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A photonic crystal based MOEMS pressure sensor design is presented in this work. The key design element is a circular diaphragm made of silicon (Si), integrated with a hexagonal ring resonator in the middle. The novelty of the work is the arrangement of the holes in the Si diaphragm in triangular orientation and optimization of sensitivity for pressure sensing. The pressure is applied at the center of the diaphragm which resulted in deformation, stress, and strain. The minimum observable deformation is 1.0073 nm and is at 6.3 µPa. The corresponding change in the refractive index is calculated for the stress applied. The resonant wavelength obtained for without load is 1.598 µm. The shift in the resonant wavelength for different loads are observed and tabulated. The modeling tool used to extract the mechanical parameters is ANSYS multiphysics. For 2D modeling and simulation of the ring resonator structure, MEEP is used for the implementation of FDTD. The Q-factor observed is 12,245 and sensitivity reported as 316.15 nm/RIU respectively.

Fake news has been a problem ever since the internet boomed. The very network that allows us to know what is happening globally is the perfect breeding ground for malicious and fake news. Combating this fake news is important because the world's view is shaped by information. People not only make important decisions based on information but also form their own opinions. If this information is false it can have devastating consequences. Verifying each news one by one by a human being is completely unfeasible. This paper attempts to expedite the process of identification of fake news by proposing a system that can reliably classify fake news. Machine Learning algorithms such as Naive Bayes, Passive Aggressive Classifier and Deep Neural Networks have being used on eight different datasets acquired from various sources. The paper also includes the analysis and results of each model. The arduous task of detection of fake news can be made trivial with the usage of the right models with the right tools.

Human eye is one of the most complex organs in human body. Eyes, the integral part of Visual system receives signals and brain computes the obtained visual details. The brain helps in detection and interpretation of information in the visible light. This Complex process includes reception of light, binocular perception, estimation of distance and categorization of objects. Any anomaly in such process causes Blindness or Visually Impairment. According to WHO survey approximately 1.3 billion people live with some form of vision impairment. The need for visual aid is essential to enhance visual ability for visually impaired. In this paper a detailed review of different types of advance techniques to enhance vision is discussed.

We aim at providing the necessary and sufficient information with respect to medical specification and condition of patient (may be an admitted patient or an outpatient of a hospital) to the concerned doctor over specific communication protocol like TCP/IP, here we set up server which necessarily in hospital is CNS (central nurse station) and concerned doctor on the hospital network would be a client to CNS, a nurse who thinks a patient requires certain doctors attention or the other way round based on patient ID the doctor can fetch various information analyze and send his/her opinion about the patient to the CNS.

The advent of VLSI technology brings in its wake huge benefits to patients, doctors and designers, undreamt before, by bringing in automation and raising the level of care nurses are able to provide. Instead of walking to each patient’s bedside to collect vital information, nurses can collect it in one location and concentrate their efforts on caring for those who need them the most. As an outcome of these requirements, a prospect arose to design a highly efficient patient care and monitoring system which can handle patients and multiple parametric measurements from every single patient in real time. Patient care and monitoring embedded systems are proposed in this work to acquire, store, display physiological information obtained from multi patients and are vital in operating rooms, emergency rooms, intensive care units, ambulances as well as at homes. The design exploits development of Novel, Fast Algorithms, Design of Architectures using labVIEW implementations.

Universal interconnection networks are prime performance tailback for high performance SoCs (Systems-on-Chip). Since shrinking the size of the ICs (Integrated Circuits) is the main aim, NoC (Network-on-Chip), being a segmental and mountable design tactic is a propitious substitute to outmoded bus-mode architectures. NoC combined with 3D-Routers and label switching technique can guarantee low power consumption, QoS along with less latency. In the proposed work, 3D NoCs are proven to be more advantageous by achieving 39.9% reduction in Area, 1.7% reduction

From the past decade the expansion of highways are slow when compared to the growth of transportation, traffic blockage becoming a central transportation issue in a metropolitan cities. Modeling of growth trend and improvement in forecasting techniques for transport population has always been and will continue to be of first importance for any major infrastructure development initiatives in the transportation engineering sector. Although many traditional, as well as some advanced methods, are in vogue for this process of estimation, there has been a continuous quest for improving the accuracy of different methods. A citywide traffic pattern is used in transportation and metropolitan planning. Traditional approaches for the estimation of traffic flow may heavily depend on the road-based sensor, and nowadays the traffic forecasting is done by using data mining techniques, machine learning, artificial intelligence, neural networks, cloud computing. Even social networks also play the vital role in predicting the traffic. Big-data-driven traffic flow prediction systems are accessible when the big data concept emerged into the field. In this area, the robustness of prediction performance depends on accuracy and timeliness. In this paper, we have studied various research works, and we are analyzed the different methods and techniques which are used to forecasting the traffic flow estimation.

Information retrieval in the form of documents, images is playing a key role in day-to-day life of humans. Real world applications scenario is changing daily, so as the improvement is also becomes a necessary. Various approaches were proposed for retrieval, but all the input images were considered under proper illumination conditions. If the images suffered with illumination angle color and viewing angle changes then it’s very difficult to retrieve similar images. We propose a system which can deal with illumination angle and color variations. Experiments were conducted on ALOI (Amsterdam Library of Object Images) dataset, which is a collection of one thousand objects each with hundred similar images. These images were recorded under changing the illumination angle, color and viewing angle. Experimental results prove that the proposed approach outperforms well in terms of retrieval efficiency \(\dots \)

Designing a highly efficient patient care and monitoring system which can handle multiple patients and multiple parametric measurements from every single patient in real time will lead in improvising the data handling capability at Central Nurse Stations (CNS) and Decentralized Nurse Stations (DCNS). The Bio signal Data Acquisition Systems have been designed to suit patients located at CNS and DCNS in a hospital. The RTL design of Bio signal Data Acquisition System was successfully simulated using Model sim. The design was placed and routed using Xilinx ISE 8.2i tool and the bit stream generated is used for downloading into the targeted FPGA. The FPGA used is XC3S400-5ft256, common for both schemes shown. At 50 MHz operation, the system is capable of wireless communication of 32 numbers of Bio signals up to 400,000 bits/s although the maximum frequency of operation of this design is 89 MHz reported by Xilinx ISE tool. This system is truly upgradeable, be it in extending the capabilities to more number of patients or in improving throughput.

There has been a focus on developing image indexing techniques which have the capability to retrieve image based on their contents. The main feature extraction methods are content Based Image Retrieval (CBIR) also known as query by Image content (QBIC). This paper presents a technique to derive the colors, shapes, textures, or any other information that can be derived from a satellite image Using Texture filters and realizing it with artificial neural networks. This image processing technique are been utilized to identify important urban features such as buildings and gardens and rural features such as natural vegetation, water bodies, and fields. Textures are represented by Texel, which are then placed into a number of sets, depending on how many textures are detected in the image.

Communication for physically challenged people is indispensable for their day to day activities. This paper presents the hardware design of smart sensors for brain machine interface which is used for acquiring the bio potential signals from three different sensors such as EEG, Eyeball and the Eye blink signals. The design was analyzed and validated using Lab View. Bio-signals from the forehead, scalp and eye movements are acquired and the artifacts generated by spurious signals are filtered out using band pass filters. Transmission and reception of these signals over wireless media assists the partially paralytic patients by taking these signals as commands and, to be independent in doing their daily chores The paper aims in exploiting the qualities of MULTISIM functionality, design complexity, and hence the design time of these signal circuits are significantly reduced and a comparative analysis is done to prove the design of the hardware developed is accurate to an extent of 90%.