Abstract. This study gives a comprehensive analysis of the properties and interactions of fibrewise maximal and minimal topological spaces. Fibrewise topology extends classical topological concepts to structured spaces, providing a thorough understanding of spaces that vary across different dimensions. We study the basic theories, crucial properties, and characterizations of maximal and minimal fibrewise topological spaces. We investigate their role in different mathematical contexts and draw connections with related topological concepts. By providing exact mathematical formulations and comprehensive examples, this abstract advances the fields of topology and mathematical analysis by elucidating the unique properties and implications of fib

In this paper we define and study new concepts of fibrewise topological spaces over B namely, fibrewise closure topological spaces, fibrewise wake topological spaces, fibrewise strong topological spaces over B. Also, we introduce the concepts of fibrewise w-closed (resp., w-coclosed, w-biclosed) and w-open (resp., w-coopen, w-biopen) topological spaces over B; Furthermore we state and prove several Propositions concerning with these concepts.

This study aimed to detect of contamination of milk and local soft cheese with Staphylococcus aureus and their enterotoxins with attempt to detect the enterotoxin genes in some isolates of this bacteria. A total of 120 samples, 76 of raw milk and 44 of soft cheese were collected from different markets of Baghdad city. Enterotoxins in these samples were detected by VIDAS Set 2 system and it was found that enterotoxin A is present in a rate of 44.74% in milk samples and in a rate 54.50% in cheese samples. While other enterotoxins B, C, D, E were not found in any rate in any samples.
Through the study 60 isolates obtained from milk and cheeses were identified as Staphylococcus aureus by cultural, morphological and biochemical test by u

In this work the effect of annealing temperature on the structure and the electrical properties of Bi thin films was studied, the Bi films were deposited on glass substrates at room temperature by thermal evaporation technique with thickness (0.4 µm) and rate of deposition equal to 6.66Å/sec, all samples are annealed in a vacuum for one hour. The X-ray diffraction analysis shows that the prepared samples are polycrystalline and it exhibits hexagonal structure. The electrical properties of these films were studied with different annealing temperatures, the d.c conductivity for films decreases from 16.42 ? 10-2 at 343K to 10.11?10-2 (?.cm)-1 at 363K. The electrical activation energies Ea1 and Ea2 increase from 0.031 to 0.049eV and

In aspect-based sentiment analysis ABSA, implicit aspects extraction is a fine-grained task aim for extracting the hidden aspect in the in-context meaning of the online reviews. Previous methods have shown that handcrafted rules interpolated in neural network architecture are a promising method for this task. In this work, we reduced the needs for the crafted rules that wastefully must be articulated for the new training domains or text data, instead proposing a new architecture relied on the multi-label neural learning. The key idea is to attain the semantic regularities of the explicit and implicit aspects using vectors of word embeddings and interpolate that as a front layer in the Bidirectional Long Short-Term Memory Bi-LSTM. First, we

Many industrial systems involve multiple criteria and objectives, and they are very complex problems in computational science, such as task scheduling. We propose bi-criteria and bi-objective scheduling problems, which are solved by two nature-inspired evolutionary algorithms, such as Simulated Annealing (SA) and Bee Algorithm (BA). This problem is characterized by scheduling a batch of tasks on multiple machines, and it is fundamental because the solution should focus on the simultaneous optimization of two conflicting objectives: the makespan minimization and the total tardiness minimization. This problem is NP-Hard, and therefore, two evolutionary methods were used to search for solutions intelligently in this huge, very complex

Secure information transmission over the internet is becoming an important requirement in data communication. These days, authenticity, secrecy, and confidentiality are the most important concerns in securing data communication. For that reason, information hiding methods are used, such as Cryptography, Steganography and Watermarking methods, to secure data transmission, where cryptography method is used to encrypt the information in an unreadable form. At the same time, steganography covers the information within images, audio or video. Finally, watermarking is used to protect information from intruders. This paper proposed a new cryptography method by using thre

Advances in digital technology and the World Wide Web has led to the increase of digital documents that are used for various purposes such as publishing and digital library. This phenomenon raises awareness for the requirement of effective techniques that can help during the search and retrieval of text. One of the most needed tasks is clustering, which categorizes documents automatically into meaningful groups. Clustering is an important task in data mining and machine learning. The accuracy of clustering depends tightly on the selection of the text representation method. Traditional methods of text representation model documents as bags of words using term-frequency index document frequency (TFIDF). This method ignores the relationship an