bluuebunny/crossref_metadata_2025_split huggingface dataset:
Generation of Single Sideband-Suppressed carrier (SSB-SC) Signal Based on Stimulated Brillouin Scattering
Authors: Bhogal Rosepreet Kaur , Sindhwani Manoj 
Published: September 2022

Abstract
A novel cost-effective wavelength shifter is suggested in this paper. This paper shows how to shift signals in the mm-wave area using a frequency shifter. Due to stimulated Brillouin scattering in optical fibre, the proposed approach produces a single sideband signal without the carrier signal. When compared to SSB-SC transmissions, the bandwidth efficiency of double sideband signals is lower. Because it employs an optical fibre with a performance degrading condition such as SBS as an application, the frequency shifter is entirely optical. The theory of Gain and Loss Spectrum of SBS within optical fibre is utilised to minimise the upshifted frequency component and boost the low shifter frequency component in order to generate improved carrier power and single sideband. The SBS phenomenon produces a single sideband, which is advantageous in advanced modulation systems and consumes less bandwidth. It’s worth noting that the SSB-SC signal may be generated using any optical approach, and the proposed work eliminates the need for non-optical components like 90-degree hybrid couplers. SSB-SC signals are capable of combating pulse broadening difficulties and have the ability to operate at terahertz frequencies. Transmission of an SSB-SC signal is also shown to validate the performance of the produced signal. Furthermore, the Q factor of SSB-SC, SSB with carrier, DSB-SC, and DSB with carrier signals is studied at various connection lengths.
Accelerating the Machine Learning Model Deployment using MLOps
Authors: Chowdary Mandepudi Nobel , Sankeerth Bussa , Chowdary Chennupati Kumar , Gupta Manu 
Published: September 2022

Abstract
Machine Learning projects acquire a large amount of data to make predictions on the data. Deploying machine learning models is a difficult task as it is involved a lot factors such as continuous builds to improve efficiency and different libraries used for prediction. As the data grow for better predictions with proper accuracy some of the parameters are to be dynamically changed for the sake of performance tuning. To enhance the variation in the parameters it takes effort and time from the developers to make the changes in the code and deploy to the production environment. In proposed work, an end to end automation cycle to enhance the timely deployment of machine learning models with better performance is presented. This automation cycle converts the changed code with varied parameters into the container image and uploads to the container registry. Later, when the new image is uploaded it auto detects and updates the production environment with the new image data by launching a new container and shutting down the previous old one. The proposed automated model will display the updated features which are developed. The users can utilize the updated model simultaneously without any downtime to obtain the new features. The main contribution of proposed work is that it can build and deploy the machine learning models automatically, without any manual intervention. The models can also be retrained for better performance of the predictions.
A prototype model for detection and classification of landslides using satellite data
Authors: Sharma Akanksha , Sharma Kamal Kumar , Sapate Suhas Gajanan 
Published: September 2022

Abstract
Landslides are natural and manmade disasters that cause threat to human life and lead to huge economic loss. Last few decade number of approaches have been developed for early detection of landslide for protecting life and saving properties. This paper proposes a prototype for an artificial intelligent model to detect and predict different types of landslides in hilly area with remote sensing techniques. All developing countries are following a steep increase in development of infrastructure like buildings, roads tunnels bridges railway tracks. Demand of connecting remote area is very high but on other side of environment it is also true that high demand of construction in morpho material area is causing many disasters like landslide. Landslide causes the loss of property and life so an early alarming will be help full for disaster management. Remotely sensed data pre-processed with artificial intelligent technologies will be helpful for landslide detection, creating landslide susceptibility map and inventory. Focus of this study is on enhancing the accuracy to detect landslide, list out the different features for extraction from satellite images and pre processing steps. This research also focuses on application of robust early prediction of type of landslide. This research will help in detection of landslide early to protect economical losses and human lives.
An Approach to Pattern Recognition for Identification of Devnagari Script Based on Fingertips and Palm
Authors: Tantarpale Ms. Sharvari , Deshmukh C. N. 
Published: September 2022

Abstract
In this paper, we present an finger point based signed language symbol to text identification and classification algorithm that is based upon RGB image datasets. The palm sized images based upon different sizes, backgrounds, orientation are captured to be preprocessed as per the requirements of developing a convolution neural network based algorithm. This algorithm utilizes Alexnet for the preprocessing requisites where in 47 symbols of Devanagari script are augmented based on the reference rulebook created for our requirements as highlighted in the paper. At the primary level this algorithm provides an excellent classification rate which promises upliftment for our research in the upcoming future. We have provided detailed steps and discussion on the classification parameters considered for our algorithm which is implemented on MATLAB platform with the help of machine learning solution libraries.
Performance evaluation of various machine learning and deep learning models for gene expression
Authors: Thakur Tanima , Batra Isha , Malik Arun 
Published: September 2022

AbstractCancer is among those deadliest diseases that affects a mass. So, it requires the timely detection and treatment. There are number of ways through which cancer can be detected. Some of those ways are some “blood tests, CT (Computerized Tomography) scan, MRI (Magnetic Resonance Imaging), X-Ray, Ultrasound, gene expression, etc.”. Genes help doctors to find whether a person is suffering or going to suffer from any disease or not. In this paper, we have gone through various ML and DL from the literature. The models are trained and tested on 5 different types of datasets. These are “Lung Adenocarcinoma (LUAD), Lung Squamous Cell Carcinoma (LUSC), Breast Invasive Carcinoma (BRCA), Kidney Renal Clear Cell Carcinoma (KIRC), and Uterine Corpus Endometrial Carcinoma (UCEC)”. The models are evaluated on the different performance measures such as “MSE, Precision, Recall, F1_Score and Accuracy”.
A Comprehensive Review of Emerging Technologies: Machine Learning and UAV in Crop Management
Authors: Yagnasree S. , Jain Anuj 
Published: September 2022

Abstract
It is a known fact that India is one among the major food producers in the world. Due to the rapid urbanization and Agrochemical interventions, plants are infected by insects, pathogens, massive infestations, which leads to the deficiency of growth nutrients and ions, thereby minimizing agricultural crop yield. These infections occur in several forms like aphids, black root rot, cankers, leaf curls, rusts, anthracnose, and blights make agriculture fail to thrive and increase the impact of crop diseases. Since plant disease prevention is a continuous process that occurs regularly, agriculturists follow several strategies to keep their crops disease-free. An efficient monitoring and supporting system for continuous and long-term plant and soil health monitoring is needed to meet the needs of growing population. In this paper, existing research works in Precision agriculture, emerging technologies – GPS, GIS, Machine learning and UAVs in analyzing crop health analysis, soil health monitoring, and crop yield prediction are reviewed.
Performance Investigation of Back-Compatible Integrated TWDM/GPON System Using MDM And Pulse Shapes
Authors: Singh Ajmer , Bhogal Rosepreet Kaur 
Published: September 2022

AbstractOptical access networks are the prominent and promising cutting edge technology to provide high speed, and cost effective operation for meeting the requirements of ever-increasing demands of users. Multiple access techniques such as Wavelength and time division in passive optical networks are important innovations to provide high capacity. A mode division multiplexed back compatible integrated next generation PON2 (TWDM PON) and GPON is demonstrated with triple play supportability in this work. Proposed system offer pay as you grow feature and also provide enhanced performance by suppressing the inter-channel interference in TWDM-PON2. System successfully works on same optical distribution network unit for both PON standards without extra arrangements and has potential to support 62.5 Gbps in full duplex mode (Symmetrical downlink/uplink). Moreover, demonstrated back compatible system is analyzed by incorporating diverse modulations such as NRZ-DPSK, RZ-DPSK, RZ-DQPSK, NRZ-DPSK and linecodings NRZ, RZ. Received power, Optical signal to noise ratio (OSNR), BER and Q factor are noted at diverse link lengths and it is noteworthy that LP modes with NRZ in TWDM PON provide outstanding results.
Design of Broadband Passive Optical Network Incorporating Different Modulation Formats and Colorless ONUs
Authors: Sachdeva Shippu , Gupta Raghav 
Published: September 2022

Abstract
In this work, a bidirectional broadband passive optical network (BPON) is proposed at 622.08 Mbps by incorporating colorless optical network units and different pulse shapes such as Duo-binary return to zero (DRZ), return to zero (RZ) and non-return to zero (NRZ). For varied link lengths, launching powers in terms of log BER, and Quality factor for downstream and upstream, the design of BPON is examined. The duo-binary advanced pulse shape outperformed the others in bidirectional BPON, achieving a symmetrical distance of 25 kilometres.
Investigation of Inter-Satellite OWC Incorporating Dense WDM and Polarization Interleaving (PI)
Authors: Chawla Sachin 
Published: September 2022

Abstract
Inter-satellite communication based on lasers (LIC) is a possible choice for future satellite networks because to ultra-high capacity and speed systems that may be achieved using compact, light-weight, and low-power optical equipment. The performance of a 64 × 40 GB/s optical wireless system with polarisation diversity for dense WDM is investigated in this research paper. Using a DWDM system with a channel spacing of 50 GHz, a high-speed system is achieved to meet the broad bandwidth needs of data services in satellites. A polarisation diversity approach is implemented in the system to decrease polarisation crosstalk and nonlinearities among nearby WDM channels. Furthermore, a comparison of the polarisation interleaved and traditional DWDM-OWC systems is performed. In addition, it was discovered that a system with varying states of polarisation across neighbouring channels performs better in terms of Q-factor and BER than a traditional system.
Effects of Orthogonal Modulations on FWM in Multichanel Systems
Authors: Ruchika  
Published: September 2022

Abstract
In multichannel systems, four wave mixing (FWM) is a conspicuous and significant performance degrading element. Optimized modulation formats are necessary to decrease FWM effects and boost the data rate supportability of multichannel systems. By combining 3-D and 2-D orthogonal modulation formats, multichannel system with eight channels and each operating at 10 Gbps is suggested in this paper. Polarization shift keying is an important modulation that has been examined bay taking Q-factor into consideration at various distances. Furthermore, FWM power is examined and a comparison for 3-D, 2-D, and 1-D modulations at different frequency spacings such as 100 GHz, 50 GHz, and 25 GHz has been established. Because 2-D orthogonal modulation has the least amount of FWM, it is suggested for usage in WDM systems with ultra-dense spacings.
An Economical and Ultra Dense WDM-PON System with Polarization Interleaving and PWR
Authors: Sachdeva Shippu , Bansal Mohit 
Published: September 2022

Abstract
In this paper, a cost effective and easy maintenance based dispersion compensation technique is proposed in ONU of the wavelength reused wavelength division multiplexing reliant passive optical network. Moreover, in order to suppress intra-channel crosstalk DQPSK is employed for downstream and for inter-channel crosstalk suppression, polarization interleaving is used in the system. Furthermore, for the investigation of proposed system in terms of dispersion reduction, three different scenarios are considered such that system with only DCF, linearly chirped FBG and joint module of DCF+FBG. System has total 4 channels and each has bit rate of 20 Gb/s with 25 GHz channel spacings. It is observed that joint module of DCF+FBG has maximum ability to compensate dispersion and linearly chirped FBG has least performance. Proposed joint technique for pulse width reduction in ONU is cost effective, highly efficient to combat with pulse width reduction issues and also needs very less maintenance.
Improvement in Depth of Reflection Co-efficient below -20 dB for Millimeter–Wave Antenna
Authors: Singh Simerpreet , Sethi Gaurav , Khinda Jaspal Singh 
Published: September 2022

AbstractA low cost microstrip antenna is designed formm–wave applications on FR4 substrate. It consist of patch, etched with an open polygon slot (OPS) at lower central edge of it and partial ground plane. This etching of OPS is used to improve depth of reflection co-efficient below -20 dB which is equivalent to mismatch loss (MLdB) ≤ 0.04 dB. This proposedmm–wave antenna also provides 3 dBi– & 5 dBi–gain-bandwidth of 6 GHz (34.72—40.72GHz) & 3.91 GHz (34.72—38.63GHz) respectively with a peak gain of 12.4 dBi at 35.1 GHz and acceptable radiation efficiency of 58.05 %. Simple design, low manufacturing cost and ease of fabrication makes proposed antenna suitable for high end practicalmm–wave applications.
Ideal congestion control model to enhance the quality of service of VANET network
Authors: Gogoi Rajkamal , Arora Sandeep Kumar 
Published: September 2022

Abstract
Vehicular Adhoc Technology (VANET) is a mobile ad-hoc network where each vehicle combines with a communication link. Well fascinated and proper connectivity between the vehicle nodes are very essential to make the communication efficient. But high mobility and rapid change in locations of the vehicles often hampers its performance. Also often disconnection and overloading issues inside the network create an extra burden to vanet. So it is very important to make the network free from these factors so that smooth communication can happen between the network. In this paper, we have proposed our algorithm to control the network from congestion occurrence. Which ultimately enhanced the performance and QoS of the network
Performance Analysis of Massive MIMO under pilot contamination.
Authors: Dutta Ragit 
Published: September 2022

Abstract
5g is fast becoming a reality in the modern world. Telecom companies all around the world are already rolling out 5G in various parts of the world. As of now there are 3 key technologies that will enable us to implement 5G in our surroundings. Massive MIMO is one of them. Massive MIMO focuses on the aspect of improving the spectral efficiency. Tremendous data rates are achievable with spectral efficiency. However there are several bottlenecks in the implementation of Massive MIMO. Pilot Contamination is one of the most prominent issues in massive MIMO. This paper is about addressing the issue of Pilot Contamination in Massive MIMO. This paper also focuses on the various mitigation schemes proposed by researchers in the past.
Load Balancing using Fixed Geometric Arrangements of Fixed and Mobile Small Cells in Mili-Meter Network
Authors: Verma Shekhar , Pandey Vaibhav , Khurana Preeti 
Published: September 2022

Abstract
The upcoming generation of cellular networks is going to make extensive use of mmWave for communication. Hence, there will be a need for small cells to counter the loss incurred due to the more energy dissipation of mmWave. Small cells contain transmitters and receivers and hence there will be the need to balance the load efficiently so that no one is overwhelmed with functions to perform while others are relatively idle. In this paper, the performance of the user association algorithm is analysed when it is subjected to different scenarios like micro-urban, macro urban, suburban and rural. these scenarios are subjected to different frequency bands of mmWave and are compared for the values of the load balancing index. The load balancing algorithm is subjected to different small cell deployment techniques and the comparison is made for best deployment strategy among Quadrature based Approach (QBA) and Random deployment. Simulation results show that the sub-urban scenario has the maximum load-balancing index. On comparing QBA and random deployment approach QBA has a higher load balancing index in the suburban and rural scenarios and random deployment has a higher load balancing index in Indoor environments.
Performance Improvement of Next-Generation Network with Cognitive Radio Network and Coordinated Multipoint Joint Transmission
Authors: Valentin Disashi , Gupta Akhil , Sharma Manmohan 
Published: September 2022

Abstract
Cognitive Radio Network (CRN) is a favourable technology for the future of wireless networks. It aims to seamlessly exploit spectrum resources by opportunistically using the unused or underused radio spectrum that is licensed. Cognitive Radio Network is a technology that is planned to be used in the 5th Generation of wireless communication. This technology is belied to be the answer to the unused and underused radio spectrum in the Radio environment. Whereas Coordinated Multipoint Joint Transmission (CoMP JT) is a technology that has already been used, first used in 3GPP LTE-Advanced. Coordinated Multipoint Joint Transmission aims to improve the performance of the cellular network. In this report, Cognitive Radio Network is being implemented along with Coordinated Multipoint Joint Transmission techniques. An inclusive and layered architecture of Cognitive Radio Network along with Coordinated multipoint Joint Transmission is being designed in this report, showing different technologies and different steps involved in the concept of this combination. Then the impact of CoMP JT on CRN is being studied. By implementing CoMP JT on CRN, it has been able to show how the performance of CRN is changing when implemented alone and when implemented with CoMP JT and some of the significant results are being depicted to better understand the changes in CRN with CoMP JT. Lastly, a study is performed on the combination of Cognitive Radio Network and Coordinated Multipoint Joint Transmission. As far as the investigation is being performed, two factors have been considered, which is: Signal to Interference plus Noise Ratio (SINR) and Total Average Throughput (TAT). The detailed study is being performed in this report and is being implemented in three different environments. Hence the results are being compared and a conclusion is being drawn based on these results.
Energy Harvesting Technique for Massive MIMO Wireless Communication Networks
Authors: Bolla Sandhya , Singh Manwinder 
Published: September 2022

Abstract
Massive For wireless data and energy transfer, MIMO, a key component of future 5G systems, is favourable. A big part of the reason for this is that it has the ability to narrow down the distribution of energy. The scope of something enormous Multiple-Input in 5G, harvesting may be used to boost system capacity and efficiency via multiple-output multiple access. This was followed by the introduction of the Simultaneous Wireless Information and Power Transfer (SWIPT) method, commonly known as energy harvesting optimization. Specific to each user’s needs, we connected a splitter on the receiver, and we measured their output using power beacons. In order to achieve the lowest possible communication rate, the user’s total gathered power is boosted. Simulations show that the proposed technique is more successful than the other options out there. There are two sources of energy for D2D transmitters: specialised beacon signals, and cellular users (CUs) radio frequency (RF) interference. In D2D transmitters, inverse power control techniques are used for power regulation. We employ Poisson Point Processes(PPP) to model the proposed hybrid network’s CU, D2D user (DU), and PB locations. Each slot in the time period is assigned a different beam forming weight. Using the alternating minimization technique, we provide a solution approach for a non-convex quadratic ally limited linear problem. Long-distance wireless power transmission requires the use of energy beam generation technologies in a large-scale MIMO system in order to make sure that the transmission is safe. In other words, this letter tries to maximise the energy efficiency of information transmission (bits per joule) while keeping the required quality of service (QoS), which is a delay constraint, in mind. This is done by maximising the transfer length and transmits power, among other things. In this case, we try to maximise the total amount of energy at the relays, use block diagonalization (BD) at the source, and try to minimise interference between the relay-destination channels. As a last step, we also run simulations of the power consumption of a generic circuit. As a supplement to this work, there are some basic online rules for all possible situations. Numerical results show that a near-optimal online technique can do the same job as its offline counterpart when the maximum power consumption of the circuit is taken into account.
Indoor Navigation System for Public Evacuation in Emergency Situation
Authors: Wakchaure Manoj , Tamboli Mubin , Sonkar Shrinivas 
Published: September 2022

Abstract
Today Technology has achieved wide scope of range. Nowadays we can see the different type of emergency application but most of them for outdoor navigation like GPS etc. AR in indoor navigation has become a good technology to show the right direction efficiently. In this paper, we are going to develop one application that focuses on indoor navigation using Augmented Reality technology. Using this application user will scan a QR code, then the system will recommend the shortest and efficient pathway. Generally, our system is useful in multi-floor buildings like malls, institutes, etc. Our pathfinder application will use a sensor inside the smartphone for navigation which will direct users to the emergency exit path.