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Domestic water purifiers (WPs) are becoming very popular for refining drinking water in the home. There is no disputing that water becomes scarce, and available water sources are under significant strain. Even though most groundwater resources are readily polluted, it is vital to have a water filter at home. When it comes to water filtration, RO water purifiers are fantastic. This analysis presents a simple multi-criteria decision-making (MCDM) methodology based on the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method to choose a household water purifier (WP). The importance of weights was calculated using the Entropy weight method (EWM) considering objective preferences. The TOPSIS-Entropy technique was used to determine the ranking order. The findings revealed that MCDM approaches for selecting WPs are beneficial. The study’s peculiarity is that it uses TOPSIS-Entropy MCDM approaches to prioritize WP selection.

Interpretive Structural Modelling (ISM) is one of the most widely used techniques in identifying the complex structural relationship between various elements. It is commonly used in multiple disciplines but hardly explored its all-encompassing scientific productivities. Hence, this paper has endeavoured to scrutinize 1480 documents using the ISM technique from 2000 to 2020 in the Scopus database. A systematic two-tier approach comprising bibliometric analysis and visualization review has been made with VOSviewer and Biblioshiny software. Extensive data mining has been done to collect required information with certain filters containing document type, language, author, subject, publication status, source title, affiliation, country, and source type. The study has generated information regarding ISM documents, their types, publications, citations, and predictions. The citation analysis is used to ascertain the most prolific and dominant authors, sources, articles, countries, and organizations. The author-keywords, index-keywords, and text data content analysis is conducted to find ISM's hotspots and progress trends. The study has found a rapid exponential pace in annual publications using the ISM technique since 2000. The most prolific and dominant articles based on total citation include Diabat and Govindan, 2011; the top source is the Journal of Cleaner Production. The chief author is Shankar R., the leading organization IIT New Delhi, India, and the leading country is India. The study has explored many research hotspots and less explored areas using ISM techniques. The present research is the first paper that has utilized bibliometric analysis to analyze the ISM publications widely. This bibliometric review has further contributed to the ISM technique, usability, and exploitation areas and future scope for scholars working in this area through its research hotspots and valuable findings.

In engineering applications, such as automobile, marine, aerospace, and railway, lightweight alloys of aluminum (Al) and magnesium (Mg) ensure design fitness for fuel economy, better efficiency, and overall cost reduction. Friction stir welding (FSW) for joining dissimilar materials has been considered better than the conventional fusion welding process because of metallurgical concerns. In this study, dissimilar joints were made between the AA6061 (A), AZ31B (B), and AZ91D (C) combinations based on the varying advancing side (AS) and retreating side (RS). The dissimilar joints prepared by the FSW process were further characterized by tensile testing, impact testing, corrosion testing, fracture, and statistical and cost analysis. The results revealed a maximum tensile strength of 192.39 MPa in AZ91 and AZ31B, maximum yield strength of 134.38 MPa in a combination of AA6061 and AZ91, maximum hardness of 114 Hv in AA6061 and AZ31B, and lowest corrosion rate of 7.03 mV/A in AA6061 and AZ31B. The results of the properties were supported by photomicrographic fracture analysis by scanning electron microscopy (SEM) observations. Further, the performance of dissimilar joints was statistically analyzed and prioritized for preference by similarity to the ideal solution (TOPSIS) method.

Political Marketing is a recent phenomenon, gaining importance quickly around the world. Politicians and their political parties are using a large number of strategies to attract and retain the voters. The present study has made an attempt to understand the perception of voters toward various political marketing strategies adopted by various politicians in India. The study has empirical research design with non-probability sampling techniques. A survey of registered voters was made; their perceptions were recorded and analyzed with various statistical tools like Garrett ranking, exploratory factor analysis, confirmatory factor analysis, structural equation modelling and path diagram. The study has derived three major factors viz. direct political marketing, relationship political marketing and transactional political marketing influencing the perception of voters toward various strategies adopted by Indian Politicians. The study has been able to frame a hypothetical model for these strategies. At the last, the study has also felt the need of further studies in this direction. Keywords: Political marketing, Strategy, Perception, Voters, India.

A research is an intellectual system, the vehicular adhoc network (VANET), supplies cars in the network with critical information. Over 150,000 individuals are impacted by traffic accidents that must be kept to a minimum, and the development of safety must be included in VANET. Traffic congestion prediction is critical to mitigating car accidents and managing traffic for the benefit of all road users. The cars in the system exhibit dynamic behavior, which adversely affects the performance of deep learning approaches for congestion of traffic prediction. In this article a hybrid approach named boosted long short-term memory ensemble (BLSTME) as well as convolution neural network (CNN) is develop to help cars navigate around congested roads by giving CNN's powerful features access to BLSTME, which helps cars in dynamic environments by forecasting the likelihood of congestion. In order to forecast traffic congestion, CNN collects traffic attribute pictures, as well as suggested BLSTME trains. It also improves classifiers that are weaker. Tensor Flow libraries were used to build the model, which was then evaluated in the actual world in a simulated scenario created using the open source software SUMO and the proprietary software OMNeT++. After several trials, various tests, and evaluations, the experiment's results are analyzed, and the model's predictions are then evaluated using relevant metrics such probable accuracy, precision, as well as recall. Thus, the experimental result indicates that the hypothesis has been proven correct with a degree of accuracy, precision, and recall of 98%, 96%, and 94% respectively. The model outperforms current methods by providing 10% better stability and performance.

This paper presents a number of novel approaches to help facilitate Deep Reinforcement Learning (DRL) for Neural Networks based agents in the domain of General Video Game Playing (GVGP). Using common processing methods, the NN can retain a fixed predetermined input and output shape while having the flexibility to play a variety of games. Training can also be made more efficient via reward normalization. Our results show that these modifications negligibly impact the learning time and performance of the model when testedupon games in the GVGAI framework. Furthermore analysis of these approaches within the parameters of the GVGAI learning competition was also performed. This research work attempts to use the adaptations presented to train an agent thatwill compete in the CEC2019 GVGAI Learning Competition.

Green Human Resources Management (GHRM) is an alignment of traditional human resource practices such as strategies, policies, procedures, and rules to the latest green and sustainable environment responsive practices. Unlike corporates, the adoption of GHRM in educational institutes (EIs) is still in its infancy stage. Through an extensive literature survey, this study identified eleven challenges in adopting the GHRM “strategy”, ten on “policy”, nine on the “procedures”, and eight on framing the GHRM “rules” aspect. The aim is to identify and develop the relationship between major and minor challenges in adopting GHRM practices in EIs. Hence, this study has applied the Interpretive Structural Modelling (ISM) technique to each GHRM practice and developed interrelation among such challenges and results verified with Analytic Hierarchy Process (AHP). The rankings of both techniques have been statistically verified with the Spearman Rank Correlation technique. The study concludes the lacking or insufficient considered four main pillars: clear vision and top management cooperation among these EIs to ensure sustainable GHRM practices from the strategy aspect perspective, benchmark in fixing accountability considering the policy aspect, suitable course curricula in universities focused on GHRM practices from procedural viewpoint, and transparency in EIs from the perspective of rules as significant challenges in GHRM adoption. The findings of the reported results can be further extended in cross-sectional and cross-cultural studies in further studies.

Just after the COVID-19 pandemic, a national lockout is initially enforced in India from March 24 to April 14, 2020, for three weeks and prolonged until May 31, 2020. Because of the mandatory restrictions, emission levels across the country decelerated dramatically during the first very few days. In this paper, the air quality index (AQI) of Ludhiana city, Punjab, has been investigated during the pre- and post-lockdown period. The air quality data of pollutant parameters (PM10, PM2.5, SO2, NO2, CO, O3, and NH3) has been collected from authorized Punjab Agriculture University (PAU), Ludhiana monitoring station of National Air Quality Index (NAQI). A descriptive statistics analysis was applied to check the acceptance level of six significant parameters, including AQI. The sample data was then analyzed using correlation and paired sample t-test to find out the significant level of each parameter under consideration. The results showed that air quality has significantly improved during the lockdown. The paper has suggested adopting such forced periodic alternatives soon to clean the environment.

Due to rapid growing of digital video, it was very complicated task for storing, processing and transferring a sequence of video. Motion Estimation (ME) is a primary tool for video compression. This paper comprises new pattern i.e. rectangular search pattern used in place of diamond search pattern in block-based motion estimation algorithm. The performance can be measured in terms of number of points searching in searching area per macro-block and quality of video by using PSNR value.

This paper presents FPGA implementation of retimed high speed adaptive filter structures for speech enhancement. In this work, various high speed adaptive filtering structures for noise cancellation are implemented for Xilinx Spartan-6 series and Virtex-4 series FPGA platforms. It has been observed that various VLSI implementations vary considerably in clock speed, hardware requirements, latency and cost. For instance, for the Spartan-6 series FPGA platform implementation, the clock speed of retimed DF-RDLMS implementation is found to be 98.309 MHz whereas that of conventional unretimed DF-LMS structure is 85.485 MHz, thereby having an improvement of 15% in clock speed. Similarly, for the Virtex-4 series FPGA platform implementation, the clock speed of retimed DF-RDLMS implementation is found to be 88.176 MHz whereas that of conventional unretimed DF-LMS structure is 75.855 MHz, thereby having an improvement of 16.5% in clock speed. The VLSI implementation and the performance analysis provides crucial information about an algorithm structure such as hardware requirements, power consumption and real-time performance. Performance of the implemented structures have been checked in terms of operating frequency, maximum combinational path delay, latency, and power consumption.

In this paper, the influence of different variables such as calcination temperature of MgO, purity of MgCl2, quantity and concentration (on Baume scale) of MgCl2 solution, quantity and type of inert filler material (sands) on the performance in terms of flow, compressive strength, and flexure strength of magnesium oxychloride cement (MOC) were evaluated. The strengths developed at 1, 3, and 7-day were used to analyze the influences. The study reveals that the degree of calcination of MgO, the concentration of MgCl2 solution (°Be), fineness of inert material, are the key factors controlling strength development in MOC. The study further suggests that the purity of MgCl2 has insignificant influence on strength development in MOC.

Industrial alarm systems are very critical for the efficient and safe operation and control of plants. Alarms are used to inform the operator about possible process deviations from the normal so that the operator can take appropriate corrective action. Alarm activation and the corresponding response from the operator together serve as one of the critical layers of protection during the occurrence of a process fault. With the rapid advancement in control systems technology over the past few decades, the number of process sensors deployed for a particular plant has dramatically increased. In addition, due to the ease in configuring the alarms in control systems, the number of alarms in a plant has also gone up. This has led to poor system performance, increase in the operator workload due to alarm overload, and catastrophic incidents in some cases. This review paper discusses such issues, provides details about the existing regulations, standards and guidelines, and challenges related to alarm management. In addition, it summarizes some of the open research problems in the area of effective alarm management.

The study explores the association between severity of illness (positive, negative, depressive and cognitive symptoms) and extra pyramidal symptoms (EPS) with dental caries, periodontal disease and prosthetic needs among patients with schizophrenia.A total of 71 schizophrenic patients diagnosed based on ICD-10 criteria participated in the study. Clinical Global Impression - Schizophrenia (CGI-SCH) scale was used to evaluate positive, negative, depressive, cognitive symptoms and overall severity of schizophrenia. Simpson-Angus Scale (SAS) was used for assessment of EPS. Dental examinations were conducted as per WHO (1997) criterion.Mean DMFT and CPI scores with periodontal pockets were 5.57 ± 2.12 and 2.37 ± 0.74; significant differences being noted among those with and without EPS (p 0.001). Positive and EPS associated with dental caries with odds ratio of 5.26 (1.05, 26.2) and 8.52 (2.31, 31.4) (p 0.001). Depressive and EPS were associated with periodontal disease with odds ratio of 4.19 (1.53, 32.5) and 5.27 (1.29, 21.5), respectively (p 0.001). Cognitive and EPS were associated with dental prosthetic needs with odds ratio of 4.33 (1.47, 31.2) (p 0.001) and 7.78 (1.43, 42.2), respectively (p 0.001).Patients with schizophrenia had high dental caries, periodontal disease and unmet dental prosthetic needs. Severity of the schizophrenic and EPS was associated with poor oral health. Efforts need to be focused on strengthening the evidence of its association with oral health indicators through further studies including cohort investigations.

In an environment where noise is our constant companion, quality of speech signal degrades considerably. Over a period of time, researchers have developed and implemented many algorithms to enhance the quality of speech signal. In this article, an attempt is made to present the significant work of researchers in the area of Field-Programmable Gate Arrays (FPGA) implementation of noise cancellation algorithms using adaptive filters. FPGA based hardware platforms have been commonly used to implement prototypes for active noise canceller (ANC) systems. The commonly used software tools for FPGA based implementations include MATLAB/Simulink, Modelsim, Xilinx System Generator, Xilinx ISE, Vivado design suite, and Altera Quartux II development platform. The performance of the algorithms achieved using FPGA based platforms give an insight of what may be achieved from the final commercial implementation. In this study, it has been observed that the performance of various adaptive filter structures varies considerably in terms of rate of convergence, throughput rate, improvement in signal-to-noise ratio (SNR), maximum clock speed, hardware complexity, power consumption and cost.

The use of dental hand pieces endanger dentists to vibration exposure as they are subjected to very high amplitude and vibration frequency. This paper has envisaged a comparative analysis of vibration amplitudes and transmissibility during idling and drilling with micro motor (MM) and air-turbine (AT) hand pieces. The study aims to identify the mean difference in vibration amplitudes during idling, explore different grasp forces while drilling with irrigant injection by the dentist, and various vibration transmission of these hand pieces. The study utilized 22 separate frequency resonances on two new and eight used MMs and two new and eight used ATs of different brands by observing the investigator at 16 different dentist clinics. The study adopted a descriptive research design with non–probability sampling techniques for selecting dentists and hand pieces. Statistical methods like Levene Test of Homogeneity, Welch ANOVA, independent t-test, and Games–Howell test were utilized with SPSS version 22 and MS-Excel. The results reveal that vibration amplitudes and vibration transmissibility when measured at position 2 are higher than in another position 1. Vibrations during idling for used MMs are more than AT hand pieces, and the used MM (MUD) and used AT (AUA) hand pieces differ due to their obsolescence and over-usage. Vibration amplitudes increase every time with the tightening of grasping of the hand piece. Vibration amplitudes for each grasping style of MM hand piece differ from all other grasping styles of AT hand pieces. Routine exposure to consistent vibrations has ill physical, mental, and psychological effects on dentists. The used hand pieces more hazardous as compared to newer ones. The study suggests that these hand pieces must be replaced periodically, sufficient to break between two operations, especially after every hand piece usage. Hence, the present research work can be further extended by creating some control groups among dentists and then studying the vibration amplitude exposure of various dental hand pieces and subsequent transmissibility to their body parts.

Emerging sensors, computers, network technologies, and connected platforms result potentially in an immeasurable collection of data within plant operations. This creates the possibility of solving problems innovatively. Because most of the data appear to be unstructured or semi-structured, organizations shall design and adopt new strategies. Further, workflow architectures with data analytics are needed including machine learning tools and artificial intelligence techniques before proto-type solutions can be developed. We shall discuss several prospects of using (big) data analytics integrated with cloud services to produce solutions for improving plant operations. The paper outlines the vision and a systematic framework highlighting the data analytics lifecycle in the area of plant operation, process safety, and environmental protection. Four rather diverse example case studies are demonstrated including (1) deep learning-based predictive maintenance monitoring modeling, (2) Natural Language Processing (NLP) for mining text, (3) barrier assessment for dynamic risk mapping (DRA), and (4) correlation development for sustainability indicators. It further discusses the challenges in both research and implementation of proposed solutions in the industry. It is concluded that a well-balanced integrated approach including machine supporting decisions integrated with expert knowledge and available information from various key resources is required to enable more informed policy, strategic, and operational risk decision-making leading to safer, reliable and more efficient operations.

Prosthetic valve implantation requires postoperative prophylactic anticoagulation to preclude thrombotic events. The aim of this review is to assess the role of anticoagulation therapy in the management of valve replacement patients.Literature from PubMed, Embase, Medline and Google Scholar were searched using the terms "valvular heart disease", "anticoagulant", "mechanical heart valve", "bioprosthesis", "bridging", "Vitamin K antagonist (VKA)", and "acenocoumarol". A committee comprising leading cardiothoracic surgeons from India was convened to review the literature and suggest key practice points.Prosthetic valve implantation requires postoperative prophylactic anticoagulation to preclude thrombotic events. A paramount risk of thromboembolic events is observed during the first three months after surgery for both mechanical and bioprosthetic devices. The VKA therapy with individualized target international normalized ratio (INR) is recommended in patients after prosthetic valve replacement. Therapies for the management of prosthetic valve complications should be based on the type of complications. Special care is mandated in distinguished individuals and those with various co-morbidities.In patients with prosthetic valve replacement, anticoagulant therapy with VKA seems to be an effective option. The role for non-VKA oral anticoagulants in the setting of prosthetic valve replacement has yet to be established. Furthermore, whether the novel oral anticoagulants are safe and efficacious in patients after placement of a bioprosthetic valve remains unanswered.

Context: Transgenders are highly disadvantaged people, deprived of adequate opportunities of earning a respectable living. The forensic literature has emphasized on two genders, male and female, the existence of a third gender (Transgenders) is almost negligible in the literature, and this makes it compulsive to determine their identity through forensic approaches at the time of disasters. Previous studies have demonstrated that no two palatal rugae pattern are alike in their configuration and this unique feature has led us to undertake a study to establish individual identities using palatal rugae pattern. Aims: The purpose of this study was to compare the palatal rugae pattern among male, female, and transgender population of the Bhopal city. Settings and Design: This study was cross sectional in nature and conducted on a convenience sample of 148 subjects selected from Bhopal city, Madhya Pradesh. The study involved 49 males, 51 females, and 48 eunuchs in the age range of 17 to 35 years. Materials and Methods: Maxillary impression using alginate impression material was made and the cast was prepared using die stone on palatal area and dental stone as a base. The palatal rugae pattern was assessed on the basis of number, length, shape, direction, and unification. Statistical Analysis Used: One way ANOVA was used for comparing the mean values between different genders. The multiple pairwise comparisons were done with the Bonferroni post hoc correction. The statistical significance was fixed at 0.05. Results: The statistically significant difference with regard to some parameters like number of rugae, fragmentary rugae, wavy rugae, curve rugae, forwardly directed, and backwardly directed rugae between transgender and other gender groups were present. Conclusion: The difference in the parameters of the palatal rugae pattern among the transgender population and the other gender group is attributed to be the genetic makeup and sexual dimorphism.

In recent years, there has been an increasing interest in the field of big data analytics. It has been established that there exist large amounts of data in the energy industry1. However, there is a need to develop methods combining domain knowledge to transform this data into meaningful information to return business intelligence. The existing literature on big data analytics focuses on applications in various fields such as healthcare, aviation industry, finance, energy industry, and supply chain. However, within the energy industry, the application of big data analytics in process safety and risk management is in the nascent stages. The objective of this study is to discuss the potential of big data analytics in the area of process safety and risk management in the energy industry. The paper outlines the systemic framework with different stakeholders, data sources, challenges, and discusses the benefits of big data analytics in process safety. Four case studies with different applications ranging from incident database analysis, predictive modeling for pump failures, dynamic risk mapping of operating plant, and image analysis to gain insights are demonstrated. It is concluded that the application of big data analytics would provide valuable insights for more informed policy, strategic, and operational risk decision-making leading to a safer and more reliable industry.

Objective: To assess the antimicrobial efficacy of the aqueous and ethanolic extracts of Triphala at various concentrations against primary plaque colonizers. Materials and methods: Preparation of the herbal extracts for this in vitro study was done using cold infusion method. Ethanol and Millipore water were used as solvents for extraction. The stock solution was prepared by adding 1000 mg of dried extract in one ml of dimethyl sulfoxide (DMSO). The stock solution was further diluted to obtain 6.25%, 12.5%, 25% and 50% concentrations of the extract. The antimicrobial efficacy testing of Triphala extracts against these bacteria was done by agar well diffusion method. 0.2% chlorhexidine was used as positive control while DMSO acted as negative control. One way Analysis of Variance and independent sample t-test were used for comparing mean diameter of inhibition zones. Results: All the concentrations of ethanolic and aqueous extracts of Triphala inhibited the growth of S. mutans, S. sanguis and S. salivarius. In general, the efficacy increased with increasing concentration with maximum inhibition at 50% concentration. There was no statistically significant difference in the mean diameter of inhibition zone between the ethanolic and aqueous extracts of triphala against S. mutans. Conclusion: Both aqueous and ethanolic extracts of Triphala have the potential to be used antiplaque agents. Key words: Antimicrobial efficacy, Triphala, Minimum Inhibitory Concentration (MIC), Dental caries, S. mutans, periodontal diseases.

Objective: This study evaluated the ability of 30% ethanolic extract of Indian propolis on dentinal tubule occlusion comparatively against CPP-ACP containing desensitizing agent GC tooth mousse. Methodology: The specimens were prepared from 30 freshly extracted sound human third molars stored in 10% formalin (pH 7.0) at a room temperature. From each specimen, a sectioned sample (5 mm length × 5 mm width × 3.5 mm depth) was obtained including the cervical area. Samples were smoothened and wet-polished with 1000- and 1200-grit aluminum oxide abrasive paper and diamond pastes, in order to stimulate the clinical aspect of hypersensitive dentin cervical surfaces. All the specimens were randomly assigned to three groups (n = 10), according to dentin surface treatments. Negative control: Untreated specimens (n = 4) and pretreated with 6% citric acid (n = 6); Test Group: 30% ethanolic extract of Indian propolis (n = 10); Positive Group: GC Tooth Mousse (n =10). All the specimens were prepared for SEM analysis. Results: GC tooth mousse promoted tubule occlusion by crystal-like deposits in the lumen of the tubules. While propolis created a thin, smooth layer over dentin surface. Conclusion: According to the SEM analysis, both desensitizing agent were able to occlude the dentinal tubules.

Objective: The aim of this study was to compare the anti-plaque efficacy of a low and high cost commercially available tooth paste among 13-20 years old adolescents in a Residential Home, Bhopal, India. Materials and Methods: The study was randomized double-blind parallel clinical trial conducted in a Residential Home, Bhopal, India. A total of 65 patients with established dental plaque and gingivitis were randomly assigned to either low cost or high cost dentifrice group for 4 weeks. The plaque and gingival scores at baseline and post-intervention were assessed and compared. Statistical analysis was performed using paired t-test and the independent sample t-test. The statistical significance was fixed at 0.05. Results: Results indicated a significant reduction in plaque and gingival scores in both groups post-intervention compared with the baseline. Difference between the groups was not significant. No adverse events were reported and both the dentifrices were well-tolerated. Conclusion: Low cost dentifrice is equally effective to the high cost dentifrice in reducing plaque and gingival inflammation.

Background: The current cross-sectional questionnaire survey was conducted to assess the oral health-related knowledge, attitude and practices among eunuchs (hijras) residing in Bhopal city, Madhya Pradesh, India. Materials and Methods: Based on a convenient non-probability snow ball sampling technique, all the self-identified eunuchs residing in the city of Bhopal who were present at the time of study and who fulfilled the selection criteria were approached. A cross section of the general population was also surveyed. An interviewer-based, predesigned, structured, close-ended 18-item questionnaire that had been designed based on the primary objective of the study was used. All the obtained data were analyzed using software, Statistical Package for Social Science version 20. Results: According to 188 (86.2%) males, 187 (87.4%) females and 168 (81.2%) eunuchs, good oral health can improve the general health. Most of the study participants including 211 (98.6%) females, 210 (96.3%) males and 205 (99%) eunuchs use either tooth paste or tooth powder to clean their teeth. While, a majority of eunuchs, i.e., 113 (54.6%), were having habit of chewing smokeless tobacco containing products such as betel nut, betel quid, gutkha, etc., The difference in use of tobacco products was statistically significant. Conclusion: The information presented in this study adds to our understanding of the common oral hygiene practices which are performed among eunuch population. Efforts to increase the awareness of oral effects of tobacco use and to eliminate the habit are needed to improve oral and general health of this population.

Industrial systems are monitored and controlled by sensors and actuators. The signals from these instruments are mostly configured as alarms in the control system which alerts the plant operators in case of an abnormal process event. A higher number of alarms appearing on the operator screen signifies poor system performance and results in additional workload on the operators and may lead to abnormal situations. These situations can further escalate to a catastrophic incident if not managed properly. There are several solutions available to address the challenges related to the alarms and their management as a part of alarm management life-cycle process defined in industrial standards and guidelines. With the advent of Open Process Automation (OPA) concept and requirement of Real-time Operational Technology (OT) services there is a need to develop solutions based on open source software platforms. To address this, an alarm management framework is proposed, that integrates the alarm management life-cycle concept provided in ANSI/ISA-18.2 with data mining and analysis methods applied on alarm and event logs generated from a control system. The framework involves four distinct levels - design, rationalize, advance, and intelligent. A methodology to benchmark an alarm system by calculating Key Performance Indicators (KPIs) is formulated, results are obtained and shown visually by designing a tool using an open source software platform (R and Python). With the use of data mining and analysis, the methodology/tool benchmarks the system for the defined metrics for alarm systems as KPIs, identifies the bad actors, provides insights about the alarm system to manage the alarm flooding. We use the results to address the key issues and thereby improve the overall efficiency of the alarm system. A historical real industrial Alarm and Event (A&E) log data-set is used as an example to demonstrate the potential application of the proposed alarm management tool, to arrive at reliable decision, contributing to better alarm management and safer operations.

Objective: The aim of this study is to evaluate the efficacy of 30% ethenolic extract of Indian propolis compared with Recaldent TM (casein phosphopeptide-amorphous calcium phosphate) in reduction of dentinals hypersensitivity, a randomized, double-blind, split mouth, controlled clinical trial was conducted among the patients residing in Central Jail. Materials and Methods: A sample of 73 teeth from 13 patients having at least three teeth with dentinal hypersensitivity (DH) were randomly allocated into three treatment groups: Group A: 30% ethenolic extract of Indian propolis, Group B: Recaldent TM , Group C: Sterile water. Verbal rating scale was used to record the degree of hypersensitivity based on patient′s response to tactile and air blast stimuli. The baseline scores were obtained. Each intervention group received applications of their respective agents consecutively on 1 st , 7 th , 14 th , and 21 st day. After each application the scores were recorded. Results: Both the 30% Indian propolis and Recaldent TM showed significant reduction in DH. Conclusions: Recaldent TM was found to be significantly better in reducing the DH compared to propolis and sterile water (P < 0.01).

In real life situations, the statistical characteristics of signal and noise are generally unknown & hence a digital filter having ‘constant coefficients’ is hardly of any use. In such situations adaptive filter is desirable. Adaptive filters are capable of adapting their filter coefficients as per the abnormality in characteristics of input signal and noise to achieve a noise free signal. This paper discusses the comparative analysis of various adaptive filter algorithms such as LMS (Least mean square), BLMS (Block LMS), NLMS (Normalized LMS), BNLMS (Block NLMS), VSLMS (Variable step size LMS) and BVSLMS (Block VSLMS) algorithms. As a input we have used Hindi audio speech signal and Babble noise as an interference signal.

The age of unmatchable technical expertise envisages noise cancellation as an acute concern, as noise is held responsible for creating hindrances in day to day communication. To overcome the noise present in the primary signal notable traditional methods surfaced over the passage of time being listed as noise barriers, noise absorbers, silencers, etc. The advanced modern day approach suppresses noise by continuous adaptation of filter weights of an adaptive filter. The change in approach was ground breaking that accredits its success to advent of adaptive filters which employs adaptive algorithms. The various premier noise cancellation algorithms include LMS, RLS etc. Further much coveted Normalized LMS, Fractional LMS, Differential Normalized LMS, Filtered-x LMS etc. ensued out of active framework in this field. The paper looks forward to provide an improved approach for noise cancellation in noisy environment using newly developed variants of Filtered x LMS (FxLMS) algorithm, Feedback FxLMS (FB-FxLMS). An initial detailed analysis of existing FXLMS algorithm and FB-FxLMS algorithm has been carried out along with the mathematics of the new proposed algorithm. The proposed algorithm is applied to noise cancellation and the results for each individual process were produced to make a suitable comparison between the existing and proposed one.

Acoustic noise is an undesired disturbance that is present in the information carrying signal in telecommunication systems. The communication process gets affected because noise degrades the quality of speech signal. Adaptive noise reduction is a method of approximating signals distorted by additive noise signals. With no prior estimates of input or noise signal, the levels of noise reduction are attainable that would be difficult or impossible to achieve by other noise cancelling algorithms, which is the advantage of adaptive technique. Adaptive filtering before subtraction allows the treatment of inputs that are deterministic or stochastic, stationary or time variable. This paper provides an analysis of various adaptive algorithms for noise cancellation and a comparison is made between them. The strengths, weaknesses and practical effectiveness of all the algorithms have been discussed. This paper deals with cancellation of noise on speech signal using three existing algorithms—Least Mean Square algorithm, Normalized Least Mean Square algorithm and Recursive Least Square algorithm and a proposed algorithm—advanced Block Least Mean Square algorithm. The algorithms are simulated in Simulink platform. Conclusions have been drawn by choosing the algorithms that provide efficient performance with less computational complexity.

Objective: To assess the relationship between exposure to different drinking water fluoride levels and children’s intelligence in Madhya Pradesh state, India. Materials and Methods: This cross-sectional study was conducted among 12-year-old school children of Madhya Pradesh state, India. The children were selected from low (< 1.5 parts per million) and high (≥1.5 parts per million) fluoride areas. A questionnaire was used to collect information on the children’s personal characteristics, residential history, medical history, educational level of the head of the family, and socioeconomic status of the family. Levels of lead, arsenic, and iodine in the urine and the levels of fluoride in the water and urine were analyzed. The children’s intelligence was measured using Raven’s Standard Progressive Matrices. Data analysis was done using the chi-square, one way analysis of variance, simple linear regression, and multiple linear regression tests. P value 0.05). However, a statistically significant difference was observed in the urinary fluoride levels (P 0.000). Reduction in intelligence was observed with an increased water fluoride level (P 0.000). The urinary fluoride level was a significant predictor for intelligence (P 0.000). Conclusion: Children in endemic areas of fluorosis are at risk for impaired development of intelligence.

This paper focuses on the perception of voters toward branding of Indian Politicians and their parties. An attempt has been made to understand how voters’ behavior and perception is psychologically influenced when a politician or a political party becomes a brand. This paper has mainly stressed upon studying various aspects which makes a political actor as a national or international brand. Once these brands are established in the minds of political consumers, are able to create a distinguished approach during electoral competition. The public image along with their national and international recognition of a political leader and his party, when attached to branding helps a lot in creating voters loyalty. In a country like India, numerous strategies have been adopted in the political system to woo voters through local and social media in the recent past. The present study has randomly selected the most accepted Indian political brands like Narendra Modi, Rahul Gandhi, Arvind Kejriwal and other left parties. A survey of 300 voters has been done who casted their valuable vote in Lok Sabha Election 2014. Chi Square test of Independence, ANOVA and Garrett Ranking has been used to analyze the results. This study has concluded the public image of Mr. Narendra Modi has helped him in becoming the most favorite brand in India. This paper has also felt the need of further research to determine the role of branding and political marketing in changing the perception of the electorates