bluuebunny/crossref_metadata_2025_split huggingface dataset:
Trust Based Security Mechanisms for Resource-Constrained Internet of Things-A Review
Authors: Prathapchandran K. , Rutravigneshwaran P. 
Published: July 2021

Abstract
The Internet of Things (IoT) defined as the assembling of real-world objects that are connected over the Internet to make human lives become well-being. The implementation and success of an IoT depend on how it’s secured. But providing security is a critical task because of various natures of IoT devices such as shared and open environment, a wide range of communication protocols, standards, self-organized, lack of central control, heterogeneity of devices, etc. To provide security solutions and mechanisms, key management, cryptographic mechanisms such as private and public-key cryptography, Intrusion Detection System (IDS), and hash functions have been used. Though it is working well, it is not suitable for lightweight IoT devices. Because of such mechanisms always demand high computational, memory, and processing. To overcome these issues, researchers have chosen trust management for providing security. In this article, some of the trust-based solutions have presented. Besides, security issues, security loopholes/attacks in various layers of IoT, security requirements, trust management in IoT, properties of trust, trust management building blocks, the role of trust management in IoT, basic trust calculation methods have presented.
The connected domination polynomial of some graph constructions
Authors: Yoosuf Rafia , Kuttipulackal Preethi 
Published: July 2021

Abstract
The connected domination polynomial of a connected graph G of order n is the polynomial

D

c

[
G
,
x
]
=

∑

i
=

γ

c

n

d

c

(
G
,
i
)

x

i

, where d

c
(G, i) is the number of connected dominating sets of G of cardinality i and γc

(G) is the connected domination number of G [5]. In this paper we find the polynomial D

c
(G, x) for some constructive graphs.
Nonexistence of Kneser solution for third order nonlinear neutral delay differential equations
Authors: Elayaraja R. , Sathish Kumar M. , Ganesan V. 
Published: July 2021

Abstract
The achieved sufficient conditions for nonexistence of so-called Kneser solutions are based on the new comparison principles, which help us decrease the problem of the wavering between the third and first-order equations. Examples are given to prove the significance of new theorems.
Optimal Control Analyze the Bulk arrival Queueing system using Estimation Theory
Authors: Kumar Bharathi Ramesh , Narayansamy Pothiraj , Bhuvaneswari Subramanian 
Published: July 2021

Abstract
In this paper, we analyze the system performance in FM/FM(k)/∞ using Estimation theory. Initially, we convert Erlang queueing system into fuzzy Erlang system, using Alpha – cut method and obtain different possible values of
α
. Finally, using Robust ranking method it’s helpful to measure the defuzzification values and analyzes the unique optimization of system performance.
Oscillatory behavior of solutions of certain third-order neutral differential equation with continuously distributed delay
Authors: Sathish Kumar M. , Ganesan V. 
Published: July 2021

AbstractThis paper concerns the oscillatory behavior of the solutions of the third-order neutral differential equation with continuously distributed delay. We prove many new sufficient conditions which ensure that every solution to be either oscillatory or converges to zero asymptotically. Examples dwelling upon the importance of our theorems are also included.
Global exponential stability analysis of anti-periodic of discontinuous BAM neural networks with time-varying delays
Authors: Radhakrishnan N. , Kodeeswaran R. , Raja R. , Maharajan C. , Stephen A. 
Published: July 2021

AbstractDiscontinuous system is playing an increasingly important role in terms of both theory and applications. In this paper, we are concerned with discontinuous BAM (bidirectional associative memory) neural networks with time-varying delays. Under the basic framework of Filippov solution, by means of differential inclusions theory, inequality technique, fundamental solution matrix of coefficients and the non-smooth analysis theory with Lyapunov-like approach, some new sufficient criteria are given to ascertain the existence and globally exponential stability of the anti-periodic solutions for the considered BAM neural networks. Simulation results of two topical numerical examples are exploited to illustrate the improvement and advantages of the established theoretical results in comparison with some existing results. Some previous known results are extended and complemented.
A Finite Source Two Commodity Inventory System with Retrial Demands and Multiple Server Vacation
Authors: Senthil Kumar P. 
Published: July 2021

Abstract
Consider a two commodity continuous review inventory system with a finite number of homogeneous sources generating demands. The maximum storage capacity for the commodity - i is S

i
(i = 1, 2). We adopt a joint reordering policy for placing orders. The lead time for the delivery of orders is assumed to have an exponential distribution. An arriving demand receives either commodity - 1 or commodity - 2 according to a Bernoulli trial. The commodities are assumed to be substitutable in the sense that during the zero stock of any commodity, the demand for that commodity can be met by the unit of the other commodity. The server goes for a vacation of an exponentially distributed duration whenever the inventory level of both commodities reaches zero. If the server finds empty stock when he returns to the system, he immediately takes another vacation. The demands that occur during stock-out period or during the server vacation period enter into the orbit of finite size. These orbiting demands retry for their demand after a random time, which is assumed to be an exponential distribution. The joint probability distribution of the inventory level and the number of demands in the orbit is obtained in the steady state case. Various system performance measures in the steady state are derived and the long-run total expected cost rate is calculated.
An approach to the study of fuzzy rough prime ideal extensions of semigroups
Authors: Subha V S , Thillaigovindan N , Chinnadurai V , Sharmila S 
Published: July 2021

Abstract
Fuzzy rough set is a pair of lower and upper approximations of fuzzy set in a fuzzy approximation space. This paper studies the extension of fuzzy rough prime and semi-prime ideals in semigroups. Then we introduce the composition theory on fuzzy rough set. Finally some new characterization of semigroups by the properties of composition on fuzzy rough ideal extension are given.
An integrated framework for knowledge based obstacle information system with image processing techniques
Authors: Vasumathy M 
Published: July 2021

Abstract
One of the most important reasons of car accidents are collisions with vehicles that are not visible to a driver. This is why driver warning systems are developed. The main threat for a driver on the highway comes from the surrounding vehicles especially when the driver is not aware of the close presence generally known as driver’s blind spot. An area in and around the vehicle that cannot be directly observed by the driver are known as blind spots. Image processing plays a vital role in this scenario to safe guard drivers from sudden obstacles and blind spots. The pre-processed sequences of images acquired using front and rear camera of a vehicle are considered to train the case base reasoning (CBR) model, which detects the presence of dangerous objects in the blind spot area. To distinguish near and far obstacles, the same CBR model is used with a specified threshold in the vehicle blind spot area. The proposed knowledge based obstacle information system obtains promising results with standard blind spot camera which can improve safety of the driver and has the potential to be applied in vehicular applications for the detection of obstacles and blind spot area.
Machine Learning Strategies for Predicting Crop Diseases
Authors: Ubalanka Vidya , Jose Anu , Viswanath Dhanya 
Published: July 2021

Abstract
Prevalence of crop diseases is a major hindrance for successful crop production. These diseases can be identified in less time and more accurate using Machine Learning (ML) strategies as compared to any manual approach. Agronomy plays a key role in anticipating crop diseases at an early stage. With the advent of computer vision, plants can be classified as diseased or healthy by extracting architectural characteristics of a leaf using various image processing techniques. Support Vector Machines (SVM) classification technique is used in distinguishing between diseased and healthy leaf from the datasets that are publicly available. SVM method exhibited high fitting and predictive precision. The proposed paper is organized in various steps such as identifying the features, extraction of features using a computer vision technique known as Scale Invariant Feature Transform (SIFT), model training and testing. Predominantly, crop diseases on a larger scale are predicted by harmonizing speed and accuracy using computer vision and machine learning strategies.
Effect of K-Factor on Capability in Power Transformers
Authors: Apryansyah Muhammad , Iwa Garniwa MK 
Published: July 2021

Abstract
Harmonic currents generated by nonlinear loads can cause overheating and premature failure of power transformers. According to IEEE Std C57.110TM - 2008, Eddy Current losses are considered proportional to the harmonic current squared multiplied by the harmonic number. This paper will discuss 2 case studies, namely: a transformer without using a harmonic filter and a transformer using a harmonic filter. This research was conducted by measuring the amount of harmonics in arc furnace customers using power quality analysis equipment for 7 days. From the research results obtained indicate that the value of the k-factor is inversely proportional to the maximum transformer capability and is directly proportional to the decrease in transformer capability. So that the transformer that is installed using a harmonic filter has a k-factor value and derating capability is smaller than the transformer without using a harmonic filter, in order not to derating capability of the transformer without using a harmonic filter or a transformer that uses a harmonic filter, it is necessary to use the K-Factor Transformer K-4.
Identifying the Impact of Noise-Levels on Mental Stress: An EEG-fNIRS Study
Authors: Alyan Emad , Saad Naufal M. , Kamel Nidal , Al-Bawri Samir Salem , Azman Zakariya Mohd , Abdul Rahman Mohammad 
Published: July 2021

Abstract
Stress is a complex response that begins when people are exposed to various stressors, including psychological and environmental factors, which are associated with negative cognitive effects. However, little is known about their interactions within the brain. This research aimed to examine the influence of low and high noise levels in the workplace on changes in brain activity in the prefrontal cortex (PFC) during stressful psychological tasks by measuring synchronized functional near-infrared spectroscopy (fNIRS) and electroencephalogram (EEG). The results showed a decreased oxygenated haemoglobin (HbO) concentrations in the right dorsolateral PFC and part of the frontopolar area when exposed to higher noise levels compared to lower levels. Results also showed a higher correlation between fNIRS-HbO and EEG-alpha power under stress conditions compared to other EEG bands. We suggest that higher levels of noise in the workplace may be directly related to increased psychological stress.
Pseudo-Differential Transconductor Circuit for a Low Supply Voltage Application
Authors: Mohd Sabari Nur Diyana Izni bt , Abu Bakar Faizah bt , Azizan Anishaziela bt , Zainol Murad Sohiful Anuar 
Published: July 2021

Abstract
This paper presents a pseudo-differential transconductor circuit. Operational Transconductance Amplifier (OTA) is a standout amongst the most functional and major circuit elements within the analog and mixed-signal circuit style. It is additionally one of the more intricate cells to plan. Due to the rising performance of new generation MOS transistors, the complexity of integrated circuit is continuously increasing with time. The reduction in component sizing is one of the main reasons for integrating millions of transistors into a single chip. There is a great demand for battery powered equipment like a laptop, wireless communication, and implantable devices. In all these devices, it is essential to maintain low power dissipation to achieve good battery life and weight. The main feature of the research is to design a pseudodifferential transconductor circuit for a low supply voltage application with the targeted gain greater than 20 dB using Mentor Graphics software. The designs are done in Pyxis Schematic and Pyxis Layout using eldo platform for simulation to simulate the functionality of the transconductor circuit. From the postlayout simulation, with supply voltage of 1.2 V, the gain of 30 dB with cut-off frequency of 398 kHz has been achieved.
Design of 2.4GHz Two Stages Cascode Class E Power Amplifier for Wireless Application
Authors: Yi Koh Siang , Murad S.A.Z , Mohyar S.N. 
Published: July 2021

Abstract
A low-power consumption internet-connected device has received considerable attention in recent years. Power amplifier (PA) is the most significant block in radio frequency (RF) transceivers because the PA consumes high power. Therefore, an efficient and low power consumption (PA) are necessary for wireless applications. This paper presents the design of 2.4 GHz two stage with cascode class E power amplifier for wireless application using CMOS 0.13-μm technology. The proposed design employed two stage topology with cascode class E configuration in order to achieve high efficiency. The simulation results show that the proposed PA delivers 35 % power added efficiency (PAE) and 22.6 dBm output power with 3.3 V power supply into a 50 Ω load.
Document Parsing Tool for Language Translation and Web Crawling using Django REST Framework
Authors: Alnavar Kruthika , Kumar R Uday , Babu C Narendra 
Published: July 2021

Abstract
There are 7.5 billion inhabitants and over 7,117 languages existing around the world, but only 20% of the people speak English. To understand the wisdom and knowledge of other cultures language translation becomes a basic need. In this paper, a computer-assisted document parsing tool is investigated. The proposed approach uses a language translator that performs translation from images eliminating the need of a human translator for images avoiding the scope for misinterpretation and misunderstanding among people of different ethnic groups. The proposed tool is also capable of performing web crawling using Django Representational State Transfer framework. Further, the proposed approach employs Python packages such as pytesseract, textblob and beautifulsoup to perform Optical Character Recognition, Translation and Extraction of Hypertext Markup Language data respectively. Experimental results of translation on four different categories of images such as Maps, Comics, Newspapers and Magazines, Scientific Publications demonstrate an accuracy of 97.2%, 93.3%, 95.82% and 98.27% respectively. By considering websites like E-commerce, Magazines, Blogs, Social Media, News and Educational sites average precision of 5.4, recall of 7.45 and F-score of 6.24 is achieved. The results reveal that the proposed system can be used as an improvement over a human translator and a data entry operator.
The Effect of Multidimensional Factors on Organizational Adoption of Enterprise Architecture: The Moderating Role of Organization Type
Authors: Ahmad Nor Azizah , Drus Sulfeeza Mohd. , Kasim Hairoladenan 
Published: July 2021

Abstract
This study explains the effects of organization type on the relationship between multidimensional factors and enterprise architecture (EA) adoption from the perspective of the organization. This study employs the Technology-Organization-Environment (TOE) framework to develop and test the model to explain EA adoption intention. Despite the importance of EA adoption in the public sector, very few empirical studies examined the key factors of EA adoption by public sector organizations and there remains a paucity of evidence on the moderating effect of organization type in the adoption of EA. This study underpinned the technology adoption model of TOE framework. A questionnaire was operationalized to measure the perceptions of Malaysian public sector organizations towards factors influencing EA adoption intention. Data collected through a survey covering 255 validated responses were analyzed using SMART-PLS tool. The results of the survey suggest that good governance, expected benefits and moderating effect have significant effects on EA adoption intention. In addition, organization type in the Malaysian public sector plays different roles on the relationships of good governance and expected benefit towards organizations’ EA adoption. Interestingly, adequate ICT infrastructure, external support and top management support were found as insignificant factors in this study. The study includes implications for academic researchers, decision-makers and practitioners to understand the influence of multidimensional factors and effectively conclude on the adoption process. The decision-makers can use the EA adoption model as a baseline for boosting EA adoption among MPS organizations.
Digital Image Recovery Based on Lifting Wavelet Transform
Authors: Taha Taha Basheer , Taha Dujan B. , Ngadiran Ruzelita , Ehkhan Phaklen 
Published: July 2021

Abstract
Recently, with the wide distribution of digital media, the need for authenticating digital images was increased. Therefore, many image tamper detection and recovery algorithms were introduced in literature to detect malicious modifications and retrieve the original images. The process of detection and recovery, however, used to have complex operation which requires long processing time. In this paper, a simplified image recovery algorithm is presented by using lifting wavelet transform. In the proposed method, the approximation band is hidden inside the bits of the original image and to be retrieved without relying on source image. For images with hidden data, the average PSNR and SSIM values were 31.22 and 0.977 respectively, and images were successfully retrieved after block attack.
Design and Simulation of a Small Power Two-Bit MC Circuit via Full Adder Logic
Authors: Bhattacharjee Soumik , Vyakaranam Aparna , Svpk Devu Satya , Shameem SSS , Sulo Rafida , Zainuddin Ahmad Anwar 
Published: July 2021

Abstract
In Very Large-Scale Integration (VLSI) systems, a magnitude comparator (MC) is a component of Arithmetic Logic Unit (ALU) used to make binary decisions. Recent technologies demand the use of power-efficient methodologies as well as techniques that require a lesser number of transistors. In this paper, a magnitude comparator is developed using full adder design logic. Full adders are basic components of the ALU which is the logical and arithmetical unit of the microprocessors and Digital Signal Processing (DSP). This design consumes less power and area when compared to other logic styles in the literature. The proposed comparator has been designed using DSCH 3.5 and simulations are done on Microwind 3.5 via 0.12 μ technologies. This comparator shows a power consumption of 31.746μW using 36 transistors. The proposed design exhibits a full adder logic-based comparator with less power consumption and transistor count as compared to those in recent literature.
Comparative Study of Energy Storage Systems (ESSs)
Authors: Asri L I M , Ariffin W N S F W , Zain A S M , Nordin J , Saad N S 
Published: July 2021

AbstractRenewable energy (RE) resources have shown impressive growth globally, as these sources do not provide enough amount that is readily adaptable to consumer needs, it can rarely allow an immediate response to demand. However, intermittency in RE supply (RES) sources, combined with fluctuating demand shifts over time, has caused a high risk of sustaining system reliability to provide customers with sufficient supply. The excess energy produced by RESs can be stored in a myriad of ways and used later during shortages or intermittent periods. This study was carried out to understand how to provide energy storage to create a future built environment where RE systems play an essential role. There are different types of a storage system with different characteristic, parameters, and costs. This paper highlights the chronology, classification, characteristic, comparison, and assessment of ESSs and energy storage systems deployment.
Smart Electronic Switching (ON/OFF) System Based on Real-time Detection of Hand Location in the Video Frames
Authors: Taban Duaa A. , Al-Zuky Ali , Kafi Shaymaa H. , Al-Saleh Anwar H. , Mohamad Haidar J. 
Published: July 2021

Abstract
Human looking forward to living in a modern and comfortable environment like smart houses. In this study, an effective user-friendly smart home prototype designed with low cost. The prototype contains eight of Light Emitting Diode (LED) considered as home appliances and controlled in real-time using eight suggested hand cases. The hand cases have different position regarded to head and shoulder levels. The hand position is detected using a new suggested algorithm programmed in Matlab software. Viola-Jones method used to detect hand in a complex background (hand with a different background) by training computer using positive (hand) and negative (non-hand) image datasets. To make computer training faster and accurate, a new idea depends on a skin detection used before computer training to determine the location and size of all positive images automatically. The LEDs in prototype switched ON/OFF using the suggested hand cases in a fast time. Where the response time of LEDs to hand cases was 0.43 second.
Synthesis and characterization of metastable phases of SnO and Sn3O4 thin films for solar cells applications
Authors: Fadaam Suha. A. , Ali Hiba M. , Salih Ayad.Ahmed. , Obaid Maithm.A. , Sabeeh Ali Ali , Habubi Nadir F. 
Published: July 2021

Abstract
Meta stable phase of SnO as stoichiometric compound is deposited utilizing thermal evaporation technique under high vacuum onto glass and p-type silicon. These films are subjected to thermal treatment under oxygen for different temperatures (150,350 and 550 °C ). The Sn metal transformed to SnO at 350 oC, which was clearly seen via XRD measurements, SnO was transformed to a nonstoichiometric phase at 550 oC. AFM was used to obtain topography of the deposited films. The grains are combined compactly to form ridges and clusters along the surface of the SnO and Sn3O3 films. Films were transparent in the visible area and the values of the optical band gap for (150,350 and 550 °C ) 3.1, 2.7and 2.4 eV respectively. AFM shows that the granular size of all films increases by increasing the oxidation temperature. The PL emission results were matched the results of the optical energy gap. The solar parameters for the three phases are studied to obtain the efficiency, which were found to be 2%, 3.7%,5.1
Large-Maximal submodules
Authors: Abduljaleel Amira A. , Yaseen Sahira M. 
Published: July 2021

AbstractThe goal of this research is to introduce the concept of Large-maximal submodule, also we will consider some properties of it, such that a proper submoduleNof an R-moduleMis said to be Large-maximal (L-maximal) submodule ofMif there exists a submoduleKofMsuch thatN < K ≤ M,thenKis essential submodule ofM (K ≤eM).