Search results for: mobile payment system

Authors: Tomasz Kosicki

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The subject of the presentation will be the administrative and legal instruments of disciplining maintenance debtors adopted by the Polish legislator, the substantive legal bases of which were adopted in the Act of 7 September 2007 on assistance to persons entitled to maintenance (Journal of Laws of 2022, item 1205). These provisions are complemented by procedural regulations resulting from the Act of 14 June 1960 - Code of Administrative Procedure (Journal of Laws of 2021, item 735, as amended). The first part of the paper will focus on the administrative proceedings regarding the recognition of the debtor as evading maintenance obligations. The initiation of this procedure ex officio is preceded by a number of actions by public administration bodies, including Conducting a maintenance interview with the debtor, during which his health and professional situation and the reasons for non-payment of maintenance are determined, Professional activation in a situation where the lack of payment of maintenance results from the lack of employment. The reasons for initiating the above-mentioned administrative proceedings ex officio will be indicated, taking into account the current views of the judicial decisions. The second part of the paper will focus on the instrument of retaining the driving license of the debtor, who was previously found to be evading maintenance. The author points out that the detention of the driving license is one of the types of administrative sanctions of a very severe nature. Doubts of a constitutional nature will also be highlighted, as well as those concerning the effectiveness of this legal instrument and the protection of the debtor's rights. The thesis will be presented that the administrative procedure for the retention of a driving license does not fulfill its role and especially does not affect the collection of maintenance obligations from debtors. All the considerations will be based on the current and most representative views of the literature on the subject and the jurisprudence of Polish administrative courts.

Keywords: maintenance debtor, administrative proceedings, detention of driving license, administrative sanction, polish administrative law, public administration

Procedia PDF Downloads 84

Authors: Ana Hol

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Digital systems are in the cognitive wave of the eTransformations and are now extensively aimed at meeting the individuals’ demands, both those of customers requiring services and those of service providers. It is also apparent that successful future systems will not just simply open doors to the traditional owners/users to offer and receive services such as Uber for example does today, but will in the future require more customized and cognitively enabled infrastructures that will be responsive to the system user’s needs. To be able to identify what is required for such systems, this research reviews the historical and the current effects of the eTransformation process by studying: 1. eTransitions of company websites and mobile applications, 2. Emergence of new sheared economy business models as Uber and, 3. New requirements for demand driven, cognitive systems capable of learning and just in time decision making. Based on the analysis, this study proposes a Cognitive eTransformation Framework capable of guiding implementations of new responsive and user aware systems.

Keywords: system implementations, AI supported systems, cognitive systems, eTransformation

Procedia PDF Downloads 238

Authors: Fatima Sohail, Faizan Iftikhar

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This paper studies the relationship between digital finance, renewable energy, and the economic development of Pakistan and least developed countries from 2000 to 2022. The paper used panel analysis and generalized method of moments Arellano-Bond approaches. The findings show that under the growth model, renewable energy (RE) has a strong and favorable link with fixed broadband and mobile subscribers. However, FB and MD have a strong but negative association with the uptake of renewable energy (RE) in the average and simple model. This paper provides valuable insights for policymakers, investors of the digital economy.

Keywords: digital finance, renewable energy, economic development, mobile subscription, fixed broadband

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Authors: Musefiu Aderinola, F. A. Amuda

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Outages of GSM signals may be experienced at some indoor locations even when there are strong outdoor receptions. This is often traced to the building penetration loss, which account for increased attenuation of received GSM signals level when a mobile signal device is moved indoor from outdoor. In this work, measurement of two existing GSM operators signal level were made outside and inside two selected buildings- mud and block which represent the prevalent building types in Kazaure, Jigawa State, Nigeria. A gionee P2 mobile phone with RF signal tracker software installed in it was used and the result shows that an average loss of 10.62dBm and 4.25dBm for mud and block buildings respectively.

Keywords: penetration loss, outdoor reception, Gionee P2, RF signal tracker, mud and block building

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Authors: Neetesh Saxena, Narendra S. Chaudhari

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Nowadays, SMS is a very popular mobile service and even the poor, illiterate people and those living in rural areas use SMS service very efficiently. Although many mobile operators have already started 3G and 4G services, 2G services are still being used by the people in many countries. In 2G (GSM), only encryption provided is between the MS and the BTS, there is no end-to-end encryption available. Sometimes we all need to send some confidential message to other person containing bank account number, some password, financial details, etc. Normally, a message is sent in plain text only to the recipient and it is not an acceptable standard for transmitting such important and confidential information. Authors propose an end-to-end encryption approach by proposing a terminal for sending/receiving a secure message. An asymmetric key exchange algorithm is used in order to transmit secret shared key securely to the recipient. The proposed approach with terminal device provides authentication, confidentiality, integrity and non-repudiation.

Keywords: AES, DES, Diffie-Hellman, ECDH, A5, SMS

Procedia PDF Downloads 415

Authors: Hafsat Iyabo Sa'adu

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A salient feature of the Nigerian Tax Law is the right of the taxpayer to demand for a refund where excess tax is paid. Section 23 of the Federal Inland Revenue Service (Establishment) Act, 2007 vests Federal Inland Revenue Services with the power to make tax refund as well as set guidelines and requirements for refund process from time to time. In addition, Section 61 of the Federal Inland Revenue Service (Establishment) Act, 2007, empowers the Federal Inland Revenue Services to issue information circular to acquaint stakeholders with the policy on the refund process. A Circular was issued to that effect to correct the position that until after the annual audit of the Service before such excess can be paid to the claimant/taxpayer. But it is amazing that such circular issuance does not feature under the states’ laws. Hence, there is an inconsistencies in the tax paying system in Nigeria. This study, therefore, sets an objective, to examine the trending concept of tax refund in Nigeria. In order to achieve this set objective, a doctrinal study went under way, wherein both federal and states laws were consulted including journals and textbooks. At the end of the research, it was revealed that the law should be specific as to the time frame within which to make the refund. It further revealed that it is essential to put up a legal framework for the tax system to recognize excess payment as debt due from the state. This would provide a foundational framework for the relationship between taxpayers and Federal Inland Revenue Service as well as promote effective tax administration in all the states of the federation. Several Recommendations were made especially relating to legislative passage of ‘’Refund Circular Bill at the states levels’ pursuant to the Federal Inland Revenue Service (Establishment) Act, 2007.

Keywords: claim, Nigeria, refund, right

Procedia PDF Downloads 118

Authors: L. Korpinen, R. Pääkkönen, F. Gobba

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Accidents and close call situations involving cell phones are nowadays possible. The objective of this study was to investigate the accidents and close call situations due to cell phone use while moving, driving, and working among Finns aged between 18 and 65. This work is part of a large cross-sectional study that was carried out on 15,000 working-age Finns. About 26% of people who had an accident, and about half of the people including close call situation with the mobile phone, answered that use of the phone influenced. In the future, it is important to take into account that the use of a mobile phone can be distracting while driving.

Keywords: blue-collar workers, accident, cell phone, close call situation

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Authors: Mkhinini Maher, Knani Jilani

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We present in this work the performances of a mobile omnidirectional robot through evaluating its management of the redundancy of actuation. Thus we come to the predictive control implemented. The distribution of the wringer on the robot actions, through the inverse pseudo of Moore-Penrose, corresponds to a -geometric- distribution of efforts. We will show that the load on vehicle wheels would not be equi-distributed in terms of wheels configuration and of robot movement. Thus, the threshold of sliding is not the same for the three wheels of the vehicle. We suggest exploiting the redundancy of actuation to reduce the risk of wheels sliding and to ameliorate, thereby, its accuracy of displacement. This kind of approach was the subject of study for the legged robots.

Keywords: mobile robot, actuation, redundancy, omnidirectional, inverse pseudo moore-penrose, reductive control

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Authors: Medhin Haftom Hailu

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The advancement of information technology has significantly impacted Ethiopia's economy, driving innovation, productivity, job creation, and global connectivity. This research examined the impact of contemporary information and communication technologies on Ethiopian economic progress. The study examined eight variables, including mobile, internet, and fixed-line penetration rates, and five macroeconomic control variables. The results showed a positive and strong effect of ICT on economic growth in Ethiopia, with 1% increase in mobile, internet, and fixed line services penetration indexes resulting in an 8.03, 10.05, and 30.06% increase in real GDP. The Granger causality test showed that all ICT variables Granger caused economic growth, but economic growth Granger caused mobile penetration rate only. The study suggests that coordinated ICT infrastructure development, increased telecom service accessibility, and increased competition in the telecom market are crucial for Ethiopia's economic growth. Ethiopia is attempting to establish a digital economy through massive investment in ensuring ICT quality and accessibility. Thus, the research could enhance in understanding of the economic impact of ICT expansion for successful ICT policy interventions for future research.

Keywords: economic growth, cointegration and error correction, ICT expansion, granger causality, penetration

Procedia PDF Downloads 79

Authors: Fredrick Ishengoma, Leonard Mselle, Hector Mongi

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The growing number of mobile phone subscribers in Tanzania offers the government a new channel for the delivery of information and government services to citizens, thus mobile Government (m-Government). In Tanzania, m-Government services usage is in the early stages, and factors that influence its adoption are yet to be known. This study seeks to identify and understand the critical success factors (CSFs) that influence citizens’ behavioural intention (BI) to adopt m-Government services in Tanzania. The study employed the mobile services acceptance model (MSAM) and extends it with external factors relevant in the Tanzanian context. A survey questionnaire was used to collect primary data from users of m-Government services in Dar es salaam and Dodoma cities, and 253 responses were received. Data were analyzed by IBM-SPSS AMOS 23.0 software using structural equation modeling (SEM). The findings of the study indicate that perceived usefulness, trust, perceived mobility, power distance, quality of service, awareness, perceived cost, personal initiatives, and characteristics significantly influence the BI to adopt m-Government services. However, perceived ease of use was found statistically insignificant to predict BI. Furthermore, the interplay between CSFs, discussion on theoretical and practical implications that follow from the results are presented.

Keywords: adoption, critical success factors, structural equation modeling, m-Government, MSAM, Tanzania

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Authors: Leonardo Ramirez Lopez, Edward Guillen Pinto, Carlos Ramos Linares

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The controversy brought about by the increasing use of mHealth apps and their effectiveness for disease prevention and diagnosis calls for immediate control. Although a critical topic in research areas such as medicine, engineering, economics, among others, this issue lacks reliable implementation models. However, projects such as Open Web Application Security Project (OWASP) and various studies have helped to create useful and reliable apps. This research is conducted under a quality model to optimize two mHealth apps for older adults. Results analysis on the use of two physical activity monitoring apps - AcTiv (physical activity) and SMCa (energy expenditure) - is positive and ideal. Through a theoretical and practical analysis, precision calculations and personal information control of older adults for disease prevention and diagnosis were performed. Finally, apps are validated by a physician and, as a result, they may be used as health monitoring tools in physical performance centers or any other physical activity. The results obtained provide an effective validation model for this type of mobile apps, which, in turn, may be applied by other software developers that along with medical staff would offer digital healthcare tools for elderly people.

Keywords: model, validation, effective, healthcare, elderly people, mobile app

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Authors: Hoyeon Park, Kyoung-jae Kim

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The product recommendation is a field of research that has received much attention in the recent information overload phenomenon. The proliferation of the mobile environment and social media cannot help but affect the results of the recommendation depending on how the factors of the user's situation are reflected in the recommendation process. Recently, research has been spreading attention to the context-aware recommender system which is to reflect user's contextual information in the recommendation process. However, until now, most of the context-aware recommender system researches have been limited in that they reflect the passive context of users. It is expected that the user will be able to express his/her contextual information through his/her active behavior and the importance of the context-aware recommender system reflecting this information can be increased. The purpose of this study is to propose a context-aware recommender system that can reflect the user's emotional state as an active context information to recommendation process. The context-aware recommender system is a recommender system that can make more sophisticated recommendations by utilizing the user's contextual information and has an advantage that the user's emotional factor can be considered as compared with the existing recommender systems. In this study, we propose a method to infer the user's emotional state, which is one of the user's context information, by using the user's facial expression data and to reflect it on the recommendation process. This study collects the facial expression data of a user who is looking at a specific product and the user's product preference score. Then, we classify the facial expression data into several categories according to the previous research and construct a model that can predict them. Next, the predicted results are applied to existing collaborative filtering with contextual information. As a result of the study, it was shown that the recommended results of the context-aware recommender system including facial expression information show improved results in terms of recommendation performance. Based on the results of this study, it is expected that future research will be conducted on recommender system reflecting various contextual information.

Keywords: context-aware, emotional state, recommender systems, business analytics

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Authors: Kuo-Kai Lin, Po-Lun Chang

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Research Background and Purpose: Following the development of the Internet and multimedia, the Internet and information technology have become crucial avenues of modern communication and knowledge acquisition. The advantages of using mobile devices for learning include making learning borderless and accessible. Mobile learning has become a trend in disease management and health promotion in recent years. End-stage renal disease (ESRD) is an irreversible chronic disease, and patients who do not receive kidney transplants can only rely on hemodialysis or peritoneal dialysis to survive. Due to the complexities in caregiving for patients with ESRD that stem from their advanced age and other comorbidities, the patients’ incapacity of self-care leads to an increase in the need to rely on their families or primary caregivers, although whether the primary caregivers adequately understand and implement patient care is a topic of concern. Therefore, this study explored whether primary caregivers’ health care provisions can be improved through the intervention of an automatic speech intelligent system, thereby improving the objective health outcomes of patients undergoing long-term dialysis. Method: This study developed an automatic speech intelligent system with healthcare functions such as health information voice prompt, two-way feedback, real-time push notification, and health information delivery. Convenience sampling was adopted to recruit eligible patients from a hemodialysis center at a regional teaching hospital as research participants. A one-group pretest-posttest design was adopted. Descriptive and inferential statistics were calculated from the demographic information collected from questionnaires answered by patients and primary caregivers, and from a medical record review, a health care scale (recorded six months before and after the implementation of intervention measures), a subjective health assessment, and a report of objective physiological indicators. The changes in health care behaviors, subjective health status, and physiological indicators before and after the intervention of the proposed automatic speech intelligent system were then compared. Conclusion and Discussion: The preliminary automatic speech intelligent system developed in this study was tested with 20 pretest patients at the recruitment location, and their health care capacity scores improved from 59.1 to 72.8; comparisons through a nonparametric test indicated a significant difference (p < .01). The average score for their subjective health assessment rose from 2.8 to 3.3. A survey of their objective physiological indicators discovered that the compliance rate for the blood potassium level was the most significant indicator; its average compliance rate increased from 81% to 94%. The results demonstrated that this automatic speech intelligent system yielded a higher efficacy for chronic disease care than did conventional health education delivered by nurses. Therefore, future efforts will continue to increase the number of recruited patients and to refine the intelligent system. Future improvements to the intelligent system can be expected to enhance its effectiveness even further.

Keywords: automatic speech intelligent system for health care, primary caregiver, long-term hemodialysis, health care capabilities, health outcomes

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Authors: P. S. Seboletswe, Z. Mkhize, L. M. Katata-Seru

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Protorhus longifolia is known as a medicinal plant that has been used traditionally to treat various ailments such as hemiplegic paralysis, blood clotting related diseases, diarrhoea, heartburn, etc. The study reports a High-Performance Thin Layer Chromatography (HPTLC) fingerprint profile of Protorhus longifolia methanolic extract and its qualitative analysis of gallic acid, rutin, and quercetin. HPTLC analysis was achieved using CAMAG HPTLC system equipped with CAMAG automatic TLC sampler 4, CAMAG Automatic Developing Chamber 2 (ADC2), CAMAG visualizer 2, CAMAG Thin Layer Chromatography (TLC) scanner and visionCATS CAMAG HPTLC software. Mobile phase comprising toluene, ethyl acetate, formic acid (21:15:3) was used for qualitative analysis of gallic acid and revealed eight peaks while the mobile phase containing ethyl acetate, water, glacial acetic acid, formic acid (100:26:11:11) for qualitative analysis of rutin and quercetin revealed six peaks. HPTLC sillica gel 60 F254 glass plates (10 × 10) were used as the stationary phase. Gallic acid was detected at the R_f = 0.35; while rutin and quercetin were not evident in the extract. Further studies will be performed to quantify gallic acid in Protorhus longifolia leaves and also identify other biomarkers.

Keywords: biomarkers, fingerprint profiling, gallic acid, HPTLC, Protorhus longifolia

Procedia PDF Downloads 142

Authors: Suraj Nair, Aravindkumar Vijayalingam, Alexander Perzylo, Alois Knoll

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In the last decade robotics research and development activities have grown rapidly, especially in the domain of service robotics. Integrating service robots into human occupied spaces such as homes, offices, hospitals, etc. has become increasingly worked upon. The primary motive is to ease daily lives of humans by taking over some of the household/office chores. However, several challenges remain in systematically integrating such systems in human shared work-spaces. In addition to sensing and indoor-navigation challenges, programmability of such systems is a major hurdle due to the fact that the potential user cannot be expected to have knowledge in robotics or similar mechatronic systems. In this paper, we propose a cognitive system for service robotics which allows non-expert users to easily model system behaviour in an underspecified manner through abstract tasks and objects associated with them. The system uses domain knowledge expressed in the form of an ontology along with logical reasoning mechanisms to infer all the missing pieces of information required for executing the tasks. Furthermore, the system is also capable of recovering from failed tasks arising due to on-line disturbances by using the knowledge base and inferring alternate methods to execute the same tasks. The system is demonstrated through a coffee fetching scenario in an office environment using a mobile robot equipped with sensors and software capabilities for autonomous navigation and human-interaction through natural language.

Keywords: cognitive robotics, reasoning, service robotics, task based systems

Procedia PDF Downloads 243

Authors: Dchieche Amina, Aboulaich Rajae

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Profit and loss sharing suggests an equitable sharing of risks and profits between the parts involved in a financial transaction. Salam is a contract in which advance payment is made for goods to be delivered at a future date. The purpose of this work is to price a new contract for profit and loss sharing based on Salam contract, using Khiyar Al Ghabn which is an agreement of choice in case of misrepresent facts.

Keywords: Islamic finance, shariah compliance, profit and loss sharing, derivatives, risks, hedging, salam contract

Procedia PDF Downloads 332

Authors: Shanko Chura Aredo, Hailu Jeldie Wodajo, Muktar Jeylan, Kedir Ilka, Abdulnasir Husein

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Toll-free numbers are calling numbers that have unique three or four digit numbers and that don’t require payment from phone lines in order to be called. With the help of these numbers, callers can connect with nearby organizations and/or people without incurring far-reaching fees. Calls to assistance centers are especially popular from toll-free phones. In the past, toll-free services have offered prospective clients and other parties a simple and cost-free means of getting in touch with enterprises. Nevertheless, unless they have an ”unlimited calling” plan, wireless subscribers will be billed for the airtime minutes used during a toll-free call. In Adama, the second largest city in Ethiopia, a call center has been installed as part of smart security system and serving since January 2023 for collection of complaints from different community levels. The call center is situated at the mayor office and has 11 active workers, 4 of these working the night time and the remaining during day time. The information reported in the form of complaints from individuals and groups are illegal constructions, illegal trade, income concealment or hiding, giving and receiving bribe, informing new faces of suspected enemies and exposing individual or group conflicts. This technology has been found to bring a significant outcome in minimizing illegal acts, public safety threats and service delivery problems.

Keywords: smart, safety, crime, call center, security

Procedia PDF Downloads 55

Authors: Carlos Gordon, Patricio Encalada, Henry Lema, Diego Leon, Dennis Chicaiza

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The following work presents a proposal of autonomous navigation of mobile robots implemented in an omnidirectional robot Kuka Youbot. We have been able to perform the integration of robotic operative system (ROS) and machine learning algorithms. ROS mainly provides two distributions; ROS hydro and ROS Kinect. ROS hydro allows managing the nodes of odometry, kinematics, and path planning with statistical and probabilistic, global and local algorithms based on Adaptive Monte Carlo Localization (AMCL) and Dijkstra. Meanwhile, ROS Kinect is responsible for the detection block of dynamic objects which can be in the points of the planned trajectory obstructing the path of Kuka Youbot. The detection is managed by artificial vision module under a trained neural network based on the single shot multibox detector system (SSD), where the main dynamic objects for detection are human beings and domestic animals among other objects. When the objects are detected, the system modifies the trajectory or wait for the decision of the dynamic obstacle. Finally, the obstacles are skipped from the planned trajectory, and the Kuka Youbot can reach its goal thanks to the machine learning algorithms.

Keywords: autonomous navigation, machine learning, path planning, robotic operative system, open source computer vision library

Procedia PDF Downloads 177

Authors: Loghman Ansarian, Teoh Mei Lin

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In an attempt to increase oral proficiency of Iranian EFL learners, the researchers compared the effect of problem-based mobile-assisted language learning with the conventional language learning approach (Communicative Language Teaching) in Iran. The experimental group (n=37) went through PBL instruction and the control group (n=33) went through conventional instruction. The results of quantitative data analysis after 26 sessions of treatment revealed that PBL could positively affect participants' knowledge of grammar, vocabulary, spoken fluency, and pronunciation; however, in terms of task achievement, no significant effect was found. This study can have pedagogical implications for language teachers, and material developers.

Keywords: problem-based learning, spoken intelligibility, Iranian EFL context, cognitive learning

Procedia PDF Downloads 175

Authors: David L. Olson, Stephen B. H. Bruder, Adam S. Watkins, Cleon E. Davis

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In global navigation satellite systems (GNSS), denied settings such as indoor environments, autonomous mobile robots are often limited to dead-reckoning navigation techniques to determine their position, velocity, and attitude (PVA). Localization is typically accomplished by employing an inertial measurement unit (IMU), which, while precise in nature, accumulates errors rapidly and severely degrades the localization solution. Standard sensor fusion methods, such as Kalman filtering, aim to fuse precise IMU measurements with accurate aiding sensors to establish a precise and accurate solution. In indoor environments, where GNSS and no other a priori information is known about the environment, effective sensor fusion is difficult to achieve, as accurate aiding sensor choices are sparse. However, an opportunity arises by employing a depth camera in the indoor environment. A depth camera can capture point clouds of the surrounding floors and walls. Extracting attitude from these surfaces can serve as an accurate aiding source, which directly combats errors that arise due to gyroscope imperfections. This configuration for sensor fusion leads to a dramatic reduction of PVA error compared to traditional aiding sensor configurations. This paper provides the theoretical basis for the depth camera aiding sensor method, initial expectations of performance benefit via simulation, and hardware implementation, thus verifying its veracity. Hardware implementation is performed on the Quanser Qbot 2™ mobile robot, with a Vector-Nav VN-200™ IMU and Kinect™ camera from Microsoft.

Keywords: autonomous mobile robotics, dead reckoning, depth camera, inertial navigation, Kalman filtering, localization, sensor fusion

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Authors: Saidatul A'isyah Ahmad Shukri, Haslina Arshad

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This study was conducted to develop an application that provides Augmented Reality experience in identifying halal food products and beverages based on Malaysian Islamic Development Department (JAKIM) database for Muslim consumers in Malaysia. The applications is operating on the mobile device using the Android platform. This application aims to provide a new experience to the user how to use the Android application implements Augmentation Reality technology The methodology used is object-oriented analysis and design (OOAD). The programming language used is JAVA programming using the Android Software Development Kit (SDK) and XML. Android operating system is selected, and it is an open source operating system. Results from the study are implemented to further enhance diversity in presentation of information contained in this application and so can bring users using these applications from different angles.

Keywords: android, augmented reality, food, halal, Malaysia, products, XML

Procedia PDF Downloads 455

Authors: Christina Tay

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This paper investigates the impact of Information and Communication Technology (ICT) on bilateral trade in goods. Empirical analysis is performed on the United States and 34 partnering countries from 2000 to 2013. Our econometric model fits the data well, explaining 52% of the variation in trade flows for goods trade, 53.2% of the variation in trade flows for goods export and 48% of the variation in trade flows for goods import. For every 10% increase in fixed broadband Internet subscribers per 100 people increases, goods trade by 7.9% and for every 5% increase in fixed broadband Internet subscribers per 100 people, goods export increases by 11%. For every 1% increase in fixed telephone line penetration per 100 people, goods trade increases by 26.3%, goods export increases by 24.4% and goods import increases by 24.8%. For every 1% increase in mobile-cellular telephone subscriptions, goods trade decreases by 29.6% and goods export decreases by 27.1%, whilst for every 0.01% increase in mobile-cellular telephone subscriptions, goods import decreases by 34.3%. For every 1% increase in the percentage of population who used the Internet from any location in the last 12 months Internet, goods trade increases by 32.5%, goods export increases by 38.9%, goods import increases by 33%. All our trade determinants as well as our ICT variables have significances on goods exports for the US. We can also draw from our study that the US relies more rather heavily on ICT for its goods export compared to goods import.

Keywords: bilateral trade, fixed broadband, fixed telephone, goods trade, information and communicative technologies, Internet, mobile-cellular phone

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Authors: G. Usha, S. Kannimuthu, K. Mahalakshmi

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Mobile Adhoc Network (MANET) is one of the most promising technologies that have applications ranging from various portable devices to military networks. MANET has no fixed infrastructure and the security of such network is a big concern. Therefore, in order to operate MANET’s securely, the misbehavior and intrusions should be detected before the attackers affect the network communication. In this article, we make a comprehensive survey against black hole attack that is a serious threat against MANET that exploits the routing behavior of the MANET. We have given broad survey solutions that detect black hole attacks in MANET. This is achieved by analyzing the techniques involved in detecting the attacks in each scheme. Furthermore, we examine about the challenges to the researchers for constructing an in-depth solution against black hole attack.

Keywords: AODV, cross layer security, mobile Adhoc network (MANET), packet delivery ratio, single layer security

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Authors: Matthew Pleshaw, Caroline Lynch, Caleb Eaton, Ali Kiapour

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The problem addressed in this proposal is that of the lacking comfort and safety of inpatient rooms, specifically at Boston Children’s Hospital, with the implementation of a system that will allow inpatient children to feel more comfortable in the unfamiliar environment of a hospital. The focus is that of advancing and enhancing the healing process for children in a long-term inpatient stay at the hospital, though a combination of announcing a clinician or hospital staff’s arrival utilizing RFID (Fig. 1), and improving communication between clinicians, parents/guardians, patients, etc. by integrating a mobile application.

Keywords: Pediatrics, Hospital, RFID, Technology

Procedia PDF Downloads 158

Authors: Jonathan Ogwal, Louis H. Kamulegeya, John M. Bwanika, Davis Musinguzi

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Introduction: Community retail Pharmacy drug distribution points (CRPDDP) were implemented in the Lango sub-region as part of the Ministry of Health’s response to improving access and adherence to antiretroviral treatment (ART). Clients received their ART refills from nearby local pharmacies; as such, the need for continuous engagement through mobile phone appointment reminders and health messages. We share learnings from the implementation of mobile text reminders and voice call follow-ups among ART clients attending the CRPDDP program in northern Uganda. Methods: A retrospective data review of electronic medical records from four pharmacies allocated for CRPDDP in the Lira and Apac districts of the Lango sub-region in Northern Uganda was done from February to August 2022. The process involved collecting phone contacts of eligible clients from the health facility appointment register and uploading them onto a messaging platform customized by Rapid-pro, an open-source software. Client information, including code name, phone number, next appointment date, and the allocated pharmacy for ART refill, was collected and kept confidential. Contacts received appointment reminder messages and other messages on positive living as an ART client. Routine voice call follow-ups were done to ascertain the picking of ART from the refill pharmacy. Findings: In total, 1,354 clients were reached from the four allocated pharmacies found in urban centers. 972 clients received short message service (SMS) appointment reminders, and 382 were followed up through voice calls. The majority (75%) of the clients returned for refills on the appointed date, 20% returned within four days after the appointment date, and the remaining 5% needed follow-up where they reported that they were not in the district by the appointment date due to other engagements. Conclusion: The use of mobile text reminders and voice call follow-ups improves the attendance of community retail pharmacy refills.

Keywords: antiretroviral treatment, community retail drug distribution points, mobile text reminders, voice call follow-up

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Authors: Beeto W. C. Leung, Nicole C. Y. Lee

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It was well known that college students experienced a high level of stress and anxiety. College athletes, a special group of college students, may even encounter a higher level of pressure and distress due to their dual endeavors in academic and athletic settings. Due to the high demands and costs of mental health services, easily accessible, web-based self-help interventions are getting more popular. The aim of the present experimental study was to examine the potential intervention effect of a mindfulness-based self-help mobile App, called 'Smiling Mind', on mindfulness and psychological well-being. Forty-six college athletes, recruited from athletic teams of two local universities in Hong Kong, were randomly assigned to the Mindfulness App Group (MAG) and the Control Group (CG). All participants were administered the Mindful Attention Awareness Scale, Geriatric Depression Scale, and Perceived Stress Scale-10 before the study (Time 1, T1) and after the 4-week intervention (Time 2, T2). MAG was requested to use the app and follow the instructions every day for at least 5 days per week. Participants were also asked to record their daily app usage time. Results showed that, for MAG, from T1 to T2, mindfulness has been increased from 3.25 to 3.92; depressive symptoms and stress has been significantly decreased from 8.6 to 5.1 and 24.8 to 13.5 respectively while for the CG, mindfulness has been decreased slightly from 3.29 to 3.13; depressive symptoms and stress has been slightly increased from 7.1 to 7.3 and 24.1 to 27.1 respectively. Three mixed-design ANOVAs with time (T1, T2) as the within-subjects factor and intervention group (MAG, CG) as the between-subjects factor revealed a main effect of time on mindfulness, F(1, 41) = 10.28, p < 0.01, depressive symptoms, F(1, 41) = 6.55, p < 0.02 and stress, F(1, 41) = 16.96, p < 0.001 respectively. Both predicted interaction between time and intervention group on mindfulness, F(1, 41) = 26.6, p < 0.001, ηp 2 =0.39, depressive symptoms, F(1, 41) = 8.00, p < 0.01, ηp 2 =0.16 and Stress F(1, 41) = 49.3, p < 0.001, ηp 2 =0.55 were significant meaning that participants using the Mindfulness Mobile App in the intervention did experienced a significant increase in mindfulness and significant decrease in depressive symptoms and perceived level of stress after the 4-week intervention when compared with the control group. The present study provided encouraging empirical support for using Smiling Mind, a self-help mobile app, to promote mindfulness and mental health in a cost-effective way. Further studies should examine the potential use of Smiling Mind in different samples, including children and adolescence, as well as, investigate the lasting effects of using the app on other psychosocial outcomes such as emotional regulations.

Keywords: college athletes, experimental study, mindfulness mobile apps, psychological well-being

Procedia PDF Downloads 117

Authors: Raquel P. F. Guiné, Daniela V. T. A. Costa, Paula M. R. Correia, Moisés Castro, Luis T. Guerra, Cristina A. Costa

Abstract:

The aim of this work was to characterize a potential target group of people interested in participating into a training program in organic farming in the context of mobile-learning. The information sought addressed in particular, but not exclusively, possible contents, formats and forms of evaluation that will contribute to define the course objectives and curriculum, as well as to ensure that the course meets the needs of the learners and their preferences. The sample was selected among different European countries. The questionnaires were delivered electronically for answering online and in the end 135 consented valid questionnaires were obtained. The results allowed characterizing the target group and identifying their training needs and preferences towards m-learning formats, giving valuable tools to design the training offer.

Keywords: mobile-learning, organic farming, rural development, survey

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Authors: Chandu Rathnayake, Isuri Anuradha

Abstract:

Early detection and accurate diagnosis of lung diseases play a crucial role in improving patient prognosis. However, conventional diagnostic methods heavily rely on subjective symptom assessments and medical imaging, often causing delays in diagnosis and treatment. To overcome this challenge, we propose a novel lung disease prediction system that integrates patient symptoms and X-ray images to provide a comprehensive and reliable diagnosis.In this project, develop a mobile application specifically designed for detecting lung diseases. Our application leverages both patient symptoms and X-ray images to facilitate diagnosis. By combining these two sources of information, our application delivers a more accurate and comprehensive assessment of the patient's condition, minimizing the risk of misdiagnosis. Our primary aim is to create a user-friendly and accessible tool, particularly important given the current circumstances where many patients face limitations in visiting healthcare facilities. To achieve this, we employ several state-of-the-art algorithms. Firstly, the Decision Tree algorithm is utilized for efficient symptom-based classification. It analyzes patient symptoms and creates a tree-like model to predict the presence of specific lung diseases. Secondly, we employ the Random Forest algorithm, which enhances predictive power by aggregating multiple decision trees. This ensemble technique improves the accuracy and robustness of the diagnosis. Furthermore, we incorporate a deep learning model using Convolutional Neural Network (CNN) with the RestNet50 pre-trained model. CNNs are well-suited for image analysis and feature extraction. By training CNN on a large dataset of X-ray images, it learns to identify patterns and features indicative of lung diseases. The RestNet50 architecture, known for its excellent performance in image recognition tasks, enhances the efficiency and accuracy of our deep learning model. By combining the outputs of the decision tree-based algorithms and the deep learning model, our mobile application generates a comprehensive lung disease prediction. The application provides users with an intuitive interface to input their symptoms and upload X-ray images for analysis. The prediction generated by the system offers valuable insights into the likelihood of various lung diseases, enabling individuals to take appropriate actions and seek timely medical attention. Our proposed mobile application has significant potential to address the rising prevalence of lung diseases, particularly among young individuals with smoking addictions. By providing a quick and user-friendly approach to assessing lung health, our application empowers individuals to monitor their well-being conveniently. This solution also offers immense value in the context of limited access to healthcare facilities, enabling timely detection and intervention. In conclusion, our research presents a comprehensive lung disease prediction system that combines patient symptoms and X-ray images using advanced algorithms. By developing a mobile application, we provide an accessible tool for individuals to assess their lung health conveniently. This solution has the potential to make a significant impact on the early detection and management of lung diseases, benefiting both patients and healthcare providers.

Keywords: CNN, random forest, decision tree, machine learning, deep learning

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Authors: Fayad Ghawbar

Abstract:

The significance of the Multiple Input Multiple Output (MIMO) system in the 5G wireless communication system is essential to enhance channel capacity and provide a high data rate resulting in a need for dual-polarization in vertical and horizontal. Furthermore, size reduction is critical in a MIMO system to deploy more antenna elements requiring a compact, low-profile design. A compact dual-band 4-MIMO antenna system has been presented in this paper with pattern and polarization diversity. The proposed single antenna structure has been designed using two antenna layers with a C shape in the front layer and a partial slot with a U-shaped cut in the ground to enhance isolation. The single antenna is printed on an FR4 dielectric substrate with an overall size of 18 mm×18 mm×1.6 mm. The 4-MIMO antenna elements were printed orthogonally on an FR4 substrate with a size dimension of 36 × 36 × 1.6 mm3 with zero edge-to-edge separation distance. The proposed compact 4-MIMO antenna elements resonate at 3.4-3.6 GHz and 4.8-5 GHz. The s-parameters measurement and simulation results agree, especially in the lower band with a slight frequency shift of the measurement results at the upper band due to fabrication imperfection. The proposed design shows isolation above -15 dB and -22 dB across the 4-MIMO elements. The MIMO diversity performance has been evaluated in terms of efficiency, ECC, DG, TARC, and CCL. The total and radiation efficiency were above 50 % across all parameters in both frequency bands. The ECC values were lower than 0.10, and the DG results were about 9.95 dB in all antenna elements. TARC results exhibited values lower than 0 dB with values lower than -25 dB in all MIMO elements at the dual-bands. Moreover, the channel capacity losses in the MIMO system were depicted using CCL with values lower than 0.4 Bits/s/Hz.

Keywords: compact antennas, MIMO antenna system, 5G communication, dual band, ECC, DG, TARC

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Authors: Engin Eyceyurt, Josko Zec

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.

Keywords: drive test, LTE, machine learning, uplink throughput prediction

Procedia PDF Downloads 156