bluuebunny/crossref_metadata_2025 huggingface dataset:
Elliptic flow of hadrons in equal-velocity quark combination mechanism in relativistic heavy-ion collisions
Authors: Song Jun , Li Hai-hong , Shao Feng-lan
Published: January 2021

We apply a quark combination model with equal-velocity combination (EVC) approximation to study the elliptic flow ($$v_{2}$$

v
2

) of hadrons in heavy-ion collisions in a wide collision energy range ($$\sqrt{s_{NN}}=$$

s

NN

=

27–5020 GeV). Utilizing the simple relationship between $$v_{2}$$

v
2

of hadrons and those of quarks under EVC, we find that $$v_{2}$$

v
2

of up/down quarks obtained by experimental data of proton is consistent with that obtained by data of $$\varLambda $$
Λ
and $$\varXi $$
Ξ
. $$v_{2}$$

v
2

of strange quarks obtained by data of $$\varOmega $$
Ω
is consistent with that obtained by data of $$\varLambda $$
Λ
and $$\varXi $$
Ξ
, and at RHIC energies it is also consistent with that obtained by data of $$\phi $$
ϕ
. This means that $$v_{2}$$

v
2

of these hadrons have a common quark-level source. Using data of $$D^0$$

D
0

, we obtain $$v_{2}$$

v
2

of charm quarks with $$p_T\lesssim 6$$

p
T

≲
6

GeV/c. We find that under EVC charm quark dominates $$v_{2}$$

v
2

of D mesons at low $$p_{T}$$

p
T

but light-flavor quarks significantly contribute to $$v_{2}$$

v
2

of D mesons in the range $$3\lesssim p_{T}\lesssim 8$$

3
≲

p
T

≲
8

GeV/c. We predict $$v_{2}$$

v
2

of charmed baryons $$\varLambda _{c}^{+}$$

Λ

c

+

and $$\varXi _{c}^{0}$$

Ξ

c

0

which show a significant enhancement at intermediate $$p_{T}$$

p
T

due to the double contribution of light-flavor quarks. The properties of the obtained quark $$v_{2}$$

v
2

under EVC are studied and a regularity for $$v_{2}$$

v
2

of quarks as the function of $$p_{T}/m$$

p
T

/
m

is found.
A new equation for period vectors of crystals under external stress and temperature in statistical physics: mechanical equilibrium condition and equation of state
Authors: Liu Gang
Published: January 2021

Starting with the rigorous derivation of the work done on the center cell by external forces, a new equation is derived for the period vectors (cell edge vectors) in crystals under external stress and temperature. Since the equation is based on the principles of statistical physics, it applies to both classical and quantum systems. The existing theory for crystals under external pressure is covered as a special case. The new equation turns out to be the mechanical equilibrium condition and the equation of state for crystals under external stress and temperature. It may be used to predict crystal structures and to study structural phase transitions and crystal expansions. For linear elastic crystals, it takes the microscopic and temperature-dependent form of the generalized Hooke’s law, and may therefore be used to calculate the corresponding elastic constants. It should be helpful in studying piezoelectric and piezomagnetic materials, as the period vectors change with external stress. It is also consistent and can be combined with the previously derived corresponding one for Newtonian dynamics.
A Novel Machine Learning Model to Predict the Staying Time of International Migrants
Authors: Shukla Prashant Kumar , Shukla Piyush Kumar , Bhatele Mukta , Chaturvedi Anoop Kumar , Sharma Poonam , Rizvi Murtaza Abbas , Pathak Yadunath
Published: January 2021

In this paper, a novel machine learning model is proposed to predict the staying time of international migrants. The competitive machine learning approaches which can be used to predict the staying time of international migrants suffer from hyper-attributes tuning and over-fitting issues. Therefore, a particle swarm optimization (PSO) based support vector machine (SVM) model is proposed to predict the staying time of international migrants. Extensive experiments are performed by considering the international migrants dataset to predict the staying time of international migrants. Experimental results illustrate that the proposed approach outperforms the existing machine learning approaches in terms of f-measure, accuracy, specificity, and sensitivity.
Lung CT Image Segmentation Using Reinforcement Learning
Authors: Gheysari Parnia , Fateh Mansoor , Rezvani Mohsen
Published: January 2021

Nowadays, lung disease is a major global problem in the world. Many of the lung diseases are untreatable and reduce the life span of the individual. Initial diagnosis of these diseases can help to completely cure the illness and reduce disease progression. Diagnosis of lung disease is often made based on CT scan images of the lungs. But the diagnosis of lung disease in CT images is a complicated and challenging task. Such a challenge is due to the noise of imaging, the lack of transparency of the image, the intensity of the lighting of some components, and so on. Eliminating these issues makes it easy to diagnose the disease for specialized physicians as well as existing automated diagnostic systems. In this paper, we propose a novel approach for lung CT image segmentation that solves some of these challenges. Also, correct accurate segmentation of these images can help to automatically detect lung diseases. The correct segmentation means a precise determination of the intensity of each area’s brightness, the exact location of the pixels in each area and the preservation of the original image. We employed a reinforcement-based approach for our image segmentation. The proposed method produces the image without noise, and the image components are split with the best accuracy. To evaluate our approach, we manually generated 200 labelled lung CT images. After that, the proposed method, along with two recently published approaches is evaluated against our generated dataset. This comparative evaluation is conducted in two qualitative and quantitative ways. For the qualitative comparison, we employed the consultation of two ultrasound radiologists for evaluating the results of our approach. We also used a similarity measurement to quantitatively evaluate the performance of our proposed segmentation method. In both evaluation approaches, the proposed algorithm provides better performance compared to the other methods. The proposed method provides an accuracy of more than 90% for lung image segmentation, which shows around 5% increase in the accuracy comparing to the state of the art. The high accuracy of this method is due to its fitness to the application.
Dynamic Behavior Predictions for Fast and Efficient Hybrid STT-MRAM Caches
Authors: Sayed Nour , Mao Longfei , Tahoori Mehdi B.
Published: January 2021

Spin Transfer Torque Magnetic Random Access Memory
(STT-MRAM) is a promising candidate as a universal on-chip memory technology due to its non-volatility, high density, and scalability. However, high write energy and latency are its major shortcomings, particularly for fast cache applications. High write costs can efficiently be reduced by relaxing the STT-MRAM non-volatility requirements at the expense of significant increase in retention failure and read disturb rates resulting in data corruption. Hybrid STT-MRAM architecture combining non-volatile (NVM) and semi-volatile (SVM) STT-MRAM blocks has been proposed recently, which provides energy-efficiency, high storage capacity, better performance, and high reliability. However, a key and challenging requirement is efficient data mapping and migration between NVM and SVM sub-arrays to maximize the benefits of such hybrid caches. On-the-fly data migration decisions usually depend on the last seen data behavior, as it is assumed to be identical to the next one, which has very limited accuracy for rapidly varying workload behavior. In this article, we propose a simple but effective on-the-fly data management policy, which mainly relies on the supervised learning data-pattern classification for quick and highly accurate prediction of the data behavior in the oncoming execution time. Three prediction approaches are proposed and compared for a maximum and average achieved accuracy of 86% and 75%, respectively. Our data management policies aim to optimally leverage the specific features of NVM (high reliability) and SVM blocks (fast and energy-efficient write) of hybrid STT-MRAM memory with minimal migration costs (i.e., energy and performance overheads). Our experimental evaluation reports that for a hybrid STT-MRAM cache with the proposed prediction techniques, the total energy consumption can be reduced around 10.5%, on average, in comparison to the state-of-the-art.
Machine Learning for Identifying Group Trajectory Outliers
Authors: Belhadi Asma , Djenouri Youcef , Djenouri Djamel , Michalak Tomasz , Lin Jerry Chun-Wei
Published: January 2021

Prior works on the trajectory outlier detection problem solely consider
individual
outliers. However, in real-world scenarios, trajectory outliers can often appear in groups, e.g., a group of bikes that deviates to the usual trajectory due to the maintenance of streets in the context of intelligent transportation. The current paper considers the
Group Trajectory Outlier
(GTO) problem and proposes three algorithms. The first and the second algorithms are extensions of the well-known DBSCAN and
k
NN algorithms, while the third one models the GTO problem as a feature selection problem. Furthermore, two different enhancements for the proposed algorithms are proposed. The first one is based on ensemble learning and computational intelligence, which allows for merging algorithms’ outputs to possibly improve the final result. The second is a general high-performance computing framework that deals with big trajectory databases, which we used for a GPU-based implementation. Experimental results on different real trajectory databases show the scalability of the proposed approaches.
EPTAS and Subexponential Algorithm for Maximum Clique on Disk and Unit Ball Graphs
Authors: Bonamy Marthe , Bonnet Édouard , Bousquet Nicolas , Charbit Pierre , Giannopoulos Panos , Kim Eun Jung , Rzążewski Paweł , Sikora Florian , Thomassé Stéphan
Published: January 2021

A (unit) disk graph is the intersection graph of closed (unit) disks in the plane. Almost three decades ago, an elegant polynomial-time algorithm was found for M
AXIMUM
C
LIQUE
on unit disk graphs [Clark, Colbourn, Johnson;
Discrete Mathematics
’90]. Since then, it has been an intriguing open question whether or not tractability can be extended to general disk graphs. We show that the disjoint union of two odd cycles is never the complement of a disk graph nor of a unit (3-dimensional) ball graph. From that fact and existing results, we derive a simple QPTAS and a subexponential algorithm running in time 2

Õ(
n
2/3
)

for M
AXIMUM
C
LIQUE
on disk and unit ball graphs. We then obtain a randomized EPTAS for computing the independence number on graphs having no disjoint union of two odd cycles as an induced subgraph, bounded VC-dimension, and linear independence number. This, in combination with our structural results, yields a randomized EPTAS for M
AX
C
LIQUE
on disk and unit ball graphs. M
AX
C
LIQUE
on unit ball graphs is equivalent to finding, given a collection of points in R
3
, a maximum subset of points with diameter at most some fixed value.

In stark contrast, M
AXIMUM
C
LIQUE
on ball graphs and unit 4-dimensional ball graphs, as well as intersection graphs of filled ellipses (even close to unit disks) or filled triangles is unlikely to have such algorithms. Indeed, we show that, for all those problems, there is a constant ratio of approximation that cannot be attained even in time 2

n

1−ɛ
, unless the Exponential Time Hypothesis fails.
MaxSense
Authors: Lyu Yangdi , Mishra Prabhat
Published: January 2021

Detection of hardware Trojans is vital to ensure the security and trustworthiness of System-on-Chip (SoC) designs. Side-channel analysis is effective for Trojan detection by analyzing various side-channel signatures such as power, current, and delay. In this article, we propose an efficient test generation technique to facilitate side-channel analysis utilizing dynamic current. While early work on current-aware test generation has proposed several promising ideas, there are two major challenges in applying it on large designs: (i) The test generation time grows exponentially with the design complexity, and (ii) it is infeasible to detect Trojans, since the side-channel sensitivity is marginal compared to the noise and process variations. Our proposed work addresses both challenges by effectively exploiting the affinity between the inputs and rare (suspicious) nodes. The basic idea is to quickly find the profitable ordered pairs of test vectors that can maximize side-channel sensitivity. This article makes two important contributions: (i) It proposed an efficient test generation algorithm that can produce the first patterns in the test vectors to maximize activation of suspicious nodes using an SMT solver, and (ii) it developed a genetic-algorithm based test generation technique to produce the second patterns in the test vectors to maximize the switching in the suspicious regions while minimizing the switching in the rest of the design. Our experimental results demonstrate that we can drastically improve both the side-channel sensitivity (62× on average) and time complexity (13× on average) compared to the state-of-the-art test generation techniques.
Survivin Regulates Bad Gene Expression by Binding to Its Promoter and Modulates Cell Cycle and Apoptosis in Esophageal Carcinoma Cell
Authors: Chen Yan , Bieerkehazhi Shayahati , Li Xiumei , Ma Lili , Yibulayin Waresijiang , Ran Jihua
Published: January 2021

Esophageal cancer (EC) is the eighth most prevalent cancer and the sixth leading cause of cancer-related mortality worldwide. As an antiapoptotic and a proapoptotic protein, respectively, survivin and Bad play an important role in carcinogenesis of the most human cancers including EC. However, the regulatory relationships between them remain unclear. We sought to investigate the effects of survivin knockdown and overexpression on the expression of Bad gene, cell cycle progression, and apoptosis of esophageal carcinoma cell. The mRNA expression levels of survivin and Bad were determined in EC tissue samples. The knockdown and overexpression experiments were performed in ECA109 and KYSE450 cells via transfection with survivin overexpression and shRNA plasmids. A Bad overexpression experiment was conducted to confirm the biological effect on knockdown of survivin via modulating Bad expression. RT-qPCR and Western blot analysis were used to detect mRNA and protein expression, respectively. Cell cycle and apoptosis were analyzed by flow cytometry. The chromatin immunoprecipitation (ChIP) was conducted to determine the binding sites of survivin on the promoter of Bad gene. By analyzing the mRNA expression of survivin and Bad in 40 ESCC patient specimens, we found that the positive expression rate of survivin in tumor tissues (88%, 35/40) was remarkably high, compared with the distal nontumor tissues (48%, 19/40,

p

 < 0.01). On the other hand, the positive expression rate of Bad in tumor tissues (70%, 28/40) was remarkably low, compared with the distal nontumor tissues (95%, 38/40,

p

 < 0.01). Overexpression of survivin decreases Bad mRNA and protein expression and promotes transformation of cell cycle to S phase. Conversely, knockdown of survivin increases Bad mRNA and protein expression and induces cell cycle arrest and apoptosis. Bad overexpression inducing apoptosis of esophageal carcinoma cell shows the similar apoptotic effect with survivin knockdown. ChIP assays indicate that survivin directly binds to the Bad promoter region, diminishing the transcriptional activity of Bad. In conclusion, the result suggested that survivin regulates Bad gene expression by binding to its promoter and modulates cell cycle and apoptosis in esophageal carcinoma cell.
The Effect of Multiwalled Carbon Nanotubes on the Thermal Conductivity and Cellular Size of Polyurethane Foam
Authors: Duc Huynh Mai , Huu Dat Nguyen , Huu Trung Tran , Trong Lu Le , Nhu Hai Luong , Ngoc Hong Phan , Van Thao Nguyen , Kieu Thi Quynh Hoa , Vu Giang Nguyen
Published: January 2021

Polyurethane (PU) foam is known as the popular material for the applications in many fields of industry and life. To improve the mechanical and thermal properties of this material, in this research, PU foam was reinforced with aniline-modified multiwalled carbon nanotubes (MWCNTs). Fourier transform infrared FTIR spectrum of modified MWCNTs showed the aniline was grafted on the surface of MWCNTs through the appearance of –NH2 stretches. The effect of MWCNTs with and without modification on the density, porosity, compressive strength, and heat conductivity of PU/MWCNT foam nanocomposites was investigated. The dispersibility of MWCNTs in the PU matrix was enhanced after modification with aniline. Compressive strength of PU nanocomposite reached the highest value after adding 3 wt.% of modified MWCNTs into PU foam. Besides, the water uptake of PU nanocomposites using 3 wt.% of MWCNTs was decreased to 13.4% as compared to that using unmodified MWCNTs. The improvement in thermal conductivity of PU/aniline-modified MWCNT nanocomposite was observed due to the change in the cellular size of PU foam in the presence of MWCNTs as shown by SEM images.
A Rare Case of Parotid Gland Tuberculosis
Authors: Singh Deepshikha , Mishra Sudhir
Published: January 2021

Parotid gland tuberculosis is a very rare form of extrapulmonary tuberculosis, with less than 200 cases reported in literature. We describe a 10-year-old female who presented with a swelling in the left parotid region during the last month. CT scan neck revealed an abscess in the left parotid gland extending into the submandibular gland, muscles, and bone. Pus aspirated by FNAC showed acid fast bacilli in the ZN stain, and GeneXpert was positive for rifampicin-sensitive Mycobacterium tuberculosis. She was successfully treated with antituberculous therapy given for 6 months. Parotid gland tuberculosis, although rare, has a good prognosis with drug therapy. Surgery is rarely required.
The Optimal PPP Model of Emergency Rescue Service
Authors: Cao Guangxi , Zhou Ling
Published: January 2021

Based on the analysis of the shortage of emergency rescue services and the supervision of public-private-partnership (PPP) projects, this paper explores the rent-seeking game predicament and establishes a three-player rent-seeking game model among government regulators, private enterprises, and government agents in the bidding operation of PPP projects by learning from Stackelberg game theory. Through the numerical simulation analysis, this paper explores the impact of the relevant variables on the model results, which can lead to the following conclusions: the emphasis on government regulators changes due to rent-seeking cost changes; when the success rate of verification is high, government regulators can take supervision randomly. Inversely, supervision channels should be broadened when the supervision fails. When the punishment on government agents and private enterprises is great, relaxing supervision may be appropriate. This study proposes the relevant policy recommendations for government regulators to improve their work.
St. Jude Cloud: A Pediatric Cancer Genomic Data-Sharing Ecosystem
Authors: McLeod Clay , Gout Alexander M. , Zhou Xin , Thrasher Andrew , Rahbarinia Delaram , Brady Samuel W. , Macias Michael , Birch Kirby , Finkelstein David , Sunny Jobin , Mudunuri Rahul , Orr Brent A. , Treadway Madison , Davidson Bob , Ard Tracy K. , Chiao Arthur , Swistak Andrew , Wiggins Stephanie , Foy Scott , Wang Jian , Sioson Edgar , Wang Shuoguo , Michael J. Robert , Liu Yu , Ma Xiaotu , Patel Aman , Edmonson Michael N. , Wilkinson Mark R. , Frantz Andrew M. , Chang Ti-Cheng , Tian Liqing , Lei Shaohua , Islam S.M. Ashiqul , Meyer Christopher , Thangaraj Naina , Tater Pamella , Kandali Vijay , Ma Singer , Nguyen Tuan , Serang Omar , McGuire Irina , Robison Nedra , Gentry Darrell , Tang Xing , Palmer Lance E. , Wu Gang , Suh Ed , Tanner Leigh , McMurry James , Lear Matthew , Pappo Alberto S. , Wang Zhaoming , Wilson Carmen L. , Cheng Yong , Meshinchi Soheil , Alexandrov Ludmil B. , Weiss Mitchell J. , Armstrong Gregory T. , Robison Leslie L. , Yasui Yutaka , Nichols Kim E. , Ellison David W. , Bangur Chaitanya , Mullighan Charles G. , Baker Suzanne J. , Dyer Michael A. , Miller Geralyn , Newman Scott , Rusch Michael , Daly Richard , Perry Keith , Downing James R. , Zhang Jinghui
Published: January 2021

Effective data sharing is key to accelerating research to improve diagnostic precision, treatment efficacy, and long-term survival in pediatric cancer and other childhood catastrophic diseases. We present St. Jude Cloud (https://www.stjude.cloud), a cloud-based data-sharing ecosystem for accessing, analyzing, and visualizing genomic data from >10,000 pediatric patients with cancer and long-term survivors, and >800 pediatric sickle cell patients. Harmonized genomic data totaling 1.25 petabytes are freely available, including 12,104 whole genomes, 7,697 whole exomes, and 2,202 transcriptomes. The resource is expanding rapidly, with regular data uploads from St. Jude's prospective clinical genomics programs. Three interconnected apps within the ecosystem—Genomics Platform, Pediatric Cancer Knowledgebase, and Visualization Community—enable simultaneously performing advanced data analysis in the cloud and enhancing the Pediatric Cancer knowledgebase. We demonstrate the value of the ecosystem through use cases that classify 135 pediatric cancer subtypes by gene expression profiling and map mutational signatures across 35 pediatric cancer subtypes.

Significance:

To advance research and treatment of pediatric cancer, we developed St. Jude Cloud, a data-sharing ecosystem for accessing >1.2 petabytes of raw genomic data from >10,000 pediatric patients and survivors, innovative analysis workflows, integrative multiomics visualizations, and a knowledgebase of published data contributed by the global pediatric cancer community.

This article is highlighted in the In This Issue feature, p. 995
Conditional Cancer Immunotherapy as a Safer Way to Step on the Gas
Authors: Keenan Bridget P. , Fong Lawrence
Published: January 2021

In this issue, Kamata-Sakurai and colleagues describe an agonist antibody to CD137 (4-1BB) that takes on an active conformation in environments with high ATP concentrations, characteristic of tumors. This represents a novel advancement in developing immunotherapies that can be administered systemically, but act locally to induce antitumor immune responses without the usual attendant toxicities.

See related article by Kamata-Sakurai et al., p. 158.
Suppressing Nucleotide Exchange to Inhibit KRAS-Mutant Tumors
Authors: Zhao Yulei , Xue Jenny Y. , Lito Piro
Published: January 2021

Guanine nucleotide exchange factors (GEF) control the rate-limiting step of physiologic RAS activation. In this issue of Cancer Discovery, Hofmann and colleagues describe the discovery of a selective inhibitor targeting the GEF, SOS1, along with its preclinical effects in suppressing KRAS-mutant tumor growth.

See related article by Hofmann et al., p. 142.
Increased Severe Adverse Outcomes and Decreased Emergency Room Visits for Pyelonephritis: First Report of Collateral Damage during COVID-19 Pandemic in Urology
Authors: Borgmann Hendrik , Struck Julian P. , Mattigk Angelika , Wenzel Mike , Pilatz Adrian , Kranz Jennifer , Weiten Richard , von Landenberg Nicolas , Spachmann Philipp Julian , Aksoy Cem , Haferkamp Axel , Boehm Katharina
Published: January 2021

Purpose: The coronavirus disease 2019 (COVID-19) pandemic is disrupting urology health-care worldwide. Reduced emergency room visits resulting in adverse outcomes have most recently been reported in pediatrics and cardiology. We aimed to compare patients with emergency room visits for pyelonephritis in 2019 (pre-COVID-19 era) and within the first wave of pandemic in 2020 (COVID-19 era) with regard to the number of visits and severe adverse disease outcomes. Methods: We performed a retrospective multicentre study comparing characteristics and outcomes of patients with pyelonephritis, excluding patients with hydronephrosis due to stone disease, in 10 urology departments in Germany during a 1-month time frame in March and April in each 2019 and 2020. Results: The number of emergency room visits for pyelonephritis in the COVID-19 era was lower (44 patients, 37.0%) than in the pre-COVID-19 era (76 patients, 63.0%), reduction rate: 42.1% (p = 0.003). Severe adverse disease outcome was more frequent in the COVID-19 era (9/44 patients, 20.5%) than in the pre-COVID-19 era (5/76 patients, 6.6%, p = 0.046). In detail, 7 versus 3 patients needed monitoring (15.9 vs. 3.9%), 2 versus no patients needed intensive-care treatment (4.5 vs. 0%), 2 versus no patients needed drain placement (4.5 vs. 0%), 2 versus no patients had a nephrectomy (4.5 vs. 0%), and 2 versus 1 patient died (4.5 vs. 1.3%). Conclusion: This report of collateral damage during CO­VID-19 showed that emergency room visits were decreased, and severe adverse disease outcomes were increased for patients with pyelonephritis in the COVID-19 era. Health authorities should set up information campaign programs actively encouraging patients to utilize emergency room services in case of severe symptoms specifically during the actual second wave of pandemic.
An image enhancement method based on gabor filtering in wavelet domain and adaptive histogram equalization
Authors: K M Jeevan , A B Anne Gowda , Kumar Padmaja Vijay
Published: January 2021

The images are not always good enough to convey the proper information. The image may be very bright or very dark sometime or it may be low contrast or high contrast. Because of these reasons image enhancement plays important role in digital image processing. In this paper we proposed an image enhancement technique in which Gabor and median filtering is performed in wavelet domain and Adaptive Histogram Equalization is performed in spatial domain. Brightness and contrast are the two parameters used for analyzing the performance of the proposed method
Effects of intensity of magnetic field generated by neodymium permanent magnet sheets on electrical characteristics of monocrystalline silicon solar cell
Authors: Panmuang Piyapat , Photong C.
Published: January 2021

In this research, the effects of magnetic field intensity on electrical characteristics of a monocrystalline silicon solar cell were investigated. The experimental test-rig under Standard Test Condition was set up and tested to observe the respective effects. The electrical characteristics in terms of current-voltage-power curves, critical solar cell parameters and fill factor were then examined and analyzed. The outcome of this study demonstrates that the external magnetic field has a positive impact on electrical parameters, the experimental results showed that applying magnetic intensity of 60-260mT significantly affected the electrical characteristics of the cell; i.e., maximized cell current, voltage and power by 12.20, 7.12 and 23.60%, respectively. In addition, this positive impact consequencely happened on the i-v and p-v electrical characteristics curves of the solar cell; reflected by 3.69% increasing in the fill factor. 
Validation of android-based mobile application for retrieving network signal level
Authors: A. Adeniji Kehinde , Surajudeen-Bakinde Nazmat T. , O. Omitola Olusegun , Ajibade Adedayo
Published: January 2021

In recent years, the evolvement of mobile devices which perform sophisticated functions have been on the rise. Mobile applications which solved engineering challenges are now available due to the high computational capabilities, large random access memory and storage location of the mobile devices. An Android application called signal detect, which measures network signal strength value from 2G-4G received on an android mobile device has been developed using android app development environment called Android studio. Validation becomes necessary because different readings were obtained on smartphones with different specifications. Two validation techniques were used to validate the data obtained. To know the efficiency of the application; a field strength meter was used to compare the readings received on the mobile device with the meter. It was observed that there is a time lag on the received values of the mobile device to the field strength meter. Therefore, a moving average technique was used to correlate the two data which increased the correlation coefficient to about 0.85.
The necessity of a lead person to monitor development stages of the DevOps pipeline
Authors: Alnamlah Betool , Alshathry Sara , Alkassim Norah , Mohd Jamail Nor Shahida
Published: January 2021

The Development-to-Operations model, known as DevOps, refers to a framework that integrates the development and operation phases of organizational applications. DevOps bridges the gap between these two processes that traditionally prolonged the implementation of these applications. This framework aims at enhancing service delivery and releasing subsequent updates based on real-time customer feedback. Consumers in this modern era prefer tailor-made services, and a slight downtime from one supplier can quickly shift their preference to the company’s competitors. However, DevOps involves sophisticated coding activities, and there is a need for someone to oversee these processes to ensure developers are not overwhelmed. The objective of this survey is to clarify the significance of a lead person to monitor the DevOps pipeline and report any failure detected in each development stage. The study utilized meta-analysis of verified tertiary resources from other researchers that took a deep dive into the DevOps model and how it works towards organizational goals in various firms. All institutions involved in multiple business platforms should take advantage of new technologies to scale up their service delivery and net profit. If adopted and appropriately monitored, DevOps can revolutionize the capabilities of most business applications by minimizing downtimes and providing uninterrupted services.
Perspectives on the adherance to scrum rules in software project management
Authors: Alsaber Leanah , Al Elsheikh Ebtesam , Aljumah Sarah , Mohd Jamail Nor Shahida
Published: January 2021

Adapting users need to fulfill their requirements and delivering products to be on time within the planned cost, is critical matter that all software project managers (SPM) put the highest priority for it while considering the users satisfaction at the same time. Agile methodology is one of the solutions provided by software engineers (SE), to get the customers involved in the system development life cycle (SDLC) to avoid the risk nonconformance cost. Yet SPM’s still facing the nonconformance costs and the dynamic changes, and the root cause of the issue is not pointed on to find a solution for it. This undertaking research aimed at determining whether software developers understand scrum rules. In addition, how does this knowledge gab affect the software projects success from the project management perspective. Furthermore, the engagement studied the impact of lack of enough knowledge on the topic to project delivery. The collected data from the qualitative and quantitative methods, which was conducted with scrum teams who worked in the health information system (HIS), Educational solutions, and Governmental solutions has showed deviations in organizational practices and team conflicting, competition, and pressure as well as declined product quality.
BotDetectorFW: an optimized botnet detection framework based on five features-distance measures supported by comparisons of four machine learning classifiers using CICIDS2017 dataset
Authors: F. Jabbar Aya , J. Mohammed Imad
Published: January 2021

A Botnet is one of many attacks that can execute malicious tasks and develop continuously. Therefore, current research introduces a comparison framework, called BotDetectorFW, with classification and complexity improvements for the detection of Botnet attack using CICIDS2017 dataset. It is a free online dataset consist of several attacks with high-dimensions features. The process of feature selection is a significant step to obtain the least features by eliminating irrelated features and consequently reduces the detection time. This process implemented inside BotDetectorFW using two steps; data clustering and five distance measure formulas (cosine, dice, driver & kroeber, overlap, and pearson correlation) using C#, followed by selecting the best N features used as input into four classifier algorithms evaluated using machine learning (WEKA); multilayerperceptron, JRip, IBK, and random forest. In BotDetectorFW, the thoughtful and diligent cleaning of the dataset within the preprocessing stage beside the normalization, binary clustering of its features, followed by the adapting of feature selection based on suitable feature distance techniques, and finalized by testing of selected classification algorithms. All together contributed in satisfying the high-performance metrics using fewer features number (8 features as a minimum) compared to and outperforms other methods found in the literature that adopted (10 features or higher) using the same dataset. Furthermore, the results and performance evaluation of BotDetectorFM shows a competitive impact in terms of classification accuracy (ACC), precision (Pr), recall (Rc), and f-measure (F1) metrics.
Performance investigations of internet protocol versions for mobile Ad-hoc network based on qualnet simulator
Authors: H. Majeed Jaber , Abed Habeeb Najmah , Khalid Al-Azzawi Waleed
Published: January 2021

A mobile ad hoc network (MANET) can be seen as a mobile nodes collection having no support of fixed infrastructure and therefore its communication is totally dependent on the network's nodes. As a result of the mobility of nodes, rapid and unpredictable changes occur within the mobile ad hoc network (MANET) arrangements. Therefore, this makes the analysis of routing protocols very crucial so as to enhance efficient communication between the wireless nodes. IPv4 and IpV6 within the MANET is another issue of concern. IPv4 which has been traditionally used for ages and IPv6; predicted to be the forthcoming network architecture model is investigated because of its protection which has been improved as well as its enormous address space provision. The analysis on Ad Hoc On Demand Vector and Dynamic Manet On Demand routing protocols are performed using Qualnet simulator under the IPv4 and IPv6 standards. A thorough evaluation of the usability and functionality of the simulator software is carried out. The metrics for performance are; Throughput, End-to-End Delay and Average jitter. Afterwards, analyses and summary of the results is conducted and summarized in order to make available an assessment of their performances.
Analysis of machine learning algorithms for character recognition: a case study on handwritten digit recognition
Authors: Mujtaba Khandy Owais , Dadvandipour Samad
Published: January 2021

This paper covers the work done in handwritten digit recognition and the various classifiers that have been developed. Methods like MLP, SVM, Bayesian networks, and Random forests were discussed with their accuracy and are empirically evaluated. Boosted LetNet 4, an ensemble of various classifiers, has shown maximum efficiency among these methods. 
Most severe risk factors in software development projects in Kuwait
Authors: J. Al-Shehab Abdullah , Alfozan Thalaya , Gadelrab Hesham
Published: January 2021

Software development projects are famous of high rate failure, this made an encouragement for researcher to investigate reasons of failure. However, literature covering under developed countries is uncommon. This research investigates the most severe risk factors in software development project in the country of Kuwait. A face-to-face questionnaire with 109 IT practitioners in Kuwait from government and private organizations was conducted. The findings reveal and identify risk factors that have a high impact on the budget, quality, and schedule. The aim of this study is to validate risk factor taxonomy through quantitative methods by experts in the field of IT. Another purpose of this research is to provide a comprehensive and updated review of risk factors from Kuwait to be presented for IT practitioners and researchers.
Optimal PID controller design using artificial bee colony algorithm for robot arm
Authors: A. Sultan Ghassan , K. Jarjes Muhammed
Published: January 2021

Proportional integral derivation (PID) controller is used in this paper for optimal design, and tuning by zeigler and nichol (ZN) with artificial bee colony algorithm. The best parameter were found using these algorithms for best performance of a robot arm. The advantage of using ABC were highlighted. The controller using the new algorithm was tested for valid control process. Different colony size has been performed for tuning process, settling time, from time domain performance, rise time, overshot, and steady state error with ABC tuning give better dynamic performance than controller using the (ZN).
Supervision and control by SCADA of an automated fire system
Authors: Chamorro-Atalaya Omar , Arce-Santillan Dora , Diaz-Leyva Teodoro , Diaz-Choque Martin
Published: January 2021

The purpose of this article is to describe the development of a prototype of a monitoring and control system for a fire-fighting system, implemented through SCADA (supervisory control and data acquisition) for which the OPC (OLE for process control) is known. Known KepServerEX6 (single data source connectivity platform), with which the integration of the PLC (programmable logic controller), the human-machine interface (HMI) and the computer will be controlled, with the application of monitoring the operating parameters of a fire fighting system. These parameters are the pressure and flow of the electric pump, the values of the parameters are regularly controlled automatically by means of a frequency variator, according to the sprinkler actuation, the variator varies its operating frequency until achieving the optimal pressure and flow values. The level of correlation between the indicators to be monitored by the SCADA system is highly significant, equal to 0.977, 0.983 and 0.997 respectively. In addition, the dispersion model of the indicators monitored by the SCADA system will be determined, is the quadratic, with a determination factor of 0.999.
Hybrid algorithm for two-terminal reliability evaluation in communication networks
Authors: Mahmood Musaria Karim , Ucan Osman , Zaidan Zahraa , M. Karim Sulaiman
Published: January 2021

Network reliability is valuable in establishing a survivable communication network. Reliability evaluation algorithms are used in the design stage and during the network deployment. This work presents a new multistage hybrid technique for two-terminal reliability evaluation problem. It is based on a combination of graph reduction techniques and tie-set method. A new approach has been introduced for deducing tie-sets in a network containing both unidirectional and bi-directional edges. The proposed algorithm can be applied for both simple and complex networks without restrictions. The results confirm that new algorithm evaluates network's reliability with decreasing computing time compared to classical algorithms. The results for a case study of a 20-node network have demonstrated that the required time for reliability evaluation is decreased from (t>1 hour) in the case of using a classical algorithm, to (t<1 second) for the new algorithm.
Modeling and real time digital simulation of microgrids for campuses Malta and Jordan based on multiple distributed energy resources
Authors: Khiat Sidahmed , Chaker Abdelkader , Zacharia Lazaros , Onen Ahmed
Published: January 2021

This paper presents the modeling and real-time digital simulation of two microgrids: the malta college of arts, science and technology (MCAST) and the german jordan university (GJU). The aim is to provide an overview of future microgrid situation and capabilities with the benefits of integrating renewable energy sources (RES), such as photovoltaic panels, diesel generators and energy storage systems for projects on both campuses. The significance of this work starts with the fact that real measurements were used from the two pilots, obtained by measuring the real physical systems. These measures were used to plan different solutions regarding RES and energy storage system (ESS) topologies and sizes. Also, the demand curves for the real microgrids of MCAST and GJU have been parameterized, which may serve as a test bed for other studies in this area. Based on actual data collected from the two pilots, a real-time digital simulation is performed using an RT-LAB platform. The results obtained by this tool allow the microgrid manager to have a very accurate vision of the facility operation, in terms of power flow and default responses.  Several scenarios are studied, extracting valuable insight for implementing both projects in the future. Eventually, the proposed models would be a blueprint for training and research purposes in the microgrid field.
On the dispatch of minigrids with large penetration levels of variable renewable energy
Authors: Dweekat Anan A. , Shaaban Mohamed , Ngu Sze Song
Published: January 2021

The continuous use of fossil fuels for decades in electricity generation has led to dire environmental consequences. This has fostered the incorporation of variable renewable energy resources (RES) to improve the environmental outlook and minimize emissions. This paper presents an approach for the dispatch of a minigrid considering variable solar photovoltaic (PV) generation. Due to the variability of the solar irradiance received from the sun during daytime only, solar irradiance is modeled as a stochastic random variable that is fitted into a Beta probability density function (PDF). The minigrid dispatch problem, modeled using stochastic optimization, is then approximated into a linear equivalent to become a mixed integer linear programming (MILP) problem that can be solved efficiently. The proposed approach is implemented on the modified IEEE 14-bus test system to verify its capability in solving the minigrid dispatch under various test case scenarios.  
Energy budget and methods for determining coordinates for a radiomonitoring system based on a small spacecraft
Authors: Aitmagambetov Altay , Butuzov Yuri , Butuzov Yuri , Tikhvinskiy Valery , Tikhvinskiy Valery , Kulakayeva Aigul , Kulakayeva Aigul , Ongenbayeva Zhadyra , Ongenbayeva Zhadyra
Published: January 2021

The existing ground-based radio monitoring systems do not allow performing the functions and tasks of radio spectrum monitoring in a quality manner. Therefore, to improve the efficiency of the radio spectrum monitoring systems for countries with a large territory, such as the Republic of Kazakhstan, it is proposed to use low-orbit small spacecrafts as radio monitoring stations. The analysis of the energy budget of radio lines on the basis of existing radio electronic means on the territory of the Republic of Kazakhstan, carried out in this work, showed the possibility of using low-orbit small spacecrafts for performing the functions and tasks of radio monitoring. The paper proposes and develops a method for determining the coordinates of radio emission sources based on the goniometric method using scanning antennas on board of one spacecraft. The ranges of the antenna scanning angles are substantiated, and the estimates of the coordinates determination errors are made. Algorithms have been developed and computer programs have been compiled to determine the coordinates of the radio emission sources, which will make it possible to use this method at the initial stages of developing a radio spectrum monitoring system based on one small spacecraft.
noção de texto na semiótica: do texto-absoluto ao texto-objeto
Authors: Moraes Letícia
Published: January 2021

O presente artigo consiste em um estudo sobre a noção de texto na semiótica de  filiação greimasiana. Neste trabalho, apresenta-se uma hipótese de percurso textual, demonstrando como a geração do texto se dá a partir de uma grandeza de ordem epistemológica até a sua manifestação em  um objeto semiótico. Com base nos estudos de L. Hjelmslev (2013 [1943]) e A. J. Greimas (1974; 2008 [1979], em colaboração com J. Courtés), discute-se a importância da análise hjelmsleviana para a constituição do objeto semiótico e apresenta uma hipótese de organização do percurso gerativo textual, desvelando seus polos e suas instâncias intermediárias - a instância textual e a instância da textualização. O percurso textual, que tem o seu início demarcado no texto-absoluto e o seu fim na manifestação do texto-objeto, auxilia a compreensão de como os diferentes objetos (ex. a canção, a pintura, a dança, a arquitetura, as práticas, etc) podem ser concebidos com base em uma grandeza não analisada, não quantificável e geral, tornando-se, todos eles, ao final do percurso, objetos semióticos. Espera-se, com a proposta, contribuir para a discussão acerca do texto enquanto objeto da semiótica.
Outcomes of Pediatric Patients With Defibrillators Following Initial Presentation With Sudden Cardiac Arrest
Authors: Robinson Jeffrey A. , LaPage Martin J. , Atallah Joseph , Webster Gregory , Miyake Christina Y. , Ratnasamy Christopher , Ollberding Nicholas J. , Mohan Shaun , Von Bergen Nicholas H. , Johnsrude Christopher L. , Garnreiter Jason M. , Spar David S. , Czosek Richard J.
Published: January 2021

Background:

Implantable cardioverter defibrillators (ICD) are recommended for secondary prevention after sudden cardiac arrest (SCA). The outcomes of pediatric patients receiving an ICD after SCA remain unclear. The objective of this study is to evaluate outcomes, future risk for appropriate shocks, and identify characteristics associated with appropriate ICD therapy during follow-up.

Methods:

Multicenter retrospective analysis of patients (age ≤21 years) without prior cardiac disease who received an ICD following SCA. Patient/device characteristics, cardiac function, and underlying diagnoses were collected, along with SCA event characteristics. Patient outcomes including complications and device therapies were analyzed.

Results:

In total, 106 patients were included, median age 14.7 years. Twenty (19%) received appropriate shocks and 16 (15%) received inappropriate shocks (median follow-up 3 years). First-degree relative with SCA was associated with appropriate shocks (
P
<0.05). In total, 40% patients were considered idiopathic. Channelopathy was the most frequent late diagnosis not made at time of presentation. Neither underlying diagnosis nor idiopathic status was associated with increased incidence of appropriate shock. Monomorphic ventricular tachycardia (hazard ratio, 4.6 [1.2–17.3]) and family history of sudden death (hazard ratio, 6.5 [1.4–29.8]) were associated with freedom from appropriate shock in a multivariable model (area under the receiver operating characteristic curve, 0.8). Time from diagnoses to evaluation demonstrated a nonlinear association with freedom from appropriate shock (
P
=0.015). In patients >2 years from implantation, younger age (
P
=0.02) and positive exercise test (
P
=0.04) were associated with appropriate shock.

Conclusions:

The risk of future device therapy is high in pediatric patients receiving an ICD after SCA, irrelevant of underlying disease. Lack of a definitive diagnosis after SCA was not associated with lower risk of subsequent events and does not obviate the need for secondary prophylaxis.