Sustainable Machining for Titanium Alloy Ti-6Al-4V

Sustainability achievement of difficult-to-machine materials is a major concern nowadays. Titanium alloy Ti-6Al-4V machined for dry, conventional and cryogenic cooling and surface finish is selected as response to assess machining sustainability through variables: cutting power, machining time, machining cost, material removal rate and cutting tool life. Results indicate that cryogenic cooling is more sustainable than dry and conventional cooling

文化遺産をめぐる「保全統治性」 : バングラデシュにおける過去の民主化、保全、表象

広島大学(Hiroshima University)博士(学術)Doctor of Philosophydoctora

A Machine Learning based Framework for KPI Maximization in Emerging Networks using Mobility Parameters

Current LTE network is faced with a plethora of Configuration and Optimization Parameters (COPs), both hard and soft, that are adjusted manually to manage the network and provide better Quality of Experience (QoE). With 5G in view, the number of these COPs are expected to reach 2000 per site, making their manual tuning for finding the optimal combination of these parameters, an impossible fleet. Alongside these thousands of COPs is the anticipated network densification in emerging networks which exacerbates the burden of the network operators in managing and optimizing the network. Hence, we propose a machine learning-based framework combined with a heuristic technique to discover the optimal combination of two pertinent COPs used in mobility, Cell Individual Offset (CIO) and Handover Margin (HOM), that maximizes a specific Key Performance Indicator (KPI) such as mean Signal to Interference and Noise Ratio (SINR) of all the connected users. The first part of the framework leverages the power of machine learning to predict the KPI of interest given several different combinations of CIO and HOM. The resulting predictions are then fed into Genetic Algorithm (GA) which searches for the best combination of the two mentioned parameters that yield the maximum mean SINR for all users. Performance of the framework is also evaluated using several machine learning techniques, with CatBoost algorithm yielding the best prediction performance. Meanwhile, GA is able to reveal the optimal parameter setting combination more efficiently and with three orders of magnitude faster convergence time in comparison to brute force approach

Efficient Detection of Skin Cancer Using Deep Learning Techniques and a Comparative Analysis Study

Many skin lesions may result in the wrong diagnosis of skin cancer, leading to delays and ultimately making the cure impossible. Framed within this statement, this article proposes an efficient skin cancer detection model and compares the six pre-trained models, used for transfer learning in ISIC 2019 dataset. Three most common types of skin cancer—melanoma, nevus, and basal cell carcinoma—are classified by using the transfer learning on the pre-trained models of the ISIC 2019 dataset, to conclude the most accurate detection results with training and test accuracy of 99.73% and 93.79%, respectively

Phage therapy: progress in pharmacokinetics

The concept of phage therapy exists in the history and it has been ignored for a long time, but the consequence of drug resistance in pathogen bacteria has forced the forgotten kingdom of phage therapy to be re-explored. However, for the successful implementation and acceptance of phage therapy worldwide, the number of factors need to be addressed. In pharmacology of phage therapy, pharmacodynamics is a straightforward concept, on the other hand, owing to the unique feature of phages to replicate and their high sensitivity, pharmacokinetics is rather complex. In this review, we have discussed pharmacokinetics and some recent advances in delivery systems as to achieve the therapeutically effective concentrations of phage in their activated form

The Nexus of Ethical Leadership, Job Performance, and Turnover Intention: The Mediating Role of Job Satisfaction

This study aims to examine the impact of ethical leadership on employees’ job satisfaction, performance, and turnover intention. A conceptual framework is developed which clearly integrates job satisfaction as a mediating mechanism in explaining the nexus among ethical leadership, job performance, and turnover intention. This framework is then analysed employing data from a sample (n = 114) of tourist companies in Lahore, Pakistan. The results reveal that ethical leadership has positive effect on employees’ job satisfaction, performance and has negative effect on their turnover intentions. Further, job satisfaction positively mediates the effect of ethical leadership on employees’ job performance and turnover intentions. The findings recommend that the demonstration of ethical leadership behaviours by managers at workplace enhances employees’ job satisfaction and performance, and decreases the intention of employees to leave the job. The main narrative of this study encompasses the imperative role of ethical leadership in the workplace where it serves as a factor that enhances employees’ job satisfaction, performance, and decreases turnover intention. This research explicitly demonstrates that in Pakistani tourism sector, ethical leadership plays a vital role to achieve performance goals. Future research could analyse the said nexus in different sectors and cultures, and may also consider other measures of individual performance. The consideration of job satisfaction as mediating variable in probing the linkages among ethical leadership, job performance, and turnover intention in the context of the workplace in Pakistan and the analysing of this linkage is novel

GPS based Bluetooth Broadcasting – Long Range Solution

In this paper, GPS based Bluetooth broadcasting for long range is proposed. System model for Long range broadcasting of messages with multiple piconets and dynamically created threshold devices, based on GPS information is presented. Our simulation results have shown that, message can be received by those devices which are out of the initial Bluetooth range in reasonable time. Flooding of multiple messages could be avoided by applying hash function. With this solution, long range data and voice communication could be done with free of cost also can be used for commercial advertising purpose

Neuromorphic AI Empowered Root Cause Analysis of Faults in Emerging Networks

Mobile cellular network operators spend nearly a quarter of their revenue on network maintenance and management. A significant portion of that budget is spent on resolving faults diagnosed in the system that disrupt or degrade cellular services. Historically, the operations to detect, diagnose and resolve issues were carried out by human experts. However, with diversifying cell types, increased complexity and growing cell density, this methodology is becoming less viable, both technically and financially. To cope with this problem, in recent years, research on self-healing solutions has gained significant momentum. One of the most desirable features of the self-healing paradigm is automated fault diagnosis. While several fault detection and diagnosis machine learning models have been proposed recently, these schemes have one common tenancy of relying on human expert contribution for fault diagnosis and prediction in one way or another. In this paper, we propose an AI-based fault diagnosis solution that offers a key step towards a completely automated self-healing system without requiring human expert input. The proposed solution leverages Random Forests classifier, Convolutional Neural Network and neuromorphic based deep learning model which uses RSRP map images of faults generated. We compare the performance of the proposed solution against state-of-the-art solution in literature that mostly use Naive Bayes models, while considering seven different fault types. Results show that neuromorphic computing model achieves high classification accuracy as compared to the other models even with relatively small training dat

Airway Clearance in Bronchiectasis: A Randomized Control Trial of N-Acetylcysteine with 3% hypertonic saline

Background: N-Acetylcysteine and 3% hypertonic saline are being used effectively for sputum clearance in chronic cases of bronchiectasis for quite some time. However, their use in acute condition of the disease seems to be underexplored. The objective of our study is to compare the role of nebulized N-acetylcysteine and 3% hypertonic saline in clearing the airway in patients with acute exacerbation of bronchiectasis. Material and Methods: A total of 136 confirmed cases of bronchiectasis were enrolled in this study. This randomized controlled trial was done in chest ward of Nishtar Hospital Multan from January 2015 to March 2017. Sampling was done by non-probability consecutive sampling and patients were divided into two groups A and B by lottery method. Verbal informed consent was taken from all participants. Group A participants received nebulization of N acetylcysteine mixed in normal saline for ten minutes, while group B participants were nebulized with 10ml of 3% hypertonic saline for ten minutes. Group B was active control group in the study. Data was collected on pre-designed Proforma, and analyzed by SPSS version 22. Numerical variables such as saturation, weight of sputum, age and blood pressure was analyzed by using t test. These were considered significant if the p value was equal or less than 0 .05. For qualitative variables chi square test was applied. Results: The mean O2 saturation of Group A, before and after treatment, was 92.11±3.07% and 94.47±2.18%, respectively. The difference was statistically significant (p value =0.001). The sputum weight of Group A, before and after treatment, was 2.63±2.39 g and 7.41±1.38 g, respectively. The difference was statistically significant (p value =0.001). The frequency of rhonchi of Group A, before and after treatment, was 52% and 76%, respectively. The difference was statistically significant (p value =0.003). While, for Group B, the mean O2 saturation, before and after treatment, was 92.36±3.13% and 93.49±2.27%, respectively. The difference was statistically significant (p value =0.012). The sputum weight, before and after treatment, was 3.11±2.01 g and 5.56±1.02 g, respectively. The frequency of rhonchi, before and after treatment, was 45% and 74% respectively. Again, the difference was statistically significant. Conclusion: Both nebulized N-acetylcysteine and 3% hypertonic saline cause airway clearance by enhancing sputum expectoration in patients with acute exacerbation of bronchiectasis equally. Both these agents also improve oxygen saturation in acute exacerbation of bronchiectasis significantly