Analysis of Faces of Family Members Using Image Processing Techniques

The recognition of family members and maintenance of a strict vigil on the strangers in the households of urban area is a very vital and important problem, especially in densely populated metropolitan cities in India like Bangalore, Kolkata, Delhi, Bombay etc., where security is of a great concern as the home alone people are getting killed regularly. The scenario may not be different either in any other business cities of neighboring countries. Through this paper, we would like to throw light on how one can establish a relation between the members of family

A Surveyon Detection of Reviews Using Sentiment Classification of Methods

Merchants selling products on the Web often ask their customers to review the products that they have purchased and the associated services. As e - commerce is becoming more and more popular, the number of customer reviews that a product receives grows rapidly. For a popular product, the number of reviews can be in hundreds or even thousands. This makes it difficult for a potential customer to read them to make an informed decision on whether to purchase the product. It also makes it difficult for the manufacturer of the product to keep track and to manage customer opinions. As the numbers of customers are growin g, reviews received by products are also growing in large amount. Thus, mining opinions from product reviews is an important research topic. In the fast decade considerable research has been done i n academia. However, existing research is more focused towa rds categorization and summary of such online opinions. In this paper we survey various techniques to classify opinion as positive or negative and also detection of reviews as spam or non - spam

Radio Resource Allocation in Cellular V2X: From Rule Based to Reinforcement Learning Based Approaches

The wireless communication technology has gained significant attention in the transportation industry over the recent years. Cellular Vehicle-to-Everything (V2X) communication facilitates the information exchange among road users (such as vehicles, pedestrians etc.) and the infrastructure with an intention to improve the overall road safety, driving comfort, traffic efficiency and save energy. Advanced use-cases aim towards enhancing key functionalities of vehicle automation by means of sensor data sharing and cooperative maneuver & trajectory planning. The introduction of the PC5 interface for sidelink (SL) communication within the mobile communication systems, supports direct exchange of messages between users, independent of the cellular network infrastructure. Two types of radio resource allocation modes are supported in Cellular V2X: managed mode and the unmanaged mode. In the managed mode, a User Equipment (UE) remains connected to the cellular network and the process of resource allocation is coordinated by the base station. In the unmanaged mode, a UE selects its radio resources from a pre-configured resource pool without any assistance from the base station. Originally both these modes were developed by considering that the vehicles exchange periodic messages which are safety-critical in nature. The existing rule based radio resource allocation algorithms in both the modes are unable to adapt their selection parameters in the events of aperiodic data traffic patterns resulting from the diverse generation rules of different V2X messaging protocols. We begin this PhD thesis by carrying out system level network simulations within the developed framework Artery-C, where we study the metrics and parameters that influence the performance of the rule-based radio resource allocation in the sidelink modes. In the first step, we derive the baseline conditions where each mode performs to its best efficiency. By varying the generation rules of the messaging protocols, we further analyze the behavior of the modes when V2X data traffic does not follow a specific pattern. Our studies have shown that both the modes suffer from frequent re-allocations because the messages are no longer periodic and the data sizes do not fit into the previously allocated radio resources. This results in poor utilization of the allocated resources. The unmanaged mode is particularly susceptible to radio resource collisions because the vehicles only have partial awareness about the resource selection decisions of other road traffic participants. As a second contribution, we examine the criteria for sidelink mode selection and the possibilities for a mode switching operation within the sidelink modes and also between the sidelink and the cellular (Uu) modes. We have formulated the strategies for mode switching and calculate the latency in each phase of the mode switch procedure. Although the managed mode has shown advantages with regard to allocation and management of radio resources, it is to be noted that a vehicle cannot remain connected to a base station at all instants of time. Also, switching between different modes is not seamless considering the associated latencies in each phase. This leads us towards the goal of improving the efficiency of the allocation & scheduling of radio resources in the unmanaged mode. After a careful review of the enhancements that can be implemented within the rule based algorithm in the unmanaged mode, it was found that there needs to be a mechanism where vehicles can continuously share their resource selection decisions, adapt their selection parameters and even re-evaluate them (if needed) within a grant period. Therefore, we investigated the Reinforcement Learning (RL) based Artificial Intelligence (AI) approaches that facilitate independent learning, adapting and decision making among spatially distributed vehicular agents. We have developed a fully de- centralized multi agent networked Markovian Decision Process (MDP) model of the Cellular V2X communication network where each agent executes an AI based radio resource scheduler. By extending the actor-critic methodology of the RL, we have derived two variants - Independent Actor Critic (IAC) and Shared Experience Actor Critic (SEAC). The results of our evaluations have indicated that both these schedulers have a potential to achieve better radio resource utilization with a reduced risk of radio resource collisions among the agents. Subsequently, it brings about 15 − 20% improvement in the reliability of the communication link which we regard as a valuable contribution. To summarize, this PhD thesis investigates the performance of the rule based radio resource allocation algorithms in Cellular V2X and proposes the qualitative improvements that can be achieved by means of reinforcement learning

Applying Machine Learning Techniques to Categorize and Reduce Stress in Human Beings

The number of individuals in the modernworld experience elevated stress level, which is non-specific response on the body and plays a significant toll on health, productivity at work, relationships and also effect overall well-being. Many individuals are not aware of the stress triggers and potential health problems caused by prolonged stress. In order to effectively combat stress and its ill effects on health, stress triggers and responses to stress must be recognized and managed in real time. In this paper, applications of machine learning techniques are suggested to categorize and reduce stress is explored. The idea of monitoring stress and reducingstress usesmethods like personalized music, wallpaper themes, favorite games or favorite food ordering and so on. Activities which reduce stress and their degree of reduction are monitored in real time and based on customized stress reduction portfolio is designed using machine learning algorithms

Studies on electrodeposited Zn-Fe alloy coating on mild steel and its characterization

Chloride bath containing ZnCl2 ∙7H2O, FeCl2 ∙H2O and a combination of sulphamic acid and citric acid (SA+CA) were optimized for electrodeposition of bright Zn-Fe alloy coating on the mild steel. Bath constituents and operating parameters were optimized by the Hull cell method for highest performance of the coating against corrosion. The effect of current density and temperature on deposit characteristics such as corrosion resistance, hardness, thickness, cathode current efficiency and glossiness, were studied. Potentiodynamic polarization and electrochemical impedance spectroscopic (EIS) methods were used to assess corrosion behaviour. Surface morphology of coatings was examined using scanning electron microscopy (SEM). The Zn-Fe alloy with intense peaks corresponding to Zn (100) and Zn (101) phases, evidenced by X-ray diffraction (XRD) study, showed the highest corrosion resistance. A new and economical chloride bath for electrodeposition of bright Zn-Fe alloy coating on mild steel was proposed and discussed

Screening of gestational diabetes mellitus in antenatal women using DIPSI guidelines

Background: GDM is associated with serious maternal as well as fetal complications, which can be prevented by early detection & prompt treatment. There is need of universal screening of all Indian pregnant women for GDM using simple & economical screening criteria. This study uses single step OGTT as per DIPSI guidelines to find out prevalence of GDM in pregnant women attending antenatal OPD.Methods: All the antenatal patients at 24-28 weeks of gestation (n = 352), attending Antenatal OPD, irrespective of their prandial state were given 75 gm glucose and venous blood samples were collected after 2 hours of oral glucose. A report of ≥140 mg% were labeled as GDM as per DIPSI guidelines.Results: Out of 506 subjects screened, 33 (6.52 %) were positive for GDM.Conclusions: Low prevalence of GDM may be because of less sensitivity of DIPSI criteria

Apigenin inhibits PMA-induced expression of pro-inflammatory cytokines and AP-1 factors in A549 cells

Acute and chronic alveolar or bronchial inflammation is thought to be central to the pathogenesis of many respiratory disorders. Cytokines and granulocyte macrophage colony-stimulating factors (GM-CSF) play an important role in chronic inflammation. Activator protein-1 (AP-1) the superfamily of transcription factors is involved in proliferation, differentiation, apoptosis, and transformation including inflammation. Understanding the function and regulation of proinflammatory factors involved in inflammation may provide the novel therapeutic strategies in the treatment of inflammatory diseases. Our aim of the present study is to investigate the pro-inflammatory cytokines and pattern of AP-1 factors expressed during activation of lung adenocarcinoma A549 cells by Phorbol-12-myristate-13-acetate (PMA) and to understand the anti-inflammatory effect of apigenin. A549 cells were treated with and without PMA or apigenin, and the cell viability was assessed by MTT assay. Expressions of inflammatory mediators and different AP-1 factors were analyzed by semi-quantitative RT-PCR. IL-6 protein secreted was analyzed by ELISA, and expressions of IL-1β, c-Jun, and c-Fos proteins were analyzed by Western blotting. Activation of A549 cells by PMA, induced the expression of pro-inflammatory cytokine (IL-1β, IL-2, IL-6, IL-8, and TNF-α) mRNAs and secretion of IL-6 and the expression of specific AP-1 factors (c-Jun, c-Fos, and Fra-1). Treatment of cells with apigenin, significantly inhibited PMA-stimulated mRNA expression of above pro-inflammatory cytokines, AP-1 factors, cyclooxygenase-2, and secretion of IL-6 protein. Results suggested that the AP-1 factors may be involved in inflammation and apigenin has anti-inflammatory effect, which may be useful for therapeutic management of lung inflammatory diseases. © 2015, Springer Science+Business Media New York

Preparation of Silver Decorated Reduced Graphene Oxide Nanohybrid for Effective Photocatalytic Degradation of Indigo Carmine Dye

Background: Even though silver decorated reduced graphene oxide (Ag-rGO) shows max- imum absorptivity in the UV region, most of the research on the degradation of dyes using Ag-rGO is in the visible region. Therefore the present work focused on the photocatalytic degradation of indigo carmine (IC) dye in the presence of Ag-rGO as a catalyst by UV light irradiation. Methods: In this context, silver-decorated reduced graphene oxide hybrid material was fabricated and explored its potential for the photocatalytic degradation of aqueous IC solution in the UV region. The decoration of Ag nanoparticles on the surface of the rGO nanosheets is evidenced by TEM analysis. The extent of mineralization of the dye was measured by estimating chemical oxygen demand (COD) values before and after irradiation. Results: The synthesized Ag-rGO binary composites displayed excellent photocatalytic activity in 2 Χ 10-5 M IC concentration and 5mg catalyst loading. The optical absorption spectrum of Ag-rGO showed that the energy band-gap was found to be 2.27 eV, which is significantly smaller compared to the band-gap of GO. 5 mg of Ag-rGO was found to be an optimum quantity for the effective degrada- tion of IC dye. The degradation rate increases with the decrease in the concentration of the dye at al- kaline pH conditions. The photocatalytic efficiency was 92% for the second time. Conclusion: The impact of the enhanced reactive species generation was consistent with higher pho- tocatalytic dye degradation. The photocatalytic mechanism has been proposed and the hydroxyl radi- cal was found to be the reactive species responsible for the degradation of dye. The feasibility of reus- ing the photocatalyst showed that the photocatalytic efficiency was very effective for the second tim

COMPARATIVE STUDY ON EFFECT OF SLOW AND FAST PHASED PRANAYAMA ON QUALITY OF LIFE AND PAIN IN PHYSIOTHERAPY GIRLS WITH PRIMARY DYSMENORRHOEA: RANDO-MIZED CLINICAL TRIAL

Objective: Few studies have been done on pranayama as therapy to improve pain and quality of life for primary dysmenorrhoea. Hence, this study is aimed at understanding the effect of slow and fast pranayama on primary dysmenorrhoea among Physiotherapy girl students. Methods: Unmarried girls (n=90) under the age group of 18-25 with primary dysmenorrhoea were randomly assigned to the study, Group A (n=45) Group B (n=45). Moos menstrual distress questionnaire (MMDQ), Numerical pain rating scale for pain, Quality of life scale by American chronic pain association were administered at baseline, after 1 st menstrual cycle and follow-up after 2 nd menstrual cycle. Group A was subjected to slow pranayama (Nadi Shodhan) and Group B was subjected to fast pranayama (Kapalbhati). Result: Significant (P<0.0001) improvement in quality of life and pain scores after intervention was seen in Group A (Nadi Shodan) as compared to Group B (Kapalbhati) . Prevalence of Primary Dysmenorrhoea was found to be high between the age group of 18-22. Conclusion: With Slow pranayama (Nadi Shodhan) the quality of life and pain scores improved when compared to Fast pranayama (Kapalbhati) indicating the benefits of Slow pranayama on Primary Dysmenorrhoea. Pranayama improves quality of life and reduces absenteeism and stress levels, so it should be implemented in college students to augment their menstrual wellbeing and should be inculcated as a routine practice to improve quality of life