ULUGH BEG MADRASAH AS A PILLAR OF ASTRONOMICAL ADVANCEMENT IN CENTRAL ASIA
The Ulugh Beg Madrasah in Samarkand is a prominent scientific and educational institution of Central Asia. The construction of the madrasah was initiated in the 15th century by Ulugh Beg, the Timurid ruler and astronomer. The madrasah played a great role in the development of astronomy, mathematics, and Islamic studies. This article discusses the h...
By Mavzuna Mukhiddinova, Valisher Sapayev, Manzura Yakubova, Maqsad Maytakubov, Dildora Agzamova, Pardaxol Haydarova, Zukhrobiddin Olimov
METAHEURISTIC-DRIVEN HYPERPARAMETER OPTIMIZATION FOR BERT IN SENTIMENT ANALYSIS
Sentiment analysis has come out as an important activity in natural language processing (NLP) applications whose data analysis is in high demand at present in the modern world. The BERT (Bidirectional Encoder Representations from Transformers) algorithm has proved to be extremely efficient when it comes to sentiment analysis tasks, and its potentia...
By Alaa A. El-Demerdash, Nahla B. Abdel- Hamid, Amira Y. Haikal
IMPLEMENTATION OF LOW POWER MEMRISTOR CONTENT ADDRESSABLE MEMORY USING FINFET
The research environment is promptly looking at the extensive development of memristor devices in industrial applications. Future technology is eagerly waiting for the upcoming developments in memristor-based devices. Memristor regulates the current flow in devices and the amount of previously flowed charges, which are stored as memory in applicati...
By Ancy Joy, Jinsa Kuruvilla
THE SURVEY OF CLUSTER BASED DATA COLLECTION PROCESS FOR IOT ENABLED WIRELESS SENSOR NETWORK USING SEVERAL OPTIMIZATION TECHNIQUE
Offers a detailed analysis of optimization algorithms and routing protocols are created to overcome the issues on energy efficiency with the Internet of Things (IoT) Enabled Wireless Sensor Networks (WSNs). The study analyses nature-based metaheuristic methods such as the Genetic Algorithms, Particle Swarm Optimization, Firefly Optimization, Gray W...
By R. Abirami, K. Sathishkumar, Liu Guanzhou, M. Ramalingam, Wasim Ahmad, Ali Bostani
PREDICTION OF TOXIC-METABOLIC DISORDERS AT EMERGENCY CONDITIONS USING MULTI-LABEL CLASSIFICATION IN MACHINE LEARNING
Diagnosing critical conditions like Acute Liver Failure (ALF), Methanol Toxicity (MT), Alcohol Poisoning (AP), and Diabetic Ketoacidosis (DKA) is difficult due to similar symptoms and complex interdependent metabolism, often resulting in delayed and incorrect diagnoses in historic clinical practice. We present a hybrid machine learning framework in...
By S. Ramadoss, A. Kumaravel
INTEGRATING SUSTAINABLE PRACTICES AND AUTOMATION IN MINING ENGINEERING EDUCATION FOR THE MODERN ERA
Sustainable practice and automation in the field of mining engineering are becoming a fundamental component of educating the future engineers to respond to the challenges facing a changing mining industry. As mining operators are increasingly being pressured to utilize more environmentally sustainable practices and to adopt new automation technolog...
By Kamala Kodirova, Ozodbek Nematov, Anastasia Seitasmanova, Sarvinoz Qodirova, Feruza Sapaeva, Fotima Babajanova, Bakhtiyor Polvonov, Abduraim Adilov
A COMPARATIVE STRATIFICATION OF FISH SPECIES USING TRANSFER LEARNING ON PRE-TRAINED DEEP LEARNING NETWORKS JUXTAPOSED WITH SHUFFLERES – A HYBRID DEEP NETWORK CLASSIFIER
The marine ecoculture is an evolving realm that necessitates thorough scrutiny of the diverse species it comprises, along with the explicit identification of the species classes that form, to be crucial for aquaculture and the ecological conservation of fish diversity. The stratification through image classification is a well-studied area of resear...
By R.P. Selvam, R. Devi
ENTREPRENEURIAL MARKETING AND INNOVATION CAPABILITIES IN HIGH TECHNOLOGY STARTUPS IN EMERGING ECONOMIES
Emerging economies have a dynamic and challenging business environment, which requires entrepreneurial marketing and innovation capabilities of the high-tech startups. Such startups are usually faced with issues of lack of resources, regulation and lack of proper infrastructure. In this regard, it is important to combine entrepreneurial marketing p...
By Jainish Roy, Rajesh Sehgal
PRECISION STOCK MARKET TREND ANALYSIS WITH HYBRID SMOOTH SVM AND WEIGHED VULTURE OPTIMIZATION
Accurate prediction of stock market trends remains a challenging task due to high volatility, non-linearity, and the dynamic nature of financial time series data. Conventional statistical and machine learning typically do not provide consistent performance due to the fixed hyperparameter settings and the inability to adapt to a shifting market situ...
By N. Subalakshmi, M. Jeyakarthic, V. Mohanaselvam
ANALYZING THE STABILITY OF SMART GRIDS USING POLICY-BASED REINFORCEMENT LEARNING MODEL
The stability of smart grids (SG) plays a critical role in improving the stability of power supply, particularly when system failures or sensor breakdowns could occur and result in a lack of input data. This paper provides a new method of prediction of smart grid consistency by using a Gradient Policy prediction model, which is based on reinforceme...
By S. Mahendran, B. Gomathy