Jian Li, Xinlei Yan, Feifei Zhao and Xin Zhao
The purpose of this paper is to solve the problem that the location of the initiation point cannot be measured accurately in the shallow underground space, this paper proposes a…
Abstract
Purpose
The purpose of this paper is to solve the problem that the location of the initiation point cannot be measured accurately in the shallow underground space, this paper proposes a method, which is based on fusion of multidimensional vibration sensor information, to locate single shallow underground sources.
Design/methodology/approach
First, in this paper, using the characteristics of low multipath interference and good P-wave polarization in the near field, the adaptive covariance matrix algorithm is used to extract the polarization angle information of the P-wave and the short term averaging/long term averaging algorithm is used to extract the first break travel time information. Second, a hybrid positioning model based on travel time and polarization angle is constructed. Third, the positioning model is taken as the particle update fitness function of quantum-behaved particle swarm optimization and calculation is performed in the hybrid positioning model. Finally, the experiment verification is carried out in the field.
Findings
The experimental results show that, with root mean square error, spherical error probable and fitness value as evaluation indicators, the positioning performance of this method is better than that without speed prediction. And the positioning accuracy of this method has been improved by nearly 30%, giving all of the three tests a positioning error within 0.5 m and a fitness less than 1.
Originality/value
This method provides a new idea for high-precision positioning of shallow underground single source. It has a certain engineering application value in the fields of directional demolition of engineering blasting, water inrush and burst mud prediction, fuze position measurement, underground initiation point positioning of ammunition, mine blasting monitoring and so on.
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Emily P. Jones, Nandita S. Mani, Rebecca B. Carlson, Carolyn G. Welker, Michelle Cawley and Fei Yu
The objective of this study is to establish the current state of library and information science (LIS) scholarship pertaining to anti-racism, equity, inclusion and social justice…
Abstract
Purpose
The objective of this study is to establish the current state of library and information science (LIS) scholarship pertaining to anti-racism, equity, inclusion and social justice initiatives.
Design/methodology/approach
Using comprehensive search strategies, three LIS databases were searched for relevant literature published in the last 10 years and results were exported and de-duplicated using Endnote. Citations were screened by two blinded, independent reviewers based on pre-defined eligibility criteria. Citations in the final data set were then hand coded by three reviewers using deductive coding. Subject terms for all citations were categorized and consolidated to identify major themes across the corpus of included publications. Results were analyzed using bibliometrics and thematic analysis.
Findings
A total of 691 unique citations were included in this analysis based on inclusion criteria. Publication productivity has generally increased from 2011 to 2020; findings show publications from 170 source titles and 944 authors representing 33 countries. Prevalent themes included access to information, multiculturalism and social justice. Various populations groups, areas of LIS practice, library types and social justice topics have been addressed in the literature. Over 15% of citations focused on anti-racism efforts in LIS.
Originality/value
This study applied both bibliometric and thematic approaches to analyzing LIS literature at macro and micro levels regarding anti-racism, equity, inclusion and social justice.
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Hamza Kaka Abdul Wahab, Faizan Alam and Eva Lahuerta-Otero
In today’s global and competitive e-commerce market spaces, social media influencers (SMIs) exert substantial influence on consumer behavior. This study aims to examine how…
Abstract
Purpose
In today’s global and competitive e-commerce market spaces, social media influencers (SMIs) exert substantial influence on consumer behavior. This study aims to examine how electronic word of mouth (e-WOM), Instagram usage and the credibility of SMIs shape the dynamics of consumer purchase behavior (PB).
Design/methodology/approach
Information was gathered from 498 users in Ghana through judgmental sampling using SmartPLS 4.
Findings
The findings revealed that influencers’ credibility has a substantial impact on their followers’ parasocial interactions. As a promotional tool, Instagram plays a significant role in how followers perceive the credibility of influencers by modifying the associations between parasocial connections, e-WOM and consumer PB.
Research limitations/implications
The findings offer valuable information for marketing professionals looking to improve their advertising efforts by collaborating with influencers, along with unique perspectives on influencer dynamics in a diverse socioeconomic context, extending beyond conventional boundaries.
Originality/value
Through an examination of the complex mechanisms underlying social media influencer advertisements on an e-commerce platform, namely, Instagram, this research uncovered the essence of customer behavior in the digital era, including the human need for connection, authenticity and trust, thus contributing to the literature empirical data from Africa, a region often overlooked in academic studies.
目的
在当今全球化且竞争激烈的电子商务市场中, 社交媒体影响者对消费者行为有着重要的影响。本研究旨在探讨网络口碑、Instagram使用以及社交媒体影响者的可信度如何塑造消费者购买行为的动态变化。
方法
使用SmartPLS 4, 通过判断抽样收集了来自加纳的 498 位用户信息。
发现
研究表明, 影响者的可信度对其粉丝的准社会互动有着显著影响。作为一种推广工具, Instagram通过影响准社会联系、网络口碑和消费者购买行为之间的关系, 在粉丝感知影响者可信度方面发挥着重要作用。
原创性
本研究通过深入剖析社交媒体影响者在Instagram等电子商务平台上进行广告活动的复杂机制, 揭示了数字时代消费者行为的本质, 其中包括人们对联系、真实性和信任的需求。此外, 研究还提供了经常被学术界忽视的非洲地区的实证数据。
研究局限性和启示
研究结果为希望通过与影响者合作来提升广告效果的营销专业人士提供了宝贵的信息。本文超越传统界限, 从不同的社会经济背景下提供了影响者动态的独特视角。
Objetivo
En un mercado tan global y competitivo como el del comercio electrónico actual, los influencers en redes sociales ejercen una influencia sustancial en el comportamiento del consumidor. Este estudio examina cómo el boca a boca electrónico, el uso de Instagram y la credibilidad de los influencers en redes sociales dan forma a la dinámica del comportamiento de compra del consumidor.
Diseño/Metodología/Enfoque
Se recogió información de 498 usuarios en Ghana mediante muestreo de conveniencia y se testó el modelo utilizando SmartPLS 4.
Resultados
Los resultados revelaron que la credibilidad de los influencers tiene un impacto sustancial en las interacciones parasociales con sus seguidores. Como herramienta promocional, Instagram juega un papel significativo en la percepción de los seguidores sobre la credibilidad de los influencers, modificando las asociaciones entre las conexiones parasociales, el boca a boca electrónico y, finalmente, el comportamiento de compra del consumidor.
Originalidad
A través del estudio de los complejos mecanismos que subjacen en los anuncios y publicaciones de los influencers en Instagram, esta investigación desveló la esencia del comportamiento del cliente en la era digital, incluyendo la necesidad de conexión humana la conexión, la autenticidad y la confianza, contribuyendo así a la literatura con datos empíricos de África, una región a menudo pasada por alto en estudios académicos.
Limitaciones e implicaciones de la investigación
Los resultados ofrecen información valiosa para los profesionales del marketing que buscan mejorar sus esfuerzos publicitarios colaborando con influencers, junto con perspectivas únicas sobre la dinámica de éstos en un contexto socioeconómico diverso, más allá de los límites convencionales.
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Warot Moungsouy, Thanawat Tawanbunjerd, Nutcha Liamsomboon and Worapan Kusakunniran
This paper proposes a solution for recognizing human faces under mask-wearing. The lower part of human face is occluded and could not be used in the learning process of face…
Abstract
Purpose
This paper proposes a solution for recognizing human faces under mask-wearing. The lower part of human face is occluded and could not be used in the learning process of face recognition. So, the proposed solution is developed to recognize human faces on any available facial components which could be varied depending on wearing or not wearing a mask.
Design/methodology/approach
The proposed solution is developed based on the FaceNet framework, aiming to modify the existing facial recognition model to improve the performance of both scenarios of mask-wearing and without mask-wearing. Then, simulated masked-face images are computed on top of the original face images, to be used in the learning process of face recognition. In addition, feature heatmaps are also drawn out to visualize majority of parts of facial images that are significant in recognizing faces under mask-wearing.
Findings
The proposed method is validated using several scenarios of experiments. The result shows an outstanding accuracy of 99.2% on a scenario of mask-wearing faces. The feature heatmaps also show that non-occluded components including eyes and nose become more significant for recognizing human faces, when compared with the lower part of human faces which could be occluded under masks.
Originality/value
The convolutional neural network based solution is tuned up for recognizing human faces under a scenario of mask-wearing. The simulated masks on original face images are augmented for training the face recognition model. The heatmaps are then computed to prove that features generated from the top half of face images are correctly chosen for the face recognition.