Search results for: mobile network communication

Authors: Asim Majeed, Anwar Ul Haq, Ayesha Asim, Mike Lloyd-Williams, Arshad Jamal, Usman Butt

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This study aims to investigate the impact of data leak of M&S customers on digital communities. Modern businesses are using digital communities as an important public relations tool for marketing purposes. This form of communication helps companies to build better relationship with their customers which also act as another source of information. The communication between the customers and the organizations is not regulated so users may post positive and negative comments. There are new platforms being developed on a daily basis and it is very crucial for the businesses to not only get themselves familiar with those but also know how to reach their existing and perspective consumers. The driving force of marketing and communication in modern businesses is the digital communities and these are continuously increasing and developing. This phenomenon is changing the way marketing is conducted. The current research has discussed the implications on M&S business performance since the data was exploited on digital communities; users contacted M&S and raised the security concerns. M&S closed down its website for few hours to try to resolve the issue. The next day M&S made a public apology about this incidence. This information was proliferated on various digital communities and it has impacted negatively on M&S brand name, sales and customers. The content analysis approach is being used to collect qualitative data from 100 digital bloggers including social media communities such as Facebook and Twitter. The results and finding provide useful new insights into the nature and form of security concerns of digital users. Findings have theoretical and practical implications. This research will showcase a large corporation utilizing various digital community platforms and can serve as a model for future organizations.

Keywords: Digital, communities, performance, dissemination, implications, data, exploitation

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Authors: Namirimu Beatrice Doreen

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In recent years, there has been growing recognition of the importance of diversity, equity, and inclusion (DEI) in advertising, driven in part by the increasing diversity of society and the expanding reach of new media platforms. As marketers grapple with the challenge of creating campaigns that resonate with a wide range of audiences, the role of new media adoption emerges as a critical, independent variable shaping the landscape of DEI in advertising. This paper delves into the evolving dynamics of DEI in advertising, examining the multifaceted challenges and opportunities encountered by brands in their pursuit of more inclusive marketing strategies. Drawing on theoretical frameworks from marketing, sociology, and communication studies, this paper explores the intricate interplay between DEI initiatives and their impact on consumer perceptions, brand reputation, and market performance. The analysis considers how new media adoption influences the effectiveness and reach of DEI initiatives as brands leverage digital platforms to engage with diverse audiences in innovative ways. Through insightful case studies, this paper illustrates best practices and identifies areas for improvement in the realm of inclusive advertising, shedding light on the practical implications of DEI principles for marketers. By synthesizing insights from academia and industry, this paper offers actionable recommendations for marketers seeking to navigate the complexities of DEI in their advertising strategies. By embracing DEI principles and harnessing the power of new media platforms, brands can foster a more equitable and inclusive advertising landscape, ultimately enhancing their connections with diverse audiences and driving positive social change.

Keywords: diversity, equity, inclusion, new media, contemporary marketing communication

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Authors: Yating Yang, Xue Zhang, Chengli Zhao

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Technology capability refers to the comprehensive ability that influences all factors of technological development. Among them, researchers’ resources serve as the foundation and driving force for technology capability, representing a significant manifestation of a country/region's technological capability. Therefore, the cross-border transfer behavior of researchers to some extent reflects changes in technological capability between countries/regions, providing a unique research perspective for technological capability assessment. This paper proposes a technological capability assessment model based on personnel transfer networks, which consists of a researchers' transfer network model and a country/region role evolution model. It evaluates the changes in a country/region's technological capability roles from the perspective of researcher transfers and conducts an analysis using artificial intelligence as a case study based on literature data. The study reveals that the United States, China, and the European Union are core nodes, and identifies the role evolution characteristics of several major countries/regions.

Keywords: transfer network, technological capability assessment, central-peripheral structure, role evolution

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Authors: Clara T. Fatoye, April Betts, Abayomi Odeyemi, Francis A. Fatoye, Isaac O. Odeyemi

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Background: The post-launch stage is the last stage in the development of a pharmaceutical product. It is important to involve patients in the development of pharmaceutical products at the post-launch stage, as patients are the end-users of pharmaceutical products. It is expected that involving them might ensure an effective working relationship among the various stakeholders. However, involving patients in the development of pharmaceutical products comes with its problems. Hence, this study examined how to resolve problems experienced by involving patients in the developments of pharmaceutical products’ at post-launch consisting of Positioning of pharmaceutical products (POPP), detailing of pharmaceutical products (DOPP) and reimbursement and Formulary Submission (R&FS). Methods: A questionnaire was used for the present study. It was administered at the ISPOR Glasgow 2017 to 104 participants, all of which were professionals from Market access (MA) and health economics and outcomes research (HEOR) backgrounds. They were asked how the issues experienced by patients can be resolved. Participants responded under six domains as follows: communication, cost, effectiveness, external factors, Quality of life (QoL) and safety. Thematic analysis was carried out to identify strategies to resolve issues experienced by patients at the post-launch stage. Results: Three (3) factors cut across at POPP, DOPP, and R&FS that is (external factors, communication and QoL). The first resolution method was an external factor that is, the relationship with stakeholders and policymakers. Communication was also identified as a resolution method that can help to resolve problems experienced by patients at the post-launch stage. The third method was QoL as perceived by the patients based on professionals’ opinions. Other strategies that could be used to resolve problems experienced were the effectiveness of pharmaceutical products at the DOPP level and cost at R&FS. Conclusion: The study showed that focusing on external factors, communication, and patients’ QoL are methods for resolving issues experienced by involving patients at the post-launch stage of pharmaceutical product development. Hence, effective working relationships between patients, policymakers and stakeholders may help to resolve problems experienced at the post-launch stage. Healthcare policymakers are to be aware of these findings as they may help them to put appropriate strategies in place to enhance the involvement of patients in pharmaceutical product development at the post-launch stage, thereby improving the health outcomes of the patients.

Keywords: patients, pharmaceutical products, post-launch stage, quality of life, QoL

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Authors: Monireh Ahmadi Bani, Adel Khorramrouz, Lalenoor Morvarid, Bagheri Mahtab

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Background:- Foot disorders are common in musculoskeletal problems. Plantar pressure distribution measurement is one the most important part of foot disorders diagnosis for quantitative analysis. However, the association of plantar pressure and foot disorders is not clear. With the growth of dataset and machine learning methods, the relationship between foot disorders and plantar pressures can be detected. Significance of the study:- The purpose of this study was to predict the probability of common foot disorders based on peak plantar pressure distribution and center of pressure during walking. Methodologies:- 2323 participants were assessed in a foot therapy clinic between 2015 and 2021. Foot disorders were diagnosed by an experienced physician and then they were asked to walk on a force plate scanner. After the data preprocessing, due to the difference in walking time and foot size, we normalized the samples based on time and foot size. Some of force plate variables were selected as input to a deep neural network (DNN), and the probability of any each foot disorder was measured. In next step, we used support vector machine (SVM) and run dataset for each foot disorder (classification of yes or no). We compared DNN and SVM for foot disorders prediction based on plantar pressure distributions and center of pressure. Findings:- The results demonstrated that the accuracy of deep learning architecture is sufficient for most clinical and research applications in the study population. In addition, the SVM approach has more accuracy for predictions, enabling applications for foot disorders diagnosis. The detection accuracy was 71% by the deep learning algorithm and 78% by the SVM algorithm. Moreover, when we worked with peak plantar pressure distribution, it was more accurate than center of pressure dataset. Conclusion:- Both algorithms- deep learning and SVM will help therapist and patients to improve the data pool and enhance foot disorders prediction with less expense and error after removing some restrictions properly.

Keywords: deep neural network, foot disorder, plantar pressure, support vector machine

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Authors: Felix Liedel

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The rise of artificial intelligence has numerous and far-reaching consequences. In addition to the obvious consequences for entire professions, the increasing interaction with chatbots also has a wide range of social consequences and implications. We are already increasingly used to interacting with digital chatbots, be it in virtual consulting situations, creative development processes or even in building personal or intimate virtual relationships. A media-theoretical classification of these phenomena has so far been difficult, partly because the interactive element in the exchange with artificial intelligence has undeniable similarities to human-to-human communication but is not identical to it. The proposed study, therefore, aims to reformulate the concept of symbolic interaction in the tradition of George Herbert Mead as symbolic interactivity in communication with chatbots. In particular, Mead's socio-psychological considerations will be brought into dialog with the specific conditions of digital media, the special dispositive situation of chatbots and the characteristics of artificial intelligence. One example that illustrates this particular communication situation with chatbots is so-called consensus fiction: In face-to-face communication, we use symbols on the assumption that they will be interpreted in the same or a similar way by the other person. When briefing a chatbot, it quickly becomes clear that this is by no means the case: only the bot's response shows whether the initial request corresponds to the sender's actual intention. This makes it clear that chatbots do not just respond to requests. Rather, they function equally as projection surfaces for their communication partners but also as distillations of generalized social attitudes. The personalities of the chatbot avatars result, on the one hand, from the way we behave towards them and, on the other, from the content we have learned in advance. Similarly, we interpret the response behavior of the chatbots and make it the subject of our own actions with them. In conversation with the virtual chatbot, we enter into a dialog with ourselves but also with the content that the chatbot has previously learned. In our exchanges with chatbots, we, therefore, interpret socially influenced signs and behave towards them in an individual way according to the conditions that the medium deems acceptable. This leads to the emergence of situationally determined digital identities that are in exchange with the real self but are not identical to it: In conversation with digital chatbots, we bring our own impulses, which are brought into permanent negotiation with a generalized social attitude by the chatbot. This also leads to numerous media-ethical follow-up questions. The proposed approach is a continuation of my dissertation on moral decision-making in so-called interactive films. In this dissertation, I attempted to develop a concept of symbolic interactivity based on Mead. Current developments in artificial intelligence are now opening up new areas of application.

Keywords: artificial intelligence, chatbot, media theory, symbolic interactivity

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Authors: Hervice Roméo Fogno Fotsoa, Germaine Djuidje Kenmoe, Claude Vidal Aloyem Kazé

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One of the main applications of machine learning is the prediction of time series. But a more accurate prediction requires a more optimal model of machine learning. Several optimization techniques have been developed, but without considering the input variables disposition of the system. Thus, this work aims to present a new machine learning architecture optimization technique based on their optimal input variables disposition. The validations are done on the prediction of wind time series, using data collected in Cameroon. The number of possible dispositions with four input variables is determined, i.e., twenty-four. Each of the dispositions is used to perform the prediction, with the main criteria being the training and prediction performances. The results obtained from a static architecture and a dynamic architecture of neural networks have shown that these performances are a function of the input variable's disposition, and this is in a different way from the architectures. This analysis revealed that it is necessary to take into account the input variable's disposition for the development of a more optimal neural network model. Thus, a new neural network training algorithm is proposed by introducing the search for the optimal input variables disposition in the traditional back-propagation algorithm. The results of the application of this new optimization approach on the two single neural network architectures are compared with the previously obtained results step by step. Moreover, this proposed approach is validated in a collaborative optimization method with a single objective optimization technique, i.e., genetic algorithm back-propagation neural networks. From these comparisons, it is concluded that each proposed model outperforms its traditional model in terms of training and prediction performance of time series. Thus the proposed optimization approach can be useful in improving the accuracy of time series forecasts. This proves that the proposed optimization approach can be useful in improving the accuracy of time series prediction based on machine learning.

Keywords: input variable disposition, machine learning, optimization, performance, time series prediction

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Authors: Kartina Sury Kariman

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Brand-to-customer (B2C) engagement has been well established through the traditional platform such as direct sales, advertising, customer service center, customer hotline as well as brand usage experiences. Increasingly, interest to B2C has evolved to include customer-to-customer (C2C) interaction analysis aligned with the vast growth of web 2.0. Hence, discussion on C2C interaction and brand strategy have captured social media as it enables brands and C2C interaction to be connected in various ways, providing opportunities for marketers to shape their brand engagement strategy while reaching C2C as the targeted outcomes. The objective here is to provide a preliminary review of C2C interaction consisting the antecedents and consequences while highlighting areas of research interest within the context from marketers perspective and the business outcomes. This paper discusses how C2C interaction defines marketers’ brand and communication strategy and how social media trend shapes the strategy when promoting the awareness of life insurance industry and educating the target market.

Keywords: social media, brand engagement, customer interaction, customer engagement, brand strategy, life insurance

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Authors: Dyah Titisari Widyastuti

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Rail-station area development that is based on the concept of TOD (Transit Oriented Development) is principally oriented to pedestrian accessibility for daily mobility. The aim of this research is elaborating how far the existing physical elements of a rail-station district could facilitate pedestrian mobility and establish a pedestrian friendly district toward implementation of a TOD concept. This research was conducted through some steps: (i) mapping the rail-station area pedestrian sidewalk and pedestrian network as well as activity nodes and transit nodes, (ii) assessing the level of pedestrian sidewalk connectivity joining trip origin and destination. The research area coverage in this case is limited to walking distance of the rail station (around 500 meters or 10-15 minutes walking). The findings of this research on the current condition of the street and pedestrian sidewalk network and connectivity, show good preference for the foot modal share (more than 50%) is achieved. Nevertheless, it depends on the distance from the trip origin to destination.

Keywords: accessibility of daily mobility, pedestrian-friendly district, rail-station district, transit oriented development

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Authors: Wann-Ming Wey

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In recent years, in addition to face the external threats such as energy shortages and climate change, traffic congestion and environmental pollution have become anxious problems for many cities. Considering private automobile-oriented urban development had produced many negative environmental and social impacts, the transit-oriented development (TOD) has been considered as a sustainable urban model. TOD encourages public transport combined with friendly walking and cycling environment designs, however, non-motorized modes help improving human health, energy saving, and reducing carbon emissions. Due to environmental changes often affect the planners’ decision-making; this research applies dynamic network process (DNP) which includes the time dependent concept to promoting friendly walking and cycling environmental designs as an advanced planning support system for environment improvements. This research aims to discuss what kinds of design strategies can improve a friendly walking and cycling environment under TOD. First of all, we collate and analyze environment designing factors by reviewing the relevant literatures as well as divide into three aspects of “safety”, “convenience”, and “amenity” from fifteen environment designing factors. Furthermore, we utilize fuzzy Delphi Technique (FDT) expert questionnaire to filter out the more important designing criteria for the study case. Finally, we utilized DNP expert questionnaire to obtain the weights changes at different time points for each design criterion. Based on the changing trends of each criterion weight, we are able to develop appropriate designing strategies as the reference for planners to allocate resources in a dynamic environment. In order to illustrate the approach we propose in this research, Taipei city as one example has been used as an empirical study, and the results are in depth analyzed to explain the application of our proposed approach.

Keywords: environment planning support systems, walking and cycling, transit-oriented development (TOD), dynamic network process (DNP)

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Authors: Ziwei Xu

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The increasing emphasis on mobility has driven the application of innovative communication technologies across various industries. In the retail sector, Near Field Communication (NFC) has emerged as a significant and transformative technology, particularly in the payment and retail supermarket sectors. NFC enables new payment methods, such as electronic wallets, and enhances information management in supermarkets, contributing to the growth of the trade. This report presents a comprehensive analysis of NFC technology, focusing on five key aspects. Firstly, it provides an overview of NFC, including its application methods and development history. Additionally, it incorporates Arthur's work on combinatorial evolution to elucidate the emergence and impact of NFC technology, while acknowledging the limitations of the model in analyzing NFC. The report then summarizes the positive influence of NFC on the retail industry along with its associated constraints. Furthermore, it explores the adoption of NFC from both organizational and individual perspectives, employing the Best Predictors of organizational IT adoption and UTAUT2 models, respectively. Finally, the report discusses the potential future replacement of NFC with biometrics technology, highlighting its advantages over NFC and leveraging Arthur's model to investigate its future development prospects.

Keywords: innovation, NFC, industry, biometrics

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Authors: Tamás Matuszka, Attila Kiss

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Due the proliferation of smartphones in everyday use, several different outdoor navigation systems have become available. Since these smartphones are able to connect to the Internet, the users can obtain location-based information during the navigation as well. The users could interactively get to know the specifics of a particular area (for instance, ancient cultural area, Statue Park, cemetery) with the help of thus obtained information. In this paper, we present an Augmented Reality system which uses Semantic Web technologies and is based on the interaction between the user and the smartphone. The system allows navigating through a specific area and provides information and details about the sight an interactive manner.

Keywords: augmented reality, semantic web, human computer interaction, mobile application

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Authors: Ayu Nabila Kusuma Pradana, Aprinaldi Jasa Mantau, Tomohiko Akahoshi

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The incidence of Disseminated intravascular coagulation (DIC) following gastrointestinal surgery has a poor prognosis. Therefore, it is important to determine the factors that can predict the prognosis of DIC. This study will investigate the factors that may influence the outcome of DIC in patients after gastrointestinal surgery. Eighty-one patients were admitted to the intensive care unit after gastrointestinal surgery in Kyushu University Hospital from 2003 to 2021. Acute DIC scores were estimated using the new Japanese Association for Acute Medicine (JAAM) score from before and after surgery from day 1, day 3, and day 7. Acute DIC scores will be compared with The Sequential Organ Failure Assessment (SOFA) score, platelet count, lactate level, and a variety of biochemical parameters. This study applied machine learning algorithms to predict the prognosis of DIC after gastrointestinal surgery. The results of this study are expected to be used as an indicator for evaluating patient prognosis so that it can increase life expectancy and reduce mortality from cases of DIC patients after gastrointestinal surgery.

Keywords: the survival rate, gastrointestinal surgery, JAAM score, neural network, machine learning, disseminated intravascular coagulation (DIC)

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Authors: Rafika Bibi, Khaled Khaladi, Hind Mokran, Mohamed Salah Boukhechem

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A high performance liquid chromatographic method with ultraviolet detection at 264nm was developed and validate for quantitative determination and separation of cefazolin and cefotaxime in urine, the mobile phase consisted of acetonitrile and phosphate buffer pH4,2(15 :85) (v/v) pumped through ODB 250× 4,6 mm, 5um column at a flow rate of 1ml/min, loop of 20ul. In this condition, the validation of this technique showed that it is linear in a range of 0,01 to 10ug/ml with a good correlation coefficient ( R>0,9997), retention time of cefotaxime, cefazolin was 9.0, 10.1 respectively, the statistical evaluation of the method was examined by means of within day (n=6) and day to day (n=5) and was found to be satisfactory with high accuracy and precision.

Keywords: cefazolin, cefotaxime, HPLC, bioscience, biochemistry, pharmaceutical

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Authors: Chaudhary Muhammad Aqdus Ilyas, Matthias Rehm, Kamal Nasrollahi, Thomas B. Moeslund

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This paper presents the investigation of data collection procedures, associated with robots when placed with traumatic brain injured (TBI) patients for rehabilitation purposes through facial expression and mood analysis. Rehabilitation after TBI is very crucial due to nature of injury and variation in recovery time. It is advantageous to analyze these emotional signals in a contactless manner, due to the non-supportive behavior of patients, limited muscle movements and increase in negative emotional expressions. This work aims at the development of framework where robots can recognize TBI emotions through facial expressions to perform rehabilitation tasks by physical, cognitive or interactive activities. The result of these studies shows that with customized data collection strategies, proposed framework identify facial and emotional expressions more accurately that can be utilized in enhancing recovery treatment and social interaction in robotic context.

Keywords: computer vision, convolution neural network- long short term memory network (CNN-LSTM), facial expression and mood recognition, multimodal (RGB-thermal) analysis, rehabilitation, robots, traumatic brain injured patients

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Authors: Young Gil Kim, Hye Min Park, Chan Jong Park, Koan Sik Joo

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A personal gamma spectrometer has to be sensitive, pocket-sized, and carriable on the users. To serve these requirements, we developed the SiPM-based portable radiation detectors. The prototype uses a Ce:GAGG scintillator coupled to a silicon photomultiplier and a radio frequency(RF) module to measure gamma-ray, and can be accessed wirelessly or remotely by mobile equipment. The prototype device consumes roughly 4.4W, weighs about 180g (including battery), and measures 5.0 7.0. It is able to achieve 5.8% FWHM energy resolution at 662keV.

Keywords: Ce:GAGG, gamma-ray, radio frequency, silicon photomultiplier

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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: Wang Yichen, Haruka Yamashita

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In recent years, in the field of sports, decision making such as member in the game and strategy of the game based on then analysis of the accumulated sports data are widely attempted. In fact, in the NBA basketball league where the world's highest level players gather, to win the games, teams analyze the data using various statistical techniques. However, it is difficult to analyze the game data for each play such as the ball tracking or motion of the players in the game, because the situation of the game changes rapidly, and the structure of the data should be complicated. Therefore, it is considered that the analysis method for real time game play data is proposed. In this research, we propose an analytical model for "determining the optimal lineup composition" using the real time play data, which is considered to be difficult for all coaches. In this study, because replacing the entire lineup is too complicated, and the actual question for the replacement of players is "whether or not the lineup should be changed", and “whether or not Small Ball lineup is adopted”. Therefore, we propose an analytical model for the optimal player selection problem based on Small Ball lineups. In basketball, we can accumulate scoring data for each play, which indicates a player's contribution to the game, and the scoring data can be considered as a time series data. In order to compare the importance of players in different situations and lineups, we combine RNN (Recurrent Neural Network) model, which can analyze time series data, and NN (Neural Network) model, which can analyze the situation on the field, to build the prediction model of score. This model is capable to identify the current optimal lineup for different situations. In this research, we collected all the data of accumulated data of NBA from 2019-2020. Then we apply the method to the actual basketball play data to verify the reliability of the proposed model.

Keywords: recurrent neural network, players lineup, basketball data, decision making model

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Authors: Sana Maidullah, Ankita Sharma

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The present study takes naturalistic decision-making approach to examine the role of personality in information processing in consumer decision making. In the technological era, most of the information comes in form of HTML or similar language via the internet; processing of this situation could be ambiguous, laborious and painful. The present study explores the role of impulsivity in creating an extreme effect on consumer decision making. Specifically, the study explores the role of impulsivity in extreme effect, i.e., extremeness avoidance (compromise effect) and extremeness seeking; the role of demographic variables, i.e. age and gender, in the relation between impulsivity and extreme effect. The study was conducted with the help of a questionnaire and two experiments. The experiment was designed in the form of two shopping websites with two product types: Hotel choice and Mobile choice. Both experimental interfaces were created with the Xampp software, the frontend of interfaces was HTML CSS JAVASCRIPT and backend was PHP MySQL. The mobile experiment was designed to measure the extreme effect and hotel experiment was designed to measure extreme effect with alignability of attributes. To observe the possibilities of the combined effect of individual difference and context effects, the manipulation of price, a number of alignable attributes and number of the non-alignable attributes is done. The study was conducted on 100 undergraduate and post-graduate engineering students within the age range of 18-35. The familiarity and level of use of internet and shopping website were assessed and controlled in the analysis. The analysis was done by using a t-test, ANOVA and regression analysis. The results indicated that the impulsivity leads to compromise effect and at the same time it also increases the relationship between alignability of attribute among choices and the compromise effect. The demographic variables were found to play a significant role in the relationship. The subcomponents of impulsivity were significantly influencing compromise effect, but the cognitive impulsivity was significant for women, and motor impulsivity was significant for males only. The impulsivity was significantly positively predicted by age, though there were no significant gender differences in impulsivity. The results clearly indicate the importance of individual factors in decision making. The present study, with precise and direct results, provides a significant suggestion for market analyst and business providers.

Keywords: impulsivity, extreme effect, personality, alignability, consumer decision making

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Authors: Rung-Shiang Cheng, Wei-Jun Hong, Jheng-Syun Wang, Kawuu W. Lin

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Users rely increasingly on Location-Based Services (LBS) and automated navigation/guidance systems nowadays. However, while such services are easily implemented in outdoor environments using Global Positioning System (GPS) technology, a requirement still exists for accurate localization and guidance schemes in indoor settings. Accordingly, the present study presents a methodology based on GPS, Bluetooth Low Energy (BLE) beacons, and Near Field Communication (NFC) technology. Through establishing graphic information and the design of algorithm, this study develops a guidance system for indoor and outdoor on smartphones, with aim to provide users a smart life through this system. The presented system is implemented on a smartphone and evaluated on a student campus environment. The experimental results confirm the ability of the presented app to switch automatically from an outdoor mode to an indoor mode and to guide the user to the requested target destination via the shortest possible route.

Keywords: beacon, indoor, BLE, Dijkstra algorithm

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Authors: Yaxiao Zhang, Yangzhou Chen

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This study investigate the formation problem for high-order continuous-time multi-robot with bounded symmetric time-varying delay protocol under switched directed communication topology. By using a linear transformation, the formation problem is transformed to stability analysis of a switched delay system. Under the assumption that each communication topology has a directed spanning tree, sufficient conditions are presented in terms of linear matrix inequalities (LMIs) that the multi-robot system can achieve a desired formation by the trade-off among the pre-exist topologies with the help of the scheme of average dwell time. A numeral example is presented to illustrate the effectiveness of the obtained results.

Keywords: multi-robot systems, formation, switched directed topology, symmetric time-varying delay, average dwell time, linear matrix inequalities (lmis)

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Authors: Kim Lytle, Tim Talty, Alan Michaels, Jeff Reed

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Implantable medical devices (IMDs) are medically necessary devices embedded in the human body that monitor chronic disorders or automatically deliver therapies. Most IMDs have wireless capabilities that allow them to share data with an offboard programming device to help medical providers monitor the patient’s health while giving the patient more insight into their condition. However, serious security concerns have arisen as researchers demonstrated these devices could be hacked to obtain sensitive information or harm the patient. Cooperative jamming can be used to prevent privileged information leaks by maintaining an adequate signal-to-noise ratio at the intended receiver while minimizing signal power elsewhere. This paper uses ray tracing to demonstrate how a low number of friendly nodes abiding by Bluetooth Low Energy (BLE) transmission regulations can enhance IMD communication security in an office environment, which in turn may inform how companies and individuals can protect their proprietary and personal information.

Keywords: implantable biomedical devices, communication system security, array signal processing, ray tracing

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Authors: Wenxuan Li, Lei Li, Jin Li, Yuanhang He

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This paper designed a secure chip for IoT communication security integrated with the PUF-based firmware protection scheme. Then, the Xilinx Kintex-7 and STM-32 were used for the prototype verification. Firmware protection worked well on FPGA and embedded platforms. For the ASIC implementation of the PUF module, contact PUF is chosen. The post-processing method and its improvement are analyzed with emphasis. This paper proposed a more efficient post-processing method for contact PUF named SXOR, which has practical value for realizing lightweight security modules in IoT devices. The analysis was carried out under the hypothesis that the contact holes are independent and combine the existing data in the open literature. The post-processing effects of SXOR and XOR are basically the same under the condition that the proposed post-processing circuit occupies only 50.6% of the area of XOR. The average Hamming weight of the PUF output bit sequence obtained by the proposed post-processing method is 0.499735, and the average Hamming weight obtained by the XOR-based post-processing method is 0.499999.

Keywords: PUF, IoT, authentication, secure communication, encryption, XOR

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Authors: Denise Levy, Anna Lucia C. H. Villavicencio

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Food irradiation is a processing and preservation technique to eliminate insects and parasites and reduce disease-causing microorganisms. Moreover, the process helps to inhibit sprouting and delay ripening, extending fresh fruits and vegetables shelf-life. Nevertheless, most Brazilian consumers seem to misunderstand the difference between irradiated food and radioactive food and the general public has major concerns about the negative health effects and environmental contamination. Society´s judgment and decision making are directly linked to perceived benefits and risks. The web-based project entitled ‘Scientific information about food irradiation: Internet as a tool to approach science and society’ was created by the Nuclear and Energetic Research Institute (IPEN), in order to offer an interdisciplinary approach to science education, integrating economic, ethical, social and political aspects of food irradiation. This project takes into account that, misinformation and unfounded preconceived ideas impact heavily on the acceptance of irradiated food and purchase intention by the Brazilian consumer. Taking advantage of the potential value of the Internet to enhance communication and education among general public, a research study was carried out regarding the possibilities and trends of Information and Communication Technologies among the Brazilian population. The content includes concepts, definitions and Frequently Asked Questions (FAQ) about processes, safety, advantages, limitations and the possibilities of food irradiation, including health issues, as well as its impacts on the environment. The project counts on eight self-instructional interactive web courses, situating scientific content in relevant social contexts in order to encourage self-learning and further reflections. Communication is a must to improve public understanding of science. The use of information technology for quality scientific divulgation shall contribute greatly to provide information throughout the country, spreading information to as many people as possible, minimizing geographic distances and stimulating communication and development.

Keywords: food irradiation, multimedia learning tools, nuclear science, society and education

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Authors: Odile Amoncou, Djedje-Kossu Zahui

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The increased demand for digital communications during the COVID-19 pandemic has seen an unprecedented surge in new telecom infrastructure around the world. The expansion has been more remarkable in countries with developing telecom infrastructures. Particularly, the three telecom operators in Cote d’Ivoire, Orange CI, MTN CI, and MOOV Africa, have considerably scaled up their exploitation technologies and capacities in terms of towers, fiber optic installation, and customer service hubs. The trend will likely continue upward while expanding the carbon footprint of the Ivorian telecom operators. Therefore, the corporate social and environmental responsibilities of these telecommunication companies can no longer be overlooked. This paper assesses the sustainability of the three Ivorian telecommunication network operators by applying a combination of commonly used sustainability management indexes. These tools are streamlined and adapted to the relatively young and developing digital network of Cote D’Ivoire. We trust that this article will push the respective CEOs to make sustainability a top strategic priority and understand the substantial potential returns in terms of saving, new products, and new clients while improving their corporate image. In addition, good sustainability management can increase their stakeholders.

Keywords: sustainability of telecom operators, sustainability management index, carbon footprint, digital communications

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Authors: Jonghoon Chun, Insung Kim, Jonghyun Lim, Gun Ro

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We believe that it is possible to provide a solution to reduce patient safety accidents by displaying correct medical records and prescription information through interactive patient identification. Our system is based on the use of smart bands worn by patients and these bands communicate with the hybrid gateways which understand both BLE and Wifi communication protocols. Through the convergence of low-power Bluetooth (BLE) and hybrid gateway technology, which is one of short-range wireless communication technologies, we implement ‘Intelligent Patient Identification and Location Tracking System’ to prevent medical malfunction frequently occurring in medical institutions. Based on big data and IOT technology using MongoDB, smart band (BLE, NFC function) and hybrid gateway, we develop a system to enable two-way communication between medical staff and hospitalized patients as well as to store locational information of the patients in minutes. Based on the precise information provided using big data systems, such as location tracking and movement of in-hospital patients wearing smart bands, our findings include the fact that a patient-specific location tracking algorithm can more efficiently operate HIS (Hospital Information System) and other related systems. Through the system, we can always correctly identify patients using identification tags. In addition, the system automatically determines whether the patient is a scheduled for medical service by the system in use at the medical institution, and displays the appropriateness of the medical treatment and the medical information (medical record and prescription information) on the screen and voice. This work was supported in part by the Korea Technology and Information Promotion Agency for SMEs (TIPA) grant funded by the Korean Small and Medium Business Administration (No. S2410390).

Keywords: BLE, hybrid gateway, patient identification, IoT, safety management, smart band

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Authors: Reza Safdari, Goli Arji, Robab Abdolkhani Maryam zahmatkeshan

Abstract:

Background and purpose: Cardiovascular diseases are among the most common diseases in all societies. The most important step in minimizing myocardial infarction and its complications is to minimize its risk factors. The amount of medical data is increasingly growing. Medical data mining has a great potential for transforming these data into information. Using data mining techniques to generate predictive models for identifying those at risk for reducing the effects of the disease is very helpful. The present study aimed to collect data related to risk factors of heart infarction from patients’ medical record and developed predicting models using data mining algorithm. Methods: The present work was an analytical study conducted on a database containing 350 records. Data were related to patients admitted to Shahid Rajaei specialized cardiovascular hospital, Iran, in 2011. Data were collected using a four-sectioned data collection form. Data analysis was performed using SPSS and Clementine version 12. Seven predictive algorithms and one algorithm-based model for predicting association rules were applied to the data. Accuracy, precision, sensitivity, specificity, as well as positive and negative predictive values were determined and the final model was obtained. Results: five parameters, including hypertension, DLP, tobacco smoking, diabetes, and A+ blood group, were the most critical risk factors of myocardial infarction. Among the models, the neural network model was found to have the highest sensitivity, indicating its ability to successfully diagnose the disease. Conclusion: Risk prediction models have great potentials in facilitating the management of a patient with a specific disease. Therefore, health interventions or change in their life style can be conducted based on these models for improving the health conditions of the individuals at risk.

Keywords: decision trees, neural network, myocardial infarction, Data Mining

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Authors: Amartya Hatua, Trung Nguyen, Andrew Sung

Abstract:

In this paper, we study the information diffusion process on Twitter as a multivariate time series problem. Our model concerns three measures (volume, network influence, and sentiment of tweets) based on 10 features, and we collected 27 million tweets to build our information diffusion time series dataset for analysis. Then, different time series clustering techniques with Dynamic Time Warping (DTW) distance were used to identify different patterns of information diffusion. Finally, we built the information diffusion prediction models for new hashtags which comprise two phrases: The first phrase is recognizing the pattern using k-NN with DTW distance; the second phrase is building the forecasting model using the traditional Autoregressive Integrated Moving Average (ARIMA) model and the non-linear recurrent neural network of Long Short-Term Memory (LSTM). Preliminary results of performance evaluation between different forecasting models show that LSTM with clustering information notably outperforms other models. Therefore, our approach can be applied in real-world applications to analyze and predict the information diffusion characteristics of selected topics or memes (hashtags) in Twitter.

Keywords: ARIMA, DTW, information diffusion, LSTM, RNN, time series clustering, time series forecasting, Twitter

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Authors: Shazia Anwer

Abstract:

This paper has discussed the unusual form of resistance in theatre against censorship board in Pakistan. The atypical approach of dramaturgy created massive space for performers and audiences to integrate and communicate. The social and religious absolutes creates suffocation in Pakistani society, strict control over all Fine and Performing Art has made art political, contemporary dramatics has started an amalgamated theatre to avoid censorship. Contemporary Punjabi theatre techniques are directly dependent on human cognition. The idea of indirect thought processing is not unique but dependent on spectators. The paper has provided an account of these techniques and their specific use for conveying specific messages across the audiences. For the Dramaturge of today, theatre space is an expression representing a linguistic formulation that includes qualities of experimental and non-traditional use of classical theatrical space in the context of fulfilling the concept of open theatre. Paper has explained the transformation of the theatrical experience into an event where the actor and the audience are co-existing and co-experiencing the dramatical experience. The denial of the existence of the 4th -Wall made two-way communication possible. This paper has elaborated that the previously marginalized genres such as naach, jugat, miras, are extensively included to counter the censorship board. Figurativeness, visual elements, allegory, scenic imagery are basic support system for contemporary Punjabi theatre. The body of the actor is used as a source for non-verbal communication, and for an escape from traditional theatrical space which by every means has every element that could be controlled and reprimanded by the controlling authority.

Keywords: communication, Punjabi theatre, figurativeness, censorship

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Authors: Hassam Hassan Elborombaly

Abstract:

The pollution generated from transportation modes, congestion and traffic heritage has led to the deterioration of historic buildings and the urban heritage in historic cities. Accordingly, this paper attempts to diagnose the transport and traffic problems in historic cities. In general and in Heritage Cities, and to investigate methods for conserving the urban heritage from negative effects of traffic congestion and of the traditional red modes of transportation. It also attempts to explore possible areas for intervention to mitigate transportation and traffic problems in the light of the principles of the sustainable transportation framework. It aims to draw conclusion and propose recommendation that would increase the efficiency and effectiveness of transportation plans in historic Cairo and consequently achieve sustainable transportation. Problems In historic cities public paths compose an irregular network enclosing large residential plots (defined as super blocks quarters or hettas). The blocks represent the basic morphology units in historic Cities. Each super block incorporates several uses (i.e. residential, non-residential, service uses and others). Local paths reach the interior of the super blocks in an organized inter core, which deals mainly with residential functions mixed with handicraft activities and is composed of several local path units; (b) the other core, which is bound by the public paths and contains a combination of residential, commercial and social activities. Objectives: 1- To provide amenity convenience and comfort for visitors and people who live and work in the area. Pedestrianizing, accessibility and safety are to be reinforced while respecting the organic urban pattern. 2- To enhance street life, vitality and activity, in order to attract people and increase economic prosperity. Research Contents • Relation between residential areas and transportation in the inner core • Analytical studies for historic areas in heritage cities • Sustainable transportation planning in heritage cities • Dynamic and flexible methodology for achieving sustainable transportation network for the Heritage Cities • Result and Recommendation

Keywords: irregular network, public paths, sustainable transportation, urban heritage

Procedia PDF Downloads 512