An Analytical Study on the Implementation of a Healthcare App to Assist People with Disabilities Using Cloud Computing and IoT

This study targets a group of people who require care, that is, people with special needs. The significance of this study lies in addressing the main problem that this group suffers from, which is the lack of awareness and information that leads to the acceptance of that group in society. This work aims to create a mobile application that contributes to spreading knowledge among people with special needs and enhancing their skills to help them become accepted by community members. This application supports people with special needs with training resources, education, suitable jobs, and other services helping them in developing their experiences and knowledge to be active in society. In addition, an evaluation questionnaire has been developed to collect data from both the private and public sectors to classify the building blocks necessary for KSA to incorporate the Internet of Things (IoT) and cloud computing into the healthcare sector. As a result, most respondents acknowledge the importance of a streamlined data-gathering process, the IoT, and cloud-based computing to meet their healthcare needs. Lastly, six main blocks for checking suppliers and the public to accept IoT and cloud healthcare applications are then acknowledged in this paper

A Sentimental Analysis Tool for Determining the Promotional Success of Fashion Images on Instagram

Sentiment Analysis (SA) or Opinion Mining is the process of analysing natural language texts to detect anemotion or a pattern of emotions towards a certain product to make a decision about that product. SA is atopic of text mining, Natural Language Processing (NLP) and web mining disciplines. Research in SA iscurrently at its peak given the amount of data generated from social media networks. The concept is thatconsumers are expressing exactly what they need, want and expect from a product but on the other hand thecompanies don’t have the tools to analyse and understand these feelings to satisfy these consumersaccordingly.One of the applications that generate a high rate of reactions and sentiments in social networks isInstagram. This study focuses on analysing the reactions generated by the top 50 fashion houses on Instagramgiven their top 20 images with the highest number of likes. The approach taken in this study is to qualify thevisual aesthetics of fashion images and to establish why some succeed on social media more than others.The basic question asked in this paper is whether there are certain visual aesthetics that appeal more to theuser and are therefore more successful on social media than others as determined by a measure we introduce,‘Social Value’. To do so, a sentiment analysis tool is developed to measure the proposed social value of eachimage. An input of comments from each image will be processed. Each comment will go through a preprocessingphase; each word will be placed through a lexicon to identify if it is positive or negative. Theoutput of the lexicon is a score value assigned to each comment to identify its degree of positivity, negativity,or it has no effect on the social value. Adding to these results, the number of likes and shares would also betaken into consideration quantifying the image’s value. A cumulative result is then produced to determine thesocial value of an image. Keywords: Sentiment Analysis; Opinion Mining; Instagram; Social Value; Aesthetic

Poslovna inteligencija i otvoreni podaci: Mogućnosti za izvođenje vrednih informacija u oblasti turizma

This paper aims to introduce the concept of data analysis which could easily be implemented by anybody involved in the subject matter with basic IT knowledge and skills. The paper is divided into two parts, the first of which presents an overview of related research from two points of view: (1) publications which refer to the analysis, or the overall use of open data from the tourism domain and (2) publications which use business intelligence tools to analyse tourism data. Results indicate that there is a significant number of publications but none of them combines the two issues in the field of tourism (open data and business intelligence). The second part refers to the possibilities of using Power BI, the business intelligence tool for analysing available open data about tourism in Serbia.Publishe

Development Schemes of Electric Vehicle Charging Protocols and Implementation of Algorithms for Fast Charging under Dynamic Environments Leading towards Grid-to-Vehicle Integration

This thesis focuses on the development of electric vehicle (EV) charging protocols under a dynamic environment using artificial intelligence (AI), to achieve Vehicle-to-Grid (V2G) integration and promote automobile electrification. The proposed framework comprises three major complementary steps. Firstly, the DC fast charging scheme is developed under different ambient conditions such as temperature and relative humidity. Subsequently, the transient performance of the controller is improved while implementing the proposed DC fast charging scheme. Finally, various novel techno-economic scenarios and case studies are proposed to integrate EVs with the utility grid. The proposed novel scheme is composed of hierarchical stages; In the first stage, an investigation of the temperature or/and relative humidity impact on the charging process is implemented using the constant current-constant voltage (CC-CV) protocol. Where the relative humidity impact on the charging process was not investigated or mentioned in the literature survey. This was followed by the feedforward backpropagation neural network (FFBP-NN) classification algorithm supported by the statistical analysis of an instant charging current sample of only 10 seconds at any ambient condition. Then the FFBP-NN perfectly estimated the EV’s battery terminal voltage, charging current, and charging interval time with an error of 1% at the corresponding temperature and relative humidity. Then, a nonlinear identification model of the lithium-polymer ion battery dynamic behaviour is introduced based on the Hammerstein-Wiener (HW) model with an experimental error of 1.1876%. Compared with the CC-CV fast charging protocol, intelligent novel techniques based on the multistage charging current protocol (MSCC) are proposed using the Cuckoo optimization algorithm (COA). COA is applied to the Hierarchical technique (HT) and the Conditional random technique (CRT). Compared with the CC-CV charging protocol, an improvement in the charging efficiency of 8% and 14.1% was obtained by the HT and the CRT, respectively, in addition to a reduction in energy losses of 7.783% and 10.408% and a reduction in charging interval time of 18.1% and 22.45%, respectively. The stated charging protocols have been implemented throughout a smart charger. The charger comprises a DC-DC buck converter controlled by an artificial neural network predictive controller (NNPC), trained and supported by the long short-term memory neural network (LSTM). The LSTM network model was utilized in the offline forecasting of the PV output power, which was fed to the NNPC as the training data. The NNPC–LSTM controller was compared with the fuzzy logic (FL) and the conventional PID controllers and perfectly ensured that the optimum transient performance with a minimum battery terminal voltage ripple reached 1 mV with a very high-speed response of 1 ms in reaching the predetermined charging current stages. Finally, to alleviate the power demand pressure of the proposed EV charging framework on the utility grid, a novel smart techno-economic operation of an electric vehicle charging station (EVCS) in Egypt controlled by the aggregator is suggested based on a hierarchical model of multiple scenarios. The deterministic charging scheduling of the EVs is the upper stage of the model to balance the generated and consumed power of the station. Mixed-integer linear programming (MILP) is used to solve the first stage, where the EV charging peak demand value is reduced by 3.31% (4.5 kW). The second challenging stage is to maximize the EVCS profit whilst minimizing the EV charging tariff. In this stage, MILP and Markov Decision Process Reinforcement Learning (MDP-RL) resulted in an increase in EVCS revenue by 28.88% and 20.10%, respectively. Furthermore, the grid-to-vehicle (G2V) and vehicle-to-grid (V2G) technologies are applied to the stochastic EV parking across the day, controlled by the aggregator to alleviate the utility grid load demand. The aggregator determined the number of EVs that would participate in the electric power trade and sets the charging/discharging capacity level for each EV. The proposed model minimized the battery degradation cost while maximizing the revenue of the EV owner and minimizing the utility grid load demand based on the genetic algorithm (GA). The implemented procedure reduced the degradation cost by an average of 40.9256%, increased the EV SOC by 27%, and ensured an effective grid stabilization service by shaving the load demand to reach a predetermined grid average power across the day where the grid load demand decreased by 26.5% (371 kW)

Immersive virtual reality in improving communication skills in children with Autism

Individuals in the Autism Spectrum often encounter situations where they have to respond to questions and situations that they do not know how to respond to, such as, questions asked by strangers including ones related to daily-life activities. A variety of research has been done to improve social and communication impairments in children with autism using technology. Immersive virtual reality is a relatively recent technology with a potential to bring an effective solution and used as a therapeutic tool to develop different skills. This paper presents a virtual reality solution to reduce the gap experienced by autistic children due to their inability to establish a communication. An interactive scenario-based system that uses role-play and turn-taking technique was implemented to evaluate and verify the effectiveness of immersive environment on the social performance of an autistic child. Preliminary testing of the system demonstrated the feasibility of VR-based system as a tool for improving the communication skill in Autism Spectrum Disorder (ASD) children. The results of the comparative usability study show the effectiveness of immersive VR in motivating and satisfying the autistic.Scopu

Cultural Heritage Management in Turkey and Egypt: A Comparative Study

Recently, there are various threats encountering the cultural heritage worldwide. Indeed, these threats make conservation and management of cultural heritage a complex process to deal with. Since the 1970s, the UNESCO started to issue many guidelines and charters related to the management and conservation of the cultural heritage. Meanwhile, the Cultural Heritage Management (CHM) including sustainability has become a significant concept especially in the European countries. Turkey and Egypt are famous for their diversified cultural and natural heritage attractions which give an opportunity for both countries to be appealing tourist destinations Nevertheless, cultural heritage of Turkey and Egypt suffers from several major problems at present. All of these require a selective policy, urgent conservation, constant monitoring, protection, and maintenance. This paper aims to examine and compare cultural heritage management in both countries according to specific criteria which will evaluate the current situation of the cultural heritage management in Turkey and Egypt from different aspects (legal framework, institutional/administrational framework, resources, and current challenges). Also, this paper shows how the cultural heritage management has been developed in both countries. Generally, it highlights the increasing importance of cultural heritage management. Furthermore; it will emphasize the significance of sustainability practices in managing world heritage sites

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Design of immersive virtual reality system to improve communication skills in individuals with autism

Individuals with autism spectrum disorder (ASD) regularly experience situations in which they need to give answers but do not know how to respond; for example, questions related to everyday life activities that are asked by strangers. Research geared at utilizing technology to mend social and communication impairments in children with autism is actively underway. Immersive virtual reality (VR) is a relatively recent technology that has the potential of being an effective therapeutic tool for developing various skills in autistic children. This paper presents an interactive scenario-based VR system developed to improve the communications skills of autistic children. The system utilizes speech recognition to provide natural interaction and role-play and turntaking to evaluate and verify the effectiveness of the immersive environment on the social performance of autistic children. In experiments conducted, participants showed more improved performance with a computer augmented virtual environment (CAVE) than with a head mounted display (HMD) or a normal desktop. The results indicate that immersive VR could be more satisfactory and motivational than desktop for children with ASD.Scopu