Strategic Choices and Organizational Challenges in Times of Crisis: Illustration of the Experience of Two Moroccan SMEs

The aim of this work is to show that organizational change is a response to certain problems generated by a market specialization strategy. Our study is based on two cases of SMEs that first engaged in a business relationship with a single client for more than five years. This led to a high degree of skills specialization and a certain organizational rigidity which was subsequently detrimental to the continuity of the company's activity, particularly when the relationship with the only single client was unexpectedly concluded, for the client had become increasingly demanding in terms of cost and time. Analysis of the data shows that both SMEs have made a series of organizational changes (restructuring of the company, recruitment of new skills, training activities, use of partnerships with other organizations, etc.) to overcome this perilous situation. As a consequence, these companies were able to reorient their business policy in order to reduce their dependence and then ensure their business sustainability and growth. Keywords: Organizational change, dependency situation, customer-supplier relationship, strategic choices. DOI: 10.7176/EJBM/12-27-04 Publication date:September 30th 202

Is the conditional entropy squeezing indicts the normalized entropic uncertainty relations steering?

A novel approach is introduced to assess one-way Normalized Entropic Uncertainty Relations (NEUR)-steering in a two-qubit system by utilizing an average of conditional entropy squeezing. The mathematical expressions of conditional entropy squeezing and NEUR-steering are derived and presented. To gain a better understanding of the relationship between the two measures, a comparative analysis is conducted on a set of two-qubit states. Our results reveal that the two measures exhibit complete similarity when applied to a maximally entangled state, while they display comparable behavior with minor deviations for partially entangled states. Additionally, it is observed that the two measures are proportionally affected by some quantum processes such as acceleration, noisy channels, and swapping. As a result, the average of conditional entropy squeezing proves to be an effective indicator of NEUR-steering.Comment: 8 pages, 5 figures. All comments are welcom

Improving the bidirectional steerability between two accelerated partners via filtering process

The bidirectional steering between two accelerated partners sharing initially different classes of entangled states is discussed. Due to the decoherence, the steerability and its degree decrease either as the acceleration increases or the partners share initially a small amount of quantum correlations. The possibility of increasing the steerability is investigated by applying the filtering process. Our results show that by increasing the filtering strength, one can improve the upper bounds of the steerability and the range of acceleration at which the steerability is possible. Steering large coherent states is much better than steering less coherent ones

Quantumness near a Schwarzschild black hole

The merging of quantum information science with the relativity theory presents novel opportunities for understanding the enigmas surrounding the transmission of information in relation to black holes. For this purpose, we study the quantumness near a Schwarzschild black hole in a practical model under decoherence. The scenario we consider in this paper is that a stationary particle in the flat region interacts with its surroundings while another particle experiences free fall in the vicinity of a Schwarzschild black hole's event horizon. We explore the impacts of Hawking radiation and decoherence on the system under investigation and find that these effects can limit the survival of quantum characteristics, but cannot destroy them completely. Hence, the results of this study possess the potential to yield valuable insights into the comprehension of the quantum properties of a real system operating within a curved space-time framework.Comment: 13 pages, 9 figures. All comments are welcom

Investigating multi-GNSS performance in the UK and China based on a zero-baseline measurement approach

GPS is the positioning tool of choice for a wide variety of applications where accurate (cm level or less) positions are required. However GPS is susceptible to a variety of errors that degrade both the quality of the position solution and the availability of these solutions. The contribution of additional observations from other GNSS systems may improve the quality of the positioning solution. This study investigates the contribution of the GLONASS and BeiDou systems and the potential improvement to the precision achieved compared to positioning using GPS only measurements. Furthermore, it is investigated whether the combination of the satellite systems can limit the noise level of the GPS-only solution. A series of zero-baseline measurements, of 1 Hz sampling rate, were recorded with different types of pairs of receivers over 12 consecutive days in the UK and in China simultaneously. The novel part in this study is comparing the simultaneous GNSS real measurements recorded in the UK and China. Moreover, the correlation between the geometry and positional precision was investigated. The results indicate an improvement in a multi-GNSS combined solution compared to the GPS-only solution, especially when the GPS-only solution derives from weak satellite geometry, or the GPS-only solution is not available. Furthermore, all the outliers due to poor satellite coverage with the individual solutions are limited and their precision is improved, agreeing also with the improvement in the mean of the GDOP, i.e. the mean GDOP was improved from 3.0 for the GPS only solution to 1.8 for the combined solution. However, the combined positioning did not show significant positional improvement when GPS has a good geometry and availability

Integration of GPS Precise Point Positioning and MEMS-Based INS Using Unscented Particle Filter

Integration of Global Positioning System (GPS) and Inertial Navigation System (INS) integrated system involves nonlinear motion state and measurement models. However, the extended Kalman filter (EKF) is commonly used as the estimation filter, which might lead to solution divergence. This is usually encountered during GPS outages, when low-cost micro-electro-mechanical sensors (MEMS) inertial sensors are used. To enhance the navigation system performance, alternatives to the standard EKF should be considered. Particle filtering (PF) is commonly considered as a nonlinear estimation technique to accommodate severe MEMS inertial sensor biases and noise behavior. However, the computation burden of PF limits its use. In this study, an improved version of PF, the unscented particle filter (UPF), is utilized, which combines the unscented Kalman filter (UKF) and PF for the integration of GPS precise point positioning and MEMS-based inertial systems. The proposed filter is examined and compared with traditional estimation filters, namely EKF, UKF and PF. Tightly coupled mechanization is adopted, which is developed in the raw GPS and INS measurement domain. Un-differenced ionosphere-free linear combinations of pseudorange and carrier-phase measurements are used for PPP. The performance of the UPF is analyzed using a real test scenario in downtown Kingston, Ontario. It is shown that the use of UPF reduces the number of samples needed to produce an accurate solution, in comparison with the traditional PF, which in turn reduces the processing time. In addition, UPF enhances the positioning accuracy by up to 15% during GPS outages, in comparison with EKF. However, all filters produce comparable results when the GPS measurement updates are available

Non-Linear Filtering for Precise Point Positioning GPS/INS integration

This research investigates the performance of non-linear estimation filtering for GPS-PPP/MEMS-based inertial system. Although integrated GPS/INS system involves nonlinear motion state and measurement models, the most common estimation filter employed is extended Kalman filter. In this paper, both unscented Kalman filter and particle filter are developed and compared with extended Kalman filter. Tightly coupled mechanization is adopted, which is developed in the raw measurements domain. Un-differenced ionosphere-free linear combination of pseudorange and carrier-phase measurements is employed. The performance of the proposed non-linear filters is analyzed using real test scenario. The test results indicate that comparable accuracy-level are obtained from the proposed filters compared with extended Kalman filter in positioning, velocity and attitude when the measurement updates from GPS measurements are available