bluuebunny/crossref_metadata_2025 huggingface dataset:
The Anatomical and Physiological Analysis of Thresholds in Domestic Architecture Case Example: Chandigarh
Authors: Prab Asees , Bansal Kanika
Published: April 2022

Thresholds impart dynamism, transitional experience, transparency, privacy, thermal control, and social engagement between the inside and the outside. The paper postulates upon this physiological (operational) identity of threshold spaces in modern domestic architecture in Chandigarh, working in tandem with their anatomical (elemental) composition, taking into consideration the limitations of climatic conditions, notions of formalism and building legislations. The survey of the specified typologies reveals that the dwellings with larger plot sizes, though weak in social engagement, have more scope for an elaborate transitional experience, in contrast to smaller units, where the progression from the inside to the outside is sudden and unceremonious. The paper concludes with a model that establishes the dependency of the physiological parameters on the anatomical elements of threshold spaces. Resultantly, the research strives to identify tools of analysis of thresholds that can be eventually applied to larger urban scale, which could be the subject of future investigations.
Building the Database on Software for Analyzing the Sewing Process of Knitted Products Applied in Industrial Production
Authors: Phan Thanh Thao , Pham Thi Le My , Phan Duy-Nam
Published: April 2022

Industry 4.0 significantly has changed the operating processes of traditional businesses. Technology, digital, and artificial intelligence (AI) applications have been put into practice to increase the effectiveness of corporate governance around the world. To be able to firmly integrate into the regional and global economy, general Vietnamese businesses and garment businesses, in particular, need to improve their management capacity and optimize both quantity and quality of products. Towards this goal, this paper presents the results of research on building a database on software to analyze the sewing process applied to industrial production for two groups of knitted products, namely polo shirt and t-shirt, the software uses Java programming language on Google's tool. The content of the topic has practical significance, aiming for industry, innovation, and infrastructure.
Formulation Development and Evaluation of Taste Masked Anthelmintics Chewable Tablets by Using Fluid Bed Processor Technique
Authors: Antil Anita , Singh Sukhbir , Sharma Naleem , Sharma Rahul
Published: April 2022

Human helminthic infections are prevalent and have serious world health consequences. Praziquantel is frequently recommended anthelmintic therapy provided in tablet form for the oral treatment of schistosome infections. The goal of this study is to create and analyze a patient-friendly flavor masked anthelmintics chewable tablet of Praziquantel using Eudragit® EPO using a "granules coating technology" using a Fluid Bed Processor GPCG 1.1. (Top Spray). This strategy is better as compared to coating of Praziquantel granules with Eudragit EPO in Rapid Mixer Granulator. Due to its limited water solubility, the formulation disintegrates and dissolves slowly at high pH. Drug release was >98% in 60 min. The key excipient in chewable tablets incorporate flavor enhancing agent and sweetening agent. By using wet granulation process the tablet are prepared. Chewable tablets are evaluated by chemical and physical evaluation methods. Physical methods and chemical method include appearance, hardness, friability, disintegration, dissolution, drug content, dosage uniformity, accelerated stability studies, and sensory evaluation.
Nutrigenomics in Lifestyle Disorders: A Review
Authors: Binoy Ashly , Bhat Dhrithi , Bhat Jahnavi G , Babu M Sarvesha , Reddy Manjunatha , Manokaran Sumathra
Published: April 2022

In the era of increasing unhealthy dietary and lifestyle habits, maintaining a healthy diet is really important to prevent a broad spectrum of diseases. Lifestyle diseases occur due to certain unhealthy daily habits (smoking, unhealthy diet, and physical inactivity) that lead to inappropriate relationships with the environment. The consumption of food in an improper quantity and lacking in quality can have adverse effects on an individual’s health. Diet can bring about certain changes in genes which can be studied in the areas of nutrigenomics, nutrigenetics, epigenetics, epigenomics, and transcriptomics. This can help us understand how genetic makeup responds to nutrition in terms of transcription and translation processes. In this review, the effect of nutrition on gene expressions related to lifestyle disorders such as metabolic syndrome, CVD, and asthma is discussed.
Investigation of Diesel Engine Combustion Characteristics for Varying Nozzle Depth at Different Spray Angles
Authors: Singh Rahul Kumar
Published: April 2022

The demand for petroleum-derived fuels is increasing every day despite their speculations about the exhaustion of petroleum fuel. Petroleum-derived fuels are classified as a suspect element for humans due to their known primary adverse effects on the environment. The concern is that the demand for petroleum fuel will rise along with the market price. Researchers around the world focus on reducing the harmful effects of petroleum fuel or finding some other substitute for petroleum fuels. A Kirloskar single cylinder diesel engine (model TV-1) was selected for simulation using commercially available AVL FIRE software. The published articles indicate the operating conditions and limitations of the single cylinder diesel engine. The geometry of the hemispherical cup piston is generated and networked in software, then the search is processed by selecting three different spray angles, such as 120o, 140o, and 160o. The standard spray angle is 120o. In addition, four nozzle depths are included in the search to analyze the effect of nozzle depth on combustion parameters. The nozzles are available in four depths: 0.5 mm, 1 mm, 1.5 mm, and 2 mm. while the nozzle depth is 1 mm standard nozzle depth. Four nozzle depths with spray angles of 120°, 140°, and 160° are examined. The results returned the combustion parameter and depend on the spray angle and the depth of the nozzle. To obtain an adequate combustion result from the above scenario, some trade-offs in terms of combustion parameters need to be considered.
An Analytical Study of Architecture Design Studios with Respect to Orientation and Facade Treatment
Authors: Kumar Ambuj , Kassa Melak , Boity Antony Kumar , Rana Aarti , Behera Shruti
Published: April 2022

Building orientation is one of the most important design tools that can have a significant impact on the control of solar radiation and wind flow into a building. A country like Ethiopia has a predominantly hot and dry climate and hence receives an ample amount of sunlight throughout the year. The buildings need to be oriented to reduce the solar heat gain on the buildings and maximize the natural ventilation. The paper investigates the effect of orientation and facade treatment of the design studios on the thermal performance of students’ mental states and physical health. The design studio building is oriented in the east-west direction and located in Nekemte Campus of Wollega University, selected as the study area. The building orientation, facade treatment, window to wall ratio, and window size and level were studied and analyzed. The results from the data analysis clearly show that the east-west facing windows helps in thermal heat gain in the building, thereby increasing the inside temperature, compared to the windows oriented in north-south directions for both ventilated and unventilated rooms.
Sintering Temperature Driven Structural, Dielectric, Ferroelectric, and Piezoelectric Properties of 0.5Ba(Zr0.2Ti0.8)O3-0.5(Ba0.7Ca0.3)TiO3 Lead-Free Composites
Authors: Sharma Sarita , Shah Jyoti , Kotnala Ravinser Kumar , Negi Nainjeet Singh
Published: April 2022

Lead-free 0.5Ba(Zr0.2Ti0.8)O3-0.5(Ba0.7Ca0.3)TiO3 composites have been synthesized via sol-gel chemical route. We have systematically investigated the influence of sintering temperature on the structural and electrical properties of the BZT-BCT composites. The 0.5Ba(Zr0.2Ti0.8)O3-0.5(Ba0.7Ca0.3)TiO3 composites were prepared by combining Ba(Zr0.2Ti0.8)O3 (BZT) and (Ba0.7Ca0.3)TiO3 (BCT) powders and sintered at different temperatures 900-14000C. The electrical properties of BZT-BCT composites improve with increasing sintering temperature. The composites sintered at 1300 and 14000C exhibit enhanced ferroelectric properties with spontaneous polarization Ps ~ 11.2 μC/cm2 and 8.66 μC/cm2 respectively. The dielectric and piezoelectric properties of BZT-BCT composites also improve with increasing sintering temperature. The dielectric constant value εʹ ~ 2938, tan δ ~ 0.016 and piezoelectric co-efficient d33 ~ 278 pC/N were measured for BZT-BCT composite sintered at 14000C while observing a considerably high transition temperature of Tc ~ 1200C. The observed results are discussed in terms of structural and microstructural analysis as a function of sintering temperature.
Secured Multiparty Access Control Model for Online Social Networking Using Machine Learning
Authors: Nakerekanti Madhu , Narsimha Dr. V B
Published: April 2022

In recent years, Online Social Networks (OSNs) have registered significant growth. They have become part of daily routine life, a phenomenon that received the serious attention of academic, technological, and social research communities. Many OSNs allow its users to post multimedia content, communicate in various ways, and share many aspects of their life in addition to building a virtual network of social relationships. While sharing data to the multiple users, there is no mechanism in place to enforce privacy and security issues in OSNs. Users in OSNs reveal personal information such as their profiles photos, relationship status, phone numbers, dates of birth, and other social activities without being aware of the risks and thefts which may occur. Therefore, this paper aims to capture the concepts of multiparty authorization and policy enforcement in an access control model. The paper deliberates broad-spectrum issues of the multi-users such as privacy and security issues, data integrity, scalability, data authentication, and so on, while sending the data. To overcome such a situation, we need to develop an innovative framework, i.e. Novel Adaptive Privacy Policy Prediction (NA3P), for multi-users access control policies using machine learning classification techniques to provide security and policy prediction for shared content.
Social Media Networking: As Facilitator of Acculturation
Authors: Kumari Savita , Jindal Priya , Chand Pawan Kumar
Published: April 2022

Globalization has made the whole world a single market for the consumer as well as for employees in terms of employment opportunities. This phenomenon, resulted in acculturation problems for global enterprises. The tension/stress of cultural adjustment at a new workplace with their own culture results in adverse effects the employee’s mental and physical health. Organizations are trying to utilize social media networking as a solution to this challenge and even employees it using as a mean to learn the culture of the organization. With the objective to explore the impact of social media networking on the acculturation of employees, the sample of 735 employees of various IT companies using the social networking platform of their organization taken, and data collected through a standardized questionnaire of 22 items, and analyzed using EFA and OLS techniques. The study resulted in a positive significant impact of social media on the acculturation of employees, however, there is a difference in employee behavior towards social media on the geographical basis.
Harmonic Mitigation in VFD Controlled Chiller Compressor Using AC Line Reactor and DC Link Choke Combination
Authors: Kumar Sumit , Chauhan Madhur , Singh Abinash , Singh Dhawan
Published: April 2022

With the goals of a better power factor and reduction in energy use, variable frequency drives (VFDs) have been standardized in various industrial applications including Heating, Ventilation, and Air-conditioning (HVAC) systems. However, key issues related to the deterioration in the power quality associated parameters (voltage harmonic distortion and current harmonic distortion) due to the growing number of VFDs demand a wholesome analysis of the problems faced by the users. In this present work, an analysis has been performed to investigate the potential impact of using alternating current (AC) line reactor and direct current (DC) link choke combination on harmonic mitigation in a VFD driven water-cooled centrifugal chiller compressor. Using a combination of AC line reactor and DC link choke as one of the low cost solutions in harmonic mitigation of a VFD driven load in HVAC systems can be decided based on the investigation done in this research work.
A Brief Review on the Use of Ferrite in Catalysis
Authors: Rana Shikha , Singh Mahavir
Published: April 2022

The developing eminently capable nanocatalyst is a befitting need of catalytic industries. This brief review provides knowledge about the recent advances in use of nanoferrite composites in various catalytic processes like immobilization of enzymes, degradation of harmful contaminants in waste water, synthesis of biofuel. Easy deactivation, less recovery, and low stability like limitations of traditional catalysts are transcended by peculiar nanocatalysts. With latest advancement in synthesis, functionalization and designing techniques the preparation process of efficient ferrite nanocatalyst hybrids is optimized. The various catalytic applications of spinel ferrites are due to facile recovery, stability, and activity provided by ferrites in catalytic processes. In the present article, the behavior of ferrite as biocatalyst, Fenton catalyst and photocatalyst have been briefly reviewed and summarized.
Energy-Saving Investigation of Entrainer Enhanced Vacuum Reactive Distillation for Ethyl Acetate Production
Authors: Patil Ganesh N , Gnanasundaram Nirmala
Published: April 2022

An entrainer-assisted vacuum reactive distillation simulation is presented to synthesise high-purity ethyl acetate from acetic acid and ethanol. This process has the advantages of both heterogeneous azeotropic distillation and reactive distillation. Cyclohexane is used as an entrainer to break the water-ethanol azeotrope and extract water from the reactive part more efficiently. The feasibility of cyclohexane is evaluated using the residue curve map technique. The influence of various process parameters, such as reflux ratio, distillate to feed ratio, feed location of reactants and number of reactive stages on reboiler duty requirement, total annual cost, and purity of the product, were investigated. Comparison of EIARD and EIVRD configurations showed that EIVRD configuration showed 24.19% savings in reboiler duty per kg of product, 20% saving in total operating cost, and 6.59% saving in TAC.
Financial Literacy and Financial Inclusion: A Systematic Literature Review
Authors: Kaur Amanjot , Verma Rajit
Published: April 2022

Financial literacy has gained tremendous importance in the last couple of decades with financial services becoming as fastest growing segment and driving economies. The government and institution have started focusing on financial literacy and financial inclusion to target inclusive economic growth, thus leading to a large body of research on the subject. The purpose of this paper is to review all aspects of financial literacy and its evolution along with financial inclusion. The study was done by doing a keyword search along with detailed cluster review of 70 research papers. The main finding of this analysis is that financial literacy efforts and studies needs to be done along with impact assessment on financial inclusion. Both these metrics have to be studies together in order to achieve a comprehensive analysis. The study can be used as a reference for researchers and policy makers to conduct further studies and review current efforts.
Analysis of Effects of PTEN-Mediated TGF-β/Smad2 Pathway on Osteogenic Differentiation in Osteoporotic Tibial Fracture Rats and Bone Marrow Mesenchymal Stem Cell under Tension
Authors: Ling Shiyong , Yan Chen , Huang Kai , Lv Bo , Wang Hua , Wang Xiaoyan , Chen Jun , Sun Jingchuan
Published: April 2022

Purpose. To discuss effects of phosphatase and tensin homolog protein (PTEN)-mediated transforming growth factor-β (TGF-β)/Smad homologue 2 (Smad2) pathway on osteogenic differentiation in osteoporotic (OP) tibial fracture rats and bone marrow mesenchymal stem cell (BMSC) under tension. Methods. A tibial fracture model was established. The rats were divided into sham-operated group and model group, and tibia tissue was collected. Purchase well-grown cultured rat BMSC, and use the Flexercell in vitro cell mechanics loading device to apply tension. The expression of PTEN was detected by qRT-PCR. After the BMSCs were transfected with si-PTEN and oe-PTEN, the force was applied to detect cell differentiation. The expression of TGF-β/Smad2 protein was detected by Western blot. The formation of calcium nodules in BMSC was detected by alkaline phosphatase (ALP) staining and alizarin red (AR) staining. Results. The expression of PTEN was higher in the model group and tension MSC group, and the expression of TGF-β and Smad2 protein was lower. The expression of TGF-β and Smad2 protein in oe-PTEN group was lower than the oe-NC group and control group. The expression of TGF-β and Smad2 protein in si-PTEN group was higher than the si-NC group and control group. The results of ALP staining and AR staining also confirmed the above results. Conclusion. PTEN-mediated TGF-β/Smad2 pathway may play a key role in the osteogenic differentiation of OP tibial fracture rats. Downregulation of PTEN and upregulation of TGF-β/Smad2 signal can promote the osteogenic differentiation of BMSC under tension.
Simultaneous Association of Variations in the Origin and Diameter of the Left Vertebral Artery in a Patient with a C1 Lateral Mass Tumor
Authors: Mousavi Seyed Reza , Farrokhi Majid Reza , Yousufzai Shayan , Naseh Maryam , Karimi Fatemeh
Published: April 2022

The anomalous origin of a hypoplastic Left Vertebral Artery (LVA) from the aortic arch is a rare anatomic variant. This study discusses the case of a patient with a C1 lateral mass tumor that surrounded a dominant Right Vertebral Artery (RVA) according to preoperative computed tomography angiography, with a hypoplastic LVA originating from the aortic arch. Surgery was performed, and the patient recovered uneventfully. To date, no study has reported the simultaneous association of two variations (origin and diameter) in the LVA. A deep understanding of abnormalities in the diameter and origin of LVA is a must for neurosurgeons as well as for thoracic and vascular surgeons to conduct surgical procedures.
The Role of CTNNB1 in Endometrial Cancer
Authors: Ledinek Živa , Sobočan Monika , Knez Jure
Published: April 2022

Endometrial cancer (EC) is the most common gynaecologic malignancy in the developed countries. Recent evidence suggests that histopathological subtyping together with molecular subgrouping can lead to more accurate assessment of the risk profile for the patient. Clinical studies suggest the currently used molecular classification improves the risk assessment of women with endometrial cancer but does not explain the differences in recurrence profiles clearly. This could be improved by novel markers. One of such are mutations in the β-catenin (CTNNB1) gene, a frequently mutated gene in endometrial cancer. This shows mutations mostly at phosphorylation sites of the β-catenin and almost exclusively in the endometrial subgroup of no specific molecular profile. CTNNB1 mutations lead to alterations in the Wnt/β-catenin signalling pathway, involved in the carcinogenesis and progression of EC by inducing transcription of target genes, whose function is to regulate the cell cycle. Although tumours with mutations in CTNNB1 tend to have low-risk characteristics, they are related to worse outcomes with significantly increased rate of disease recurrence and lower overall survival.
Equivalence Assessment Method of Forest Tourism Safety Based on Internet of Things Application
Authors: Qi Yuan , Gao Xuan
Published: April 2022

With the continuous development of the society, China's economy and technology have been greatly improved, and network technology has also been widely used in life. In China's forestry management, the use of Internet of Things technology has gradually formed a model, which has greatly helped the economic benefits of forests. In addition, with the rapid development of the tourism industry, the number of tourists has increased sharply, the tourism infrastructure and tourism management are relatively lagging behind, and tourism safety accidents have occurred from time to time. However, the application of IoT technology in forestry is still in its infancy, with a small scope of application and low technical level. Aiming at the uniqueness of forest management, this paper proposes the development direction and application planning of IoT in forest resource supervision and service, forest fire prevention and control and service, ecological environment monitoring, and forest tourism supervision and service. In addition, this paper also discusses the acquisition technology of geological disasters, air quality, meteorological conditions, passenger flow conditions, and traffic flow mainly involved in tourism safety from the macroperspective of the Internet of Things. At the same time, the specific application of these technologies in tourist attractions is discussed to provide some technical reference for the realization of scientific and safe tourism management.
Clinicohematological, Mutagenic, and Oxidative Stress Induced by Pendimethalin in Freshwater Fish Bighead Carp (Hypophthalmichthys nobilis)
Authors: Wang Jin-qing , Hussain Riaz , Ghaffar Abdul , Afzal Gulnaz , Saad Abdul Qadeer , Ahmad Noman , Nazir Urooj , Ahmad Hafiz Ishfaq , Hussain Tarique , Khan Ahrar
Published: April 2022

Currently, aquatic and terrestrial ecosystems are continuously and chronically polluted by cocktails of countless chemical compounds. The susceptibility to infections is tremendously increasing in a variety of organisms due to exposure to environmental pollutants. Pendimethalin, an herbicide, is continuously used in agriculture to remove unwanted broadleaf weeds across the globe. Therefore, this study investigates the mechanisms of toxicity of pendimethalin in freshwater fish bighead carp upon exposure to low and environmentally relevant concentrations. For this purpose, 48 fish without any clinical abnormalities were kept in a glass aquarium in different experimental groups (T0, T1, T2, and T3). These groups were treated with pendimethalin at 0.00, 0.25, 0.50, and 0.75 mg/L, respectively. Four fish were randomly picked from each experimental group and killed at 72, 96, and 120 hours of the trial to study hematobiochemical parameters and visceral tissues including the brain, liver, heart, gills, and kidneys for histopathology. Herbicide-treated fish indicated various physical and behavioral abnormalities including hypersecretion of mucus, erratic swimming, operculum movement, air gulping, tremors of fins, loss of equilibrium, and increased surface breathing. Histopathologically, gills tissues of treated fish indicated atrophied lamellae, uplifting of secondary lamellae, necrosis of primary and secondary lamellar epithelial cells, telogenesis, congestion, and lamellar fusion. Histopathological examination of liver tissues of treated fish showed mild to moderate congestion, necrosis of hepatocytes, and atrophy of hepatocytes while kidneys revealed degeneration of renal tubules, glomerular atrophy, ceroid, and necrosis of renal tubules. The erythrocyte counts, monocyte and lymphocyte counts, and hemoglobin values were significantly (P<0.05) reduced in pendimethalin-treated fish. Results on serum biochemistry showed that the biomarkers of kidneys, heart, and liver were significantly higher in fish of treated groups. In addition, values of different biochemical reactions like reactive oxygen species (ROS), thiobarbituric acid reactive species (TBARS), total proteins, and quantity of different antioxidant enzymes including reduced glutathione (GSH), catalase, and superoxide dismutase (SOD) were significantly different when compared to untreated fish. Moreover, the percentile of different nuclear abnormalities in red blood cells and frequency of DNA damage increased significantly in treated fish. It can be concluded from the findings that pendimethalin causes its toxic effects via disruption of physiological and hematobiochemical reactions of fish.
Multinode Data Offloading for Urban Wireless Sensor Networks Based on Fog Computing: A Multiarmed Bandit Approach
Authors: Shan Yuchen , Wang Hui , Zhang Chenxiang
Published: April 2022

Urban wireless sensor networks (UWSNs) are an important application scenario for the Internet of Things (IoT). With the emergence of many computationally intensive applications based on urban environments, sensors in wireless sensor networks are unable to meet demands such as latency due to their limited resources. Fog computing architectures have the potential to liberate data transmission from resource-constrained sensor nodes through data offloading. Therefore, data collection and scalable collaboration based on fog architectures are seen as a challenge. For the multinode data offloading problem, a multinode data offloading strategy based on stable matching and MAB (multi-armed bandit) model is proposed to maximize the offloading success rate while guaranteeing the latency requirements of the source task nodes. Firstly, the multinode data offloading problem is modelled. Secondly, the case of multinode selection conflict is considered, and selection conflict and information exchange are reduced by the MAB model and the fallback timer. Then, an adjustment strategy is proposed based on the idea of delayed reception in the stable matching of game theory. Finally, the multinode data offloading problem is solved by successive iterations. The proposed algorithm not only accomplishes coordinated cooperation between nodes to achieve high-quality data offloading and avoid collisions between nodes but also reduces the amount of information exchanged between nodes. The effectiveness of the algorithm is demonstrated by theoretical analysis and simulation experiments.
An Improved Harmony Search Approach for Block Placement for VLSI Design Automation
Authors: Karimullah Shaik , Vishnuvardhan D. , Arif Muhammad , Gunjan Vinit Kumar , Shaik Fahimuddin , Siddiquee Kazy Noor-e-alam
Published: April 2022

The technology grows quickly in the area of the VLSI physical design; it is crucial to integrate the greater number of transistors and parts into a very small range. Before the placement is completed, the physical and technical positioning of the blocks in the chip area is planned, which is nothing but floor planning. In order to lessen the placement region in the physical layout, floor planning must be carried out effectively. This paper proposes a blended harmony search and particle swarm optimization (BHSPS) algorithm which is the deliberate blend of the harmony search (HS) algorithm, and the particle swarm optimization (PSO) algorithm is proposed to acquire the central goal of the VLSI placement strategy. The objective here is to lessen the field of plan. The MATLAB code for the blended harmony search and particle swarm optimization (BHSPS) algorithm is compiled, and investigations were carried out for better examination through the standard MCNC, i.e., North Carolina Microelectronics Center benchmark circuits.
BCFDPS: A Blockchain-Based Click Fraud Detection and Prevention Scheme for Online Advertising
Authors: Lyu Qiuyun , Li Hao , Zhou Renjie , Zhang Jilin , Zhao Nailiang , Liu Yan
Published: April 2022

Online advertising, which depends on consumers’ click, creates revenue for media sites, publishers, and advertisers. However, click fraud by criminals, i.e., the ad is clicked either by malicious machines or hiring people, threatens this advertising system. To solve the problem, many schemes are proposed which are mainly based on machine learning or statistical analysis. Although these schemes mitigate the problem of click fraud, several problems still exist. For example, some fraudulent clicks are still in the wild since their schemes only discover the fraudulent clicks with a probability approaching but not 100%. Also, the process of detecting a click fraud is executed by a single publisher, which makes a chance for the publisher to obtain illegal income by deceiving advertisers and media sites. Besides, the identity privacy of consumers is also exposed because the schemes deal with the plain text of consumers’ real identity. Therefore, in this paper, a blockchain-based click fraud detection and prevention scheme (BCFDPS) for online advertising is proposed to deal with the above problems. Specifically, the BCFDPS mainly introduces bilinear pairing to implicitly verify whether a consumer’s real digital identity is contained in a click message to significantly avoid click fraud and employs a consortium blockchain to ensure the transparency of the detection and prevention process. In our scheme, the clicks by machines or fraud ones by a human can be accurately detected and prevented by media sites, publishers, and advertisers. Furthermore, ciphertext-policy attribute-based encryption is adopted to protect the identity privacy of consumers. The implementation and evaluation results show that compared with the existing click fraud detection and prevention schemes based on machine learning and statistical analysis, BCFDPS achieves detection of each fraudulent click with a probability of 100% and consumes lower computation cost; furthermore, BCFDPS adds functions of consumers’ privacy protection and click fraud detection and prevention, compared to the existing blockchain-based online advertising scheme, by introducing limited communication cost (

4,984

bytes) at lower storage cost.
Parameter Estimation in Step Stress Partially Accelerated Life Testing under Different Types of Censored Data
Authors: Kamal Mustafa , Siddiqui Sabir Ali , Rahman Ahmadur , Alsuhabi Hassan , Alkhairy Ibrahim , Barry Thierno Souleymane
Published: April 2022

A long testing period is usually required for the life testing of high-reliability products or materials. It is possible to shorten the testing process by using ALTs (accelerated life tests). Due to the fact that ALTs test products in harsher settings than are typical use conditions, the life expectancy of the objects they evaluate is reduced. Censored data in which the specific failure timings of all units assigned to test are not known, or all units assigned to test have not failed, may arise in ALTs for a variety of reasons, including operational failure, device malfunction, expense, and time restrictions. In this paper, we have considered the step stress partially accelerated life test (SSPALT) under two different censoring schemes, namely the type-I progressive hybrid censoring scheme (type-I PHCS) and the type-II progressive censorship scheme (type-II PCS). The failure times of the items are assumed to follow NH distribution, while the tampered random variable (TRV) model is used to explain the effect of stress change. In order to obtain the estimates of the unknown parameters, the maximum likelihood estimation (MLE) approach is adopted. Furthermore, based on the asymptotic theory of MLEs, the approximate confidence intervals (ACIs) are also constructed. The point estimates under two censoring schemes are compared in terms of root mean squared errors (RMSEs) and relative absolute biases (RABs), while ACIs are compared in terms of their lengths and coverage probabilities (CPs). The performance of the estimators has been evaluated and compared under two censoring schemes with various sample sizes through a simulation study. Simulation results show that estimates with type-I PHCS outperform estimates with type-II PCS in terms of RMSEs, RABs, lengths, and CPs. Finally, a real-world numerical example of insulating fluid failure times is presented to show how the approaches will work in reality.
Hyperspectral Image Classification: Potentials, Challenges, and Future Directions
Authors: Datta Debaleena , Mallick Pradeep Kumar , Bhoi Akash Kumar , Ijaz Muhammad Fazal , Shafi Jana , Choi Jaeyoung
Published: April 2022

Recent imaging science and technology discoveries have considered hyperspectral imagery and remote sensing. The current intelligent technologies, such as support vector machines, sparse representations, active learning, extreme learning machines, transfer learning, and deep learning, are typically based on the learning of the machines. These techniques enrich the processing of such three-dimensional, multiple bands, and high-resolution images with their precision and fidelity. This article presents an extensive survey depicting machine-dependent technologies’ contributions and deep learning on landcover classification based on hyperspectral images. The objective of this study is three-fold. First, after reading a large pool of Web of Science (WoS), Scopus, SCI, and SCIE-indexed and SCIE-related articles, we provide a novel approach for review work that is entirely systematic and aids in the inspiration of finding research gaps and developing embedded questions. Second, we emphasize contemporary advances in machine learning (ML) methods for identifying hyperspectral images, with a brief, organized overview and a thorough assessment of the literature involved. Finally, we draw the conclusions to assist researchers in expanding their understanding of the relationship between machine learning and hyperspectral images for future research.
[Retracted] Statistical Inference and Mathematical Properties of Burr X Logistic‐Exponential Distribution with Applications to Engineering Data
Authors: AL Sobhi Mashail M.
Published: April 2022

The Burr X logistic‐exponential distribution is introduced in this study as a novel logistic‐exponential distribution extension that may be utilized to efficiently describe engineering data. There are J‐shape, symmetrical, left‐skewed, reversed‐J shape, and right‐skewed densities available, as well as decreasing, rising, bathtub, unimodal, J‐shape, and reversed‐J shape hazard rates. The fundamental mathematical features of the proposed model were obtained. The new model’s parameters were estimated using seven different approaches, including maximum likelihood, Anderson–Darling, maximum product of spacing, least‐squares, Cramér–von Mises, percentiles, and weighted least squares. To evaluate the performance of the recommended estimation methods, a full simulation study was carried out. Finally, the adaptability of the provided distribution was tested using two real datasets from engineering science, revealing that the new model can yield a close match when compared to competing models.
Research on Intelligent Campus and Visual Teaching System Based on Internet of Things
Authors: Xu Tao , Wang Zhi-hong , Zhang Xian-qi
Published: April 2022

The rapid development of Internet of things technology provides robust conditions for building a perfect intelligent campus. A visual teaching question answering system is essential for creating a smart campus, significantly improving education quality. However, the accuracy of the existing teaching question answering system is not high. To solve this problem, this paper proposes a visual teaching system based on a knowledge map. The system mainly includes two parts: problem processing and answer search. In the part of problem processing, combined with the pretraining language model, a new model framework is constructed to deal with the problem of entity reference recognition, entity link, and relationship extraction. By setting three kinds of classification labels, the problem is divided into simple, chain, and multientity problems. Different solutions are given to the above three classification problems in the answer search part. The experimental results show that the answer accuracy of this system is higher than other comparison methods.
Prediction Model of Urban Street Public Space Art Design Indicators Based on Deep Convolutional Neural Network
Authors: Li Yang , Wu Jing , Cao Lingli
Published: April 2022

Object detection in public spaces on urban streets has always been an important research topic in the field of computer vision networks. Due to the complex and changeable scene in the prediction of public space art design indicators, there are still problems in the research of target detection algorithms in practical applications. Based on the DCNN, this paper studies the accurate detection algorithm and implementation of urban streets in complex scenes. This paper uses the characteristics of DCNN coding to collect and compress data at the same time, studies the prediction module of urban street saliency detection algorithm, and combines saliency map to determine the saliency of urban street art design indicators in the measurement domain. The experimental method can greatly shorten the index prediction scan time and solve the problems of high window calibration redundancy and long positioning time in index prediction. The experimental results show that the proposed method combining urban street mask and public space feature information can reduce other interference information, the average accuracy of target detection is increased by 0.398, and the error is reduced to 3.12%, which significantly promotes urban streets and improves recognition accuracy.
Defects in Very Long-Chain Fatty Acid Oxidation Presenting as Different Types of Cardiomyopathy
Authors: Alaei Fariba , Shakiba Marjan , Saneifard Hedyeh , Vahidshahi Kourosh , Alaei Mastaneh
Published: April 2022

Cardiac involvement may accompany various inborn errors of metabolism (IEM) including fatty acid oxidation (FAO) disorders, presenting as rhythm disturbances, conduction abnormalities, cardiomyopathies, pericardial effusion, and sudden cardiac death. FAO disorders are rare mitochondrial diseases with variable organ involvements and clinical presentations. Very long-chain acyl-CoA dehydrogenase deficiency (VLCADD) is a FAO disorder with diverse clinical presentations. We report two VLCADD patients with cardiac involvement and diverse presentations. The first patient represents with cardiogenic shock and dilated cardiomyopathy (DCM) at childhood. The second patient represents with suspicious sepsis at early infancy and hypertrophic cardiomyopathy (HCM) at further evaluation. IEM should be thought of in every individual case with suspicious sepsis or cardiac failure regardless of age or previous history.
GEO Database Screening Combined with In Vitro Experiments to Study the Mechanism of hsa_circ_0003570 in Infantile Hemangiomas
Authors: Tian Yu , Zhuang Shihao , Zhang Jiantao , You Tonghui , Xu Zihang , Yang Wanli , Hao Bin , Wang Weifeng , Yang Tao
Published: April 2022

Objective. In this study, we screened out a type of differentially expressed circular RNA in infantile hemangioma (IH) cells and analyzed the mechanism in the malignant biological behavior of IH. Methods. Based on the GSE98795, GSE100682, and GSE43742 datasets, differential expression analysis of circRNAs, microRNAs, and mRNAs was performed. The relative expression level of RNA was detected by quantitative real-time polymerase chain reaction (qRT-PCR). MTT assay, Transwell, flow cytometry analysis, and western blot were used to study the effects of hsa_circ_0003570, hsa-miR-138-5p, and RGS5 on the proliferation and apoptosis of hemangioma endothelial cells (HEMECs). Results. The hsa_circ_0003570 and RGS5 mRNA were upregulated in HEMECs, but hsa-miR-138-5p was downregulated. Silencing of hsa_circ_0003570 inhibited the proliferation of HEMECs and promoted the apoptosis of HEMECs. The malignant biological behaviors of hsa_circ_0003570 on the proliferation and apoptosis of HEMECs were reversed by hsa-miR-138-5p. Hsa_circ_0003570 acted as the ceRNA of hsa-miR-138-5p and upregulated the expression of RGS5. Silencing of RGS5 inhibited the proliferation, migration, and invasion of HEMECs and promoted apoptosis. Conclusion. Hsa_circ_0003570 promotes IH cell proliferation and inhibits IH cell apoptosis through hsa-miR-138-5p/RGS5 axis.
On Hamiltonian Decomposition Problem of 3-Arc Graphs
Authors: Xu Guangjun , Sun Qiang , Liang Zuosong
Published: April 2022

A 4-tuple

y
,
x
,
v
,
w

in a graph is a 3-arc if each of

y
,
x
,
v

and

x
,
v
,
w

is a path. The 3-arc graph of

H

is the graph with vertex set all arcs of

H

and edge set containing all edges joining

x
y

and

v
w

whenever

y
,
x
,
v
,
w

is a 3-arc of

H

. A Hamilton cycle is a closed path meeting each vertex of a graph. A graph

H

including a Hamilton cycle is called Hamiltonian and

H

has a Hamiltonian decomposition provided its edge set admits a partition into disjoint Hamilton cycles (possibly with a single perfect matching). The current paper proves that every connected 3-arc graph consists of more than one Hamilton cycle. Since the 3-arc graph of a cubic graph is 4-regular, it further proves that each 3-arc graph of a cubic graph in a certain family has a Hamiltonian decomposition.
Database Development Based on Deep Learning and Cloud Computing
Authors: Liu Rukun , Wang Teng , Yang Yuxue , Yu Bingjie
Published: April 2022

In this research, the author develops databases based on deep learning and cloud computing technology. On the basis of designing the overall architecture of the database with the distributed C/S mode as the core, use J2EE (Java 2 Platform, Enterprise Edition) as the development tool, apply Oracle server database, extract data features with in-depth learning technology, allocate data processing tasks based with cloud computing technology, so as to finally complete data fusion and compression. Finally, the overall development of the database is completed by designing the database backup scheme and external encryption. The test results show that the database developed by the above method has low performance loss, can quickly complete the processing of subdatabase and subtable, and can effectively support the distributed storage of data.
Research on the Evaluation Model of Dance Movement Recognition and Automatic Generation Based on Long Short-Term Memory
Authors: Yuan Xiuming , Pan Peipei
Published: April 2022

With the development of random image processing technology and in-depth learning, it is possible to recognize human movements, but it is difficult to recognize and evaluate dance movements automatically in artistic expression and emotional classification. Aiming at the problems of low efficiency, low accuracy, and unsatisfactory evaluation in dance motion recognition, this paper proposes a long short-term memory (LSTM) model based on deep learning to recognize dance motion and automatically generate corresponding features. This paper first introduces the related deep learning model recognition methods and describes the related research background. Secondly, the method of identifying dance movements is identified concretely, and the process of identifying concretely is given. Finally, through the comparison of different dance movements through experiments, it shows that there are obvious advantages in the accuracy of action recognition, error rate, similarity, and model evaluation method.
Mathematical Problems in Engineering Decision-Making Based on Improved Entropy Weighting Method: An Example of Passenger Comfort in a Smart Cockpit of a Car
Authors: Yang Jianjun , Xing Shanshan , Qiu Ruizhi , Chen Yimeng , Hua Chunrong , Dong Dawei
Published: April 2022

The entropy method is used in many decisions on indicator weights and has been proven to be effective. The traditional entropy method has two shortcomings in calculating indicator weights. On the one hand, when the developed indicator is considered to have no influence, it will lead to the meaningless calculation formula of the entropy method, and on the other hand, when the entropy method is dealing with data with entropy values close to 1, there will be entropy jumps leading to data distortion. To solve the above shortcomings, two correction coefficients are introduced in this paper, and the improved entropy weight method is applied to the evaluation model of the passenger comfort of the intelligent cockpit of the car, and the effectiveness of the improved entropy weight method is proved.
Network Intrusion Detection Method Combining CNN and BiLSTM in Cloud Computing Environment
Authors: Gao Jing
Published: April 2022

A network intrusion detection method combining CNN and BiLSTM network is proposed. First, the KDD CUP 99 data set is preprocessed by using data extraction algorithm. The data set is transformed into image data set by data cleaning, data extraction, and data mapping; Second, CNN is used to extract the parallel local features of attribute information, and BiLSTM is used to extract the features of long-distance-dependent information, so as to fully consider the influence between the front and back attribute information, and attention mechanism is introduced to improve the classification accuracy. Finally, C5.0 decision tree and CNN BiLSTM deep learning model are combined to skip the design feature selection and directly use deep learning model to learn the representational features of high-dimensional data. Experimental results show that, compared with the methods based on AE-AlexNet and SGM-CNN, the network intrusion detection effect of this method is better, the average accuracy can be improved to 95.50%, the false-positive rate can be reduced to 4.24%, and the false positive rate can be reduced to 6.66%. The proposed method can significantly improve the performance of network intrusion detection system.
The Correlation between the Increased Expression of Aquaporins on the Inner Limiting Membrane and the Occurrence of Diabetic Macular Edema
Authors: Chen Yiqi , Chen Huan , Wang Chenxi , Yu Jiafeng , Tao Jiwei , Mao Jianbo , Shen Lijun
Published: April 2022

Purpose. Diabetic macular edema (DME) is a major cause of vision loss in patients with diabetic retinopathy; this study is aimed at comparing the expression of aquaporins (AQPs) on the inner limiting membranes (ILMs) of various vitreoretinal diseases and investigating the role of aquaporins expressed on the ILMs in mediating the occurrence of DME. Methods. The whole-mounted ILM specimens surgically excised from patients with various vitreoretinal diseases (idiopathic macular hole, myopic traction maculopathy, and diabetic retinopathy) were analyzed by immunohistochemistry (IHC). The distribution and morphology of AQP4, AQP7, and AQP11 on the ILMs were correlated with immunohistochemical staining characteristics. Moreover, immunofluorescence of AQP4 was performed on the ILM specimens of the patient in four groups: the control group, negative control group, no DME group, and DME group. The immunofluorescence intensity value of AQP4 was measured using ImageJ. The difference between the four groups and the correction between the immunofluorescence value and central foveal thickness (CFT) were analyzed. Results. In IHC sections, the expression of AQP4, AQP7, and AQP11 on ILMs of diabetic retinopathy (DR) with macular edema, respectively, seemed to be more abundant than in the idiopathic macular hole (iMH) and myopic traction maculopathy (MTM). Moreover, markedly higher fluorescence intensity of AQP4 of ILMs was determined in the DME group (

51.05
±
5.67

) versus the other three groups (

P
<
0.001

). A marked positive association was identified between the fluorescence intensity of AQP4 and CFT (

r
=
0.758

;

P
=
0.011

). Conclusions. AQP4, AQP7, and AQP11 can be expressed on human ILM in vivo. The increased expression of AQPs on the ILMs of DR may be associated with the occurrence of DME. Moreover, the degree of DME may be positively correlated with the expression of AQP4 on the ILMs.