Statistical Comparison of Architecture Driven Modernization with other Cloud Migration Frameworks and Formation of Clusters

Corporations are migrating their legacy software systems towards the cloud environment for amelioration, to avail benefits of the cloud. Long term success of modernizing a legacy software depends on the characteristics of the chosen cloud migration approach. Organizations must think over how strategically imperative is the chosen cloud migration framework to their business? Thus, the Object Management Group (OMG) has defined standards for the modernization process based on Architecture Driven Modernization (ADM) framework. ADM serves as a vehicle for facilitating the arrangement of information technology with business stratagem and its architecture. Until now, it seems that there is no systematic mapping among ADM and other cloud migration frameworks, highlighting the demanding features. This research aims to give an in-depth study of similar cloud migration frameworks. Thus, the researchers introduced the clusters containing cloud migration frameworks having similar features to ADM. This systematic mapping can be seen as a valuable asset for those who are interested in choosing the best migration framework from the pool of cloud modernization frameworks, according to their legacy software requirements. The clustering technique is used to appraise and compare ADM with some of the other cloud migration frameworks for highlighting the similarities and key differences. The quality of clusters is evaluated by the Rand index and Silhouette measurements. The study distills the record and yields a sound and healthy catalog for essential events and concerns that are communal in cloud migration frameworks. This research offers the one-stop-shop convenience that the industry desperately desires.

A Domain-Specific Modelling Language for Adventure Educational Games and Flow Theory

Designing educational games is a complex task and needs collaboration between game developers and an educator. Domain-Specific Modeling Language (DSML) offers an approach to simplify the design activities of educational games and support the involvement of both game developers and educators. This paper presents an extension of Serious Game Logic and Structure Modeling Language (GLiSMo), a DSML that designs the logical and structural views of educational adventure games. The gap in the original GLiSMo is that it did not allow an educational game to be designed according to any learning theories. Furthermore, the original GLiSMo does not cover all concepts in the adventure genre. The authors intend to extend the original GLiSMo by adding the concepts of Flow Theory and concepts of the adventure genre to make it more expressive. The extended DSML is called FA-GLiSMo. The authors evaluated the expressiveness of FA-GLiSMo using Framework for Qualitative Assessment of DSLs (FQAD). The result shows that the expressiveness of FA-GLiSMo is still ‘incomplete’ due to the lack of clarity of semantics for several domain concepts. Improvements were performed, and the finalized FA-GLiSMo now has fifteen (15) concepts of the Logic diagram, nineteen (19) concepts of the Structure diagram, and a new diagram called the Flow diagram containing five (5) concepts of the Flow Theory. The authors also demonstrate in this paper the concrete syntax of FA-GLiSMo using the Tales of Monkey Island game as a case study

Drought stress, its effect on maize production and development of drought tolerance through potassium application

Today, the world is facing many problems for crop production among them drought is the most dangerous. Here in this paper we have reviewed the threat of drought to food security in future especially related to maize production. Water is a cooling agent plays an important role in the functioning of plant body. Drought stress have deleterious effects on the seedling establishment, vegetative growth, photosynthesis, root growth, anthesis, anthesis-silking interval, pollination and grain formation in maize crop. The deleterious effects of drought can be mediated by application of nutrients which may enhance tolerance to drought stress. Among the nutrients potassium can enhance the tolerance in maize plant for drought stress. The application of potassium enhanced root growth and stem elongation. Similarly, potassium increased leaf water potential, osmotic potential and turgor potential under drought stress. Likewise, gas exchange parameters are improved by potassium. Application of potassium enhanced the photosynthetic rate and has better effect on other attributes. Most importantly potassium is greatly helpful in transport of sugars prepared in leaves to fruit. Potassium enhanced the yield and yield related parameters of maize crop. It seems quite important to study the role of potassium for increasing the plant tolerance to drought stress and to increase yield of crop under drought stress

Spatiotemporal variation in land use land cover in the response to local climate change using multispectral remote sensing data

Climate change is likely to have serious social, economic, and environmental impacts on farmers whose subsistence depends on nature. Land Use Land Cover (LULC) changes were examined as a significant tool for assessing changes at diverse temporal and spatial scales. Normalized Difference Vegetation Index (NDVI) has the potential ability to signify the vegetation structures of various eco-regions and provide valuable information as a remote sensing tool in studying vegetation phenology cycles. In this study, we used remote sensing and Geographical Information System (GIS) techniques with Maximum Likelihood Classification (MLC) to identify the LULC changes for 40 years in the Sahiwal District. Later, we conducted 120 questionnaires administered to local farmers which were used to correlate climate changes with NDVI. The LULC maps were prepared using MLC and training sites for the years 1981, 2001, and 2021. Regression analysis (R2) was performed to identify the relationship between temperature and vegetation cover (NDVI) in the study area. Results indicate that the build-up area was increased from 7203.76 ha (2.25%) to 31,081.3 ha (9.70%), while the vegetation area decreased by 14,427.1 ha (4.5%) from 1981 to 2021 in Sahiwal District. The mean NDVI values showed that overall NDVI values decreased from 0.24 to 0.20 from 1981 to 2021. Almost 78% of farmers stated that the climate has been changing during the last few years, 72% of farmers stated that climate change had affected agriculture, and 53% of farmers thought that rainfall intensity had also decreased. The R2 tendency showed that temperature and NDVI were negatively connected to each other. This study will integrate and apply the best and most suitable methods, tools, and approaches for equitable local adaptation and governance of agricultural systems in changing climate conditions. Therefore, this research outcome will also meaningfully help policymakers and urban planners for sustainable LULC management and strategies at the local level

BUILDING PRIOR DENSITIES FOR MAXIMUM ENTROPY REFINEMENT OF X-RAY DATA FOR TOPOLOGICAL ANALYSIS

The aim of this research work is to develop a method to provide a reasonable “prior” electron density that can be used in the so-called “Maximum Entropy Method” (MEM) refinement of X-ray diffraction (XRD) data in order to reconstruct experimental electron density at a resolution allowing its accurate topological analysis. A program was developed which build electron density on a regular grid in the “Independent Atom Model” (IAM) approach, more precisely from the knowledge of individual “spherical” atomic scattering factors of the atoms constituting the unit cell of the studied compounds. IAM X-ray structure factors of bismuth and its prior density on a grid has been generated to be tested with the MEM “Enigma” software. Preliminary accuracy and performances have been compared when such reasonable “prior” density is used instead of starting with “flat” density. &nbsp

Monitoring the dynamic changes in vegetation cover using spatio-temporal remote sensing data from 1984 to 2020

Anthropogenic activities and natural climate changes are the central driving forces of global ecosystems and agriculture changes. Climate changes, such as rainfall and temperature changes, have had the greatest impact on different types of plant production around the world. In the present study, we investigated the spatiotemporal variation of major crops (cotton, rice, wheat, and sugarcane) in the District Vehari, Pakistan, from 1984 to 2020 using remote sensing (RS) technology. The crop identification was pre-processed in ArcGIS software based on Landsat images. After pre-processing, supervised classification was used, which explains the maximum likelihood classification (MLC) to identify the vegetation changes. Our results showed that in the study area cultivated areas under wheat and cotton decreased by almost 5.4% and 9.1% from 1984 to 2020, respectively. Vegetated areas have maximum values of NDVI (>0.4), and built-up areas showed fewer NDVI values (0 to 0.2) in the District Vehari. During the Rabi season, the temperature was increased from 19.93 °C to 21.17 °C. The average temperature was calculated at 34.28 °C to 35.54 °C during the Kharif season in the District Vehari. Our results showed that temperature negatively affects sugarcane, rice, and cotton crops during the Rabi season, and precipitation positively affects sugarcane, rice, and cotton crops during the Kharif season in the study area. Accurate and timely assessment of crop estimation and relation to climate change can give very useful information for decision-makers, governments, and planners in formulating policies regarding crop management and improving agriculture yields

ROLE OF SONOELASTOGRAPHY IN THE EVALUATION OF THYROID NODULES

Thyroid nodular disease is one of the most common endocrine disorder. B mode ultrasound provides useful characteristic information about thyroid nodules but it has noticeably low accuracy to differentiate benign from malignant. Fine needle aspiration is widely been used in differentiation of benign and malignant thyroid nodules but it is an invasive procedure. Sonoelastography is a newly developed non- invasive technique which uses ultrasound and gives information about the stiffness of tissue. It estimates the hardness of thyroid lesions in association with adjacent tissues and assists in the differentiation of benign from malignant nodules.Objective:The objective of this study was to evaluate the role sonoelastography in the evaluation of thyroid nodules. Methods:This study was conducted on 72 Patients of age between 18-80 years of either gender at Institute of Nuclear Medicine and Oncology Lahore (INMOL) Pakistan, from 25 March 2019 to 23 August 2019 for duration of five months. Elastography was performed using Toshiba Aplio 500.  Patient having one or more solid nodules in thyroid on conventional ultrasound examination were included in the study and the sonoelastography of nodules was confirmed with histopathological findings of nodules. Results: A total 72 participants were included in our study. The mean age of participants was 42.11 years. Gender distribution shows that 51.4% (n=37) were male and 48.6% (n=35) were female. Sonoelastographic strain ratio of 55.6% nodules (n=40) was more than 2.1(malignant feature) and 44.4% nodules (n=32) have less than 2.1 (benign). Histopathology showed 56.9% of participants (n=41) have malignant nodules and 43.1% (n=31) have benign nodules. The comparison of sonoelastography and histopathology in reference with nodules shows that the results of histopathology and sonoelastography were same and support each other. Conclusion: Sonoelastography is non-invasive and cost-effective imaging technique to diagnose thyroid nodules either benign or malignant. Keywords: Ultrasound Elastography, Thyroid Nodules, Benign, Malignant, Fine Needle Aspiration. DOI: 10.7176/JHMN/66-08 Publication date:September 30th 201

Toward a reinforcement-sensitive psychophysiological model for health-related behaviours and health communications

This dissertation explores the hypothesised role of psychobiological personality dimensions in shaping specific health-related behaviours and propositions potential health communications. The primary aim was to investigate Eysenck’s and Gray’s personality dimensions in relationship to specific smoking, alcohol-use, substance-use, physical exercise and eating behaviours. Past research has either focussed on a narrow range of behaviours or examined the relation between personality, health behaviours and message interventions insufficiently. It is argued that most health behaviours are a function of psychophysiological processes and social learning, and future research should find them differentially conditionable by appropriate punishment- or reward-oriented messages. The dissertation draws on the Hippocrates-Galen-Avicennic tradition and the works of Pavlov, Skinner, Mowrer, Eysenck and Gray, and examines the previously ignored work of Avicenna on human temperament and emotions. A taxonomy of health-related behaviours and a framework for health communication and behaviour change are presented. The behavioural taxonomy of Indulgent-Denial, Delinquent-Inert, and Escape-Maintenance is assessable by physiological and psychological markers, and corresponds to Eysenck’s three-dimensional personality structure. The partly validated model explains behavioural variations by composites of nervous conduction and reactivity of behavioural systems in the brain, and also outlines possible communication interventions. The dissertation is anchored in positivism, assuming intrinsic biogenetic influences as the psychophysiological reality. A retrospective Study consisting of a single cross-sectional survey explored the multivariate relationship between the psychobiological personality dimensions and health-related behaviours in a student sample. In line with the protocols approved by the Ethics Committee, two standard personality instruments, the Eysenck Personality Questionnaire-Revised and the Sensitivity to Punishment and Sensitivity to Reward Questionnaire, and an especially developed Behavioural Questionnaire provided the self-report measurements. Demographic effects on behavioural and personality variables were discovered by chi-square tests and two-way multivariate analysis of variance respectively, associations between variables were observed by correlational analysis, likelihood of a specific behaviour on the basis of personality variables was examined by a logistic model, and health diagnostic accuracies of personality measures were assessed by Receiver Operating Characteristic analysis. It was found that high Extraversion and high Psychoticism scorers, and so Indulgent and Delinquent Behaviours were more likely to show appetitive associations, whereas high Neuroticism scorers and thereby Escape Behaviours were more likely to show aversive associations. All Eysenckian dimensions revealed low-to-moderate Reward-sensitivity while Neuroticism showed combined strengths of Punishment- and Reward-sensitivity. The intercorrelations of personality dimensions supported Gray that the Eysenckian dimensions probably represent unequal mixtures of Punishment- and Reward-sensitivity. The associations between personality and behaviours indicate Reward-sensitivity and Psychoticism as the most useful personality disorder dimensions, and the research questions the often-attributed role of Extraversion as a cardinal well-being dimension. Statistically and practically significant relationships between Extraversion and alcohol-use, Psychoticism and heavy alcohol-use, Psychoticism and substance-use, Psychoticism and heavy substance-use, and Neuroticism and binge-eating were observed, but the health diagnostic accuracies of personality measures were mostly poor and the correlations and odds ratios between personality and behavioural data were subject to a ceiling effect. The thesis questions whether personality measures may be a data collection method and not a diagnostic test for health-related behaviours. It is argued that personality data alone may be of insufficient diagnostic value in clinical decision-making and healthcare setting. Thus, the dissertation asserts that health-risk behaviours will be best understood when examined in relation to the reinforcement-sensitive behavioural systems in brain and the contexts in which these behaviours occur. A psychophysiological framework of behavioural assessment and modification is advisable instead of strict personality-based models or a one-size-fits-all approach, in view of theoretical and empirical knowledge about the neuronal growth through life, nerve physiology, early childhood development, relationships between conscious and unconscious processes, the anachronistic assumption of immutability of personality traits as risk factors, results of the data analysis and the observation that health-risk behaviours are of different types and should entail differential emotional appeals. The thesis has created an architecture for future behavioural research with an emphasis on systematic punishment- or reward-oriented health communication interventions, an area that has received comparatively little empirical attention. KEY WORDS: Behavioural Epidemiology, Behavioural Medicine, Health Communication, Personality Factors in Health and Behaviour Change, Population Health

Are you selling the right colour? A cross-cultural review of colour as a marketing cue

Should a marketer adopt a pancultural or a culture-specific approach in using colour in marketing? This paper reviews the psychological and sociocultural associations and meanings of colour(s) in a cross-cultural marketing perspective, and outlines its role as a marketing cue. It is argued that a cross-cultural perspective of colour research and application is imperative for developing global marketing strategies, and the cultural values, marketing objectives and desired customer relationship levels would dictate the choice of colour in corporate and marketing communications in the 21st Century. IdentifYing appropriate colour-culture clusters also facilitates the development of a colour theory in marketing