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Two dimensional fuzzy context-free languages and tiling patterns
Fuzzy context-free languages are powerful compared to fuzzy regular languages as they are generated by fuzzy context-free grammars and fuzzy pushdown automata, which follow an enhanced computational mechanism. A two dimensional language (picture language) is a collection of two dimensional words, which are a rectangular array of symbols made up of finite alphabets. Two dimensional automata can recognize two dimensional languages that could not be recognized by one dimensional automata. In this paper, we introduce two dimensional fuzzy context-free languages generated by the two dimensional fuzzy context-free grammars and accepted by the two dimensional fuzzy pushdown automata in order to deal with the vagueness that arises in two dimensional context-free languages. We can construct a two dimensional fuzzy context free grammar from the given two dimensional fuzzy pushdown automata and vice versa. In addition, we prove that two dimensional fuzzy context-free languages are closed under union, column concatenation, column star, homomorphism, inverse homomorphism, reflection about right-most vertical, reflection about base, conjugation and half-turn and also show that two dimensional fuzzy context-free languages are not closed under matrix homomorphism, quarter-turn and transpose. Further, we have given the applications and the uses of closure properties in the formation of tiling patterns. 2024 Elsevier B.V. -
On Two-Dimensional Approximate Pattern Matching Using Fuzzy Automata
Pattern matching has been extensively studied in the last few decades, owing to its great contribution in various fields such as search engines, computational biology, etc. Several real-life situations require patterns that allow ambiguity in specified positions. In this paper, one-dimensional and two-dimensional approximate pattern matching models have been constructed using fuzzy automata. The similarity function used in fuzzy automata enables the occurrence of all exact and similar one-dimensional and two-dimensional patterns. This kind of searching approximate patterns is not possible with regular search models. The time complexity of the proposed algorithm has also been analyzed. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
PICTURE PROCESSING ON ISOMETRIC FUZZY REGULAR ARRAY LANGUAGES
Isometric array grammar is one of the simplest model to generate picture languages, since both sides of its production rule have the same shape. In this paper, we have introduced isometric fuzzy regular array grammars to generate isometric fuzzy regular array languages and discussed its closure properties. Also, the relation between isometric fuzzy regular array grammar and boustrophedon fuzzy finite automata has been discussed. Moreover, we study the relation between two dimensional fuzzy regular grammars with returning fuzzy finite automata and boustrophedon fuzzy finite automata. Further, the hierarchy results of these three classes of languages have been discussed. 2024 KSCAM. -
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Statistical Learning inPharmacovigilance: A Data-Driven Approach to AI-Enhanced Drug Safety Monitoring
Pharmacovigilance is transforming at warp speed in response to big data and advanced analytical techniques. This paper will provide an overview of where pharmacovigilance currently stands by focusing on integrating artificial intelligence (AI), machine learning (ML) and real-world data (RWD) in order to improve drug safety monitoring. These new methods are increasingly supplementing traditional ones which serve as their base. The purpose of this survey is to assess how effective they are, point out the major challenges standing in their way as well as offer recommendations for future research. In conclusion, although AI and ML could prove helpful especially with handling large volume and complexity of datasets, there is a need for tackling data quality, integration issues and regulatory acceptance concerns first. Standardized methodologies should be worked out and collaboration among all stakeholders encouraged so as to maximize the pharmacovigilance benefits that can come from these technologies. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2026. -
Quantitative X-ray and Spectroscopic Analysis of Nanocrystalline and Amorphous Carbon Materials
Carbon and its various allotropic forms is a blooming and extensively investigated field for the past few decades. The revolution which started with the discovery of fullerenes in 1985 continues with the newly discovered wonder material graphene and has never failed to amass the interest of scientific community. After all these years it still stays as a hot topic of research. This is primarily due to their unique physical and chemical properties which makes them suitable for a whole host of applications ranging from thin film technology to nano-medicine. But, the production cost of these novel materials is an issue which shadows its glory and hence it is essential to find out efficient and cost effective sources and production methods for these materials. Graphene oxide has attracted much interest because of its low cost, easy access and unique ability to get converted into graphene. Graphene oxide is basically, a graphene sheet which consists of either carboxyl or hydroxyl groups. Foreseeing the upcoming era of carbon nanomaterials on account of their revolutionary applications and the ever increasing demand for economical and viable sources, we have identified and explored the structural parameters of an efficient and cost effective precursor of the same. In the present investigation, wood charcoal and coconut shell charcoal, which is a superior source of activated carbon, is produced by a slow thermal decomposition method in a limited supply of oxygen. It is an impure form of carbon- is a black residue composed mainly of carbon, ash and char. Wood charcoal is transformed into Graphite oxide (GO) by a modified Hummers method. Spectroscopic analysis of the samples is carried out by various techniques such as X-ray diffraction (XRD), Raman Spectroscopy, Fourier Transform Infrared Spectroscopy (FTIR), X-ray Photoelectron Spectroscopy (XPS), UV-Vis spectroscopy and Scanning Electron Microscopy (SEM). The various structural parameters are calculated from XRD and Raman data. -
Integrating AI Tools into HRM to Promote Green HRM Practices
The image of Human Resource Management (HRM) is undergoing a drastic transformation. The conventional methods are evolving due to the emergence of technology, especially with the integration of Artificial Intelligence (AI) and data analytics into the HR processes. With the rapidly changing concept of the overall growth of an organization, AI is becoming a vital stimulant for sustainable growth. AI-powered tools promote data-driven decision-making for talent acquisition, performance management, workforce training and development, optimization of energy consumption and waste reduction. Green HRM aligns these efforts by integrating sustainability considerations into talent management strategies, nurturing employees eco-engagement, and promoting environmentally responsible practices within the workforce. This research paper aims to explore the synergies between AI tools and Green HRM practices, investigating how the integration of AI technologies into HR processes can contribute to the promotion of environmental sustainability. By examining real-world case studies, this study aims to investigate the potential of AI-powered solutions in shaping the future of HRM through the lens of sustainability. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
IoT-Enabled Analysis of COVID Data: Unveiling Insights from Temperature, Pulse Rate, and Oxygen Measurements
The COVID-19 pandemic has forced unparalleled transformation on healthcare systems around the world, demanding new and improved approaches for effective monitoring and diagnosis. In this context, we present a study titled IoT-Enabled Analysis of COVID Data: Unveiling Insights from Temperature, Pulse Rate, and Oxygen Measurements. The global impact of COVID-19, with millions of confirmed cases and fatalities, underscores the urgency of finding efficient monitoring solutions. To address this crisis, IoT-Enabled Health Monitoring Systems have emerged as a promising tool for remote patient monitoring and infection risk reduction. These systems leverage sensors to collect real-time data on the temperature, pulse rate, and oxygen saturation levels of the subject. The integration of a mobile application enables immediate access to this critical health information. In this study, we explore the use of IoT systems, which have demonstrated accuracy comparable to other devices on the market. By leveraging these technologies, we aim to provide healthcare professionals with valuable insights into patients health status, aiding in early detection, monitoring, and timely intervention. Our research contributes to the efforts to battle the COVID-19 pandemic by highlighting the potential of IoT-enabled monitoring systems in enhancing healthcare delivery, reducing infection risks, and ultimately saving lives. 2024 Scrivener Publishing LLC. -
Looking beyond leadership mantras
The Key is not to Reject the Leadership theories, But to Supplement them with the Intellectual Depth that the Humanities and Social Sciences Can Provide, Writes P Jhon Kennedy -
The Curious Political Phenomenon of Shashi Tharoor's Praise For Modi and the Congresss Dilemma
If Tharoor is indeed preparing for a new political chapter, he should turn the page clearly. -
Indias Struggle Continues With Gender Equality: A Long Way To Go
While some countries inch forward, others remain stagnant or regress. India, unfortunately, falls into the latter group. Ranked 131 out of 148 countries, Indias gender parity score is just 64.1 per cent, making it one of the lowest globally -
Women in STEM: Act beyond enrolment
While India boasts of a rising proportion of female STEM graduates, their participation in tech sector jobs remains low. This and other Asian examples show focusing on enrolment is ineffective in boosting equality without parallel efforts to dismantle workplace hurdles -
Necessary toolkit
The 2025 UGC notification and the proposed caste survey, one offering legal legitimacy, the other empirical clarity, are both necessary -
Strained Symbiosis: AIADMK, BJP, and the Shrinking Space for Dravidian Politics in Tamil Nadu
In Tamil Nadu, the electorate still listens keenly for ideological clarity. The question is: will the AIADMK find the courage to speak? -
Keeladi vs Vedic History: The Battle for Indias Past
Keeladi is not simply about pottery shards and drainage systems; it is about who gets to shape the story of India. -
The right method of choosing good professors
Recruitment practices can sometimes leave students in the hands of professors who are experts in their subject but struggle to explain it clearly, writes P John J Kennedy -
Kerala schools to discuss drug abuse prevention, emotional well-being, digital discipline, legal rights and hygiene
With its high literacy rates and relatively strong infrastructure, Kerala is uniquely equipped to pilot such programmes, writes P John J Kennedy -
Ahead of 2026 election, how can DMK retain credibility and control the narrative?
The path to Fort St. George lies as much through governance as through the peoples imagination. And in that realm, the verdict is never final -
More Than Legacy: Stalins Political Formula That Keeps DMK on Top
Stalins mix of legacy, governance, and resistance seems to have struck the right chord with the TN electorate.