Mobile Phone Network Research Articles

Assessment of Employees` Involvement influence on Performance of MTNOs in Kenya

The objective of the study was to assess the extent of employees` involvement on performance of MTNOs in Kenya. Sub-variables used for the independent variable were: employees` autonomy, quality circles and employees` suggestion schemes. Performance of Mobile Telephone Operators in Kenya was assessed in terms of profit margins and market share. Mixed methodology was used in collecting and interpreting data. Primary data was gathered using self-guided semi-structured questionnaires and secondary data was obtained from published profit margins and percentages of market share obtained from the companies` reports. Study population was 6,167 which included all the employees in the Mobile Telephone Network Operators in Kenya and a total sample size of 361 employees was obtained but 258 questionnaires were filled and returned. Data analysis was done using descriptive statistics and inferential statistics. The study hypothesis was tested at 95% confidence interval and 0.05 α level of significance. Study null hypothesis (H0) stated that: Employees` involvement does not have a positive influence on performance of MTNOs in Kenya. Regression analysis model demonstrated that employees` involvement had a positive influence on organizations’ performance of MTNOs accounting for 48.3% of the performance (R squared = .483). The study concluded that there was a significant relationship between employees` involvement and organization`s performance therefore rejecting the null hypothesis H0 at β = .695 and P = .000.

Focused Cardiac Ultrasound Findings in Children Presenting With Shock to a Tertiary Care Hospital in Rwanda.

Shock remains a leading proximate cause of death in children. Children in sub-Saharan African (SSA) countries present with shock from a wide range of pathologies. Routine physiologic parameters may not reflect underlying physiology. No previous work has systematically described ultrasound findings in children with shock in an SSA country. We set out to perform focused cardiac ultrasound (FOCUS) on children with shock in Rwanda and describe the findings in this pilot study. In a prospective descriptive study, we trained pediatric residents to perform FOCUS on children presenting with shock to an urban tertiary care pediatric emergency department in Kigali, Rwanda. Images were transmitted via cellphone network and reviewed by experts. Primary outcome was expert's description of the FOCUS findings. Secondary outcomes included mortality at 48-hour, change in assessment and treatment after FOCUS, and agreement of FOCUS findings between residents and experts. Between January 2020 and April 2020, 25 subjects were enrolled by 8 residents. Eleven of 25 (44%) were newly diagnosed with acquired or congenital heart disease. The 48-hour mortality rate was higher in this group compared with those without heart disease (8 of 11 vs 1 of 14). The resident reported changing assessment and treatment based on FOCUS findings in 60% of patients (15 of 25). There was good to excellent agreements between residents and FOCUS experts on left ventricle function, pericardial effusion, and intravascular volume. In children presenting with signs and symptoms of shock in SSA, one could perform a screening FOCUS to distinguish between hypovolemic and cardiogenic shock.

Electromagnetic Pollution as a Possible Explanation for the Decline of House Sparrows in Interaction with Other Factors

In recent decades, there has been a decline of the House Sparrow (Passer domesticus), mainly in European cities, and several hypotheses have been proposed that attempt to determine the causes of this rapid decline. Previous studies indicated that house sparrows were significantly negatively associated with increasing electromagnetic radiation and sparrows disappeared from areas most polluted. In addition, there are many studies on the impact of radiation on other bird and non-bird species, as well as numerous laboratory studies that demonstrated detrimental effects at electric field strength levels that can be found in cities today. Electromagnetic radiation is the most plausible factor for multiple reasons, including that this is the only one that affects the other hypotheses proposed so far. It is a type of pollution that affects productivity, fertility, decreases insects (chicken feed), causes loss of habitat, decreases immunity and can promote disease. Additionally, the recent sparrow decline matches the deployment of mobile telephony networks. Further, there are known mechanisms of action for non-thermal effects of electromagnetic radiation that may affect sparrows causing their decline. Thus, electromagnetic radiation must be seriously considered as a factor for house sparrows’ decline, probably in synergy with the other factors previously proposed.

Reimaging the mobile money ecosystem and financial inclusion of MSMEs in Uganda: Hedonic motivation as mediator

PurposeMobile money is a service in which the mobile phone is used to access financial services. Thus, the mobile money platform should be user-friendly with hedonic features that are attractive and pleasurable to the users. The main purpose of this paper is to establish the mediating effect of hedonism in the relationship between mobile money adoption and usage and financial inclusion of micro small and medium enterprises (MSMEs) in Uganda.Design/methodology/approachThis study reports interesting findings by using data obtained from MSMEs located in northern Uganda. The structural equation and measurement models were generated in analysis of moment structures (AMOS) to answer the hypotheses of this study.FindingsThe findings suggest that including hedonism in the model improves mobile money adoption and usage by 12.7 percentage points in order to promote financial inclusion of MSMEs in Uganda. Hedonism is found to affect mobile money adoption and usage, which in turn influences financial inclusion.Research limitations/implicationsThis study used cross-sectional data to document the mediating effect of hedonism in the relationship between mobile money adoption and usage and financial inclusion. The study analyzed mobile money adoption and usage, hedonism, and financial inclusion from the MSMEs owners' perspective. Future research could use relevant longitudinal data to verify multiple benefits of hedonism in enhancing mobile money adoption and usage as well as other potential digital financial technologies.Practical implicationsThis study categorically informs mobile telephone network operators and inventors of mobile money applications to invest more in developing pleasurable and user-friendly mobile money features that can attract more users. The digital financial services' application developers should design user-friendly mobile money applications that suit the needs of all users. This requires careful understanding of diverse attractive features of mobile money services.Originality/valueThis study offers direction to developers of mobile money applications to design pleasurable and user-friendly mobile money platform with features, which are attractive to the different users. Particularly, it highlights the role of hedonic motivation in promoting adoption and use of mobile money technology to increase the scope of financial inclusion of MSMEs in a developing country like Uganda. Indeed, the novelty in this paper is grounded on a blend of financial technology and psychology to promote financial inclusion in under developed economies.

Assessment of ECG during hybrid comprehensive telerehabilitation in heart failure patients-Subanalysis of the Telerehabilitation in Heart Failure Patients (TELEREH-HF) randomized clinical trial.

BackgroundExercise training in heart failure (HF) patients should be monitored to ensure patients’ safety. Electrocardiographic (ECG) telemonitoring was used to assess the safety of hybrid comprehensive telerehabilitation (HCTR).ObjectiveAnalysis of ECG recorded during HCTR in HF patients.MethodsThe TELEREH‐HF multicenter, randomized, controlled trial enrolled 850 HF patients with New York Heart Association class I‐III and left ventricular ejection fraction of ≤40%. This subanalysis focuses on 386 patients (aged 62 ± 11 years, LVEF 31 ± 7%) randomized to HCTR. HCTR was telemonitored with a device allowing to record 16‐s fragments of ECG and to transmit the data via mobile phone network to the monitoring center.ResultsIn 386 patients, 16,622 HCTR sessions were recorded and 66,488 ECGs fragments were evaluated. Sinus rhythm was present in 320 (83%) and permanent atrial fibrillation (AF) in 66 (17%) patients, respectively. The most common arrhythmias were ventricular and atrial premature beats, recorded in 76.4% and 27.7% of the patients, respectively. Non‐sustained ventricular tachycardia (21 episodes in 8 patients) and paroxysmal AF episodes (6 in 4 patients) were rare. None of the analyzed demographic and clinical characteristics was predictive for onset of the new arrhythmias on exercise.ConclusionTelerehabilitation in HF patients was safe without the evidence for symptomatic arrhythmias requiring discontinuation of telerehabilitation. Only one mildly symptomatic paroxysmal AF episode led to the short‐term suspension of the training program. The most common arrhythmias were atrial and ventricular premature beats. These arrhythmias did not result in any changes in rehabilitation and therapy regimens.

Analytics of location-based big data for smart cities: Opportunities, challenges, and future directions

The growing ubiquity of location/activity sensing technologies and location-based services (LBS) has led to a large volume and variety of location-based big data (LocBigData), such as location tracking or sensing data, social media data, and crowdsourced geographic information. The increasing availability of such LocBigData has created unprecedented opportunities for research on urban systems and human environments in general. In this article, we first review the common types of LocBigData: mobile phone network data, GPS data, Location-based social media data, LBS usage/log data, smart card travel data, beacon log data (WiFi or Bluetooth), and camera imagery data. Secondly, we describe the opportunities fueled by LocBigData for the realization of smart cities, mainly via answering questions ranging from “what happened” and “why did it happen” to “what's likely to happen in the future” and “what to do next”. Thirdly, pitfalls of dealing with LocBigData are summarized, such as high volume/velocity/variety; non-random sampling; messy and not clean data; and correlations rather than causal relationships. Finally, we review the state-of-the-art research trends in this field, and conclude the article with a list of open research challenges and a research agenda for LocBigData research to help achieve the vision of smart and sustainable cities.

Nomophobia and the connection anxiety dimensions: a cross-sectional study among students and nurses.

Nomophobia, a form of behavioral addiction, is uncontrolled, obsessive fear of being disconnected from the mobile phone network. Excessive use of smartphone during care, a source of errors and distractions, is among the top ten risks related to the use of technologies in healthcare. The study aims to investigate the presence of nomophobia among nurses and students of the Degree in Nursing and any differences based on gender, age group and seniority. A cross-sectional quantitative descriptive study conducted at Università Politecnica delle Marche and Azienda Ospedali Riuniti Marche Nord departments; the NMP-Q questionnaire (Nomophobia Questionnaire) was administered to a non-probabilistic sample of nurses and nursing students. The data were analyzed using descriptive and inferential non-parametric statistical measurements. A total of 280 questionnaires were returned, 141 for students and 139 for nurses. The mean total score for students and nurses was moderate and overlapping (M=79.9 vs. 79.3, p>0.05), with no difference by gender and course year (p>0.05); in the sample of nurses score is higher in men (M=89.8 vs. 76.0, p=0.037), under 30 (M=72.0) and over 50 years (M=83.1, p=0.021). The comparison between the two groups shows higher percentages of moderate nomophobic grade among students (+17pp), mild (+8.2 pp) and severe (+7.4 pp) among nurses, without significant gender differences. In the perspective of proper risk management, the level of nomophobia found in both groups should not be underestimated. This study highlights the importance of monitoring the phenomenon, adopting information and awareness-raising policies aimed at healthcare personnel as early as university training: distracting factors associated with the over-use of smartphones in the workplace make nurses, particularly newly graduates and with less expertise, more vulnerable and more exposed to the risk of error.

Guest Editorial: Security and Privacy

Over the past two decades, a wide range of cyber security and privacy standards and regulations have been developed, covering a large number of application areas being both technical and business-oriented in nature. These standards and guidelines have been published by formal national and international standardization bodies and government agencies, as well as by industry consortia. Many of them are widely used, including the IETF standards that form the basis for the operation of the Internet; the ISO/IEC 27000 series of standards that has become the internationally adopted system for managing corporate information security; and the standards for mobile telephony published by the 3GPP that underlie all generations of mobile telephone networks. Despite their wide deployment, there will always be a need to revise existing standards and to develop new standards to cover new domains.

The Randomness and Robustness of Triadic, Tetradic, and Pentadic Evolution Patterns in a Large-Scale Mobile Phone Network

The Randomness and Robustness of Triadic, Tetradic, and Pentadic Evolution Patterns in a Large-Scale Mobile Phone Network

Performance Evaluation of DSRC-Zigbee Heterogeneous Network for Intelligent Transportation System

Transportation is one of the primary needs of human beings that cannot be avoided, with the increasing vehicle can lead to a congested road situation which can lead to less safe road safety. An Intelligent Transportation System (ITS) can be used to increase road safety. This system uses a Dedicated Short-Range Communication (DSRC) protocol for network access due to its low latency transmission time. Unfortunately, there is research shows that DSRC has a performance issue in a dense area or increased network load. This problem is mostly solved with a heterogeneous network DSRC-LTE but utilizes mobile phone networks that dynamically change can lead to inconsistent and unpredictable network performance. There is some research about ZigBee for ITS shows that it is decent enough for non-critical applications. Thus, the authors try to utilize Zigbee to create the DSRC-Zigbee heterogeneous network so that the network is independent for the ITS application. The proposed heterogeneous network is a fixed model due to its simple architecture. OMNeT++ and Simulation of Urban Mobility (SUMO) are used to evaluate the performance of the network in an urban area with various scenarios. The simulation result shows that the proposed heterogeneous network is capable to improve the messages dissemination rate by 15.78% and 1.22% in a certain scenario compared to the homogeneous network DSRC only.

MOBILE PHONE TECHNOLOGY FOR ENHANCING SMALL-SCALE FISHING IN TANZANIA. A CASE OF NYASA DISTRICT

 Information and communications technology is a catalyst to the development of socio-economic sectors in Tanzania including the fishing sector. However, despite the contribution made by mobile phone technologies as one of the ICT modern gears in the development of fishing industry, most small-scale fishers are poor, and their working environment is of great risks due to various challenges. This being the case, the current study investigated the extent to which smallscale fishermen use mobile phone technology for enhancing safety and increase of fishery production through the access to reliable market information. The study employed interviews, focus group discussion, documents review, and observation in collecting data. Purposive and snowball sampling techniques were used to obtain 70 respondents from Nyasa District Council which is found in Ruvuma Region, Tanzania. Content analysis technique was employed in data analysis. The findings indicate that although mobile phone technology is used by small-scale fishermen such as marketing of fishery products and sharing information about where to get big cashes, to a great extent, mobile phone technologies do not help them to improve safeties due to various challenges such as poor cell phone network, high costs of purchasing airtime and low quality of mobile handset which in turn hindering an effective communication. It was further observed that drowning, poor knowledge on weather forecast, poor fishing equipment, sexual transmitted diseases, stressful life, and family separation are key challenges that affect the lives of small-scale fishing practitioners in Lake Nyasa. This study contributes knowledge to the already existing literature on the role of mobile phone technology in the development of small-scale fishing sector in Tanzania and it lays down basis for development mobile virtual platform for improving safety and increase fishing productivity of the target users

DUKE: A Solution for Discovering Neighborhood Patterns in Ego Networks

Given the rapid growth of social media websites and the ease of aggregating ever-richer social data, an inevitable research question that can be expected to emerge is whether different interaction patterns of individuals and their meaningful interpretation can be captured for social network analysis. In this work, we present a novel solution that discovers occurrences of prototypical 'ego network' patterns from social media and mobile-phone networks, to provide a data-driven instrument to be used in behavioral sciences for graph interpretations. We analyze nine datasets gathered from social media websites and mobile phones, together with 13 network measures, and three unsupervised clustering algorithms. Further, we use an unsupervised feature similarity technique to reduce redundancy and extract compact features from the data. The reduced feature subsets are then used to discover ego patterns using various clustering techniques. By cluster analysis, we discover that eight distinct ego neighborhood patterns or ego graphs have emerged. This categorization allows concise analysis of users' data as they change over time. We provide fine-grained analysis for the validity and quality of clustering results. We perform clustering verification based on the following three intuitions: i) analyzing the clustering patterns for the same set of users crawled from three social media networks, ii) associating metadata information with the clusters and evaluating their performance on real networks, iii) studying selected participants over an extended period to analyze their behavior.

An intelligent algorithm to reduce and eliminate coverage holes in the mobile network

Abstract The need for services in the world of telecommunications and the prosperity and rapid development of this sector around the world has led mobile phone companies to compete to provide the best services to customers. One of these devices used for communications is the mobile phone. The mobile phone is simply an electronic device that is mainly serving unwired telecommunications through a cellular network of particular base stations known as cell sites. There are many obstacles or problems in the telecommunication field, and the relevant institutions and companies should find solutions to these obstacles and problems. One of these obstacles in telecommunications is the coverage holes. Coverage holes occur when the location of the mobile phone is set in midway between the two base transceiver stations (BTSs). This causes an abnormal interruption in communication until the user crosses the coverage holes area. This paper presents an intelligent algorithm as a set of technical steps that can be used to improve the communication services of the mobile phone network and to solve the communication problems via the reduction of the coverage holes between two BTSs. It suggests a method that could alleviate this problem using a strategy that reduces the coverage holes by developing an intelligent algorithm system to receive signal strength indicators and use AT command “+CREG” to disconnect and reconnect to available BTS within an acceptable energy level. As a result, the connection turned from marginal into good connection.

TRANSIT: Fine-grained human mobility trajectory inference at scale with mobile network signaling data

Call detail records (CDR) collected by mobile phone network providers have been largely used to model and analyze human-centric mobility. Despite their potential, they are limited in terms of both spatial and temporal accuracy thus being unable to capture detailed human mobility information. Network Signaling Data (NSD) represent a much richer source of spatio-temporal information currently collected by network providers, but mostly unexploited for fine-grained reconstruction of human-centric trajectories. In this paper, we present TRANSIT, TRAjectory inference from Network SIgnaling daTa, a novel framework capable of processing NSD to accurately distinguish mobility phases from stationary activities for individual mobile devices, and reconstruct, at scale, fine-grained human mobility trajectories, by exploiting, with a DBSCAN-based clustering approach, the inherent recurrence of human mobility and the higher sampling rate of NSD. The validation on a ground-truth dataset of GPS trajectories showcases the superior performance of TRANSIT (80% precision and 96% recall) with respect to state-of-the-art solutions in the identification of movement periods, as well as an average 190 m spatial accuracy in the estimation of the trajectories. We also leverage TRANSIT to process a unique large-scale NSD dataset of more than 10 millions of individuals and perform an exploratory analysis of city-wide transport mode shares, recurrent commuting paths, urban attractivity and analysis of mobility flows.

Revealing correlation patterns of individual location activity motifs between workdays and day-offs using massive mobile phone data

Recently, people are increasingly interested in understanding broader and longer-term individual activity-travel behaviors across days or even weeks. However, the relationship of individual daily activity-travel behaviors over multi-days only remains partially revealed, especially between workdays and day-offs. Thus, we develop an effective framework to extract individual daily activity-travel patterns from massive mobile phone network data on basis of location activity motifs (LAMs), which are beneficial to combining the locations, activities, and trips in daily activity-travel behaviors. We then discover that the modified number of LAMs over time conforms well to the classic exploration and preferential return (EPR) model after excluding the influence of the number of trips, which reproduces the human activity-travel behavior characteristics on daily scale and indicates that the complex relationship of LAMs exists between workdays and day-offs. Furthermore, we emphasize three categories of correlation patterns while the relationship of LAMs between workdays and day-offs is instantiated using association rules mining algorithm. Ultimately, the regular individual differences and obvious spatial heterogeneity reveal the formation mechanism of correlation patterns. These empirical results contribute to develop different but related transportation strategies between workdays and day-offs by understanding individual daily activity-travel behaviors.

An Investigation of the Influence of Organizational Structure on Performance of Mobile Telephone Network Operators in Kenya

The objective of the study was to investigate influence of organizational structure on performance of Mobile Telephone Network Operators in Kenya. Sub-variables used for the independent variable were teamwork organizational structure, learning organization structure and boundary-less structure. Performance of Mobile Telephone Operators in Kenya was analyzed in terms of profit margins and market share. Structural contingency theory was used to explain the relationship between organizational structures on performance. Mixed methodology was used in collecting and interpreting data. Primary data was gathered using self-guided semi-structured questionnaires and secondary data was obtained from published profit margins and percentages of market share obtained from the companies` reports. Study population was 6,167 which included all the employees in the Mobile Telephone Network Operators in Kenya and a total sample size of 361 employees was obtained but 258 questionnaires were filled and returned. Data analysis was done using descriptive statistics and inferential statistics. The study hypothesis was tested at 95% confidence interval and 0.05 α level of significance. Study H0 stated that: Organizational structure does not positively influence performance of MTNOs in Kenya. Goodness of fit model demonstrated that organizational structure had a positive influence on organizations’ performance of MTNOs accounting for 16.4% of the performance (R squared = 0.164). The study concluded that there was a statistically significant influence of organizational structure on organization`s performance therefore rejecting the null hypothesis H0 at β = 0.405 and P = 0.000.

The e-RFIDuino: An Arduino-based RFID environmental station to monitor mobile tags

We present a datalogger based on Arduino cards and commercially available tools for radio frequency identification, which we term the e-RFIDuino. Designed to be robut, easy to build and install, it detects and records the mobility of objects tagged with active transponders emitting in the ultra-high frequency domain (433.5 MHz). It functions without connection to the power supply network and is adapted to harsh outdoor environments. Once installed in the field and its on-site sensing field is determined, the data collected (timestamp of detection, transponder identification number, and received signal strength indication) allow estimation of the virtual velocity of tracer passage and investigation of displacement patterns at the scale of the area of detection. Experimental tests showed the device to have very high effectiveness when used to monitor the passage of sediment tracers in a torrential river system during various flood events over several months. The total cost to construct this open source device is below 850 Euros, and it is easily customizable. In the future, it could be equipped with a system for data transmission over the mobile telephone network to reduce the field effort and time required to obtain data, and to provide real-time triggering of field acquisitions at the most appropriate times.

Evaluation of home detection algorithms on mobile phone data using individual-level ground truth

Inferring mobile phone users’ home location, i.e., assigning a location in space to a user based on data generated by the mobile phone network, is a central task in leveraging mobile phone data to study social and urban phenomena. Despite its widespread use, home detection relies on assumptions that are difficult to check without ground truth, i.e., where the individual who owns the device resides. In this paper, we present a dataset that comprises the mobile phone activity of sixty-five participants for whom the geographical coordinates of their residence location are known. The mobile phone activity refers to Call Detail Records (CDRs), eXtended Detail Records (XDRs), and Control Plane Records (CPRs), which vary in their temporal granularity and differ in the data generation mechanism. We provide an unprecedented evaluation of the accuracy of home detection algorithms and quantify the amount of data needed for each stream to carry out successful home detection for each stream. Our work is useful for researchers and practitioners to minimize data requests and maximize the accuracy of the home antenna location.

Analysis of Contribution of Employees` Team Building Programs on Performance of Mobile Telephone Network Operators in Kenya

Team building is the process of causing a group of people to work together effectively as a team, especially by means of activities and events designed to increase motivation and promote cooperation. Effective teamwork allows teams to produce outcomes greater than the sum of individual members. The objective of the study was to determine contribution of employees` team building programs on performance of Mobile Telephone Network Operators (MTNOs) in Kenya. Variables used to analyze contribution of employees` team building programs on performance of Mobile Telephone Network Operators (MTNOs) in Kenya were team building workshops, team building seminars and team bonding meetings. Performance of Mobile Telephone Operators was analyzed in terms of profit margins and market share. Social identity theory was used to explain the contribution of employees` team building programs on performance. Study population was 6,167 which included all the employees in the Mobile Telephone Network Operators in Kenya and a total sample size of 361 employees was obtained although only 258 questionnaires were filled and returned. Proportionate stratification formula was used to allocate sample sizes to each department of the Mobile Telephone Operators. Data analysis was done using descriptive statistics and inferential statistics. The hypothesis was tested at 95% confidence interval and 0.05 α level of significance. Study H 0 stated that: employees` team building programs have no significant relationship with performance of MTNOs in Kenya. Goodness of fit model demonstrated that team building programs had a positive influence on performance of MTNOs accounting for 38.1% of the performance (R squared = .381). The study concluded that there was a statistically significant influence of team building programs on performance therefore rejecting the null hypothesis at β = .617, P = .000. Keywords: Team Building Programs, Performance, MTNOs in Kenya DOI: 10.7176/EJBM/13-11-07 Publication date: June 30 th 2021

Exposure of South Korean Population to 5G Mobile Phone Networks (3.4-3.8 GHz).

As industrialized countries race to install and deploy 5G networks, some countries have taken the lead and already have operational 5G networks in place. South Korea is among these. In this study, we measured exposure to electromagnetic fields in South Korea to evaluate the relative contribution of 5G as compared with other frequencies such as 2G, 3G, and 4G. Results show that the emission of 5G contributes about 15% to total telecommunications emissions. The highest levels were observed in the vicinity of 5G antennas and remain below the limits set by the International Commission on Non-Ionizing Radiation Protection (ICNIRP). © 2021 Bioelectromagnetics Society.