Search results for: online dispute resolution systems

Authors: Abul Bashar

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The recent surge in the adoption of cloud computing systems by various organizations has brought forth the challenge of evaluating their performance. One of the major issues faced by the cloud service providers and customers is to assess the ability of cloud computing systems to provide the desired services in accordance to the QoS and SLA constraints. To this end, an opportunity exists to develop means to ensure that the desired performance levels of such systems are met under simulated environments. This will eventually minimize the service disruptions and performance degradation issues during the commissioning and operational phase of cloud computing infrastructure. However, it is observed that several simulators and modelers are available for simulating the cloud computing systems. Therefore, this paper presents a critical evaluation of the state-of-the-art modeling and simulation frameworks applicable to cloud computing systems. It compares the prominent simulation frameworks in terms of the API features, programming flexibility, operating system requirements, supported services, licensing needs and popularity. Subsequently, it provides recommendations regarding the choice of the most appropriate framework for researchers, administrators and managers of cloud computing systems.

Keywords: cloud computing, modeling framework, performance evaluation, simulation tools

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Authors: Yuriy A. Shevchenko, Konstantin V. Nefedev

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We consider the antiferromagnetic systems of Ising spins located at the sites of the hexagonal, triangular and pyrochlore lattices. Such systems can be diluted to a certain concentration level by randomly replacing the magnetic spins with nonmagnetic ones. Quite recently we studied density of states (DOS) was calculated by the Wang-Landau method. Based on the obtained data, we calculated the dependence of the residual entropy (entropy at a temperature tending to zero) on the dilution concentration for quite large systems (more than 2000 spins). In the current study, we obtained the same data for small systems (less than 20 spins) by a complete search of all possible magnetic configurations and compared the result with the result for large systems. The shape of the curve remains unchanged in both cases, but the specific values of the residual entropy are different because of the finite size effect.

Keywords: entropy, pyrochlore, spin ice, Wang-Landau algorithm

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Authors: Kalthoum Riahi, Max T. Rietberg, Javier Perez y Perez, Corné Dijkstra, Bennie ten Haken, Lejla Alic

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Magnetic nanoparticles (MNPs) are widely used to facilitate magnetic particle imaging (MPI) which has the potential to become the leading diagnostic instrument for biomedical imaging. This comparative study assesses the effects of changing iron content and excitation frequency on point-spread function (PSF) representing the effect of magnetization reversal. PSF is quantified by features of interest for MPI: i.e., drive field amplitude and full-width-at-half-maximum (FWHM). A superparamagnetic quantifier (SPaQ) is used to assess differential magnetic susceptibility of two commercially available MNPs: Synomag®-D50 and Synomag®-D70. For both MNPs, the signal output depends on increase in drive field frequency and amount of iron-oxide, which might be hampering the sensitivity of MPI systems that perform on higher frequencies. Nevertheless, there is a clear potential of Synomag®-D for a stable MPI resolution, especially in case of 70 nm version, that is independent of either drive field frequency or amount of iron-oxide.

Keywords: magnetic nanoparticles, MNPs, differential magnetic susceptibility, DMS, magnetic particle imaging, MPI, magnetic relaxation, Synomag®-D

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Authors: Constanza A. Barriga, Rafael Bernardi, Amokrane Berdja, Christian D. Guzman

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Most image restoration methods in astronomy rely upon probabilistic tools that infer the best solution for a deconvolution problem. They achieve good performances when the point spread function (PSF) is spatially invariable in the image plane. However, this latter condition is not always satisfied with real optical systems. PSF angular variations cannot be evaluated directly from the observations, neither be corrected at a pixel resolution. We have developed a method for the restoration of images affected by static and anisotropic aberrations using deep neural networks that can be directly applied to sky images. The network is trained using simulated sky images corresponding to the T-80 telescope optical system, an 80 cm survey imager at Cerro Tololo (Chile), which are synthesized using a Zernike polynomial representation of the optical system. Once trained, the network can be used directly on sky images, outputting a corrected version of the image, which has a constant and known PSF across its field-of-view. The method was tested with the T-80 telescope, achieving better results than with PSF deconvolution techniques. We present the method and results on this telescope.

Keywords: aberrations, deep neural networks, image restoration, variable point spread function, wide field images

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Authors: Ali Kazemi

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The digital evolution of financial services, while offering unprecedented convenience and accessibility, has also escalated the vulnerabilities to fraudulent activities. In this study, we introduce a distinct approach to real-time anomaly detection in financial transactions, aiming to fortify the defenses of banking and financial institutions against such threats. Utilizing unsupervised machine learning algorithms, specifically autoencoders and isolation forests, our research focuses on identifying irregular patterns indicative of fraud within transactional data, thus enabling immediate action to prevent financial loss. The data we used in this study included the monetary value of each transaction. This is a crucial feature as fraudulent transactions may have distributions of different amounts than legitimate ones, such as timestamps indicating when transactions occurred. Analyzing transactions' temporal patterns can reveal anomalies (e.g., unusual activity in the middle of the night). Also, the sector or category of the merchant where the transaction occurred, such as retail, groceries, online services, etc. Specific categories may be more prone to fraud. Moreover, the type of payment used (e.g., credit, debit, online payment systems). Different payment methods have varying risk levels associated with fraud. This dataset, anonymized to ensure privacy, reflects a wide array of transactions typical of a global banking institution, ranging from small-scale retail purchases to large wire transfers, embodying the diverse nature of potentially fraudulent activities. By engineering features that capture the essence of transactions, including normalized amounts and encoded categorical variables, we tailor our data to enhance model sensitivity to anomalies. The autoencoder model leverages its reconstruction error mechanism to flag transactions that deviate significantly from the learned normal pattern, while the isolation forest identifies anomalies based on their susceptibility to isolation from the dataset's majority. Our experimental results, validated through techniques such as k-fold cross-validation, are evaluated using precision, recall, and the F1 score alongside the area under the receiver operating characteristic (ROC) curve. Our models achieved an F1 score of 0.85 and a ROC AUC of 0.93, indicating high accuracy in detecting fraudulent transactions without excessive false positives. This study contributes to the academic discourse on financial fraud detection and provides a practical framework for banking institutions seeking to implement real-time anomaly detection systems. By demonstrating the effectiveness of unsupervised learning techniques in a real-world context, our research offers a pathway to significantly reduce the incidence of financial fraud, thereby enhancing the security and trustworthiness of digital financial services.

Keywords: anomaly detection, financial fraud, machine learning, autoencoders, isolation forest, transactional data analysis

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Authors: Dragana Calic

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The openness, availability and the sheer volume of big data have provided, what some regard as, an invaluable and rich dataset. Researchers, businesses, advertising agencies, medical institutions, to name only a few, collect, share, and analyze this data to enable their processes and decision making. However, there are important ethical considerations associated with the use of big data. The rapidly evolving nature of online technologies has overtaken the many legislative, privacy, and ethical frameworks and principles that exist. For example, should we obtain consent to use people’s online data, and under what circumstances can privacy considerations be overridden? Current guidance on how to appropriately and ethically handle big data is inconsistent. Consequently, this paper focuses on two quite distinct but related ethical considerations that are at the core of the use of big data for research purposes. They include empowering the producers of data and empowering researchers who want to study big data. The first consideration focuses on informed consent which is at the core of empowering producers of data. In this paper, we discuss some of the complexities associated with informed consent and consider studies of producers’ perceptions to inform research ethics guidelines and practice. The second consideration focuses on the researcher. Similarly, we explore studies that focus on researchers’ perceptions and experiences.

Keywords: big data, ethics, producers’ perceptions, researchers’ perceptions

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Authors: Deybith Venegas-Rojas, Sercan Keskin, Svenja Riekeberg, Sana Azim, Stephanie Manz, R. J. Dwayne Miller, Hoc Khiem Trieu

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Liquid Transmission Electron Microscopy (TEM) is a growing area with a broad range of applications from physics and chemistry to material engineering and biology, in which it is possible to image in-situ unseen phenomena. For this, a nanofluidic device is used to insert the nanoflow with the sample inside the microscope in order to keep the liquid encapsulated because of the high vacuum. In the last years, Si3N4 windows have been widely used because of its mechanical stability and low imaging contrast. Nevertheless, the pressure difference between the inside fluid and the outside vacuum in the TEM generates bulging in the windows. This increases the imaged fluid volume, which decreases the signal to noise ratio (SNR), limiting the achievable spatial resolution. With the proposed device, the membrane is fortified with a microstructure capable of stand higher pressure differences, and almost removing completely the bulging. A theoretical study is presented with Finite Element Method (FEM) simulations which provide a deep understanding of the membrane mechanical conditions and proves the effectiveness of this novel concept. Bulging and von Mises Stress were studied for different membrane dimensions, geometries, materials, and thicknesses. The microfabrication of the device was made with a thin wafer coated with thin layers of SiO2 and Si3N4. After the lithography process, these layers were etched (reactive ion etching and buffered oxide etch (BOE) respectively). After that, the microstructure was etched (deep reactive ion etching). Then the back side SiO2 was etched (BOE) and the array of free-standing micro-windows was obtained. Additionally, a Pyrex wafer was patterned with windows, and inlets/outlets, and bonded (anodic bonding) to the Si side to facilitate the thin wafer handling. Later, a thin spacer is sputtered and patterned with microchannels and trenches to guide the nanoflow with the samples. This approach reduces considerably the common bulging problem of the window, improving the SNR, contrast and spatial resolution, increasing substantially the mechanical stability of the windows, allowing a larger viewing area. These developments lead to a wider range of applications of liquid TEM, expanding the spectrum of possible experiments in the field.

Keywords: liquid cell, liquid transmission electron microscopy, nanofluidics, nanofluidic cell, thin films

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Authors: Murzabekova Gulden

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Directional implicit functions for underdetermined nonsmooth systems in terms of the new tool of the Nonsmooth analysis - exhausters are considered. A method for finding an implicit function for underdetermined nonsmooth systems is proposed.

Keywords: implicit function, exhauster, nonsmooth systems

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Authors: Edouard Ngor Sarr, Abel Diatta, Serigne Mor Toure, Ousmane Sall, Lamine Faty

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Thanks to Web 2, we are witnessing a form of democratization of the spoken word, an exponential increase in the number of users on the web, but also, and above all, the accumulation of a daily flow of content that is becoming, at times, uncontrollable. Added to this is the rise of a violent social fabric characterised by hateful and racial comments, insults, and other content that contravenes social rules and the platforms' terms of use. Consequently, managing and regulating this mass of new content is proving increasingly difficult, requiring substantial human, technical, and technological resources. Without regulation and with the complicity of anonymity, this toxic content can pollute discussions and make these online spaces highly conducive to abuse, which very often has serious consequences for certain internet users, ranging from anxiety to suicide, depression, or withdrawal. The toxicity of a comment is defined as anything that is rude, disrespectful, or likely to cause someone to leave a discussion or to take violent action against a person or a community. Two levels of measures are needed to deal with this deleterious situation. The first measures are being taken by governments through draft laws with a dual objective: (i) to punish the perpetrators of these abuses and (ii) to make online platforms accountable for the mistakes made by their users. The second measure comes from the platforms themselves. By assessing the content left by users, they can set up filters to block and/or delete content or decide to suspend the user in question for good. However, the speed of discussions and the volume of data involved mean that platforms are unable to properly monitor the moderation of content produced by Internet users. That's why they use human moderators, either through recruitment or outsourcing. Moderating comments on the web means assessing and monitoring users‘ comments on online platforms in order to strike the right balance between protection against abuse and users’ freedom of expression. It makes it possible to determine which publications and users are allowed to remain online and which are deleted or suspended, how authorised publications are displayed, and what actions accompany content deletions. In this study, we look at the problem of automatic moderation of toxic comments in the face of local African languages and, more specifically, on social network comments in Senegal. We review the state of the art, highlighting the different approaches, algorithms, and tools for moderating comments. We also study the issues and challenges of moderation in the face of web ecosystems with lesser-known languages, such as local languages.

Keywords: moderation, local languages, Senegal, toxic comments

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Authors: Abdullah Beyazkurk, Onur Ozdemir

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The evolution of warfare has been affected from technological developments to a large extent. Another important factor that affected the evolution of warfare is the space. Technological developments became cornerstones for the organization of the forces on the field, while space of the battlefield gained importance with the introduction of urban areas as 'battlefields'. The use of urban areas as battlefields increased the casualty, while technological developments began to play a remedial role. Thus, the unmanned systems drew attention as the remedy. Today's widely used unmanned aerial vehicles have great effects on the operations. On the other hand, with the increasing urbanization, and the wide use of urban areas as battlefields make it a necessity to benefit from unmanned systems on the ground as well. This study focuses on the use of unmanned aerial systems as well as unmanned ground systems in urban warfare, with regards to their performance and cost affectivity. The study defends that the use of unmanned vehicles will be remedial for increasing casualty rates, while their precision and superhuman capacity will manifest the performance advantage. The findings of this study will help modern armies focus on unmanned systems, especially for the urban, anti-terror, or counter insurgency operations.

Keywords: technology, warfare, urban warfare, unmanned systems, unmanned ground vehicles, unmanned aerial vehicles

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Authors: Wanyi Zhu, Xia Ming, Huafeng Wang, Junda Chen, Lu Liu, Jiangwei Jiang, Guohua Liu

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Anomaly detection is a first and imperative step needed to respond to unexpected problems and to assure high performance and security in large data center management. This paper presents an online anomaly detection system through an innovative approach of ensemble machine learning and adaptive differentiation algorithms, and applies them to performance data collected from a continuous monitoring system for multi-tier web applications running in Alibaba data centers. We evaluate the effectiveness and efficiency of this algorithm with production traffic data and compare with the traditional anomaly detection approaches such as a static threshold and other deviation-based detection techniques. The experiment results show that our algorithm correctly identifies the unexpected performance variances of any running application, with an acceptable false positive rate. This proposed approach has already been deployed in real-time production environments to enhance the efficiency and stability in daily data center operations.

Keywords: Alibaba data centers, anomaly detection, big data computation, dynamic ensemble learning

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Authors: Liwen Hou

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The booming mobile business has been penetrating the taxi industry worldwide with P2P (peer to peer) taxi services, as an emerging business model, transforming the industry. Parallel with other mobile businesses, member recommendations and online reviews are believed to be very effective with regard to acquiring new users for P2P taxi services. Based on an empirical dataset of the taxi industry in China, this study aims to reveal which factors influence users’ recommendations and review-writing behaviors. Differing from the existing literature, this paper takes the taxi driver’s perspective into consideration and hence selects a group of variables related to the drivers. We built two models to reflect the factors that influence the number of recommendations and reviews posted on the platform (i.e., the app). Our models show that all factors, except the driver’s score, significantly influence the recommendation behavior. Likewise, only one factor, passengers’ bad reviews, is insignificant in generating more drivers’ reviews. In the conclusion, we summarize the findings and limitations of the research.

Keywords: online recommendation, P2P taxi service, review-writing, word of mouth

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Authors: Anil Koklu, Amin Mansoorifar, Ali Beskok

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Dielectric spectroscopy (DS) is a noninvasive, label free technique for a long term real-time measurements of the impedance spectra of biological cells. DS enables characterization of cellular dielectric properties such as membrane capacitance and cytoplasmic conductivity. We have developed a lab-on-a-chip device that uses an electro-activated microwells array for loading, DS measurements, and unloading of biological cells. We utilized from dielectrophoresis (DEP) to capture target cells inside the wells and release them after DS measurement. DEP is a label-free technique that exploits differences among dielectric properties of the particles. In detail, DEP is the motion of polarizable particles suspended in an ionic solution and subjected to a spatially non-uniform external electric field. To the best of our knowledge, this is the first microfluidic chip that combines DEP and DS to analyze biological cells using electro-activated wells. Device performance is tested using two different cell lines of prostate cancer cells (RV122, PC-3). Impedance measurements were conducted at 0.2 V in the 10 kHz to 40 MHz range with 6 s time resolution. An equivalent circuit model was developed to extract the cell membrane capacitance and cell cytoplasmic conductivity from the impedance spectra. We report the time course of the variations in dielectric properties of PC-3 and RV122 cells suspended in low conductivity medium (LCB), which enhances dielectrophoretic and impedance responses, and their response to sudden pH change from a pH of 7.3 to a pH of 5.8. It is shown that microfluidic chip allowed online measurements of dielectric properties of prostate cancer cells and the assessment of the cellular level variations under external stimuli such as different buffer conductivity and pH. Based on these data, we intend to deploy the current device for single cell measurements by fabricating separately addressable N × N electrode platforms. Such a device will allow time-dependent dielectric response measurements for individual cells with the ability of selectively releasing them using negative-DEP and pressure driven flow.

Keywords: microfluidic, microfabrication, lab on a chip, AC electrokinetics, dielectric spectroscopy

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Authors: M. S. Razana, Z. W. Shafiuddin

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Internal auditing is one of the most important activities for organizations that implement information security management systems (ISMS). The purpose of internal audits is to ensure the ISMS implementation is in accordance to the ISO/IEC 27001 standard and the organization’s own requirements for its ISMS. Competent internal auditors are the main element that contributes to the effectiveness of internal auditing activities. To realize this need, CyberSecurity Malaysia is now in the process of becoming a certification body that certifies ISMS internal auditors. The certification scheme will assess the competence of internal auditors in generic knowledge and skills in management systems, and also in ISMS-specific knowledge and skills. The certification assessment is based on the ISO/IEC 19011 Guidelines for auditing management systems, ISO/IEC 27007 Guidelines for information security management systems auditing and ISO/IEC 27001 Information security management systems requirements. The certification scheme complies with the ISO/IEC 17024 General requirements for bodies operating certification systems of persons. Candidates who pass the exam will be certified as an ISMS Internal Auditor, whose competency will be evaluated every three years.

Keywords: ISMS internal audit, ISMS internal auditor, ISO/IEC 17024, competence, certification

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Authors: H. Weigelt-Marom

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Over the years and up to the arousal of the COVID-19 pandemic, deaf or hard of hearing students studying in higher education institutions, participated lectures on campus using hearing aids and strategies adapted for frontal learning in a classroom. Usually, these aids were well known to them from their earlier study experience in school. However, the transition to online lessons, due to the latest pandemic, led deaf or hard of hearing students to study outside of their physical, well known learning environment. The change of learning environment and structure rose new challenges for these students. The present study examined the learning experience, limitations, challenges and benefits regarding learning online with lecture and classmates via the “Zoom” video conference program, among deaf or hard of hearing students in academia setting. In addition, emotional and social aspects related to learning in general versus the “Zoom” were examined. The study included 18 students diagnosed as deaf or hard of hearing, studying in various higher education institutions in Israel. All students had experienced lessons on the “Zoom”. Following allocation of the group study by the deaf and hard of hearing non-profit organization “Ma’agalei Shema”, and receiving the participants inform of consent, students were requested to answer a google form questioner and participate in an interview. The questioner included background information (e.g., age, year of studying, faculty etc.), level of computer literacy, and level of hearing and forms of communication (e.g., lip reading, sign language etc.). The interviews included a one on one, semi-structured, in-depth interview, conducted by the main researcher of the study (interview duration: up to 60 minutes). The interviews were held on “ZOOM” using specific adaptations for each interviewee: clear face screen of the interviewer for lip and face reading, and/ or professional sign language or live text transcript of the conversation. Additionally, interviewees used their audio devices if needed. Questions regarded: learning experience, difficulties and advantages studying using “Zoom”, learning in a classroom versus on “Zoom”, and questions concerning emotional and social aspects related to learning. Thematic analysis of the interviews revealed severe difficulties regarding the ability of deaf or hard of hearing students to comprehend during ”Zoom“ lessons without adoptive aids. For example, interviewees indicated difficulties understanding “Zoom” lessons due to their inability to use hearing devices commonly used by them in the classroom (e.g., FM systems). 80% indicated that they could not comprehend “Zoom” lessons since they could not see the lectures face, either because lectures did not agree to open their cameras or, either because they did not keep a straight forward clear face appearance while teaching. However, not all descriptions regarded learning via the “zoom” were negative. For example, 20% reported the recording of “Zoom” lessons as a main advantage. Enabling then to repeatedly watch the lessons at their own pace, mostly assisted by friends and family to translate the audio output into an accessible input. These finding and others regarding the learning experience of the group study on the “Zoom”, as well as their recommendation to enable deaf or hard of hearing students to study inclusively online, will be presented at the conference.

Keywords: deaf or hard of hearing, learning experience, Zoom, qualitative research

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Authors: Miguel Llorens-Marin, Adolfo Hernandez, Maria Puelles-Gallo

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The increasing influence of Online Travel Agencies (OTAs) on hotel bookings and the electronic word-of-mouth (eWOM) contained in them has been featured by many scientific studies as a major factor in the booking decision. The main reason is that nowadays, in the hotel sector, consumers first come into contact with the offer through the web and the online environment. Due to the nature of the hotel product and the fact that it is booked in advance to actually seeing it, there is a lack of knowledge about its actual features. This makes eWOM a major channel to help consumers to reduce their perception of risk when making their booking decisions. This research studies the relationship between aspects of customer influenceability by reading eWOM communications, at the time of booking a hotel, with the propensity to write a review. In other words, to test relationships between the reading and the writing of eWOM. Also investigates the importance of different underlying motivations for writing eWOM. Online surveys were used to obtain the data from a sample of hotel customers, with 739 valid questionnaires. A measurement model and Path analysis were carried out to analyze the chain of relationships among the independent variable (influenceability from reading reviews) and the dependent variable (propensity to write a review) with the mediating effects of additional variables, which help to explain the relationship. The authors also tested the moderating effects of age and gender in the model. The study considered three different underlying motivations for writing a review on a hotel experience, namely hedonic, altruistic and conflicted. Results indicate that the level of influenceability by reading reviews has a positive effect on the propensity to write reviews; therefore, we manage to link the reading and the writing of reviews. Authors also discover that the main underlying motivation to write a hotel review is the altruistic motivation, being the one with the higher Standard regression coefficient above the hedonic motivation. The authors suggest that the propensity to write reviews is not related to sociodemographic factors (age and gender) but to attitudinal factors such as ‘the most influential factor when reading’ and ‘underlying motivations to write. This gives light on the customer engagement motivations to write reviews. The implications are that managers should encourage their customers to write eWOM reviews on altruistic grounds to help other customers to make a decision. The most important contribution of this work is to link the effect of reading hotel reviews with the propensity to write reviews.

Keywords: hotel reviews, electronic word-of-mouth (eWOM), online consumer reviews, digital marketing, social media

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Authors: Ekaterina Malova

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Type 1 diabetes (T1D) is a chronic illness requiring immense lifestyle changes to reduce the chance of life-threatening complications. Moving to a college may be the first time for a young adult with T1D to take responsibility for all the aspects of their diabetes care. In addition, people with T1D constantly face stigmatization and discrimination as a result of their health condition, which puts additional pressure on young adults with T1D. Hence, omissions in diabetes self-care often occur during the time of transition to college when both the social and physical environment of young adults changes drastically and contribute to the fact that emerging young adults remain one of the age groups with the highest hemoglobin levels and poorest diabetes control. However, despite potential severe health risks caused by a lack of proper diabetes self-care, little is known about the experiences of emerging adults embarking on a higher education journey as this population. Thus, young adults with type 1 diabetes are a 'forgotten group,' meaning that their experiences are rarely addressed by researchers. Given that self-disclosure and information-seeking can be challenging for individuals with stigmatized illnesses, online platforms like YouTube have become a popular medium of self-disclosure and information-seeking for people living with T1D. Thus, this study aims to provide an analysis of experiences that college students with T1D choose to share with the general public online and explore the nature of information being communicated by college students with T1D to the online community in personal narratives posted on YouTube. A systematic approach was used to retrieve a video sample by searching YouTube with keywords 'type 1 diabetes' and 'college,' with results ordered by relevance. A total of 18 videos were saved. Video lengths ranged from 2 to 28 minutes. The data were coded using NVivo. Video transcripts were coded and analyzed utilizing the thematic analysis method. Three key themes emerged from thematic analysis: 1) Advice, 2) Personal experience, and 3) Things I wish everyone knew about T1D. In addition, Theme 1 was divided into subtopics to differentiate between the most common types of advice: 1) Overcoming stigma and b) Seeking social support. The identified themes indicate that two groups of the population can potentially benefit from watching students’ video testimonies: 1) lay public and 2) other students with T1D. Given that students in the videos reported a lack of T1D education in the lay public, such video narratives can serve important educational purposes and reduce health stigma, while perceived similarity and identification with students in the videos may facilitate the transition of health information to other individuals with T1D and positively affect their diabetes routine. Thus, online video narratives can potentially serve both educational and persuasive purposes, empowering students with T1D to stay in control of T1D while succeeding academically.

Keywords: type 1 diabetes, college students, health communication, transition period

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Authors: Naman Solanki, Souraj Mondal

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With the world moving towards online communication, the video datastore has exploded in the past few years. Consequently, it has become crucial to analyse participant’s engagement levels in online communication videos. Engagement prediction of people in videos can be useful in many domains, like education, client meetings, dating, etc. Video-level or frame-level prediction of engagement for a user involves the development of robust models that can capture facial micro-emotions efficiently. For the development of an engagement prediction model, it is necessary to have a widely-accepted standard dataset for engagement analysis. DAiSEE is one of the datasets which consist of in-the-wild data and has a gold standard annotation for engagement prediction. Earlier research done using the DAiSEE dataset involved training and testing standard models like CNN-based models, but the results were not satisfactory according to industry standards. In this paper, a multi-level classification approach has been introduced to create a more robust model for engagement analysis using the DAiSEE dataset. This approach has recorded testing accuracies of 0.638, 0.7728, 0.8195, and 0.866 for predicting boredom level, engagement level, confusion level, and frustration level, respectively.

Keywords: computer vision, engagement prediction, deep learning, multi-level classification

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Authors: M. Khoshab, M. J. Sedigh

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Dynamic systems, which in mathematical point of view are those governed by differential equations, are much more difficult to study and to predict their behavior in comparison with static systems which are governed by algebraic equations. Economical systems such as market are among complicated dynamic systems. This paper tries to adopt a very simple mathematical model for market and to study effect of supply and demand function on behavior of the market while the supply side experiences a lag due to production restrictions.

Keywords: dynamic system, lag on supply demand, market stability, supply demand model

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Authors: Charléa M. Smith, Raiden L. Schodowski, Arletty Pinel

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Due to the COVID-19 pandemic, the Faculty of Medical Sciences of The University of the West Indies (UWI) Mona in Kingston, Jamaica, had to rapidly migrate to digital and blended learning. Students in the preclinical stage of the program transitioned to full-time online learning, while students in the clinical stage experienced decreased daily patient contact and the implementation of a blend of online lectures and virtual clinical practice. Such sudden changes were coupled with the institutional pressure of the need to introduce a novel approach to education without much time for preparation, as well as additional strain endured by the faculty, who were overwhelmed by serving as frontline workers. During the period July 20 to August 23, 2021, this study surveyed preclinical and clinical students to capture their experiences with these changes and their recommendations for future use of digital modalities of learning to enhance medical education. It was conducted with a fellow student of the 2021 cohort of the MultiPod mentoring program. A questionnaire was developed and distributed digitally via WhatsApp to all medical students of the UWI Mona campus to assess students’ experiences and perceptions of the advantages, challenges, and impact on individual knowledge proficiencies brought about by the transition to predominantly digital learning environments. 108 students replied, 53.7% preclinical and 46.3% clinical. 67.6% of the total were female and 30.6 % were male; 1.8% did not identify themselves by gender. 67.2% of preclinical students preferred blended learning and 60.3% considered that the content presented did not prepare them for clinical work. Only 31% considered that the online classes were interactive and encouraged student participation. 84.5% missed socialization with classmates and friends and 79.3% missed a focused environment for learning. 80% of the clinical students felt that they had not learned all that they expected and only 34% had virtual interaction with patients, mostly by telephone and video calls. Observing direct consultations was considered the most useful, yet this was the least-used modality. 96% of the preclinical students and 100% of the clinical ones supplemented their learning with additional online tools. The main recommendations from the survey are the use of interactive teaching strategies, more discussion time with lecturers, and increased virtual interactions with patients. Universities are returning to face-to-face learning, yet it is unlikely that blended education will disappear. This study demonstrates that students’ perceptions of their experience during mobility restrictions must be taken into consideration in creating more effective, inclusive, and efficient blended learning opportunities.

Keywords: blended learning, digital learning, medical education, student perceptions

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Authors: Raquel C. A. G. Mota, Livia R. Menezes, Emerson O. da Silva

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Both silver nanoparticles and titanium dioxide have been extensively used in tissue engineering since they’ve been approved by the Food and Drug Administration (FDA), and present a bactericide effect when added to a polymeric matrix. In this work, the focus is on fabricating binary systems with both nanoparticles so that the synergistic effect can be investigated. The systems were tested by Nuclear Magnetic Resonance (NMR), Thermogravimetric Analysis (TGA), Fourier-Transformed Infrared (FTIR), and Differential Scanning Calorimetry (DSC), and X-ray Diffraction (XRD), and had both their bioactivity and bactericide effect tested. The binary systems presented different properties than the individual systems, enhancing both the thermal and biological properties as was to be expected. The crystallinity was also affected, as indicated by the finding of the DSC and XDR techniques, and the NMR showed a good dispersion of both nanoparticles in the polymer matrix. These findings indicate the potential of combining TiO₂ and silver nanoparticles in biomedicine.

Keywords: metallic nanoparticles, nanotechnology, polymer nanocomposites, polymer science

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Authors: Thu Thuy Nguyen

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In recent years, mediation has gained a great attention from many jurisdictions thanks to its advantages. With respect to Asia, mediation has a long history of development in this region with various types to amicably settle disputes in civil and commercial issues. The modern mediation system in several Asian countries and territories comprises three main categories, namely court-annexed mediation, mediation within arbitral proceedings and institutional mediation. Court-annexed mediation (or in-court mediation) is mediation conducted by the court in the course of judicial procedures. In dealing with cross-border business disputes, in-court mediation exposes a number of advantages in comparison with two other types of mediation, especially in terms of enforcement of final result. However, the confidentiality of mediation process in subsequent judicial proceedings, qualifications of court judges and the issue of recognition and enforcement of foreign judgment are normally seen as drawbacks of court-annexed mediation as in court-annexed mediation judges will be casts as dual roles as both mediator and ultimate adjudicator in the same dispute. This paper will examine the strengths and weaknesses of in-court mediation in settling transnational business disputes in selected Asian countries, including China, Hong Kong, Japan, Singapore and Vietnam.

Keywords: court-annexed mediation, international commercial disputes, Asia, strengths and weaknesses

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Authors: Gennady P. Ginkul, Sergey Yu. Soloviov

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The article proposes to use so-called "quotation-based algorithm" for simulation of decision making process in distributed expert systems and multi-agent systems. The idea was adopted from the techniques for group decision-making. It is based on the assumption that one expert system to perform its logical inference may use rules from another expert system. The application of the algorithm was demonstrated on the example in which the consolidated decision is the decision that requires minimal quotation.

Keywords: backward chaining inference, distributed expert systems, group decision making, multi-agent systems

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Authors: Venkata Narayana Chejarla, Nafisa Parvez Shaik, Gopi Vara Prasad Marabathula, Deva Kumar Bejjam

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Yoga is an advanced, well-recognized method with roots in Indian philosophy. Yoga benefits both the body and the psyche. Yoga is a regular exercise that helps people relax and sleep better while also enhancing their balance, endurance, and concentration. Yoga can be learned in a variety of settings, including at home with the aid of books and the internet as well as in yoga studios with the guidance of an instructor. Self-learning does not teach the proper yoga poses, and doing them without the right instruction could result in significant injuries. We developed "Online Yoga Asana Trainer using Deep Learning" so that people could practice yoga without a teacher. Our project is developed using Tensorflow, Movenet, and Keras models. The system makes use of data from Kaggle that includes 25 different yoga poses. The first part of the process involves applying the movement model for extracting the 17 key points of the body from the dataset, and the next part involves preprocessing, which includes building a pose classification model using neural networks. The system scores a 98.3% accuracy rate. The system is developed to work with live videos.

Keywords: yoga, deep learning, movenet, tensorflow, keras, CNN

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Authors: Amal M. Alrayes, Hayat M. Ali

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Since the beginning of distance education with the rapid evolution of technology, the social network plays a vital role in the educational process to enforce the interaction been the learners and teachers. There are many Web 2.0 technologies, services and tools designed for educational purposes. This research aims to investigate instructors’ acceptance towards web-based learning systems in higher educational institutes in Kingdom of Bahrain. Questionnaire is used to investigate the instructors’ usage of Web 2.0 and the factors affecting their acceptance. The results confirm that instructors had high accessibility to such technologies. However, patterns of use were complex. Whilst most expressed interest in using online technologies to support learning activities, learners seemed cautious about other values associated with web-based system, such as the shared construction of knowledge in a public format. The research concludes that there are main factors that affect instructors’ adoption which are security, performance expectation, perceived benefits, subjective norm, and perceived usefulness.

Keywords: Web 2.0, higher education, acceptance, students' perception

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Authors: Tomas Menard

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The design of control-law for engineering systems has been investigated for many decades. While many results are concerned with continuous systems with continuous output, nowadays, many controlled systems have to transmit their output measurements through network, hence making it discrete-time. But it is well known that the sampling of a system whose control-law is based on the continuous output may render the system unstable, especially when this sampling period is long compared to the system dynamics. The control design then has to be adapted in order to cope with this issue. In this paper, we consider systems which can be modeled as double integrator with uncertainty on the input since many mechanical systems can be put under such form. We present a control scheme based on an observer using only discrete time measurement and which provides continuous time estimation of the state, combined with a continuous control law, which stabilized a system with second-order dynamics even in the presence of uncertainty. It is further shown that arbitrarily long sampling periods can be dealt with properly setting the control scheme parameters.

Keywords: dynamical system, control law design, sampled output, observer design

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Authors: Wilson Enríquez, Daniel Cardenas

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This article proposes a filter bank format combined with the mathematical tool called polyphase decomposition and the discrete Fourier transform (DFT) with the purpose of improving the performance of the fifth-generation communication systems (5G). We started with a review of the literature and the study of the filter bank theory and its combination with DFT in order to improve the performance of wireless communications since it reduces the computational complexity of these communication systems. With the proposed technique, several experiments were carried out in order to evaluate the structures in 5G systems. Finally, the results are presented in graphical form in terms of bit error rate against the ratio bit energy/noise power spectral density (BER vs. Eb / No).

Keywords: multi-carrier system (5G), filter bank, polyphase decomposition, FIR equalizer

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Authors: Alexander P. Eremeev, Ivan E. Kurilenko, Pavel R. Varshavskiy

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In this paper, the problem of the application of temporal reasoning and case-based reasoning in intelligent decision support systems is considered. The method of case-based reasoning with temporal dependences for the solution of problems of real-time diagnostics and forecasting in intelligent decision support systems is described. This paper demonstrates how the temporal case-based reasoning system can be used in intelligent decision support systems of the car access control. This work was supported by RFBR.

Keywords: analogous reasoning, case-based reasoning, intelligent decision support systems, temporal reasoning

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Authors: Taiki Baba, Tomoaki Hashimoto

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The random dither quantization method enables us to achieve much better performance than the simple uniform quantization method for the design of quantized control systems. Motivated by this fact, the stochastic model predictive control method in which a performance index is minimized subject to probabilistic constraints imposed on the state variables of systems has been proposed for linear feedback control systems with random dither quantization. In other words, a method for solving optimal control problems subject to probabilistic state constraints for linear discrete-time control systems with random dither quantization has been already established. To our best knowledge, however, the feasibility of such a kind of optimal control problems has not yet been studied. Our objective in this paper is to investigate the feasibility of stochastic model predictive control problems for linear discrete-time control systems with random dither quantization. To this end, we provide the results of numerical simulations that verify the feasibility of stochastic model predictive control problems for linear discrete-time control systems with random dither quantization.

Keywords: model predictive control, stochastic systems, probabilistic constraints, random dither quantization

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Authors: W. S. Barber, S. L. King

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This paper is a qualitative case study analysis of the development of a fully online learning community of graduate students through arts-based community building activities. With increasing numbers and types of online learning spaces, it is incumbent upon educators to continue to push the edge of what best practices look like in digital learning environments. In digital learning spaces, instructors can no longer be seen as purveyors of content knowledge to be examined at the end of a set course by a final test or exam. The rapid and fluid dissemination of information via Web 3.0 demands that we reshape our approach to teaching and learning, from one that is content-focused to one that is process-driven. Rather than having instructors as formal leaders, today’s digital learning environments require us to share expertise, as it is the collective experiences and knowledge of all students together with the instructors that help to create a very different kind of learning community. This paper focuses on innovations pursued in a 36 hour 12 week graduate course in higher education entitled “Critical and Reflective Practice”. The authors chronicle their journey to developing a fully online learning community (FOLC) by emphasizing the elements of social, cognitive, emotional and digital spaces that form a moving interplay through the community. In this way, students embrace anywhere anytime learning and often take the learning, as well as the relationships they build and skills they acquire, beyond the digital class into real world situations. We argue that in order to increase student online engagement, pedagogical approaches need to stem from two primary elements, both creativity and critical reflection, that are essential pillars upon which instructors can co-design learning environments with students. The theoretical framework for the paper is based on the interaction and interdependence of Creativity, Intuition, Critical Reflection, Social Constructivism and FOLCs. By leveraging students’ embedded familiarity with a wide variety of technologies, this case study of a graduate level course on critical reflection in education, examines how relationships, quality of work produced, and student engagement can improve by using creative and imaginative pedagogical strategies. The authors examine their professional pedagogical strategies through the lens that the teacher acts as facilitator, guide and co-designer. In a world where students can easily search for and organize information as self-directed processes, creativity and connection can at times be lost in the digitized course environment. The paper concludes by posing further questions as to how institutions of higher education may be challenged to restructure their credit granting courses into more flexible modules, and how students need to be considered an important part of assessment and evaluation strategies. By introducing creativity and critical reflection as central features of the digital learning spaces, notions of best practices in digital teaching and learning emerge.

Keywords: online, pedagogy, learning, communities

Procedia PDF Downloads 406