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The purpose of this paper is to establish a combined forecasting model to predict regional logistics demand, which is an important procedure on decision making of regional logistics planning.

There are several kinds of mathematical models often used in forecasting regional logistics demand. Trend extrapolation method extrapolates the future development trends bases on the hypothesis that the regional logistics will develop steadily. Grey system method predicts the change of logistics demand by the generation and development of original data sequence and excavation of inherent rules of the original data. Regression method obtains the change rules through the analysis between explained variable and explanatory variables. Each method has unique characteristics. In order to improve the accuracy of the prediction, combined methods are established. Genetic algorithm is used to determine the weights of different single models.

The results show that the combined forecasting model optimised by genetic algorithm can improve the accuracy.

Combined forecasting model can integrate the advantages of different single forecasting models. The key of improving the accuracy is to determine the weights of single forecasting models. Genetic algorithm can do well in finding suitable weights of each single forecasting model.

The paper succeeds in providing a combined forecasting model using genetic algorithm to determine the weights of each single prediction model, which helps to the decision making of regional logistics demand.

The purpose of this paper is to describe and discuss the use of Chinese medicine in the prevention and treatment of coronavirus disease 2019 (COVID-19) in China and Asia.

This paper provides a brief overview of the COVID-19. Based on the syndrome differentiation (辨證論治), the concept of clearing heat and detoxifying lung in traditional Chinese medicine is used to prevent and treat COVID-19 through restoring the vital qi (正氣) in human body and regulating the lung as well as spleen to strengthen the immune system. Traditional Chinese medicine has been used as a complementary therapy for the possible intervention of COVID-19 including traditional Chinese herbal decoctions, Chinese traditional patent medicines, acupuncture and moxibustion as well as the traditional health exercises in China and parts of Asia.

Traditional Chinese medicine plays a significant role in the prevention and treatment of COVID-19 pandemic. The infection cases of China are around 80,000 and a steady decline compared with the USA which has 5,000,000 infection cases and continuous increases. It is shown that more than 90% of patients recovered after the treatment of traditional Chinese herbal decoctions and Chinese traditional patent medicines without any side-effect compared to the use of Remdesivir (GS-5734). Acupuncture (針灸) and moxibustion (艾灸) stimulate the immune and nervous systems for preventing infectious diseases. Taichi (太極) and Baduanjin (八段錦) as the auxiliary aerobic exercise under the theory of Chinese medicine can enhance the immune system and improve the lung function. Thus, an integration of traditional Chinese Medicine and Western medicine is the best strategy for the prevention, treatment and control of COVID-19 pandemic in the future.

This paper describes traditional Chinese medicine as an effective way for the prevention and treatment of COVID-19.

Displacement measurement in large-scale structures (such as excavation walls) is one of the most important applications of close-range photogrammetry, in which achieving high precision requires extracting and accurately matching local features from convergent images. The purpose of this study is to introduce a new multi-image pointing (MIP) algorithm is introduced based on the characteristics of the geometric model generated from the initial matching. This self-adaptive algorithm is used to correct and improve the accuracy of the extracted positions from local features in the convergent images.

In this paper, the new MIP algorithm based on the geometric characteristics of the model generated from the initial matching was introduced, which in a self-adaptive way corrected the extracted image coordinates. The unique characteristics of this proposed algorithm were that the position correction was accomplished with the help of continuous interaction between the 3D model coordinates and the image coordinates and that it had the least dependency on the geometric and radiometric nature of the images. After the initial feature extraction and implementation of the MIP algorithm, the image coordinates were ready for use in the displacement measurement process. The combined photogrammetry displacement adjustment (CPDA) algorithm was used for displacement measurement between two epochs. Micro-geodesy, target-based photogrammetry and the proposed MIP methods were used in a displacement measurement project for an excavation wall in the Velenjak area in Tehran, Iran, to evaluate the proposed algorithm performance. According to the results, the measurement accuracy of the point geo-coordinates of 8 mm and the displacement accuracy of 13 mm could be achieved using the MIP algorithm. In addition to the micro-geodesy method, the accuracy of the results was matched by the cracks created behind the project’s wall. Given the maximum allowable displacement limit of 4 cm in this project, the use of the MIP algorithm produced the required accuracy to determine the critical displacement in the project.

Evaluation of the results demonstrated that the accuracy of 8 mm in determining the position of the points on the feature and the accuracy of 13 mm in the displacement measurement of the excavation walls could be achieved using precise positioning of local features on images using the MIP algorithm.The proposed algorithm can be used in all applications that need to achieve high accuracy in determining the 3D coordinates of local features in close-range photogrammetry.

Some advantages of the proposed MIP photogrammetry algorithm, including the ease of obtaining observations and using local features on the structure in the images rather than installing the artificial targets, make it possible to effectively replace micro-geodesy and instrumentation methods. In addition, the proposed MIP method is superior to the target-based photogrammetric method because it does not need artificial target installation and protection. Moreover, in each photogrammetric application that needs to determine the exact point coordinates on the feature, the proposed algorithm can be very effective in providing the possibility to achieve the required accuracy according to the desired objectives.

With the upgrade of natural language interaction technology, the simulation extension of intelligent voice assistants (IVAs) and the uncertainty of products and services have received more and more attention. However, most of the existing research focuses on investigating the application of theories to explain consumer behavior related to intention to use and adopt IVAs, while ignoring the impact of its privacy issues on consumer resistance. This article especially examines the negative impact of artificial intelligence-based IVAs’ privacy concerns on consumer resistance, and studies the mediating effect of perceived creepiness in the context of privacy cynicism and privacy paradox and the moderating effect of anthropomorphized roles of IVAs and perceived corporate social responsibility (CSR) of IVAs’ companies. The demographic variables are also included.

Based on the theory of human–computer interaction (HCI), this study addresses the consumer privacy concerns of IVAs, builds a model of the influence mechanism on consumer resistance, and then verifies the mediating effect of perceived creepiness and the moderating effect of anthropomorphized roles of IVAs and perceived CSR of IVAs companies. This research explores underlying mechanism with three experiments.

It turns out that consumers’ privacy concerns are related to their resistance to IVAs through perceived creepiness. The servant (vs. partner) anthropomorphized role of IVAs is likely to induce more privacy concerns and in turn higher resistance. At the same time, when the company’s CSR is perceived high, the impact of the concerns of IVAs’ privacy issues on consumer resistance will be weakened, and the intermediary mechanism of perceiving creepiness in HCI and anthropomorphism of new technology are further explained and verified. The differences between different age and gender are also revealed in the study.

The research conclusions have strategic reference significance for enterprises to build the design framework of IVAs and formulate the response strategy of IVAs’ privacy concerns. And it offers implications for researchers and closes the research gap of IVAs from the perspective of innovation resistance.

The purpose of this article is to investigate the magnetic properties and the hysteresis loops behavior of a ferrimagnetic cubic nanowire with mixed spins S_A = 3/2 and S_B = 2.

We have used the Monte Carlo simulation to examine the influences of the exchange interaction J_B, the crystal field ∆ and the temperature on the magnetic properties and hysteresis loops of the nanowire. More exactly, we have shown the temperature dependence of the sublattice magnetizations (m_A and m_B) and the total magnetization (M) for several values of the Hamiltonian parameters, as well as the corresponding phase diagrams. Finally, the effect of an external magnetic field is studied by plotting the hysteresis loops of the system for different values of exchange interaction, crystal field and temperature.

The obtained results show the existence of second-order phase transitions, as well as the compensation behavior. Moreover, according to the values of the Hamiltonian parameters, the system can exhibit one, two or three hysteresis loops.

The magnetic nanowires are of great interest in experimental works, but without theoretical explanations, the experimental results cannot be clarified in depth. For this, we contribute through this theoretical study to understand the nanowires, especially those with mixed spins (2, 3/2).

Maintenance is a critical business function with a great impact on economic, environmental and social aspects. However, maintenance decisions' planning has been driven by merely economic and technical measures with inadequate consideration of environmental and social dimensions. This paper presents a review of the literature pertaining to sustainable maintenance decision-making models supported by a bibliometric analysis that seeks to establish the evolution of this research over time and identify the main research clusters.

A systematic literature review, supported with a bibliometric and network analysis, of the extant studies is conducted. The relevant literature is categorized based on which sustainability pillar, or possibly multiple ones, is being considered with further classification outlining the application area, modeling approach and the specific peculiarities characterizing each area.

The review revealed that maintenance and sustainability modeling is an emerging area of research that has intensified in the last few years. This fertile area can be developed further in several directions. In particular, there is room for devising models that are implementable, based on reliable and timely data with proven tangible practical results. While the environmental aspect has been considered, there is a clear scarcity of works addressing the social dimension. One of the identified barriers to developing applicable models is the lack of the required, accurate and timely data.

This work contributes to the maintenance and sustainability modeling research area, provides insights not previously addressed and highlights several avenues for future research. To the best of the authors' knowledge, this is the first review that looks at the integration of sustainability issues in maintenance modeling and optimization.

The purpose of this paper is to study the magnetic properties and the hysteresis behavior of a ferrimagnetic cubic Ising nanowire with mixed spins S = 3/2 and S = 5/2 in which the atoms are placed alternately.

In order to investigate the effects of the exchange interactions and crystal field on the magnetic properties and hysteresis behavior of the nanowire, we have used the Monte Carlo simulation. More precisely, we have plotted the thermal variations of the sublattice and total magnetizations for different values of the Hamiltonian parameters, and we have presented the corresponding phase diagrams. In addition, the influence of an external magnetic field is examined by plotting the variations of hysteresis loops with the change of temperature and crystal field.

All phase transition found in this study are of second-order and the critical temperatures increase linearly with the increase of the exchange interactions. The compensation temperatures appear only for some domains of crystal field D and exchange interaction J_B of the sublattice (B). Moreover, when studying the hysteresis behavior, the system can show one or double hysteresis loops.

The authors consider that this research is consistent with the scientific axis of the journal which benefits a great esteem in our country and in the world. In addition, the results are of technological interest.

The authors investigate the magnetic properties of a mixed spin-3/2 and spin-2 Blume-Capel model on square and cubic lattices with two different single-ion anisotropies.

To study the critical behavior of a mixed spin-3/2 and spin-2 system, the authors have used a real space renormalization group approximation and specifically the Migdal-Kadanoff technique. The authors give the phase diagrams for two different cases: (1) on the (Δ/|J|, 1/|J|) plane with Δ_A = Δ_B = Δ, and (2) on the (Δ_A/|J|, 1/|J|) and (Δ_B/|J|, 1/|J|) planes for selected values of Δ_B/|J| and Δ_A/|J|, respectively.

The phase diagrams obtained show that the system exhibits both second- and first-order phase transitions as well as tricritical points for some values of the anisotropies. Moreover, using the variation of the free energy and its derivative at low temperatures, the authors have seen the appearance of first-order transitions at very low temperatures.

Few investigations of mixed spin-3/2 and spin-2 systems with crystal field have been realized. For this reason, the authors use the renormalization group approach to complete the work done on these systems. In absence of an exact solution, this contributes to the synthesis of the approximation results on mixed spins models.

Digital voice assistants use wake word engines (WWEs) to monitor surrounding audio for detection of the voice assistant's name. There are two failed conditions for a WWE, false negative and false positive. Wake word false positives threaten a loss of personal privacy because, upon activation, the digital assistant records audio to the voice cloud service for processing.

This observational study attempted to identify which Amazon Alexa wake word and Amazon Echo smart speaker resulted in the fewest number of human voice false positives. During an eight-week period, false-positive data were collected from four different Amazon Echo smart speakers located in a small apartment with three female roommates.

Results from this study suggest the number of human voice false positives are related to wake word selection and Amazon Echo hardware. Results from this observational study determined that the wake word Alexa resulted in the fewest number of false positives.

This study suggests Amazon Alexa users can better protect their privacy by selecting Alexa as their wake word and selecting smart speakers with the highest number of microphones in the far-field array with 360-degree geometry.

The purpose of the article is to report a study on evaluation of smart manufacturing (SM) performance using a grey theory-based approach.

In total, 30 criteria and 79 attributes for SM performance have been developed. A grey theory-based approach has been used for SM performance evaluation. The grey index has been calculated, and weaker areas have been derived. Performance level of SM has been evaluated using the Euclidean distance approach.

The SM performance index is found to be (3.036, 12.296). The ideal grey performance importance index (GPII) is obtained as (3.025, 4.875). The level of visibility and traceability, vertical integration, lead time and configuration data espionage and control ability are strong performing attributes. Integration abilities of services and manufacturing systems, ability of self-control, worker and raw material productivity, collaboration among buyers and suppliers and dynamic scheduling are identified as weaker areas, and suggestions for improvement have been derived. SM performance level has been identified as “Good.”

Additional performance measures could be included as a part of evaluation. Practitioners can overcome weaker areas in the early phase. Management achieves confidence and practitioners attain success in implementation of SM in industry through the developed SM performance indexing system.

Identification of SM performance measures and analysis of SM performance is the original contribution of the authors. The developed approach assists practitioners and managers to focus more on specific areas for performance improvement.