Binary logistic regression methods for modeling broncho-pneumonia status in infants from tertiary health institutions in north central Nigeria

Acute respiratory tract infections, predominantly bronchopneumonia, are one of the leading causes of infant deaths in developing countries and around the world. This work models the effects of the significant risk factors on infants’ bronchopneumonia status and also fits some reduced models and determines the best model with minimum number of parameters. The data for this study consist of a random sample of 433 births to women seen in the obstetrics clinic of two sampled tertiary health institutions in north-central Nigeria. These include University Teaching Hospital (UTH) Abuja, and Federal Medical Center (FMC) Keffi, Nasarawa State. Binary logistic regression was used to identify and model the effects of the various risk factors while stepwise regression technique was used to fit some reduced logistic regression models. Then the best fitting model with minimum number of parameters was identified using likelihood ratio statistic. It was observed that baby’s weight at birth, baby’s weight four weeks since birth, and mother’s occupation have significant effects on infant’s bronchopneumonia status. Additionally, among the four fitted reduced models, model4 is the best predictor of infants’ bronchopneumonia status, followed by model3 and then model2. Therefore, community service like home visiting for health education, supplementation of vitamin A, etc., would be an advantage if provided for teenaged pregnant women as it would, in turn, reduce incidence of low birth weight and thereby reduce bronchopneumonia infection among these children.Keywords: Bronchopneumonia, Multiple Logistic Regression Model, Fitness, likelihood ratio tes

Modelling for classifying different shadow of obstacles on a c-Si PV panel

Shadow of Obstacles (SoO) on a PV Panel is classified depending on time with changing pattern of the shadow. Due to obstacles, the performance of a silicon c-Si PV panel reduces by a significant level. Different types of obstacles cast shadow on the panel and interrupt to get irradiation reducing the generated power. The simulation model is implemented in Matlab/Simulink to observe the changing pattern and variation of output power with changing shadow pattern of the obstacles. The results show identical behaviors. It is clearly viewed in both PV generated I-V and P-V curves. Their pattern of graphs is changed depending on the time for time-dependent obstacles. Graphs pattern is also changed with depending on time-independent obstacles and that does not vary with time. The identification of the behavior of the obstacle is vital to improve the PV system performance

A generalized approach for design of contingency versatile DC voltage droop control in multi-terminal HVDC networks

The non-deterministic nature of power fluctuations in renewable energy sources impose challenges to the design of DC voltage-droop controller in Multi-Terminal High-Voltage DC (MTDC) systems. Fixed droop control does not consider converters’ capacity and system operational constraints. Consequently, an adaptive droop controller is counseled for appropriate power demand distribution. The previous adaptive droop control studies based on the converters’ Available-Headroom (AH) have lacked the demonstration of the droop gain design during consecutive power disturbances. In this paper, the design of the adaptive DC voltage droop control is investigated with several approaches, based on the permitted converters’ global and/or local AH and Loading Factor (LF). Modified adaptive droop control approaches are presented along with a droop gain perturbation technique to achieve the power-sharing based on the converters’ AH and LF. In addition, the impact of Multi-Updated (MU), Single-Updated (SU), and Irregular-Updated (IU) droop gains is investigated. The main objective of the adaptive droop control design is to minimize the power-sharing burden on converters during power variations/consecutive disturbances while maintaining the constraints of the DC grid (i.e., voltage and power rating). The presented approaches are evaluated through case studies with a 4-terminal and 5-terminal radial MTDC networks.Qatar Foundation; Qatar National Research FundScopu

Review on State-of-the-Art Unidirectional Non-Isolated Power Factor Correction Converters for Short-/Long-Distance Electric Vehicles

Electrification of the transportation sector has originated a worldwide demand towards green-based refueling infrastructure modernization. Global researches and efforts have been pondered to promote optimal Electric Vehicle (EV) charging stations. The EV power electronic systems can be classified into three main divisions: power charging station configuration (e.g., Level 1 (i.e., slow-speed charger), Level 2 (i.e., fast-speed charger), and Level 3 (i.e., ultra-fast speed charger)), the electric drive system, and the auxiliary EV loads. This paper emphasizes the recent development in Power Factor Correction (PFC) converters in the on-board charger system for short-distance EVs (e.g., e-bikes, e-trikes, e-rickshaw, and golf carts) and long-distance EVs (passenger e-cars, e-trucks, and e-buses). The EV battery voltage mainly ranges between 36 V and 900 V based on the EV application. The on-board battery charger consists of either a single-stage converter (a PFC converter that meets the demands of both the supply-side and the battery-side) or a two-stage converter (a PFC converter that meets the supply-side requirements and a DC-DC converter that meets the battery-side requirements). This paper focuses on the single-phase unidirectional non-isolated PFC converters for on-board battery chargers (i.e., Level 1 and Level 2 charging infrastructure). A comprehensive classification is provided for the PFC converters with two main categories: (1) the fundamental PFC topologies (i.e., Buck, Boost, Buck-Boost, SEPIC, C k, and Zeta converters) and (2) the modified PFC topologies (i.e., improved power quality PFC converters derived from the fundamental topologies). This paper provides a review of up-to-date publications for PFC converters in short-/long-distance EV applications.Qatar National Research FundScopu

Crop response to seed-row placed sulfur fertilizers

Non-Peer Reviewe

Renal Vein Thrombosis

ObjectiveThe aim of this article is to review the published English literature on aetiology, pathology, clinical presentation, diagnostic methods and treatment of renal vein thrombosis.Materials and methodsWe searched the published literature from Medline & Pubmed using keywords renal vein thrombosis, anti-phospholipid syndrome and nephrotic syndrome. Data was extracted from individual case reports, case series, articles on pathology, diagnostic tests, treatment modalities, and previous reviews. Case reports which did not add any new information were excluded.ResultsWe selected 60 references based on the above criteria. Renal vein thrombosis is relatively rare. CT angiography is considered the investigation of choice. Alternatives include MR angiography or renal venography in highly selected patients. As the condition is relatively uncommon, consensus on the best form of therapy for this condition has been slow to evolve. The trend in management has shifted to non-surgical therapies particularly systemic anticoagulation except in highly selected group of patients

A study on the Flora of El-Qantara Sharq in North Sinai, Egypt

AbstractThe study on the Flora of El Qantara Sharq revealed that the presence of 138 species belonging to 110 genera follows 39 Angiospermae families. The percentages of the representation of these families were Gramineae by 15.9%, Compositae by 13.7%, Leguminosae by 10.8%, Chenopodiaceae by 10.1%, and Cruciferae by 4.3%, while each of Caryophyllaceae, Cyperaceae and Polygonaceae was represented by 3.6% and the percentage was 2.8% for both of Convolvulaceae and Zygophyllaceae whereas it was 2.1% for each of Aizoaceae, Amaranthaceae and Tamaricaceae. The percentage was 1.4% for each of Euphorbiaceae, Orobanchaceae, Solanaceae and Umbelliferae. The remainder families, Asclepiadaceae, Ceratophyllaceae, Combretaceae, Geraniaceae, Haloragiadaceae, Juncaceae, Labiatae, Malvaceae, Neuradaceae, Nitrariaceae, Palmae, Plantaginaceae, Potamogetonaceae, Primulaceae, Ranunculaceae, Salicaceae, Scrophulariaceae, Thymelaeaceae, Typhaceae, Urticaceae and Verbenaceae were represented by one species (0.7%) for each. Shrubs were represented by 11.5% of the recorded species while the percentages of perennial and annual herbs were 21.7% and 63% respectively. Three parasite species were recorded: Cistanche phelypaea (L.) Cout., Cuscuta campestris Yunck. and Orobanche crenata Forssk

Noise-robust method for image segmentation

Segmentation of noisy images is one of the most challenging problems in image analysis and any improvement of segmentation methods can highly influence the performance of many image processing applications. In automated image segmentation, the fuzzy c-means (FCM) clustering has been widely used because of its ability to model uncertainty within the data, applicability to multi-modal data and fairly robust behaviour. However, the standard FCM algorithm does not consider any information about the spatial linage context and is highly sensitive to noise and other imaging artefacts. Considering above mentioned problems, we developed a new FCM-based approach for the noise-robust fuzzy clustering and we present it in this paper. In this new iterative algorithm we incorporated both spatial and feature space information into the similarity measure and the membership function. We considered that spatial information depends on the relative location and features of the neighbouring pixels. The performance of the proposed algorithm is tested on synthetic image with different noise levels and real images. Experimental quantitative and qualitative segmentation results show that our method efficiently preserves the homogeneity of the regions and is more robust to noise than other FCM-based methods

Data Mining based Soft Computing Skills towards Prevention of Cyber Crimes on the Web

Internet is the vital resource of Information technology through which the source of Information can be transfer from one machine to anther machine ,information can be receive from one machine and it can be processed and send to another one in this sense it become a great hub distribution of information resources. Now that information can be utilized for educational, for commercial, for personal, by means of that has a various shapes and structure of its necessity. And this results into the traffic over the Internet. Therefore a robust and ideal methodology need to produced for tracing and detecting terror based activities by using traffic content as the auditing of information is being shown These methodologies read and detect the Abnormal and typical behavior of terrorist by using and applying various algorithms of Data Mining and the textual content of terror related web sites and finally profile is give and used by the system to take a real action in the form of tracing and detecting of such suspected person which are evolves in terror activities. As a modern term of computer science its combines with neural networks, artificial intelligence and advanced information technology in the terms of Web or Internet, no doubt Data mining also has a wide scope and verities of large range of web based Applications, with reference to the soft computing Technology which combines with Fuzzy Logic, Artificial Intelligence, Neural networks, and genetic Algorithm in the proposed computing. In this paper the various approaches of soft computing is discussed. DOI: 10.17762/ijritcc2321-8169.15037