bluuebunny/crossref_metadata_2025 huggingface dataset:
Data mining technique to analyse and predict crime using crime categories and arrest records
Authors: Khatun Most. Rokeya , Ayon Safial Islam , Hossain Md. Rahat , Alam Md. Jaber
Published: June 2021

Generally, crimes influence organisations as it starts occurring frequently in society. Because of having many dimensions of crime data, it is difficult to mine the available information using off the shelf or statistical data analysis tools. Improving this process will aid the police as well as crime protection agencies to solve the crime rate in a faster period. Also, criminals can often be identified based on crime data. Data mining includes strategies at the convergence of machine learning and database frameworks. Using this concept, we can extract previously unknown useful information and their patterns of occurrence from unstructured data. The sole purpose of this paper is to give an idea of how data mining can be utilised by crime investigation agencies to discover relevant precautionary measures from prediction rates. Data sets are analysed by some supervised classification algorithms, namely decision tree, K-nearest neighbours (KNN) and random forest algorithms. Crime forecasting is done for frequently occurring crimes like robbery, assault, theft, etc. Specifically, the results indicate the superiority of the random forest algorithm in test accuracy.
Mobile communication (2G, 3G & 4G) and future interest of 5G in Pakistan: a review
Authors: Iqbal Muhammad Saqib , Abdul Rahim Zulhasni , Hussain Syed Aamer , Ahmad Norulhusna , Mad Kaidi Hazilah , Ahmad Robiah , Dziyauddin Rudzidatul Akmam
Published: June 2021

The use of mobile communication is growing radically with every passing year. The new reality is the fifth generation (5G) of mobile communication technology. 5G requires expensive infrastructural adjustment and upgradation. Currently, Pakistan has one of the most significant numbers of biometrically verified mobile users. However, at the same time, the country lags incredibly in the field of mobile internet adoption, with just half of the mobile device owners avail broadband subscription. It is a viable market with a large segment yet to be tapped. With the advancing progression in Pakistan towards the internet of things (IoT) connectivity, i.e., solar-powered home solutions, smart city projects, and on-board diagnostics (OBD), the urgency for speed, bandwidth and reliability are on the rise. In this paper, Pakistan's prevalent mobile communication networks, i.e., second, third and fourth generation (2G, 3G and 4G), were analyzed and examined in light of the country's demographics and challenges. The future of 5G in Pakistan was also discussed. The study revealed that non-infrastructural barriers influence the low adoption rate, which is the main reason behind the spectrum utilization gap, i.e., the use of 3G, and the 4G spectrum is minimal.
Effect of Covid-19 on the electronic payment system: usage level trust and competence perspectives
Authors: Odeh Mahmoud , Yousef Mohammad
Published: June 2021

Covid-19 has dramatically spread globally and dramatically made several effects in almost all sectors. Electronic commerce and electronic payment systems are important sectors which affected directly by the Covid-19 pandemic. Online markets and electronic payment systems have been recognized as one of the fastest-growing technology in the last decade even within normal situations. However, several factors may influence such growth, which many consider as barriers or enablers of using the electronic payment system. This study aims to shed the light on the influence of Covid-19 on the electronic payment system from trust and competence perspectives. The study employed both qualitative and quantitative methodological approaches for data collection and analysis. The data was collected from 31 semi-structured interviews, 718 surveys, and annual reports. NVivo, Microsoft Visio, and Microsoft power business intelligence were used for the data analysis process. As a part of this study, a proposed framework has been developed which includes both technical and managerial parts.
A comparative analysis on traditional wired datasets and the need for wireless datasets for IoT wireless intrusion detection
Authors: Seong Teh Boon , Ponnusamy Vasaki , Zaman Jhanjhi Noor , Annur Robithoh , Talib M N
Published: June 2021

IoT networks mostly rely on wireless mediums for communication, and due to that, they are very susceptible to intrusions. And due to the tiny nature, processing complexity, and limited storage capacities, IoT networks require very reliable intrusion detection systems (IDS). Although there are many IDS types of research available in the literature, most of these systems are suitable for wired network environments, and the benchmark datasets used for these research works are mostly relying on wired datasets such as KDD Cup’99 and NSL-KDD. IoT and wireless networks are distinct in nature as wireless networks give more emphasis on the data link layer and physical layer. These concerns are not given much attention in traditional wired datasets in the body of knowledge. Therefore, in this research, an IDS system is developed using a newly available IoT wireless dataset (NaBIoT) in the literature with the datasets focusing much on the common IoT related attacks, and related layers are taken into consideration. The IDS system developed is evaluated by comparing with various machine learning algorithms in terms of evaluation metrics such as accuracy, F1 score, false positive, and false negative. Moreover, the IoT wireless dataset is compared against the traditional NSL-KDD datasets to evaluate the need for IoT wireless datasets. The NaBIoT datasets show its effectiveness in detecting wireless intrusions. Besides that, the simulation is performed with different combinations of features to conclude that certain features are primary in detecting attacks, and IDS does not require all the features to perform detection. This can reduce the detection time mainly for machine learning and creating the models. This research results have proposed some of the critically important features to be used and eliminating not such important features.   
Analysis and evaluation of symmetrical key ciphers for internet of things smart home
Authors: S. Abdulla Lujain , K. Mahmood Musaria , F. Salih Abbas , M. Karim Sulaiman
Published: June 2021

A large number of sensors and intelligent devices are interconnected via the internet to collect data as part of the internet of things (IoT) applications. Data security is one of the important challenges for these applications due to vulnerability of the internet. IoT devices limiting factors, such as delay-sensitivity, restricted memory, and low computing capability, make choosing the appropriate data encryption standard extremely important. The current research focuses on evaluating four data security, block cipher standards for the IoT smart home application. Considering the encryption/decryption speed, DES, TDES, AES, and SAFER+ standards are evaluated by implementing the algorithms with MATLAB to determine the best security solution. The simulation of the four standards shows the superiority of SAFER+ standard in term of encryption speed compared to others added to its capabilities on security, and software implementation opportunity. The use of classical symmetric key standards for real time data security in the IoT application can be validated through the selection of SAFER+.
Hybrid bacteria foraging-particle swarm optimization algorithm in DTC performance improving for induction motor drive
Authors: Eddine Rezgui Salah , Benalla Hocine , Bouhebel Houda
Published: June 2021

This paper presents a hybrid algorithm that combines the particle swarm optimization method with the bacteria foraging technique, named: BF-PSO. The aim is to achieve more efficient and precise parameters determination of the regulators that leads to performance improvement in the speed-loop control of an induction motor (IM) implemented in a direct torque control (DTC). The approach consists of tuning the proportional-integral (PI) parameters that meet high dynamics and tracking behavior using the hybrid BF-PSO algorithm. Investigations have been completed with Matlab/Simulink and several performance tests are conducted. The comparison results are exposed with the most used indices in the controllers' tuning with optimization techniques. It will be shown that the presented technique presents better quality results compared to the conventional method of calculated PI.
Classification of Quranic topics based on imbalanced classification
Authors: Arkok Bassam Sulaiman , Zeki Akram Mohammed
Published: June 2021

Imbalanced classification techniques have been applied widely in the field of data mining. It is used to classify the imbalanced classes that are not equal in the number of samples. The problem of imbalanced classes is that the classification performance tends to the class with more samples while the class with few samples will obtain poor performance. This problem can be occurred in the Qur’anic classification due to the different number of verses. Many studies classified Qur’anic verses, which depended on the traditional classification. However, no study classified Qur’anic topics based on the techniques of imbalanced classification. Therefore, this paper aims to apply the methods of imbalanced classification as synthetic minority over-sampling technique (SMOTE), random over sample (ROS), and random under sample (RUS) methods to classify the Qur’anic topics that are imbalanced. Many metrics were used in this research to evaluate the experimental results. These metrics are sensitivity/recall, specificity, overall accuracy, F-Measure, G-mean, and matthews correlation coefficient (MCC). The results showed that the Quranic classification performance improved when imbalanced classification techniques were applied
Self-diagnostic approach for cell counting biosensor
Authors: Al-Gayem Qais , F. Jaafar Hussain , S. Hreshee Saad
Published: June 2021

In this research, a test monitoring strategy for an array of biosensors is proposed. The principle idea of this diagnostic technique is to measure and compare the impedance of each sensor in the array to achieve fully controlled online health monitoring technique at the system level. The work includes implementation of the diagnostic system, system architecture for analogue part, and SNR analysis. The technique has been applied on a cell coulter counting biochip where the design and fabrication of this sensing chip with electrodes make the coulter counter be an effective mean to count and analyses the cells in a blood sample. The experimental results show that the indication factor of the sensing electrodes has increased from 1 to 1.8 gradually depending on the fault level.
Comparative study of off-grid and grid-connected hybrid power system: issues, future prospects and policy framework
Authors: Adebanji Bankole , Atoki Oluwaseun , Fasina Taiwo , Adetan Oluwumi , Abe Adewale
Published: June 2021

A sustainable energy system is of utmost importance for any significant development in any nation.This work identified some obstacles inhibiting rapid renewable energy growth in Nigeria and recommended some policy measures in overcoming them. Moreover, a comparative study of off-grid (OG) and grid-connected (GC) small hydro-solar photovoltaic-diesel hybrid system was carried out using Oyan river, Abeokuta, Nigeria as a case study. The hybrid components were modeled with and without the grid. The hydro solar resources data of the area were collected and analyzed using hybrid optimization model for electric renewable (HOMER) software. The simulation results proved that the GC hybrid power system is better than the OG hybrid power system in technical and economic terms depending on the location. This paper, therefore, proposed the use of OG hybrid power system for electrification of distant villages especially where extending the grid seems infeasible and the use of GC hybrid power system in the urban areas. The work will assist power sector stakeholders in making informed decisions towards the growth of hybrid power system technology in Nigeria.
Comparative study between fast terminal and second order sliding mode controls applied to a wind energy conversion system
Authors: Abdelwahed Touati , Radouane Majdoul , Abderrahim Taouni , Aboulfatah Mohamed , Nabila Rabbah
Published: June 2021

A he wind energy conversion system (WECS) consists of many subsystems, which present control difficulties due to the strong nonlinearities of the models and the effects of internal or external disturbances. In this work, the WECS is based on a doubly feed induction generator (DFIG) directly connected to the stator side network and interconnected via a power converter on the rotor side. The aim of the control strategy is to achieve regular regulation of the powers supplied by the generator and to produce energy of better quality. in order to improve the dynamic behavior of the doubly fed induction generator (DFIG); a comparative study is presented between two advanced control strategies; the second order sliding mode control and the FTSMC fast terminal sliding mode control. The proposed advanced tracking controller is synthesized based on the Lyapunov stability theory and guarantees the existence of the sliding mode around the sliding surface in a finite time. The analysis of the simulation results under the Matlab/Simulink environment confirms the effectiveness of the proposed methods through the performances obtained.
Calcification detection for intravascular ultrasound image using direct acyclic graph architecture: pre-trained model for 1-channel image
Authors: Sofian Hannah , Ming Than Joel Chia , Mohamad Suraya , Mohd Noor Norliza
Published: June 2021

Coronary artery calcification is a calcium buildup within the walls of the arteries. It is considered a predominant marker for coronary artery disease. Thus many approaches have been developed for the automatic detection of calcification. The previous calcification detection was on segmentation of other structures as pre-processing steps or using the fact that the calcification often appears as a bright region. In this paper, an automated system proposed using a deep learning approach to detect the calcification absence and calcification presence in coronary artery IVUS image. A useful advantage of deep learning, compared to other methods is,  it uses representations and features directly from the raw data, bypassing the need to manually extract features, a common that required in the traditional machine learning framework. The type of deep learning architecture used is 27 layers of convolutional neural networks (CNNs) using Direct Acyclic Graph. The proposed system used 2175 images and achieved an accuracy of 98.16% for Cartesian coordinate images and 99.08% for Polar Reconstructed Coordinate images.
Predicting temperature of Erbil City applying deep learning and neural network
Authors: R. K. Al- Jumur Sardar M. , Wahhab Kareem Shahab , Z. Yousif Raghad
Published: June 2021

One of the most significant and daunting activities in today's world is temperature prediction. The meteorologists traditionally predict temperature via some statistical models aimed to forecast the fluctuations that might have happened to atmospheric parameters such as temperature, humidity, etc. The main objective of this paper is to build an intelligent temperature prediction model of Erbil city in KRG/ Iraq based on a historical dataset from 1992 to 2016 in each year there are twelve months’ average temperature readings from (January to December). Hence to resolve this prediction problem an up-to-date deep learning neural network has been used, the network model is based on <span id="docs-internal-guid-850bd062-7fff-c6c8-9146-ba6427eb24e0" style="font-size: 9pt; font-family: 'Times New Roman'; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;">long short-term memory (LSTM) as an artificial recurrent neural network (RNN) architecture which employed to estimate the future average temperature. The implementing model uses the dataset from real-time 30 weather stations deployed in the area of the city. The prediction performance of the proposed recurrent neural network model has been compared with some state of art algorithms like Adeline neural network, Autoregressive neural network (NAR), and <span id="docs-internal-guid-14d37b98-7fff-0f76-848f-ad9f89224f77" style="font-size: 9pt; font-family: 'Times New Roman'; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;"> generalized regression neural network (GRNN). The results show that the proposed model based on deep learning gives minimum prediction error.
Reclassification, Thromboembolic, and Major Bleeding Outcomes Using Different Estimates of Renal Function in Anticoagulated Patients With Atrial Fibrillation: Insights From the PREFER-in-AF and PREFER-in-AF Prolongation Registries
Authors: Rohla Miklos , Pecen Ladislav , Cemin Roberto , Patti Giuseppe , Siller-Matula Jolanta M. , Schnabel Renate B. , Huber Kurt , Kirchhof Paulus , De Caterina Raffaele
Published: June 2021

Background:

The Cockcroft-Gault formula is recommended to determine a renal indication for dose reduction of dabigatran, edoxaban, and rivaroxaban. Nephrology guidelines now recommend the Modification of Diet in Renal Disease (MDRD) and Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) formulae as more accurate estimates of glomerular filtration rate.

Methods:

We analyzed anticoagulated patients with atrial fibrillation who were enrolled in the Prevention of Thromboembolic Events – European Registry in Atrial Fibrillation (PREFER in AF). The proportion of patients with dissimilar renal dosing indications was assessed when applying Cockcroft-Gault, MDRD, or CKD-EPI. Thromboembolic and major bleeding events at 1 year were compared in patients in whom Cockcroft-Gault and CKD-EPI provided concordant or discordant results around a threshold of 50 mL/minute.

Results:

Out of 1288 patients with atrial fibrillation with chronic kidney disease in whom Cockcroft-Gault suggested a dose reduction of dabigatran, edoxaban, or rivaroxaban (creatinine clearance ≤50 mL/minutes), 19% and 16% were reclassified to the respective higher doses, and 24% and 23% to the respective lower doses by applying the MDRD and CKD-EPI formulae, respectively. In patients potentially receiving a different dose of dabigatran, edoxaban, or rivaroxaban when using CKD-EPI, we observed an excess of thromboembolic events (4.1% versus 0.8%; odds ratio, 5.5 [95% CI, 1.5–20.8];
P
=0.01). Major bleeding rates were nonsignificantly different in the discordance versus concordance group (5.7% versus 2.7%; odds ratio, 2.2 [95% CI, 0.9–5.6];
P
=0.09).

Conclusions:

The MDRD and CKD-EPI formulae suggest a different dosing in up to a quarter of anticoagulated patients with atrial fibrillation. This seems to impact hard outcomes.
Toward Dynamic Risk Prediction of Outcomes After Coronary Artery Bypass Graft: Improving Risk Prediction With Intraoperative Events Using Gradient Boosting
Authors: Mori Makoto , Durant Thomas J.S. , Huang Chenxi , Mortazavi Bobak J. , Coppi Andreas , Jean Raymond A. , Geirsson Arnar , Schulz Wade L. , Krumholz Harlan M.
Published: June 2021

Background:

Intraoperative data may improve models predicting postoperative events. We evaluated the effect of incorporating intraoperative variables to the existing preoperative model on the predictive performance of the model for coronary artery bypass graft.

Methods:

We analyzed 378 572 isolated coronary artery bypass graft cases performed across 1083 centers, using the national Society of Thoracic Surgeons Adult Cardiac Surgery Database between 2014 and 2016. Outcomes were operative mortality, 5 postoperative complications, and composite representation of all events. We fitted models by logistic regression or extreme gradient boosting (XGBoost). For each modeling approach, we used preoperative only, intraoperative only, or pre+intraoperative variables. We developed 84 models with unique combinations of the 3 variable sets, 2 variable selection methods, 2 modeling approaches, and 7 outcomes. Each model was tested in 20 iterations of 70:30 stratified random splitting into development/testing samples. Model performances were evaluated on the testing dataset using the C statistic, area under the precision-recall curve, and calibration metrics, including the Brier score.

Results:

The mean patient age was 65.3 years, and 24.7% were women. Operative mortality, excluding intraoperative death, occurred in 1.9%. In all outcomes, models that considered pre+intraoperative variables demonstrated significantly improved Brier score and area under the precision-recall curve compared with models considering pre or intraoperative variables alone. XGBoost without external variable selection had the best C statistics, Brier score, and area under the precision-recall curve values in 4 of the 7 outcomes (mortality, renal failure, prolonged ventilation, and composite) compared with logistic regression models with or without variable selection. Based on the calibration plots, risk restratification for mortality showed that the logistic regression model underestimated the risk in 11 114 patients (9.8%) and overestimated in 12 005 patients (10.6%). In contrast, the XGBoost model underestimated the risk in 7218 patients (6.4%) and overestimated in 0 patients (0%).

Conclusions:

In isolated coronary artery bypass graft, adding intraoperative variables to preoperative variables resulted in improved predictions of all 7 outcomes. Risk models based on XGBoost may provide a better prediction of adverse events to guide clinical care.
Chronic Kidney Disease and Cerebrovascular Disease
Authors: Kelly Dearbhla M. , Ademi Zanfina , Doehner Wolfram , Lip Gregory Y.H. , Mark Patrick , Toyoda Kazunori , Wong Christopher X. , Sarnak Mark , Cheung Michael , Herzog Charles A. , Johansen Kirsten L. , Reinecke Holger , Sood Manish M.
Published: June 2021

The global health burden of chronic kidney disease is rapidly rising, and chronic kidney disease is an important risk factor for cerebrovascular disease. Proposed underlying mechanisms for this relationship include shared traditional risk factors such as hypertension and diabetes, uremia-related nontraditional risk factors, such as oxidative stress and abnormal calcium-phosphorus metabolism, and dialysis-specific factors such as cerebral hypoperfusion and changes in cardiac structure. Chronic kidney disease frequently complicates routine stroke risk prediction, diagnosis, management, and prevention. It is also associated with worse stroke severity, outcomes and a high burden of silent cerebrovascular disease, and vascular cognitive impairment. Here, we present a summary of the epidemiology, pathophysiology, diagnosis, and treatment of cerebrovascular disease in chronic kidney disease from the Kidney Disease: Improving Global Outcomes Controversies Conference on central and peripheral arterial disease with a focus on knowledge gaps, areas of controversy, and priorities for research.
Representing the Cosmos and Transforming the Human: The Onto-hermeneutic Visions of Chung-ying Cheng’s The Primary Way: Philosophy of Yijing
Authors: Ng On-cho
Published: June 2021

The review essay critically evaluates, synoptically presents, and admiringly celebrates Chung-ying Cheng latest work, The Primary Way: Philosophy of Yijing. It sees the book’s publication as an emblem of an intellectual jubilee – a half-centenary of scholarly lucubration and achievement in Chinese and comparative philosophy by Cheng, who was trained at Harvard in American pragmatism and analytic philosophy. The essay reveals why Cheng returns to the Yijing time and again. The principal reason is that this ancient classic, to his way of thinking, offers us “the primary Way,” the anchoring normative criteria, perspectives, and values in a nutshell, whereby reality may be deciphered, discerned, and distinguished. To put it in metaphoric terms, the Yijing is the fount of Chinese philosophy. Whether interpreting Chinese thoughts in general or reading the Yijing in particular, Cheng brings western theoretical perspectives to bear on the understanding of the Chinese texts, which are, in and of themselves, replete with deep philosophical meanings. Cheng appropriates the Yijing for his own primary end, which is to disclose, via his onto-hermeneutic reading, a living, transformative ethico-moral philosophy that is onto-cosmologically alive and onto-generatively fecund: the primary Way. In doing so, he not only offers us innovative scholarship on the ancient classic but also opens up a theoretical and methodological frontier, an onto-hermeneutic one, where Chinese thought and philosophy may be explored anew.
Advancing Economic and Social Rights, Including Education in the Context of European Minorities—2019
Authors: Riekkinen Mariya
Published: June 2021

This article reviews international developments which took place in 2019 with a focus on economic and social rights of members of European minorities, including the right to education. The developments are reviewed based on the practice of the UN, CoE, as well as EU organizations and their bodies whose activities relate to human rights issues. This review also covers the documents of the said bodies adopted in 2018 yet having remained non- promulgated until 2019.

In a nutshell, probably the most significant developments— in terms not only of the greater number of cases resolved but also of new rules proclaimed— occurred within the European Court of Human Rights (ECtHR). In particular, the ECtHR used the notion of ‘institutional racism’ in connection with police violence against Roma individuals in the case Lingurar v. Romania. The Court also articulated an extremely limited ratione materiae right to obtaining psychiatric treatment in a minority language in Rooman v. Belgium. Advancements include developments at unesco which adopted the first- ever international treaty on higher education and continued efforts in approximating diversity in education by elaborating on multi- language education.
Language Rights of European Minorities in the Administration of Justice, Public Administration and Public Services
Authors: Nagy Noémi
Published: June 2021

This article provides an overview of European minorities’ language rights in the administration of justice, public administration, and public services in 2019. Relevant legal developments are presented in the activities of the major international organizations, i.e. the United Nations, the Organization for Security and Cooperation in Europe, the European Union, and the Council of Europe. Since the most relevant treaties on the language rights of minorities in Europe are the European Charter for Regional or Minority Languages and the Framework Convention for the Protection of National Minorities, special attention is paid to the implementation thereof.

Whereas international monitoring mechanisms devoted to the effective protection of minorities are abundant, language rights of national minorities receive less attention, especially in the fields of official language use, that is, in public administration and justice. The regulation of these areas has been traditionally considered as almost exclusively belonging to the states’ competence, and international organizations are consequently reluctant to interfere. As a result, the official use of minority languages differs in the various countries of Europe, with both good practices (e.g. the Netherlands, Spain, Finland) and unbalanced situations (e.g. Estonia, Ukraine, Azerbaijan).
Cultural Activities/Facilities and the Media
Authors: Ragozina Liudmila , Chebotarev Gennady , Titova Elena
Published: June 2021

This article reviews the 2019 international developments related to cultural activities and facilities as well as issues concerning media in the context of European minorities. Among the highlights are the preliminary views delivered by the UN Human Rights Committee concerning the cultural autonomy of the Sami indigenous peoples in Finland in Sanila-Aikio v. Finland and Käkkäläjärvi et al. v. Finland, the 2019 International Year of Indigenous Languages, and the EU Council Recommendation on a comprehensive approach to the teaching and learning of languages. The theme of biand multilingual education is enhanced within UNESCO, the Framework Convention for the Protection of National Minorities, the European Charter for Regional or Minority Languages, and the EU.
Latinizing the Alphabet in Kazakhstan
Authors: Riekkinen Mariya , Zhatkanbayeva Aizhan , Kozhabek Kanat , Aigarinova Gulnar
Published: June 2021

Upon acquisition of independence in 1991, Kazakhstan was the only post- Soviet state where the titular nation did not have an overwhelming majority, the number of Kazakhs being fewer than the number of ethnic Russians. This explains to a certain extent why the Russian language, unlike other minority languages, has, to date, enjoyed a position of lingua franca in Kazakhstan and is used on equal grounds with Kazakh. Our contribution attempts to study the possible impact on the status of the Russian language of a 2017 project known as the ‘trinity of languages’— Kazakh, Russian and English— which includes a reform to Latinize the Kazakh alphabet. It will consider the possible polarization in the society with the younger generation probably choosing English and the older generation preferring the language as they know it.
The Rohingya: Myanmar’s Unwanted Minority
Authors: Sidhu Jatswan S.
Published: June 2021

This article analyses the plight of Myanmar’s unwanted people— the Rohingya. Although they have inhabited the country for centuries, the Rohingya are not listed as one of the 135 legally recognized ethnic groups by the state and are therefore categorized as illegal immigrants. Rendered stateless, subject to decades of oppression and systematic human rights violations by the country’s successive governments, these people have now become, according to the UN, the most persecuted minority in the world. While an estimated 1.5 to 2 million Rohingya once lived in Myanmar, only around one- fifth remain at present. Over the last four decades, almost two thirds of its population have fled the country due to state- sponsored ethnic persecution. This article addresses: the reason for the Rohingya’s statelessness; their disputed origins and the issue of Rohingya identity; the context of the Rohingya crisis; the nature of human rights violations against the community; the situation of the Rohingya in Bangladesh; and, finally, international reaction to the crisis.
Engineering Cell Membrane-Based Nanovesicles for Melanoma Tumor Treatment
Authors: Xin Shengchang , Wu Yingyi , Huang Zhijie , Huang Yisheng , Jia Bo , Zhao Jing
Published: June 2021

Malignant melanoma has a poor prognosis because of its strong ability to invade tissues and metastasize. Immune checkpoint blockades significantly improve the clinical response in the development of melanoma. However, there are some obstacles to overcome, such as cost and limited application.
Therefore, prospective approaches remain to be exploited. We designed cellular nanovesicles (NVs) expressing PD-1 to reactivate T cells by disrupting the PD-1/PD-L1 immunoinhibitory pathway. Furthermore, siNF90 was wrapped into PD-1 NVs to inhibit the proliferation of tumor cells. Such a dual
target effect is helpful for the treatment of melanoma. In addition, our results showed that treatment with PD-1 @siNF90 NVs inhibited the growth of melanoma tumors and extended the survival time of mice, exhibiting a better effect than PD-1 NVs alone. The data also verified that the percentage
of CD8+ T cells in tumors was highest after PD-1 @siNF90 NVs treatment. To sum up, PD-1 @siNF90 NVs could serve as safe and effective blockers in the treatment of melanoma.
Effective Hybrid Technique in Security Based Wireless Sensor Network
Authors: Krishnaraj N. , Vinoth Kumar K. , Jayasankar T. , Eswaramoorthy V.
Published: June 2021

The Wireless Sensor Network (WSN) is a service provider for remote sensing, including wireless transmission and infrastructure, or for the central monitoring of network assets. Over the years, many researchers have tested the WSN for many tests, such as area Monitoring, Environmental
Monitoring, Disaster Management, and Security Monitoring. This does not apply to suggestions for detection and monitoring frameworks. In the present investigation, a strategy is proposed secure directing protocol which offering a versatility. Choice of security, bunch training and high-level
cassette results also compared with the LEACH Protocol Control Protocol as progressive network stability.
Optimized Design of Low Power Complementary Metal Oxide Semiconductor Low Noise Amplifier for Zigbee Application
Authors: Manjula S. , Karthikeyan R. , Karthick S. , Logesh N. , Logeshkumar M.
Published: June 2021

An optimized high gain low power low noise amplifier (LNA) is presented using 90 nm CMOS process at 2.4 GHz frequency for Zigbee applications. For achieving desired design specifications, the LNA is optimized by particle swarm optimization (PSO). The PSO is successfully implemented for optimizing noise figure (NF) when satisfying all the design specifications such as gain, power dissipation, linearity and stability. PSO algorithm is developed in MATLAB to optimize the LNA parameters. The LNA with optimized parameters is simulated using Advanced Design System (ADS) Simulator. The LNA with optimized parameters produces 21.470 dB of voltage gain, 1.031 dB of noise figure at 1.02 mW power consumption with 1.2 V supply voltage. The comparison of designed LNA with and without PSO proves that the optimization improves the LNA results while satisfying all the design constraints.
Efficient Contourlet Transformation Technique for Despeckling of Polarimetric Synthetic Aperture Radar Image
Authors: Rahim Robbi , Murugan S. , Manikandan R. , Kumar Ambeshwar
Published: June 2021

In Polarimetric SAR (PolSAR) and synthetic aperture radar (SAR) requires efficient filtering approach for effective processing of captured quad-polarized images. Due to polarization speckles arises in the captured PolSAR images which causes complexity in collection of data from PolSAR
images. This limitation has been overcome through application of effective despeckling technique for efficient processing of PolSAR images. Several techniques have been evolved over past three decades to reduce those speckle in image captured by PolSAR, and recent research studies illustrated
a efficient trend for filtering local single-point to non-local patch-based or global collaborative filtering. In this paper, applied contourlet technique for effective despeckling of PolSAR images. This contourlet transformation technique perform thresholding and transformation for efficient
despeckling of captured images. Contourlet transformation technique is applied in PolSAR images with speckle and performance metrices are observed. Contourlet technique is comparatively examined with conventional transformation technique which involved in despeckling of images. Analysis of
results exhibited that DWT (Discrete Wavelet Transform) approach exhibits similar performance related to contourlet transformation technique. Through analysis of results it is observed that computation time also significantly reduced in contourlet transformation rather than conventional technique.
Further mean and window sizing also significantly maintained in contourlet technique for various noise variance.
Projection of the Impact of Climate Change on Crude Oil Prices Based on Relevance Vector Machine
Authors: Gabralla Lubna Abdelkareim
Published: June 2021

We propose an alternative algorithm referred to RVM (relevance vector machine) to circumvent the support vector machine’s (SVM) unnecessary use of basic functions, a large number of support vectors, lack of probabilistic prediction, and longer time computation complexity (TCC).
Global annual land-ocean average temperature (GASAT) data and WTI oil market price data extracted from the National Aeronautic and Space Administration US and the US Energy Administration, respectively. The data were preprocessed and used to build RVM models. To evaluate the proposed RVM,
its performance was compared to that of a SVM. The results were validated using ANOVA. A significant correlation between the two datasets was found. The relevance vectors for the RVM were significantly less than the support vectors for the SVM, and the TCC for the RVM was significantly better
than the TCC for the SVM. The prediction accuracy of both the RVM and the SVM were found to be statistically equal. The RVM model was able to project the impact of GASAT on WTI crude oil prices from 2014 to 2023. The projection can be used by intergovernmental organizations to formulate a
global response to combat WTI crude oil price negative impact, which is expected to worsen in the next decade.
The Manitoba Agriculture Mesonet: Technical Overview
Authors: RoTimi Ojo E. , Manaigre Lynn
Published: June 2021

Established primarily to improve weather monitoring across the agricultural regions of the province, the Manitoba Agriculture Weather Program (MAWP) began officially in 2005 with funding from the provincial government for the establishment of a network of 28 automated weather monitoring stations. The network steadily grew to 46 stations between 2007 and 2014 as a result of partnership with local commodity and research groups. In response to the Manitoba flood of 2011, more stations were installed and the network grew to 108 weather stations in 2019. The stations are solar powered, and scheduled maintenance is conducted at each station twice per year. Weather parameters monitored include air temperature, barometric pressure, precipitation, relative humidity, soil moisture, soil temperature, solar radiation, wind speed, and wind direction using research-grade sensors. The observations are transmitted via cellular telemetry every 15 min in the spring, summer, and fall but hourly in the winter to conserve energy supply due to reduced daylight and below-freezing temperatures. The data can be viewed by the public within 1 min of data collection. The data are used to generate agronomic-related maps such as thermal unit computation of growing degree-days and corn heat units as well as disease risk maps such as Fusarium head blight. Beyond agriculture, the data have been used for aviation investigation and for undergraduate course instruction among other applications.
The Climatology and the Midwinter Suppression of the Cold Season North Pacific Storm Track in CMIP6 Models
Authors: Yang Minghao , Li Chongyin , Chen Xiong , Tan Yanke , Li Xin , Zhang Chao , Chen Guiwan
Published: June 2021

The reproducibility of climatology and the midwinter suppression of cold season North Pacific storm track (NPST) in historical runs of 18 CMIP6 models is evaluated against the NCEP reanalysis data. The results show that the position of the climatological peak area of 850 hPa meridional eddy heat flux (v′t′850) is well captured by these models. The spatial patterns of climatological v′t′850 are basically consistent with the NCEP reanalysis. Generally, NorESM2-LM and CESM2-WACCM present a relatively strong capability to reproduce the climatological amplitude of v′t′850 with lower RMSE than the other models. Compared with CMIP5 models, the inter-model spread of v′t′850 climatology among the CMIP6 models is smaller, and their multi-model ensemble is closer to the NCEP reanalysis. The geographical distribution in more than half of the selected models is further south and east. For the subseasonal variability of v′t′850, nearly half of the models exhibit a double-peak structure. In contrast, the apparent midwinter suppression in the NPST represented by the 250 hPa filtered meridional wind variance (v′v′250) is reproduced by all the selected models.

In addition, the present study investigates the possible reasons for simulation biases regarding climatological NPST amplitude. It is found that a higher model horizontal resolution significantly intensifies the climatological v′v′250. There is a significant in-phase relationship between climatological v′t′250 and the intensity of the East Asian winter monsoon (EAWM). However, the climatological v′t′850 is not sensitive to the model grid spacing. Additionally, the climatological low-tropospheric atmospheric baroclinicity is uncorrelated with climatological v′v′250. The stronger climatological baroclinic energy conversion is associated with the stronger climatological v′t′850.
Safety and Efficacy of Prophylactic Enoxaparin Adjusted by Anti-Factor Xa Peak Levels in Pancreatic Surgery
Authors: Kramme Katherine , Sarraf Paya , Shebrain Saad , Munene Gitonga
Published: June 2021

Background

Recommended prophylactic doses of enoxaparin (Lovenox) are associated with subprophylactic anti-Factor Xa (anti-Xa) levels. This study examines the safety and efficacy of anti-Xa-guided dosing of enoxaparin in pancreatic surgery.

Methods

Prospectively enrolled patients undergoing pancreatic surgery received enoxaparin dosing adjusted based on peak anti-Xa levels and were compared to a historical cohort of patients.

Results

Baseline characteristics were similar between the intervention and control groups. In the intervention group, 73.9% initially had subprophylactic peak anti-Xa levels. There were no differences in the venous thromboembolism (VTE) rates between the intervention and control groups (0% vs. 7.69%; P = .084), major bleeding events (4.35% vs. 2.56%; P = .627), RBC transfusion (15.2% vs. 25.6%; P = .257), or Hgb on discharge (9.82 vs. 9.44 g/dL; P = .244). Subtherapeutic anti-Xa levels were correlated with a higher BMI ( P = .033), longer OR time ( P = .011), and length of stay ( P = .018).

Conclusions

Enoxaparin 40 mg once daily is associated with subprophylactic peak anti-Xa levels. Dose adjustment based on anti-Xa levels trended toward a lower rate of in-hospital VTE without an increase in bleeding or transfusion requirement.
High-Resolution Fourier Transform Infrared (FT-IR) Spectroscopic Imaging for Detection of Lung Structures and Cancer-Related Abnormalities in a Murine Model
Authors: Augustyniak Karolina , Chrabaszcz Karolina , Smeda Marta , Stojak Marta , Marzec Katarzyna M. , Malek Kamilla
Published: June 2021

Label-free molecular imaging is a promising utility to study tissues in terms of the identification of their compartments as well as chemical features and alterations induced by disease. The aim of this work was to assess if higher magnification of optics in the Fourier transform infrared (FT-IR) microscope coupled with the focal plane detector resulted in better resolution of lung structures and if the histopathological features correlated with clustering of spectral images. FT-IR spectroscopic imaging was performed on paraffinized lung tissue sections from mice with optics providing a total magnification of 61× and 36×. Then, IR images were subjected to unsupervised cluster analysis and, subsequently, cluster maps were compared with hematoxylin and eosin staining of the same tissue section. Based on these results, we observed minute features such as cellular compartments in single alveoli and bronchiole, blood cells and megakaryocytes in a vessel as well as atelectasis of the lung. In the case of the latter, differences in composition were also noted between the tissue from the non-cancerous and cancerous specimen. This study demonstrated the ability of high-definition FT-IR imaging to evaluate the chemical features of well-resolved lung structures that could complement the histological examination widely used in animal models of disease.
Mitigating the Costs of Spatial Transformations With a Situation Awareness Augmented Reality Display: Assistance for the Joint Terminal Attack Controller 3-17
Authors: Wickens Christopher D. , Mifsud Domenick , Rodriguez Richi , Ortega Francisco R.
Published: June 2021

Objective

Evaluate and model the advantage of a situation awareness (SA) supported by an augmented reality (AR) display for the ground-based joint terminal attack Controller (JTAC), in judging and describing the spatial relations between objects in a hostile zone.

Background

The accurate world-referenced description of relative locations of surface objects, when viewed from an oblique slant angle (aircraft, observation post) is hindered by (1) the compression of the visual scene, amplified at a lower slang angle, (2) the need for mental rotation, when viewed from a non-northerly orientation.

Approach

Participants viewed a virtual reality (VR)-simulated four-object scene from either of two slant angles, at each of four compass orientations, either unaided, or aided by an AR head-mounted display (AR-HMD), depicting the scene from a top-down (avoiding compression) and north-up (avoiding mental rotation) perspective. They described the geographical layout of four objects within the display.

Results

Compared with the control condition, that condition supported by the north-up SA display shortened the description time, particularly on non-northerly orientations (9 s, 30% benefit), and improved the accuracy of description, particularly for the more compressed scene (lower slant angle), as fit by a simple computational model.

Conclusion

The SA display provides large, significant benefits to this critical phase of ground-air communications in managing an attack—as predicted by the task analysis of the JTAC.

Application

Results impact the design of the AR-HMD to support combat ground-air communications and illustrate the magnitude by which basic cognitive principles “scale up” to realistically simulated real-world tasks such as search and rescue.
Policy response for disadvantaged groups during the COVID-19 pandemic: Vietnam experiences
Authors: Hung Nguyen Tuan , Trang Vu Thu , Ly Dang Kim Khanh , Hanh Le Hong , Long Nguyen Xuan , Nam Pham Tien
Published: June 2021

This article aims to describe the Vietnamese Government’s policy response to support disadvantaged groups affected by the COVID-19 pandemic through the relief package. The Vietnamese policy response is characterized by rapid response, priority for disadvantaged groups in communities, social work core values in the policy, openness, and transparency. We hope the experiences from Vietnam could be helpful for similar settings in the world.
Manufacturing of B4C particle reinforced A360 aluminium cellular composite materials by the integration of stir casting and space holder methods
Authors: Sunar Talha , Cetin Melik
Published: June 2021

Stir casting method has become prominent for fabrication of metal matrix composites in recent years. This method can be adjusted for casting around space holding particles to obtain cellular composite materials. In this study, a specific method which is a combination of stir casting and space holder techniques were used to produce open-celled A360 aluminium-B4C composite foams with regular sized and distributed pores. Weight ratios of reinforcement particles determined as 0.5, 1, 1.5 and 2%. The influences of particle reinforcement on the microstructure and the mechanical behaviour of composite foams were investigated. Microstructures were analysed with optical microscope (OM), scanning electron microscope (SEM). Compression and hardness tests were carried out to observe the effects of reinforcement on mechanical properties. Compression strength properties and hardness of composites increased with the ceramic reinforcement, however the plastic strength of the composite foams showed worsening trend after a certain reinforcement ratio (0.5 wt.%). Energy absorption properties of the composite foams showed parallel trends with compressive strength properties.