Abstract

People are supposed to use language harmoniously and compatibly. However, aggression may characterize much of human communication. Aggression has long been recognized as a negative anti-social issue that prevails in most personal interactions. If it abounds in familial communications, it is more dangerous due to its harmful effects on individuals, and consequently on societies. Aggression refers to all the instances in which we try to get our way without any consideration for others. Moriarty’s novel (2014), Big Little Lies, is argued to represent the patterns of aggressive communications. This study aims to find out the motivations behind aggressive language in familial communication in this

The topological indices of the "[(µ3-2, 5-dioxyocyclohexylidene)-bis ((2-hydrido)-nonacarbonyltriruthenium]” were studied within the quantum theory of atoms in the molecule (QTAIM), clusters are
analyzed using the density functional theory (DFT). The estimated topological variables accord with prior
descriptions of comparable transition metal complexes. The Quantum Theory of Atom, in molecules
investigation of the bridging core component, Ru3H2, revealed critical binding points (chemical bonding)
between Ru (1) and Ru (2) and Ru (3). Consequently, delocalization index for this non-bonding interaction
was calculated in the core of Ru3H2, the interaction is of the (5centre–5electron) class.

The utilization of sugarcane molasses (SCM), a byproduct of sugar refining, offers a promising bio-based alternative to conventional chemical admixtures in cementitious systems. This study investigates the effects of SCM at five dosage levels, 0.25%, 0.50%, 0.75%, 1.00%, and 1.25% by weight of cement, on cement mortar performance across fresh, mechanical, thermal, durability, and density criteria. A comprehensive experimental methodology was employed, including flow table testing, compressive strength (7, 14, and 28 days) and flexural strength measurements, embedded thermal sensors for real-time hydration monitoring, water absorption and chloride ion penetration tests, as well as 28-day density determination. Results revealed clear

Cassava, a significant crop in Africa, Asia, and South America, is a staple food for millions. However, classifying cassava species using conventional color, texture, and shape features is inefficient, as cassava leaves exhibit similarities across different types, including toxic and non-toxic varieties. This research aims to overcome the limitations of traditional classification methods by employing deep learning techniques with pre-trained AlexNet as the feature extractor to accurately classify four types of cassava: Gajah, Manggu, Kapok, and Beracun. The dataset was collected from local farms in Lamongan Indonesia. To collect images with agricultural research experts, the dataset consists of 1,400 images, and each type of cassava has

The internet has been a source of medical information, it has been used for online medical consultation (OMC). OMC is now offered by many providers internationally with diverse models and features. In OMC, consultations and treatments are available 24/7. The covid-19 pandemic across-the-board, many people unable to go to hospital or clinic because the spread of the virus. This paper tried to answer two research questions. The first one on how the OMC can help the patients during covid-19 pandemic. A literature review was conducted to answer the first research question. The second one on how to develop system in OMC related to covid-19 pandemic. The system was developed by Visual Studio 2019 using software object-oriented approach. O

Solar energy is one of the immeasurable renewable energy in power generation for a green, clean and healthier environment. The silicon-layer solar panels absorb sun energy and converts it into electricity by off-grid inverter. Electricity is transferred either from this inverter or from transformer, consumed by consumption unit(s) available for residential or economic purposes. The artificial neural network is the foundation of artificial intelligence and solves many complex problems which are difficult by statistical methods or by humans. In view of this, the purpose of this work is to assess the performance of the Solar - Transformer - Consumption (STC) system. The system may be in complete breakdown situation due to failure of both so

Computer vision seeks to mimic the human visual system and plays an essential role in artificial intelligence. It is based on different signal reprocessing techniques; therefore, developing efficient techniques becomes essential to achieving fast and reliable processing. Various signal preprocessing operations have been used for computer vision, including smoothing techniques, signal analyzing, resizing, sharpening, and enhancement, to reduce reluctant falsifications, segmentation, and image feature improvement. For example, to reduce the noise in a disturbed signal, smoothing kernels can be effectively used. This is achievedby convolving the distributed signal with smoothing kernels. In addition, orthogonal moments (OMs) are a cruc

Abstract: The utility of DNA sequencing in diagnosing and prognosis of diseases is vital for assessing the risk of genetic disorders, particularly for asymptomatic individuals with a genetic predisposition. Such diagnostic approaches are integral in guiding health and lifestyle decisions and preparing families with the necessary foreknowledge to anticipate potential genetic abnormalities. The present study explores implementing a define-by-run deep learning (DL) model optimized using the Tree-structured Parzen estimator algorithm to enhance the precision of genetic diagnostic tools. Unlike conventional models, the define-by-run model bolsters accuracy through dynamic adaptation to data during the learning process and iterative optimization