Science and Technology - Recent Updates and Future Prospects Vol. 6

Weather forecasting is a daunting challenge the world faces nowadays. Rainfall prediction is especially vital for agricultural and meteorological departments and is one of the most challenging tasks. Many researchers have contributed to rainfall prediction using methods ranging from statistical models to computational models.The computational model K-nearest Neighbour Technique (KNN) has been used to predict Chennai Rainfall for various data transformations in the study. Comparison and analysis was made using the error measure MAPE.

Online grocery shopping is trending worldwide as one of the most expedient e-commerce practices. Many people have started purchasing their groceries online and this has allowed the researchers to identify and analyse the factors that influence the consumers for making online purchases. We have observed that until around 5 years back, the daily grocery requirements of the Indian consumers were fulfilled by the local Kirana store and to some extent by the emerging hypermarkets/supermarkets. But, with the popularity of the internet and the penetration of smartphones into the daily lives of people, several online grocery stores have been able to penetrate the Indian markets. The busy lives of people especially the urban working population, make online grocery shopping a popular choice. With traditional households still being widely spread in Indian society, online companies need to have a resounding approach to influence the buying habits and shopping patterns of consumers. The aim of this study is to understand the attitude of Indian consumers toward online grocery shopping and determine the factors that influence the consumer decision making to shop for groceries online. In this paper, we have comprehensively explored different areas associated with online grocery shopping and this study can be advantageous for online grocery retailers to articulate effective policies to gain customer confidence toward online grocery shopping. First, in-depth interviews with 20 to 25 people were conducted to have an overall impression of the views of Indian consumers on shopping the groceries online. Then, a survey with a well-thought-out questionnaire was circulated to around 150 people. The total number of complete responses was collected from 125 people. The primary data was collected and analysed to determine the consumer attitude towards online grocery shopping. The findings of the study show that the consumers are influenced by various factors like time-saving and convenience provided by online grocery shopping platforms. The result indicated that 64% of the respondents shop for groceries online, yet a considerable population was still comfortable shopping through the traditional brick-and-mortar stores. They are also influenced by the quality of products and the return policy as well as the level of comfort while using the online shopping website/ app. We have also been able to understand the reasons that prevent people from online shopping. Some people find themselves lacking the technical skills to shop online, but most people who do not shop online like going to the market personally. In the case of online shopping, an area of concern for most shoppers is trusting online applications. People are concerned about the privacy of their personal information while shopping online and need the thoughtfulness of the retailers to encourage more consumers to opt for online shopping platforms.

This chapter advances the analysis of gaze dynamics by employing Multiscale Entropy (MSE) to evaluate 5020 binocular eye movement recordings from 407 college-aged participants. Utilizing the comprehensive GazeBaseVR dataset, this study investigates the complexity of user interactions across a variety of virtual reality (VR) tasks such as vergence, smooth pursuit, video viewing, reading, and random saccades. The data, collected at 250 Hz using an ET-enabled VR headset, provides a robust foundation for understanding the predictability and complexity of gaze patterns. By incorporating a longitudinal perspective from recordings taken up to six times over a 26-month period, this analysis deepens our understanding of eye movement behavior in VR environments. This chapter highlights the potential of MSE in crafting more intuitive and immersive VR interfaces, thereby enhancing user experience. Recent advancements and additional references have been included to discuss the evolving role of MSE in optimizing VR technology for personalized and comfortable user interactions.

The measurement of uranium in diverse matrices like mineralized rocks, ores, beneficiation products, and other diverse matrices using a Laser/LED fluorimeter, without resorting to any separation technique is presented and critically evaluated. The main emphasis is on advances and challenges in the available technique, RAP’s: Reliability, Applicability, and Practicability. Among fluorimetry techniques, Laser/LED fluorimeter is the technique of choice to fulfil the desired parameters by suitably selecting fluorescence-enhancing reagents and methods of measurement. Application of differential technique (DT) in laser-induced fluorimetry/ICP-OES for the direct determination of uranium is recommended for routine accurate determination of uranium over a wide range of concentrations, which is based on the comparison of the response of the standard with a sample of similar but unknown concentration on the same sample weight basis. Differential laser-induced fluorimetry method has been evaluated using standards, SY-2, SY-3, reference uranium ore, BL-2a, low-grade uranium ore-IAEA reference samples, and core samples of diverse matrices. The relative standard deviation of the method was 0.3–0.5% in nine replicates for 0.04–3.4% U₃O₈ in mineralized silicate rock samples and 0.5–0.9% at 18.1, 36.2, 61.2, and 99.6% U₃O₈ in concentrates and mineralized grab samples. In this approach, the procedure of elimination of interference by simple dilution of the sample has the distinct advantage of being quick and very simple to perform because it does not require any chemical preparation or extraction. The results are in good agreement with the published data and those obtained by conventional fluorimetry and other methods, and of comparable precision to those obtained by titrimetric assay. It is a self-standardized green methodology of measurement and guarantees the quality of an analytical result (Accuracy, high precision, reliability, comparability, and traceability). Application of differential technique in Laser-/LED-fluorimetry/ICP-OES has the inherent high metrological quality and will be useful for the analysis of uranium in ores, certification of reference materials, borehole core assay, beneficiation product, and other diverse applications in the entire nuclear fuel cycle worldwide.

The study sought to assess the Code to determine if the current ideals of mitigating the causes of climate change are precisely aligned to the attainment of the Intended Nationally Determined Contribution (INDC), and realization of Sustainable Development Goals 13 - Climate Action (SDG). The process of the study is to derive a situational understanding and implementation analysis of the Code, to develop a matrix of proposed policies as the basis for creating guidelines for restoring the forest and coastal conditions of the locality. The study used qualitative thematic and PESTEL analyses particularly the hybrid approach via structural and value types of coding. The themes necessitate the occurrence of a triangular effect that brings forth a reflexive identity for the amendment or development of the Code to a more responsive policy towards sustainable climate conditions. The immediate management implications to PGIS are inherently implied in the weaknesses of the Code, which are seen in the lack of necessary provisions that call for immediate action and the improvement of the implementation process. The primordial recommendation is to research and examine the remaining Articles of the Code to gain a holistic understanding of the needed inclusions prior to appropriate actions by PGIS legislative officials. This will provide an all-inclusive scrutiny of the areas of weaknesses, strengths, opportunities, and threats of the Code, and unleashes the best approach to fighting climate change.

Aims: This study aims to develop a highly sensitive fiber optic hydraulic acoustic sensor utilizing a Fabry-Perot interferometer formed inside an open cavity at the end of an optical fiber, enhancing its potential for precise acoustic measurements in various media.

Study Design:  The research involves experimental design utilizing optical fiber technologies and interferometry.

Place and Duration of Study: Research conducted at the Department of Photonics, Kazan National Research Technical University, Kazan, Russia, from September 2023 to December 2023.

Methodology: A macro cavity in the shape of a droplet was engineered at the fiber end using a combination of catastrophic plasma melting and controlled fusion. The end face of the optical fiber, shaped into this macro cavity, was immersed in liquid to form a closed area with gas, where the interface surfaces served as Fabry-Perot mirrors. This setup was utilized to measure the sensitivity of the system to changes in acoustic waves across different frequencies and pressures.

Results: The newly developed fiber optic microphone exhibited sensitivity across a broad acoustic frequency range from 1 Hz to 100 kHz. Notably, limiting the interferometer length variation demonstrated a linear change in the reflection coefficient, varying between 0.017 and 0.089, confirming high precision and significant improvement over traditional sensors.

Conclusion: The innovative use of an open cavity Fabry-Perot interferometer in fiber optic microphones presents a significant advancement in acoustic sensing technology. This development offers a promising route for enhancing the performance of acoustic sensors used in various scientific and industrial applications. Further studies are recommended to explore the integration of this technology into commercial sensing systems.

The present study uses timeline matrix-formed datasets with a variety of common Japanese-styled agri-tools. We base our deep learning approach on achievements in the acoustic deep learning fields, where timeline physical data is transformed into WAV formatted sound file data. Recent improvements in analyzing agri-work have considered up-to-date technologies with deep learning approaches to understand how solutions reflect the experience of traditional agri-workers.  To comprehend acceleration and angular velocity, physical timeline data can be used to derive certain physical features of workers. There is still need for improvement even if different strategies have been put into place internationally for both indoor and outdoor agricultural (agri-) working areas. We apply a deep learning-based method and qualitatively demonstrate the classification of physical timeline datasets. To create our dataset, our subjects were six experienced agri-manual workers and six completely inexperienced men. The targeted task was cultivating the semi-crunching position using a simple, Japanese-style hoe. We captured the subjects’ acceleration and angular velocity data from an integrated multi-sensor module mounted on a wood lilt 15 cm from the gripping position of the dominant hand. We used Python code and recent distributed libraries for computation. For data classification, we successively executed a Recurrent Neural Network (RNN), which we evaluated using wavelet analyses such as the Fast Fourier Transform (FFT). These methods of analyzing digital data could be of practical use for providing key suggestions to improve daily tasks. Future users could automatically or semi-automatically apply our approaches to classify a wide variety of digital matrix-formed data. In the long term, we aim to check and improve the system durability, long-term performance, and other methodological mixing patterns.

Batam is a Sumatra Island border that connects Singapore, Malaysia, and Indonesia. Batam is strategically located near the sea border that separates Johor, Malaysia and Sumatra. The purpose of this study is to determine whether the ASEAN Economic Community has made a decision on the ASEAN connectivity application in 2015. Sea border transportation must be redeveloped because it is believed that the establishment of an open market ASEAN economic community in Southeast Asia is dependent on connectivity among ASEAN countries. To learn more, this case study closely examines the ferry routes connecting Batam to Singapore and Johor. The method is field research in Singapore, Batam and Johor and the most important result is the maritime information about ship safety and the condition of ferry terminals in Batam, Singapore and Johor.

Randomized algorithms, which incorporate randomness into their logic to solve computational problems, have become indispensable tools in computer science. This thesis explores the diverse roles and impacts of randomized algorithms, challenging the notion that they are inherently antagonistic due to their stochastic nature. By examining their theoretical foundations, practical applications, and broader implications, this study demonstrates how randomized algorithms contribute positively across various fields.

The research begins with a detailed analysis of the theoretical underpinnings of randomized algorithms, including probabilistic analysis. It then delves into numerous applications where randomized algorithms outperform deterministic methods, such as information retrieval, art and entertainment, cryptography, and computational biology. Through these examples, the thesis illustrates how randomness can lead to more efficient, scalable, and robust solutions.

Additionally, this study addresses the ethical and societal implications of employing randomized algorithms. It highlights scenarios where these algorithms enhance fairness, equity, privacy, and security, countering the argument that their inherent unpredictability is detrimental. The challenges and limitations of randomized algorithms are also discussed, emphasizing the importance of careful implementation and ethical considerations to mitigate potential risks.

By synthesizing insights from a wide range of scholarly sources and real-world applications, this thesis provides a comprehensive evaluation of the role of randomized algorithms in modern computing. It advocates for a balanced perspective, recognizing the benefits of randomness in solving complex problems while also acknowledging and addressing the associated challenges. This nuanced approach underscores the potential of randomized algorithms to drive innovation and progress in various computational domains [1].

In this study, we investigated the structural, optical, and magnetic properties of GaSbMn thin films fabricated via magnetron sputtering on a glass substrate. To introduce Mn into the GaSb matrix at low concentrations, the substrate temperatures were varied from 200 °C to 400 °C. The X-ray results show that the thin films are polycrystalline with a preferential orientation in the (220) direction of GaSb. accompanied by a secondary phase of MnSb. Raman spectroscopy revealed the presence of vibrational phonon modes of GaSb and a Coupled LO-Phonon-Plasmon Mode (CLOPM). The carrier concentration, derived from , ranged from approximately 10¹⁸ to 10¹⁹ cm-³. The magnetization behavior was studied using temperature cycling (H fixed) and field cycling measurements (T fixed). The magnetization loops at room temperature show that Mn-doped GaSb films exhibit weak magnetic behavior. The Curie temperature, T_C, was determined from the magnetization vs. temperature curves. T_C takes high values in the range of 300 K to 570 K, which is related to the formation of Mn_xSb_y nanoparticles embedded into the GaSb matrix.

Aims: In this work, we studied the influence of Mn content on GaSb thin films deposited by magnetron R.F. sputtering. To this end, the structural, morphological, optical, and magnetic properties were analyzed and correlated with the experimental conditions.

Study Design: Experimental and theoretical study.

Place and Duration of Study: Laboratorio de Nanoestructuras Semiconductoras, Departamento de Física y Química, Universidad Nacional de Colombia, sede Manizales, Manizales - Colombia, between January 2021 and February 2022.

Methodology: GaSbMn thin films were fabricated using a non-epitaxial growth method, specifically magnetron sputtering, with variations in growth temperature. To study the morphological, structural, optical, and magnetic properties and to correlate these with the experimental conditions, X-ray diffraction, EDS-SEM, Raman spectroscopy, and magnetization measurements were carried out.

Results: GaSbMn thin films exhibit intriguing paramagnetic properties that are contingent upon experimental parameters. Through structural analysis, we identified the formation of Mn_xSb_y nanoparticles embedded within the GaSb matrix. The observed MnSb-like phonon modes at 242 cm^-1 (LVM), 251 cm^-1 (TO), and 264 cm^-1 (LO) align well with the reported vibrational modes of MnSb documented in the literature. Estimating a hole density of approximately 10¹⁹ cm^-3 from the CLOPM frequency  in Raman spectroscopy further supports our findings. The Mn₂Sb phase predominantly contributes to magnetization at elevated temperatures. Utilizing the mean-field model, we can compute the mean potential resulting from dipolar interactions between any pair of moments \(\mu_{i}\) and \(\mu_{j}\) at a distance \(r_{ij}\).

Conclusion: GaAsMn thin films exhibit notable magnetic properties that vary with the growth conditions. Long-range interactions among isolated magnetic moments were analyzed using the mean-field model, demonstrating that the dipolar interaction field is influenced by the growth temperature. The high Curie temperatures observed in the samples are attributed to the presence of the Mn_1+xSb phase.