Smart handoff technique for internet of vehicles communication using dynamic edge-backup node

© 2020 The Authors. Published by MDPI. This is an open access article available under a Creative Commons licence. The published version can be accessed at the following link on the publisher’s website: https://doi.org/10.3390/electronics9030524A vehicular adhoc network (VANET) recently emerged in the the Internet of Vehicles (IoV); it involves the computational processing of moving vehicles. Nowadays, IoV has turned into an interesting field of research as vehicles can be equipped with processors, sensors, and communication devices. IoV gives rise to handoff, which involves changing the connection points during the online communication session. This presents a major challenge for which many standardized solutions are recommended. Although there are various proposed techniques and methods to support seamless handover procedure in IoV, there are still some open research issues, such as unavoidable packet loss rate and latency. On the other hand, the emerged concept of edge mobile computing has gained crucial attention by researchers that could help in reducing computational complexities and decreasing communication delay. Hence, this paper specifically studies the handoff challenges in cluster based handoff using new concept of dynamic edge-backup node. The outcomes are evaluated and contrasted with the network mobility method, our proposed technique, and other cluster-based technologies. The results show that coherence in communication during the handoff method can be upgraded, enhanced, and improved utilizing the proposed technique.Published onlin

Effect of Ostracism and General Education on Career Development under Mediation of Personality: A Study of Religious Schools in Pakistan

How ostracism affects personality and career development of the students in recognized religious schools (Madrassas) in Pakistan? How general education averts ostracism and improves personality and career development in Madrassas? How all these variables are associated? It was significant finding answers to these questions as yet in literature the mentioned variables are considered separate constructs whereas this study observed them interplaying in 4 recognized Madrassas. The study collected data from a simple random sample of size 280 protégés using reliable and valid instrument. Data analyses were conducted using Pearson’s correlation, regression and mediation test. Ostracism played positive role both on personality and career development while general education was lagging behind against expectation. Study recommended rational improvements, direction for future research expressing its limitations

Assessing Gender Mainstreaming in Developmental Organizations of Abbottabad

The study assesses strategies of various developmental organizations in Abbottabad to incorporate gender in Project management. This is census based research because of various limitations attached with data collection, whole population considered to reduce the chances of maximum error. Data analysis performed by descriptive statistics, correlation and regression. The results show that there are strategies at national level and various international commitments as well. Moreover, a five year project also implemented successfully by UNDP to spread the awareness of gender mainstreaming and to make the organizations to adopt gender mainstreaming in their policies, planning and managements. However, primary data analysis shows that employers are aware of gender mainstreaming and have aptitude about gender mainstreaming, but due to no implementation of designed national level policies, both genders feel lot of problems regarding the fulfillment of their duties. These problems create stress and frustration and deteriorate the effectiveness of employers work that ultimately impact badly on overall efficiency of organizations

An AI-enabled Bias-Free Respiratory Disease Diagnosis Model using Cough Audio: A Case Study for COVID-19

Cough-based diagnosis for Respiratory Diseases (RDs) using Artificial Intelligence (AI) has attracted considerable attention, yet many existing studies overlook confounding variables in their predictive models. These variables can distort the relationship between cough recordings (input data) and RD status (output variable), leading to biased associations and unrealistic model performance. To address this gap, we propose the Bias Free Network (RBFNet), an end to end solution that effectively mitigates the impact of confounders in the training data distribution. RBFNet ensures accurate and unbiased RD diagnosis features, emphasizing its relevance by incorporating a COVID19 dataset in this study. This approach aims to enhance the reliability of AI based RD diagnosis models by navigating the challenges posed by confounding variables. A hybrid of a Convolutional Neural Networks (CNN) and Long-Short Term Memory (LSTM) networks is proposed for the feature encoder module of RBFNet. An additional bias predictor is incorporated in the classification scheme to formulate a conditional Generative Adversarial Network (cGAN) which helps in decorrelating the impact of confounding variables from RD prediction. The merit of RBFNet is demonstrated by comparing classification performance with State of The Art (SoTA) Deep Learning (DL) model (CNN LSTM) after training on different unbalanced COVID-19 data sets, created by using a large scale proprietary cough data set. RBF-Net proved its robustness against extremely biased training scenarios by achieving test set accuracies of 84.1%, 84.6%, and 80.5% for the following confounding variables gender, age, and smoking status, respectively. RBF-Net outperforms the CNN-LSTM model test set accuracies by 5.5%, 7.7%, and 8.2%, respectivelyComment: 13 pages, 7 figures, 5 table

Persimmon (Diospyros kaki) fruit: hidden phytochemicals and health claims

Currently, nutrition and health linkages focused on emerging strategy of diet based regimen to combat various physiological threats including cardiovascular disorders, oxidative stress, diabetes mellitus, etc. In this context, consumption of fruits and vegetables is gaining considerable importance as safeguard to maintain human health. Likewise, their phytochemicals and bioactive molecules are also becoming popular as promising demulcent against various ailments. The current review is an effort to sum up information regarding persimmon fruit with special reference to its phytochemistry and associated health claims. Accordingly, the role of its certain bioactive molecules like proanthocyanidin, carotenoids, tannins, flavonoids, anthocyanidin, catechin, etc. is highlighted. Owing to rich phytochemistry, persimmon and its products are considered effective in mitigating oxidative damage induced by reactive oxygen species (ROS). The antioxidant potential is too responsible for anti-malignant and anti-melanogenic perspectives of persimmon functional ingredients. Additionally, they are effectual in soothing lifestyle related disparities e.g. cardiovascular disorders and diabetes mellitus. There are proven facts that pharmacological application of persimmon or its functional ingredients like proanthocyanidin may helps against hyperlipidemia and hyperglycemia. Nevertheless, astringent taste and diospyrobezoars formation are creating lacuna to prop up its vitality. In toto, persimmon and its components hold potential as one of effective modules in diet based therapy; however, integrated research and meta-analysis are still required to enhance meticulousness