ACTIVITY BASED COSTING FOR BETTER COST MANAGEMENT

Implementing change in management, successfully and profitably, is the greatest challenge for modern enterprises. Innovation in strategies, marketing performance, role of competition, change in technology, change in customer needs, management initiatives are all facts of life in the global environment today. Cost management works with its customer to manage change more profitably. Activity-Based Costing (ABC) is a new methodology of product costing which measures the cost of products more accurately. Overhead allocation is much more sophisticated under this system. This paper attempts to highlight the need, importance and methodology of ABC for better Cost Management in modern enterprises.Cost management; Cost and activity drivers; Activity based costing (ABC); ABC implementation; ABC applications

Informative SNP Selection and Validation

The search for genetic regions associated with complex diseases, such as cancer or Alzheimer\u27s disease, is an important challenge that may lead to better diagnosis and treatment. The existence of millions of DNA variations, primarily single nucleotide polymorphisms (SNPs), may allow the fine dissection of such associations. However, studies seeking disease association are limited by the cost of genotyping SNPs. Therefore, it is essential to find a small subset of informative SNPs (tag SNPs) that may be used as good representatives of the rest of the SNPs. Several informative SNP selection methods have been developed. Our experiments compare favorably to all the prediction and statistical methods by selecting the least number of informative SNPs. We proposed algorithms for faster prediction which yielded acceptable trade off. We validated our results using the k-fold test and its many variations

Essays on reducing emissions from deforestation and forest degradation in the Terai Arc landscape of Nepal

Opportunity costs of conserving forest for the purpose of greenhouse gas emissions reductions underpin economic sustainability of ‘reducing emissions from deforestation and forest degradation (REDD+)’ and are essential to ascertain before embarking into this newly proposed mechanism to mitigate climate change. Two major determinants of REDD+ opportunity costs are the drivers of deforestation and forest degradation and the carbon stock. These factors differ from place to place. Use of global land use models and of forest carbon stock estimates to design REDD+ at sub-national or national scale may be misleading if they do not reflect local socio-economic and agro-ecological conditions. This study examined the potential costs of emissions reductions in the Terai Arc Landscape of Nepal, one of the biodiversity hotspots of the world. The first part of the thesis examines the underlying causes of deforestation and forest degradation. A sythesized econometric model of deforestation is prepared including rarely integrated part of forest degradation. A newly assembled panel data sets of 15 districts of Nepal over a 19-year period were used for the analysis. The results highlight that increased agricultural yield and promotion of community-based forest management regimes reduce deforestation. Fuel wood, the main source of energy used for cooking in the landscape, is the proximate cause of forest degradation along with timber extraction. Alternative energy sources like solar and biogas can be substituted for fuel wood to reduce forest degradation. The second part of the study deals with carbon stock in the forests. The research estimated the distribution of C stock across the different pools and management regimes of tropical Sal forest. It applied a field measurement approach and collected biomass data from 113 sample plots. The estimated average total carbon stock was 228.76±19.61 Mg ha⁻¹. The value of total C stock, however, varied according to management regimes. The estimated carbon stocks differed from all earlier estimates based on biome-average dataset. Evidence of strong association of C stock with management regime provides valuable information for policy makers to make informed choice of management regime for the landscape. The third part of the study is focused on estimation of opportunity costs of emissions reductions through avoided deforestation and forest degradation. A bottom-up approach is applied using time series data of agriculture, timber and fuel wood production and prices to estimate the opportunity costs. The estimated mean opportunity cost of emissions reductions from avoided deforestation on the Terai Arc Landscape is found to be US$ 8.95 per Mg CO₂e. The study reveals that emission reduction from avoided forest degradation is cheaper than emission reduction through avoided deforestation. The opportunity cost estimates are higher than those reported in earlier global studies and are attributed to higher agricultural returns and lower carbon density in the forest of the Terai Arc Landscape. The study suggests that the levels of funding needed for REDD+ based on the earlier global estimates may be insufficient for effective emissions reductions. Policy makers to be cautious when using global models and values to design any sub-national REDD+ scheme

A PROSPECTIVE OBSERVATIONAL STUDY ON PATTERN OF ADVERSE DRUG REACTION TO ANTIBIOTICS COMMONLY PRESCRIBED IN THE HOSPITALIZED PEDIATRIC PATIENTS

Objective: Antibiotics are the almost usually specified or authorized medication in hospitals, and antibiotics were found to be the almost bothersome classes of drugs providing or endowing to adverse drug reactions (ADRs). Therefore, the present study was conducted to check or regulate the precautions (ADRs) of antibiotics usually specified or authorized in the pediatrics unit. Methods: A potential, experimental, non-interventionist study was conducted or executed in the Department of Pediatrics for a time of 6 months to analyze the ADRs reported spontaneously from the hospital using patient statistics, objective and medication information, data of ADRs, onset time, causal drug details, outcome, and severity. Results: Among 72 ADRs observed, beta-lactams and quinolones were set up to be contributing the highest number of ADRs. The duct or abdominal system was the almost commonly affected organ, followed by respiratory system and the cardiovascular system. The assessment by the World Health Organization causation estimation scale demonstrated that 5.56% ADRs were certain, 55.56% were possible, 30.56% were probable, and 8.33% were unlikely. Conclusion: Thus, the pattern of ADRs occurring in the pediatric population was observed and assessed. Early recognition and management of ADRs are essential to reduce the burden of ADR

An Intelligent Controller for the Signal Generation of Solar Energy and Battery Storage Supported Multi-Level UPQC

This study examines, the solar power and battery energy storage associated diode clamped five-level unified Power quality conditioner (5L-UPQC) to handle the PQ related problems. To eliminate the requirement of the complex transformations like abc, dq0, ?? , the ANN based control scheme with LMBP training method is adopted for the 5L-UPQC to produce the necessary reference signals for the voltage source converters (VSC’s). The prime goal of the proposed scheme is to maintain stable DLCV during load shifting, reduction of THD. In addition, the grid voltage distortions like sag, disturbance and swell were eliminated. The suggested method was demonstrated on two cases with several permutations of loads. However, to reveal the performance of the developed method, the comparison is carried out with the PIC and SMC

A STUDY ON USAGE OF OPEN EDUCATIONAL RESOURCES (OER) FORMAT TO ENHANCING THE ACADEMIC PERFORMANCE OF HIGHER SECONDARY SCHOOL STUDENTS IN RAMANATHAPURAM EDUCATIONAL DISTRICT

Open Educational Resources (OER) are freely available, openly allowed text, media, and other digital resources that are useful for instruction. The Open Educational Resources (OER) formats are used for this study with the help of the internet. The investigator as a facilitator for this study. The learning is through open educational resources in three months. The quarterly marks were used for pretest and half-yearly marks were used for the post-test score. The experimental method and single group design were employed in the study. 40 students were taken for this study. The simple random sampling has used the study. The findings were there is no significant difference between the groups. The academic performance is may increase through Open Educational Resource (OER) format learning.

PHARMACEUTICO-ANALYTICAL STUDY OF ANILARI RAS: A HERBO MINERAL COMPOUND

Rasasastra is a branch of Ayurvedic medicine which deals with preparation of the drugs with metals and minerals having higher therapeutic efficacy with quick action in minute dose. Present preparation Anilari Ras is a herbo-mineral formulation used for treating all types of Vata disorders. This drug is a variety of Tamra bhasma (incinerated Copper) preparation processed with Shodit parad (Purified Mercury), Shodit Gandhak (Purified Sulphur), Shodit Tamra (Purified Copper) and Bhavana dravyas (liquids used for trituration) are Nirgundi patra swarasa (Vitex negundo Linn.),  Eranda mula kashaya (Ricinus communis Linn) and Citraka mula kashaya (Plumbago zeylanica Linn). Triturating Rasa drugs with herbal liquids (Bhavana) increases the efficacy of formulation. Puta in the preparation imparts Laghutva (easily assimilating) property, helps in particle reduction and facilitates nano particle formation which enhances rapid action of the medicine. The pharmaceutically developed drug was subjected for certain Analytical tests like Organoleptic, Physico-chemical, Scanning Electron Microscope (SEM), Energy- Dispersive X-ray Spectroscopy (EDS) and X-ray diffraction (XRD), with a view to standardize the formulation. The results show major peaks of Meta Cinnabar (HgS), Covellite (CuS) and minor peaks of Sulphur (S8). The Average grain size in SEM at 5K X is 218.4 nm and at 7K X is 210.0 nm

Static and dynamic bifurcation analysis of autonomous ODE systems using reductive pertubation method

Master'sMASTER OF ENGINEERIN

An intelligent system to detect slow denial of service attacks in software-defined networks

Slow denial of service attack (DoS) is a tricky issue in software-defined network (SDN) as it uses less bandwidth to attack a server. In this paper, a slow-rate DoS attack called Slowloris is detected and mitigated on Apache2 and Nginx servers using a methodology called an intelligent system for slow DoS detection using machine learning (ISSDM) in SDN. Data generation module of ISSDM generates dataset with response time, the number of connections, timeout, and pattern match as features. Data are generated in a real environment using Apache2, Nginx server, Zodiac FX OpenFlow switch and Ryu controller. Monte Carlo simulation is used to estimate threshold values for attack classification. Further, ISSDM performs header inspection using regular expressions to mark flows as legitimate or attacked during data generation. The proposed feature selection module of ISSDM, called blended statistical and information gain (BSIG), selects those features that contribute best to classification. These features are used for classification by various machine learning and deep learning models. Results are compared with feature selection methods like Chi-square, T-test, and information gain