Fuzzy Cognitive Map based Prediction Tool for Schedule Overrun

The main aim of any software development organizations is to finish the project within acceptable or customary schedule and budget Software schedule overrun is one of a question that needs more concentration Schedule overrun may affect the whole project success like cost quality and increases risks Schedule overrun can be reason of project failure In today s competitive world controlling the schedule slippage of software project development is a challenging task Effective handling of schedule is an essential need for any software project organization The main tasks for software development estimation are determining the effort cost and schedule of developing the project under consideration Underestimation of project done knowingly just to win contract results into loses and also the poor quality project So precise schedule prediction leads to efficient control of time and budget during software development In this paper we developed a new technique for the prediction of schedule overrun This paper also presents the comparison with other algorithms of schedule estimation and Tool developed by us and at last proved that Fuzzy cognitive map based prediction tool gives more accurate results than other training algorithm

Controlling the size distribution of nanoparticles through the use of physical boundaries during laser ablation in liquids

A simple, yet effective method of controlling the size and size distributions of nanoparticles produced as a result of laser ablation of target material is presented. The method employs the presence of physical boundaries on either sides of the ablation site. In order to demonstrate the potential of the method, experiments have been conducted with copper and titanium as the target materials that are placed in two different liquid media (water and isopropyl alcohol). The ablation of the target material immersed in the liquid medium has been carried out using an Nd:YAG laser. Significant differences in the size and size distributions are observed in the cases of nanoparticles produced with and without confining boundaries. It is seen that for any given liquid medium and the target material, the mean size of the nanoparticles obtained with the boundary-fitted target surface is consistently higher than that achieved in the case of open (flat) targets. The observed trend has been attributed to the plausible role(s) of the confining boundaries in prolonging the thermalisation time of the plasma plume. In order to ascertain that the observed differences in sizes of the nanoparticles produced with and without the presence of the physical barriers are predominantly because of the prolonged thermalisation of the plasma plume and not due to the possible formation of oxide layer, select experiments with gold as the target material in water have also been performed. The experiments also show that, irrespective of the liquid medium, the increase in the mean size of the copper-based nanoparticles due to the presence of physical boundaries is relatively higher than that observed in the case of titanium target material under similar experimental conditions.Comment: 24 pages, 9 figures, a part of this work has been published in Photonics Prague 2017, (Proc. SPIE 10603, Photonics, Devices, and Systems VII, 1060304) titled "A novel method for fabrication of size-controlled metallic nanoparticles

Direct Analysis in Real Time by Mass Spectrometric Technique for Determining the Variation in Metabolite Profiles of Cinnamomum tamala Nees and Eberm Genotypes

Cinnamomum tamala Nees & Eberm. is an important traditional medicinal plant, mentioned in various ancient literatures such as Ayurveda. Several of its medicinal properties have recently been proved. To characterize diversity in terms of metabolite profiles of Cinnamomum tamala Nees and Eberm genotypes, a newly emerging mass spectral ionization technique direct time in real time (DART) is very helpful. The DART ion source has been used to analyze an extremely wide range of phytochemicals present in leaves of Cinnamomum tamala. Ten genotypes were assessed for the presence of different phytochemicals. Phytochemical analysis showed the presence of mainly terpenes and phenols. These constituents vary in the different genotypes of Cinnamomum tamala. Principal component analysis has also been employed to analyze the DART data of these Cinnamomum genotypes. The result shows that the genotype of Cinnamomum tamala could be differentiated using DART MS data. The active components present in Cinnamomum tamala may be contributing significantly to high amount of antioxidant property of leaves and, in turn, conditional effects for diabetic patients

The role of entanglement for enhancing the efficiency of quantum kernels towards classification

Quantum kernels are considered as potential resources to illustrate benefits of quantum computing in machine learning. Considering the impact of hyperparameters on the performance of a classical machine learning model, it is imperative to identify promising hyperparameters using quantum kernel methods in order to achieve quantum advantages. In this work, we analyse and classify sentiments of textual data using a new quantum kernel based on linear and full entangled circuits as hyperparameters for controlling the correlation among words. We also find that the use of linear and full entanglement further controls the expressivity of the Quantum Support Vector Machine (QSVM). In addition, we also compare the efficiency of the proposed circuit with other quantum circuits and classical machine learning algorithms. Our results show that the proposed fully entangled circuit outperforms all other fully or linearly entangled circuits in addition to classical algorithms for most of the features. In fact, as the feature increases the efficiency of our proposed fully entangled model also increases significantly

Quantum-inspired attribute selection algorithm: A Fidelity-based Quantum Decision Tree

A classical decision tree is completely based on splitting measures, which utilize the occurrence of random events in correspondence to its class labels in order to optimally segregate datasets. However, the splitting measures are based on greedy strategy, which leads to construction of an imbalanced tree and hence decreases the prediction accuracy of the classical decision tree algorithm. An intriguing approach is to utilize the foundational aspects of quantum computing for enhancing decision tree algorithm. Therefore, in this work, we propose to use fidelity as a quantum splitting criterion to construct an efficient and balanced quantum decision tree. For this, we construct a quantum state using the occurrence of random events in a feature and its corresponding class. The quantum state is further utilized to compute fidelity for determining the splitting attribute among all features. Using numerical analysis, our results clearly demonstrate that the proposed algorithm cooperatively ensures the construction of a balanced tree. We further compared the efficiency of our proposed quantum splitting criterion to different classical splitting criteria on balanced and imbalanced datasets. Our simulation results show that the proposed splitting criterion exceeds all classical splitting criteria for all possible evaluation metrics

Determinants of Nutritional Status of Urban Slum Girls up to Two Years

Background: The prevalence of malnutrition is a significant area of concern in many developing countries, where it is a major public health problem.Objective: To estimate the prevalence of malnutrition and to find out association of malnutrition with some common variables amongst up to two years girls children.Material and Methods: Nutritional assessment was done using anthropometry and clinical examination. Children were weighed and measured as per the WHO guidelines on Anthropometry. Epi. Info 2002 software package was used to calculate the Z scores and for statistical analysis.Results: The study findings revealed that out of total 126 girls, more than half (53.2%) of the children studied were normal. Peak prevalence of malnutrition was observed in 1-2 years of age. Majority of the mothers of malnourished girls were illiterate (52.5%) and lower class (84.7%). More than half (52.2%) of the children were found normal who were on exclusive breastfed up to 6 months.Conclusions: The study found that malnourishment is linked with breast feeding practices, complementary feeding, literacy, socio-economic status, immunization status, looks (hygiene) and knowledge of mother about childhood illnesses, their treatment and family planning practices

Simple and Efficient Group Key Distribution Protocol using Matrices

Group Key Distribution (GKD) protocols are designed to distribute a group key to several users for establishing a secure communication over a public network. The central trusted authority, called the key distribution center (KDC) is in charge of distributing the group keys. For securing the communication, all the users share a common secret key in advance with KDC. In this paper, we propose a secure and efficient Group Authenticated Key Distribution (GAKD) protocol based on the simple idea of encryption in matrix rings. In this protocol, each user registers in private with the KDC, while all the other information can be transferred publicly. The scheme also supports authentication of group keys without assuming computational hard problems such as Integer Factorization Problem (IFP).The analysis of our GAKD protocol shows that the proposed protocol is resistant to reply, passive and impersonation attacks. Our construction leads to a secure, cost and computation- effective GAKD protocol

Clinical effectiveness of selective nerve root block in lumbar radiculopathy

Background: Epidural steroid injections (ESIs) have been used as an adjunct in the treatment of sciatica. Since the early reports, success rates ranging from 18% to 90% (average, 67%) have been documented. However, the efficacy of ESI has lasted, on the average, less than 3 months.Methods: This study was conducted at Abrol medical centre, Punjab from June 2019 to June 2020. One hundred patients with back pain documented with lumbar disc disease treated initially with rest, analgesics and physiotherapy for at least six weeks were included in the study and treated with transforaminal epidural steroid injection. The protocol of the study was approved by ethical committee. Patients to be participated in this study were documented. Patients with lumbar disc disease were given transforaminal epidural steroid injection in Orthopaedics operation theatre of our institute. Informed and written consent were obtained as per ethical committee guidelines.Results: Pre-procedure Roland Morris disability mean score was 17.54 and it got reduced to 5.57 by 4th day immediately post injection, was 6.44 by 6 weeks, by 3rd month 7.1 and by end of 6 months it was 8.34. Improvement in score on 4th day post injection was 68.24 percent which is considered significant and successful.Conclusions: Transforaminal epidural steroid treatment better medication for pain relief, patient satisfaction, disability improvement and functional improvement

EFFECT OF BALL MILLING ON PEAK CURRENT AND EQUIVALENT SERIES RESISTANCE OF METAL OXIDE BASED ELECTROCHEMICAL DOUBLE LAYER CAPACITOR

Recently, advances have been made in improving both energy and power density of energy storing devices. Electrochemical Double Layer capacitor (EDLC) is one of the technologies that we are looking forward to fulfill the low power- low energy applications such as memory back up. ELDC is mainly a pulse power device even though it is seen as a replacement to battery in low power applications. At present EDLC technology is under development stage. Power density, energy density, specific capacitance, internal resistances are required to be improved. Electrochemistry plays a crucial role in the storage as well as in the generation of energy. Hence, the particles size and distribution are need to be optimized. Ball milling is the tool for optimizing the size of the components used to make the EDLCs. Ball milling has significant effect on the various parameters of the EDLC. It was found that as we increase the time of ball milling the Equivalent Series Resistance (ESR) decreases and the peak current increases. But he changes are significant for higher time of ball milling