• Clinical and Experimental Pediatrics
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• v.63 no.6
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• pp.232-236
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• 2020

Background: Children today get access to smartphones at an early age. However, their ability to use mobile apps has not yet been studied in detail. Purpose: This study aimed to assess the ability of children aged 2-8 years to perform touchscreen gestures and follow prompting techniques, i.e., ways apps provide instructions on how to use them. Methods: We developed one mobile app to test the ability of children to perform various touchscreen gestures and another mobile app to test their ability to follow various prompting techniques. We used these apps in this study of 90 children in a kindergarten and a primary school in New Delhi in July 2019. We noted the touchscreen gestures that the children could perform and the most sophisticated prompting technique that they could follow. Results: Two- and 3-year-old children could not follow any prompting technique and only a minority (27%) could tap the touchscreen at an intended place. Four- to 6-year-old children could perform simple gestures like a tap and slide (57%) and follow instructions provided through animation (63%). Seven- and 8-year-old children could perform more sophisticated gestures like dragging and dropping (30%) and follow instructions provided in audio and video formats (34%). We observed a significant difference between the number of touchscreen gestures that the children could perform and the number of prompting techniques that they could follow (F=544.0407, P<0.05). No significant difference was observed in the performance of female versus male children (P>0.05). Conclusion: Children gradually learn to use mobile apps beginning at 2 years of age. They become comfortable performing single-finger gestures and following nontextual prompting techniques by 8 years of age. We recommend that these results be considered in the development of mobile apps for children.

• Electronics and Telecommunications Trends
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• v.38 no.6
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• pp.1-11
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• 2023

Large language models seem promising for handling reasoning problems, but their underlying solving mechanisms remain unclear. Large language models will establish a new paradigm in artificial intelligence and the society as a whole. However, a major challenge of large language models is the massive resources required for training and operation. To address this issue, researchers are actively exploring compact large language models that retain the capabilities of large language models while notably reducing the model size. These research efforts are mainly focused on improving pretraining, instruction tuning, and alignment. On the other hand, chain-of-thought prompting is a technique aimed at enhancing the reasoning ability of large language models. It provides an answer through a series of intermediate reasoning steps when given a problem. By guiding the model through a multistep problem-solving process, chain-of-thought prompting may improve the model reasoning skills. Mathematical reasoning, which is a fundamental aspect of human intelligence, has played a crucial role in advancing large language models toward human-level performance. As a result, mathematical reasoning is being widely explored in the context of large language models. This type of research extends to various domains such as geometry problem solving, tabular mathematical reasoning, visual question answering, and other areas.

• Journal of Distribution Science
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• v.22 no.1
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• pp.25-36
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• 2024

Purpose: The study attempts to explore the operational performance of the existing Malaysian logistics companies and the extent of their adoption of digitalization. The role of digitalization in enhancing the performance of companies in the logistics industry in Malaysia, for value creation, is the topic of study. Research design, data and methodology: A qualitative research method with a semi-structured interview approach was applied and judgmental sampling was used as the sampling technique to collect data. The research has chosen nine companies in the logistics industry in Peninsular Malaysia, with the interviews aimed at eleven members of top and middle-level management. Data analysis was performed using logical system techniques to examine and evaluate data, reorganizing feedback, comparing it with literature, and transforming it into structured, valuable information after interviews. Results: The study revealed mixed opinions on digitalization in logistics, despite its potential benefits such as improved operational efficiency, real-time information, and customer service. However, high costs may hinder financial performance and require revisions due to stakeholder involvement. Conclusions: The Malaysian logistics industry's adoption of digitalization is gaining traction, with most companies satisfied with their status. However, challenges like cost and inefficiency persist, prompting calls for government support to improve efficiency and reduce costs while ensuring sustainable transportation.

• International Journal of Computer Science & Network Security
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• v.24 no.5
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• pp.103-110
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• 2024

In the quickly developing world, the idea of the conventional advancement needs to advance[1]. When applied to the advanced work environment, the conventional strategies give as much damage as they do great. Tragically, an absence of versatility in the customary techniques has prompted an inflexible work structure that is truly not viable with the present business. The Agile technique is, subsequently, a more adequate practice, in view of creating programming at a faster speed, while as yet looking after proficiency. The coordinated programming improvement strategies are concentrated in this paper. As per study results, Agile software development group needs solid client association; great light-footed task the executives' measures; item proprietor expands business esteem conveyed by group and need and draw in partners; great deft designing procedures or practices; and great advancements and advancement apparatuses[2]. This examination has suggestions for positive social change since associations that comprehend the basic components might have the option to improve project the executives' systems and money saving advantages prompting higher effectiveness, productivity, and efficiency hence profiting the board, representatives, and client. This survey paper incorporates various methodologies of Agile and their analysis.

• Corrosion Science and Technology
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• v.23 no.1
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• pp.72-81
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• 2024

The Ti-6Al-4V alloy is widely used as an implant material due to its higher fatigue strength and strengthto-weight ratio compared to pure titanium, excellent corrosion resistance, and bone-like properties that promote osseointegration. For rapid osseointegration, the adhesion between the titanium surface and cellular biomolecules is crucial because adhesion, morphology, function, and proliferation are influenced by surface characteristics. Polymeric peptides and similar coating technologies have limited effectiveness, prompting a demand for alternative materials. There is growing interest in 2D nanomaterials, such as MoS₂, for good corrosion resistance and antibacterial, and bioactive properties. However, to coat MoS₂ thin films onto titanium, typically a low-temperature hydrothermal synthesis method is required, resulting in the synthesis of films with a toxic 1T@2H crystalline structure. In this study, through high-temperature annealing, we transformed them into a non-toxic 2H structure. The implant coating technique proposed in this study has good corrosion resistance and biocompatibility, and antibacterial properties.

• Clinics in Shoulder and Elbow
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• v.25 no.3
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• pp.230-235
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• 2022

Background: Unstable distal clavicles experience high non-union rates, prompting surgeons to recommend surgery for more predictable outcomes. There is a lack of consensus on the optimal method of surgical fixation, with an array of techniques described in the literature. We describe an alternative method of fixation involving the use of a distal clavicular anatomical locking plate with Fibertape cerclage augmentation in our series of patients. Methods: Nine patients (8 males and 1 female), with a mean age of 36 years, who sustained unstable fracture of the distal clavicle in our institution were treated with our described technique. Postoperative range of motion, functional and pain scores, and time to radiographic union were measured over a mean follow-up period of 10 months. Incidences of postoperative complications were also recorded. Results: At the last patient consult, the mean visual analog scale score was 0.88±0.35, with a mean Disabilities of the Arm, Shoulder, and Hand (DASH) score of 1.46±0.87 and American Shoulder and Elbow Surgeons (ASES) score of 94.1±3.57. The mean range of motion achieved was forward flexion at 173°±10.6°, abduction at 173°±10.6°, and external rotation at 74.4°±10.5°. All patients achieved internal rotation at a vertebral height of at least L2 with radiographical union at a mean of 10 weeks. No removal of implants was required. Conclusions: Our described technique of augmented fixation of the distal clavicle is effective, produces good clinical outcomes, and has minimal complications.

• Land and Housing Review
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• v.14 no.4
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• pp.95-102
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• 2023

Numerous investigations have explored the integration of machine leaning algorithms with high-resolution drone image for object detection in urban settings. However, a prevalent limitation in vehicle extraction studies involves the reliance on bounding boxes rather than instance segmentation. This limitation hinders the precise determination of vehicle direction and exact boundaries. Instance segmentation, while providing detailed object boundaries, necessitates labour intensive labelling for individual objects, prompting the need for research on automating unsupervised instance segmentation in vehicle extraction. In this study, a novel approach was proposed for vehicle extraction utilizing unsupervised SVM classification applied to vehicle bounding boxes in drone images. The method aims to address the challenges associated with bounding box-based approaches and provide a more accurate representation of vehicle boundaries. The study showed promising results, demonstrating an 89% accuracy in vehicle extraction. Notably, the proposed technique proved effective even when dealing with significant variations in spectral characteristics within the vehicles. This research contributes to advancing the field by offering a viable solution for automatic and unsupervised instance segmentation in the context of vehicle extraction from image.