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A survey on next-generation Mixed Line Rate (MLR) and energy-driven Wavelength-Division Multiplexed (WDM) optical networks /
Journal of Optical Communications, Vol.36, Issue 2, pp.516-532, ISSN No: 2191-6322. -
A Survey on P4 Challenges in Software Defined Networks: P4 Programming
Software Defined Networking (SDN) has been a prominent technology in the last decade that increases networking programmability. The SDN philosophy decouples the application, control, and data plane to increase the network programmability. The data plane is an essential but unsolved component that receives less attention than control and application planes. Traditionally, the data plane uses fixed functions that forward packets using a limited number of protocols. The P4 (Programming Protocol-independent Packet Processors) language makes it possible to program SDN data plane, which push the SDN to the next level. In the research community and industry, programming the data plane has garnered significant attention. Surprisingly, there has been no comprehensive reviews of programmable data-plane switches, which have many advantages in today's networks. The authors reviewed the evolution of networks from legacy to programmable data planes, explained the fundamentals of programmable switches, and summarized the network generation from traditional to programmable networks. In this paper, SDN is described from a P4-centric standpoint and discusses over 75 related research papers. Several taxonomies for the field are provided, outline potential research areas, and provide greater details regarding the patterns that have led to the development of this technology. 2013 IEEE. -
A Survey on Solution of Imbalanced Data Classification Problem Using SMOTE and Extreme Learning Machine
Imbalanced data are a common classification problem. Since it occurs in most real fields, this trend is increasingly important. It is of particular concern for highly imbalanced datasets (when the class ratio is high). Different techniques have been developed to deal with supervised learning sets. SMOTE is a well-known method for over-sampling that discusses imbalances at the level of the data. In the area, unequal data are widely distributed, and ensemble learning algorithms are a more efficient classifier in classifying imbalances. SMOTE synthetically contrasts two closely connected vectors. The learning algorithm itself, however, is not designed for imbalanced results. The simple ensemble idea, as well as the SMOTE algorithm, works with imbalanced data. There are detailed studies about imbalanced data problems and resolving this problem through several approaches. There are various approaches to overcome this problem, but we mainly focused on SMOTE and extreme learning machine algorithms. 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
A survey on the intersection graphs of ideals of rings
Let L(R) denote the set of all non-trivial left ideals of a ring R. The intersection graph of ideals of a ring R is an undirected simple graph denoted by G(R) whose vertices are in a one-to-one correspondence with L(R) and two distinct vertices are joined by an edge if and only if the corresponding left ideals of R have a non-zero intersection. The ideal structure of a ring reects many ring theoretical properties. There is so much research that has been conducted during the last decade to explore the properties of G(R). This is a survey of the developments in the study on the intersection graphs of ideals of rings since its introduction in 2009. 2022 by the authors. -
A survey on various applications of internet of things on blockchain platform
[No abstract available] -
A Survey on Various Handoff Methods in Mobile Ad Hoc Network Environment
Communication has never been the same since the advent of cellular phones and numerous applications with different functionalities seem to crop up on a daily basis. Various applications seem to crop up on a daily basis. Ad hoc networks were developed with the intent of creating networks made up of interconnected nodes, on-the-go. Ad hoc networks have numerous applications, the most popular being vehicular ad hoc networks (VANETs). In VANETs, moving vehicles are considered to be the mobile nodes and mobile vehicular nodes move at high speeds. Mobility of the nodes makes it difficult to maintain stable communication links between the nodes and the access points. A process known as handoff is used to bridge this gap and is considered to be one of the solutions for unstable communication links over larger distances. Handoff can usually be seen when the nodes are mobile and start to move away from the access points. This paper discusses and compares various handoff methods that were proposed by various researchers with an intent to increase positive attributes while negating the rest of the components that do not support in increasing the efficiency of the handoff process. 2020, Springer Nature Singapore Pte Ltd. -
A Sustainability Approach to Geopolymer Brick Manufacture Using Mine Wastes
India has tons of by-products of industries like fly ash, ground granulated blast furnace slag (GGBS), and mine tailings from different ores. By incorporating these wastes in bricks, the carbon footprint can be minimized. This research pivots around the use of iron ore tailings (IOT) and slag sand as a substitute for clay or shale in the manufacture of stabilized geopolymer blocks. Iron ore tailings and slag sand were used for substitution in the range of 20-40% and 15-40% with increments of 5%. Fly ash, ground granulated blast furnace slag, and sodium silicates (Na2SiO3) were used with a constant value of 15%. The bricks were cast and cured at ambient temperature. The study includes testing of mechanical properties of geopolymer bricks as per IS recommendations. To study the macroanalysis, SEM and XRD analyses were also carried out on raw materials and developed composites. The outcomes of this investigation show that the inclusion of 25% of IOT and 30% of slag sand is acceptable as brick material. Springer Nature Singapore Pte Ltd. 2022. -
A sustainable approach for fish waste valorization through polyhydroxyalkanoate production by Bacillus megaterium NCDC0679 and its optimization studies
Polyhydroxyalkanoates (PHAs) are considered as the only class of truly biodegradable and biocompatible polymers. Although extensive research has been carried out in producing them from a wide variety of organisms, their commercialization still faces hurdles majorly associated with the cost of production media. This research work exploits the use of discarded fish scale waste as a major media component for biopolymer production. The major novelty of the research work is the utilization of a Bacillus megaterium NCDC0679 for PHA production using fish scale waste that is not reported previously. Furthermore, a sequential and systematic statistical optimization strategy employing response surface methodology was used to trace out the level of the most significant variables and their interaction effects on PHA production add to the significant novelty of this work. The significance of the model developed was determined from the p values of ANOVA. Under optimized levels of glucose (50g/L), NaCl (0.125g/L), and fish scale hydrolysate concentration (62.5% v/v), maximum PHA yield of 6.33g/L was achieved in the shake flask culture system. This was found to be 5.50-fold higher than the unoptimized medium. The ANOVA results established the significance of the model (p < 0.05). The extracted polymer was characterized through Fourier-transform infrared (FTIR), nuclear magnetic resonance (NMR), X-ray diffraction (XRD), differential scanning calorimetry (DSC), and thermogravimetric analysis (TGA). Thus, the present investigation suggests an innovative method for valorization of fish scale waste for commercial production of PHA. 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature. -
A sustainable non-enzymatic approach for determination of cholesterol using piper nigrum derived porous carbon/?-Fe2O3 composite electrode
Activated porous carbon (APC) obtained from Piper nigrum along with ?-Fe2O3 have been used to modify carbon paste electrode (CPE) for the highly sensitive and selective electrochemical determination of cholesterol. The enhanced synergistic properties observed between the biomass-derived APC and ?-Fe2O3 uplifts the electrocatalytic activity of the modified electrode (APC-Fe2O3/CPE). The prepared ?-Fe2O3 nanoparticles were characterised by Fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), Dynamic light scattering (DLS), zeta potential measurements and Thermogravimetric analysis (TGA). High resolution transmission electron microscopy (HRTEM), Field emission scanning electron microscopy (FESEM), X-ray diffraction (XRD) and electrochemical techniques were used to study the physico-chemical properties of the modified electrodes. Experimental conditions such as effect of pH, scan rate and concentration of cholesterol were optimized. Wide linear dynamic range between 25 nM and 300 nM, low limit of detection (LOD) and limit of quantification (LOQ) of 8 nM and 26 nM respectively make the method very effective and sensitive. Cholesterol in human blood serum samples was non-enzymatically determined using the developed method. 2021 The Electrochemical Society. -
A SWOT analysis of integrating cognitive and non-cognitive learning strategies in education
Students must receive the knowledge and skills they require for succeeding in a constantly changing world. Meeting each student's diverse needs, nevertheless, is difficult. For the purpose to promote student development and improve educational outcomes, this review study attempts to give a thorough conceptual framework for integrating both cognitive and non-cognitive learning methodologies. While non-cognitive learning focuses on social and interpersonal skills, emotional intelligence, and resilience, cognitive learning involves the acquisition of intellectual skills and critical thinking. Both types of education are essential for children's holistic development. Integrating non-cognitive and cognitive approaches in education sector has several advantages. It promotes a well-rounded education by offering a balanced approach that addresses the intellectual, emotional, and social elements of student progress. To support the suggested conceptual framework, a thorough analysis of recent research on the subject is conducted. The implementation of cognitive and non-cognitive learning in the present condition is examined through a bibliometric analysis, which identifies research trends and gaps. In addition, a SWOT analysis has been done to assess the advantages, disadvantages, opportunities, and threats related to these strategies. The issues and areas that require additional research and development are better understood due to this analysis. The research's conclusions demonstrate the importance of adopting a well-rounded educational strategy which considers various demands of students. The education system can encourage academic performance, critical thinking, socio-emotional well-being, and prepare students for success in a variety of spheres of life by integrating cognitive and non-cognitive learning. It also points out the research gaps and underlines the value of further study for enhancing comprehension and cognitive and non-cognitive learning methodologies' application. 2024 John Wiley & Sons Ltd. -
A synbiotic composition and application thereof /
Patent Number: 202041045417, Applicant: Alok Kumar Malaviya. -
A system and method based on neural network and hidden markov modelling for predicting drug property /
Patent Number: 202141030994, Applicant: Mr.Katikireddy Srinivas. -
A system and method for evidence base practice in education /
Patent Number: 202111058901, Applicant: Roopali Sharma.
A system (1) for evidence base practice in education comprising student data module; teacher data module (3); researcher data module (4); industry expert data module (5); server (6); network (7); student interest module (8); counselling module (9); concept clearing module (10); wherein each module is comprising a computer system websites which are accessible to the network and whole data of the modules is stored in the server (6). -
A system and method for integrated monitoring, control and management of various parameters of agriculture and crop growth and a device for implementing the same /
Patent Number: 202041010535, Applicant: S Rakesh Kumar.
A system and method for integrated monitoring and management of vital agricultural parameters that are key for sustained plant growth and enhanced crop output, qualitatively and quantitatively is provided. The key aspects of sustained and healthy growth of agricultural crops, viz., temperature, moisture, humidity are monitored and controlled through means, comprising of temperature sensor, soil moisture sensor, motor pump progressively controlled by Arduino and the collated data are displayed through screen. -
A system and method for managing goods using their information /
Patent Number: 202121047598, Applicant: Anil Kumar.
A system (100) and method (100A) for managing goods using their information comprising a RFID reader (101), weherin RFID reader reading an RFID tag; an antenna (102) for identifying a tag, communication unit receiving a RFID tag value extracted by reading the RFID tag (103) from an RFID reader (101) of a transferor of an object with an attached RFID tag (103); a display unit (107) comprises a display (106) and a communication unit (105); a processing and control device (104) for mapping information of the tag. -
A system for automatic pallet changer in warehouse by using machine learning /
Patent Number: 202141042804, Applicant: Dr. G. Balakrishnan.
The system for automatic pallet changer in warehouse by using machine learning comprising to automatic pallet changer in warehouse. More particularly present invention relates to the automatic pallet changer using by machine learning system and technique by use of its supporting members and also receiving actual-time robotics information and using the real-time robotics statistics to decide an amount of time to rearrange the pallets to the premier layout and determine out the most reliable controlled-get admission to dense grid layout to which to set up the pallets is further based totally on predetermined pallet locations in the warehouse for precise pallets, and in which, within the most suitable managed-get entry to dense grid format, the particular pallets are located on the predetermined pallet places also most appropriate deep lanes format, pallets having objects expected to be shipped out of the warehouse within a threshold period of time from a present date. -
A system for confidential inference and model protection using secure multi-party computation /
Patent Number: 202241004611, Applicant: Kapil Tiwari.
The present invention relates to probabilistic inference based on secure multi-party computation (SMPC) techniques, and more particularly to Confidential Inference and Model Protection. The present invention addresses the privacy concern of model owners and ML client, by using the confidential inference and model protection aka CoInMPro, a technique to boost privacy of model parameters and client input during ML inference without affecting accuracy by paying a marginal performance cost. -
A system for confidential inference and model protection using secure multi-party computation /
Patent Number: 202241004611, Applicant: Kapil Tiwari.
The present invention relates to probabilistic inference based on secure multi-party computation (SMPC) techniques, and more particularly to Confidential Inference and Model Protection. The present invention addresses the privacy concern of model owners and ML client, by using the confidential inference and model protection aka CoInMPro, a technique to boost privacy of model parameters and client input during ML inference without affecting accuracy by paying a marginal performance cost. -
A system for confidential training and inference for vertically partitioned dataset using secure multi-party computation /
Patent Number: 202241057386, Application: Kapil Tiwari.
The present invention applies to probabilistic inference employing secure multi-party computation (SMPC) methodologies including confidential training, inference, and model protection for vertically partitioned datasets. The proposed invention addresses privacy
complexities of vertically partitioned data owners, model owners, and ML clients using confidential training, inference, and model protection (CoTraIn-VPD), a technique to boost data, model parameter, and client input privacy during ML inference without affecting accuracy or performance. -
A system for confidential training and inference for vertically partitioned dataset using secure multi-party computation /
Patent Number: 202241057386, Application: Kapil Tiwari.
The present invention applies to probabilistic inference employing secure multi-party computation (SMPC) methodologies including confidential training, inference, and model protection for vertically partitioned datasets. The proposed invention addresses privacy complexities of vertically partitioned data owners, model owners, and ML clients using confidential training, inference, and model protection (CoTraIn-VPD), a technique to boost data, model parameter, and client input privacy during ML inference without affecting accuracy or performance.