The extent of present exploration is studying and assessing the outcome of replacing of cement with a variety of proportions of each of Metakaoline&GGBS (0%, 5 %, 10 %& 15%) for aggregate binder ratio of 1.75 along withwater-binder ratio of 0.275 within distinctive proportions of glass fibers (0%, 0.5 %, & 0.75 % ) along with consistent percent of polypropylene fibers of 0.25 % to generate High performance Concrete. Cubes are treated at seven as well as twenty-eight days and then evaluated for compressive strength.

Keywords: Metakaoline, GGBS, Glass Fibres, Polypropylene fibers, High-Performance Concrete, Conplast SP-430, Compressive strength.

The present paper deals with study ofcompressive strength of rigid road pavements by replacing 15% of fine aggregate with M sand. Water binder ratio of 0.30is incorporated where cement is partially replaced by Ground Granulated Blast Furnace Slag by0%, 10%, 20% and 30% which is a mineral admixture and Glass Fibresare added by 0.5% and 0.75%. To improve workability of mixes, super plasticizerConplast SP-430is used (0.8%).This study examines compressive strength of concrete mixtures containing various combinations of GGBS based Glass Fibre reinforced concrete pavement mixes designed by Absolute Volume Method. Cubes of 100x100x100 mm are cast, cured for 7 & 28 days before testing. The results are analyzed and useful conclusions are drawn.

Keywords: GGBS, M Sand, Concrete Pavement, Glass Fibres, Compressive Strength, Sand Replacement, Rigid Pavement.

The present paper deals with analysis of rigid pavements made by usingM Sand as fine aggregate. Water binder ratio of 0.300 is used where cement is partially replaced by Ground Granulated Blast Furnace Slag& Metakaolin0%, 10%, 20% and 30%. Glass fibre is added by 0.5% and 0.75%. To improve workability of mixes, super plasticizers Conplast SP-430 is used. This study examines compressive strength of concrete mixtures containing various combinations of Granulated Blast Furnace Slag& Metakaolinbased glass fibre reinforced concrete pavement mixes designed by Absolute volume method. Cubes of 100x100x100 mmare cast, cured for 7 & 28 days before testing. The results are analyzed and useful conclusions are drawn.

Keywords: Metakaolin, GGBS, Glass Fibres, Rigid Pavement, Compressive strength, Super plasticizer, Absolute volume method.

The present paper deals with study offlexuralstrength of rigid road pavements by replacing 15% of fine aggregate with M sand. Water binder ratio of 0.30isused where cement is partially replaced by Ground Granulated Blast Furnace Slag by0%, 10%, 20% and 30% which is a mineral admixture and Glass Fibresare added by 0.5% and 0.75%. To improve workability of mixes, super plasticizerConplast SP-430is used (0.8%).This study examines flexuralstrength of concrete mixtures containing various combinations of GGBS based Glass Fibre reinforced concrete pavement mixes designed by Absolute Volume Method. Beams of 100x100x500 mm are cast, cured for 7 & 28 days before testing. The results are analyzed and useful conclusions are drawn.

Keywords: GGBS, M Sand, Concrete Pavement, Glass Fibres, Flexural Strength, Sand Replacement, Rigid Pavement.

Training course masterminding about versatile robots want to verification an ideal training course. The optimality attained can switch into the training course, time, energy make use of and therefore on. The training course organizing in the designed automaton additionally depends upon the globe where it functions, for example, stationary or powerful, known or brand-new. The organizing of the world-wide direction making use of A * computations and hereditary computations can be certainly researched in this record. The known amazing condition wherein the control teach place will compute the most short method and speak with the cell and cell robots will combine the method to obtain the interest on. The control teach place will display screen the training course the item gives embarked. The cell coding explores the briefest training course, and if the item recognizes any hurdle in the objective training course, the cell coding will refresh...........

Keywords: A* Algorithm, Artificial Intelligence, Path Planning, Robotic Motion, MATLAB.

Nowadays the disposal of industrial and Agro wastes has become serious concern to environment and special attention is required towards handling them. Agricultural wastes such as Rice husk ash, sugarcane bagasse ash etc. and the Industrial wastessuch as GGBS, Fly ash etc. can be partially replaced with cement. In the present paper, theattempt is made towards the utilization of GGBS and Fly ash in cement concrete pavement. The use of these wastes would not only be economical but it also helps in reduction of greenhouse gases and makes the environment pollution free. The mineral admixture such as fly ash, silica fume etc. has been utilized in many of the developed countries.In the present investigation GGBS...........

Keywords: GGBS, M-sand, Flyash, River sand, Ordinary portlandcement, Compressive strength, Concrete Pavement.

Till date there is very less applications of holograms. Because holographic projection is still in research topic. Our project is based on a holographic projector which takes an input image and store the output in Holographic Versatile Disc(HVD) and project the image as holograms. We will use this projector for commercial advertisement in replacement of hoarding banner. Advantage of any holographic projector is that it will be seen from anywhere around. It is also cost effective as it is also one time investment as we only have to store new image in HVD. This image can be replaced many time as we want and this process will also take less power supply. One holographic projector will be equivalent to 4 hoarding banners.

Keywords: Holographic Projector, Holographic Versatile Disc (HVD).

In this paper, the concepts of edge domination in picture fuzzy graphs are introduced. The edge domination number 𝛾𝑒(𝐺) for some standard picture fuzzy graphs was determined. The edge independent set of a picture fuzzy graphs are defined. Theorems related to edge domination and edge independent set in picture fuzzy graphs are stated and proved.

Keywords: Picture fuzzy graph, Edge dominating set, Edge domination number, Edge independent set, Edge independent number of picture fuzzy graph. AMS Subject Classification: 05C12.

The purpose of this study was to develop a sleep disorder detection system using deep learning. A pressure distribution sensor was used to collect sleep data from all examinees. We can know the movement of sleep from body pressure that happens on the sensor. We did not use the measurement that have to attach to the examinee's body. Thus, they might not feel any strange or uncomfortable. Previous study, we analyzed data using support vector machine (SVM) and the identification ratio was 77.78%. In this study, for more accuracy rate, we used neural network model to classify images of sleeping. Moreover, study participants, sampling rate and study environment is same as previous study. We used deep learning by images processing. Each of image was the average for the pressure on the sensor in 3 hours (superimposed image). We color the average of pressure using 100 level color with 10 tone of color. The identification ratio of this study was 94.44%. The identification ratio has increased from previous study.

Keywords: Athens insomnia scale, Deep learning, Detection system, Sleep disorder, Image classifying, Pressure distribution sensor,LeNet model.

Traffic sign detection and recognition are important functions in an Advanced Driver Assistance Systems (ADAS). The detection of traffic sign will locate the presence of the signboard and its recognition will identify the detected sign. In the real world, knowing the content of the sign is much more important than simply knowing the existence of a sign. This paper implements traffic sign detection using color and contour analysis and compares the performance with Single Shot Multi Box Detector deep learning algorithm (SSD). The classification of traffic signs is also done using Convolutional Neural Network (CNN).

Keywords:Traffic Sign detection, Convolutional Neural Network (CNN), Contour based Segmentation, Single Shot Multi Box Detector (SSD), Jetson TX1.