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In many real-life situations ranging from financial to volcanic data, growth is described either by a power law – which is linear in log-log scale or by a quadratic dependence in the log-log scale. The purpose of this paper is to explain this empirical fact.

The authors use natural scale invariance requirements.

In this paper, the authors used natural scale invariance requirement to explain the ubiquity of quadratic log-log dependencies. The authors also explain what to do if quadratic log-log models turn out to be insufficiently accurate. In this case, scale-invariance requirements lead to dependencies which in the log-log scale take cubic, 4th order, etc. form.

To the best of authors’ knowledge, this is the first theoretical explanation of the empirical quadratic log-log dependence.

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.

In this work, we estimated the different entropies like Shannon entropy, Rényi divergences, Csiszár divergence by using Jensen’s type functionals. The Zipf’s–Mandelbrot law and hybrid Zipf’s–Mandelbrot law are used to estimate the Shannon entropy. The Abel–Gontscharoff Green functions and Fink’s Identity are used to construct new inequalities and generalized them for m-convex function.

The purpose of this study is to account for a recent non-mainstream econometric approach using microdata and how it can inform research in business administration. More specifically, the paper draws from the applied microeconometric literature stances in favor of fitting Poisson regression with robust standard errors rather than the OLS linear regression of a log-transformed dependent variable. In addition, the authors point to the appropriate Stata coding and take into account the possibility of failing to check for the existence of the estimates – convergency issues – as well as being sensitive to numerical problems.

The author details the main issues with the log-linear model, drawing from the applied econometric literature in favor of estimating multiplicative models for non-count data. Then, he provides the Stata commands and illustrates the differences in the coefficient and standard errors between both OLS and Poisson models using the health expenditure dataset from the RAND Health Insurance Experiment (RHIE).

The results indicate that the use of Poisson pseudo maximum likelihood estimators yield better results that the log-linear model, as well as other alternative models, such as Tobit and two-part models.

The originality of this study lies in demonstrating an alternative microeconometric technique to deal with positive skewness of dependent variables.

The positive illiquidity–return relationship (so-called liquidity premium) is a well-established pattern in international developed stock markets. The magnitude of liquidity premium should increase with market illiquidity. Existing studies, however, do not confirm this conjecture with regard to frontier markets. This may result from applying different approaches to the investors' holding period. The paper aims to identify the role of the holding period in shaping the illiquidity–return relationship in emerging and frontier stock markets, which are arguably considered illiquid.

The authors utilise the data on stocks listed on fourteen exchanges in Central and Eastern Europe. The authors regress stock returns on liquidity measures variously transformed to reflect the clientele effect in a liquidity–return relationship.

The authors show that the investors' holding period moderates the illiquidity–return relationship in CEE markets and also show that the liquidity premium in these markets is statistically and economically relevant.

The findings may be of great interest to investors, companies and regulators. Investors and companies should take liquidity into account when making decisions; regulators should employ liquidity-enhancing actions to decrease companies' cost of capital and expand firms' investment opportunities, which will improve growth perspectives for the entire economy.

These findings enrich the understanding of the role that the investors' holding period plays in the illiquidity–return relationship in CEE markets. To the best knowledge, this is the first study which investigates the effect of holding period on liquidity premium in emerging and frontier markets.

In this study, the authors introduce a solvability of special type of Langevin differential equations (LDEs) in virtue of geometric function theory. The analytic solutions of the LDEs are considered by utilizing the Caratheodory functions joining the subordination concept. A class of Caratheodory functions involving special functions gives the upper bound solution.

The methodology is based on the geometric function theory.

The authors present a new analytic function for a class of complex LDEs.

The authors introduced a new class of complex differential equation, presented a new technique to indicate the analytic solution and used some special functions.

For aiding computer security experts in their study, log files are a crucial piece of information. Especially the time domain is very important for us because in most cases, timestamps are the only linking points between events caused by attackers, faulty systems or simple errors and their corresponding entries in log files. With the idea of storing and analyzing this log information in graph databases, we need a suitable model to store and connect timestamps and their events. This paper aims to find and evaluate different approaches how to store timestamps in graph databases and their individual benefits and drawbacks.

We analyse three different approaches, how timestamp information can be represented and stored in graph databases. For checking the models, we set up four typical questions that are important for log file analysis and tested them for each of the models. During the evaluation, we used the performance and other properties as metrics, how suitable each of the models is for representing the log files’ timestamp information. In the last part, we try to improve one promising looking model.

We come to the conclusion, that the simplest model with the least graph database-specific concepts in use is also the one yielding the simplest and fastest queries.

Limitations to this research are that only one graph database was studied and also improvements to the query engine might change future results.

In the study, we addressed the issue of storing timestamps in graph databases in a meaningful, practical and efficient way. The results can be used as a pattern for similar scenarios and applications.

This Scholarship of Teaching and Learning research is a part of the larger study grant to analyze written reflections through learning log among the third and final year students undertaking BPME 3073 Entrepreneurship module in University Utara Malaysia (UUM). The paper aims to discuss these issues.

The data collection techniques are researcher-directed textual data through reflective learning log, taken from 140 students from three classes. A thematic approach was utilized to present the reflections of the students and all data were recorded in a verbatim format.

The findings show that most students have never written a reflective log or essay in the formative assessment. As a consequence, they had difficulty in writing the reflection when being requested to do so. A total 75 (approximately 55 percent) of the reflective logs were identified as level 1 (from 1 to 5 percent) in which reflections were simply written in a descriptive manner, resulted in a balance of 61 learning logs being utilized for further analysis. The students’ reflections on their entrepreneurship’s experience systematically categorize into four different themes comprised of: the nature of entrepreneurship module, entrepreneurial characteristics, opportunity recognition, and creativity and innovation.

As for the limitation of the study, it is important to not to underestimate the challenges of introducing a grade assessment that most of them are not familiar with in their university academic journey. Students need guidance, assurance and confidence writing something that require personal opinion, own thinking, sensitive and personal nature of narration. For most students as found out in this study, self-confessional writing is hard to come by (they dare not attempt it in the first place), only a handful appreciating the writing start with “I,” “me” as first person. More research in this study should be conducted across the university to gauge the response from the students to see if the result of this study is only applicable to this group of students or to this discipline of studies. The researchers would also like to recommend for future studies which take the form of a longitudinal study of similar kind to examine the problems and challenges with regards to promoting learning reflection at the undergraduate level.

Based on the result of the 61 students who had demonstrated an ability in reflective writing, it is suggested that perhaps the university should consider offering coursework that contains a component of reflective writing as part of the assessment. As such, if this is implemented, students of such ability like the one in this sample group would have been benefitted from such assessment which look at reflective ability (Greene, 2014) and which they were allowed to form a broader perspective in relation to the module undertaken. This in turns will foster the growth of reflective ability which is recognized as a learned behavior (Gustafson and Bennett, 1999). In addition, for the future exercise of this reflective learning log, the researcher opined that we should encourage our students to engage with another student (e.g. close friend) in a way that encourages talking with, questioning, or confronting, helped the reflective process by placing the learner in a safe environment in which self-revelation can take place. In addition, students were able to distance themselves from their actions, ideas and beliefs, by holding them up for scrutiny in the company of a peer with whom they are willing to take such risks (Hatton and Smith, 1995).

The results of this research have strongly suggested the need to urgently develop among the students the skills in writing reflectively as they go through the process of higher education which is useful in molding their future professional and entrepreneurial behavior as when they entered the job market which requires a critical reasoning ability.

Fresh vegetables contain advantageous phytochemical components, making them one of the most significant sources of nutrition. The threat of harmful bacteria still exists because these vegetables are not heated in restaurants before being consumed. Therefore, this study aimed to evaluate the microbial quality of fresh vegetables in restaurants of different levels.

A total of 499 fresh vegetable samples (from sandwiches and fresh-cut vegetable salads) were collected from 3 different types of food service establishment: 201 from international restaurants (IRs), 210 from national restaurants (NRs), and 88 from cafeterias (CAs). The samples were prepared and inoculated on specific growth media. The aerobic mesophilic bacteria (AMB) Campylobacter spp., Staphylococcus aureus (S. aureus), Enterobacteriaceae, Escherichia coli (E. coli) and yeast and molds were counted, and Listeria monocytogenes, Salmonella spp. and Escherichia coli O157 were detected using specialized medium.

High counts of S. aureus, above 3 log cfu/g, suggested that 71.5% of samples collected from NRs and 77.3% from CA were not accepted, whereas 81.6% of samples collected from IRs were accepted. The low population of E. coli, less than 2 log cfu/g, suggested that 99.0, 97 and 92.0 % of samples collected from IRs, NRs and CA, respectively, were accepted. Listeria monocytogenes and Escherichia coli O157 were absent from every sample. One sample was positive for Salmonella spp. in each of the NR and CA sample groups.

RIs adhere to health and hygiene standards better than NRs and CAs, according to the findings of vegetable contamination tests.

This paper aims to test three parametric models in pricing and hedging higher-order moment swaps. Using vanilla option prices from the volatility surface of the Euro Stoxx 50 Index, the paper shows that the pricing accuracy of these models is very satisfactory under four different pricing error functions. The result is that taking a position in a third moment swap considerably improves the performance of the standard hedge of a variance swap based on a static position in the log-contract and a dynamic trading strategy. The position in the third moment swap is taken by running a Monte Carlo simulation.

This paper undertook empirical tests of three parametric models. The aim of the paper is twofold: assess the pricing accuracy of these models and show how the classical hedge of the variance swap in terms of a position in a log-contract and a dynamic trading strategy can be significantly enhanced by using third-order moment swaps. The pricing accuracy was measured under four different pricing error functions. A Monte Carlo simulation was run to take a position in the third moment swap.

The results of the paper are twofold: the pricing accuracy of the Heston (1993) model and that of two Levy models with stochastic time and stochastic volatility are satisfactory; taking a position in third-order moment swaps can significantly improve the performance of the standard hedge of a variance swap.

The limitation is that these empirical tests are conducted on existing three parametric models. Maybe more critical insights could have been revealed had these tests been conducted in a brand new derivatives pricing model.

This work is 100 per cent original, and it undertook empirical tests of the pricing and hedging accuracy of existing three parametric models.