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Neurocognitive aspects of mathematical achievement in children
Neurocognitive factors, including information integration and executive functioning, contribute significantly to a child's early success in math achievement, even though the significance of home and school environments cannot be ignored. There are only a few studies that have systematically examined how information integration and executive function skills impact different aspects of learning math and math achievement. Using a comprehensive tool such as the brain-Based Intelligence Test (BBIT), a brain-based comprehensive approach to the understanding of cognition, for the assessment of information integration and executive function skills can have significant implications for mathematical education and remediation (brain plasticity). The Author(s), under exclusive license to Springer Nature Switzerland AG 2021. All rights reserved. -
Forgiving Behavior among Emerging Adults: The Influence of Religiosity and Spirituality and Personality Traits
The present study aims to examine the three important aspects of emerging adulthood, religiosity and spirituality, personality traits, and forgiveness which bring well-being benefits. It is hypothesized that religiosity and spirituality along with personality traits predict forgiveness among emerging adults. The Neo Five-Factor Inventory (NEO FFI), the Religiosity and Spirituality Scale for Youth (RaSSY), and the Heartland Forgiveness Scale (HFS) were administered to 364 female and 390 male emerging adults (n = 754; mean age = 21 years, SD = 14.88) selected through purposive sampling technique from colleges in Bangalore. Data were analyzed using correlational and hierarchical regression analysis. This study found that religiosity and spirituality and the Big Five personality traits positively correlated with forgiveness whereas all personality traits, except neuroticism, strongly predicted forgiveness more than religiosity and spirituality. These findings suggest that faith-based coping and religious social support in combination with personality traits help emerging adults practice forgiveness in their daily life, leading to further insight into the theories of forgiveness and well-being. 2023 Taylor & Francis Group, LLC. -
Machine Intelligence: Computer Vision and Natural Language Processing
Machines are being systematically empowered to be interactive and intelligent in their operations, offerings. and outputs. There are pioneering Artificial Intelligence (AI) technologies and tools. Machine and Deep Learning (ML/DL) algorithms, along with their enabling frameworks, libraries, and specialized accelerators, find particularly useful applications in computer and machine vision, human machine interfaces (HMIs), and intelligent machines. Machines that can see and perceive can bring forth deeper and decisive acceleration, automation, and augmentation capabilities to businesses as well as people in their everyday assignments. Machine vision is becoming a reality because of advancements in the computer vision and device instrumentation spaces. Machines are increasingly software-defined. That is, vision-enabling software and hardware modules are being embedded in new-generation machines to be self-, surroundings, and situation-aware. Machine Intelligence emphasizes computer vision and natural language processing as drivers of advances in machine intelligence. The book examines these technologies from the algorithmic level to the applications level. It also examines the integrative technologies enabling intelligent applications in business and industry. Features: Motion images object detection over voice using deep learning algorithms Ubiquitous computing and augmented reality in HCI Learning and reasoning in Artificial Intelligence Economic sustainability, mindfulness, and diversity in the age of artificial intelligence and machine learning Streaming analytics for healthcare and retail domains Covering established and emerging technologies in machine vision, the book focuses on recent and novel applications and discusses state-of-the-art technologies and tools. 2024 Taylor & Francis Group, LLC. -
Data science: the Artificial Intelligence (AI) algorithms-inspired use cases
The data science field is growing fast with the faster maturity and stability of its implementation technologies. We had been fiddling with traditional data analytics methods. But now, with Artificial Intelligence (AI), it is possible to embark on predictive and prescriptive insights generation in time. There are several data science (DS) use cases emerging with the wider adoption and adaptation of AI technologies and tools. This chapter is dedicated to illustrate various AI-inspired use cases. The Institution of Engineering and Technology 2022. -
Study on the growth of the ott platform during lockdown and its future scope
This research tries to review the growth of OTT platforms throughout the lockdown. It's vital to understand the extent of increase within the popularity of OTT platforms throughout lockdown to understand their future scope. It's evident that, since their launch, OTT platforms have solely discovered an upward curve in their usage, and because of the pandemic and lockdown there has been exponential increase in its popularity because of the modification in consumption patterns of individuals for diversion through numerous media platforms. This analysis conducted a survey and analyzed the opinions of individuals relating to OTT platforms, their consumption patterns, and its comparison with cinema to examine if OTT platforms were slowly taking on the foremost fashionable standard medium of diversion. It had been found that individuals used OTT over the other platforms outside of TV and YouTube to pass their time or for diversion. 2024, IGI Global. -
Routing Protocol for Low Power and Lossy Network Using Energy Efficient Priority Based Routing
Internet of Thing (IoT) collects huge amount of data from the surrounding by monitoring and sensing. Further, transferring these data from IoT devices to cloud environment seems is very challenging. Such that, this paper concentrates on energy consumption, in which the energy efficient routing and priority dependent techniques are proposed. This technique depends upon the RPL network (Routing Protocol for Low power and Lossy), which efficiently predicts routing over contents. Every network slot utilizes timing pattern while forwarding image data, audio data. The proposed method enhances the strength of routing protocol and also avoids congestion. The outcomes of the study illustrates that proposed Energy efficient priority based routing (EEPR) technique minimize overheads on mesh, energy consumption and end-end delay. Also, the proposed method outperforms the existing QRPL methods in IoT platform. 2021, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature. -
Compositionally Homogeneous Soft Wrinkles on Elastomeric Substrates: Novel Fabrication Method, Water Collection from Fog, and Triboelectric Charge Generation
Functionality and stimuli-response of natural and artificial elastomeric materials depend significantly on the morphology of their surfaces. Structural transformability and tunable responsiveness of wrinkles on elastomeric materials can enable numerous applications in flexible electronics, optics, and adhesives. Currently existing fabrication techniques rely on sophisticated instrumentation, complex experimental setups, and expensive reagents. These methods are limited in terms of mechanical robustness of the wrinkles produced. Here, a simple, inexpensive, scalable, and reproducible strategy, making use of buckling instability for the creation of soft surface wrinkles on polydimethylsiloxane (PDMS), is presented. PDMS with lower elastic modulus is spin-coated onto a mechanically stretched film of PDMS with a higher elastic modulus. Thermal curing followed by the release of prestrain resulted in the formation of wrinkles in the top layer of the PDMS. The hydrophobic soft surface wrinkles with compositional homogeneity exhibit efficient fog water collection and triboelectric charge generation useful for the preparation of triboelectric nanogenerator devices. Furthermore, the substrates show high mechanical stability and mechanoresponsive optical behaviors. The simplicity and general applicability of the method presented here is expected to establish a promising pathway toward the formation of soft wrinkles in other elastomeric systems also, facilitating important applications in various fields. 2022 Wiley-VCH GmbH. -
Facile fabrication of stable wettability gradients on elastomeric surfaces for applications in water collection and controlled cell adhesion
We have developed a simple and effective method to prepare stable wettability gradients on an elastomeric soft substrate, polydimethylsiloxane (PDMS). In our method, a partially cured PDMS film composed of a definite ratio of elastomer and crosslinking agent was heated over a hot surface with a temperature gradient. This causes differential thermal curing of the PDMS film and the water contact angle (wettability) of the resultant surface showed gradual variation across the length. This method allows us to design and fabricate wettability gradients with rationally controlled directionality and shapes (e.g., linear and radial gradients). The stability of the wettability gradients was studied and a chemical treatment method was developed to enhance the stability at room temperature. Stable wettability gradients prepared through this method can find applications as reliable platforms and scaffolds offering controlled or directional wetting and adhesion. We have demonstrated the practical applications of the wettability gradients in directional water collection, controlled crystallization of materials, and controlled cell adhesion of HeLa cells, osteoblasts and NIH/3T3 cells. The multi-functional characteristics of these wettable gradients are expected to be handy in other domains using soft materials and interfaces also. 2023 The Royal Society of Chemistry. -
Fabrication and Applications of Wrinkled Soft Substrates: An Overview
Morphology of soft materials, including those of natural systems has great influence in controlling their surface functionalities and responses to external stimuli. Surface morphological features of natural soft systems are produced through controlled cell growth and tissue growth. Artificial systems capable of emulating the morphology-dependent physicochemical responses of natural soft substrates can be prepared through various methods such as surface oxidation, thermal stress, compressive stress, etc. Wrinkling is an important morphological irregularity on soft substrates which can be leveraged in this direction. Wrinkling in artificial soft systems can be achieved through several experimental strategies such as compressive stress, thermal stress, surface oxidation, etc. The tunable, reversible and responsive nature of wrinkled soft substrates make them a potential tool for numerous applications in electronics, optics, adhesives, etc. In this review, have briefly summarized and commented on recent developments in different types of wrinkled soft substrates, their preparation, and emergent applications. 2022 Wiley-VCH GmbH. -
Do flexible working hours influence employee skill enhancement and productivity? Evidence from polyvalent workers
This chapter investigates the influence of flexible working schedules affect the productivity and skill development of polyvalent workers. A thorough literature analysis guided the creation of a questionnaire that was given to 153 polyvalent workers as a sample. The gathered data was subjected to statistical analysis in order to determine how flexible work schedules affected worker productivity and skill development. The results show a strong correlation between flexible work schedules and increased productivity and skill development among employees. Furthermore, it was discovered that these results were significantly impacted by flexible working hours. Flexible schedules can help multitasking employees, who are skilled in a range of jobs, improve their productivity and further develop their skills. Companies that use polyvalent labour are encouraged to think about adopting flexible work schedules as a way to improve worker productivity and abilities. 2024, IGI Global. All rights reserved. -
Do gender diversity and leadership style influence team performance and innovation among the employees: Evidence from the IT sector
The aim of this chapter is to investigate the influence of gender diversity and leadership style on team performance and innovation of potential teams in the information technology sector. A questionnaire was developed, and a sample of 403 responses were collected from the employees. The analysis of the collected data was done using statistical tests of correlation and logistical regression, in order to understand the relationship and impact of gender diversity and leadership style on team performance and innovation potential of teams. The following findings emerged from the analysis. The findings reveal that there is a positive and significant relationship between gender diversity, leadership style, team performance, and innovation. Also, the result from logistics regression evidence that gender diversity and communication have an impact on team performance, whereas organisational culture and communication have an impact on innovation potential within teams. 2024, IGI Global. All rights reserved. -
Amalgamation of corporate social responsibility with the principles of the circular economy for sustainable growth
The next chapter extends more with the discussion of CE principles integrated into CSR strategies maintaining a business case strong in sustainable practice beyond the traditional model. Closed- loop supply chains, sustainability in product design, Product- as- a- Service for resource efficiency, waste minimization, and improvement within the corporate resilience system come to mind as CE- oriented strategies. This chapter continues to cover the challenge of responsible leadership and advocacy in policy to push over hurdles, support sustainable culture change, and position companies as corporate citizens. It brings out attention to future trends of urban mining and CE in developing markets, showing how companies adopting circular models will derive long- term growth and competitiveness. Recommendations to firms to totally embed CE in their CSR framework could include, notably around actionables, especially in terms of strong metrics, engagement, and creating leadership that supports environmental and social accountability. 2025, IGI Global. All rights reserved. -
Topological Indices Based on Distance Labeling
This thesis explores the prospect of combining two prime branches of graph theory, newlineviz., topological indices and graph labeling, specifcally radio labeling. The majority newlineof the work includes the topological radio indices of graphs and their properties. Topological indices are numerical values associated with graphs and invariant with graph isomorphisms. Apart from Topological Radio Indices, it provides some additions to the eccentricity-based topological indices. newlineRadio labeling or radio coloring, c, is assigned to a graph G such that the label difference between any two vertices must be greater than diam(G)+ 1 and#8722; d(u,v). Optimum radio labeling is the foundation for defning Topological radio indices. Labeling whose span is the radio number of the graph and which leads to the minimum value of the index newlineis considered the optimum radio labeling. The topological radio indices and coindices newlineare defned and are found out for some special classes of graphs, including gear graphs, newlinewheel graphs, and star graphs. The bounds for the frst, second and third Zagreb radio indices have been established and characterized for the classes of graphs for which the bound is sharp. Furthermore, newlinespecifc relationships between Zagreb radio indices and coindices are established concerning different parameters of the graph. newlineThe idea of consecutive radio labeling is explicitly studied. We have characterized the newlinegraphs with diameter 2 admitting consecutive radio labeling. We have studied the properties of graphs admitting consecutive radio labeling and stated the necessary and suffcient conditions for a graph to follow consecutive radio labeling. The study extended to eccentricity-based topological indices, viz., the forgotten eccentricity indices. The maximum d(u,v) for all v in V(G) is the eccentricity of the vertex u in G. This work also investigates eccentricity-based coindices and some of their properties. newlineApart from this, some uniquely radio colorable graphs are examined and characterized. -
A method for identification of restarted radio sources from large radiosurveys
Active galaxies hosting radio jets can exhibit distinct active phases marked by two sets of radio lobes. Typically, these episodic radio sources have been identified through morphological observations. In addition, spectral characteristics-based methods are also employed wherever multi-frequency deep radio observations are available. However, these methods are inefficient in detecting restarted radio sources that do not exhibit a clear morphology. To address this, a method of using the spectral curvature (SPC=?150MHz1400MHz-?74MHz150MHz) to identify restarted radio sources is presented. This is based on the fact that restarted radio sources with significant remnant emission are expected to have concave spectra in contrast to the convex or straight spectra observed in most radio sources. We use available wide area radio surveys in the range of frequencies from 74MHz to 1.4GHz to search for episodic radio sources and to shortlist 9,405 sources based on the criteria of SPC?0.5. The candidates thus identified can be followed up for detailed morphological and spectral index studies. This method will find application in the automated identification of episodic radio sources in large radio sky surveys from telescopes like LOFAR and SKA. Indian Academy of Sciences 2025. -
Cost Effective Synthesis of Carbon Nanoparticles and Exploring the Fluorescence and Electrochemical Applications
Graphene-based materials and composites for sensing are a fascinating field in material science research that is experiencing rapid advancement. But the applications of graphene-based materials were often hampered by their high production cost, low yield, expensive and scarce precursors, harmful processing techniques, etc. Coal is made up of islands of nanometer-sized crystalline carbon domains linked by a 3D network of amorphous aliphatic carbon and polymerized aromatic hydrocarbons that can be extracted using mild oxidizing agents. In this context, the present study reports the successful usage of low-grade coal, lignite as an ideal precursor for the production of carbon nanostructures for various sensing applications. This research is divided into three parts where value addition to coal is being done along with finding solutions to three major environmental issues: fluorescence sensing of copper ion; noninvasive glucose fluorescence sensing; simultaneous electrochemical sensing of heavy newlinemetal ions cadmium and lead. In the first study, carbon nanostructures were synthesized from lignite by a simple, scalable, and economical technique and the as-prepared carbon nanostructures, namely LC1, LC2 and LC3, demonstrated excellent fluorescence characteristics. LC3 exhibited remarkable copper ion sensing with a dual linear range with limits of detection (LOD) as low as 1.32 pM and 2.35 pM, with limits of quantification (LOQ) 4 pM and 7.14 pM respectively. The accuracy of the manufactured sensor was shown by the recovery rates of copper ions, which varied from 98.18% to 101.2% with Relative newlineStandard Deviations (RSDs) below 0.4%. The results are captivating, implying that newlinethese lignite derived carbon nanostructures could be employed to efficiently and newlineeconomically detect low concentrations of copper ions in water. In the second study, carbon nanoribbons and nanosheets with superior fluorescence were synthesized from lignite, using a facile chemical oxidation process. -
Enhanced Spam Detection in Short Message Service using Hybrid Techniques
Receiving unwanted text messages, or SMS spam, costs consumers time and money and poses a security concern. To address this issue, we can deploy a system that recognizes and automatically filters out undesirable messages. This method, a testament to the advancement in technology, employs machine learning algorithms that gain knowledge from a pool of communications classified as spam or not. Managing various message contents and languages is one of the system's unique challenges. Notwithstanding these challenges, the approach may be effective in reducing unsolicited communications, improving the security of people's mobile devices and saving them time and money. To address this issue, a variety of machine learning approaches have been employed, ranging from more modern deep learning methods like Convolutional Neural Networks (CNNs) to more traditional ones like Naive Bayes. It is common practice to assess the effectiveness of SMS spam classifiers using measures like as F1-score, precision, and recall. All things considered, SMS spam classification is crucial for protecting the security and privacy of mobile phone users and has useful applications in everyday situations. Grenze Scientific Society, 2025. -
CCIR: The Next Frontier in Mobile Network Evolution - Integrating Communication and Computing for Enhanced Services
The mobile RAN is the bridge and enabler between end users and application services, and fortunately, the computational capacity of base stations in RANs[1] has experienced tremendous growth accompanied by increasingly stringent service requirements from emerging applications such as AR/VR. These two trends imply an unprecedented opportunity that the abundant computing resources in base stations could be leveraged to host latency-sensitive applications if being managed properly, thereby giving rise to a new vision named Communication and Computing Integrated RAN (CCIR), where not only communication but also computing services are delivered by RANs in a coherent way[2]. In fact, CCIR implies an even more radical departure of designing future mobile networks-going beyond regarding the role of RANs as connecting links. This article provides an elaboration on the fundamental design philosophies and principles of CCIR, the logical architecture. We will explore further on key tech-nologies toward realizing our vision. Specifically, we provide a thorough view on what CCIR really means - it involves different integration granularities between communication and computing functions; meanwhile it keeps evolving until approaching real-time joint scheduling and holistic resource management based on one unified infrastructure. To assess the feasibility and advantages brought by CCIR, several field experiments were carried out where computing resources are migrated within different base stations. In conclusion, CCIR is a prospective evolution direction for future mobile networks dealing with communication-computation-converged requirements in new service use scenarios[3]. Using current infrastructure more intelligently and efficiently will facilitate better user experience, greener mobile networks as well as serve as better platform for future advancements in wireless technology. Grenze Scientific Society, 2025. -
Exploring the Role of Artificial Intelligence in Educational Technology
AI is a dedicated field that addresses cognitive challenges often linked to human intelligence, including learning, problem-solving, and pattern recognition. This chapter investigates the evolving role of artificial intelligence (AI) in educational technology (EdTech). EdTech, short for EdTech, uses technology to support teaching and learning. EdTech firms employ advanced technology to offer personalized, experiential learning and online mentorship. With the rapid advancements in AI and its integration into various sectors, the educational landscape has witnessed significant transformations. This study explores the potential of AI as a powerful tool in enhancing teaching and learning experiences, improving educational outcomes, and addressing individual student needs. Employing the research synthesis methodology, this chapter provides a comprehensive overview of AIs role in EdTech, highlighting its capacity to revolutionize teaching and learning practices. Finally, the chapter concludes with an outlook on the future of AI in EdTech, discussing emerging trends and potential growth areas. 2026 selection and editorial matter, A.V. Senthil Kumar, Ankita Chaturvedi, Atul Bansal, and Rohaya Latip; individual chapters, the contributors.