Localization is an essential demand in wireless sensor networks (WSNs). It relies on several types of measurements. This paper focuses on positioning in 3-D space using time-of-arrival- (TOA-) based distance measurements between the target node and a number of anchor nodes. Central localization is assumed and either RF, acoustic or UWB signals are used for distance measurements. This problem is treated by using iterative gradient descent (GD), and an iterative GD-based algorithm for localization of moving sensors in a WSN has been proposed. To localize a node in 3-D space, at least four anchors are needed. In this work, however, five anchors are used to get better accuracy. In GD localization of a moving sensor, the algo

The proposal of this study is demonstrating a simple vapor sensor for chloroform (CHCI₃) utilitizing air gap region of the Mach-Zehnder interferometer (MZI) by using a single mode optical fiber coupler (3 dB) structure. In the last few decades, flammable liquids such as chloroform have been highly used. This chemical liquid has some degrees of carcinogenic effects in humans in addition to acute and chronic exposure results like blurred vision and nausea.  The two arms of MZI contain a free space gap utilized to serve the sensing mechanism by adding chemical liquid volumes (0.2, 0.4, 0.6, 0.8, and 1) ml and to set the phase difference with air-gap distance 0.5 mm. The small variation in the effective refractive index of ch

Data mining is one of the most popular analysis methods in medical research. It involves finding patterns and correlations in previously unknown datasets. Data mining encompasses various areas of biomedical research, including data collection, clinical decision support, illness or safety monitoring, public health, and inquiry research. Health analytics frequently uses computational methods for data mining, such as clustering, classification, and regression. Studies of large numbers of diverse heterogeneous documents, including biological and electronic information, provided extensive material to medical and health studies.

The current study was conducted in Baghdad governorate (Karkh and Al-Rasafa regions) which included collecting 50 samples of freshly slaughtered sheep meat randomly collected from local slaughter areas and approved governmental slaughterhouses (25 liver and 25 ulna muscles). The results of the aflatoxin B1 detection showed that all samples were contaminated with this toxin at different concentrations ranging from 25–422 ppb and 65–492 ppb for each ulna muscles and liver, respectively. The histopathological and immunological study was conducted in meat samples containing higher and lower concentrations of the toxin. The results of the pathological study in the liver revealed that the concentration (492 ppb) caused thickening of t

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 Optical Fiber sensor based on the Surface Plasmon Resonance (SPR) technology has
been a successful performance sensing and presents high sensitivity. This thesis investigates the
performance of several structure of SPR sensor in field of refractive index and chemical
applications. A structure of Multi-Mode Fiber- Single Mode Fiber- Multi Mode Fiber (MMFSMF-MMF)

At the level of both individuals and companies, Wireless Sensor Networks (WSNs) get a wide range of applications and uses. Sensors are used in a wide range of industries, including agriculture, transportation, health, and many more. Many technologies, such as wireless communication protocols, the Internet of Things, cloud computing, mobile computing, and other emerging technologies, are connected to the usage of sensors. In many circumstances, this contact necessitates the transmission of crucial data, necessitating the need to protect that data from potential threats. However, as the WSN components often have constrained computation and power capabilities, protecting the communication in WSNs comes at a significant performance pena

Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an object under de

Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an ob