Search results for: Prashant Kumar Tiwari
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 650

Search results for: Prashant Kumar Tiwari

560 Optimization of Process Parameters of Pressure Die Casting using Taguchi Methodology

Authors: Satish Kumar, Arun Kumar Gupta, Pankaj Chandna

Abstract:

The present work analyses different parameters of pressure die casting to minimize the casting defects. Pressure diecasting is usually applied for casting of aluminium alloys. Good surface finish with required tolerances and dimensional accuracy can be achieved by optimization of controllable process parameters such as solidification time, molten temperature, filling time, injection pressure and plunger velocity. Moreover, by selection of optimum process parameters the pressure die casting defects such as porosity, insufficient spread of molten material, flash etc. are also minimized. Therefore, a pressure die casting component, carburetor housing of aluminium alloy (Al2Si2O5) has been considered. The effects of selected process parameters on casting defects and subsequent setting of parameters with the levels have been accomplished by Taguchi-s parameter design approach. The experiments have been performed as per the combination of levels of different process parameters suggested by L18 orthogonal array. Analyses of variance have been performed for mean and signal-to-noise ratio to estimate the percent contribution of different process parameters. Confidence interval has also been estimated for 95% consistency level and three conformational experiments have been performed to validate the optimum level of different parameters. Overall 2.352% reduction in defects has been observed with the help of suggested optimum process parameters.

Keywords: Aluminium Casting, Pressure Die Casting, Taguchi Methodology, Design of Experiments

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559 Navigation of Multiple Mobile Robots using Rule-based-Neuro-Fuzzy Technique

Authors: Saroj Kumar Pradhan, Dayal Ramakrushna Parhi, Anup Kumar Panda

Abstract:

This paper deals with motion planning of multiple mobile robots. Mobile robots working together to achieve several objectives have many advantages over single robot system. However, the planning and coordination between the mobile robots is extremely difficult. In the present investigation rule-based and rulebased- neuro-fuzzy techniques are analyzed for multiple mobile robots navigation in an unknown or partially known environment. The final aims of the robots are to reach some pre-defined goals. Based upon a reference motion, direction; distances between the robots and obstacles; and distances between the robots and targets; different types of rules are taken heuristically and refined later to find the steering angle. The control system combines a repelling influence related to the distance between robots and nearby obstacles and with an attracting influence between the robots and targets. Then a hybrid rule-based-neuro-fuzzy technique is analysed to find the steering angle of the robots. Simulation results show that the proposed rulebased- neuro-fuzzy technique can improve navigation performance in complex and unknown environments compared to this simple rulebased technique.

Keywords: Mobile robots, Navigation, Neuro-fuzzy, Obstacle avoidance, Rule-based, Target seeking

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558 In Search of a Suitable Neural Network Capable of Fast Monitoring of Congestion Level in Electric Power Systems

Authors: Pradyumna Kumar Sahoo, Prasanta Kumar Satpathy

Abstract:

This paper aims at finding a suitable neural network for monitoring congestion level in electrical power systems. In this paper, the input data has been framed properly to meet the target objective through supervised learning mechanism by defining normal and abnormal operating conditions for the system under study. The congestion level, expressed as line congestion index (LCI), is evaluated for each operating condition and is presented to the NN along with the bus voltages to represent the input and target data. Once, the training goes successful, the NN learns how to deal with a set of newly presented data through validation and testing mechanism. The crux of the results presented in this paper rests on performance comparison of a multi-layered feed forward neural network with eleven types of back propagation techniques so as to evolve the best training criteria. The proposed methodology has been tested on the standard IEEE-14 bus test system with the support of MATLAB based NN toolbox. The results presented in this paper signify that the Levenberg-Marquardt backpropagation algorithm gives best training performance of all the eleven cases considered in this paper, thus validating the proposed methodology.

Keywords: Line congestion index, critical bus, contingency, neural network.

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557 Intelligent Transport System: Classification of Traffic Signs Using Deep Neural Networks in Real Time

Authors: Anukriti Kumar, Tanmay Singh, Dinesh Kumar Vishwakarma

Abstract:

Traffic control has been one of the most common and irritating problems since the time automobiles have hit the roads. Problems like traffic congestion have led to a significant time burden around the world and one significant solution to these problems can be the proper implementation of the Intelligent Transport System (ITS). It involves the integration of various tools like smart sensors, artificial intelligence, position technologies and mobile data services to manage traffic flow, reduce congestion and enhance driver's ability to avoid accidents during adverse weather. Road and traffic signs’ recognition is an emerging field of research in ITS. Classification problem of traffic signs needs to be solved as it is a major step in our journey towards building semi-autonomous/autonomous driving systems. The purpose of this work focuses on implementing an approach to solve the problem of traffic sign classification by developing a Convolutional Neural Network (CNN) classifier using the GTSRB (German Traffic Sign Recognition Benchmark) dataset. Rather than using hand-crafted features, our model addresses the concern of exploding huge parameters and data method augmentations. Our model achieved an accuracy of around 97.6% which is comparable to various state-of-the-art architectures.

Keywords: Multiclass classification, convolution neural network, OpenCV, Data Augmentation.

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556 Stature Prediction Model Based On Hand Anthropometry

Authors: Arunesh Chandra, Pankaj Chandna, Surinder Deswal, Rajesh Kumar Mishra, Rajender Kumar

Abstract:

The arm length, hand length, hand breadth and middle finger length of 1540 right-handed industrial workers of Haryana state was used to assess the relationship between the upper limb dimensions and stature. Initially, the data were analyzed using basic univariate analysis and independent t-tests; then simple and multiple linear regression models were used to estimate stature using SPSS (version 17). There was a positive correlation between upper limb measurements (hand length, hand breadth, arm length and middle finger length) and stature (p < 0.01), which was highest for hand length. The accuracy of stature prediction ranged from ± 54.897 mm to ± 58.307 mm. The use of multiple regression equations gave better results than simple regression equations. This study provides new forensic standards for stature estimation from the upper limb measurements of male industrial workers of Haryana (India). The results of this research indicate that stature can be determined using hand dimensions with accuracy, when only upper limb is available due to any reasons likewise explosions, train/plane crashes, mutilated bodies, etc. The regression formula derived in this study will be useful for anatomists, archaeologists, anthropologists, design engineers and forensic scientists for fairly prediction of stature using regression equations.

Keywords: Anthropometric dimensions, Forensic identification, Industrial workers, Stature prediction.

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555 Assessment of Heavy Metal Concentrations in Tunas Caught from Lakshweep Islands, India

Authors: Mahesh Kumar Farejiya, Anil Kumar Dikshit

Abstract:

The toxic metal contamination and their biomagnification in marine fishes is a serious public health concern specially, in the coastal areas and the small islands. In the present study, concentration of toxic heavy metals like zinc (Zn), cadmium (Cd), lead (Pb), nickel (Ni), cobalt (Co), chromium (Cr) and mercury (Hg) were determined in the tissues of tunas (T. albacores) caught from the area near to Lakshdweep Islands. The heavy metals are one of the indicators for the marine water pollution. Geochemical weathering, industrialization, agriculture run off, fishing, shipping and oil spills are the major pollutants. The presence of heavy toxic metals in the near coastal water fishes at both western coast and eastern coast of India has been well established. The present study was conducted assuming that the distant island will not have the metals presence in a way it is at the near main land coast. However, our study shows that there is a significant amount of the toxic metals present in the tissues of tuna samples. The gill, lever and flash samples were collected in waters around Lakshdweep Islands. They were analyzed using ICP–AES for the toxic metals after microwave digestion. The concentrations of the toxic metals were found in all fish samples and the general trend of presence was in decreasing order as Zn > Al > Cd > Pb > Cr > Ni > Hg. The amount of metals was found to higher in fish having more weight.

Keywords: Biomagnifications, marine environment, toxic heavy metals, Tuna fish.

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554 Numerical Studies on Thrust Vectoring Using Shock Induced Supersonic Secondary Jet

Authors: Jerin John, Subanesh Shyam R., Aravind Kumar T. R., Naveen N., Vignesh R., Krishna Ganesh B, Sanal Kumar V. R.

Abstract:

Numerical studies have been carried out using a validated two-dimensional RNG k-epsilon turbulence model for the design optimization of a thrust vector control system using shock induced supersonic secondary jet. Parametric analytical studies have been carried out with various secondary jets at different divergent locations, jet interaction angles, jet pressures. The results from the parametric studies of the case on hand reveal that the primary nozzle with a small divergence angle, downstream injections with a distance of 2.5 times the primary nozzle throat diameter from the primary nozzle throat location warrant higher efficiency over a certain range of jet pressures and jet angles. We observed that the supersonic secondary jet opposing the core flow with jets interaction angle of 40o to the axis far downstream of the nozzle throat facilitates better thrust vectoring than the secondary jet with same direction as that of core flow with various interaction angles. We concluded that fixing of the supersonic secondary jet nozzle pointing towards the throat direction with suitable angle at a distance 2 to 4 times of the primary nozzle throat diameter, as the case may be, from the primary nozzle throat location could facilitate better thrust vectoring for the supersonic aerospace vehicles.

Keywords: Fluidic thrust vectoring, rocket steering, supersonic secondary jet location, TVC in spacecraft.

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553 Testing a Flexible Manufacturing System Facility Production Capacity through Discrete Event Simulation: Automotive Case Study

Authors: Justyna Rybicka, Ashutosh Tiwari, Shane Enticott

Abstract:

In the age of automation and computation aiding manufacturing, it is clear that manufacturing systems have become more complex than ever before. Although technological advances provide the capability to gain more value with fewer resources, sometimes utilisation of the manufacturing capabilities available to organisations is difficult to achieve. Flexible manufacturing systems (FMS) provide a unique capability to manufacturing organisations where there is a need for product range diversification by providing line efficiency through production flexibility. This is very valuable in trend driven production set-ups or niche volume production requirements. Although FMS provides flexible and efficient facilities, its optimal set-up is key in achieving production performance. As many variables are interlinked due to the flexibility provided by the FMS, analytical calculations are not always sufficient to predict the FMS’ performance. Simulation modelling is capable of capturing the complexity and constraints associated with FMS. This paper demonstrates how discrete event simulation (DES) can address complexity in an FMS to optimise the production line performance. A case study of an automotive FMS is presented. The DES model demonstrates different configuration options depending on prioritising objectives: utilisation and throughput. Additionally, this paper provides insight into understanding the impact of system set-up constraints on the FMS performance and demonstrates the exploration into the optimal production set-up.

Keywords: Automotive, capacity performance, discrete event simulation, flexible manufacturing system.

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552 Pattern Recognition Based Prosthesis Control for Movement of Forearms Using Surface and Intramuscular EMG Signals

Authors: Anjana Goen, D. C. Tiwari

Abstract:

Myoelectric control system is the fundamental component of modern prostheses, which uses the myoelectric signals from an individual’s muscles to control the prosthesis movements. The surface electromyogram signal (sEMG) being noninvasive has been used as an input to prostheses controllers for many years. Recent technological advances has led to the development of implantable myoelectric sensors which enable the internal myoelectric signal (MES) to be used as input to these prostheses controllers. The intramuscular measurement can provide focal recordings from deep muscles of the forearm and independent signals relatively free of crosstalk thus allowing for more independent control sites. However, little work has been done to compare the two inputs. In this paper we have compared the classification accuracy of six pattern recognition based myoelectric controllers which use surface myoelectric signals recorded using untargeted (symmetric) surface electrode arrays to the same controllers with multichannel intramuscular myolectric signals from targeted intramuscular electrodes as inputs. There was no significant enhancement in the classification accuracy as a result of using the intramuscular EMG measurement technique when compared to the results acquired using the surface EMG measurement technique. Impressive classification accuracy (99%) could be achieved by optimally selecting only five channels of surface EMG.

Keywords: Discriminant Locality Preserving Projections (DLPP), myoelectric signal (MES), Sparse Principal Component Analysis (SPCA), Time Frequency Representations (TFRs).

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551 Web–Based Tools and Databases for Micro-RNA Analysis: A Review

Authors: Sitansu Kumar Verma, Soni Yadav, Jitendra Singh, Shraddha, Ajay Kumar

Abstract:

MicroRNAs (miRNAs), a class of approximately 22 nucleotide long non coding RNAs which play critical role in different biological processes. The mature microRNA is usually 19–27 nucleotides long and is derived from a bigger precursor that folds into a flawed stem-loop structure. Mature micro RNAs are involved in many cellular processes that encompass development, proliferation, stress response, apoptosis, and fat metabolism by gene regulation. Resent finding reveals that certain viruses encode their own miRNA that processed by cellular RNAi machinery. In recent research indicate that cellular microRNA can target the genetic material of invading viruses. Cellular microRNA can be used in the virus life cycle; either to up regulate or down regulate viral gene expression Computational tools use in miRNA target prediction has been changing drastically in recent years. Many of the methods have been made available on the web and can be used by experimental researcher and scientist without expert knowledge of bioinformatics. With the development and ease of use of genomic technologies and computational tools in the field of microRNA biology has superior tremendously over the previous decade. This review attempts to give an overview over the genome wide approaches that have allow for the discovery of new miRNAs and development of new miRNA target prediction tools and databases.

Keywords: MicroRNAs, computational tools, gene regulation, databases, RNAi.

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550 Development of a Cost Effective Two Wheel Tractor Mounted Mobile Maize Sheller for Small Farmers in Bangladesh

Authors: M. Israil Hossain, T. P. Tiwari, Ashrafuzzaman Gulandaz, Nusrat Jahan

Abstract:

Two-wheel tractor (power tiller) is a common tillage tool in Bangladesh agriculture for easy access in fragmented land with affordable price of small farmers. Traditional maize sheller needs to be carried from place to place by hooking with two-wheel tractor (2WT) and set up again for shelling operation which takes longer time for preparation of maize shelling. The mobile maize sheller eliminates the transportation problem and can start shelling operation instantly any place as it is attached together with 2WT. It is counterclockwise rotating cylinder, axial flow type sheller, and grain separated with a frictional force between spike tooth and concave. The maize sheller is attached with nuts and bolts in front of the engine base of 2WT. The operating power of the sheller comes from the fly wheel of the engine of the tractor through ‘V” belt pulley arrangement. The average shelling capacity of the mobile sheller is 2.0 t/hr, broken kernel 2.2%, and shelling efficiency 97%. The average maize shelling cost is Tk. 0.22/kg and traditional custom hire rate is Tk.1.0/kg, respectively (1 US$=Tk.78.0). The service provider of the 2WT can transport the mobile maize sheller long distance in operator’s seating position. The manufacturers started the fabrication of mobile maize sheller. This mobile maize sheller is also compatible for the other countries where 2WT is available for farming operation.

Keywords: Cost effective, mobile maize sheller, maize shelling capacity, small farmers, two-wheel tractor.

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549 Fuzzy Logic Based Improved Range Free Localization for Wireless Sensor Networks

Authors: Ashok Kumar, Vinod Kumar

Abstract:

Wireless Sensor Networks (WSNs) are used to monitor/observe vast inaccessible regions through deployment of large number of sensor nodes in the sensing area. For majority of WSN applications, the collected data needs to be combined with geographic information of its origin to make it useful for the user; information received from remote Sensor Nodes (SNs) that are several hops away from base station/sink is meaningless without knowledge of its source. In addition to this, location information of SNs can also be used to propose/develop new network protocols for WSNs to improve their energy efficiency and lifetime. In this paper, range free localization protocols for WSNs have been proposed. The proposed protocols are based on weighted centroid localization technique, where the edge weights of SNs are decided by utilizing fuzzy logic inference for received signal strength and link quality between the nodes. The fuzzification is carried out using (i) Mamdani, (ii) Sugeno, and (iii) Combined Mamdani Sugeno fuzzy logic inference. Simulation results demonstrate that proposed protocols provide better accuracy in node localization compared to conventional centroid based localization protocols despite presence of unintentional radio frequency interference from radio frequency (RF) sources operating in same frequency band.

Keywords: localization, range free, received signal strength, link quality indicator, Mamdani fuzzy logic inference, Sugeno fuzzy logic inference.

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548 Rheological and Computational Analysis of Crude Oil Transportation

Authors: Praveen Kumar, Satish Kumar, Jashanpreet Singh

Abstract:

Transportation of unrefined crude oil from the production unit to a refinery or large storage area by a pipeline is difficult due to the different properties of crude in various areas. Thus, the design of a crude oil pipeline is a very complex and time consuming process, when considering all the various parameters. There were three very important parameters that play a significant role in the transportation and processing pipeline design; these are: viscosity profile, temperature profile and the velocity profile of waxy crude oil through the crude oil pipeline. Knowledge of the Rheological computational technique is required for better understanding the flow behavior and predicting the flow profile in a crude oil pipeline. From these profile parameters, the material and the emulsion that is best suited for crude oil transportation can be predicted. Rheological computational fluid dynamic technique is a fast method used for designing flow profile in a crude oil pipeline with the help of computational fluid dynamics and rheological modeling. With this technique, the effect of fluid properties including shear rate range with temperature variation, degree of viscosity, elastic modulus and viscous modulus was evaluated under different conditions in a transport pipeline. In this paper, two crude oil samples was used, as well as a prepared emulsion with natural and synthetic additives, at different concentrations ranging from 1,000 ppm to 3,000 ppm. The rheological properties was then evaluated at a temperature range of 25 to 60 °C and which additive was best suited for transportation of crude oil is determined. Commercial computational fluid dynamics (CFD) has been used to generate the flow, velocity and viscosity profile of the emulsions for flow behavior analysis in crude oil transportation pipeline. This rheological CFD design can be further applied in developing designs of pipeline in the future.

Keywords: Natural surfactant, crude oil, rheology, CFD, viscosity.

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547 Prediction of Optimum Cutting Parameters to obtain Desired Surface in Finish Pass end Milling of Aluminium Alloy with Carbide Tool using Artificial Neural Network

Authors: Anjan Kumar Kakati, M. Chandrasekaran, Amitava Mandal, Amit Kumar Singh

Abstract:

End milling process is one of the common metal cutting operations used for machining parts in manufacturing industry. It is usually performed at the final stage in manufacturing a product and surface roughness of the produced job plays an important role. In general, the surface roughness affects wear resistance, ductility, tensile, fatigue strength, etc., for machined parts and cannot be neglected in design. In the present work an experimental investigation of end milling of aluminium alloy with carbide tool is carried out and the effect of different cutting parameters on the response are studied with three-dimensional surface plots. An artificial neural network (ANN) is used to establish the relationship between the surface roughness and the input cutting parameters (i.e., spindle speed, feed, and depth of cut). The Matlab ANN toolbox works on feed forward back propagation algorithm is used for modeling purpose. 3-12-1 network structure having minimum average prediction error found as best network architecture for predicting surface roughness value. The network predicts surface roughness for unseen data and found that the result/prediction is better. For desired surface finish of the component to be produced there are many different combination of cutting parameters are available. The optimum cutting parameter for obtaining desired surface finish, to maximize tool life is predicted. The methodology is demonstrated, number of problems are solved and algorithm is coded in Matlab®.

Keywords: End milling, Surface roughness, Neural networks.

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546 Numerical Studies on Thrust Vectoring Using Shock-Induced Self Impinging Secondary Jets

Authors: S. Vignesh, N. Vishnu, S. Vigneshwaran, M. Vishnu Anand, Dinesh Kumar Babu, V. R. Sanal Kumar

Abstract:

Numerical studies have been carried out using a validated two-dimensional standard k-omega turbulence model for the design optimization of a thrust vector control system using shock induced self-impinging supersonic secondary double jet. Parametric analytical studies have been carried out at different secondary injection locations to identifying the highest unsymmetrical distribution of the main gas flow due to shock waves, which produces a desirable side force more lucratively for vectoring. The results from the parametric studies of the case on hand reveal that the shock induced self-impinging supersonic secondary double jet is more efficient in certain locations at the divergent region of a CD nozzle than a case with supersonic single jet with same mass flow rate. We observed that the best axial location of the self-impinging supersonic secondary double jet nozzle with a given jet interaction angle, built-in to a CD nozzle having area ratio 1.797, is 0.991 times the primary nozzle throat diameter from the throat location. We also observed that the flexible steering is possible after invoking ON/OFF facility to the secondary nozzles for meeting the onboard mission requirements. Through our case studies we concluded that the supersonic self-impinging secondary double jet at predesigned jet interaction angle and location can provide more flexible steering options facilitating with 8.81% higher thrust vectoring efficiency than the conventional supersonic single secondary jet without compromising the payload capability of any supersonic aerospace vehicle.

Keywords: Fluidic thrust vectoring, rocket steering, self-impinging secondary supersonic jet, TVC in aerospace vehicles.

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545 Treatment of Biowaste (Generated in Biodiesel Process) - A New Strategy for Green Environment and Horticulture Crop

Authors: Shivani Chaturvedi, Santosh Satya, S. K. Tiwari

Abstract:

Recent research on seeds of bio-diesel plants like Jatropha curcas, constituting 40-50% bio-crude oil indicates its potential as one of the most promising alternatives to conventional sources of energy. Also, limited studies on utilization of de-oiled cake have revealed that Jatropha bio-waste has good potential to be used as organic fertilizers produced via aerobic and anaerobic treatment. However, their commercial exploitation has not yet been possible. The present study aims at developing appropriate bio-processes and formulations utilizing Jatropha seed cake as organic fertilizer, for improving the growth of Polianthes tuberose L. (Tuberose). Pot experiments were carried out by growing tuberose plants on soil treated with composted formulations of Jatropha de-oiled cake, Farm Yard Manure (FYM) and inorganic fertilizers were also blended in soil. The treatment was carried out through soil amendment as well as foliar spray. The growth and morphological parameters were monitored for entire crop cycle. The growth Length and number of leaves, spike length, rachis length, number of bulb per plant and earliness of sprouting of bulb and yield enhancement were comparable to that achieved under inorganic fertilizer. Furthermore, performance of inorganic fertilizer also showed an improvement when blended with composted bio-waste. These findings would open new avenues for Jatropha based bio-wastes to be composted and used as organic fertilizers for commercial floriculture.

Keywords: Organic fertilizer, Jaropha cake, Tuberose (Polianthes tuberosa L.).

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544 Solution of The KdV Equation with Asymptotic Degeneracy

Authors: Tapas Kumar Sinha, Joseph Mathew

Abstract:

Recently T. C. Au-Yeung, C.Au, and P. C. W. Fung [2] have given the solution of the KdV equation [1] to the boundary condition , where b is a constant. We have further extended the method of [2] to find the solution of the KdV equation with asymptotic degeneracy. Via simulations we find both bright and dark Solitons (i.e. Solitons with opposite phases).

Keywords: KdV equation, Asymptotic Degeneracy, Solitons, Inverse Scattering

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543 Female Work Force Participation and Women Empowerment in Haryana

Authors: Dinabandhu Mahata, Amit Kumar, Ambarish Kumar Rai

Abstract:

India is known as a country of diversity regarding the social, cultural and wide geographical variations. In the north and north-west part of the country, the strong patriarchal norms and the male dominance based social structure are the important constructs. Patriarchal social setup adversely affects the women’s social and economic wellbeing and hence in that social structure women are considered as second level citizen. Work participation rate of women has directly linked to the development of society or household. Haryana is one of the developed states of India, still being ahead in economic prosperity, much lagged behind in gender-based equality and male dominance in all dimensions of life. The position of women in the Haryana is no better than the other states of India. Haryana state has the great difference among the male-female sex ratio which is a serious concern for social science research as a demographic problem for the state. Now women are requiring for their holistic empowerment and that will take care of them for an enabling process that must lead to their economic as well as social transformation. Hence, the objective of the paper is to address the role of sex ratio, women literacy and her work participation in the process of their empowerment with special attention to the gender perspective. The study used the data from Census of India from 1991 to 2011. This paper will examine the regional disparity of sex ratio, literacy rate and female work participation and the improvement of empowerment of women in the state of Haryana. This paper will suggest the idea for focusing much intensively on the issues of women empowerment through enhancement of her education, workforce participation and social participation with people participation and holistic approach.

Keywords: Sex ratio, literacy rate, workforce participation rate, women empowerment, Haryana.

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542 Some Properties of IF Rough Relational Algebraic Operators in Medical Databases

Authors: Chhaya Gangwal, R. N. Bhaumik, Shishir Kumar

Abstract:

Some properties of Intuitionistic Fuzzy (IF) rough relational algebraic operators under an IF rough relational data model are investigated and illustrated using diabetes and heart disease databases. These properties are important and desirable for processing queries in an effective and efficient manner.

 

Keywords: IF Set, Rough Set, IF Rough Relational Database, IF rough Relational Operators.

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541 Minimization of Non-Productive Time during 2.5D Milling

Authors: Satish Kumar, Arun Kumar Gupta, Pankaj Chandna

Abstract:

In the modern manufacturing systems, the use of thermal cutting techniques using oxyfuel, plasma and laser have become indispensable for the shape forming of high quality complex components; however, the conventional chip removal production techniques still have its widespread space in the manufacturing industry. Both these types of machining operations require the positioning of end effector tool at the edge where the cutting process commences. This repositioning of the cutting tool in every machining operation is repeated several times and is termed as non-productive time or airtime motion. Minimization of this non-productive machining time plays an important role in mass production with high speed machining. As, the tool moves from one region to the other by rapid movement and visits a meticulous region once in the whole operation, hence the non-productive time can be minimized by synchronizing the tool movements. In this work, this problem is being formulated as a general travelling salesman problem (TSP) and a genetic algorithm approach has been applied to solve the same. For improving the efficiency of the algorithm, the GA has been hybridized with a noble special heuristic and simulating annealing (SA). In the present work a novel heuristic in the combination of GA has been developed for synchronization of toolpath movements during repositioning of the tool. A comparative analysis of new Meta heuristic techniques with simple genetic algorithm has been performed. The proposed metaheuristic approach shows better performance than simple genetic algorithm for minimization of nonproductive toolpath length. Also, the results obtained with the help of hybrid simulated annealing genetic algorithm (HSAGA) are also found better than the results using simple genetic algorithm only.

Keywords: Non-productive time, Airtime, 2.5 D milling, Laser cutting, Metaheuristic, Genetic Algorithm, Simulated Annealing.

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540 Image Segmentation Using Suprathreshold Stochastic Resonance

Authors: Rajib Kumar Jha, P.K.Biswas, B.N.Chatterji

Abstract:

In this paper a new concept of partial complement of a graph G is introduced and using the same a new graph parameter, called completion number of a graph G, denoted by c(G) is defined. Some basic properties of graph parameter, completion number, are studied and upperbounds for completion number of classes of graphs are obtained , the paper includes the characterization also.

Keywords: Completion Number, Maximum Independent subset, Partial complements, Partial self complementary.

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539 Modelling and Dimension Analysis of a Multipurpose Convertible Laptop Table Using Autodesk Fusion 360

Authors: Nitesh Pandey, Manish Kumar, Pankaj Gupta, Amit Kumar Srivastava

Abstract:

The convertible table is a versatile and adaptable item designed to provide numerous solutions in one. The design incorporates numerous features that offer both ease and functionality. The description of the versatile convertible table in this overview encompasses a range of features that can be tailored to accommodate various user requirements. With its changeable functionality, this piece can easily transform into a workstation, dining table, or coffee table to suit various needs. Significantly, this multipurpose convertible laptop table includes a specific section for electronic devices such as computers and tablets, offering convenience for remote workers and online learners. In addition, providing storage space for essential equipment promotes a tidy workspace by facilitating the organization of many items. The integrated flash system offers supplementary illumination for dimly lit surroundings, while the cooling fans prevent the table's surface from overheating in hot weather or during prolonged laptop usage, making it an optimal and superior choice for laptop users. In order to cater to the needs of students, painters, and other individuals who require writing tools on a regular basis, a pencil and pen stand is included, hence enhancing the versatility of the table. The scissor lift mechanism allows for easy modifications in height, making it convenient to customize usage and providing the option of using it as a standing desk. Overall, this convertible table exemplifies its ability to adapt, its user-friendly nature, and its usefulness in a wide range of situations and settings.

Keywords: Furniture design, laptop stand, study table, learning tool, furniture manufacturing, contemporary design.

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538 Light Harvesting Titanium Nanocatalyst for Remediation of Methyl Orange

Authors: Brajesh Kumar, Luis Cumbal

Abstract:

An ecofriendly Citrus paradisipeel extract mediated synthesis of TiO2 nanoparticles is reported under sonication. U.V.-vis, Transmission electron microscopy, Dynamic light scattering, and X-ray analyses are performed to characterize the formation of TiO2 nanoparticles. It is almost spherical in shape, having a size of 60–140 nm and the XRD peaks at 2θ = 25.363° confirm the characteristic facets for anatase form. The synthesized nanocatalyst is highly active in the decomposition of methyl orange (64 mg/L) in sunlight (~73%) for 2.5h.

Keywords: Ecofriendly, TiO2 nanoparticles, Citrusparadisi, TEM.

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537 Solitons in Nonlinear Optical Lattices

Authors: Tapas Kumar Sinha, Joseph Mathew

Abstract:

Based on the Lagrangian for the Gross –Pitaevskii equation as derived by H. Sakaguchi and B.A Malomed [5] we have derived a double well model for the nonlinear optical lattice. This model explains the various features of nonlinear optical lattices. Further, from this model we obtain and simulate the probability for tunneling from one well to another which agrees with experimental results [4].

Keywords: Double well model, nonlinear optical lattice, Solitons, tunneling.

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536 Translator Design to Model Cpp Files

Authors: Er. Satwinder Singh, Dr. K.S. Kahlon, Rakesh Kumar, Er. Gurjeet Singh

Abstract:

The most reliable and accurate description of the actual behavior of a software system is its source code. However, not all questions about the system can be answered directly by resorting to this repository of information. What the reverse engineering methodology aims at is the extraction of abstract, goal-oriented “views" of the system, able to summarize relevant properties of the computation performed by the program. While concentrating on reverse engineering we had modeled the C++ files by designing the translator.

Keywords: Translator, Modeling, UML, DYNO, ISVis, TED.

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535 On Bounding Jayanti's Distributed Mutual Exclusion Algorithm

Authors: Awadhesh Kumar Singh

Abstract:

Jayanti-s algorithm is one of the best known abortable mutual exclusion algorithms. This work is an attempt to overcome an already known limitation of the algorithm while preserving its all important properties and elegance. The limitation is that the token number used to assign process identification number to new incoming processes is unbounded. We have used a suitably adapted alternative data structure, in order to completely eliminate the use of token number, in the algorithm.

Keywords: Abortable, deterministic, local spin, mutual exclusion.

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534 Some Static Isotropic Perfect Fluid Spheres in General Relativity

Authors: Sachin Kumar, Y. K. Gupta, J. R. Sharma

Abstract:

In the present article, a new class of solutions of Einstein field equations is investigated for a spherically symmetric space-time when the source of gravitation is a perfect fluid. All the solutions have been derived by making some suitable arrangements in the field equations. The solutions so obtained have been seen to describe Schwarzschild interior solutions. Most of the solutions are subjected to the reality conditions. As far as the authors are aware the solutions are new.

Keywords: Einstein's equations, General Relativity, PerfectFluid, Spherical symmetric.

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533 Heart Rate Variability Analysis for Early Stage Prediction of Sudden Cardiac Death

Authors: Reeta Devi, Hitender Kumar Tyagi, Dinesh Kumar

Abstract:

In present scenario, cardiovascular problems are growing challenge for researchers and physiologists. As heart disease have no geographic, gender or socioeconomic specific reasons; detecting cardiac irregularities at early stage followed by quick and correct treatment is very important. Electrocardiogram is the finest tool for continuous monitoring of heart activity. Heart rate variability (HRV) is used to measure naturally occurring oscillations between consecutive cardiac cycles. Analysis of this variability is carried out using time domain, frequency domain and non-linear parameters. This paper presents HRV analysis of the online dataset for normal sinus rhythm (taken as healthy subject) and sudden cardiac death (SCD subject) using all three methods computing values for parameters like standard deviation of node to node intervals (SDNN), square root of mean of the sequences of difference between adjacent RR intervals (RMSSD), mean of R to R intervals (mean RR) in time domain, very low-frequency (VLF), low-frequency (LF), high frequency (HF) and ratio of low to high frequency (LF/HF ratio) in frequency domain and Poincare plot for non linear analysis. To differentiate HRV of healthy subject from subject died with SCD, k –nearest neighbor (k-NN) classifier has been used because of its high accuracy. Results show highly reduced values for all stated parameters for SCD subjects as compared to healthy ones. As the dataset used for SCD patients is recording of their ECG signal one hour prior to their death, it is therefore, verified with an accuracy of 95% that proposed algorithm can identify mortality risk of a patient one hour before its death. The identification of a patient’s mortality risk at such an early stage may prevent him/her meeting sudden death if in-time and right treatment is given by the doctor.

Keywords: Early stage prediction, heart rate variability, linear and non linear analysis, sudden cardiac death.

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532 A Comparative Study of Image Segmentation using Edge-Based Approach

Authors: Rajiv Kumar, Arthanariee A. M.

Abstract:

Image segmentation is the process to segment a given image into several parts so that each of these parts present in the image can be further analyzed. There are numerous techniques of image segmentation available in literature. In this paper, authors have been analyzed the edge-based approach for image segmentation. They have been implemented the different edge operators like Prewitt, Sobel, LoG, and Canny on the basis of their threshold parameter. The results of these operators have been shown for various images.

Keywords: Edge Operator, Edge-based Segmentation, Image Segmentation, Matlab 10.4.

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531 Rate of Convergence for Generalized Baskakov-Durrmeyer Operators

Authors: Durvesh Kumar Verma, P. N. Agrawal

Abstract:

In the present paper, we consider the generalized form of Baskakov Durrmeyer operators to study the rate of convergence, in simultaneous approximation for functions having derivatives of bounded variation.

Keywords: Bounded variation, Baskakov-Durrmeyer operators, simultaneous approximation, rate of convergence.

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