bluuebunny/crossref_metadata_2025_split huggingface dataset:
Solar assisted cooling rule in indoor air quality
Authors: Baniyounes Ali M. , Ghadi Yazeed Y. 
Published: June 2020

<p>Indoor air quality as always is the centre of attention for researchers, architect developers and public health officials. As every-one know. The human exposure to a variety of indoor pollutants and the high cost of energy are the motivation for these kinds of studies. Fungus and mould growth has always been a problem in subtropical climate areas due to the high temperature and high humidity. Generally in institutional buildings, most of the internal heat load is generated by human body and thermal comfort is achieved with extensive usage of recycled air and air conditioning. The main considerations in any air conditioning system economisers are based on the usage of recycled air and air ventilation. The current practice in an institutional building cooling system under subtropical climate is to curb the mould issue by overcooling large recirculation airflow to remove the moisture content from the air, which is considered as an expensive practice. The use of a solar desiccant cooling system to reduce moisture from the air and to improve indoor air quality is found to be economical, environmental friendly and readily achievable in the tropics. This technology is the future alternative to the conventional vapour compression cooling system to maintain human thermal comfort conditions and enhance indoor air quality. Solar desiccant cooling systems are also environmentally friendly and energy efficient. This paper presents review on a solar desiccant cooling system and its effect on indoor air quality. It first introduces the issue of air moisture, mould growth and indoor air quality and then the development and application of thermally activated desiccant cooling technologies.</p>
A new approach to image classification based on a deep multiclass AdaBoosting ensemble
Authors: Asil Hasan , Bagherzadeh Jamshid 
Published: June 2020

In recent years, deep learning methods have been developed in order to solve the problems. These methods were effective in solving complex problems. Convolution is one of the learning methods. This method is applied in classifying and processing of images as well. Hybrid methods are another multi-component machine learning method. These methods are categorized into independent and dependent types. Ada-Boosting algorithm is one of these methods. Today, the classification of images has many applications. So far, several algorithms have been presented for binary and multi-class classification. Most of the above-mentioned methods have a high dependence on the data. The present study intends to use a combination of deep learning methods and associated hybrid methods to classify the images. It is presumed that this method is able to reduce the error rate in images classification. The proposed algorithm consists of the Ada-Boosting hybrid method and bi-layer convolutional learning method. The proposed method was analyzed after it was implemented on a multi-class Mnist data set and displayed the result of the error rate reduction. The results of this study indicate that the error rate of the proposed method is less than Ada-Boosting and convolution methods. Also, the network has more stability compared to
the other methods.
Harvesting in electric vehicles: combining multiple power tracking and fuel-cells
Authors: Parada-Salado Juan-Gerardo , Gaona-Cárdenas Luis-Fernando , Rodríguez-Licea Martín-Antonio , Pérez-Pinal Francisco-Javier 
Published: June 2020

Exploitation of green energy sources is essential to diminish the deterioration of our environment. The energy harvesting, represents an alternative to achieve greater range in electric and hybrid vehicles. An energy management strategy (EMS) must be optimized to obtain the best beneﬁts in such vehicles, which is not a trivial task. If harvesting or energy recovery devices are added, the EMS becomes a dual-purpose algorithm: minimizing fuel consumption and maximizing energy harvest through maximum
power point tracking (MPPT) controllers. Known studies consider separate EMS, one for traction and another for regenerative braking, without considering harvest devices such as solar panels, regenerative suspension, thermal generators, among others. Furthermore, the electronic power converters used, are not designed to handle such unequal power levels. In this article, an electronic platform to include multiple energy harvesting devices in a fuel-cell hybrid electric vehicle, was presented together with a multiple MPPT-EMS. The EMS is easily implementable, and considers quasiconstant cell energy extraction and ﬁltering of current transients to the battery bank ensuring the longevity of the devices. A new mathematical model of the platform, a closed loop stability analysis, and numerical and Hardware-in-the-Loop (HIL) validations were presented. Some experimental validation results were also provided.
An optimized method towards formal verification of mixed signals using differential fed neural network over FFNN
Authors: D.S. Vidya , Ramachandra Manjunath 
Published: June 2020

<span lang="EN-US">Today, the semiconductor industries are rapidly usinganalog and mixed signals to achieve cost-effective solutions on a System on Chip (SoC) design. The SoC device is a part of analog, digital and essential mixed-signal models/circuits merged on a semiconductor device, which provides the platform to build modern retail/consumer electronics appliances with smart technology. In order to evaluate the mixed signals, the conventional approaches are not effective with respect to its performance, time and manufacturing cost. Thus, the recent researches were much interested in formal verification technique as it provides the evidence of conscious algorithms in a system. The demand for formal verification in the SoC designs in the context of software and hardware platform is high because of its cost and accuracy. Thus, the paper introduces atechnique of formal verification for mixed signals by using training models of the Differential fed neural network (DFNN) over feedforward neural network (FFNN). The formal verification is performed through equivalence checking by using recently adopted designs as reference designs. The outcomes of the verification techniques suggests that DFNN based technique improves the training accuracy and optimizes the hardware resources like area, power than the FFNN based technique.</span>
Measurement of low frequency mechanical vibrations based on an inverted magnetic pendulum
Authors: V. Awad Susana , Orozco Joaquin F , Hoyos Fredy E 
Published: June 2020

<span>In this paper is presented the mathematical model, design and construction of a prototype of a vibration frequency meter in an adjustable range of 2 Hz to 30 Hz; The experimental results and their analysis are also presented, making a comparative evaluation with the theoretical model. The device is based on the principle of resonance applied in an inverted magnetic pendulum whose natural frequency can be modified by variations of physical parameters. The oscillation of the pendulum is recorded detecting variations in the magnetic field using hall effect sensors; the data recorded with a microprocessor is analyzed and the results are simultaneously plotted in a computer interface. The data obtained were processed to be plotted in the frequency domain, facilitating its analysis. It was proved that the prototype can be used as a frequency meter and that the adjustable character of the device works according to the mathematical model. Finally, The effect of the friction force was studied, it was concluded that the friction force affects the measurement after a considerable period of time of oscillation, but not in the first moments.</span>
Detection of electrocardiogram QRS complex based on modified adaptive threshold
Authors: Hussein Ehab AbdulRazzaq , Hassooni Ali Shaban , Al-Libawy Hilal 
Published: June 2020

<p>It is essential for medical diagnoses to analyze Electrocardiogram (ECG signal). The core of this analysis is to detect the QRS complex. A modified approach is suggested in this work for QRS detection of ECG signals using existing database of arrhythmias. The proposed approach starts with the same steps of previous approaches by filtering the ECG. The filtered signal is then fed to a differentiator to enhance the signal. The modified adaptive threshold method which is suggested in this work, is used to detect QRS complex. This method uses a new approach for adapting threshold level, which is based on statistical analysis of the signal. Forty-eight records from an existing arrhythmia database have been tested using the modified method. The result of the proposed method shows the high performance metrics with sensitivity of 99.62% and a positive predictivity of 99.88% for QRS complex detection.</p>
Predictive torque control of electric vehicle
Authors: Abdelkoui Mohammed El Amin , Hazzab Abdeldjebar 
Published: June 2020

<span lang="EN-US">The following article represents the development of a traction system of an electrical vehicle (EV) that consist of two Three-phase squirel-cage induction motors (IM) that permit the drive of the two front driving wheels. The two motors are controlled using the Predictive Torque Control (PTC) method; A technique based on the next step prediction and evaluation of the electromagnetic torque and stator flux In a cost function in order to determinate the inverter switching vector that minimize the error between references and predicted values. PTC is what we tried to underline in this paper, so we explain below the principle of the method; and the system mathematical description is provided. An electronic differential is applied on the system to control independently the speed of the two wheels at different operating conditions in order to characterize the driving wheel system behavior, the robustness in steady state and in transient state.</span>
Finding a suitable threshold value for an iris-based authentication system
Authors: Wangkeeree Narongrit , Boonkrong Sirapat 
Published: June 2020

<span>Authentication is the first line of defense of any information technology systems. One of the popular methods used today is biometric, and iris authentication is gaining popularity. However, the threshold value is deemed to be secure and appropriate has not been thoroughly studied. Threshold is a value that defines the acceptable amount of the correct bits of the image before securely passing the authentication process. Therefore, the main aim of this research was to find a secure and suitable threshold value used in iris authentication system, where iris localization was done by using Circle Hough Transform technique. Iris image databases v.4 from the Chinese Academy of Sciences Institute of Automatic (CASIA) were used in this research. The way to find the appropriate threshold was to test for the right balance of the GAR, FRR and FAR values when trying to verify the person’s identity. The results of the test revealed that the appropriate threshold had the value of 72.9246 percent of all the available bits of the iris image. Both had a high GAR and very low FAR and FRR values. It can be concluded that the obtained threshold value was suitable and secure.</span>
UWB elliptical patch monopole antenna with dual-band notched characteristics
Authors: Majeed A H , Sayidmarie K H 
Published: June 2020

<p class="Default">In this paper, a new approach to the design of an UWB monopole antenna with dual band-notched characteristics is presented. The antenna has the form of an elliptical monopole over a ground plane having an elliptical slot to achieve the UWB. The dual-band notch function is created by inserting a U-shaped and a C-shaped slots on the radiating patch, thus no extra size is needed. The proposed antenna shows a good omnidirectional radiation pattern across the band from 3.2 to more than 14 GHz. The dual band-rejection is for 4.88-5.79GHz centered at 5.4GHz and 7.21-8.46 GHz centered at 7.8 GHz. The antenna prototype using the FR-4 substrate with ε<sub>r</sub>=4.3 has a compact size of 25mm×25 mm ×1.45mm. The fabricated prototype showed experimental results comparable to those obtained from the simulations.</p>
Speech to text conversion and summarization for effective understanding and documentation
Authors: A Vinnarasu , Jose Deepa V 
Published: June 2020

<p class="western" style="margin-top: 0.21cm; margin-bottom: 0cm;" align="justify"><span>Speech, is the most powerful way of communication with which human beings express their thoughts and feelings through different languages. The features of speech differs with each language. However, even while communicating in the same language, the pace and the dialect varies with each person. This creates difficulty in understanding the conveyed message for some people. Sometimes lengthy speeches are also quite difficult to follow due to reasons such as different pronunciation, pace and so on. Speech recognition which is an inter disciplinary field of computational linguistics aids in developing technologies that empowers the recognition and translation of speech into text. Text summarization extracts the utmost important information from a source which is a text and provides the adequate summary of the same. The research work presented in this paper describes an easy and effective method for speech recognition. The speech is converted to the corresponding text and produces summarized text. This has various applications like lecture notes creation, summarizing catalogues for lengthy documents and so on. Extensive experimentation is performed to validate the efficiency of the proposed method</span></p>
Computational Sinc-scheme for extracting analytical solution for the model Kuramoto-Sivashinsky equation
Authors: Al-Khaled Kamel , Abu-Irwaq Issam 
Published: June 2020

The present article is designed to supply two different numerical<br />solutions for solving Kuramoto-Sivashinsky equation. We have made<br />an attempt to develop a numerical solution via the use of<br />Sinc-Galerkin method for Kuramoto-Sivashinsky equation, Sinc<br />approximations to both derivatives and indefinite integrals reduce<br />the solution to an explicit system of algebraic equations. The fixed<br />point theory is used to prove the convergence of the proposed<br />methods. For comparison purposes, a combination of a Crank-Nicolson<br />formula in the time direction, with the Sinc-collocation in the<br />space direction is presented, where the derivatives in the space<br />variable are replaced by the necessary matrices to produce a system<br />of algebraic equations. In addition, we present numerical examples<br />and comparisons to support the validity of these proposed<br />methods.
An algorithm for IoT based vehicle verification system using RFID
Authors: Samuel Alen Joseph , Sebastian Shoney 
Published: June 2020

The verification of vehicle documents is an important role of transport department which is rising day by day due to the mass registration of the vehicles. An automated vehicle verification system can improve the efficiency of this process. In this paper, we propose an IOT based vehicle verification system using RFID technology. As a result, the vehicle checking which is done now manually can be replaced by automation. There is a loss of a significant amount of time when the normal vehicle checking is done manually. The proposed system will make this process automated. The present verification process is using inductive loops that are placed in a roadbed for detecting vehicles as they pass through the loop of the magnetic field. Similarly, the sensing devices spread along the road can detect passing vehicles through the Bluetooth mechanism. The fixed audio detection devices that can be used to identify the type of vehicles on the road. Other measurements are fixed cameras installed in specific points of roads for categorising the vehicles. But all these mechanisms cannot verify the documents and certificates of the vehicles. In our work, we have suggested an algorithm using RFID technology to automate the documentation verification process of the vehicles like Pollution, Insurance, Rc book etc with the help of RFID reader placed at road checking areas. This documents will be updated by the motor vehicle department at specific periods.
The best quintic Chebyshev approximation of circular arcs of order ten
Authors: Rababah Abedallah M. 
Published: June 2020

<p>Mathematically, circles are represented by trigonometric parametric equations and implicit equations. Both forms are not proper for computer applications and CAD systems. In this paper, a quintic polynomial approximation for a circular arc is presented. This approximation is set so that the error function is of degree $10$ rather than $6$; the Chebyshev error function equioscillates $11$ times rather than $7$; the approximation order is $10$ rather than $6$. The method approximates more than the full circle with Chebyshev uniform error of $1/2^{9}$. The examples show the competence and simplicity of the proposed approximation, and that it can not be improved.</p>
A cost-effective 2-tier security paradigm to safeguard cloud data with faster authentication
Authors: R.S Veena , Pujeri Ramachandra V. , M Indiramma 
Published: June 2020

The recent technological advancement has taken cloud computing (CC) infrastructure to a significant level where the increasing level of research interest laid upon cost-effective storage management. Owing to the potential distributed and pervasive storage facility, it lacks efficiency towards fully preserving the integrity of user data attributes. Thereby, the collaborative sharing of user data leads to a situation which opens up various forms of security loop-holes. In the past various forms of security protocols are witnessed which have attempted to solve this similar issue with cryptographic solutions but at the same time lacks sustainability and robustness from a computational perspective. Thereby, the study introduces a 2-tier framework which offers higher-degree of access control along with Virtual Machine (VM) storage security. The study basically optimizes the performance of the model by speeding up the authentication process. The performance validation of the system has been done with respect to conventional encryption standards. The outcome obtained demonstrate that the proposed solution outperforms the existing security standards in terms of processing time, time to generate a secret key and key size for encryption.
Relationship Between Time‐Dependent Proteinuria and Risk of Stroke in Population With Different Glucose Tolerance Status
Authors: Wang Anxin , Zhang Jia , Li Jingjing , Li Haibin , Zuo Yingting , Lv Wei , Chen Shuohua , Li Junjuan , Meng Xia , Wu Shouling , Zhao Xingquan , Wang Yongjun 
Published: June 2020

Background
Proteinuria often changes and is known as a “time‐dependent exposure.” The effect of time‐dependent proteinuria on the risk of future stroke remains unclear. Proteinuria is often detected in patients with diabetes mellitus. The present study was designed to evaluate the association between time‐dependent proteinuria and the risk of stroke in a patient cohort with different glucose tolerance status.

Methods and Results
A total of 82 938 participants, who were free of myocardial infarction or stroke and underwent fasting blood glucose and urinary protein measurements at baseline in the Kailuan study, were enrolled. Proteinuria was determined using urine dipstick tests at baseline and subsequent follow‐ups. Time‐dependent proteinuria was defined as the status of urine protein updated through the follow‐up examinations, separately. Time‐dependent Cox regression models were used to analyze the relationship between time‐dependent proteinuria and the risk of stroke. During a median follow‐up of 8.37 years, 2538 participants developed stroke. After adjusting for confounding factors, the hazard ratio (95% CI) for stroke in time‐dependent proteinuria among all participants, and the normoglycemia, prediabetes, and diabetes mellitus populations were 1.68 (1.49–1.89), 1.73 (1.47–2.05), 2.15 (1.70–2.72), and 1.30 (1.03–1.65), respectively. There were interaction effects in patients with normoglycemia and prediabetes compared with those with diabetes mellitus. Findings were similar for ischemic and hemorrhagic strokes and were confirmed in sensitivity analyses.

Conclusions
Time‐dependent proteinuria is an independent risk factor of stroke, especially in the normoglycemia and prediabetes populations.
Reflections on the Scholarly Imaginations of Good and Evil in the Book of Esther
Authors: Lee Lydia 
Published: June 2020

Abstract
The present article seeks to describe, analyze, and evaluate the modern scholarly attempts to grapple with the moral issues about good and evil in the Hebrew Esther story. The first part of the article examines the anti-Semitic sentiments looming behind the pre-World War II European, especially the Protestant, commentators’ ethics assessments of the book of Esther and its Jewish characters, before pointing out a blind spot in these assessments. The second part of the article offers a systematic analysis of the gradual change of attitude induced mainly by the Jewish scholars in the aftermath of the Second World War. Lastly, the paper turns the spotlight on the Esther studies conducted by recent feminist and other marginalized biblical scholars. Attempts are made to demonstrate how their works, coming from different social contexts, enrich the academic discussions about good and evil in the book of Esther.
A Tale of Two Purims: Food-Identity Ideology and Purim Reception from the Late Persian to the Byzantine Christian Era
Authors: Miles Johnny 
Published: June 2020

Abstract
Royal banquets in the ancient world typically reinforced a particular food-identity ideology. mt Esther reveals an identity of excessiveness and self-indulgence to Persian banquets that easily lent to Grecian stereotypes of Persians also appropriated by Hellenistic Jewish writers. By contrast, Mordecai emended Jewish Purim with a food-identity ideology of moderation and compassion for its inscribed memory. This article traces the reception history of Purim from the late Persian to the Christian Roman and Byzantine eras to reveal in effect two Purims. Throughout these eras, the incorporated memory of Purim with its incidences of drunkenness and gluttony punctuated by occasional outbursts of violence principally, if not wholly, neglected Purim’s inscribed memory, despite efforts at emendation, inauguration of different festivals among Alexandrian Jews, and rabbinic dicta of “food gifts to the poor” as an act of tzedakah.
Sympathy for a Gentile King: Nebuchadnezzar, Exile, and Mortality in the Book of Daniel
Authors: Waller Daniel James 
Published: June 2020

Abstract
Nebuchadnezzar II sacked Jerusalem and destroyed its temple. Yet he emerges in Daniel 1-4 as a compelling and sometimes sympathetic hero-villain. Drawing upon the concept of the story-collection, this article considers the implications of this genre for character formation, examines the further thematic means by which Nebuchadnezzar’s sympathetic characterization is generated in the book of Daniel, and explains his character in terms that make his often contradictory nature understandable across the text of the book. This article argues that Nebuchadnezzar’s dreams reflect deep-seated anxieties about his own mortality and relates these anxieties about death and time to Daniel’s broader themes of time, mortality, and exile. It suggests an analogy between the death of the self and the death of one’s state, and suggests that Nebuchadnezzar’s portrayal in Daniel has a role to play in our understanding of Daniel as a reflection upon life in exile.