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Analysis of log message is very important for the identification of a suspicious system and network activity. This analysis requires the correct extraction of variable entities. The variable entities are extracted by comparing the logs messages against the log patterns. Each of these log patterns can be represented in the form of a log signature. In this paper, we present a hybrid approach for log signature extraction. The approach consists of two modules. The first module identifies log patterns by generating log clusters. The second module uses Named Entity Recognition (NER) to extract signatures by using the extracted log clusters. Experiments were performed on event logs from Windows Operating System, Exchange and Unix and validation of the result was done by comparing the signatures and the variable entities against the standard log documentation. The outcome of the experiments was that extracted signatures were ready to be used with a high degree of accuracy.

The purpose of the study was to test the usability of the MyLA app prototype by its potential users. Furthermore, the Web app will be introduced in the framework of “Mobile Learning Analytics”, a cooperation project between the Cooperative State University Mannheim and University of Mannheim. The participating universities focus on the support of personalized and self-regulated learning. MyLA collects data such as learning behavior, as well as personality traits. Last but not least, the paper will contribute to the topic of learning analytics and mobile learning in higher education.

For the empirical investigation, a mixed-method design was chosen. While 105 participants took part in the conducted online survey, after testing the app prototype, seven students joined an additional eye tracking study. For the quantitative part, a selected question pool from HIMATT (highly integrated model assessment technology and tools) instrument was chosen. The eye tracking investigation consisted of three tasks the participants had to solve.

The findings showed that the students assessed the idea of the app, as well as the navigation positively. Only the color scheme of the prototype was not very attractive to a noticeable amount of the participants. So, it requires slight modifications concerning the app design. For the eye tracking study, it can be stated that the students viewed the relevant parts, and they basically had no difficulties to solve the tasks.

Due to the empirical testing of the app prototype, the project team was able to adjust the application and to add further features. Furthermore, the backend was programmed and an additional tool (MyLA dashboard) was developed for lecturers. A mutual understanding of the targets, privacy issue and relevant features are indispensable for further development of the project.

Social media empower individuals to voice their opinions about issues that they perceive to be unacceptable. When many others add their opinions and large quantities of messages containing negative word-of-mouth suddenly spread online, an online firestorm occurs. By extending the situational theory of problem solving (Kim and Grunig, 2011) into the domain of online communication, this study aims to identify the drivers for participating in online firestorms.

With reference to a fictitious online firestorm trigger (i.e. perceived moral misconduct) posted on Facebook, a qualitative pre-study and quantitative online survey were conducted. Based on the responses of 410 participants, an ordinary least squares regression was modeled to examine the factors of participating in the online firestorm. Later, structural equation modeling was applied to test the model and gauge its fit with the data.

Participants' involvement recognition, perception of being collective actors and approval of slacktivism behaviors positively predicted their participation in the online firestorm, whereas non-anonymity hampered it.

The study's findings not only contribute to the current understandings of online firestorms but are also valuable for developing theory and forms of professional crisis management. Moreover, they offer insights into the factors of online communication environments that encourage users to voice their opinions.

This study aims to explore how businesswomen running micro and small enterprises (MSEs) use social media (SM) to engage customers. The study also investigates how SM (vs traditional media) and customer engagement improve business performance.

This qualitative study is based on interviews with businesswomen.

Businesswomen use SM actively but not effectively. SM are used primarily for advertising and promotion. External factors, such as family and friends, are more influential in the decision of women to use SM in business. Women mostly use defensive rather than offensive strategies. Effective use of SM in conjunction with conventional marketing tools can improve customer engagement and increase business performance.

The research findings are valuable for marketing managers, women entrepreneurs and micro and small businesses in making decisions to effectively use SM.

This study investigates customer engagement from the owner/manager’s perspective in contrast to the general customer-centric approach. The study contributes analysing an important and scarcely explored area, which is the use of SM by women-run MSEs in less developed countries to engage consumers.

Este estudio explora cómo las mujeres de negocios que dirigen micro y pequeñas empresas (MSE) utilizan las redes sociales para atraer a los clientes. El estudio también investiga cómo las redes sociales (frente a los medios tradicionales) y la involucración de los clientes mejoran el rendimiento empresarial.

Este estudio cualitativo se basa en entrevistas con mujeres empresarias.

Las mujeres empresarias utilizan las redes sociales de forma activa, pero no eficaz. Las redes sociales se utilizan principalmente para la publicidad y la promoción. Los factores externos, como la familia y los amigos, influyen más en la decisión de las mujeres de utilizar las redes sociales en los negocios. Las empresarias utilizan sobre todo estrategias defensivas en lugar de ofensivas. El uso eficaz de las redes sociales junto con las herramientas de marketing convencionales puede mejorar el compromiso de los clientes y aumentar el rendimiento de la empresa.

Los resultados de la investigación son valiosos para las directivas de marketing, las mujeres empresarias y las micro y pequeñas empresas a la hora de tomar decisiones y para utilizar eficazmente las redes sociales.

Este estudio investiga el compromiso del cliente desde la perspectiva del propietario/gerente en contraste con el enfoque general centrado en el cliente. El estudio contribuye a analizar un área importante y escasamente explorada, que es el uso de las redes sociales por parte de las microempresas dirigidas por mujeres en los países menos desarrollados para involucrar a los consumidores.

本研究探讨了经营微型和小型企业（MSEs）的女商人如何使用社交媒体来吸引客户。该研究还调查了社交媒体（相对于传统媒体）和客户参与如何提高企业绩效。

这项定性研究是基于对女商人的采访。

女商人积极使用社交媒体, 但并非有效。社交媒体主要用于广告和推广。外部因素, 如家庭和朋友, 对妇女在商业中使用社交媒体的决定更有影响力。女性大多使用防御性而非进攻性策略。将社交媒体与传统的营销工具有效地结合起来使用, 可以提高客户的参与度, 增加企业的业绩。

研究结果对营销经理、女企业家和小微企业做出有效使用社交媒体的决定很有价值。

本研究从业主/经理的角度调查了客户参与度, 与一般的以客户为中心的方法不同。该研究有助于分析一个重要的、很少被探索的领域, 即欠发达国家的妇女经营的微型企业使用社交媒体来吸引消费者。

Internet of Things’ (IoT’s) first wave started with tracking services for better inventory management mainly using radio frequency identification (RFID) technology. Later on, monitoring services became one of the major interests, including sensing technologies, and then more actuation for remote control-type of IoT applications such as smart homes, smart cities and Industry 4.0. In this paper, the authors focus on the RFID technology impairment. They propose to take advantage of the mature IoT technologies that offer native service discovery such as blutooth or LTE D2D ProSe or Wifi Direct. Using the automatic service discovery in the new framework will make heterogeneous readers aware of the presence of other readers and this will be used by the proposed distributed algorithm to better control the multiple RFID reader interference problem. The author clearly considers emerging Industry 4.0 use case, where RFID technology is of major interest for both identification and tracking. To enhance the RFID tag reading performance, collisions in the RFID frequency should be minimized with reader-to-reader coordination protocols. In this paper, the author proposes a simple distributed reader anti-collision protocol named DiSim that makes use of proximity services of IoT network and is compliant with the current RFID standards. The author evaluates the efficiency of the proposal via simulation.

In this paper, the author proposes a simple distributed reader anti-collision protocol named DiSim that makes use of proximity services of IoT network and is compliant with the current RFID standards. The author evaluates the efficiency of the proposal via simulation to study its behavior in very dense and heterogeneous RFID environments. Specifically, the author explores the coexistence of powerful static readers and small mobile readers, comparing the proposal with a standard ETSI CSMA method. The proposal reduces significantly the number of access attempts, which are resource-expensive for the readers. The results show that the objectives of DiSim are met, producing low reader collision probability and, however, having lower average readings per reader per time.

DiSim is evaluated with the ETSI standard LBT protocol for multi-reader environments in several environments with varied levels of reader and tag densities, having both static powerful RFID readers and heterogeneous randomly moving mobile RFID readers. It effectively reduces the number of backoffs or contentions for the RFID channel. This has high reading success rate due to the avoided collisions; however, the readers are put to wait, and DiSim has less average readings per reader per time. As an additional side evaluation, the ETSI standard LBT mechanism was found to present a good performance for low-density mid-coverage scenarios, however, with high variability on the evaluation results.

To show more results, the author needs to do real experimentation in a warehouse, such as Amazon warehouse, where he expects to have more and more robots, start shelves, automatic item finding on the shelve, etc.

Future work considers experimentation in a real warehouse equipped with heterogeneous RFID readers and real-time analysis of RFID reading efficiency also combined with indoor localization and navigation for warehouse mobile robots.

More automatization is expected in the future; this work makes the use of RFID technology more efficient and opens more possibilities for services deployment in different domains such as the industry which was considered not only in this paper but also in smart cites and smart homes.

Compared to the literature, the proposal offers the advantage to not be dependent on a centralized server controlling the RFID readers. It also offers the possibility for an existing RFID architecture to add new readers from a different manufacturer, as the readers using the approach will have the possibility to discover the capabilities of the new interaction other RFID readers. This solution takes advantage of the available proximity service that will be more and more offered by the IoT technologies.

This study assessed two technology systems aimed at enabling a man with intellectual disability, blindness, deafness and motor and tactile discrimination problems to make verbal requests through simple one-hand signs.

The study was conducted according to an ABAB design. During the B (intervention) phases, the man used the two systems, which included (1) nine mini recording devices fixed on the man’s clothes or wheelchair (i.e. in positions the man touched with his sign movements) and (2) nine tags with radio frequency identification codes (fixed at approximately the same positions as the mini recording devices) and a dedicated tag reader, respectively. Making a sign (i.e. touching a recording device or reaching a tag) led to the verbalization of the request related to that sign.

During baseline, the mean frequency of signs/requests made was below 2 per session, and only some of those requests were identified/satisfied. During the intervention, the mean frequency of requests made and satisfied was about 10 per session with each of the systems.

The results, which are to be taken with caution given the preliminary nature of the study, seem to suggest that the systems can help translate simple signs into verbal requests.

For companies that intend to respond to the modern conscious consumers' needs, a great competitive advantage is played on the ability to incorporate sustainability messages in marketing communications. The aim of this paper is to address this important priority in the web context, building a semantic algorithm that allows content managers to evaluate the quality of sustainability web contents for search engines, considering the current semantic web development.

Following the Design Science (DS) methodological approach, the study develops the algorithm as an artefact capable of solving a practical problem and improving the operation of content managerial process.

The algorithm considers multiple factors of evaluation, grouped in three parameters: completeness, clarity and consistency. An applicability test of the algorithm was conducted on a sample of web pages of the Google blog on sustainability to highlight the correspondence between the established evaluation factors and those actually used by Google.

Studying content marketing for sustainability communication constitutes a new field of research that offers exciting opportunities. Writing sustainability contents in an effective way is a fundamental step to trigger stakeholder engagement mechanisms online. It could be a positive social engineering technique in the hands of marketers to make web users able to pursue sustainable development in their choices.

This is the first study that creates a theoretical connection between digital content marketing and sustainability communication focussing, especially, on the aspects of search engine optimization (SEO). The algorithm of “Sustainability-contents SEO” is the first operational software tool, with a regulatory nature, that is able to analyse the web contents, detecting the terms of the sustainability language and measuring the compliance to SEO requirements.

This paper aims to explore the recognition and success of different ways of branding native advertising in influencer marketing.

The data are evaluated using statistical tests, correlation and cluster analysis.

It was found that the higher the recognition rate of a post tagged in a particular way, the better the tagging method for influencer marketing on Instagram. Based on the findings of this study, word tag is recommended first because it is flexible and has one of the highest recognition rates.

The generalizability of the results across different regional settings requires further investigation.

Good labeling of native advertising leads to greater success.

This study can be used by marketing managers, advertisers and influencers to gain insight into the issue, as well as to better select the appropriate labeling method for their advertising content.

Este trabajo tiene como objetivo explorar el reconocimiento y el éxito de diferentes formas de branding de publicidad nativa en el marketing de influencers.

Los datos se evalúan mediante pruebas estadísticas, correlación y análisis de conglomerados.

Se encontró que cuanto mayor es la tasa de reconocimiento de un post etiquetado de una manera particular, mejor es el método de etiquetado para el marketing de influencers en Instagram. Basándose en los resultados de este estudio, se recomienda en primer lugar el etiquetado por palabras porque es flexible y tiene una de las tasas de reconocimiento más altas.

Un buen etiquetado de la publicidad nativa conduce a un mayor éxito.

Este estudio puede ser utilizado por directores de marketing, anunciantes e influencers para obtener información sobre el tema, así como para seleccionar mejor el método de etiquetado adecuado para su contenido publicitario.

La generalizabilidad de los resultados en diferentes entornos regionales requiere más investigación.

本文旨在探讨影响者营销中不同方式的品牌原生广告的识别和成功。

使用统计测试、相关性和聚类分析对数据进行评估。

研究发现, 以特定方式标记的帖子的识别率越高, Instagram上影响者营销的标记方式就越好。基于这项研究的结果, 首先推荐单词标签, 因为它很灵活, 而且有最高的识别率之一。

对原生广告进行良好的标注会带来更大的成功。

本研究可供营销经理、广告商和影响者使用, 以深入了解这一问题, 并更好地为其广告内容选择合适的标签方法。

研究结果在不同地区环境中的普适性需要进一步调查。

This study aims to analyze communication from the perspective of social marketing, positive emotions, and the topics chosen by Spanish tourist destinations to show their destination image. Additionally, this research shows a message classification model, based on the aforementioned characteristics, that has generated a greater impact, offering clarity to tourism managers on the type of content they should publish to achieve greater visibility.

The methodology used in this work combines content analysis and data mining techniques. The classification tree using the chi-square automatic interaction detector (CHAID) algorithm was selected to determine predictors of like behaviour.

The results show that the predictor variables have been emotions, social marketing and topics. Also, the characteristics of the messages most likely to have a high impact are those related to emotions of joy or happiness, their purpose is behavioural, and they talk about rural, cultural issues, special dates, getaways, or highlights of a town or city for something specific.

This study is the first to analyze the content of the tweets shared by destination tourism managers from a social marketing, positive emotions, and sustainability perspective, determining the possible predictors of likes on Twitter. The authors contribute to the literature by deepening the understanding of how social marketing and the positive emotions promoted drive a more significant impact in tourism communication campaigns on social media. The authors provide destination managers with a way better to understand the variables relevant to users in tourism content.

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.