. It also provides the same input/output interface as UNIX and Linux by means of matching IoT devices with the directory of file system and also the files. In addition, it has a variety of approaches as to the devices. Thus, it can be applied to not only incident information but also other platforms. This paper proposes the incident information system that identifies and provides various data in real time as to urgent matters on roads based on the existing USN/M2M and IoT visualization platform.

Keywords: incident information system, IoT, virtualization platform, USN, M2M

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Authors: Martin Pumera

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Graphene materials are being widely used in electrochemistry due to their versatility and excellent properties as platforms for biosensing. Here we present current trends in the electrochemical biosensing of pesticides and other toxic compounds. We explore two fundamentally different designs, (i) using graphene and other 2-D nanomaterials as an electrochemical platform and (ii) using these nanomaterials in the laboratory on chip design, together with paramagnetic beads. More specifically: (i) We explore graphene as transducer platform with very good conductivity, large surface area, and fast heterogeneous electron transfer for the biosensing. We will present the comparison of these materials and of the immobilization techniques. (ii) We present use of the graphene in the laboratory on chip systems. Laboratory on the chip had a huge advantage due to small footprint, fast analysis times and sample handling. We will show the application of these systems for pesticide detection and detection of other toxic compounds.

Keywords: graphene, 2D nanomaterials, biosensing, chip design

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Authors: Tiera Tanksley, Amanda M. McLeroy

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The advent of technology and social media has ushered in a new era of communication, providing platforms for news dissemination and cause advocacy. However, this digital landscape has also exposed a distressing phenomenon termed "Black death," or trauma porn. This paper delves into the profound effects of repeated exposure to traumatic content on Black youth via social media, exploring the psychological impacts and potential reinforcing of stereotypes. Employing Critical Race Technology Theory (CRTT), the study sheds light on algorithmic anti-blackness and its influence on Black youth's lives and educational experiences. Through ethnographic content analysis, the research investigates common manifestations of Black death encountered online by Black adolescents. Findings unveil distressing viral videos, traumatic images, racial slurs, and hate speech, perpetuating stereotypes. However, amidst the distress, the study identifies narratives of activism and social justice on social media platforms, empowering Black youth to engage in positive change. Coping mechanisms and community support emerge as significant factors in navigating the digital landscape. The study underscores the need for comprehensive interventions and policies informed by evidence-based research. By addressing algorithmic anti-blackness and promoting digital resilience, the paper advocates for a more empathetic and inclusive online environment. Understanding coping mechanisms and community support becomes imperative for fostering mental well-being among Black adolescents navigating social media. In education, the implications are substantial. Acknowledging the impact of Black death content, educators play a pivotal role in promoting media literacy and digital resilience. Creating inclusive and safe online spaces, educators can mitigate negative effects and encourage open discussions about traumatic content. The application of CRTT in educational technology emphasizes dismantling systemic biases and promoting equity. In conclusion, this study calls for educators to be cognizant of the impact of Black death content on social media. By prioritizing media literacy, fostering digital resilience, and advocating for unbiased technologies, educators contribute to an inclusive and just educational environment for all students, irrespective of their race or background. Addressing challenges related to Black death content proactively ensures the well-being and mental health of Black adolescents, fostering an empathetic and inclusive digital space.

Keywords: algorithmic anti-Blackness, digital resilience, media literacy, traumatic content

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Authors: Igor A. Podgorny

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TurboTax AnswerXchange is a social Q/A system supporting users working on federal and state tax returns. Content quality and popularity in the AnswerXchange can be predicted with propensity models using attributes of the question and answer. Using uplift modeling, we identify features of questions and answers that can be modified during the question-asking and question-answering experience in order to optimize the AnswerXchange content quality. We demonstrate that adding details to the questions always results in increased question popularity that can be used to promote good quality content. Responding to close-ended questions assertively improve content quality in the AnswerXchange in 90% of cases. Answering knowledge questions with web links increases the likelihood of receiving a negative vote from 60% of the askers. Our findings provide a rationale for employing the uplift modeling approach for AnswerXchange operations.

Keywords: customer relationship management, human-machine interaction, text mining, uplift modeling

Procedia PDF Downloads 228

Authors: Gaye Senbag

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In English language teaching, feedback is considered as one of the main components of writing instruction. Teachers put a lot of time and effort in order to provide learners with written feedback for effective language learning. At Anadolu University School of Foreign Languages (AUSFL) students are given written feedback for their each piece of writing through online platforms such as Edmodo and Turnitin, and traditional methods. However, little is known regarding how learners value and respond to teacher-provided feedback. As the perceptions of the students remarkably affect their learning, this study examines how they perceive the effectiveness of feedback provided by the teacher. Aiming to analyse it, 30 intermediate level (B1+ CEFR level) students were given a questionnaire, which includes Likert scale questions. The results will be discussed in detail.

Keywords: feedback, perceptions, writing, English Language Teaching (ELT)

Procedia PDF Downloads 218

Authors: Adriana Piatti-Crocker

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Drawing on archival documentation, digital platforms, academic journals, and reports, this research will explore the diffusion of a protest movement in Latin America. Starting in Argentina in 2015, this paper will explain how the hashtag #NiUnaMenos (“Not One Woman Less”), created to combat violence against women and girls, led to the spread of a regionwide movement. A year after its introduction, hundreds of thousands of activists mobilized on the streets of major cities in Latin America. Movements arose to protest against specific circumstances and contexts under the hashtag #NiUnaMenos, but the main goal of all of these protests was to fight against misogynist violence. Moreover, unlike previous social movements, the use of social media, such as Facebook, Instagram, Whatsapp, and Twitter, changed the depth and scope of these protests and led to an unprecedented speed in helping transmit their messages, strategies, identities, and goals.

Keywords: social protests, #NiUnaMenos ( Not one woman less), diffusion of social protests, protests and mysoginist violence

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Authors: Faiza Mahi, Fatima Debbat, Mohamed Fayçal Khelfi

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This paper proposes a control approach using Fuzzy Lo system. More precisely, the study focuses on the improvement of users service in terms of analysis and control of a transportation system their waiting times in the exchange platforms of passengers. Many studies have been developed in the literature for such problematic, and many control tools are proposed. In this paper we focus on the use of fuzzy logic technique to control the system during its evolution in order to minimize the arrival gap of connected transportation means at the exchange points of passengers. An example of illustration is worked out and the obtained results are reported. an important area of research is the modeling and simulation ordering system. We describe an approach to analysis using Fuzzy Logic. The hybrid simulator developed in toolbox Matlab consists calculation of waiting time transportation mode.

Keywords: Fuzzy logic, Hybrid system, Waiting Time, Transportation system, Control

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Authors: Haytam Kasem

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The problem of quick and easy reversible attachment has become of great importance in different fields of technology. For the reason, during the last decade, a new emerging field of adhesion science has been developed. Essentially inspired by some animals and insects, which during their natural evolution have developed fantastic biological attachment systems allowing them to adhere and run on walls and ceilings of uneven surfaces. Potential applications of engineering bio-inspired solutions include climbing robots, handling systems for wafers in nanofabrication facilities, and mobile sensor platforms, to name a few. However, despite the efforts provided to apply bio-inspired patterned adhesive-surfaces to the biomedical field, they are still in the early stages compared with their conventional uses in other industries mentioned above. In fact, there are some critical issues that still need to be addressed for the wide usage of the bio-inspired patterned surfaces as advanced biomedical platforms. For example, surface durability and long-term stability of surfaces with high adhesive capacity should be improved, but also the friction and adhesion capacities of these bio-inspired microstructures when contacting rough surfaces. One of the well-known prototypes for bio-inspired attachment systems is biomimetic wall-shaped hierarchical microstructure for gecko-like attachments. Although physical background of these attachment systems is widely understood, the influence of counter-face roughness and its relationship with the friction force generated when sliding against wall-shaped hierarchical microstructure have yet to be fully analyzed and understood. To elucidate the effect of the counter-face roughness on the friction of biomimetic wall-shaped hierarchical microstructure we have replicated the isotropic topography of 12 different surfaces using replicas made of the same epoxy material. The different counter-faces were fully characterized under 3D optical profilometer to measure roughness parameters. The friction forces generated by spatula-shaped microstructure in contact with the tested counter-faces were measured on a home-made tribometer and compared with the friction forces generated by the spatulae in contact with a smooth reference. It was found that classical roughness parameters, such as average roughness Ra and others, could not be utilized to explain topography-related variation in friction force. This has led us to the development of an integrated roughness parameter obtained by combining different parameters which are the mean asperity radius of curvature (R), the asperity density (η), the deviation of asperities high (σ) and the mean asperities angle (SDQ). This new integrated parameter is capable of explaining the variation of results of friction measurements. Based on the experimental results, we developed and validated an analytical model to predict the variation of the friction force as a function of roughness parameters of the counter-face and the applied normal load, as well.

Keywords: friction, bio-mimetic micro-structure, counter-face roughness, analytical model

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Authors: Alex Ellery

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Geoengineering approaches to climate change mitigation are unpopular and regarded with suspicion. Of these, space-based approaches are regarded as unworkable and enormously costly. Here, a space-based approach is presented that is modest in cost, fully controllable and reversible, and acts as a natural spur to the development of solar power satellites over the longer term as a clean source of energy. The low-cost approach exploits self-replication technology which it is proposed may be enabled by 3D printing technology. Self-replication of 3D printing platforms will enable mass production of simple spacecraft units. Key elements being developed are 3D-printable electric motors and 3D-printable vacuum tube-based electronics. The power of such technologies will open up enormous possibilities at low cost including space-based geoengineering.

Keywords: 3D printing, in-situ resource utilization, self-replication technology, space-based geoengineering

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Authors: Nino Grigolaia

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The paper discusses the importance of the development of the gig economy in the economy of Georgia, analyzes the trends of the development of the gig economy, and identifies the main challenges in this field. Objective. The objective of the study is to assess the role of the gig economy, identify the main challenges and develop recommendations. Methodologies. Analysis, synthesis, comparison, induction and other methods are used; A desk study has been conducted. Findings. The advantages and disadvantages of the gig economy are identified, and the impact of the changes caused by the development of the gig economy on labor relations and employment is determined. It is argued that the ongoing technological changes have led to the emergence of new global trends in the labor market and increased the inequality of income distribution. Conclusions. Based on the analysis of the gig economy in the world and in Georgia, relevant recommendations are proposed, namely: establishing a new system of regulating the incomes of employees in this field, developing a real social protection mechanism, Development of political and legal instruments for regulation of gig economy and others.

Keywords: gig economy, economy of Georgia, digital platforms, labor relations

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Authors: Aydin Teymourifar, Gurkan Ozturk

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In this paper, a hybrid distributed algorithm has been suggested for the multi-objective job shop scheduling problem. Many new approaches are used at design steps of the distributed algorithm. Co-evolutionary structure of the algorithm and competition between different communicated hybrid algorithms, which are executed simultaneously, causes to efficient search. Using several machines for distributing the algorithms, at the iteration and solution levels, increases computational speed. The proposed algorithm is able to find the Pareto solutions of the big problems in shorter time than other algorithm in the literature. Apache Spark and Hadoop platforms have been used for the distribution of the algorithm. The suggested algorithm and implementations have been compared with results of the successful algorithms in the literature. Results prove the efficiency and high speed of the algorithm.

Keywords: distributed algorithms, Apache Spark, Hadoop, job shop scheduling, multi-objective optimization

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Authors: Shivani Singh, Shantanu Nakhare, Kalyani Nair, Rohan Shetty

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As social networking is growing at a rapid pace today it is vital that we work on improving its management. Research has shown that the content present in online social networks may have significant influence on impressionable minds. If such platforms are misused, it will lead to negative consequences. Detecting insults or inappropriate messages continues to be one of the most challenging aspects of Online Social Networks (OSNs) today. We address this problem through a Machine Learning Based Soft Text Classifier approach using Support Vector Machine algorithm. The proposed system acts as a screening mechanism the alerts the user about such messages. The messages are classified according to their subject matter and each comment is labeled for the presence of profanity and insults.

Keywords: machine learning, online social networks, soft text classifier, support vector machine

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Authors: Yiea Funk Te, Daniel Mueller, Irena Pletikosa Cvijikj

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Small and medium enterprises (SMEs) play an important role in the economy of many countries. When the overall world economy is considered, SMEs represent 95% of all businesses in the world, accounting for 66% of the total employment. Existing studies show that the current business environment is characterized as highly turbulent and strongly influenced by modern information and communication technologies, thus forcing SMEs to experience more severe challenges in maintaining their existence and expanding their business. To support SMEs at improving their competitiveness, researchers recently turned their focus on applying data mining techniques to build risk and growth prediction models. However, data used to assess risk and growth indicators is primarily obtained via questionnaires, which is very laborious and time-consuming, or is provided by financial institutes, thus highly sensitive to privacy issues. Recently, web mining (WM) has emerged as a new approach towards obtaining valuable insights in the business world. WM enables automatic and large scale collection and analysis of potentially valuable data from various online platforms, including companies’ websites. While WM methods have been frequently studied to anticipate growth of sales volume for e-commerce platforms, their application for assessment of SME risk and growth indicators is still scarce. Considering that a vast proportion of SMEs own a website, WM bears a great potential in revealing valuable information hidden in SME websites, which can further be used to understand SME risk and growth indicators, as well as to enhance current SME risk and growth prediction models. This study aims at developing an automated system to collect business-relevant data from the Web and predict future growth trends of SMEs by means of WM and data mining techniques. The envisioned system should serve as an 'early recognition system' for future growth opportunities. In an initial step, we examine how structured and semi-structured Web data in governmental or SME websites can be used to explain the success of SMEs. WM methods are applied to extract Web data in a form of additional input features for the growth prediction model. The data on SMEs provided by a large Swiss insurance company is used as ground truth data (i.e. growth-labeled data) to train the growth prediction model. Different machine learning classification algorithms such as the Support Vector Machine, Random Forest and Artificial Neural Network are applied and compared, with the goal to optimize the prediction performance. The results are compared to those from previous studies, in order to assess the contribution of growth indicators retrieved from the Web for increasing the predictive power of the model.

Keywords: data mining, SME growth, success factors, web mining

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Authors: Norman Sinnigen, Igor Izyurov, Marina Krylova, Hamidreza Jamalabadi, Sarah Alizadeh, Martin Walter

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Background: EEG is a non-invasive brain activity recording technique with a high temporal resolution that allows the use of real-time applications, such as neurofeedback. However, EEG data are susceptible to electrooculographic (EOG) and electromyography (EMG) artifacts (i.e., jaw clenching, teeth squeezing and forehead movements). Due to their non-stationary nature, these artifacts greatly obscure the information and power spectrum of EEG signals. Many EEG artifact correction methods are too time-consuming when applied to low-density EEG and have been focusing on offline processing or handling one single type of EEG artifact. A software-only real-time method for correcting multiple types of EEG artifacts of high-density EEG remains a significant challenge. Methods: We demonstrate an improved approach for automatic real-time EEG artifact correction of EOG and EMG artifacts. The method was tested on three healthy subjects using 64 EEG channels (Brain Products GmbH) and a sampling rate of 1,000 Hz. Captured EEG signals were imported in MATLAB with the lab streaming layer interface allowing buffering of EEG data. EMG artifacts were detected by channel variance and adaptive thresholding and corrected by using channel interpolation. Real-time independent component analysis (ICA) was applied for correcting EOG artifacts. Results: Our results demonstrate that the algorithm effectively reduces EMG artifacts, such as jaw clenching, teeth squeezing and forehead movements, and EOG artifacts (horizontal and vertical eye movements) of high-density EEG while preserving brain neuronal activity information. The average computation time of EOG and EMG artifact correction for 80 s (80,000 data points) 64-channel data is 300 – 700 ms depending on the convergence of ICA and the type and intensity of the artifact. Conclusion: An automatic EEG artifact correction algorithm based on channel variance, adaptive thresholding, and ICA improves high-density EEG recordings contaminated with EOG and EMG artifacts in real-time.

Keywords: EEG, muscle artifacts, ocular artifacts, real-time artifact correction, real-time ICA

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Authors: Pei-Chun Lee, Sheng-Shih Wang

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This paper presents a route guidance system for car owners to find their cars in parking garages. The presents system comprises a positioning-assisting subsystem and a car-finding mobile app. The positioning-assisting subsystem mainly uses the iBeacon technology for indoor positioning. The car-finding mobile app guides car owners to their cars based on a non-map navigation strategy. This study also designs a virtual coordinate system to support identifying the locations of parking spaces and iBeacon devices. We use Arduino and Android as the platforms to implement the proposed positioning-assisting subsystem and car-finding mobile app, respectively. We have also deployed the system in a parking garage in our campus for testing. Experimental results verify that our system can efficiently and correctly guide car owners to the parking spaces of their cars.

Keywords: guidance, iBeacon, mobile app, navigation

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Authors: Wided Batita, Stéphane Roche, Claude Caron

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Geodesign is an emergent term related to a new and complex process. Hence, it needs to rethink tools, technologies and platforms in order to efficiently achieve its goals. A few tools have emerged since 2010 such as CommunityViz, GeoPlanner, etc. In the era of Web 2.0 and collaboration, WikiGIS has been proposed as a new category of tools. In this paper, we present WikiGIS functionalities dealing mainly with the iteration and traceability management to support the collaboration of the Geodesign process. Actually, WikiGIS is built on GeoWeb 2.0 technologies —and primarily on wiki— and aims at managing the tracking of participants’ editing. This paper focuses on a simplified simulation to illustrate the strength of WikiGIS in the management of traceability and in the access to history in a Geodesign process. Indeed, a cartographic user interface has been implemented, and then a hypothetical use case has been imagined as proof of concept.

Keywords: geodesign, history, traceability, tracking of participants’ editing, WikiGIS

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Authors: Sam Ng, Lewis Leighton, Sam Atkinson, Carson Yan, Landan Hu, Leslie Cheung, Brian Yap, Kent Lung, Ketat Sarakune

Abstract:

This paper introduces a method for verifying cryptocurrency reserves that balances the need for both transparency and data confidentiality. Our methodology employs cryptographic techniques, including Merkle Trees, Bulletproof, and zkSnark, to verify that total assets equal or exceed total liabilities, represented by customer funds. Importantly, this verification is achieved without disclosing sensitive information such as the total asset value, customer count, or cold wallet addresses. We delve into the construction and implementation of this methodology. While the system is robust and scalable, we also identify areas for potential enhancements to improve its efficiency and versatility. As the digital asset landscape continues to evolve, our approach provides a solid foundation for ensuring continued trust and security in digital asset platforms.

Keywords: cryptocurrency, crypto-currency, proof-of-reserve, por, zero-knowledge, ZKP

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Authors: Tai Nguyen, Minh Bui, Huong Ninh, Tu Nguyen, Hai Tran

Abstract:

GraphCut algorithm has been widely utilized to solve various types of computer vision problems. Its expensive computational cost encouraged many researchers to improve the speed of the algorithm. Recent works proposed schemes that work on parallel computing platforms such as CUDA. However, the problem of low convergence speed prevents the usage of GraphCut for real time applications. In this paper, we propose global suppression heuristic to boost the conver-gence process of the algorithm. A parallel implementation of GraphCut algorithm on CUDA designed for the image stitching problem is introduced. Our method achieves up to 3× time boost on the graph of size 80 × 480 compared to the best sequential GraphCut algorithm while achieving satisfactory stitched images, suitable for panorama applications. Our source code will be soon available for further research.

Keywords: CUDA, graph cut, image stitching, texture synthesis, maxflow/mincut algorithm

Procedia PDF Downloads 100

Authors: Sunho Seo, Younghwan Shin, Jong-Hong Park, Sooeun Song, Junsung Kim, Jusik Yun, Yongkyun Kim, Jong-Moon Chung

Abstract:

In order to effectively cope with large and complex disasters, disaster response training is needed. Recently, disaster response training led by the ROK (Republic of Korea) government is being implemented through a 4 year R&D project, which has several similar functions as the HSEEP (Homeland Security Exercise and Evaluation Program) of the United States, but also has several different features as well. Due to the unpredictiveness and diversity of disasters, existing training methods have many limitations in providing experience in the efficient use of disaster incident response and recovery resources. Always, the challenge is to be as efficient and effective as possible using the limited human and material/physical resources available based on the given time and environmental circumstances. To enable repeated training under diverse scenarios, an AR (Augmented Reality) and VR (Virtual Reality) combined simulator is under development. Unlike existing disaster response training, simulator based training (that allows remote login simultaneous multi-user training) enables freedom from limitations in time and space constraints, and can be repeatedly trained with different combinations of functions and disaster situations. There are related systems such as ADMS (Advanced Disaster Management Simulator) developed by ETC simulation and HLS2 (Homeland Security Simulation System) developed by ELBIT system. However, the ROK government needs a simulator custom made to the country's environment and disaster types, and also combines the latest information and communication technologies, which include AR, VR, and MPEG-DASH (Moving Picture Experts Group - Dynamic Adaptive Streaming over HTTP) technology. In this paper, a new disaster response training simulator is proposed to overcome the limitation of existing training systems, and adapted to actual disaster situations in the ROK, where several technical features are described.

Keywords: augmented reality, emergency response training simulator, MPEG-DASH, virtual reality

Procedia PDF Downloads 276

Authors: Gayathri Nagarajan, L. D. Dhinesh Babu

Abstract:

Health care is one of the prominent industries that generate voluminous data thereby finding the need of machine learning techniques with big data solutions for efficient processing and prediction. Missing data, incomplete data, real time streaming data, sensitive data, privacy, heterogeneity are few of the common challenges to be addressed for efficient processing and mining of health care data. In comparison with other applications, accuracy and fast processing are of higher importance for health care applications as they are related to the human life directly. Though there are many machine learning techniques and big data solutions used for efficient processing and prediction in health care data, different techniques and different frameworks are proved to be effective for different applications largely depending on the characteristics of the datasets. In this paper, we present a framework that uses ensemble machine learning technique gradient boosted trees for data classification in health care big data. The framework is built on Spark platform which is fast in comparison with other traditional frameworks. Unlike other works that focus on a single technique, our work presents a comparison of six different machine learning techniques along with gradient boosted trees on datasets of different characteristics. Five benchmark health care datasets are considered for experimentation, and the results of different machine learning techniques are discussed in comparison with gradient boosted trees. The metric chosen for comparison is misclassification error rate and the run time of the algorithms. The goal of this paper is to i) Compare the performance of gradient boosted trees with other machine learning techniques in Spark platform specifically for health care big data and ii) Discuss the results from the experiments conducted on datasets of different characteristics thereby drawing inference and conclusion. The experimental results show that the accuracy is largely dependent on the characteristics of the datasets for other machine learning techniques whereas gradient boosting trees yields reasonably stable results in terms of accuracy without largely depending on the dataset characteristics.

Keywords: big data analytics, ensemble machine learning, gradient boosted trees, Spark platform

Procedia PDF Downloads 219

Authors: Xuefan Li, Donghua Li, Juanjuan Li

Abstract:

This study explores the changes in policies toward Chinese students studying abroad in different countries during the pre-pandemic, pandemic, and post-pandemic periods. Interviews and questionnaire surveys were conducted with participating institutions at the China International Education Exhibition. The results indicate that institutions were impacted by the pandemic differently, with a gradual recovery in the two years following the initial outbreak. Institutions encourage and support Chinese students to resume offline studies during the post-pandemic period. The impact of the pandemic on the recruitment of Chinese students by international institutions varied, with different measures being adopted by different institutions. Compared with universities, colleges were more affected in terms of student employment rates. Some institutions were able to respond quickly and effectively to the pandemic due to their online teaching platforms. Overall, this study is expected to provide insights into the changes in policies toward Chinese students studying abroad during the pandemic and highlights the diverse responses of international institutions.

Keywords: international education, Chinese international education, COVID-19 pandemic, international institutions

Procedia PDF Downloads 59