Sudhanshu Kumar

This book presents a comprehensive assessment of anti-cartel enforcement and investigative procedures in India. It makes a case for enhanced sanctions for cartel conduct in India. Cartels are considered the most pernicious violation of competition law, referred to as "cancer to the free market economy". While competition laws in most jurisdictions prescribe strict sanctions against cartels, Indian Competition Law provides only civil penalties, with an upper ceiling for proven cartel conduct. This volume assesses the effectiveness of anti-cartel enforcement of the Competition Commission of India (CCI). It explores investigative procedures of the CCI through multiple qualitative and quantitative indicators and the extent to which enforcement of anti-cartel laws in India has led to cartel deterrence. Further, it also examines the priorities and processes of the CCI in terms of anti-cartel enforcement, their sanctioning mechanism and their dependency of computation of penalty on varied factors. Featuring detailed case law studies and engaging data, this book will be an essential read for students and researchers of law and legal studies, competition law, corporate law, intellectual property law, and business law.

Nell'ambito degli obiettivi globali sostenibili, la crescita economica una delle principali sfide che ogni parte del mondo deve affrontare. L'Odisha, uno degli Stati orientali in via di sviluppo dell'India, possiede molti luoghi turistici noti che possono contribuire alla generazione di reddito e alla crescita economica. Di recente, il governo ha pianificato di trasformare alcuni luoghi turistici in "centri di eco-ritiro", in modo da attirare un maggior numero di turisti in questi luoghi. Per raggiungere questo obiettivo, il feedback dei turisti deve essere analizzato a fondo, in modo da migliorare la qualit del servizio e la crescita del settore turistico. In questo contesto, viene proposto un framework di sentiment analysis basato sugli aspetti, basato sulle recensioni di Google map fornite dai turisti sulla localit turistica di Konark. Inizialmente, le recensioni online vengono analizzate utilizzando Selenium. Successivamente, viene proposto un metodo di apprendimento per trasferimento che utilizza e mette a punto il modello BERT. Le prestazioni vengono confrontate con quelle di altri modelli all'avanguardia. Inoltre, per migliorare la velocit di scraping delle recensioni, viene proposto un algoritmo di aggregazione incrementale delle recensioni (IRA). Per una migliore comprensione degli aspetti, si propone anche l'apprendimento a breve termine e a pochi scatti con GPT3. Infine, viene sviluppata un'applicazione web-based per automatizzare le attivit .

Im Hinblick auf die nachhaltigen globalen Ziele ist das Wirtschaftswachstum eine der gr ten Herausforderungen f r jeden Teil der Welt. Odisha, einer der sich entwickelnden stlichen Bundesstaaten Indiens, verf gt ber viele bekannte Touristenorte, die zur Einkommensgenerierung und zum Wirtschaftswachstum beitragen k nnen. K rzlich hat die Regierung des Bundesstaates geplant, einige Touristenorte zu " ko-Retreat-Zentren" zu machen, die mehr Touristen an diese Orte locken k nnen. Um dieses Ziel zu erreichen, muss das Feedback der Touristen gr ndlich analysiert werden, um sowohl die Qualit t der Dienstleistungen als auch das Wachstum des Tourismussektors zu verbessern. In diesem Zusammenhang wird ein aspektbasierter Stimmungsanalyserahmen vorgeschlagen, der auf Google-Map-Bewertungen basiert, die von Touristen f r den Touristenort Konark abgegeben wurden. Zun chst werden die Online-Bewertungen mit Selenium ausgewertet. Dann wird eine Transfer-Learning-Methode vorgeschlagen, die das BERT-Modell nutzt und fein abstimmt. Die Leistung wird mit anderen modernen Modellen verglichen. Zur Verbesserung der Geschwindigkeit beim Abwracken von Bewertungen wird ein inkrementeller Bewertungsaggregator-Algorithmus (IRA) vorgeschlagen. F r ein besseres Verst ndnis der Aspekte werden auch Prompt-Engineering und "few-shot learning" mit GPT3 vorgeschlagen. Schlie lich wird eine webbasierte Anwendung entwickelt, um die Aufgaben zu automatisieren.

Dans le cadre des objectifs mondiaux durables, la croissance conomique est l'un des principaux d fis relever dans toutes les r gions du monde. L'Odisha, l'un des tats orientaux en d veloppement de l'Inde, poss de de nombreux sites touristiques r put s qui peuvent contribuer la g n ration de revenus et la croissance conomique. R cemment, son gouvernement a pr vu de faire de certains lieux touristiques des "centres d' co-retraite", ce qui peut attirer davantage de touristes dans ces lieux. Pour atteindre cet objectif, les commentaires des touristes doivent tre analys s en profondeur, ce qui permettra d'am liorer la qualit du service et la croissance du secteur touristique. Dans ce contexte, un cadre d'analyse des sentiments bas sur les aspects est propos sur la base des avis donn s par les touristes sur la carte Google pour le site touristique de Konark. Dans un premier temps, les avis en ligne sont scrapp s l'aide de Selenium. Ensuite, une m thode d'apprentissage par transfert est propos e en utilisant et en affinant le mod le BERT. Les performances sont compar es d'autres mod les de pointe. En outre, pour am liorer la vitesse de suppression des avis, un algorithme d'agr gation incr mentale d'avis (IRA) est propos . L'ing nierie rapide et l'apprentissage court terme avec GPT3 sont galement propos s pour une meilleure compr hension des aspects. Enfin, une application web est d velopp e pour automatiser les t ches.

No mbito dos objectivos globais sustent veis, o crescimento econ mico um dos principais desafios enfrentados por qualquer parte do mundo. Odisha, um dos estados orientais em desenvolvimento da ndia, tem muitos locais tur sticos bem conhecidos que podem contribuir para a gera o de receitas e para o crescimento econ mico. Recentemente, o seu governo planeou transformar alguns locais tur sticos em "centros de retiro ecol gico", o que pode atrair mais turistas para esses locais. Para atingir este objetivo, o feedback dos turistas deve ser analisado minuciosamente, o que permitir melhorar a qualidade do servi o e o crescimento do sector do turismo. Neste contexto, proposto um quadro de an lise de sentimentos baseado em aspectos, com base nas opini es de turistas no mapa do Google sobre o local tur stico de Konark. Inicialmente, os coment rios em linha s o eliminados utilizando o Selenium. Em seguida, proposto um m todo de aprendizagem por transfer ncia utilizando e afinando o modelo BERT. O desempenho comparado com outros modelos topo de gama. Al m disso, para aumentar a velocidade de elimina o das cr ticas, proposto um algoritmo Incremental Review Aggregator (IRA). Prop e-se tamb m uma engenharia r pida e uma aprendizagem de poucos disparos com GPT3 para uma melhor compreens o dos aspectos. Finalmente, desenvolvida uma aplica o baseada na Web para automatizar as tarefas.

In the sustainable global goals, economic growth is one of the major challenges faced by any part of the world. Odisha, one of the developing eastern state of India, has many well-known tourist places which can contribute to revenue generation and economic growth. Recently, its government has planned to make some tourist places as "eco-retreat centers" which can attract more tourist to these places. To achieve this objective, the tourist feedback must be analyzed thoroughly which will enhance both quality of service and growth in tourism sector. In this context, an aspect-based sentiment analysis framework is proposed based on Google map reviews given by tourists on Konark tourist spot. Initially, the online reviews are scrapped using Selenium. Then a transfer learning method is proposed utilizing and fine tuning BERT model. The performance is compared with other state-of-the-art models. Further, to enhance the reviews scrapping speed, an Incremental Review Aggregator (IRA) algorithm is proposed. Prompt engineering and few-shot learning with GPT3 is also proposed for better understanding of the aspects. Finally, a web-based application is developed to automate the tasks.

This book presents a comprehensive assessment of anti-cartel enforcement and investigative procedures in India. It makes a case for enhanced sanctions for cartel conduct in India. Cartels are considered the most pernicious violation of competition law, referred to as "cancer to the free market economy". While competition laws in most jurisdictions prescribe strict sanctions against cartels, Indian Competition Law provides only civil penalties, with an upper ceiling for proven cartel conduct. This volume assesses the effectiveness of anti-cartel enforcement of the Competition Commission of India (CCI). It explores investigative procedures of the CCI through multiple qualitative and quantitative indicators and the extent to which enforcement of anti-cartel laws in India has led to cartel deterrence. Further, it also examines the priorities and processes of the CCI in terms of anti-cartel enforcement, their sanctioning mechanism and their dependency of computation of penalty on varied factors. Featuring detailed case law studies and engaging data, this book will be an essential read for students and researchers of law and legal studies, competition law, corporate law, intellectual property law, and business law.