Energy savings are very common in IoT sensor networks because IoT sensor nodes operate with their own limited battery. The data transmission in the IoT sensor nodes is very costly and consume much of the energy while the energy usage for data processing is considerably lower. There are several energy-saving strategies and principles, mainly dedicated to reducing the transmission of data. Therefore, with minimizing data transfers in IoT sensor networks, can conserve a considerable amount of energy. In this research, a Compression-Based Data Reduction (CBDR) technique was suggested which works in the level of IoT sensor nodes. The CBDR includes two stages of compression, a lossy SAX Quantization stage which reduces the dynamic range of the sensor data readings, after which a lossless LZW compression to compress the loss quantization output. Quantizing the sensor node data readings down to the alphabet size of SAX results in lowering, to the advantage of the best compression sizes, which contributes to greater compression from the LZW end of things. Also, another improvement was suggested to the CBDR technique which is to add a Dynamic Transmission (DT-CBDR) to decrease both the total number of data sent to the gateway and the processing required. OMNeT++ simulator along with real sensory data gathered at Intel Lab is used to show the performance of the proposed technique. The simulation experiments illustrate that the proposed CBDR technique provides better performance than the other techniques in the literature.
With the rapid development of smart devices, people's lives have become easier, especially for visually disabled or special-needs people. The new achievements in the fields of machine learning and deep learning let people identify and recognise the surrounding environment. In this study, the efficiency and high performance of deep learning architecture are used to build an image classification system in both indoor and outdoor environments. The proposed methodology starts with collecting two datasets (indoor and outdoor) from different separate datasets. In the second step, the collected dataset is split into training, validation, and test sets. The pre-trained GoogleNet and MobileNet-V2 models are trained using the indoor and outdoor se
... Show MoreRecently, there has been an increasing advancement in the communications technology, and due to the increment in using the cellphone applications in the diverse aspects of life, it became possible to automate home appliances, which is the desired goal from residences worldwide, since that provides lots of comfort by knowing that their appliances are working in their highest effi ciency whenever it is required without their knowledge, and it also allows them to control the devices when they are away from home, including turning them on or off whenever required. The design and implementation of this system is carried out by using the Global System of Mobile communications (GSM) technique to control the home appliances – In this work, an ele
... Show MoreBackground: Anterior disc displacement with reduction (ADDWR) is the most common form of the internal derangement (ID) of temporomandibular joint (TMJ). It is a painful progressive dysfunction and clinically characterized by reciprocal clicking due to shift in the disc anteriorly in relation to the condyle and fossa during mandible elevation. Minimally invasive therapy such as intra-articular injection of platelet-rich plasma (PRP) has been used. PRP is a natural autologous product with a high platelet concentration obtained by centrifugation process to enhance tissue healing through several growth factors (GFs), which are released after endogenous activation. The aim of this study is to assess this technique which is increasingly used toda
... Show MoreBackground: In recent years, the prevalence of obesity has climbed sharply. Still, only a few safe and effective medications are approved as weight-loss drugs. Objective: This study aims to assess the knowledge and practice of community pharmacists in Iraq regarding the use of Liraglutide and Semaglutide as weight-loss medications. Method: A cross-sectional survey was implemented using a validated questionnaire and a convenient sample of Iraqi community pharmacists from different governorates. The questionnaire was created after conducting a literature review of the most important articles about liraglutide and semaglutide. The questionnaire consists of three sections. The first part was used to collect demographic information. The
... Show MoreBackground: In recent years, the prevalence of obesity has climbed sharply. Still, only a few safe and effective medications are approved as weight-loss drugs. Objective: This study aims to assess the knowledge and practice of community pharmacists in Iraq regarding the use of Liraglutide and Semaglutide as weight-loss medications. Method: A cross-sectional survey was implemented using a validated questionnaire and a convenient sample of Iraqi community pharmacists from different governorates. The questionnaire was created after conducting a literature review of the most important articles about liraglutide and semaglutide. The questionnaire consists of three sections. The first part was used to collect demographic information. The second a
... Show MoreThis document provides an examination of research, on combining orthogonal frequency division multiplexing (OFDM) and optical fibers in communication networks. With the increasing need for data speeds and efficient use of bandwidth experts have been exploring the connection between OFDM, valued for its ability to handle multipath interference and optimize spectral usage and optical fiber technology which provides superior data transmission capabilities with low signal loss and strong protection, against electromagnetic disturbances. The review summarizes discoveries from studies examining the pros and cons of using OFDM, in optical communication networks. It discusses obstacles like fiber nonlinearity, chromatic dispersion and the effects o
... Show MoreImproved Merging Multi Convolutional Neural Networks Framework of Image Indexing and Retrieval