Abstract: The impact of COVID-19 has a significant effect on all sectors of society globally. Health information technology (HIT) has become an effective health strategy in this age of distancing. In this regard, Mobile Health (mHealth) plays a critical role in managing patient and provider workflows during the COVID-19 pandemic. Therefore, the users' perception of service quality about mHealth services plays a significant role in shaping confidence and subsequent behaviors regarding the mHealth users' intention of use. This study's objective was to explore levels of user attributes analyzed by a qualitative method of how health practitioners and patients are satisfied or dissatisfied with using mHealth services; and analyzed the users' intention in the context of Taiwan during the COVID-19 pandemic. This research explores the experienced usability of a mHealth services during the Covid-19 pandemic. This study uses qualitative methods that include in-depth and semi-structured interviews that investigate participants' perceptions and experiences and the meanings they attribute to them. The five cases consisted of health practitioners, clinic staff, and patients' experiences using mHealth services. This study encourages participants to discuss issues related to the research question by asking open-ended questions, usually in one-to-one interviews. The findings show the positive and negative attributes of mHealth service quality. Hence, the significant importance of patients' and health practitioners' issues on several dimensions of perceived service quality is system quality, information quality, and interaction quality. A concept map for perceptions regards to emergency uses' intention of mHealth services process is depicted. The findings revealed that users pay more attention to "Medical care", "ease of use" and "utilitarian benefits" and have less importance for "Admissions and Convenience" and "Social influence". To improve mHealth services, the mHealth providers and health practitioners should better manage users' experiences to enhance mHealth services. This research contributes to the understanding of service quality issues in mHealth services during the COVID-19 pandemic.
Abstract: The Mobile field hospital is critical in terms of managing emergencies in crisis. It is a sub-section of the main hospitals and the health sector, tasked with delivering responsive, immediate, and efficient medical services during a crisis. With the aim to prevent further crisis, the assessment of the cyber assets follows different methods, to distinguish its strengths and weaknesses, and in turn achieve cyber resiliency. The work focuses on assessments of cyber resilience in field hospitals with trends growing in both the field hospital and the health sector in general. This creates opportunities for the adverse attackers and the response improvement objectives for attaining cyber resilience, as the assessments allow users and stakeholders to know the level of risks with regards to its cyber assets. Thus, the purpose is to show the possible threat vectors which open up opportunities, with contrast to current trends in the assessment of the mobile field hospitals’ cyber assets.
Abstract: Tourism is considered an important sector for most countries, while maintaining good tourism attractions can promote national economic development. The State of Palestine is historically considered a wealthy country full of many archaeological places. In the city of Bethlehem, for example, the Church of the Nativity is the most important touristic site, but it does not have enough technology development to attract tourists. In this paper, we propose a smart mobile application named “Pal-STAR” (Palestine Smart Tourist Augmented Reality) as an innovative solution which targets tourists and assists them to make a visit inside the Church of the Nativity. The application will use augmented reality and feature a virtual tourist guide showing views of the church while providing historical information in a smart, easy, effective and user-friendly way. The proposed application is compatible with multiple mobile platforms and is considered user friendly. The findings show that this application will improve the practice of the tourism sector in the Holy Land, it will also increase the number of tourists visiting the Church of the Nativity and it will facilitate access to historical data that have been difficult to obtain using traditional tourism guidance. The value that tourism adds to a country cannot be denied, and the more technological advances are incorporated in this sector, the better the country’s tourism sector can be served. Palestine’s economy is heavily dependent on tourism in many of its main cities, despite several limitations, and technological development is needed to enable this sector to flourish. The proposed mobile application would definitely have a good impact on the development of the tourism sector by creating an Augmented Reality environment for tourists inside the church, helping them to navigate and learn about holy places in a non-traditional way, using a virtual tourist guide.
Abstract: The advent of the Internet, mobile devices and social media is revolutionizing the experience of retail customers by linking multiple sources through various channels. Omnichannel retailing is a retailing that combines multiple channels to allow customers to seamlessly leverage all the distribution information online and offline while shopping. Therefore, today data are an asset more critical than ever for all organizations. Nonetheless, because of its heterogeneity through platforms, developers are currently facing difficulties in dealing with personal data. Considering the possibilities of omnichannel communication, this paper presents channel categorization that could enhance the customer experience of omnichannel center called hyper center. The purpose of this paper is fundamentally to describe the connection between the omnichannel hyper center and the customer, with particular attention to privacy protection. The first phase was finding the most appropriate channels of communication for hyper center. Consequently, a selection of widely used communication channels has been identified and analyzed with regard to the effect requirements for optimizing user experience. The evaluation criteria are divided into 3 groups: general, user profile and channel options. For each criterion the weight of importance for omnichannel communication was defined. The most important thing was to consider how the hyper center can make user identification while respecting the privacy protection requirements. The study carried out also shows what customer experience across digital networks would look like, based on an omnichannel approach owing to privacy protection principles.
Abstract: Over the past 20 years, internet has seen continual advancement and with the advent of online technology, various types of web-based games have been developed. Games are frequently being used among different age groups from baby boomers to generation Z. Games are not only used for entertainment but also utilized as a learning approach transmitting education to a level that is more interesting and effective for students. One of the popular web-based education games is Kahoot with growing popularity and usage, which is being used in different fields of studies. However, little knowledge is available on university students’ perception of Kahoot environment and application for learning subjects. Hence, the objective of the current study is to investigate students’ perceptions of Kahoot application and environment as a learning tool. The study employed a survey approach by distributing Google Forms –created questionnaire, with high level of reliability index, to 62 students (11 males and 51 females). The findings show that students have positive attitudes towards Kahoot application and its environment for learning. Regarding Kahoot application, it was indicated that activities created using Kahoot are more interesting for students, Kahoot is useful for collaborative learning, and Kahoot enhances interest in learning lesson. In terms of Kahoot environment, it was found that using this application through mobile is easy for students, its design is simple and useful, Kahoot-created activities can easily be shared, and the application can easily be used on any platform. The findings of the study have implications for instructors, policymakers and curriculum developers.
Abstract: With the increased utilization of technology devices around the world, healthcare and medical diagnosis are critical issues that people worry about these days. Doctors are doing their best to avoid any medical errors while diagnosing diseases and prescribing the wrong medication. Subsequently, artificial intelligence applications that can be installed on mobile devices such as rule-based expert systems facilitate the task of assisting doctors in several ways. Due to their many advantages, the usage of expert systems has increased recently in health sciences. This work presents a backward rule-based expert system that can be used for a headache diagnosis and medication recommendation system. The structure of the system consists of three main modules, namely the input unit, the processing unit, and the output unit.
Abstract: Today’s International Service Learning practices require an update: modern technologies, fresh educational frameworks, and a new operating system to accountably prosper. This paper describes a model of International Service Learning (ISL), which combines current technological hardware, electronic platforms, and asynchronous communications that are grounded in inclusive pedagogy. This model builds on the work around collaborative field trip learning, extending the reach to international partnerships across continents. Mobile technology, 21st century skills and summit-basecamp modeling intersect to support novel forms of learning that tread lightly on fragile natural ecosystems, affirm local reciprocal partnership in projects, and protect traveling participants from common yet avoidable cultural pitfalls.
Abstract: The reason for conducting this research is to develop an algorithm that is capable of classifying news articles from the automobile industry, according to the competitive actions that they entail, with the use of Text Mining (TM) methods. It is needed to test how to properly preprocess the data for this research by preparing pipelines which fits each algorithm the best. The pipelines are tested along with nine different classification algorithms in the realm of regression, support vector machines, and neural networks. Preliminary testing for identifying the optimal pipelines and algorithms resulted in the selection of two algorithms with two different pipelines. The two algorithms are Logistic Regression (LR) and Artificial Neural Network (ANN). These algorithms are optimized further, where several parameters of each algorithm are tested. The best result is achieved with the ANN. The final model yields an accuracy of 0.79, a precision of 0.80, a recall of 0.78, and an F1 score of 0.76. By removing three of the classes that created noise, the final algorithm is capable of reaching an accuracy of 94%.
Abstract: This paper presents the results of a mechatronic design based on a 4-wheel omnidirectional mobile robot that can be used in indoor logistic applications. The low-level control has been selected using two open-source hardware (Raspberry Pi 3 Model B+ and Arduino Mega 2560) that control four industrial motors, four ultrasound sensors, four optical encoders, a vision system of two cameras, and a Hokuyo URG-04LX-UG01 laser scanner. Moreover, the system is powered with a lithium battery that can supply 24 V DC and a maximum current-hour of 20Ah.The Robot Operating System (ROS) has been implemented in the Raspberry Pi and the performance is evaluated with the selection of the sensors and hardware selected. The mechatronic system is evaluated and proposed safe modes of power distribution for controlling all the electronic devices based on different tests. Therefore, based on different performance results, some recommendations are indicated for using the Raspberry Pi and Arduino in terms of power, communication, and distribution of control for different devices. According to these recommendations, the selection of sensors is distributed in both real-time controllers (Arduino and Raspberry Pi). On the other hand, the drivers of the cameras have been implemented in Linux and a python program has been implemented to access the cameras. These cameras will be used for implementing a deep learning algorithm to recognize people and objects. In this way, the level of intelligence can be increased in combination with the maps that can be obtained from the laser scanner.
Abstract: Traffic control has been one of the most common and irritating problems since the time automobiles have hit the roads. Problems like traffic congestion have led to a significant time burden around the world and one significant solution to these problems can be the proper implementation of the Intelligent Transport System (ITS). It involves the integration of various tools like smart sensors, artificial intelligence, position technologies and mobile data services to manage traffic flow, reduce congestion and enhance driver's ability to avoid accidents during adverse weather. Road and traffic signs’ recognition is an emerging field of research in ITS. Classification problem of traffic signs needs to be solved as it is a major step in our journey towards building semi-autonomous/autonomous driving systems. The purpose of this work focuses on implementing an approach to solve the problem of traffic sign classification by developing a Convolutional Neural Network (CNN) classifier using the GTSRB (German Traffic Sign Recognition Benchmark) dataset. Rather than using hand-crafted features, our model addresses the concern of exploding huge parameters and data method augmentations. Our model achieved an accuracy of around 97.6% which is comparable to various state-of-the-art architectures.
Abstract: MIMO-OFDM communication system presents a key
solution for the next generation of mobile communication due
to its high spectral efficiency, high data rate and robustness
against multi-path fading channels. However, MIMO-OFDM system
requires a perfect knowledge of the channel state information and
a good synchronization between the transmitter and the receiver
to achieve the expected performances. Recently, we have proposed
two algorithms for channel estimation and timing synchronization
with good performances and very low implementation complexity
compared to those proposed in the literature. In order to validate and
evaluate the efficiency of these algorithms in real environments, this
paper presents in detail the implementation of 2 × 2 MIMO-OFDM
system based on LabVIEW and USRP 2920. Implementation results
show a good agreement with the simulation results under different
configuration parameters.
Abstract: We report upon a study introducing a chatbot to develop learning communities at a London University, with a largely international student base. The focus of the chatbot was twofold; to ease the transition for students into their first year of university study, and to increase study engagement. Four learning communities were created using the chatbot; level 3 foundation, level 4 undergraduate, level 6 undergraduate and level 7 post-graduate. Students and programme leaders were provided with access to the chat bot via mobile app prior to their study induction and throughout the autumn term of 2019. At the end of the term, data were collected via questionnaires and focus groups with students and teaching staff to allow for identification of benefits and challenges. Findings indicated a positive correlation between study engagement and engagement with peers. Students reported that the chatbot enabled them to obtain support and connect to their programme leader. Both staff and students also made recommendation on how engagement could be further enhanced using the bot in terms of; clearly specified purpose, integration with existing university systems, leading by example and connectivity. Extending upon these recommendations, a second pilot study is planned for September 2020, for which the focus will be upon improving attendance rates, student satisfaction and module pass rates.
Abstract: Mass media seem to provide a rich content for language acquisition. Exposure to television, the Internet, the mobile phone and other technological gadgets and devices helps enrich the student’s lexicon positively as well as negatively. The difficulties encountered by students while learning and acquiring second languages in addition to their eagerness to comprehend the content of a particular program prompt them to diversify their methods so as to achieve their targets. The present study highlights the significance of certain media channels and their involvement in language acquisition with the employment of the Natural Approach to further grasp whether students, especially secondary and high school students, learn and acquire errors through watching subtitled television programs. The chief objective is investigating the deductive and inductive relevance of certain programs beside the involvement of peripheral learning while acquiring mistakes.
Abstract: Fiber Reinforced Polymer (FRP) composites enjoy an array of applications ranging from aerospace, marine and military to automobile, recreational and civil industry due to their outstanding properties. A structural glass fiber reinforced polymer (GFRP) composite sandwich panel made from E-glass fiber skin and a modified phenolic core has been manufactured in Australia for civil engineering applications. One of the major mechanisms of damage in FRP composites is skin-core debonding. The presence of debonding is of great concern not only because it severely affects the strength but also it modifies the dynamic characteristics of the structure, including natural frequency and vibration modes. This paper deals with the investigation of the dynamic characteristics of a GFRP beam with single and multiple debonding by finite element based numerical simulations and analyses using the STRAND7 finite element (FE) software package. Three-dimensional computer models have been developed and numerical simulations were done to assess the dynamic behavior. The FE model developed has been validated with published experimental, analytical and numerical results for fully bonded as well as debonded beams. A comparative analysis is carried out based on a comprehensive parametric investigation. It is observed that the reduction in natural frequency is more affected by single debonding than the equally sized multiple debonding regions located symmetrically to the single debonding position. Thus it is revealed that a large single debonding area leads to more damage in terms of natural frequency reduction than isolated small debonding zones of equivalent area, appearing in the GFRP beam. Furthermore, the extents of natural frequency shifts seem mode-dependent and do not seem to have a monotonous trend of increasing with the mode numbers.
Abstract: The network connectivity of medical devices is increasing at a rapid rate. Many medical devices, such as vital sign monitors, share information via wireless or wired connections. However, these connectivity options suffer from a variety of well-known limitations. Wireless connectivity, especially in the unlicensed radio frequency bands, can be disrupted. Such disruption could be due to benign reasons, such as a crowded spectrum, or to malicious intent. While wired connections are less susceptible to interference, they inhibit the mobility of the medical devices, which could be critical in a variety of scenarios. This work explores the application of Light Fidelity (Li-Fi) communication to enhance the security, performance, and mobility of medical devices in connected healthcare scenarios. A simple bridge for connected devices serves as an avenue to connect traditional medical devices to the Li-Fi network. This bridge was utilized to conduct bandwidth tests on a small Li-Fi network installed into a Mock-ICU setting with a backend enterprise network similar to that of a hospital. Mobile and stationary tests were conducted to replicate various different situations that might occur within a hospital setting. Results show that in room Li-Fi connectivity provides reasonable bandwidth and latency within a hospital like setting.
Abstract: Mobile phones are one of the main tools for promoting the wellbeing of people and supporting the integration of communities on the margins such as refugees. Information and Communication Technology has the potential to contribute towards reducing isolation, loneliness, and to assist in improving interpersonal relations and fostering acculturation processes. Therefore, the use of mobile phones by refugees might contribute to their social connectedness. This paper aims to demonstrate how existing literature has shown how the use of mobile phones by refugees should engender social connectedness amongst the refugees. Data for the study are drawn from existing literature; we searched a number of electronic databases for papers published between 2010 and 2019. The main findings of the study relate to the use of mobile phones by refugees to (i) create a sense of belonging, (ii) maintain relationships, and (iii) advance the acculturation process. The analysis highlighted a gap in the research over refugees and social connectedness. In particular, further studies should consider evaluating the differences between those who have a refugee permit, those who are waiting for the refugee permit, and those whose request was denied.
Abstract: Wireless communication technology is rapidly changing with recent developments in portable devices and communication protocols. This has generated demand for more advanced and compact antenna structures and therefore, proposed work focuses on Meander Line Antenna (MLA) design. Here, Pentaband MLA is designed on a FR4 substrate (85 mm x 40 mm) with dielectric constant (ϵr) 4.4, loss tangent (tan ) 0.018 and height 1.6 mm with coplanar feed and open stub structure. It can be operated in LTE (0.670 GHz-0.696 GHz) GPS (1.564 GHz-1.579 GHz), WCDMA (1.920 GHz-2.135 GHz), LTE UL frequency band 23 (2-2.020 GHz) and 5G (3.10 GHz-3.550 GHz) application bands. Also, it gives good performance in terms of Return Loss (RL) which is < -10 dB, impedance bandwidth with maximum Bandwidth (BW) up to 0.21 GHz and realized gains with maximum gain up to 3.28 dBi. Antenna is simulated with open stub and without open stub structures to see the effect on impedance BW coverage. In addition to this, it is checked with human hand and head phantoms to assure that it falls within specified Specific Absorption Rate (SAR) limits.
Abstract: The evolution in mobile broadband technologies has allowed to increase the download rates in users considering the current services. The evaluation of technical parameters at the link level is of vital importance to validate the quality and veracity of the connection, thus avoiding large losses of data, time and productivity. Some of these failures may occur between the eNodeB (Evolved Node B) and the user equipment (UE), so the link between the end device and the base station can be observed. LTE (Long Term Evolution) is considered one of the IP-oriented mobile broadband technologies that work stably for data and VoIP (Voice Over IP) for those devices that have that feature. This research presents a technical analysis of the connection and channeling processes between UE and eNodeB with the TAC (Tracking Area Code) variables, and analysis of performance variables (Throughput, Signal to Interference and Noise Ratio (SINR)). Three measurement scenarios were proposed in the city of Bogotá using QualiPoc, where two operators were evaluated (Operator 1 and Operator 2). Once the data were obtained, an analysis of the variables was performed determining that the data obtained in transmission modes vary depending on the parameters BLER (Block Error Rate), performance and SNR (Signal-to-Noise Ratio). In the case of both operators, differences in transmission modes are detected and this is reflected in the quality of the signal. In addition, due to the fact that both operators work in different frequencies, it can be seen that Operator 1, despite having spectrum in Band 7 (2600 MHz), together with Operator 2, is reassigning to another frequency, a lower band, which is AWS (1700 MHz), but the difference in signal quality with respect to the establishment with data by the provider Operator 2 and the difference found in the transmission modes determined by the eNodeB in Operator 1 is remarkable.
Abstract: The current and future cellular mobile communication networks generate enormous amounts of data. Networks have become extremely complex with extensive space of parameters, features and counters. These networks are unmanageable with legacy methods and an enhanced design and optimization approach is necessary that is increasingly reliant on machine learning. This paper proposes that machine learning as a viable approach for uplink throughput prediction. LTE radio metric, such as Reference Signal Received Power (RSRP), Reference Signal Received Quality (RSRQ), and Signal to Noise Ratio (SNR) are used to train models to estimate expected uplink throughput. The prediction accuracy with high determination coefficient of 91.2% is obtained from measurements collected with a simple smartphone application.
Abstract: Vehicular Adhoc Networks (VANETs), a subset of Mobile Adhoc Networks (MANETs), refers to a set of smart vehicles used for road safety. This vehicle provides communication services among one another or with the Road Side Unit (RSU). Security is one of the most critical issues related to VANET as the information transmitted is distributed in an open access environment. As each vehicle is not a source of all messages, most of the communication depends on the information received from other vehicles. To protect VANET from malicious action, each vehicle must be able to evaluate, decide and react locally on the information received from other vehicles. Therefore, message verification is more challenging in VANET because of the security and privacy concerns of the participating vehicles. To overcome security threats, we propose Monitoring Algorithm that detects malicious nodes based on the pre-selected threshold value. The threshold value is compared with the distrust value which is inherently tagged with each vehicle. The proposed Monitoring Algorithm not only detects malicious vehicles, but also isolates the malicious vehicles from the network. The proposed technique is simulated using Network Simulator2 (NS2) tool. The simulation result illustrated that the proposed Monitoring Algorithm outperforms the existing algorithms in terms of malicious node detection, network delay, packet delivery ratio and throughput, thereby uplifting the overall performance of the network.