High-tech augmentative and alternative communication (AAC) methods are on a constant rise; however, the interaction between the user and the assistive technology is still challenged for an optimal user experience centered around the desired activity. This review presents a range of signal sensing and acquisition methods utilized in conjunction with the existing high-tech AAC platforms for individuals with a speech disability, including imaging methods, touch-enabled systems, mechanical and electro-mechanical access, breath-activated methods, and brain–computer interfaces (BCI). The listed AAC sensing modalities are compared in terms of ease of access, affordability, complexity, portability, and typical conversational speeds. A revelation of the associated AAC signal processing, encoding, and retrieval highlights the roles of machine learning (ML) and deep learning (DL) in the development of intelligent AAC solutions. The demands and the affordability of most systems hinder the scale of usage of high-tech AAC. Further research is indeed needed for the development of intelligent AAC applications reducing the associated costs and enhancing the portability of the solutions for a real user’s environment. The consolidation of natural language processing with current solutions also needs to be further explored for the amelioration of the conversational speeds. The recommendations for prospective advances in coming high-tech AAC are addressed in terms of developments to support mobile health communicative applications.

https://www.mdpi.com/1424-8220/19/8/1911/pdf

Augmentative and Alternative Communication (AAC) Advances: A Review of Configurations for Individuals with a Speech Disability.

This paper presents a methodology for enhancement of panorama images environment by calculating high dynamic range. Panorama is constructing by merge of several photographs that are capturing by traditional cameras at different exposure times. Traditional cameras usually have much lower dynamic range compared to the high dynamic range in the real panorama environment, where the images are captured with traditional cameras will have regions that are too bright or too dark. A more details will be visible in bright regions with a lower exposure time and more details will be visible in dark regions with a higher exposure time. Since the details in both bright and dark regions cannot preserve in the images that are creating using traditional cameras, the proposed system have to calculate one using the images that traditional camera can actually produce. The proposed systems start by get LDR panorama image from multiple LDR images using SIFT features technology and then convert this LDR panorama image to the HDR panorama image using inverted local patterns. The results in this paper explained that the HDR panorama images that resulting from the proposed method is more realistic image and appears as it is a real panorama environment.

https://www.beei.org/index.php/EEI/article/download/2362/1735

Generation of high dynamic range for enhancing the panorama environment

The study examined the impact of the use of the Mozabook application for digital education in enhancing the performance of electronic-learning to ensure strategic educational success and the urgent need to use E-learning to increase and enable scientific knowledge to confront the exceptional circumstances that afflict the world in general and Iraq in particular for the spread of the Corona epidemic and its harm to society and home quarantine. Therefore, the diversity of software ap-plications available to teachers and students reflected the tremendous development and unique potential to achieve the goals of E-learning of what increased of knowledge of community awareness of how to use modern E-learning tools and in a way that ensures accuracy in use and awareness of its effective role in spreading education among the student community. The study aims to find better methods to deal and to prefer the role of digital education as in creating a knowledge-ability that meets the requirements of the educational process from methodological content, educational method and study tools such as blackboard, notebook, drawing tools and scientific, engineering, chemical, biological, geo-graphic and historical laboratories and other requirements that attract the student and his eagerness to study in this Digital education, so an application that works with three-dimensional technology was chosen with the availability of all audio, visual and sensory means to increase the interaction and desire of the student for the scientific subject, which is the educational Mozabook application. The study included test of major hypotheses, which leads to knowledge and determination of whether there is a correlation relationship, or an effect with significant moral, each according to its location for the application of the Mozabook digital educa-tion and E-learning. The two researchers selected academics and students as a field of the Ministry of Higher Education and Scientific Research for practical application based on the use of the questionnaire and the benefit of analyzing its results after its treatment using a number of statistical methods such as arithmetic mean, standard deviation, correlation coefficient, regression coefficient and path analysis.

/pdf/the-interactive-role-using-the-mozabook-digital-education-18teiss7j0.pdf

The Interactive Role Using the Mozabook Digital Education Application and its Effect on Enhancing the Performance of eLearning

The global online communication channel made possible with the internet has increased credit card fraud leading to huge loss of monetary fund in their billions annually for consumers and financial institutions. The fraudsters constantly devise new strategy to perpetrate illegal transactions. As such, innovative detection systems in combating fraud are imperative to curb these losses. This paper presents the combination of multiple classifiers through stacking ensemble technique for credit card fraud detection. The fuzzy-rough nearest neighbor (FRNN) and sequential minimal optimization (SMO) are employed as base classifiers. Their combined prediction becomes data input for the meta-classifier, which is logistic regression (LR) resulting in a final predictive outcome for improved detection. Simulation results compared with seven other algorithms affirms that ensemble model can adequately detect credit card fraud with detection rates of 84.90% and 76.30%.

/pdf/credit-card-fraud-detection-using-fuzzy-rough-nearest-2assu6vzyi.pdf

Credit Card Fraud Detection Using Fuzzy Rough Nearest Neighbor and Sequential Minimal Optimization with Logistic Regression

This study deals with the issue of improving educational services for schools of talent and intelligence. The availability of devices, equipment, sensors, and the Internet of things applications led to a direct contribution to improve the level of student education. In addition, the students can complete the tasks and homework easily. The talented and intelligent students are more efficient, skilled, and active. In addition, they are Deeping to understand virtual reality and coexist with it with awareness and consciousness of the development period of information, the spread of equipment, and smart devices. Educational entities achieved their goals by graduating intelligent students who can join the labor market and contribute to the development of the country. In this research, the important features of the Internet of things that are available in the educational environment were studied, and how to get the benefit from them in developing educational services and scientific research service. The Developing of artificial intelligence capabilities, building the right management strategies and creating comprehensive (security, health, and economic) databases that can be relied upon with complete reliability.

/pdf/enhancement-of-educational-services-by-using-the-internet-of-5gl70f86d4.pdf

Enhancement of educational services by using the internet of things applications for talent and intelligent schools

Du to the raising  number  of  using Internet of Things (I O T) for personal and commercial devices and applications, as well as the continues needs for improving the quality of the performance for the internet – connected devices enhance the researchers to investigate solutions for managing the data through the network Because of the fact that  the internet-connected devices needs addresses for each sensor node uses the IP-network and a large number of electronic modules is fabricated to be compatible with IPv4 only like NodeMcu, ESP8266, Arduino WIFI, and ESP32  with knowing that the IPv4 has a limited addresses number that will not be enough for the needs of  IOT developments, Many researchers turned to IPv6. In the  proposed system, another solution is suggested instead of the IPV6. The proposed idea is based on Non-IP Wireless Sensor Network (WSN) by connecting many sensing nodes to the sink-node that has an IP to forward the data to the server to be visualized in a web-portal. By this method, it is able to connect more than one node to the internet over only one IP, there for the data rate that are needed will be decreased. In addition, by using the non-IP network, the data rate and the power consuming by the sensor nodes have been reduced, the practical results are discussed for connecting four nodes over one IP4 and how it will reduce the data rate and the power consuming. In this work, the esp33 has been used as a Sink-node, and the wireless transceiver module( NRF24) has been utilized to transmit the data from nodes to esp32.

/pdf/reducing-the-data-rate-in-internet-of-things-applications-by-2fl2u78h2s.pdf

Reducing the Data Rate in Internet of Things Applications by Using Wireless Sensor Network

This New learning educational methods, which depending on Learning Management System (LMS), have been used by universities in the top education universities in the world. However, most of the Iraqi universities use the traditional education methods in the classroom. The purpose of this study was to examine the benefit of using LMS in higher education.  This study shows how to implement and use modern educational techniques in Engineering College of Wasit University. This paper shows that using modern education tools in the class lead to increase the productivity of student, save time with less effort for instructors with high accuracy of exam results. In addition, using LMS system allows students to obtain more information in a short time. Moreover, this system gives students an opportunity to interact with the instructor and among themselves. The findings show the benefits of integrating LMS in higher education and recommend other institutions to implement it.

https://www.learntechlib.org/p/216484/paper_216484.pdf

Using Modern Education Technique in Wasit University

In recent years, the Internet of things has become an urgent need in all of things that a person needs with least  effort and time. It covers in several areas, including controlling traffic and parking, following up on general and private buildings that  what you need of  periodic maintenance, and reducing energy through using  lighting Smart. In this paper, we focus on important thing and widespread in Iraq  , collection of solid waste in the streets without treatment, which causes environmental and psychological damage to the citizen.in addition , the solid waste deposal need set up sensors(RFID,GPS, ultrasonic, GSM,…etc), connecting them to Arduino Uno to accomplish specific intelligent processing that we need. Moreover, the system provides waste containers and warns the concerned departments in the city of the need to empty them when they reach a certain level, which makes the streets healthier, more attractive and free from rodents.

/pdf/using-internet-of-things-application-for-disposing-of-solid-2tvltm4xvx.pdf

Using Internet of Things Application for Disposing of Solid Waste

This paper focuses on respiratory phase detection and classification without the help of the airflow measurements. Instead of using the airflow measurements to identify breathing phases, the proposed work depends on advanced digital signal processing techniques to process the acoustic signal of respiration that was collected using a microphone placed in front of the subject's nose. The recorded signal is processed using the voiced-unvoiced algorithm to differentiate between the voiced period and the unvoiced (silence) period. The desired features are extracted from each voiced phase. Finally, support vector machine is used to distinguish between the inspiration and the expiration phases according to the extracted features. The signals were recorded from a number of subjects who do not have a history of pulmonary diseases. The proposed method has achieved an accuracy of 95% when tested on the subjects.

Automatic detection and classification of acoustic breathing cycles

Liver disease counts to be one of the most prevalent diseases in the worldwide. Therefore, this paper is aim to address the problem of predicting liver disease progression. As the existing predictive models focus on predicting the label of disease; the probability of developing the disease is still obscure. This paper, therefore, has proposed a model to predict the probability occurrence of liver diseases. The proposed predictive model used logistic regression abilities to predict the probability of liver disease occurrence. ILPD dataset was used to analyze the performance of the model. The predictive model has shown outstanding performance with a prediction accuracy rate of 72.4%, the sensitivity of 90.3%, the specificity of 78.3 %, Type I Error of 9.7 %, Type II Error of 21.7 %, and ROC of 0.758%. The model has furthermore confirmed the feasibility of the laboratory tests such as as (Age; Direct Bilirubin (DB), Alamine_Aminotransferase (SGPT), Total_Protiens (TP), Albumin (ALB)) to predict the disease progression. The predictive model will be helpful to patients and doctors to realize the progression of the disease and make a suitable timely intervention.

/pdf/a-predictive-model-for-liver-disease-progression-based-on-2a69bvrbgt.pdf

Omar Yahya

Papers

Reducing the Data Rate in Internet of Things Applications by Using Wireless Sensor Network

Using Modern Education Technique in Wasit University

Using Internet of Things Application for Disposing of Solid Waste

Automatic detection and classification of acoustic breathing cycles

A Predictive model for liver disease progression based on logistic regression algorithm