DAV Institute of Engineering and Technology is an engineering institute in Jalandhar City, established by the Dayanand Anglo-Vedic College Trust and Management Society.The DAV College Trust and Management Society is the largest non-government educational organization in India, managing a chain of about 700 institutions in India and abroad. The institute is located in the heart of city adjacent to DAV College, Jalandhar, on the left side of the Jalandhar-Amritsar National Highway.The institute received ISO 9001:2000 certification in 2005 under joint accreditation of SGS Group and UKAS Quality Management.The institute offers a B.Tech. program in six fields of engineering as well as M.Tech, MCA and MBA programs. Wikipedia.
Ryait H.S.,Baba Banda Singh Bahadur Engineering College |
Arora A.S.,DAV Institute of Engineering and Technology |
Agarwal R.,Thapar University
IEEE Transactions on Biomedical Circuits and Systems | Year: 2010
Surface electromyogram (SEMG) is a common method of measurement of muscle activity. It is noninvasive and is measured with minimal risk to the subject. The analysis of SEMG signal depends on a number of factors, such as amplitude as well as time- and frequency-domain properties. In the present investigation, the study of SEMG signals at different below elbow muscles for four operations of the hand wrist/grip-like opening (op)/closing (cl)/down (d)/up (u) was carried out. Myoelectric signals were extracted by using a single-channel SEMG amplifier consisting of a differential amplifier, noninverting amplifier, and interface module. Matlab softscope was used to acquire the SEMG signal from the hardware. After acquiring the data from six selected locations, interpretations were made for the estimation of parameters of the SEMG using the Matlab- filter algorithm and the fast Fourier transform technique. An interpretation of wrist/grip operations using principal component analysis (PCA) was carried out. PCA was used to identify the best SEMG signal capturing system out of two-channel, three-channel, and four-channel systems. Two acupressure points (on wrist) were also selected for the analysis with other points on the arm. SEMG signal's study at different locations, including pressure points, will be a very helpful tool for the researchers in understanding the behavior of SEMG for the development of the prosthetic hand. © 2010 IEEE.
Goel S.,DAV Institute of Engineering and Technology |
Singh S.P.,National Institute of Technology Jalandhar |
Singh P.,National Institute of Technology Jalandhar
Engineering Structures | Year: 2012
The paper presents an experimental investigation on the flexural fatigue strength of Self Compacting Fibre Reinforced Concrete (SCFRC) beams. The fatigue life data of SCFRC containing 0.5%, 1.0% and 1.5% by volume of steel fibres have been obtained by conducting flexural fatigue tests on approximately 188 beam specimens of size 100. ×. 100. ×. 500. mm under third point loading at different stress levels, ranging from 0.90 to 0.70. Approximately 144 complimentary static flexural tests were also carried out to facilitate fatigue testing. All the static flexural and flexural fatigue tests were conducted on a 100. kN closed loop servo-controlled actuator. The results have been represented in the form of . S-. N diagrams and to predict the flexural fatigue strength of SCFRC, material coefficients of the fatigue equations have been estimated. Subsequently, family of . S-. N-. P f curves has been generated from the fatigue test data to graphically represent the relationship between stress level . S, fatigue life . N, and probability of failure . P f, thus incorporating probability of failure into the fatigue life data of SCFRC. The experimental coefficients of the fatigue equation have also been obtained from the fatigue test data to represent the . S-. N-. P f curves analytically. The two-million cycles fatigue strength of SCFRC has been found to be higher than that of Normally Vibrated Fibre Reinforced Concrete (NVFRC). © 2012 Elsevier Ltd.
Saini S.,DAV Institute of Engineering and Technology |
Ahuja I.S.,Punjabi University |
Sharma V.S.,National Institute of Technology Jalandhar
International Journal of Precision Engineering and Manufacturing | Year: 2012
In machining of parts, surface quality is one of the most specified customer requirements. Major indication of surface quality on machined parts is surface roughness. There are various machining parameters which have an effect on the surface roughness, but these effects have not been adequately quantified. In order for manufacturers to maximize their gains from utilizing finish hard turning, accurate predictive models for surface roughness and tool wear must be constructed. This paper utilizes response surface methodology (RSM) for modeling to predict surface roughness and tool wear for variety of cutting conditions in finish hard turning. The experimental data obtained from performed experiments in finish turning of hardened AISI H-11 steel have been utilized. Decrease in feed rate and increase in cutting speed resulted in significant increase in surface quality. However, increase in cutting speed also produced relatively higher tool wear. Also depth of cut did not significantly affect the tool wear and surface roughness. © KSPE and Springer 2012.
Ahuja K.,DAV Institute of Engineering and Technology |
Singh B.,National Institute of Technology Kurukshetra |
Khanna R.,Thapar University
Optik | Year: 2014
Deployment of heterogeneous wireless networks is spreading throughout the world as users want to be connected anytime, anywhere, and anyhow. Meanwhile, users are increasingly interested in multimedia applications such as audio, video streaming and Voice over IP (VoIP), which require strict Quality of Service (QoS) support. Provisioning of Always Best Connected (ABC) network with such constraints is a challenging task. Considering the availability of various access technologies, it is difficult for a network operator to find reliable criteria to select the best network that ensures user satisfaction while reducing multiple network selection. Designing an efficient Network selection algorithm, in this type of environment, is an important research problem. In this paper, we propose a novel network selection algorithm utilizing signal strength, available bit rate, signal to noise ratio, achievable throughput, bit error rate and outage probability metrics as criteria for network selection. The selection metrics are combined with PSO for relative dynamic weight optimization. The proposed algorithm is implemented in a typical heterogeneous environment of EDGE (2.5G) and UMTS (3G). Switching rate of the user between available networks has been used as the performance metric. Moreover, a utility function is used to maintain desired QoS during transition between networks, which is measured in terms of the throughput. It is shown here that PSO based approach yields optimal network selection in heterogeneous wireless environment. © 2013 Elsevier GmbH.
Kohli A.,DAV Institute of Engineering and Technology |
Singh H.,National Institute of Technology Kurukshetra
Materials and Manufacturing Processes | Year: 2012
In the present article, an effective procedure of response surface methodology (RSM) is utilized to find the optimal values of process parameters for induction hardening of AISI 1040 steel under three different conditions of the material to predict total case depth. The three material conditions are untreated as-received (rolled), normalized, and tempered. Various process parameters, such as feed rate, current, dwell time, and gap between the workpiece and induction coil are experimentally explored. The experimental results show that the proposed mathematical models can predict the total case depth within the limits of the factors being investigated. The optimal values of process parameters have been verified by confirmation experiments. After ascertaining the optimal sample (corresponding to the best setting of induction hardening process parameters), tensile strength tests were performed so that the comparison could be done between the optimal induction hardened material and material without subjecting to induction hardening. It was concluded that the tempered is the most favorable raw material for making shafts, axles, or other automobile components during induction hardening process as almost finely distributed martensite was observed during scanning electron microscope (SEM) analysis. © 2012 Copyright Taylor and Francis Group, LLC.