Microbiological Antibiotic Assay Validation of Gentamicin Sulfate Using Two-Dose Parallel Line Model (PLM)

Till nowadays microbiological assay is still widely used with several antibiotics that are composed of a mixture of related active compounds. However, obtaining a reasonably valid determination of the potency is dependent on the validity and the suitability of the assay design. The present work aimed to validate an assay design of an aminoglycoside antibiotic (Gentamicin Sulfate) using a two-dose Parallel Line Model agar diffusion assay in a large 8×8 rectangular plate. All preparatory procedures were done following United States Pharmacopeia and the Inhibition Zones were measured using a digital caliper to the nearest 0.01 mm. Analysis of variance of compendial requirements of regression and parallelism were found to be satisfactorily meeting the acceptance criteria. Specificity was achieved for the product under investigation with no detectable IZ that could be found for all components except the antibiotic. The validation method showed acceptable linearity of r2≥0.98. Accuracy and precision parameters showed RSD (%)<2. All relative error value estimates were below 4%. The proposed validation design for 32×32 cm antibiotic plates yielded valid results and can be projected for the routine Quality Control analysis of the antibiotic material, especially which is incorporated into a finished medicinal dosage form. Doi: 10.28991/HIJ-2021-02-04-04 Full Text: PDF

The Effect of Gurney Flap and Trailing-edge Wedge on the Aerodynamic Behavior of an Axial Turbine Blade

In this research, the effect of Gurney flap and trailing-edge wedge on the aerodynamic behavior of blunt trailing-edge airfoil Du97-W-300 which is equipped with vortex generator is studied. To do this, the role of Gurney flap and trailing-edge wedge on the lift and drag coefficient and also aerodynamic performance of the airfoil is studied. Validation of the numerical model is performed by comparison of the obtained results with those of experiment. Results show that before stall, Gurney flap leads to the increase in the aerodynamic performance in a wider range of angle of attack. Numerical findings reveal that the maximum increment for the aerodynamic performance is obtained at low angle of attack when trailing-edge wedge is employed. It is found that for the highest considered value of Gurney flap and trailing-edge wedge heights, where the highest values for the lift occur, the higher aerodynamic performance at low angle of attack is obtained when trailing-edge wedge is used and at high angle of attack, the Gurney flap results in a higher aerodynamic performance. It is also shown that when high aerodynamic performance is concerned, addition of Gurney flap to the airfoil leads to the higher value for the lift. Doi: 10.28991/HIJ-2021-02-04-03 Full Text: PDF

Towards the Internet of Behaviors in Smart Cities through a Fog-To-Cloud Approach

Recent advances in Internet of Things (IoT) and the rising of the Internet of Behavior (IoB) have made it possible to develop real-time improved traveler assistance tools for mobile phones, assisted by cloud-based machine learning, and using fog computing in between IoT and the Cloud. Within the Horizon2020-funded mF2C project an Android app has been developed exploiting the proximity marketing concept and covers the essential path through the airport onto the flight, from the least busy security queue through to the time to walk to gate, gate changes, and other obstacles that airports tend to entertain travelers with. It gives chance to travelers to discover the facilities of the airport, aided by a recommender system using machine learning, that can make recommendations and offer voucher according with the traveler’s preferences or on similarities to other travelers. The system provides obvious benefits to the airport planners, not only people tracking in the shops area, but also aggregated and anonymized view, like heat maps that can highlight bottlenecks in the infrastructure, or suggest situations that require intervention, such as emergencies. With the emerging of the COVID pandemic the tool could be adapted to help in the social distancing to guarantee safety. The use of the fog-to-cloud platform and the fulfilling of all centricity and privacy requirements of the IoB give evidence of the impact of the solution. Doi: 10.28991/HIJ-2021-02-04-01 Full Text: PDF

Digital Transformation: Smart Strategy in Administrative Reform in Vietnam

Objectives: Digital transformation is becoming such a big trend that countries worldwide cannot resist because it brings prosperity and development to social progress. Therefore, countries, especially emerging countries, need to quickly bring the latest technology advances into socio-economic development. Therefore, the purpose of the article is to point out the theoretical issues of digital transformation, the advantages and challenges, and their impact on Vietnam's provincial administrative reform and forecast the trend of impacts of the digital transformation to administrative reform at the provincial level. Methods/Analysis: Qualitative and quantitative research methods have been used together, in which quantitative methods used available literature sources. The qualitative method has been developed based on designing two questionnaires on digital transformation and administrative reform, thereby exploring the current results of digital transformation and administrative reform in a cross-section. Findings: Research has shown that the reality of digital transformation and administrative reform in provincial administrative agencies in Vietnam is still limited. Although administrative reform is superior to digital transformation, they are closely positive related. Novelty /Improvement: Research shows that administrative reform at the provincial level in Vietnam will become more competent and more efficient when administrative agencies promote the application of digital transformation; both digital transformation and administration reform need to be concerned at the same time. Moreover, a more focus on developing digital capacity and skills for civil servants is necessary for digital transformation and administrative reform to achieve high efficiency. Doi: 10.28991/HIJ-2021-02-04-06 Full Text: PDF

Engine Downsizing; Global Approach to Reduce Emissions: A World-Wide Review

Engine downsizing is a promising method to reduce emissions and fuel consumption of internal combustion engines. The main concept is reducing engine displacement volume keeping needed output characteristics unchanged. The issue became one of the most filed of interest in recent years after the International Energy Agency defined a target of 50 % reduction in global average emissions by the year 2030. In this review paper, different aspects of researchers’ efforts on engine downsizing are configured and due to overlaps, categorized into five main areas. Each category is discussed thoroughly and recent works are pointed. The global attention into these categories, countries involved and the trend changed in recent four years are presented in details. Doi: 10.28991/HIJ-2021-02-04-010 Full Text: PDF

The Global Equity Market Reactions of the Oil & Gas Midstream and Marine Shipping Industries to COVID-19: An Entropy Analysis

This article quantifies the information flow between major equities in the Oil & Gas Midstream and Marine Shipping industries, on the basis of the effective transfer entropy methodology. In addition, the article provides the first analysis of the investors` fear and market expectations in these sectors, according to Rényi entropy approach. The period of study was extended over five years, to fully capture the pre/post-COVID situations. The entropy results reveal a major change in the underlying information flow pattern among equities in the Oil & Gas Midstream and Marine Shipping sectors, in the aftermath of COVID-19. According to the new (post-COVID) paradigm, the stocks in the Oil & Gas Midstream and Integrated Freight & Logistics industries have gained momentum in occupying six of the ten positions within the list of most-influencing equities in the market, in terms of information transmission. The disorder and randomness has decreased for over 89% of the studied equities, after virus outbreak. For the equities detected with high information-transmission standing, the Rényi entropy results indicate that investors more likely showed higher level of future expectations and lower level of fear regarding frequent market events, within the post-COVID timeline. Doi: 10.28991/HIJ-2021-02-04-07 Full Text: PDF

Towards a Sentiment Analysis of Tweets from Online Newspapers Regarding the Coronavirus Pandemic

In the last year, both offline and online news have had the Coronavirus pandemic as their subject, especially social networking Twitter has significantly increased the news regarding Covid-19. The objectives of the project are: the analysis of news regarding the Coronavirus pandemic extracted from the Twitter profile of ANSA, a well-known Italian news agency and the analysis of sentiment and the number of likes for each news extracted The sentiment analysis has been carried out using the MAL lexicon (Morphologically Affective Lexicon), where the tweet is split into words and each paola is associated with a score. Positive (with a score greater than zero), negative (with a score less than zero) and neutral (with a score equal to zero) news were identified. As a result, it emerges that the sentiment changed day by day, so it is necessary to use sentiment indicators called indices, but only the positive sentiment index is taken into consideration as the negative one is complementary and the neutral one is almost zero. The positive index is then related to some parameters extrapolated from the Civil Protection site: number of cases, number of deaths and entry into intensive care. Furthermore, in addition to the parameters listed above, the positivity index is related to the days in which the decrees of the Prime Minister (DPCM) were signed. The last relationship analyzed is that between the average number of likes and the number of deaths. The results of the research shows that the sentiment of the news of the Ansa Agency contains 62.3% of positive news, 37.3% of negative news and only 0.3% of neutral news. Furthermore, sentiment is not influenced by the daily parameters: number of cases, number of deaths, entry into intensive care units and DPCMs. But there is a relationship between the average of like and the number of deaths. Doi: 10.28991/HIJ-2021-02-04-08 Full Text: PDF

Statistical Similarity of Mortality and Recovery Ratios for Covid-19 Patients based on Gender and Age

Background: Studying the behavior of patients infected to Covid-19 is an essential issue for health authorities during the global pandemic, so the aim of this study is to investigate the statistical similarity between the recovery and mortality ratios based on the patients’ age and gender. To this purpose, the well-known statistical testing method of Kolmogorov-Smirnov has been utilized to investigate the similarity of distribution functions for mortality and recovery rates for patients infected to Covid-19. Results: Data for 1015 patients resulted in dead, recovery, and transferred have been collected and analyzed. The age is cross-classified by gender where the rates’ cumulative distribution functions are independently calculated and depicted for females and males. The results revealed there is no significant difference between the distribution functions of mortality and recovery rates by gender but there is by age. Conclusion: The research results would support the health authorities to manage the admission and discharging procedures of the Covid-19 patients where the hospitality services are traditionally provided differently by gender. Doi: 10.28991/HIJ-2021-02-04-05 Full Text: PDF

Information Systems Development Methodologies: A Review Through a Teleology Approach

The information systems analysis and design methodologies devised at the outbreak of the third industrial revolution shaped the systems analysis disciple and have trickled down to all systems influencing most aspects of human development. To cope with the explosion of digital technology, these methodologies had to be developed rapidly, drawing from a wide range of theoretical backgrounds, based mainly on the “hard” scientific method and the “softer” systems approach. In the run-up to industry 4.0, with multiple information systems emerging, reflection on systems’ design fundamentals is important. Intended to serve human activity and well-being, information systems are anthropocentric. Their success lies in their ability to serve human goals. Information systems analysis and design methodologies play a role in this by ensuring the best match between what is sought from systems and what they deliver in terms of the systems’ underlying final cause, or “telos”. The paper investigates the teleological orientation of four founding systems analysis and design methodologies. Using the Wood-Harper and Fitzgerald taxonomy in order to identify the conceptual origins of the four methodologies under review, it categorizes and subsequently incorporates them in an extended taxonomy, assesses whether and how they are devised to cater to the incorporation of goals and explains the inferred results based on the taxonomy. The paper posits that the founding information systems analysis and design methodologies do not have a marked teleological orientation and do not dispose of techniques for adequately incorporating systems’ goals. Doi: 10.28991/HIJ-2021-02-04-09 Full Text: PDF

Optimization of Fuzzy Support Vector Machine (FSVM) Performance by Distance-Based Similarity Measure Classification

This research aims to determine the maximum or minimum value of a Fuzzy Support Vector Machine (FSVM) Algorithm using the optimization function. SVM is considered as an effective method of data classification, as opposed to FSVM, which is less effective on large and complex data because of its sensitivity to outliers and noise. One of the techniques used to overcome this inefficiency is fuzzy logic with its ability to select the right membership function, which significantly affects the effectiveness of the FSVM algorithm performance. This research was carried out using the Gaussian membership function and the Distance-Based Similarity Measurement consisting of the Euclidean, Manhattan, Chebyshev, and Minkowsky distance methods. Subsequently, the optimization of the FSVM classification process was determined using four proposed FSVM models and normal SVM as comparison references. The results showed that the method tends to eliminate the impact of noise and enhance classification accuracy effectively. FSVM provides the best and highest accuracy value of 94% at a penalty parameter value of 1000 using the Chebyshev distance matrix. Furthermore, the model proposed will be compared to the performance evaluation model in preliminary studies (Xiao Kang et al., 2018). The result further showed that using FSVM with Chebyshev distance matrix and a Gaussian membership function provides a better performance evaluation value. Doi: 10.28991/HIJ-2021-02-04-02 Full Text: PDF