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OUTWARD FOREIGN DIRECT INVESTMENT FROM INDIA IN THE SERVICE SECTOR WITH REFERENCE TO IT INDUSTRY
Growing international integration through trade and investment is the emerging scenario of the 21st century. International Investment flows, particularly Foreign Direct Investment (FDI), have become a rising manifestation of this growing global linkage between nations. Outward Foreign Direct Investments (OFDI) from India in the service sector is emerging as a significant aspect of Indias international economic integration. Firms from India are incorporating outward foreign direct investment as part of their corporate strategy to compete globally and to acquire key assets. Outward investments is being adopted as part of their global strategy to emerge as leaders in their respective domain.As the significance of outward investment rises, it is important to understand the motivation and strengths behind such flows. With rising significance of services sector, more studies to explain the nature and factors behind outward FDI assumes importance. Therefore a focus on growth of OFDI from service sector like knowledge??intensive information-technology (IT) sector has become very relevant. IT firms from India have created a global presence and brand image. It is therefore important to consider various factors which give competitive advantage to the firms. The present study is divided into six chapters. The first chapter provides an overview and introduces the research issue. The second chapter comprises of a review of literature in the area. Research Methodology is outlined in the third chapter. The fourth chapter consists of an analysis of the trends in Indian outward foreign direct investment. The fifth chapter provides the analysis and interpretation of factors influencing foreign investments by firms. The sixth chapter gives the summary and conclusions of the study. Results of the study indicate that Indias outward foreign direct investment is showing a rising trend and that there are significant changes in the pattern of these outflows. The outflows by service sector firms have increased and there is also rising investment to developed countries. The changing trend is a reflection of the global aspirations of Indian firms and their willingness to compete in the world market. The study shows that India firms, though small in comparison to multinationals from developed world, do have competitive advantage. They have leveraged these advantages and acquired strategic assets to enhance their competitive position. The firms are gaining from experience and building tacit knowledge. These skills are applied to creating a network to supplement and augment their competitive advantage. In this endeavor, macro factors are also playing a significant role. Technological and information revolution has given firms an opportunity to strengthen their competitive advantage. In this endeavor, firms in developing country like India have benefited from a vast pool of educated, skilled and technically qualified human resource. They have been facilitated by a liberalized government policy and the domestic economic climate, which has given them opportunities for entrepreneurship. Rising outward FDI is a manifestation of these changes. As Indian firms seek to strengthen their competitive positions and augment their assets, the outflow of investment to nations that have intellectual assets will increase. At the same time the traditional motive of undertaking investments to seek larger markets is still important. Though India is still a fledgling in the spectrum of outward investments, Indian firms are fast rising up to the challenge of competitive global atmosphere with aggressive strategies. Indian economy is emerging as one of the largest economies in the world. With the second largest population in the world, India has to utilize every opportunity to build sustainable growth with greater international economic linkages with rest of the world. -
Distributed denial-of-service detection and mitigation using software-defined network and internet of things
Internet of Things (IoT) is one of the promising technologies that are developing quickly in various fields such as automation, safety and health. It is a heterogeneous network that links various physical devices. It consists of a variety of vulnerabilities due to its heterogeneous nature. It makes a different level of security issues. Distributed Denial-of-service (DDoS) attack denies services to an authentic user and makes the resources of network inaccessible. DDoS attack is a significant problem for IoT. It is easy to carry out this attack on an IoT network. Main aim of the proposed methodology is to use Software-defined Network (SDN). The primary structure of proposed system is to integrate SDN and IoT technology. This combination is to provide a more secure infrastructure compare to traditional system. The secondary structure of proposed system is used to detect and mitigate the DDoS attacks. The proposed methodology is to check associativity of MAC IP address, source IP address and destination IP address. It was able to detect and mitigate the attack in short span of time. The results are compared on different parameters. That parameters are packet delay time, flow entries and average packet received per second by the controller. This hybrid method is to provide higher security and improve the Quality of Service (QoS). 2019, Institute of Advanced Scientific Research, Inc.. All rights reserved. -
Content Based Deep Factorization Framework for Scientific Article Recommender System
With the advancement in technology and the tremendous number of citations available in the digital libraries, it has become difficult for the research scholars to find a relevant set of reference papers. The accelerating rate of scientific publications results in the problem of information overload because of which the scholars spend their 70% of the time finding relevant papers. A citation recommendation system resolves the issue of spending a good amount of time and other resources for collecting a set of papers by providing the user with personalised recommendations of the articles. Existing state of art models do not take high-low order feature interactions into consideration, due to which the recommendations are not up to the desired level of performance. In this paper, we propose a content-based model which combines Deep Neural Network (DNN) and Factorization Machines (FM) where no pre-trainings are required for providing the citation recommendations. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Content Based Scientific Article Recommendation System Using Deep Learning Technique
The emergence of the era of big data has increased the ease with which scientific users can access academic articles with better efficiency and accuracy from a pool of papers available. With the exponential increase in the number of research papers that are getting published every year, it has made scholars face the problem of information overload where they find it difficult to conduct comprehensive literature surveys. An article recommendation system helps in overcoming this issue by providing users with personalized recommendations based on their interests and choices. The common approaches used for recommendation are Content-Based Filtering (CBF) and Collaborative Filtering (CF). Even though there is much advancement in the field of article recommendation systems, a content-based approach using a deep learning technology is still in its inception. In this work, a C-SAR model using Gated Recurrent Unit (GRU) and association rule mining Apriori algorithm to provide a recommendation of articles based on the similarity in the content were proposed. The combination of a deep learning technique along with a classical algorithm in data mining is expected to provide better results than the state-of-art model in suggesting similar papers. 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Document Classification for Recommender Systems Using Graph Convolutional Networks
Graph based recommender systems have time and time again proven their efficacy in the recommendation of scientific articles. But it is not without its challenges, one of the major ones being that these models consider the network for recommending while the class and domain of the article go unnoticed. The networks that embed the metadata and the network have highly scalable issues. Hence the identification of an architecture that is scalable and which operates directly on the graph structure is crucial to its amelioration. This study analyses the accuracy and efficiency of the Graph Convolutional Networks (GCN) on Cora Dataset in classifying the articles based on the citations and class of the article. It aims to show that GCN based networks provide a remarkable accuracy in classifying the articles. 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Similarity Analysis for Citation Recommendation System using Binary Encoded Data
Citations are a crucial part of an academic dissertation, project or scientific work. The most time-consuming task for any scholar is to find suitable citations for any work. Thus, a convenient citation recommendation system provides completeness and fulfillment for citing the giants' works. Moreover, attaining high quality for any citation recommendation system is challenging as it should not only recommend relevant papers but also should match the context of the paper. An advanced algorithm SABED (Similarity Analysis using Binary Encoded Data) has been proposed that converts text metadata of the article like author name, doi of the paper, keywords, abstract and content of the paper into the binary format and is fired into the database. The binary formatted query fired fetches the accurate matches thereby increasing the accuracy of search probability and similarity analysis. This similarity analysis can be further used to provide recommendations to the users. The proposed system concentrates on the similarity of the content and hence the context of the papers is not taken into consideration. 2020 IEEE. -
A Citation Recommendation System Using Deep Reinforcement Learning
Recommender systems have seen tremendous growth in the last few years due to the emergence of web services like YouTube, Netflix, and Amazon, etc. An excessive amount of data is being utilized to give proper recommendations to the users. The number of research articles getting published every day is increasing exponentially and thus an efficient model is required to provide accurate and relevant recommendations to the research scholars. The proposed Deep Reinforcement Recommender for Citations (DRRC) model uses reinforcement learning to train the available citation network to achieve the most relevant recommendations. The proposed DRRC model outperforms the state-of-the-art models. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Similarity analysis of court judgements using association rule mining on case citation data-a case study
Information Retrieval System (IRS) is an automated mechanism of retrieving required information from a collection of unstructured or semi-structured data. IRS reduces the efforts of identifying the required information from an enormous database. Legal domain is one of the major producers of complex information which consist of semi-structured and unstructured data. Knowledge based legal information systems are revolutionizing all processes involved in this domain and hence need for more effective legal knowledge management approaches are increasing. This paper proposes association rule mining as knowledge extraction technique that can be used effectively for analyzing relatedness of documents in legal domain. Through this work, authors present their efforts in analyzing similarity in legal documents from the citations done in court judgement by applying Association rule mining. International Research Publication House. -
Melamine derived N-doped Carbon nanotubes: A durable catalyst support for Pt nanoparticles in proton exchange membrane fuel cell
A cost-effective thermal pyrolysis route was adopted to synthesize N-doped carbon nanotube (NCNT) in a single step with the aid of melamine (carbon and nitrogen source) and cobalt catalyzed growth for the formation of N-doped carbon nanotubes. The NCNT was acid treated (fNCNT) to remove the metallic Co from the CNT which was elucidated using X-ray diffraction. Even though these noble metal-free materials are explored as Oxygen reduction reaction (ORR) electrocatalyst, for it to be employed in actual fuel cell the cathode requires noble metals such as Platinum (Pt) nanoparticles to improve its sluggish kinetics. Thus, this study is mainly focused on employing fNCNT as catalyst support in PEMFC, wherein the electrocatalyst was synthesized using microwave-assisted polyol method to decorate Pt nanoparticles on fNCNT, demonstrating its excellent durability of 32% electrochemical active surface area (ECSA) loss when subjected to standard protocols, and full cell performance of hybrid ((Pt/fNCNT) + CB) 412 mW cm?2 (better than commercial Pt/C) when deployed as electrocatalyst for ORR in Polymer electrolyte membrane (PEM) fuel cell, thus our findings open new avenues to explore, design and develop N-doped carbon nanotubes as durable catalyst for fuel cells. Graphical abstract: (Figure presented.) The Author(s), under exclusive licence to Springer Nature B.V. 2024. -
A facile one-step microwave synthesis of Pt deposited on N & P co-doped graphene intercalated carbon black - An efficient cathode electrocatalyst for PEM fuel cell
A facile, single step microwave assisted polyol route for simultaneously depositing platinum as well as co-doping graphene oxide, is herein proposed. However, low durability and full cell performance of Pt/NPG (platinum deposited on nitrogen phosphorous co-doped graphene) was observed due to restacking of graphene layers. This issue was addressed by intercalating CB into the graphene layers as spacers during the synthesis (in-situ addition of spacers - Pt/(NPG + S)). Moreover, to study the influence of spacers, external addition of spacers (ex-situ - Pt/(NPG) + S) were also examined. Results from our study indicate that in-situ addition of spacers- Pt/(NPG + S) enhanced the full cell performance (405 mW cm?2) and exhibited <40% ECSA loss (37.47%), thereby attaining DoE target. Thus, emerging as a durable cathode electrocatalyst (Pt/(NPG + S)) for PEM fuel cells. 2022 Hydrogen Energy Publications LLC -
Carbon-Based and TMDs-Based Materials as Catalyst Support for Fuel Cells
Global energy consumption and environmental pollution caused by the extensive use of fossil fuels have increased the need to look forward to more renewable energy sources. Fuel cell, one of the promising energy conversion devices, has the potential to outsmart the existing devices but has several setbacks to be employed on a larger scale. One of the hindrances is the sluggish oxygen reduction reaction kinetics at the cathode and hence requires electrocatalysts to improve its overall performance. This chapter provides a brief overview of graphene and transition metal dichalcogenides (TMDs)- based composites that have the potential to be used as a catalyst support. 2024 World Scientific Publishing Company. -
ARise to the occasion: Elevating customer engagement
Augmented reality (AR) is being used to transform the landscape of online retail by enhancing customer engagement and experience. This chapter delves into how AR's unique capabilities, such as virtual try-on and interactive product visualisation, can overcome the limitations of traditional online shopping and create deeper connections between brands and consumers. It explains how AR personalises the customer journey by providing customised product recommendations and immersive virtual experiences that drive purchase decisions. By analysing past implementations and future trends, this chapter demonstrates how ARM can usher in a new era of customer engagement and personalised experiences in online retail. 2024, IGI Global. All rights reserved. -
One-step synthesized Pt-dispersed N, P co-doped graphene as an efficient oxygen reduction reaction ORR electrocatalyst
A simple yet effective strategy to simultaneously deposit Platinum and co-doped (Nitrogen & Phosphorous) graphite oxide (rGO) using microwave irradiation has been carried out, labeled as Pt/NP-rGO. The successful deposition of Pt was confirmed using X-ray diffractogram (XRD), transmission electron microscope (TEM), and selected area electron diffraction (SAED) pattern. The Pt particles with average size of 3.5nm were deposited during microwave irradiation. Further, co-doping was confirmed using X-ray photoelectron spectroscopy (XPS). The synthesized Pt/NP-rGO was analyzed in situ as an oxygen reduction reaction electrocatalyst in acidic medium. Our results indicate that Pt/NP-rGO follows a four e? ORR process attributed to increased adhesion between the Pt and N, P co-doped graphene oxide due to e? transfer from graphene to N and P atoms, thus indicating its potential in energy-related applications as an effective ORR electrocatalyst. The Author(s), under exclusive licence to The Materials Research Society 2024. -
Application of Corn Oil Derived Carbon Nano-onions Using Flame Pyrolysis as Durable Catalyst Support for Polymer Electrolyte Membrane Fuel Cells
The reliance of carbon black as catalyst support for Pt in PEM fuel cell has posed a major challenge in its durability as carbon blacks are highly prone to corrosion. As an alternative, CNTs, CNFs, and graphene are explored as catalyst support, however at the expense of tedious synthesis procedure and production cost. So to combat this issue, a facile flame pyrolysis route was adopted to produce carbon nano-onions using eco-friendly corn oil. Further modification in the carbon nano-onions exhibited better corrosion resistance in comparison to carbon black (Vulcan XC-72R). Also, a systematic approach was adopted towards developing a durable electrocatalyst which was designed to withstand harsh fuel cell operating conditions. The electrocatalyst was successfully analyzed using stringent standard testing protocols (< 40% ECSA loss). Among all the electrocatalyst studied, Pt/fOC exhibited only 37.1% loss in electrochemical active surface area (ECSA) after 5000 cycles, thus indicating its excellent durability. A full cell was also constructed with Pt/fOC as cathode electrocatalyst which showed a maximum power density of 365 mW cm?2, comparable to commercial Pt/C (367 mW cm?2). To the best of our knowledge, this is the first study on the application of corn oil derived carbon nano-onions as catalyst support for PEM fuel cells. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024. -
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Understanding the technological evolution in electronic payments system in India and the acceptance
Banking in India has seen amazing technical and infrastructure advancements during the last two decades. Businesses can use the payment and settlement system to receive and make payments for goods and services, as well as to repay money. The RBIs commitment to providing the general population with low-cost, accessible, and all-inclusive payment services has contributed in the quick acceptance and paradigm shift from paper to electronic medium. Using the larger TAM model, this article evaluates payment technology advancements from 2019 through 2022. According to the study, there was a 100% rise in UPI/IMPS and a 40% increase in NEFT compared to December 2018. The paper discusses the acceptability of the paradigm transition from paper to electronic payment media. The papers scope is limited to three years, from January 2019 to December 2021. The study contributes to various findings and insights on Indias embrace of digital payment and the payment paradigm change. 2024 Inderscience Enterprises Ltd. -
Gut Microbiome Characterisation of Chrysomya megacephala: Isolation, Identification, Antibiotic Profiling, and Initial Documentation of Leclercia adecarboxylata from the Fly
Chrysomya megacephala, known for its vector potential, harbors a diverse microbiota crucial in understanding disease transmission dynamics. Herein, we report the first documentation of Leclercia adecarboxylata isolated from C. megacephala. L. adecarboxylata is an Enterobacteriaceae, gram-negative bacillus that cause infections in human and animals. Additionally, we have reported the presence of Pseudomonas aeruginosa and Enterococcus faecalis from C. megacepahala. The study carried out the antibiotic profiling and hemolytic assays, which revealed distinct resistance patterns and virulence characteristics, shedding light on potential public health implications. L. adecarboxylata, Pseudomonas aeruginosa and Enterococcus faecalis showed positive result for hemolysis and in terms of antibiotic resistance P. aeruginosa strains showed resistance to Amoxicillin, Ampicillin and Tetracycline while, E. faecalis showed resistance towards Streptomycin and Tetracycline. However, L. adecarboxylata showed sensitivity to all antibiotics. This study was conducted from Kozhikode, Kerala, India, and this is the first of its kind of study from the region to analyse the vector potential of C. megacephala. These findings underscore the significance of comprehensive microbiological investigations in vector-borne disease surveillance and management strategies. The Author(s) 2024. -
"Case" as "text" in the class: Plethora of pedagogical and structural nuances
The research work undertakes to examine "case, ? "case study, ? and "case pedagogy. ? As the first step, the chapter explores the feel of the Case. This leads to a further investigation and lets out certain malfunctions: gross lapses, loopholes, casualties, and shortcomings. Case then has been subjected to further investigations. Keeping intact the primary concerns of case scan and its explications thereupon, the study takes up the interpretations and intricacies involved in understanding the case. These expose the puzzles involved in the pedagogical exercises in educational institutions. The research with astute expedience does the operation with logical reasoning. The work leads to proper remedial measures and redefines case and case grasp. Using theory of ontology, case is subjected to closer examination. Theory of epistemology further deepens research pursuits to unravel a few more case mysteries. From these, the authors evolve a few keys and tips to study case more effectively. All help readers build up exemplary teaching methods and effective learning concepts. 2022, IGI Global. All rights reserved. -
Enhancement of free convection from horizontal-base straight-fin heat sink by partial shrouding
This work presents a simple method to improve natural convection heat transfer performance of horizontal-base straight-fin heat sink by adding partial shroud plates on top of the heat sink at both ends. Experiments are conducted in conjunction with a detailed three-dimensional (3D) computational study. The numerical model is validated using experimental results. With partial shrouding, the modification and effective utilization of airflow surrounding the heat sink leads to significant heat transfer enhancement. The installation of shroud plates effectively improves the mass flowrate of air admitted into the fin channel. Further, the airflow drawn above the heat sink dissipates heat from the upper surface of the shroud plate. There is also a significant heat dissipation from the lower surface of the shroud plate which is exposed to cold air drawn from the side-end of the heat sink. The heat transfer from the existing optimal conventional heat sink is improved by 17% with the introduction of shroud plates. An optimal width of the shroud plate is identified to exist for the maximum heat transfer. The percentage enhancement in heat transfer achieved by partial shrouding increases with a decrease in the fin height and with an increase in the fin spacing. The proposed compact heat sink design would be of application in enhancing passive heat dissipation from light-emitting diode (LED) lights and other electronic devices, especially when size constraints exist. Copyright 2020 by ASME -
Visual Culture, Spectatorship and Humanitarian Disaster: Vanni Eli and the Representation of the Sri Lankan Civil War
This article examines the dialogic encounter between the spectator and the spectacle in the context of war crimes and humanitarian disasters (in this context, the Sri Lankan civil war) in Vanni Eli, a short film by a Sri Lankan Tamizh diasporic filmmaker Tamiliam Subhas. The narrative introduces us not only to the military disaster that is war but also to the humanitarian disasters effected through war. The article studies the role of the spectator who 'witnesses' the torture, and thus complicates the ethics of both the act of torture and the viewing of it.By looking closely at the ingenious ways of narrating torture the article argues that the creative representation of war and disaster implicates within its discourse not merely the participants and the victims of the war alone but also the 'peripheral' subjects like the mice (the film's lead 'actors'), and by extension, the spectators participating in the discursive construction of the victimized. Despite the symbolic disembodiment and effacement of the tortured, their suffering is recognized as a humanitarian disaster with the shared grammar of suffering common to all. 2012 Mudra Institute of Communications.