Mapping organizational complexity: a network-based approach to behavior through machine learning tools

The current uncertain, dynamic scenario calls for a systemic perspective when referring to organizational complexity and behavior. Our research contributes to the analysis of organizational complexity through multidimensional behavioral mapping. Our method uses machine learning tools to detect the interconnections between the different behaviors of a person in his/her operating context. First, the research project dealt with prototyping a model to read the organizational behavior, the related detection tool, and a data analysis methodology. It used machine learning tools and ended with a data visualization phase. We set our model to read the organizational behavior by comparing the literature benchmark theories with our field experience. The model was organized around 4 areas and 16 behaviors. These were the basis for singling out the indicators and the questionnaire items. The data analysis methodology aimed at detecting the interconnections between behaviors. We designed it by joining univariate analysis with a multivariate technique based on the application of machine learning tools. This led to a high-resolution network map through three specific steps: (a) creating a multidimensional topology based on a Kohonen Map (a type of unsupervised learning artificial neural network) to geometrically represent behavioral relationships; (b) implementing k-means clustering for identifying which areas of the map have behavior similarity or affinity factors; and (c) locating people and the various identified clusters within the map. The research highlighted the validity of machine learning tools to detect the multidimensionality of organizational behavior. Therefore, we could delineate the networking of the observed elements and visualize an otherwise unattainable complexity through multimedia and interactive reporting. Application in the field of research consisted of the design and development of a prototype integrated with our LMS platform via a plugin. Field experimentation confirmed the effectiveness of the method for creating professional growth and development paths. Furthermore, this experimentation allowed us to obtain significant data by applying our model to several sectors, namely pharmaceutical, TLC, banking, automotive, machinery, and services.

Rice crop response to site variability in a multi-locational trial: A call for site specific management

Yield is a net expression of genotype (G) x environment (E) interactions including management. However, the segregation of 'E' into respective causes is seldom done while 'G' is a constant. Soil is a component of 'E' with imminent variability in attributes among multiple locations. Data on yield response of varieties to a set of treatments in different soils from multi-locational yield maximisation trial under All India Coordinated Rice Improvement Project were regularly gathered. A dataset pertaining to a trial conducted in Karaikal district of Puducherry Union Territory was analysed to ascertain the site-specific crop responses with inherent variability in soils. Rice varieties, ADT 46, BPT 5204 and CR 1009 were tested for responses at 17 sites with farmer fertiliser practices (FFP), regional recommended fertiliser dose (RDF) and software, 'Nutrient Expert®' (2016) (NE) derived fertiliser quantities. Analysis of variance showed that test sites explained 59.3% variability in yield. A multivariate technique, Factor Analysis extracted two factors, which are linear combinations of soil attributes those explained 76% of variance in soils. Factor scores classified soils into four groups, owing to variability in soil properties. Soil texture influenced yield significantly (across varieties and treatments) (R2 = 11.1%). Sites varied in excess duration in nursery ranging from 2 - 26 days. However, this excess duration reduced number of panicles m-2 only in CR 1009 (r = -0.328**). General linear model with sites and treatments as fixed factors, their interactions and panicles m-2 as covariate predicted better (R2 = 90.3%) with their significant contribution to the model. The order of R2 (%) was Sites (59.3) > Varieties (27.4) > Treatments (13.6%) in explaining variability in yield highlighting site-specific responses. Mean differences between ADT 46 and BPT 5204; BPT 5204 and CR 1009 were significant. Yield significantly changed across sites and treatments when fertiliser management shifted from non-specific (FFP) to site-specific NE based calculations through RDF (region specific). Results of this trial placed emphasis on soil test-based crop management to realise the uniform best, which clearly is site specific crop management.

Roles of Managers and Stakeholders Perception on Solar Technology Adoption Intention: A Case of Micro, Small and Medium Enterprises (MSMEs) in Lagos State, Nigeria

Powers shortages is rampant in Africa of which Nigeria is not an exception and solar technology as a viable alternative source of electricity which would mitigate this problem has meted slow adoption. This study aimed to explore the impact of mindset/attitude from Theory of planned behavior (TPB), Disruptive Innovation Theory (DIA), awareness-knowledge, opportunity and barrier over managers (owners) of MSMEs intention to adopt solar technology for their businesses. A questionnaire was administrated to collect data from a sample of 400 managers (owners) of MSMEs respondents’ in Lagos State, Nigeria. A multivariate technique was applied to test the hypotheses using Structural Equation Modeling (AMOS-23). The findings showed that mindset/attitude, (DIA) and opportunity have a significant impact on solar technology intention, however, awareness-knowledge and barrier were not significant. These independent variables explained 71% variance of the dependent variable intention. In addition, DIA was found to have a significant impact on opportunity, barrier and mindset/attitude however, barrier on mindset/attitude was not significant. These findings not only provide evidence for MSMEs strategic planning to ensure sustainable business growth for their businesses but also provide new knowledge to policy and decision makers, the manufacturing & installation (suppliers) companies and other stakeholders for renewable energy as a part of long term sustainable development.

A Discriminant Model For Skill Oriented Prediction of Female Cricketers Depending Upon Selected Performance Parameters

Research Purpose. The study aimed to develop a discriminant model for cricketers on the basis of physiological & anthropometric variables. Material and Methods. The study included sixty female seniors BCCI board players representing five different states with mean age 23.4 ± 2.03, mean height 152.1 ± 3.44, and mean weight 52.4 ± 4.21. A multivariate technique was used to predict the cricket performance by classifying the players into batsmen and pace bowlers on the basis of selected physiological & anthropometrical variables. Results. All the assumptions were positively full-filled (Shapiro-Wilk test p > 0.05 and F = 8.121, p = 0.264 for Box’sM test) for applying discriminant analysis to develop the model. A total of eleven performance variables were initially selected for the study and after applying the stepwise statistical technique of discriminant analysis, the model selected certain variables, namely Muscle Mass (1.311), Fat (-0.182) & Shoulder Diameter (0.292) and showed its effectiveness as the Eigenvalue for the fit model was 0.848. Conclusion. A discriminant function F1 = -29.531 + (1.311 × Muscle Mass) + (-0.182 × Fat) + (0.292 × Shoulder Diameter) was developed. The percentage of total variation explained by the model was 71.9%. A total of 93.2% of the observations were correctly classified using the proposed discriminant model.

EFFECT OF HIGH PROTEIN DIET IN ACTIVITY OF ANTIOXIDANTS AND LEVEL OF INFLAMMATION ON SPRINT ATHLETE

This study aims to analyze the effect of a low-carbohydrate high-protein diet to increase the level of antioxidant, decrease inflammation and improve performance of athlete. The research was carried out by experimental research methods, within the design of "Randomized Control Group Pretest Posttest Design".A sample was taken from 20 people who met the inclusion and exclusion criteria from 30 teenage athletes in PASI East Java sprints. The Data were collected by measuring the sprint results by finish photo camera and laboratory examinations to determine the levels of antioxidants (SOD) and the inflammation degree (TNF α)in blood. The data were analyzed using multivariate technique (Manova) Hotelling's method (T2). Hypothesis testing using α0.05. The results and conclusions of the study stated that the normal diet had no effect on the variables of sprint running speed, SOD and TNF-α levels. While low-carbohydrate and high-protein diet can increase SOD levels of 211.44 /gHb, reduce (TNF α) at least 0.309 pg/ml, and the average increase in antioxidant activity caused by low-carbohydrate-high-protein diet is 24,989 / gHb higher than normal diet, the decrease in the degree of inflammation is 0.196 pg/ml, however, it has no effect on the speed of sprint.

Effect of high protein diet in activity of antioxidants and level of inflammation on sprint athlete

This study aims to analyze the effect of a low-carbohydrate high-protein diet to increase the level of antioxidant, decrease inflammation and improve performance of athlete. The research was carried out by experimental research methods, within the design of “Randomized Control Group Pretest Posttest Design”. A sample was taken from 20 people who met the inclusion and exclusion criteria from 30 teenage athletes in PASI East Java sprints. The Data were collected by measuring the sprint results by finish photo camera and laboratory examinations to determine the levels of antioxidants (SOD) and the inflammation degree (TNF-α) in blood. The data were analyzed using multivariate technique (Manova) Hotelling’s method (T2). Hypothesis testing using α = 0.05. The results and conclusions of the study stated that the normal diet had no effect on the variables of sprint running speed, SOD and TNF-α levels. While low-carbohydrate and high-protein diet can increase SOD levels of 211.44/gHb, reduce (TNF-α) at least 0.309 pg/ml, and the average increase in antioxidant activity caused by low-carbohydrate-high-protein diet is 24.989/gHb higher than normal diet, the decrease in the degree of inflammation is 0.196 pg/ml, however, it has no effect on the speed of sprint.

Research on the Impact of mHealth Apps on the Primary Healthcare Professionals in Patient Care

The goal of this study was to develop and use a questionnaire in order to analyse the effects of eHealth apps on patient care using Jordanian population. A two-stage cross-sectional research was conducted. A questionnaire was developed in the beginning to evaluate its consistency and legitimacy using Cronbach’s alpha coefficient, a multitrait connection atmosphere; the multivariate technique is component examination. In the study’s another phase, correlation and regression are used to determine the influence of eHealth apps on patient care. The five major axes of the final surveys were healthcare efficiency, teaching, notices, consultation, and follow-up. Individuals from diverse demographic aspects, such as gender, age, job experience, and education level, have no differing perspectives on cell phone use in their amenities, according to a staff’s viewpoint evaluation. In general, mobile health applications had a good influence on health services and healthcare, which would be an important setting for the operative use of mobile headphones in public policy; such a background would affect in workers’ intents to practice and adopt mHealth.

Synthesis, Characterization, and Application of Co-Al-Zn Layered Double Hydroxide/Hydrochar Composite for Simultaneous Removal of Cationic and Anionic Dyes

Decontamination of organic dyes from wastewater requires efficient and compatible materials that must be able to remove dyes with different charges at the same time. In this study, composites of layered double hydroxide (LDH) and hydrochar (HC) were prepared and tested for use as general-purpose sorbents for the simultaneous removal of cationic and anionic dyes (i.e., methylene blue (MB), methyl orange (MO), and reactive yellow (RY)). Characterization studies reveal that the surface functional groups on composites are –OH, NO3, M–O bonds. It was observed that crystallinity of LDH decreased with an increasing amount of HC. Preliminary experiments showed that the dyes (i.e., MB, MO, and RY) were well removed simultaneously onto the composite with HC (2.0 g HC/prepared composite). This composite was selected for more experiments, and the adsorption efficiency was optimized by the multivariate technique using the response surface methodology (RSM). Removal efficiency of 100% was obtained for all three dyes with an adsorption capacity of 243, 5.3, and 16.3 µmol g−1 for MB, MO, and RY, respectively. Elovich’s initial intake rates (α) were 4,272, 441, and 99.5 mg g−1 min−1 for RY, MB, and MO, respectively. Data fitted in various models suggested second-order multiplex kinetics, where the surface heterogeneity response was sorbate dependent.

Evaluation of Hydrophilic and Lipophilic Antioxidant Capacity in Spanish Tomato Paste: Usefulness of Front-Face Total Fluorescence Signal Combined with Parafac

The hydrophilic and lipophilic antioxidant activities due to the main bioactive components present in Spanish tomato paste samples were studied, using standardized and fluorescent methods. After extraction, phenolic antioxidants (Folin-Ciocalteu method) and total antioxidant activity (TEAC assay) were evaluated, examining differences between hydrophilic and lipophilic extracts corresponding to different samples. Total fluorescence spectra of extracts (excitation-emission matrices, EEMs) were recorded in the front-face mode at two different ranges: 210–300 nm/310–390 nm, and 295–350 nm/380–480 nm, for excitation and emission, respectively, in the hydrophilic extracts. In the lipophilic extracts, the first range was 230–283 nm/290–340 nm, while the second range was 315–383 nm/390–500 nm for excitation and emission, respectively. EEMs from a set of 22 samples were analyzed by the second-order multivariate technique Parallel Factor Analysis (PARAFAC). Tentative assignation of the different components to the various fluorophores of tomato was tried, based on literature. Correlation between the antioxidant activity and score values retrieved for different components in PARAFAC model was obtained. The possibility of using EEMs-PARAFAC to evaluate antioxidant activity of hydrophilic and lipophilic compounds in these samples was examined, obtaining good results in accordance with the Folin-Ciocalteu and TEAC assays.