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Open Access
Article
Publication date: 22 July 2020

Nsikak P. Owoh and M. Mahinderjit Singh

The proliferation of mobile phones with integrated sensors makes large scale sensing possible at low cost. During mobile sensing, data mostly contain sensitive information of…

1830

Abstract

The proliferation of mobile phones with integrated sensors makes large scale sensing possible at low cost. During mobile sensing, data mostly contain sensitive information of users such as their real-time location. When such information are not effectively secured, users’ privacy can be violated due to eavesdropping and information disclosure. In this paper, we demonstrated the possibility of unauthorized access to location information of a user during sensing due to the ineffective security mechanisms in most sensing applications. We analyzed 40 apps downloaded from Google Play Store and results showed a 100% success rate in traffic interception and disclosure of sensitive information of users. As a countermeasure, a security scheme which ensures encryption and authentication of sensed data using Advanced Encryption Standard 256-Galois Counter Mode was proposed. End-to-end security of location and motion data from smartphone sensors are ensured using the proposed security scheme. Security analysis of the proposed scheme showed it to be effective in protecting Android based sensor data against eavesdropping, information disclosure and data modification.

Details

Applied Computing and Informatics, vol. 18 no. 1/2
Type: Research Article
ISSN: 2210-8327

Keywords

Open Access
Article
Publication date: 20 August 2021

Daniel Hofer, Markus Jäger, Aya Khaled Youssef Sayed Mohamed and Josef Küng

For aiding computer security experts in their study, log files are a crucial piece of information. Especially the time domain is very important for us because in most cases…

2112

Abstract

Purpose

For aiding computer security experts in their study, log files are a crucial piece of information. Especially the time domain is very important for us because in most cases, timestamps are the only linking points between events caused by attackers, faulty systems or simple errors and their corresponding entries in log files. With the idea of storing and analyzing this log information in graph databases, we need a suitable model to store and connect timestamps and their events. This paper aims to find and evaluate different approaches how to store timestamps in graph databases and their individual benefits and drawbacks.

Design/methodology/approach

We analyse three different approaches, how timestamp information can be represented and stored in graph databases. For checking the models, we set up four typical questions that are important for log file analysis and tested them for each of the models. During the evaluation, we used the performance and other properties as metrics, how suitable each of the models is for representing the log files’ timestamp information. In the last part, we try to improve one promising looking model.

Findings

We come to the conclusion, that the simplest model with the least graph database-specific concepts in use is also the one yielding the simplest and fastest queries.

Research limitations/implications

Limitations to this research are that only one graph database was studied and also improvements to the query engine might change future results.

Originality/value

In the study, we addressed the issue of storing timestamps in graph databases in a meaningful, practical and efficient way. The results can be used as a pattern for similar scenarios and applications.

Details

International Journal of Web Information Systems, vol. 17 no. 5
Type: Research Article
ISSN: 1744-0084

Keywords

Open Access
Article
Publication date: 19 April 2022

Niklas Rönnberg, Rasmus Ringdahl and Anna Fredriksson

The noise and dust particles caused by the construction transport are by most stakeholders experienced as disturbing. The purpose of this study is to explore how sonification can…

1101

Abstract

Purpose

The noise and dust particles caused by the construction transport are by most stakeholders experienced as disturbing. The purpose of this study is to explore how sonification can support visualization in construction planning to decrease construction transport disturbances.

Design/methodology/approach

This paper presents an interdisciplinary research project, combining research on construction logistics, internet of things and sonification. First, a data recording device, including sound, particle, temperature and humidity sensors, was implemented and deployed in a development project. Second, the collected data were used in a sonification design, which was, third, evaluated with potential users.

Findings

The results showed that the low-cost sensors used could capture “good enough” data, and that the use of sonification for representing these data is interesting and a possible useful tool in urban and construction transport planning.

Research limitations/implications

There is a need to further evolve the sonification design and better communicate the aim of the sounds used to potential users. Further testing is also needed.

Practical implications

This study introduces new ideas of how to support visualization with sonification planning the construction work and its impact on the vicinity of the site. Currently, urban planning and construction planning focus on visualizing the final result, with little focus on how to handle disturbances during the construction process.

Originality/value

Showing the potentials of using low-cost sensor data in sonification, and using sonification together with visualization, is the result of a novel interdisciplinary research area combination.

Details

Smart and Sustainable Built Environment, vol. 12 no. 4
Type: Research Article
ISSN: 2046-6099

Keywords

Open Access
Article
Publication date: 24 March 2021

Maria Banagou, Saša Batistič, Hien Do and Rob F. Poell

Understanding employee knowledge hiding behavior can serve organizations in better implementing knowledge management practices. The purpose of this study is to investigate how…

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Abstract

Purpose

Understanding employee knowledge hiding behavior can serve organizations in better implementing knowledge management practices. The purpose of this study is to investigate how personality and work climate influence knowledge hiding, by examining the respective roles of openness to experience and relational (specifically, communal sharing and market pricing) climates.

Design/methodology/approach

Multilevel modeling was used with two distinct samples, one from Vietnam with 119 employees in 20 teams and one from The Netherlands with 136 employees in 32 teams.

Findings

In both samples, the hypothesized direct relationship between openness and knowledge hiding was not found. In the Vietnamese sample, only the moderating effect of market pricing climate was confirmed; in the Dutch sample, only the moderating effect of communal sharing climate was confirmed. The findings of the Vietnamese sample suggest that people with a high sense of openness to experience hide knowledge less under low market pricing climate. In the Dutch sample, people with high openness to experience hide knowledge less under high communal sharing climate. The authors conclude that, in comparison with personality, climate plays a stronger role in predicting knowledge hiding behavior.

Research limitations/implications

Small sample size and self-reported data might limit the generalizability of this study’s results.

Practical implications

The paper highlights how organizational context (relational climate) needs to be taken into account in predicting how personality (openness to experience) affects knowledge hiding.

Originality/value

This paper contributes to a better understanding of the knowledge hiding construct by extending the set of known antecedents and exploring the organizational context in which such phenomena happen.

Details

Journal of Knowledge Management, vol. 25 no. 11
Type: Research Article
ISSN: 1367-3270

Keywords

Open Access
Article
Publication date: 5 June 2020

Matthew B. Perrigino, Benjamin B. Dunford, Paul G. Biondich, Theresa Cullen and Benjamin R. Pratt

Open source software (OSS) communities devoted to the development of electronic medical records (EMRs) have grown in recent years. The purpose of this paper is to focus on the…

Abstract

Purpose

Open source software (OSS) communities devoted to the development of electronic medical records (EMRs) have grown in recent years. The purpose of this paper is to focus on the challenge the leaders of these communities face in terms of building perceptions of psychological ownership among community members.

Design/methodology/approach

Surveys (n = 50) and brief interviews (n = 56) with individual members of an open source EMR community (most of whom are based in African nations) were used.

Findings

Among community members, normative commitment (in comparison to extrinsic motivation and affective commitment) was the strongest predictor of psychological ownership. Interviews revealed that community members tended to feel a greater sense of ownership toward the end user (i.e. hospitals and clinics) than toward the community itself.

Practical implications

To foster engagement and retention – and enhance the worldwide impact of their community on healthcare practices – leaders of open source EMR communities can offer incentives related to certifications and status-based rewards, hold annual meetings to allow members to develop a better understanding of the community and encourage members to “pay it forward” by involving end users (i.e. hospital and clinic employees) within the community, thus furthering public health initiatives.

Originality/value

OSS communities experience unique challenges compared to traditional organizations. This necessitates a reconsideration of the applicability of commonly accepted principles, tenets and recommendations from the management literature.

Details

Journal of Humanities and Applied Social Sciences, vol. 2 no. 3
Type: Research Article
ISSN: 2632-279X

Keywords

Open Access
Article
Publication date: 7 July 2022

Sirilak Ketchaya and Apisit Rattanatranurak

Sorting is a very important algorithm to solve problems in computer science. The most well-known divide and conquer sorting algorithm is quicksort. It starts with dividing the…

1188

Abstract

Purpose

Sorting is a very important algorithm to solve problems in computer science. The most well-known divide and conquer sorting algorithm is quicksort. It starts with dividing the data into subarrays and finally sorting them.

Design/methodology/approach

In this paper, the algorithm named Dual Parallel Partition Sorting (DPPSort) is analyzed and optimized. It consists of a partitioning algorithm named Dual Parallel Partition (DPPartition). The DPPartition is analyzed and optimized in this paper and sorted with standard sorting functions named qsort and STLSort which are quicksort, and introsort algorithms, respectively. This algorithm is run on any shared memory/multicore systems. OpenMP library which supports multiprocessing programming is developed to be compatible with C/C++ standard library function. The authors’ algorithm recursively divides an unsorted array into two halves equally in parallel with Lomuto's partitioning and merge without compare-and-swap instructions. Then, qsort/STLSort is executed in parallel while the subarray is smaller than the sorting cutoff.

Findings

In the authors’ experiments, the 4-core Intel i7-6770 with Ubuntu Linux system is implemented. DPPSort is faster than qsort and STLSort up to 6.82× and 5.88× on Uint64 random distributions, respectively.

Originality/value

The authors can improve the performance of the parallel sorting algorithm by reducing the compare-and-swap instructions in the algorithm. This concept can be used to develop related problems to increase speedup of algorithms.

Details

Applied Computing and Informatics, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2634-1964

Keywords

Open Access
Article
Publication date: 30 September 2021

Samuel Heuchert, Bhaskar Prasad Rimal, Martin Reisslein and Yong Wang

Major public cloud providers, such as AWS, Azure or Google, offer seamless experiences for infrastructure as a service (IaaS), platform as a service (PaaS) and software as a…

2292

Abstract

Purpose

Major public cloud providers, such as AWS, Azure or Google, offer seamless experiences for infrastructure as a service (IaaS), platform as a service (PaaS) and software as a service (SaaS). With the emergence of the public cloud's vast usage, administrators must be able to have a reliable method to provide the seamless experience that a public cloud offers on a smaller scale, such as a private cloud. When a smaller deployment or a private cloud is needed, OpenStack can meet the goals without increasing cost or sacrificing data control.

Design/methodology/approach

To demonstrate these enablement goals of resiliency and elasticity in IaaS and PaaS, the authors design a private distributed system cloud platform using OpenStack and its core services of Nova, Swift, Cinder, Neutron, Keystone, Horizon and Glance on a five-node deployment.

Findings

Through the demonstration of dynamically adding an IaaS node, pushing the deployment to its physical and logical limits, and eventually crashing the deployment, this paper shows how the PackStack utility facilitates the provisioning of an elastic and resilient OpenStack-based IaaS platform that can be used in production if the deployment is kept within designated boundaries.

Originality/value

The authors adopt the multinode-capable PackStack utility in favor of an all-in-one OpenStack build for a true demonstration of resiliency, elasticity and scalability in a small-scale IaaS. An all-in-one deployment is generally used for proof-of-concept deployments and is not easily scaled in production across multiple nodes. The authors demonstrate that combining PackStack with the multi-node design is suitable for smaller-scale production IaaS and PaaS deployments.

Details

Applied Computing and Informatics, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2634-1964

Keywords

Open Access
Article
Publication date: 28 March 2022

Yunfei Li, Shengbo Eben Li, Xingheng Jia, Shulin Zeng and Yu Wang

The purpose of this paper is to reduce the difficulty of model predictive control (MPC) deployment on FPGA so that researchers can make better use of FPGA technology for academic…

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Abstract

Purpose

The purpose of this paper is to reduce the difficulty of model predictive control (MPC) deployment on FPGA so that researchers can make better use of FPGA technology for academic research.

Design/methodology/approach

In this paper, the MPC algorithm is written into FPGA by combining hardware with software. Experiments have verified this method.

Findings

This paper implements a ZYNQ-based design method, which could significantly reduce the difficulty of development. The comparison with the CPU solution results proves that FPGA has a significant acceleration effect on the solution of MPC through the method.

Research limitations implications

Due to the limitation of practical conditions, this paper cannot carry out a hardware-in-the-loop experiment for the time being, instead of an open-loop experiment.

Originality value

This paper proposes a new design method to deploy the MPC algorithm to the FPGA, reducing the development difficulty of the algorithm implementation on FPGA. It greatly facilitates researchers in the field of autonomous driving to carry out FPGA algorithm hardware acceleration research.

Details

Journal of Intelligent and Connected Vehicles, vol. 5 no. 2
Type: Research Article
ISSN: 2399-9802

Keywords

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