Crow-ENN

DNA sequence classification is one of the main research activities in bioinformatics on which, many researchers have worked and are working on it. In bioinformatics, machine learning can be applied for the analysis of genomic sequences like the classification of DNA sequences, comparison of DNA sequences. This article proposes a new hybrid meta-heuristic model called Crow-ENN for leukemia DNA sequences classification. The proposed algorithm is the combination of the Crow Search Algorithm (CSA) and the Elman Neural Network (ENN). DNA sequences of Leukemia are used to train and test the proposed hybrid model. Five other comparable models i.e. Crow-ANN, Crow-BPNN, ANN, BPNN and ENN are also trained and tested on these DNA sequences. The performance of models is evaluated in terms of accuracy and MSE. The overall simulation results show that the proposed model has outperformed all the other five comparable models by attaining the highest accuracy of over 99%. This model may also be used for other classification problems in different fields because it can achieve promising results.

Effects of Electromagnetic Radiation of Mobile Phones on the Human Brain

With the expanding use of wireless cellular networks, concerns have been communicated about the possible interaction of electromagnetic radiation with the human life, explicitly, the mind and brain. Mobile phones emanate radio frequency waves, a type of non-ionizing radiation, which can be absorbed by tissues nearest to where the telephone is kept. The effects on neuronal electrical activity, energy metabolism, genomic responses, neurotransmitter balance, blood–brain barrier permeability, mental psychological aptitude, sleep, and diverse cerebrum conditions including brain tumors are assessed. Health dangers may likewise develop from use of cellular communication, for instance, car accidents while utilizing the device while driving. These indirect well-being impacts surpass the immediate common troubles and should be looked into in more detail later on. In this chapter, we outline the possible biological impacts of EMF introduction on human brain.

Promoting Healthy Food Habits Through an mHealth Application

MHealth involves the provision of health products, services, and information through mobile and wireless technologies. Companies and institutions in the healthcare sector are progressively proposing innovative mhealth solutions that simultaneously reduce costs and improve the quality of life of citizens. In this chapter, a mobile app is proposed to promote healthy food habits through better management of the food each person has at home. This app intends to reduce food waste and promotes the development of good food practices based on the nutritional value of each recipe and the indication of potential allergies to ingredients. The development of the app was based on the best practices of Mobile UX, which is fundamental to offer intuitive interaction and rapid learning for the user. Furthermore, other factors also relevant in the context of mobile apps were considered in the development, namely usability, data backup, performance, security, scalability, and interoperability.

Insulin DNA Sequence Classification Using Levy Flight Bat With Back Propagation Algorithm

Various nature-inspired algorithms are used for optimization problems. Recently, one of the nature-inspired algorithms became famous because of its optimality. In order to solve the problem of low accuracy, famous computational methods like machine learning used levy flight Bat algorithm for the problematic classification of an insulin DNA sequence of a healthy human, one variant of the insulin DNA sequence is used. The DNA sequence is collected from NCBI. Preprocessing alignment is performed in order to obtain the finest optimal DNA sequence with a greater number of matches between base pairs of DNA sequences. Further, binaries of the DNA sequence are made for the aim of machine readability. Six hybrid algorithms are used for the classification to check the performance of these proposed hybrid models. The performance of the proposed models is compared with the other algorithms like BatANN, BatBP, BatGDANN, and BatGDBP in term of MSE and accuracy. From the simulations results it is shown that the proposed LFBatANN and LFBatBP algorithms perform better compared to other hybrid models.

Mobile Apps for Human Nutrition

Lack of proper diet causes many diseases like night blindness, gum death, rickets, osteomalacia, etc. Similarly, undernutrition will cause a low intelligence quotient (IQ), osteoporosis, anemia, scurvy, pellagra, etc. Over-nutrition will result in obesity, Type II diabetes mellitus, and ischemic heart diseases. Also, the unhygienic intake of food, intake of food on no fixed time, intake of fast food intake of other unhealthy stuff can lead to irregularities in the human body. Adopting healthy habits, physical activity, exercise, sports, and walking can lead to a healthy lifestyle of an individual. In addition, today's busy schedule and less time availability restricts individuals to visit the doctors or nutritionists. Many mobile applications were developed for monitoring and calculating an energy level as well as healthy nutrition. This review chapter has assessed the use and features of various mobile phone health applications, which helps individuals to overcome and monitor the above-mentioned health-related issues.

Psychology With Mahnoor App

One in four people in the world will be affected by mental or neurological disorders at some point in their lives. Around 450 million people currently suffer from such conditions, placing mental disorders among the leading causes of ill-health and disability worldwide, according to the World Health Organization. Keeping in mind the above facts, Self Assessment Psychology Dictionary and Notes app has been designed and developed to educate psychology students and psychological patients. With the help of this application the user can do different physiological tests like Hads Mood, Internet Addiction Test, The Robertson Emotional Distress Scale, Beck Anxiety Inventory and Zung Self-Rating Anxiety Scale. The application has a smart algorithm that calculates the result on the basis of the user inputs. The application also generates the certificate for the user to share and use it for further treatment. The application provides detail information about psychology and psychologist. Apart from that, the application has a psychology dictionary of psychology-related topics.

QoS-Aware Data Dissemination Mechanisms for Wireless Body Area Networks

To reduce healthcare costs and improve human well-being, a promising technology known as wireless body area networks (WBANs) has recently emerged. It is comprised of various on-body as well as implanted sensors which seamlessly monitor the physiological characteristics of the human body. The information is heterogeneous in nature, requires different QoS factors. The information may be classified as delay-sensitive, reliability-sensitive, critical, and routine. On-time delivery and minimum losses are the main QoS-factors required to transmit the captured information. Various researchers have work to provide the required QoS, and some have also considered the other constraints due to the characteristics and texture of the human body. In this research work, we have discussed the communication architecture of WBANS along with the various challenges of WBANS. Furthermore, we have classified and discussed the existing QoS-aware data dissemination mechanisms. In the end, a comparative study of existing QoS-aware data dissemination mechanisms highlights the pros and cons of each mechanism.

The Effect of List-Liner-Based Interaction Technique in a 3D Interactive Virtual Biological Learning Environment

Various interaction techniques (such as direct, menu-based, etc.) are provided to allow users to interact with virtual learning environments. These interaction techniques improve their performance and learning but in a complex way. In this chapter, we investigated a simple list-liner based interface for gaining access to different modules within a 3D interactive Virtual Learning Environment (VLE). We have implemented a 3D interactive biological VLE for secondary school level students by using virtual mustard plant (VMP), where students interact by using 3D interactive device with the help of list-liner based interface. The aim of this work is to provide an easy interaction interface to use list-liner interaction technique by using 3D interactive device in an information-rich and complex 3D virtual environment. We compared list-liner interface with direct interface and evaluations reveal that the list-liner interface is very suitable and efficient for student learning enhancement and that the students can easily understand and use the system.

Optimizing Learning Weights of Back Propagation Using Flower Pollination Algorithm for Diabetes and Thyroid Data Classification

A number of ANN methods are used, but BP is the most commonly used algorithms to train ANNs by using the gradient descent method. Two main problems which exist in BP are slow convergence and local minima. To overcome these existing problems, global search techniques are used. This research work proposed new hybrid flower pollination based back propagation HFPBP with a modified activation function and FPBP algorithm with log-sigmoid activation function. The proposed HFPBP and FPBP algorithm search within the search space first and finds the best sub-search space. The exploration method followed in the proposed HFPBP and FPBP allows it to converge to a global optimum solution with more efficiency than the standard BPNN. The results obtained from proposed algorithms are evaluated and compared on three benchmark classification datasets, Thyroid, diabetes, and glass with standard BPNN, ABCNN, and ABC-BP algorithms. The simulation results obtained from the algorithms show that the proposed algorithm performance is better in terms of lowest MSE (0.0005) and high accuracy (99.97%).

Virtual Reality in Medical Education

The aim of this research is to examine student acceptance and use of virtual reality technologies in medical education. Within the scope of the research, a questionnaire consisting of 4 sub-dimensions and 21 items was developed by the researchers. This questionnaire consists of sub-dimensions of performance expectancy, effort expectancy, facilitating conditions, and social influence. The study was conducted on 421 university students who participated in courses and activities related to the use of virtual reality applications in medical education. The findings of the research demonstrated that the students' acceptance and use of virtual reality applications were high in medical education. Various suggestions were made for researchers and educators in accordance with the findings.