PEDAGOGICAL IMPACT OF MULTI SENSORY VIRTUAL REALITY SIMULATIONS ON HISTORICAL PERSPECTIVE TAKING AND SPATIAL UNDERSTANDING IN SECONDARY EDUCATION
The development of historical perspective-taking and spatial cognition has been a long-standing issue in secondary education, where traditional text-centred, lecture-based methods of study can hardly engage students in the complex historical environment. The paper under analysis explores the pedagogical effects of multi-sensory Virtual Reality (VR)...
By Shaxlo Xudaykulova, Ganisher Tagayev, Nozimakhon Yigitalieva, Murodjon Axmedov, Kamola Kudrat-Zoda, Ulug Tilloyev, Farrukh Saydullaev
AI AUGMENTED NEURAL FEEDBACK FOR PRECISION ACQUISITION OF NON-NATIVE PHONOLOGY IN SYNCHRONOUS DIGITAL LEARNING ENVIRONMENTS
The ongoing challenge of learning non-native phonology in the synchronous digital learning setting is a primary obstacle to intelligible pronunciation and communicative competence. Conventional online teaching is rarely accompanied by real-time, personalized corrective feedback, leading to the persistence of fossilized pronunciation errors and poor...
By Shoira Djabbarova, Tursinoy Kakhorova, Nargiza Dusmatova, Shokhsanam Tadjiboeva, Makhfuza Akhmedova, Rano Khamraeva, Xudoymurod Dusyarov
DYNAMIC ATTRIBUTE FILTERING FOR HIGH-ACCURACY MALICIOUS ACTIVITY RECOGNITION IN CLOUD PLATFORMS
Cloud computing is a critical infrastructure to the modern digital services, which provides the ability to store data on a scale, distributed computing, and the ability to deploy services flexibly. Moreover, the high rate of cloud environment development has also contributed to the risk of malicious intrusions like the spread of malware, unauthoriz...
By Sanaboyina Madhusudhana Rao, Arpit Jain
ACAPE-FID ADAPTIVE CONVOLUTION-ASSISTED POLAR ENCODER WITH FLEXIBLE ITERATIVE DECODING FOR HIGH-EFFICIENCY FPGA WIRELESS COMMUNICATION
Reliable wireless communication needs a highly efficient Forward Error Correction (FEC) technique in order to counter the effects of noise, interference, and losses. Most existing FEC techniques add too much redundancy and create extra latency, thereby reducing the efficiency of bandwidth utilization. Hence, the purpose of the current research is t...
By T. Ranjitha Devi, C. Kamalanathan
HOUSEHOLD E-WASTE MANAGEMENT AND CIRCULAR ECONOMY PATHWAYS IN KERALA WITH FOCUS ON POLICY AWARENESS AND DISPOSAL BEHAVIOUR
Electronic waste (e-waste) is posing an increasing challenge to environmental sustainability and human health in India, especially among the digitalizing states such as Kerala. This study examines the household electronic waste generation, disposal, concerns, policy awareness, and opportunities of circular economy through surveying 150 households i...
By K.V. Nidhi Varghese, D. Mahila Vasanthi Thangam
QUANTUM-ENHANCED DEEP LEARNING MODEL FOR CROP–WEED CLASSIFICATION IN SORGHUM IMAGERY USING THE SORGHUM CROP WEED DATASET CLASSIFICATION
Classification of crops and weeds is an important aspect in precision agriculture, as it aids in providing a means for efficient weed control and reduced herbicide applications to achieve high crop productivity. In this paper, a quantum-classical hybrid deep learning approach is presented for accurate identification of crops and weeds from sorghum ...
By J. Justina Michael, Logeshwari Radhakrishnan, R. Radhika, P.L. Joseph Raj, M. Mahalakshmi
EVALUATION RATIO OF SHEET PILE LENGTH AND DISTANCE EFFECTS SEEPAGE BENEATH CONCRETE DAMS USING SOFTWARE
Seepage through concrete dams plays an important role in the stability of the foundations due to the fact that high uplift pressures and exit gradients can cause piping, erosion, and ultimately the collapse of the structure. This research focuses on the effect of the position and the depth of the sheet piles on seepage in concrete dams employing a ...
By Alaa Mohsin Dawood, Noor Hashim Abd Almunaf, Hawraa Khalid Hannon, Furqan Wahhab Abdulsada, Melak Haider Almosawy
PREDICTING INVESTMENT PREFERENCES FOR GOLD AND REAL ESTATE AMONG INDIAN SALARIED EMPLOYEES USING GRAPH NEURAL NETWORKS
The decisions made in investing among salaried individuals are guided by financial objectives, risk appetite, and demographics, with gold and real estate continuing to be some of the most favored ones in India. In this study, investment preference for gold and real estate among salaried individuals in India and a prediction model for predicting pre...
By Twinkle, S Nazim Sha
SELF-ADAPTIVE COGNITIVE AI AGENT FRAMEWORK FOR PERSONALIZED ENGLISH SKILL DEVELOPMENT THROUGH CONTINUOUS LEARNER BEHAVIOUR MODELLING
The current teaching method of foreign languages is more and more adopting the method of using intelligent software to observe the learner's behavior and adapt teaching methods accordingly, but the teaching software currently used in the field of English learning still has many limitations such as relying on rigid rule sets or single-pass learning ...
By Zebo Botirova, Gulnoza Oybekova, Muzayyamkhon Zokirkhonova, Maftuna Rakhmatova, Feruza Erkulova, Rasulbek Ergashev
APPLICATION OF NEURO-SYMBOLIC KNOWLEDGE MINING FOR CUSTOMER BEHAVIOR ANALYSIS AND STRATEGIC CRM DECISION-MAKING
Rapid development of digital platforms has led to an abundance of data collected from customers, necessitating the use of intelligent methods that can be used to analyze behavior patterns and aid in making effective Customer Relationship Management (CRM) decisions. Current CRM artificial intelligence systems mainly aim at high prediction accuracy a...
By Reem Abdalla, H Niroshini Infantia