Showing papers by "SDM College of Engineering and Technology published in 2019"

Automation of irrigation system through embedded computing technology

Abstract: Dearth of fresh water worldwide has given rise to solemn alarms since a decade. Economical administration of water resources plays a critical role when it is mainly with reference to the agriculture zone. Irrigation is generally functions along with canal plan by which water is pumped up into fields once at regular period of time according to farmers habitual ways without appropriate measurements with none feedback of water level in field. This kind of irrigation method will definitely hinder the crop growth and health and produces a poor yield as a result of some crops area component too susceptible to water content in soil. The ingenuous ICT technique presents an insolent system that uses minimum value soil wetness sensing element and temperature sensing element to manage facility in water shortage regions. The sensor, those vocations on the standard of moisture reliant resistance amendment between two points within the soil, is invented with the help of low cost materials and ways. Moisture and temperature knowledge is fetched from a sensing element node is distributed through an Arduino to a centralized server that controls facility. An automaton application is developed to envision the daily wetness and temperature knowledge. Moreover, the planned wetness sensing and temperature sensing ways have the power to be incorporated into machine-controlled which is automatic irrigation theme and perform automated, exactness agriculture in conjunction with de-centralized water management system. Application results illustrate that system through the embedded controlled technology which makes it complete intelligent irrigation, enhance the agricultural produce and improve soil health by irrigation, the water is used fruitfully and irrigation system automation is achieved mostly in all aspects.

Controlled partial image encryption based on LSIC and chaotic map

Abstract: Partial image encryption plays a vital role in the field of medical image encryption, because small amount of encryption leads to high security with low computation complexity. This paper presents controlled partial image encryption using LSIC and chaotic map. It consists of two methods. In method-1 image is divided into 16x16 blocks. Entropy of each block is compared with threshold entropy from entropy selection table. If entropy of each block is greater than predefined threshold entropy then that block is XORed with 16x16 random block generated by converting each row of LSIC into 16x16 block. In method-2 entropy of block greater than predefined threshold entropy then pixels within that block is shuffled using chaotic map. Based on different threshold entropy values different partial encrypted images are obtained. From the experimental results shows that proposed methods can controlled amount of encryption as per the requirements.

QSPR Analysis of certain Distance Based Topological Indices

Abstract: In QSAR/QSPR study, topological indices are utilized to guess the bioactivity of chemical compounds. In this paper, we study the QSPR analysis of selected distance and degree-distance based topological indices. Our study reveals some important results which help us to characterize the useful topological indices based on their predicting power

Accuracy Prediction for Distributed Decision Tree using Machine Learning approach

Abstract: Machine Learning is one of the finest fields of Computer Science world which has given the innumerable and invaluable solutions to the mankind to solve its complex problems. Decision Tree is one such modern solution to the decision making problems by learning the data from the problem domain and building a model which can be used for prediction supported by the systematic analytics. In order to build a model on a huge dataset Decision Tree algorithm needs to be transformed to manifest itself into distributed environment so that higher performance of training the model is achieved in terms of time, without compromising the accuracy of the Decision Tree built. In this paper, we have proposed an enhanced version of distributed decision tree algorithm to perform better in terms of model building time without compromising the accuracy.

Cadmium selenide quantum dots: Synthesis, characterization and their humidity and temperature sensing properties with poly-(dioctylfluorene)

Abstract: In this paper, we report synthesis, thin film characteristics and sensing properties of cadmium selenide (CdSe) quantum dots (QDs) for enhancing the humidity and temperature sensing of a polymeric semiconductor poly-(9,9-di-n-octylfluorenyl-2,7-diyl) (F8). Transmission electron microscopy (TEM) has been performed to study the texture, distribution over surface and size of the synthesized CdSe QDs. TEM image revealed slightly non-uniform distribution of the QDs with an average size of 4 nm having three-dimensional quantum confinement features. Atomic force microscopy (AFM) is carried out to investigate the average grain size and surface roughness of the F8-CdSe nanocomposite film. To understand the role of CdSe QDs on the sensing properties of F8, a blend F8-CdSe QDs has been prepared at 10:1 wt-percent (wt%) of F8 and CdSe QDs, respectively, in chloroform. An Ag/F8-CdSe QDs/Ag surface-type sensor has been fabricated via spin coating F8-CdSe QDs nanocomposite on a 45 μm gap between the pre-patterned silver (Ag) electrodes on glass substrate. The fabricated Ag/F8-CdSe QDs/Ag sensor has been studied for humidity and temperature sensing by measuring capacitance (C) of the sensor as a function of humidity and temperature, respectively. The Ag/F8-CdSe QDs/Ag sensor exhibits enhancement in the sensing parameters such as response time and recovery time i.e., 9 s and 7 s, respectively, as compared to our previously studied Ag/F8/Ag sensor whose response and recovery time were 15 s and 7 s, respectively. This improvement is due to the addition of CdSe QDs in F8 polymer matrix which changes some of the important properties of the F8-CdSe QDs nanocomposite such as electron polarizability, polarity, hydrophobicity and size dependent properties. The role of porosity (P) in the sensing properties of the active film of Ag/F8-CdSe QDs/Ag device has also been explored. The Ag/F8-CdSe QDs/Ag based sensor shows approximately linear change in C as a function of humidity and temperature with wide range of sensitivity from 25 percent relative humidity (%RH) to 90%RH and from 16 to 186 °C, respectively.

Effect of Tungsten Carbide Reinforcement on the Aluminum 6061 Alloy

Abstract: Aluminum matrix composites are often preferred in automotive, aerospace, and ship building owing to their enhanced properties over conventional engineering aluminum alloys. In this article, the results of the investigations on the mechanical properties and sliding wear behavior of aluminum–tungsten carbide (WC) composites are presented and discussed. Metal matrix composites of Al6061 containing different percentages of WC were prepared by powder metallurgy techniques. All testing was conducted according to ASTM standards. The dry sliding wear tests were conducted at a constant velocity and load varying from 10 to 40 N. The composite density was found to increase with greater filler contents and is further in agreement with the values of theoretical density. The Brinell hardness and ultimate tensile strength of the composites increased with a greater ceramic phase and decreased filler size, with a decrease of percentage elongation. The dry sliding wear of the composites with WC reinforcement displayed the greater resistance to wear.

Impact of process induced residual stresses on interlaminar fracture toughness in carbon epoxy composites

Abstract: Residual stresses are induced in composite laminates during the process of manufacturing due to thermal mismatch between composite constituents during curing. Processes induced residual stresses effects the safety of structural components and can play a main role in matrix cracking, crack initiation and propagation. The objective of this research is to study the influence induced residual stresses on interlaminar fracture toughness (GI) of Carbon/Epoxy laminates. Initially laminates were cured under room temperature followed by post curing at various temperatures using a chosen cure cycle. Slitting method was employed to determine the residual stress distribution in post cured laminates and its effects on GI was estimated using Double Cantilever beam (DCB) test. The results show a gradual increase in GI with increase in compressive residual stresses in composite laminate. Further, the fracture surfaces of laminates were carefully studied using scanning electron microscope to know the interfacial adhesion of matrix and fiber.

Provenance and Implications of Heavy Minerals in the Beach Sands of India's Central West Coast

Abstract: Shalini, G.; Hegde, V.S.; Soumya, M., and Korkoppa, M.M., 2020. Provenance and implications of heavy minerals in the beach sands of India's central west coast. Journal of Coastal Research, 36(2), 353–361. Coconut Creek (Florida), ISSN 0749-0208.The heavy mineral assemblage and mineral chemistry of the beach sands of Mulki, Karnataka, central west coast of India, are discussed in this paper to understand their provenance. The study is based on the seasonal modification in shoreface profiles and identification of heavy minerals under binocular microscope followed by electron probe micro-analysis. The heavy mineral assemblage of the Mulki estuarine beach sands includes ilmenite, magnetite, zircon, rutile, hornblende, epidote, kyanite, and tremolite. There are two generations of ilmenite. The older generation is characterized by porous ilmenite that shows TiO2/FeO between 1.32 and 8.09. The second generation of ilmenite is characterized by fresh, rounded to angular grains that have relatively lower TiO2/FeO ratios ( 97% and another with TiO2 <94%. The presence of two generations of ilmenite and rutile suggests reworking of the older generation, probably derived from the offshore region or a paleobeach brought by the combined action of alongshore current and waves to the present beach, and a second generation brought by the modern drainage system. The heavy mineral assemblage and mineral chemistry suggest mixed provenance consisting of basic igneous rocks, acidic rocks, and high-grade metamorphic rocks. Mafic and acidic source rocks are indicated by the presence of two types of ilmenite, one with Cr2O3 and the other devoid of Cr2O3, and two types of hornblende, one rich in MgO and the other poor in MgO. High-grade metamorphic source rocks are indicated by the presence of rutile, kyanite, and tremolite. The Mulki-Pavanje River drains from a low-grade metamorphic terrain. Therefore, high-grade metamorphic minerals are attributed to an external source brought by alongshore drift.

A quasi-ballistic drain current, charge and capacitance model with positional carrier scattering dependency valid for symmetric DG MOSFETs in nanoscale regime.

Abstract: This paper presents a physically valid quasi-ballistic drain current model applicable for nanoscale symmetric Double Gate (SDG) MOSFETs. The proposed drain current model includes both diffusive and ballistic transport phenomena. The model considers the important positional carrier scattering dependency effect near the source region described in terms of transmission and reflection co-efficients related to the scattering theory. The significance of carrier transport near the bottleneck source region is illustrated where the carriers diffuse into the channel at a relatively lower velocity before accelerating ballistically. The results obtained demonstrate carrier scattering dependency at the critical layer defined near the low field source region on the drain current characteristics. The proposed model partly evolves from Natori’s ballistic bulk MOSFET model that is modified accordingly to be valid for a symmetric Double Gate MOSFET in the nanoscale regime. Carrier degeneracy and Fermi–Dirac statistics are included in the work so as to justify the complete physicality of the model. The model is further extended and is shown to be continuous in terms of terminal charges and capacitances in all regions of operation. A comparative analysis is also done between the proposed quasi-ballistic model and a hypothetical complete ballistic device.

A Survey of Various Cryptographic Techniques: From Traditional Cryptography to Fully Homomorphic Encryption

Abstract: With the advent in Internet and networking applications, security is a major concern in the current era of Information Technology. The huge amount of information exchanged over the Internet is vulnerable to security threats and attacks. Cryptography provides secure exchange of encrypted data by sharing a key. The major concern with this approach is data privacy as anybody with the key can access the data. Moreover, user loses control over data once it is uploaded to the cloud and must rely on cloud service provider. User must share a key with cloud service provider to perform any operations like searching, sorting, etc., or need to download and decrypt the data and then perform the operation. These approaches lead to privacy issue and repeated encryption decryption, even for small computation. These concerns are addressed by Homomorphic Encryption (HE), which enables the cloud service provider to carry out computations on ciphered data without decrypting it. With the advent of HE scheme, in 2009, the Fully Homomorphic Encryption (FHE) scheme was invented by C. Gentry, which allows any computational function to operate on encrypted data. But the practical implementation of FHE is still in research. This survey focuses on various traditional and modern cryptography techniques along with the different schemes of HE and FHE.

Influence of Kenaf and GO on interlaminar radial stresses in glass/epoxy L‑bend laminates

Abstract: Laminates of L-bends are inherently weak in the through thickness direction at the region of curvature. To address this behavior, experimental investigations have been made to find the influence of graphene oxide (GO) and Kenaf short fibres on interlaminar radial stress of a unidirectional glass epoxy L-bend composite laminate. Kenaf in the range of 5–10 wt% and GO in the range of 1–2 wt% were loaded at each ply at the curvature of a L-bend and their influence on curved beam strength (CBS) was investigated experimentally as per ASTM D6415. L-bend composite specimens with and without fillers were fabricated with the aid of hand lamination technique. Four point bending fixtures were designed and fabricated to hold the specimen firmly in the uniaxial tension machine. Tests were carried out as per ASTM D6415 and load displacement plots were carefully recorded. Experimental data revealed that the laminate loaded with Kenaf fibres at the curvature radius of L-bend had greater influence on CBS and interlaminar stresses than GO. Further, the delaminated surfaces of L-bend at the curvature region was carefully examined using scanning electron microscope to know the interfacial adhesion mechanism of Kenaf and GO with epoxy and glass fibre.

A Review On Existing QoS Routing Protocols in Vanet Based on Link Efficiency and Link Stability

Abstract: Vehicular ad hoc network (VANET) is a category of mobile ad hoc network (MANET). VANET provides wireless communication among vehicle-to-vehicle (V2V) and vehicle to a computing device located on roadside infrastructure called Road Side Unit (RSU). The communication between vehicles can be used for safety provisioning and emergency awareness by exchanging information among traffic participants to realize a cooperative and more efficient transportation system. An important issue associated with V2V communications used for traffic safety and emergency awareness applications (TSEAAs) is better routing with the Quality of Service (QoS) support. This paper reviews the existing QoS routing protocols based on the two important parameters: link efficiency and link stability.

Power Generation From Renewable Energy Sources Derived From Biodiesel and Low Energy Content Producer Gas for Rural Electrification

Abstract: The work presented mainly focuses on the power generation from engine-gasifier integrated system suitably modified to operate on selected renewable as well as fossil-derived fuel combinations. In this direction, biodiesel of Honge oil methyl ester (HOME), fuel oil (FO) also called pyrolysis plastic oil (PPO), were selected as pilot injected fuels in the modified diesel engine to operate in dual fuel mode with low energy content producer gas as inducted fuel. Accordingly, the performance, combustion, and emission characteristics of a single cylinder, four stroke water cooled direct injection (DI) compression ignition (CI) engine operated in dual fuel mode using these fuel combinations were investigated as potential sources for power generation applications. In the first phase of the work, production of fuel oil from low-density polyethylene waste (LDPE) using thermal and catalytic process has been investigated. Thermal cracking yielded 97.2 wt% conversions compared to 99.1 wt% by catalytic cracking with catalyst to plastic ratio of 0.2 and biodiesel was obtained using transesterification process from the Honge oil, which is locally and abundantly available in India. Further, in the next phase of the work, performance of dual fuel engine was investigated using HOME and fuel oil (ranging from 0% to 30% in HOME) blend and producer gas induction. Optimized performance of dual fuel operation using combination of HOME and FO blend called HFO and producer gas induction was done using different engine operating parameters such as reentrant type combustion chamber (RCC), 230 bar injection pressure, 4 hole, and 0.25 mm nozzle orifice which showed a 4.9% increased performance with acceptable levels of emissions compared to HOME-PG operation with conventional unmodified diesel engine provided with hemispherical combustion chamber (HCC). Results of investigation on HOME + FO-PG operation with RCC showed significant changes in ignition delay, increased cylinder pressure, heat release rate, and decreased combustion duration compared to HOME-PG operation with conventional existing engine facility. However, extended investigations in engine technology with further development would enhance the performance and feasibility of these fuels for dual fuel operation and future power generation exploitations.

A novel SMLR-PSO model to estimate the chlorophyll content in the crops using hyperspectral satellite images

Abstract: The estimating the chlorophyll contents in the crops helps to identify the condition of crops and different classification of crops with soil characteristics in order to assist the farmer or others with agriculture growth. In this paper, a hybrid approach is introduced to estimate the Chlorophyll contents in the crops using hyperspectral image segmentation with active learning, which consists of two main steps. First, we use a sparse multinomial logistic regression (SMLR) model to learn the class posterior probability distributions with Quadratic Programming or joint probability distribution. Second, we use the information acquired in the previous step to segment the hyper spectral image using a Markov Random field segments to estimate the dependencies using spatial information and edge Information by minimum spanning forest rooted on markers. In order to reduce the cost of acquiring large training sets, PSO optimization is performed based on the SMLR posterior probabilities on the Normalized difference vegetation index (NDVI). The state-of-the-art performance of the proposed approach is illustrated using real hyper spectral data sets collected from the North Karnataka in a number of experimental comparisons with recently developed or statistical hyperspectral image analysis methods in terms of precision, recall and f—measure.

DSP implementation of modified variable vector quantization based image compression using DCT and synthesis on FPGA

Abstract: In the extant context of data compression, numerous data reduction techniques have evolved and produced many innovative solutions. These elucidations may have resulted in further complexities during physical realizations. This research endeavor put forth experimentation outcomes in the field of Discrete Cosine Transform (DCT) based image compression using modified vector quantization and prototyping the algorithm on Digital Signal Processor (DSP) TMS320C6713 platform. In addition, such an algorithm is synthesized on Virtex5 XC5VSX50T Field Programmable Gate Array (FPGA). The performance metrics used and calculated here at algorithm level are Mean Square Error (MSE), Peak Signal to Noise Ratio (PSNR_, Compression Ratio (CR), Bits per Pixel (bpp), percentage Space Saving in accordance with modified variable vector quantization levels from 10 to 90.

Research outlook and state-of-the-art methods in context awareness data modeling and retrieval

Abstract: As the data or information gets increased in various applications, it is very much essential to make the retrieval and modeling easier and simple. Number of modeling aspects already exists for this crisis. Yet, context awareness modeling plays a significant role in this. However, there requires some advancement in modeling system with the incorporation of advanced technologies. Hence, this survey intends to formulate a review on the context-aware modeling in two aspects: context data retrieval and context data modeling. Here, the literature analyses on diverse techniques associated with context awareness modeling. It reviews 60 research papers and states the significant analysis. Initially, the analysis depicts various applications that are contributed in different papers. Subsequently, the analysis also focuses on various features such as web application, time series model, intelligence models and performance measure. Moreover, this survey gives the detailed study regarding the chronological review and performance achievements in each contribution. Finally, it extends the various research issues, mainly the adoption of Evolutionary algorithms, which can be useful for the researchers to accomplish further research on context-aware system.

Study and tailoring of screen-printed resistive films for disposable strain gauges

Abstract: The present work aims at fabrication and characterization of the novel dispersion based piezoresistive strain gauges. The novelty of present work is in the material-set and technique used to synthesize the low-cost, graphite powder based composites of various proportions without the need for additional pre-treatment or functionalization. When filler and resins are properly formulated, they can be printed in variety of shapes over different substrates such as glass, acrylic, plastics (such as PVC, PDMS, PMMA, PET, PI), metal foils, paper etc. They may be of great interest to integrate mechanical, chemical or temperature sensing functions in many electronic circuits and devices. In the current work, the resistive composite dispersions are screen-printed on glass substrate to fabricate the strain gauges and to study their piezoresistive strain performance. Graphite particles in the powder are found to have irregular shape and size. Thickness of screen-printed films varies in the range 13–27 μm. Gauge factors ranging from 17 up to 70 is achieved for the strain gauges having satisfactory stability, linearity and repeatability. The variation in GF is found to be less than 2%. Maximum hysteresis and nonlinearity were observed to be less than 2% FSO (Full Scale Output). Repeatability is found to be minimum 98%. The dispersion composition is tuned to obtain a better sensitivity. Regarding temperature effects, all the strain gauge samples exhibited a negative value of TCR, lowest being -2 × 10−4 /oC. Graphite powder and printing ink are inexpensive and commercially-available. Also, technique used to fabricate strain gauges avoids high-end equipment and expensive clean room facilities. These devices are robust, easy to scale & pattern, safely disposable strain gauges with are fairly good performance fabricated at low cost. These features make them a good candidate for pressure sensors, weigh bridges, displacement sensors, crack sensors, strain sensors etc. The real time potential applications are in different sectors such as automotive, aerospace, biomedical, oceanography and industrial purposes.

Distribution system Network Reconfiguration for Voltage profile improvement and loss reduction Using BPSO

Abstract: The paper focuses on fimding the best topology of IEEE-69 bus distribution network by interchanging the status of tie and sectionalizing switches without creating any loop in the network, the aim of the research is to improvise the system reliability in terms of voltage profile maximization and overall system loss minimization. Binary Particle swarm optimization (BPSO) is applied to achieve best switching without violating parameters allied to distribution system thereby ensuring the security of the system. The results obtained are satisfactory.

Effects of Hybrid SVD–DCT Based Image Compression Scheme Using Variable Rank Matrix and Modified Vector Quantization

Abstract: The advent of modern image processing concepts and cutting edge solutions, various architectures of image compression have reached every individual electronic gadgets and embedded systems. Many such designs were suggested and tried, gratifying the present day requirements of electronic industry. On these grounds, the proposed system deals with addressing the consequences of hybrid system, which employs low rank matrix SVD and a modified variable vector quantization matrix DCT in image compression. The efficiency of such proposed system is evaluated with the help of MSE, PSNR, CR, bpp and percentage space saving. DCT alone proves to be better technique over the SVD-DCT hybrid method.

Estimating distance threshold for greedy subspace clustering

Abstract: Many approaches have been proposed to recognize clusters in subspaces. However, their performance is highly sensitive to input parameter values. The purpose and expected ranges of these parameters may not available to a non-expert user. The parameter setting producing optimal results can only be known after repeated execution of the clustering process every time with a different set, which is very time consuming. Most of the existing algorithms show high runtimes due to excessive data scans. In this work, we propose a subspace clustering technique that estimates the distance threshold parameter automatically from the data for each attribute and works on the basis of single linkage clustering, in bottom up, greedy fashion. The experimental results show that, the algorithm produces optimal results without accepting any input from the user, achieves up to 10 times better runtime and improved accuracy in a single run without requiring any tuning of parameter values.

Classification of Brain Hemorrhages in MRI Using Naïve Bayes- Probabilistic Kernel Approach

Abstract: A brain hemorrhage is one type of stroke, which is caused due to artery burst in the brain, killing the brain cells due to bleeding. Therefore, to reduce the criticality among the patients, for treatment, the doctors depend on accurate reports on the location of hemorrhage. Magnetic resonance imaging (MRI) is one of the best imaging modality when functional and structural abnormalities need to be found. To aid the identification of presence of abnormality, a novel NB-PKC algorithm for effective recognition of brain hemorrhages in MRI is proposed. A series of preprocessing is done, then the image undergoes binary thresholding process for applying an image mask on the hemorrhage region. Then for segmentation a modified multi-level segmenting algorithm is applied, using minimal local binary pattern and GLCM, combined features are extracted and finally for classification a novel Naïve Bayes- Probabilistic Kernel Classification is applied. These techniques designed could accurately identify the position and classified whether the image had an abnormality or not and could reduce human errors.

Q-Factor Based Modified Adaptable Vector Quantization Techniques for DCT-Based Image Compression and DSP Implementation

Abstract: In the context of multimedia application, image compression is an integral part of image processing, which is a significant constituent in the present world of computation and communication The work presented here focusses on the design and the selection of modified adaptive vector quantization techniques used in the image compression and its influence on the quality (Q-factor) of the reconstructed image The proposal also considers and suggests the modifications to two existing methods by providing comparative evaluation Both experiments have been tested on MATLAB framework and DSP TMS320C6713 The performance metrics used in the proposed designs are MSE, PSNR, CR, bpp, and percentage space saving with respect to variations in quantization levels, starting from 10 to 90 Such suggested implementations prove to provide better off-the-shelf solutions

Realization of a micro composite based pressure sensor: Its performance study for linearity, hysteresis and sensitivity

Abstract: The relevance of pressure sensors in daily life applications has been phenomenal in diversified disciplines such as engineering, bio-medical, automobile, aerospace etc. Making right choice of pressure sensors is crucial in any of these disciplines. Of late, the pursuit of making the pressure sensors applicable to various domains has spurred a variety of innovative activities. They are being fabricated using novel materials and unconventional fabrication methodology. Also, the advent of microelectromechanical systems has provided new horizons for a variety of realizations that led to the development of efficient and robust pressure sensors. The electromechanical characteristics of the sensing materials and the fabrication methodologies employed to realize the sensor have significant influence on performance of the sensor. This paper reports the micro composite based piezoresistive gauge pressure sensor performance study which was realized by screen printing technique. Graphite-PVC resin based dispersions are screen printed on flat, circular shaped, 1.98 mm thick stainless-steel diaphragm. The transducing layers are directly printed on the deforming polymer coated diaphragm so that the coupling factor is high, resulting in an efficient transfer of strain. Pressure cyclic study and its effect on linearity, hysteresis, sensitivity, stability etc. are investigated. The sensitivity is found to be 0.357 mV/bar. The maximum hysteresis and non-linearity are found to be less than 0.8% FSO. A fairly satisfactory sensitivity, linearity, hysteresis and stability are accomplished at a low cost. By observing the performance characteristics of the realized pressure sensor it can be used in commercial, industrial, automotive, aerospace and strategic fields. Some of the applications could be in tire pressure sensing, air filling in petrol bunks, petrol/diesel/oil/water tankers, water supply pipelines, oil/gas explorations, hydraulic jacks and mines etc.

A Novel on Biometric Parameter’s Fusion on Drowsiness Detection Using Machine Learning

Abstract: The operator driving vehicle in night has become a major problem nowadays The largest number of accidents in the world is due to drowsiness To overcome this problem, we have developed a machine for a longer period which detects drowsiness and alert the operator Early detection of fatigued state has become important to develop a detection system According to the previous work, we found a lot of issues in detecting drowsiness when wearing spectacles and in dark and light condition In our research paper, we have overcome these issues to detect drowsiness based on the fusion of visual parameters like face detection, eye detection, and yawning in all conditions and wearing spectacles

A Quasi-Ballistic Drain current model with Positional Scattering Dependency applicable for Nanoscale DG MOSFETs

Abstract: This work presents a simple physics based quasi-ballistic drain current model applicable for nanoscale Double Gate (DG) MOSFETs. The proposed model is physical and includes both drift-diffusion and ballistic transport phenomena. The model considers scattering effects that occur in real nanoscale devices, in terms of transmission and reflection co-efficients related to scattering theory. The results obtained in the proposed work provide an intuitive analysis and signify the positional scattering dependency at the critical layer near the low field source region on the drain current characteristics. An insightful and comparative analysis is done for the proposed quasi-ballistic model, with a hypothetical complete ballistic device and a velocity saturated short channel DG MOSFET model.

Image Quality Improvements Using Quantization Matrices of Standard Digital Cameras in DCT Based Compressor

Abstract: In the field of image compression, loads of scope exist for research. This work facilitates the platform to investigate and divulge the evidence of usage of vector quantization process in unique, prominent and renowned digital cameras of the present day. The work encompasses discrete cosine transform (DCT) based image compression technique using vector quantization of corresponding digital cameras, applied to standard test images. The luminance and chrominance quantization matrices of two digital cameras, namely Canon PowerShot A700 (Superfine) and Fuji FinePix A700 (Fine), are selected, which are investigated and verified as quantization level of 50. The proposed technique comprises not only one level of quantization; however, the vector quantization is variable from level 10 to 75. Both qualitative and quantitative analysis are carried out to verify the functionality and applicability of the algorithm. In addition, the functional verification of the said technique is carried out on Raspberry Pi low-cost embedded platform.