bluuebunny/crossref_metadata_2025 huggingface dataset:
Cerebral Venous Thrombosis in the Setting of Malignancy: Case Report and Review of the Literature
Authors: Logothetis Constantine N. , Pizanis Charles
Published: September 2020

Cerebral venous thrombosis (CVT) is a rare condition that can be difficult to diagnose due to its vague and nonspecific symptoms. It is even more unusual to identify CVT in association with malignancy. Given the rarity of this disease, treatment and management of CVT in the setting of malignancy is not well defined. This case report and review of the literature addresses the epidemiology, pathophysiology, and medical treatment for malignancy-related CVT.
Diagnostic and Prognostic Potentials of Long Noncoding RNA ELF3-AS1 in Glioma Patients
Authors: Mei Jun-chi , Yan Ge , Mei Si-qing
Published: September 2020

Objective. Accumulating evidence implies that long noncoding RNAs (lncRNAs) play a crucial role in predicting survival for glioma patients. However, the potential function of lncRNA ELF3-antisense RNA 1 (ELF3-AS1) in tumors remained largely unclear. The aim of this study was to explore the expression of lncRNA ELF3-antisense RNA 1 (ELF3-AS1) and evaluate its functions in glioma patients. Patients and Methods. ELF3-AS1 expressions were examined by RT-PCR in 182 pairs of glioma specimens and adjacent normal tissues. The receiver operating characteristic (ROC) curve was performed to estimate the diagnostic value of ELF3-AS1. The chi-square tests were used to examine the associations between ELF3-AS1 expression and the clinicopathological characters. The overall survival (OS) and disease-free survival (DFS) were analyzed by log-rank test, and survival curves were plotted according to Kaplan-Meier. The prognostic value of the ELF3-AS1 expression in glioma patients was further analyzed using univariate and multivariate Cox regression analyses. Loss-of-function assays were performed to determine the potential function of ELF3-AS1 on the proliferation and invasion of glioma cells. Results. The ELF3-AS1 expression level was significantly higher in glioma specimens compared with adjacent nontumor specimens (p<0.01). A high expression of ELF3-AS1 was shown to be associated with the WHO grade (p=0.023) and KPS score (p=0.012). ROC assays revealed that high ELF3-AS1 expression had an AUC value of 0.8073 (95% CI: 0.7610 to 0.8535) for glioma. Using the Kaplan-Meier analysis, we found that patients with a high ELF3-AS1 expression had significantly poor OS (p=0.006) and DFS (p=0.0002). In a multivariate Cox model, we confirmed that ELF3-AS1 expression was an independent poor prognostic factor for glioma patients. The functional assay revealed that knockdown of ELF3-AS1 suppressed the proliferation and invasion of glioma cells. Conclusions. Our findings confirmed that ELF3-AS1 functions as an oncogene in glioma and indicated that ELF3-AS1 is not only an important prognostic marker but also a potential therapy target for glioma.
Successful Resection of a Giant Pulmonary Colloid Adenocarcinoma via Median Sternotomy
Authors: Nakamura Daisuke , Kondo Ryoichi , Makiuchi Akiko , Itagaki Hiroko
Published: September 2020

We report on a giant pulmonary colloid adenocarcinoma successfully resected using a median sternotomy approach. A 69-year-old woman visited our hospital owing to a giant mass detected on chest radiography. A giant cystic mass measuring 115 × 90 mm was detected in the right upper lung using computed tomography. We suspected mucinous adenocarcinoma and performed right upper lobectomy and mediastinal lymph node dissection with median sternotomy. The surgical field of view for the tumor and superior vena cava was satisfactory, and compression but not invasion of the superior vena cava and chest wall by the tumor was observed. The tumor was pathologically diagnosed as a colloid adenocarcinoma of stage IIIA with pT4N0M0. The postoperative course was uneventful, with no signs of recurrence at one and a half years after operation. Thus, this case demonstrates that for giant lung tumor surgery, median sternotomy is useful and safe for improving the surgical field of view.
Performance comparison of different control strategies for the regulation of DC-DC negative output super-lift luo-converter
Authors: Motlak Hassan Jassim , Rahi Ahmed S.
Published: September 2020

In last years, dc-dc converters solve the most issues in the industrial application in the area of power electronics, especially renewable energy, military applications and affiliated engineering developments. They are used to convert the DC input that unregulated to regulated output perhaps larger or smaller than input according to the type of converters. This paper presents three primary control method used for negative output Super lift Luo DC-DC converter. These methods include a Voltage mode control (VMC), Current mode control (CMC), and Sliding mode control (SMC). The goal of this article is to study and selected an appropriate and superior control scheme for negative DC-DC converters. The simulation results show the effectiveness of Sliding mode control for enhancing the performance of the negative dc-dc converter. Also, this method can keep the output voltage constant under load conditions. simulation results obtained by the MATLAB/Simulink environment.
An effective RGB color selection for complex 3D object structure in scene graph systems
Authors: Van Chung Le , Nguyen Gia Nhu , Nguyen Tri Huu , Nguyen Tung Sanh , Le Dac-Nhuong
Published: September 2020

The goal of this project is to develop a complete, fully detailed 3D interactive model of the human body and systems in the human body, and allow the user to interacts in 3D with all the elements of that system, to teach students about human anatomy. Some organs, which contain a lot of details about a particular anatomy, need to be accurately and fully described in minute detail, such as the brain, lungs, liver and heart. These organs are need have all the detailed descriptions of the medical information needed to learn how to do surgery on them, and should allow the user to add careful and precise marking to indicate the operative landmarks on the surgery location. Adding so many different items of information is challenging when the area to which the information needs to be attached is very detailed and overlaps with all kinds of other medical information related to the area. Existing methods to tag areas was not allowing us sufficient locations to attach the information to. Our solution combines a variety of tagging methods, which use the marking method by selecting the RGB color area that is drawn in the texture, on the complex 3D object structure. Then, it relies on those RGB color codes to tag IDs and create relational tables that store the related information about the specific areas of the anatomy. With this method of marking, it is possible to use the entire set of color values (R, G, B) to identify a set of anatomic regions, and this also makes it possible to define multiple overlapping regions.
Energy efficient routing in wireless sensor network based on mobile sink guided by stochastic hill climbing
Authors: Y. M. Mr. Raghavendra , Mahadevaswamy Dr. U. B.
Published: September 2020

In Wireless Sensor Networks (WSNs), the reduction of energy consumption in the batteries of a sensor node is an important task. Sensor nodes of WSNs perform three significant functions such as data sensing, data transmitting and data relaying. Routing technique is one of the methods to enhance the sensor nodes battery lifetime. Energy optimization is done by using one of the heuristic routing methods for sensing and transmitting the data. To enhance the energy optimization mainly concentrated on data relaying. In this work stochastic hill climbing is adapted. The proposed solution for data relaying utilizes geographical routing and mobile sink technique. The sink collects the data from cluster heads and movement of the sink is routed by stochastic hill climbing. Network simulator 2 is used for experimentation purpose. This work also compares with the existing routing protocols like Energy-efficient Low Duty Cycle (ELDC), Threshold sensitive Energy Efficient sensor Network (TEEN) and Adaptive clustering protocol. The proposed work shows promising results with respect to lifetime, average energy of nodes and packet delivery ratio.
A statistical analysis of corpus based approach on learning sentence patterns
Authors: Bhargavi S. , Anbazhagan K.
Published: September 2020

This research paper examines the adverse effect of theoretical explanation of the grammatical rules among the learners. Exploration of the methods and materials taught inductively or deductively is the panacea to achieve the required goal. The study throws light on the pedagogical implication of adopting appropriate methods and materials for building the learners’ grammar and language. It primarily intends to explore a new teaching method using language corpora that can be employed in the English grammar classes in colleges at the undergraduate level. It strives to evaluate the effectiveness of teaching sentence patterns through corpus based activities comparing with the traditional based teaching. Thus the methodology aims to encourage students to become independent corpus users.
Development modeling methods of analysis and synthesis of fingerprint deformations images
Authors: Majeed AlKaraawi Haider Hassan , Dhahir Mohammed Qasim , Alameri Ibrahim Ahmed , Mohsen Mowafak K.
Published: September 2020

The current study is to develop modeling methods, Analysis and synthesis of fingerprints deformations images and their application in problems of automatic fingerprint identification. In the introduction justified urgency of the problem, is given a brief description of thematic publications. In this study will review of modern technologies of biometric technologies and methods of biometric identification, the review of fingerprint identification systems, investigate for distorting factors. The influence of deformations is singled out, the causes of deformation of fingerprints are analyzed. The review of modern ways of the account and modeling of deformations in problems of automatic fingerprint identification is given. The scientific novelty of the work is the development of information technologies for the analysis and synthesis of deformations of fingerprint images. The practical value of the work in the application of the developed methods, algorithms and information technologies in fingerprints identification systems. In addition, it has been found that our paper "devoted to research methods and synthesis of the fingerprint deformations" is a more appropriate choice than other papers.
A new exact equivalent circuit of the medium voltage three-phase induction motor
Authors: Solar Laura Collazo , Costa Montiel Angel A. , Llanes Miriam Vilaragut , Santos Vladimir Sousa , Colina Abel Curbelo
Published: September 2020

This paper proposes a new equivalent circuit for medium voltage and great power induction motors considering the more complete information given by the manufacturer. A methodology for obtaining the parameters of the equivalent circuit is presented, having this circuit the advantage of allowing the electrical calculation of all the power losses and the realization of the power balance. It is an achievement of this work a new way of calculating and representing the additional losses using a resistance located in the rotor circuit. Then, three types of losses are considered as a part of a power balance: the conventional or joule effect variable losses, the constant losses, and the additional losses. The proposed method is straight and non-iterative. It was applied to a case study motor of 6000 V and 2500 kW located at the Maximo Gomez Power Plant in Cuba.
PSO-CCO_MIMO-SA: A particle swarm optimization based channel capacity optimzation for MIMO system incorporated with smart antenna
Authors: T. G. Shivapanchakshari , Aravinda H. S.
Published: September 2020

With the radio channels physical limits, achieving higher data rate in the multi-channel systems is been a biggest concern. Hence, various spatial domain techniques have been introduced by incorporating array of antenna elements (i.e., smart antenna) in recent past for the channel limit expansion in mobile communication antennas. These smart antennas help to yield the improved array gain or bearm forming gain and hence by power efficiency enhanmaent in the channel and antenna range expansion. The use of smart antenna leads to spatial diversity and minimizes the fading effect and improves link reliability. However, in the process of antenna design, the proper channel modelling is is biggest concern which affect the wireless system performance. The recent works of MIMO design systems have discussed the issues in number of antenna selection which suggests that optimization of MIMO channel capacity is required. Hence, a Particle Swarm Optimization based channel capacity optimzation for MIMO system incorporated with smart antenna is introduced in this paper. From the outcomes it is been found that the proposed PSO based MIMO system achieves better convergenece speed which results in better channel capacity.
Evaluation of non-parametric identification techniques in second order models plus dead time
Authors: Robles-Algarín Carlos , Rodríguez Omar , Ospino Adalberto
Published: September 2020

In this paper, a set of non-parametric identification techniques are used in order to obtain second order models plus dead time for an underdamped system. Initially, non-parametric techniques were used to identify the system from the temperature data of a coal-heated oven. In this case, the identification techniques proposed by Stark, Jahanmiri - Fallahi and Ogata were used, which require obtaining two or three points of the step response for the system under study. In addition, the Matlab PID Tuner app was used to identify the underdamped system and compare the results with the other methods. The results show that the PID Tuner and the method proposed by Ogata are the ones that best represent the dynamics of the underdamped system, taking into account the values for the Integral Absolute Error (IAE) and the correlation coefficient. With the Stark method an IAE of 181.56 was obtained, while with the PID Tuner the best performance was achieved with an IAE of 21.59. In terms of the results obtained with the cross correlation, the best performance was achieved with the PID tuner and the Stark method.
Demand robust counterpart open capacitated vehicle routing problem time windows and deadline model of garbage transportation with LINGO 13.0
Authors: Puspita Fitri Maya , Br. Simanjuntak Ani Sahara , Melati Rima , Octarina Sisca
Published: September 2020

Demand robust counterpart-open capacitated vehicle routing problem with time windows and deadline (DRC-OCVRPtw,d) model formed and explained in this paper, is the model used to find the minimum distance and the time needed for vehicles to transport garbage in Sukarami Sub-District, Palembang that consists of the time it takes for the vehicle to pass through the route. Time needed to transport garbage to the vehicle is called time windows. Combination of the thoses times is called deadline. The farther

the distance passed by vehicle and the more garbage transported, the longer the deadline is needed. This DRC-OCVRPtw,d model is completed by LINGO 13.0 to obtain the optimal route and time deadline for Sukarami Sub-District. The model shows that the improved model of open vehicle routing problem involving the robustness, time windows and deadline can achieve the optimal routes that enable driver to save operational time in picking up the garbage compared to similar problem not involving no-time windows and deadline stated in previous research.
On solving fuzzy delay differential equation using bezier curves
Authors: Jameel Ali F. , Amen Sardar G. , Saaban Azizan , Man Noraziah H.
Published: September 2020

In this article, we plan to use Bezier curves method to solve linear fuzzy delay differential equations. A Bezier curves method is presented and modified to solve fuzzy delay problems taking the advantages of the fuzzy set theory properties. The approximate solution with different degrees is compared to the exact solution to confirm that the linear fuzzy delay differential equations process is accurate and efficient. Numerical example is explained and analyzed involved first order linear fuzzy delay differential equations to demonstrate these proper features of this proposed problem.
Courses timetabling based on hill climbing algorithm
Authors: Rjoub Abdoul
Published: September 2020

In addition to its monotonous nature and excessive time requirements, the manual school timetable scheduling often leads to more than one class being assigned to the same instructor, or more than one instructor being assigned to the same classroom during the same slot time, or even leads to exercise in intentional partialities in favor of a particular group of instructors. In this paper, an automated school timetable scheduling is presented to help overcome the traditional conflicts inherent in the manual scheduling approach. In this approach, hill climbing algorithms have been modified to transact hard and soft constraints. Soft constraints are not easy to be satisfied typically, but hard constraints are obligated. The implementation of this technique has been successfully experimented in different schools with various kinds of side constraints. Results show that the initial solution can be improved by 72% towards the optimal solution within the first 5 seconds and by 50% from the second iteration while the optimal solution will be achieved after 15 iterations ensuring that more than 50% of scientific courses will take place in the early slots time while more than 50% of non-scientific courses will take place during the later time's slots.
Prediction of atmospheric pollution using neural networks model of fine particles in the town of Kennedy in Bogota
Authors: Pedraza Juan Camilo , Romero Oswaldo Alberto , Espitia Helbert Eduardo
Published: September 2020

This work shows an application based on neural networks to determine the prediction of air pollution, especially particulate material of 2.5 micrometers length. This application is considered of great importance due to the impact on human health and high impact due to the agglomeration of people in cities. The implementation is performed using data captured from several devices that can be installed in specific locations for a particular geographical environment, especially in the locality of Kennedy in Bogotá. The model obtained can be used for the design of public policies that control air quality.
Hybrid bat-ant colony optimization algorithm for rule-based feature selection in health care
Authors: Sagban Rafid , Marhoon Haydar A. , Alubady Raaid
Published: September 2020

Rule-based classification in the field of health care using artificial intelligence provides solutions in decision-making problems involving different domains. An important challenge is providing access to good and fast health facilities. Cervical cancer is one of the most frequent causes of death in females. The diagnostic methods for cervical cancer used in health centers are costly and time-consuming. In this paper, bat algorithm for feature selection and ant colony optimization-based classification algorithm were applied on cervical cancer data set obtained from the repository of the University of California, Irvine to analyze the disease based on optimal features. The proposed algorithm outperforms other methods in terms of comprehensibility and obtains better results in terms of classification accuracy.
Voltage collapse prediction using artificial neural network
Authors: Isaac Samuel , Adebola Soyemi , Ayokunle Awelewa , James Katende , Claudius Awosope
Published: September 2020

Unalleviated voltage instability frequently results in voltage collapse; which is a cause of concern in power system networks across the globe but particularly in developing countries. This study proposed an online voltage collapse prediction model through the application of a machine learning technique and a voltage stability index called the new line stability index (NLSI_1). The approach proposed is based on a multilayer feed-forward neural network whose inputs are the variables of the NLSI_1. The efficacy of the method was validated using the testing on the IEEE 14-bus system and the Nigeria 330-kV, 28-bus National Grid (NNG). The results of the simulations indicate that the proposed approach accurately predicted the voltage stability index with an R-value of 0.9975 with a mean square error (MSE) of 2.182415x10−5 for the IEEE 14-bus system and an R-value of 0.9989 with an MSE of 1.2527x10−7 for the NNG 28 bus system. The results presented in this paper agree with those found in the literature.
Bulk power system availability assessment with multiple wind power plants
Authors: Cepeda Angie C. , Rios Mario A.
Published: September 2020

The use of renewable non-conventional energy sources, as wind electric power energy and photovoltaic solar energy, has introduced uncertainties in the performance of bulk power systems. The power system availability has been employed as a useful tool for planning power systems; however, traditional methodologies model generation units as a component with two states: in service or out of service. Nevertheless, this model is not useful to model wind power plants for availability assessment of the power system. This paper used a statistical representation to model the uncertainty of power injection of wind power plants based on the central moments: mean value, variance, skewness and kurtosis. In addition, this paper proposed an availability assessment methodology based on application of this statistical model, and based on the 2m+1 point estimate method the availability assessment is performed. The methodology was tested on the IEEE-RTS assuming the connection of two wind power plants and different correlation among the behavior of these plants.
System uncertainties estimation based adaptive robust backstepping control for DC DC buck converter
Authors: Mary Ali Hussien , Miry Abbas Hussien , Miry Mohammed Hussein
Published: September 2020

This paper proposed a novel adaptive robust backstepping control scheme for DC-DC buck converter subjected to external disturbance and system uncertainty. Uncertainty in the load resistance and the input voltage represent the big challenge in buck converter control. In this work, an adaptive estimator for matched and mismatched uncertainties based backstepping control is applied for DC-DC buck converter. The updating laws are determined based on the lyapunov theorem. Thus, the difference between the estimated parameters and actual parameters converges to zero. The proposed control method is compared with the conventional sliding mode control and integral sliding mode control. Simulation results demonstrate the effectiveness and robustness of the proposed controller.
Focused and collimated Gaussian laser beam scintillation in weakly turbulent marine atmospheric medium
Authors: Abbas Ahmed A. , Gerçekcioğlu Hamza , Göktaş H. Haldun
Published: September 2020

The scintillation index on the axis for Gaussian beams focused and collimated in weak marine turbulence is formulated via the usage of Rytov method. The average bit error rate  is evaluated using this formulation. The scintillation index and  versus propagation distance and source size are determined by using the log-normal distributed. Intensity for the collimated and focused. Gaussian beams, which are exhibited for wavelength, source size, focal length, and . The focused beams are revealing more advantageous than collimated beams in an atmospheric marine environment. The findings of this study are significant for optical communication system performance in this layer.
Features of genetic algorithm for plain text encryption
Authors: Abduljabbar Riyadh Bassil , Hamid Oday Kamil , Alhyani Nazar Jabbar
Published: September 2020

The data communication has been growing in present day. Therefore, the data encryption became very essential in secured data transmission and storage and protecting data contents from intruder and unauthorized persons. In this paper, a fast technique for text encryption depending on genetic algorithm is presented. The encryption approach is achieved by the genetic operators Crossover and mutation. The encryption proposal technique based on dividing the plain text characters into pairs, and applying the crossover operation between them, followed by the mutation operation to get the encrypted text. The experimental results show that the proposal provides an important improvement in encryption rate with comparatively high-speed Processing.
M-ary phase-shift keying using finite impulse response filter based on window function method
Authors: Daraghma Raed S. M.
Published: September 2020

Digital filters are vastly utilized in the area of communication. A perfect digital filter efficiency is significant and hence to design a digital finite impulse response filter (FIR) favorable all the wanted situations is necessary. In this paper, a new proposed FIR digital filter designed, the fineness of the submitted filter is tested in terms of BER and then matched with another window, namely Hamming, Hanning, and Blackman. The design procedure done in the MATLAB software. It is concluded that the Blackman window is the best window to design the FIR digital filter, because it is bit error rate is better than another window.
Sustainable governance in smart cities and use of supervised learning based opinion mining
Authors: Iqbal Hena , Paul Sujni , Khan Khaliquzzaman
Published: September 2020

Evaluation is an analytical and organized process to figure out the present positive influences, favourable future prospects, existing shortcomings and ulterior complexities of any plan, program, practice or a policy. Evaluation of policy is an essential and vital process required to measure the performance or progression of the scheme. The main purpose of policy evaluation is to empower various stakeholders and enhance their socio-economic environment. A large number of policies or schemes in different areas are launched by government in view of citizen welfare. Although, the governmental policies intend to better shape up the life quality of people but may also impact their every day’s life. A latest governmental scheme Saubhagya launched by Indian government in 2017 has been selected for evaluation by applying opinion mining techniques. The data set of public opinion associated with this scheme has been captured by Twitter. The primary intent is to offer opinion mining as a smart city technology that harness the user-generated big data and analyse it to offer a sustainable governance model.
Fingerprint positioning of users devices in long term evolution cellular network using K nearest neighbour algorithm
Authors: Alhasan Mohammed J. , Abdulhussein Sarmad Muneer , Khwayyir Ali H. K.
Published: September 2020

The rapid exponential growth in wireless technologies and the need for public safety has led to increasing demand for location-based services. Terrestrial cellular networks can offer acceptable position estimation for users that can meet the statutory requirements set by the Federal Communications Commission in case of network-based positioning, for safety regulations. In this study, the proposed radio frequency pattern matching (RFPM) method is implemented and tested to determine a user’s location effectively. The RFPM method has been tested and validated in two different environment. The evaluations show remarkable results especially in the Micro cell scenario, at 67% of positioning error 15m and at 90% 31.78m for Micro cell scenario, with results of 75.66m at 67% and 141.4m at 90% for Macro cell scenario.
A new parallel bat algorithm for musical note recognition
Authors: Younis ِAnsam Nazar , Ramo Fawzia Mahmood
Published: September 2020

Music is a universal language that does not require an interpreter, where feelings and sensitivities are united, regardless of the different peoples and languages, The proposed system consists of two main stages: the process of extracting important properties using the linear discrimination analysis (LDA) This step is carried out after the initial treatment process using various procedures to remove musical lines, The second stage describes the recognition process using the bat algorithm, which is one of the metaheuristic algorithms after modifying the bat algorithm to obtain better discriminating results. The proposed system was supported by parallel implementation using the (Developed Bat Algorithm DBA), which increased the speed of implementation significantly. The method was applied to 1250 different images of musical notes. The proposed system was implemented using MATLAB R2016a, Work was done on a Windows10 Processor OS (Intel ® Core TM i5-7200U CPU @ 2.50GHZ 2.70GHZ) computer.
Conformable chebyshev differential Equation of first kind
Authors: Rababah Abedallah
Published: September 2020

In this paper, the Chebyshev-I conformable differential equation is considered. A proper power series is examined; there are two solutions, the even solution and the odd solution. The Rodrigues’ type formula is also allocated for the conformable Chebyshev-I polynomials.
A latency-aware max-min algorithm for resource allocation in cloud
Authors: Shakil Kashish Ara , Alam Mansaf , Khan Samiya
Published: September 2020

Cloud computing is an emerging distributed computing paradigm. However, it requires certain initiatives that need to be tailored for the cloud environment such as the provision of an on-the-fly mechanism for providing resource availability based on the rapidly changing demands of the customers. Although, resource allocation is an important problem and has been widely studied, there are certain criteria that need to be considered. These criteria include meeting user’s quality of service (QoS) requirements. High QoS can be guaranteed only if resources are allocated in an optimal manner. This paper proposes a latency-aware max-min algorithm (LAM) for allocation of resources in cloud infrastructures. The proposed algorithm was designed to address challenges associated with resource allocation such as variations in user demands and on-demand access to unlimited resources. It is capable of allocating resources in a cloud-based environment with the target of enhancing infrastructure-level performance and maximization of profits with the optimum allocation of resources. A priority value is also associated with each user, which is calculated by analytic hierarchy process (AHP). The results validate the superiority for LAM due to better performance in comparison to other state-of-the-art algorithms with flexibility in resource allocation for fluctuating resource demand patterns.
Software development effort estimation modeling using a combination of fuzzy-neural network and differential evolution algorithm
Authors: Karimi Amir , Gandomani Taghi Javdani
Published: September 2020

Software cost estimation has always been a serious challenge lying ahead of software teams that should be seriously considered in the early stages of a project. Lack of sufficient information on final requirements, as well as the existence of inaccurate and vague requirements, are among the main reasons for unreliable estimations in this area. Though several effort estimation models have been proposed over the recent decade, an increase in their accuracy has always been a controversial issue, and researchers' efforts in this area are still ongoing. This study presents a new model based on a hybrid of adaptive network-based fuzzy inference system (ANFIS) and differential evolution (DE) algorithm. This model tries to obtain a more accurate estimation of software development effort that is capable of presenting a better estimate within a wide range of software projects compared to previous works. The proposed method outperformed other optimization algorithms adopted from the genetic algorithm, evolutionary algorithms, meta-heuristic algorithms, and neuro-fuzzy based optimization algorithms, and could improve the accuracy using MMRE and PRED (0.25) criteria up to 7%.
Electrical characterization of si nanowire GAA-TFET based on dimensions downscaling
Authors: Abdul-Kadir Firas Natheer , Hashim Yasir , Shakib Muhammad Nazmus , Taha Faris Hassan
Published: September 2020

This research paper explains the effect of the dimensions of Gate-all-around Si nanowire tunneling field effect transistor (GAA Si-NW TFET) on ON/OFF current ratio, drain induces barrier lowering (DIBL), sub-threshold swing (SS), and threshold voltage (VT). These parameters are critical factors of the characteristics of tunnel field effect transistors. The Silvaco TCAD has been used to study the electrical characteristics of Si-NW TFET. Output (gate voltage-drain current) characteristics with channel dimensions were simulated. Results show that 50nm long nanowires with 9nm-18nm diameter and 3nm oxide thickness tend to have the best nanowire tunnel field effect transistor (Si-NW TFET) characteristics.
Developing digital signal clustering method using local binary pattern histogram
Authors: Rasras Rashad J. , Zahran Bilal , Abu Sara Mutaz Rasmi , AlQadi Ziad
Published: September 2020

In this paper we presented a new approach to manipulate a digital signal in order to create a features array, which can be used as a signature to retrieve the signal. Each digital signal is associated with the local binary pattern (LBP) histogram; this histogram will be calculated based on LBP operator, then k-means clustering was used to generate the required features for each digital signal. The proposed method was implemented, tested and the obtained experimental results were analyzed. The results showed the flexibility and accuracy of the proposed method. Althoug different parameters of the digital signal were changed during implementation, the results obtained showed the robustness of the proposed method.
Measuring User Intention for Continued Usage of Internet of Medical Devices—A Proposed Framework
Authors: Singh Manpreet , Mittal Amit
Published: September 2020

Internet of Medical Devices is a connected ecosystem of devices, physicians and patients intended to deliver affordable and quality healthcare to masses. The study is intended to identify and establish variables which influence user intentions for continued usage for this purpose we
have used Unified Theory of Acceptance and use of technology (UTAUT) model, Expectation Confirmation Theory (ECT) and Medical Device Technology Development Process theory (MDTDP). App Quality, system stability and User experience are other variables utilized in study the study aims to bring
in focus variables which influence “intentions for continued usage.” These insights will be valuable to all interested in connected devices ecosystem in healthcare and can be imbibed for creating better customer experience in an era of IOMD and healthcare.
Blockchain: A New Technology to Enhance Data Security and Privacy in Internet of Things
Authors: Simaiya Sarita , Lilhore Umesh Kumar , Sharma Sanjeev Kumar , Gupta Kamali , Baggan Vidhu
Published: September 2020

A revolutionary technology well into the world of technology has been in the modern world of technology the Internet of Things. Due to continuing increases as nothing more than a consequence of either the rapid development of computing Internet of things-based applications implementations.
Many technologies become increasingly embraced throughout compatible devices such as home automation and also smart cities. These IoT applications become operated on both the Internet, whereby information becomes transported publicly between a network to the next, therefore flowing information
requires a great deal of further privacy consideration to guarantee IoT applications become reliable Internet of things technologies have been using various techniques of data protection of security and privacy. However, all such modern security systems have always been sufficient to ensure
the Internet of things perceived safety. A Blockchain has become a revolutionary authoritative digital technology that really transforms commercial transactions absolutely. This is also a collaborative service that facilitates it uses a variety of features of cybersecurity. Blockchain technology
seems to be the missing piece of the puzzle throughout the IoT to address problems of usability, anonymity, including security. Block chain’s crypto algorithms must enable transparency from customers very confidential. Throughout this research article, we introduce an analysis of IoT
security concerns; blockchain gets addressed briefly as well as later addresses the security of IoT applications dependent on blockchain technologies.
A Gender Specific Survey Assessment of Internet Home-Use in Malaysia
Authors: Hashim Wahidah , Othman Marini , Moamin A. Mahmoud , Maseleno Andino
Published: September 2020

This research consists of five categories which are: social media, online shopping, playing games, watching videos and reading blogs. In this research, a survey was conducted to assess the internet dependency among the young housewives in Klang Valley. Data collected from an online
survey which was responded by 200 respondents is analysed for usage pattern and allowing the identification of the seriousness of internet addiction for segment. It is found that there are many problematic use of the technology which may impact life quality of the housewives, children under
their care, and the family at large. Recommendation are made to towards a more appropriate use of the technology.
Using Predictive Analytics to Measure the Effectiveness of Select Direct Marketing Attributes in the Banking Sector
Authors: Mittal Ruchi
Published: September 2020

Data mining and predictive analytics are critical for the effective and sustainable functioning of the services economy. Banking is a very significant component of the services economy due to its socio-economic impact and its impact on the development of any country’s economy.
The banking sector is also a major source and a subject of research for data scientists. This study uses select non-metric (demographics) and metric (direct marketing attributes) data from the UCI database. The study explores and predicts the relationship among age, bank balance and call duration
of the marketing campaign. Marital status and education levels are included the measure their moderation effect on the proposed model.
Performance Evaluation of Semantic Based Image Retrieval System from Cyberspace (SBIRSC) Framework
Authors: Singh Virender , Gupta Rajeev
Published: September 2020

With the popularity and remarkable development of digital imaging technology and its usage in various domains, an extraordinary level of accuracy required in the existing image retrieval techniques. The retrieval of the requested images on the basis of the user query by convoluted features
in cyberspace is a very big challenge. Various researchers were already proposed multiple techniques for image retrieval. But, after concluding the detailed research, the authors have analyzed that most of the search-engines does not produce an accurate result. In this context, a new generation
of digital images retrieval from cyberspace applications must be developed. This paper presents the performance evaluation of the proposed semantic-based image retrieval system from the cyberspace (SBIRSC) framework. The proposed framework was tested on various datasets like Flickr, Shutterstock,
Pixabay, Everypixel, Bing available on the cyberspace. The performance of the proposed framework is evaluated by using accuracy and response time.
Effective Cryptographic Renewal Method with Rivest-Shamir-Adleman, Modified Artificial Bee Colony Optimization to Achieve Secure Cloud Storage and Computation in Cloud Computing
Authors: Aggarwal Mayank , Malik Anju , Madhukar Mani
Published: September 2020

With the tremendous development of the online information, the term “Cloud Computing” offers multiple kinds of outsourcing and storage services to the user. Data security and privacy issues introduces multiple hurdles into it such as data leakage, calculating the key for
data encryption, lack of proper security policies and renewal of application in cloud environment. One of the main issues is how to store encrypted data, decrypt it when required and renewal of application to face the security challenges. In this work we have proposed a secured and timestamp
value based approach using RSA-MABC algorithm for encryption and decryption process. The work has been simulated in Cloudsim and results show our approach takes less time for encryption and decryption with added security features of renewing the secret key based on timestamp. Our results of
encryption and decryption time along with the results of ttest shows that our work is better than exiting approaches.
High Performance Query Execution and Graph Visualization for Effectual Big Data Analytics with Cloud
Authors: Garg Prachi , Goel Sandip Kumar , Sachdeva Sakshi , Oberoi Neelam
Published: September 2020

The domain of data science contains enormous approaches and high performance techniques in which there is need to evaluate the data from multiple dimensions so that the effectual outcomes and predictive knowledge can be extracted. Data Science and Analytics is now days one of the conspicuous
streams of advanced knowledge discovery. Following are the key constituents and assorted elements which are required in the data science for cavernous and multi-dimensional analytics of the datasets including Streaming of Data from Multiple Sources and Channels, Pre-Processing and Cleaning
of Real Time Streaming Data, Feature Engineering and Extraction of Prime Elements from Datasets, Numerical Analysis and Scientific Computations, Statistical Analytics on Datasets, Data Engineering Visualization, Plotting and Predictive Analytics. The paper is presenting the usage patterns
and cavernous analytics of big data with the high performance visualization using Grafana.
Long-term Results of Thoracic Endovascular Aortic Repair Using a Low-Profile Stent-Graft
Authors: Beropoulis Efthymios , Fazzini Stefano , Austermann Martin , Torsello Giovanni B. , Damerau Sarah , Torsello Giovanni Federico
Published: September 2020

Purpose

To evaluate the long-term results associated with the Zenith Alpha thoracic stent-graft, which was designed to address challenging access vessel anatomy.

Materials and Methods

A retrospective analysis was conducted of 44 consecutive patients (mean age 72.5±8.3 years; 25 men) treated in a single center between August 2010 and October 2014 with a minimum follow-up of 5 years in survivors. The Zenith Alpha thoracic stent-graft was used to treat thoracic aortic aneurysms (n=37), thoracoabdominal aortic aneurysm (n=5), or penetrating aortic ulcer (n=2). Ten patients (23%) were American Society of Anesthesiologists class IV, and 9 (20%) had nonelective procedures. Access vessel anatomy was demanding (mean minimum diameter 5.4 mm, tortuosity index 1.3). The primary endpoint at 5 years was ongoing clinical success (freedom from aneurysm-/procedure-related death, secondary intervention, type I or III endoleak, infection, thrombosis, aneurysm expansion, rupture, or conversion). Secondary endpoints were freedom from all-cause mortality, device migration, stent fractures, fabric erosions, endoleaks, neurological events, and access vessel complications.

Results

The ongoing clinical success was 84% (37 of 44 patients) owing to 4 aneurysm-related deaths (9%), 3 type I or III endoleaks (1 in a deceased patient), and 1 aneurysm expansion without detectable endoleak. There were 3 access vessel complications (7%), and no postoperative neurological events. Migration was observed in 2 cases (5%). There were no stent fractures or fabric tears.

Conclusion

Despite the alterations in stent-graft design and material to reduce profile, the Zenith Alpha thoracic stent-graft showed favorable long-term results even in multimorbid patients with demanding iliac anatomy.
Correction to: Increased risk of tinnitus following a trigeminal neuralgia diagnosis: a one-year follow-up study
Authors: Cheng Yen-Fu , Xirasagar Sudha , Yang Tzong-Han , Wu Chuan-Song , Kao Yi-Wei , Shia Ben-Chang , Lin Herng-Ching
Published: September 2020

An amendment to this paper has been published and can be accessed via the original article.
Bone ingrowth into open architecture PEEK interference screw after ACL reconstruction
Authors: Lind Martin , Nielsen Torsten , Sørensen Ole Gade , Mygind-Klavsen Bjarne , Faunø Peter , Leake-Gardner Stacy
Published: September 2020

Purpose

Open or fenestrated interference screw design that allow bone ingrowth is a concept for improved bone healing to softtissue graft and bone filling in bone tunnels after anterior cruciate ligament reconstruction (ACLR) The aim of the current study was to assess CT scanning evaluated bone ingrowth into an open architecture interference screws in the tibial tunnel of patients undergoing ACL with soft tissue grafts. It was hypothesized that open architecture interference screws would stimulate bone ingrowth into the screw cavities.

Methods

Twelve patients requiring ACLR were included. They underwent arthroscopic ACLR with semitendinosus−/gracilis tendon graft and an open architecture polyetheretherketone (PEEK) interference screw. The patients were scanned with a multi-slice CT scanner two weeks, six and twelve months postoperatively. On CT reconstruction slices bone ingrowth into the screw was measured. Subjective and objective clinical outcome international knee documentation committee score and instrumented knee laxity determination were collected.

Results

At six months no implants demonstrated more than 10% bone ingrowth. At twelve months 42% (5/12) implants had more than 10% bone ingrowth (p = 0.009). The average bone filling into the screws was 7.7%. There was no tunnel widening or cyst formation seen in relation to any of the implants. Subjective IKDC score improved significantly from 50.6 baseline to 80.1 at 24 month follow-up. Preoperative side-to-side knee laxity improved from 3.7 (2.1) to 1.4 (1.2) mm at twelve months. There were no serious adverse events in relation to the new open architecture thread PEEK interference screw during or after hamstring ACL reconstruction.

Conclusion

The present study demonstrated that open architecture thread PEEK interference screw can stimulate bone ingrowth into the screws after soft tissue ACL reconstruction with at 12 months with an average bone filling into screws was 7.7%. Knee stability, functional, subjective and objective outcomes were similar to large volume ACL outcome studies.

Trial registration

The study was registered at ClinicalTrials # NCT02382341. 12-09-2014.

Level of evidence

IV.
Soluble human leukocyte antigen-G evaluation in pregnant women with gestational diabetes mellitus
Authors: Abdel Hameed Muhamad R. , Ibrahiem Osama Ahmed , Ahmed Entsar Hamed , Sedky Paula Rofaeel , Mousa Naglaa Mohamed M. A.
Published: September 2020

Background

Gestational diabetes mellitus is any degree of glucose intolerance with onset or first recognition occurring late in second trimester and third trimester of pregnancy. It constitutes a greater impact on diabetes epidemic as it carries a major risk for developing type 2 diabetes mellitus to the mother and her fetus later in life. human leukocyte antigen (HLA)-G is a class Ib gene presents in the human major histocompatibility complex (MHC). HLA-G has an important role for mother and fetus tolerance during pregnancy, also in the pancreatic islet cells protection. This is a case-control study, measuring serum HLA-G levels by ELISA in 60 pregnant women with gestational diabetes compared with 36 normal pregnant women.

Results

HLA-G levels were significantly high in pregnant women with gestational diabetes mellitus (GDM) in contrast to women with normal pregnancy (P = 0.001).

Conclusion

Women with GDM had significantly higher levels of soluble HLA-G than women without GDM, suggesting that HLA-G molecule is among the factors for regulation and control of the immune response and the induction of tolerance. Soluble HLA-G could be considered an important follow-up investigation for all pregnant primary health care for early detection of gestational diabetes.