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21 – 30 of over 10000Rong Wang, Jin Wu, Chong Li, Shengbo Qi, Xiangrui Meng, Xinning Wang and Chengxi Zhang
The purpose of this paper is to propose a high-precision attitude solution to solve the attitude drift problem caused by the dispersion of low-cost micro-electro-mechanical system…
Abstract
Purpose
The purpose of this paper is to propose a high-precision attitude solution to solve the attitude drift problem caused by the dispersion of low-cost micro-electro-mechanical system devices in strap-down inertial navigation attitude solution of micro-quadrotor.
Design/methodology/approach
In this study, a three-stage attitude estimation scheme that combines data preprocessing, gyro drifts prediction and enhanced unscented Kalman filtering (UKF) is proposed. By introducing a preprocessing model, the quaternion orientation is calculated as the composition of two algebraic quaternions, and the decoupling feature of the two quaternions makes the roll and pitch components independent of magnetic interference. A novel real-time based on differential value (DV) estimation algorithm is proposed for gyro drift. This novel solution prevents the impact of quartic characteristics and uses the iterative method to meet the requirement of real-time applications. A novel attitude determination algorithm, the pre-process DV-UKF algorithm, is proposed in combination with UKF based on the above solution and its characteristics.
Findings
Compared to UKF, both simulation and experimental results demonstrate that the pre-process DV-UKF algorithm has higher reliability in attitude determination. The dynamic errors in the three directions of the attitude are below 2.0°, the static errors are all less than 0.2° and the absolute attitude errors tailored by average are about 47.98% compared to the UKF.
Originality/value
This paper fulfils an identified need to achieve high-precision attitude estimation when using low-cost inertial devices in micro-quadrotor. The accuracy of the pre-process DV-UKF algorithm is superior to other products in the market.
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Huiliang Cao, Rang Cui, Wei Liu, Tiancheng Ma, Zekai Zhang, Chong Shen and Yunbo Shi
To reduce the influence of temperature on MEMS gyroscope, this paper aims to propose a temperature drift compensation method based on variational modal decomposition (VMD)…
Abstract
Purpose
To reduce the influence of temperature on MEMS gyroscope, this paper aims to propose a temperature drift compensation method based on variational modal decomposition (VMD), time-frequency peak filter (TFPF), mind evolutionary algorithm (MEA) and BP neural network.
Design/methodology/approach
First, VMD decomposes gyro’s temperature drift sequence to obtain multiple intrinsic mode functions (IMF) with different center frequencies and then Sample entropy calculates, according to the complexity of the signals, they are divided into three categories, namely, noise signals, mixed signals and temperature drift signals. Then, TFPF denoises the mixed-signal, the noise signal is directly removed and the denoised sub-sequence is reconstructed, which is used as training data to train the MEA optimized BP to obtain a temperature drift compensation model. Finally, the gyro’s temperature characteristic sequence is processed by the trained model.
Findings
The experimental result proved the superiority of this method, the bias stability value of the compensation signal is 1.279 × 10–3°/h and the angular velocity random walk value is 2.132 × 10–5°/h/vHz, which is improved compared to the 3.361°/h and 1.673 × 10–2°/h/vHz of the original output signal of the gyro.
Originality/value
This study proposes a multi-dimensional processing method, which treats different noises separately, effectively protects the low-frequency characteristics and provides a high-precision training set for drift modeling. TFPF can be optimized by SEVMD parallel processing in reducing noise and retaining static characteristics, MEA algorithm can search for better threshold and connection weight of BP network and improve the model’s compensation effect.
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Spam emails classification using data mining and machine learning approaches has enticed the researchers' attention duo to its obvious positive impact in protecting internet…
Abstract
Spam emails classification using data mining and machine learning approaches has enticed the researchers' attention duo to its obvious positive impact in protecting internet users. Several features can be used for creating data mining and machine learning based spam classification models. Yet, spammers know that the longer they will use the same set of features for tricking email users the more probably the anti-spam parties might develop tools for combating this kind of annoying email messages. Spammers, so, adapt by continuously reforming the group of features utilized for composing spam emails. For that reason, even though traditional classification methods possess sound classification results, they were ineffective for lifelong classification of spam emails duo to the fact that they might be prone to the so-called “Concept Drift”. In the current study, an enhanced model is proposed for ensuring lifelong spam classification model. For the evaluation purposes, the overall performance of the suggested model is contrasted against various other stream mining classification techniques. The results proved the success of the suggested model as a lifelong spam emails classification method.
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Gitte Tjornehoj and Lars Mathiassen
While the literature on software process improvement (SPI) offers a number of studies of small software firms, little is known about how such initiatives evolve over time. On this…
Abstract
Purpose
While the literature on software process improvement (SPI) offers a number of studies of small software firms, little is known about how such initiatives evolve over time. On this backdrop, this paper aims to investigate how adoption of SPI technology was shaped over a ten year period (1996‐2005) in a small Danish software firm.
Design/methodology/approach
The investigation is based on a longitudinal, interpretative case study of improvement efforts over a ten‐year period. To help structure the investigation, we focus on encounters that impacted engineering, management, and improvement practices within the firm. The study contributes to the SPI‐literature and the literature on organizational adoption of technology.
Findings
The paper finds the improvement effort fluctuating and shaped between management's attempt to control SPI technology adoption and events that caused the process to drift in unpredictable directions.
Practical implications
The experiences suggest that managers of small software firms remain flexible and constantly negotiate technology adoption practices between control and drift, creating momentum and direction according to firm goals through attempts to control, while at the same time exploring backtalk, options, and innovations from drifting forces inside and outside the firm.
Originality/value
Based on the research, the paper recommends substituting the “from control to drift” perspective on organizational adoption of complex technologies like SPI with a “negotiating control and drift” perspective.
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The purpose of this paper is to present a novel and simple prediction model of long-term metal oxide semiconductor (MOS) gas sensor baseline, and it brings some new perspectives…
Abstract
Purpose
The purpose of this paper is to present a novel and simple prediction model of long-term metal oxide semiconductor (MOS) gas sensor baseline, and it brings some new perspectives for sensor drift. MOS gas sensors, which play a very important role in electronic nose (e-nose), constantly change with the fluctuation of environmental temperature and humidity (i.e. drift). Therefore, it is very meaningful to realize the long-term time series estimation of sensor signal for drift compensation.
Design/methodology/approach
In the proposed sensor baseline drift prediction model, auto-regressive moving average (ARMA) and Kalman filter models are used. The basic idea is to build the ARMA and Kalman models on the short-term sensor signal collected in a short period (one month) by an e-nose and aim at realizing the long-term time series prediction in a year using the obtained model.
Findings
Experimental results demonstrate that the proposed approach based on ARMA and Kalman filter is very effective in time series prediction of sensor baseline signal in e-nose.
Originality/value
Though ARMA and Kalman filter are well-known models in signal processing, this paper, at the first time, brings a new perspective for sensor drift prediction problem based on the two typical models.
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Output stability or drift overtime has long been a major performance deficiency for gas sensors irrespective of what technology or methodology is used for their conception…
Abstract
Purpose
Output stability or drift overtime has long been a major performance deficiency for gas sensors irrespective of what technology or methodology is used for their conception. Software correction may alleviate the problem somewhat but it is not always applicable. It has long been the objective of many researchers in this field to overcome this problem fundamentally and for good. The purpose of this paper is to show that this objective has now finally been achieved.
Design/methodology/approach
Conventional non‐dispersive infrared (NDIR) dual beam methodology utilizes the ratio of signal channel output over reference channel output for signal processing. The signal filter overlaps the absorption band of the gas of interest while the reference filter does not. However, this ratio changes as the source ages. The current methodology uses an absorption bias between signal and reference channel outputs. This absorption bias is created by using a path length for the signal channel greater than that for the reference channel. Both the signal and reference detectors carry an identical spectral filter overlapping the absorption band of the gas to be measured.
Findings
Implementation of the currently patented NDIR gas‐sensing methodology has been carried out in different gas sensor configurations for over a year in the laboratory. Performance results for these sensors showing insignificant output drifts overtime have been repeatedly demonstrated via simulated aging for the source.
Originality/value
The paper puts forward the view that the recent breakthrough of the Near Zero Drift methodology for NDIR gas sensors will very quickly change the hierarchy of technology dominance and utility for gas sensors at large.
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Signe Vikkelsø, Mikkel Stokholm Skaarup and Julie Sommerlund
Innovation partnerships are a popular model for organizing publicly supported innovation projects. However, partners often have different timelines and planning horizons…
Abstract
Purpose
Innovation partnerships are a popular model for organizing publicly supported innovation projects. However, partners often have different timelines and planning horizons, understanding of purpose and concepts of value. This hybridity poses organizational challenges pertaining to trust, goal setting, learning and coordination, which may lead to “mission drift,” i.e. compromising or displacement of intended goals. Despite the risk mission drift poses, its underlying dynamics are not sufficiently understood, and the means to mitigate it are unclear. This study aims to address these questions.
Design/methodology/approach
Through eight broad and one deep case study of innovation partnerships funded by Innovation Fund Denmark (IFD), the authors investigate how partnerships reconcile multiple expectations and interests within the IFD framework and how this might lead to mission drift. The authors draw upon existing theories on the organizational challenges of innovation partnerships and supplement these with new empirically based propositions on the risk of mission drift.
Findings
This study identifies a core tension between partnership complexity and the degree of formalization. Depending on how these dimensions are combined in relation to particular goals, the partnership mission is likely to become narrower or more unpredictable than intended. Thus, the authors theorize the significance of partnership composition and requisite formalization for a given innovation purpose.
Originality/value
This study contributes to the theoretical understanding of mission drift in innovation partnerships by opening the organizational black box of partnerships. The findings underscore the value of explorative case studies for specifying the contingencies of organizational design and governance mechanisms for different innovation goals.
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G. Geoffrey Booth, Juha‐Pekka Kallunki, Petri Sahlström and Jaakko Tyynelä
This paper aims to investigate who causes post‐announcement drift and whether this drift is observed for various types of news announcements.
Abstract
Purpose
This paper aims to investigate who causes post‐announcement drift and whether this drift is observed for various types of news announcements.
Design/methodology/approach
Using Finnish share ownership data, the authors examine the trading behavior of foreign and domestic investors during the post‐announcement periods of scheduled earnings and unscheduled non‐earnings announcements.
Findings
The results show that the post‐announcement drift exists for both types of news, but only if the news is negative. As a group, foreign investors react first by selling shares of firms reporting negative information. Domestic investors act in the opposite manner.
Originality/value
The results imply that the post‐announcement drift is a special case of a more general post‐disclosure phenomenon and that investor differences (most likely information processing skills) is one likely explanation for its pervasiveness.
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Jintian Hu, Jin Liu, Yidi Wang and Xiaolin Ning
This study aims to address the problem of the divergence of traditional inertial navigation system (INS)/celestial navigation system (CNS)-integrated navigation for ballistic…
Abstract
Purpose
This study aims to address the problem of the divergence of traditional inertial navigation system (INS)/celestial navigation system (CNS)-integrated navigation for ballistic missiles. The authors introduce Doppler navigation system (DNS) and X-ray pulsar navigation (XNAV) to the traditional INS/CNS-integrated navigation system and then propose an INS/CNS/DNS/XNAV deep integrated navigation system.
Design/methodology/approach
DNS and XNAV can provide velocity and position information, respectively. In addition to providing velocity information directly, DNS suppresses the impact of the Doppler effect on pulsar time of arrival (TOA). A pulsar TOA with drift bias is observed during the short navigation process. To solve this problem, the pulsar TOA drift bias model is established. And the parameters of the navigation filter are optimised based on this model.
Findings
The experimental results show that the INS/CNS/DNS/XNAV deep integrated navigation can suppress the drift of the accelerometer to a certain extent to improve the precision of position and velocity determination. In addition, this integrated navigation method can reduce the required accuracy of inertial navigation, thereby reducing the cost of missile manufacturing and realising low-cost and high-precision navigation.
Originality/value
The velocity information provided by the DNS can suppress the pulsar TOA drift, thereby improving the positioning accuracy of the XNAV. This reflects the “deep” integration of these two navigation methods.
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Hesam Ketabdari, Amir Saedi Daryan, Nemat Hassani and Mohammad Safi
In this paper, the seismic behavior of the gusset plate moment connection (GPMC) exposed to the post-earthquake fire (PEF) is investigated.
Abstract
Purpose
In this paper, the seismic behavior of the gusset plate moment connection (GPMC) exposed to the post-earthquake fire (PEF) is investigated.
Design/methodology/approach
For this purpose, for the sake of verification, first, a numerical model is built using ABAQUS software and then exposed to earthquakes and high temperatures. Afterward, the effects of a series of parameters, such as gusset plate thickness, gap width, steel grade, vertical load value and presence of the stiffeners, are evaluated on the behavior of the connection in the PEF conditions.
Findings
Based on the results obtained from the parametric study, all parameters effectively played a role against the seismic loads, although, when exposed to fire, it was found that the vertical load value and presence of the stiffener revealed a great contribution and the other parameters could not significantly affect the connection performance. Finally, to develop the modeling and further study the performance of the connection, the 4 and 8-story frames are subjected to 11 accelerograms and 3 different fire scenarios. The findings demonstrate that high temperatures impose rotations on the structure, such that the story drifts were changed compared to the post-earthquake drift values.
Originality/value
The obtained results can be used by engineers to design the GPMC for the combined action of earthquake and fire.
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