bluuebunny/crossref_metadata_2025 huggingface dataset:
[Retracted] Construction of an Intelligent Analysis Model for Website Information Based on Big Data and Cloud Computing Technology
Authors: Chen Ronghua , Yang Bei
Published: January 2022

Based on big data and cloud computing technology, the development process of this system includes hardware cluster deployment of the delivery system, optimization of website delivery strategy, and development of the delivery management background system. The main functions in the following aspects are realized: first, we built the website back‐end delivery subsystem and data collection and analysis subsystem to realize the control of website delivery and data collection; second, we designed and developed a process management subsystem for booking, management, and delivery of website resources and developed the contract management and order management subsystems to realize the accurate placement of user portraits on the website; then, the placement data monitoring and effect feedback subsystems, and the data inventory subsystem of the website system were designed and developed. Finally, based on the research of Android and based on the Eclipse platform, this article has completed the construction of the Android 4.0.3 version environment, successfully used the Java development language to develop a website information intelligent analysis and navigation system, and analyzed the various functional modules of the entire system. Experimental results show that the system not only realizes ordinary route and site query functions but also combines map API, integrates big data and cloud computing technology, and realizes congestion avoidance query, time optimal query, population heat map, and real‐time viewing. The nearby use of this software’s personnel density distribution and other functions provides great convenience for personal travel, which can facilitate the real‐time planning of travel plans, and has great practical and practical significance. Through the different levels of testing of various subsystems, the website delivery system meets the functional and nonfunctional requirements proposed by the network and on this basis realizes the use of group wisdom based on Pearson correlation coefficient, Cosine similarity, and Tanimoto coefficient for collaborative filtering website recommendation algorithm.
Research on the Allocation Method of Regional Science and Technology Resources from the Perspective of Rationality
Authors: Zhang Huozhong , Zhou Yongjun
Published: January 2022

At present, the allocation efficiency of regional scientific and technological resources is low, and there are few research studies on social equity and economic efficiency. Therefore, this paper puts forward the allocation method of regional scientific and technological resources based on rationality. With the support of rationality perspective, the evaluation model of reform path of regional scientific and technological resource allocation is constructed to analyze the economic benefits and equity benefits of regional scientific and technological resource allocation. According to the principle of optimum allocation of regional science and technology resources, three-dimensional structure is constructed to maximize national investment and benefit and determine the optimal Pareto of resource allocation to measure the efficiency of resource allocation. The evaluation index system of the reform path of resource allocation is constructed by selecting the evaluation index of the reform path of resource allocation. The benchmark platform of big data was selected to generate data sets to be processed, and the spark on yam platform was used to submit jobs and generate spark job running data sets. The operation performance prediction model was established to optimize the configuration parameters of regional science and technology resources. The analysis results show that the designed method has high configuration capability and good effectiveness.
Computed Tomography Image Features under Deep Learning Algorithm Applied in Staging Diagnosis of Bladder Cancer and Detection on Ceramide Glycosylation
Authors: Xu Yisheng , Lou Jianghua , Gao Zhiqin , Zhan Ming
Published: January 2022

The research is aimed at investigating computed tomography (CT) image based on deep learning algorithm and the application value of ceramide glycosylation in diagnosing bladder cancer. The images of ordinary CT detection were improved. In this study, 60 bladder cancer patients were selected and performed with ordinary CT detection, and the detection results were processed by CT based on deep learning algorithms and compared with pathological diagnosis. In addition, Western Blot technology was used to detect the expression of glucose ceramide synthase (GCS) in the cell membrane of tumor tissues and normal tissues of bladder. The comparison results found that, in simple CT clinical staging, the coincidence rates of T1 stage, T2a stage, T2b stage, T3 stage, and T4 stage were 28.56%, 62.51%, 78.94%, 84.61%, and 74.99%, respectively; and the total coincidence rate of CT clinical staging was 63.32%, which was greatly different from the clinical staging of pathological diagnosis (

P
<
0.05

). In the clinical staging of algorithm-based CT test results, the coincidence rates of T1 stage and T2a stage were 50.01% and 91.65%, respectively; and those of T2b stage, T3 stage, and T4 stage were 100.00%; and the total coincidence rate was 96.69%, which was not obviously different from the clinical staging of pathological diagnosis (

P
>
0.05

). Therefore, it could be concluded that the algorithm-based CT detection results were more accurate, and the use of CT scans based on deep learning algorithms in the preoperative staging and clinical treatment of bladder cancer showed reliable guiding significance and clinical value. In addition, it was found that the expression level of GCS in normal bladder tissues was much lower than that in bladder cancer tissues. This indicated that the changes in GCS were closely related to the development and prognosis of bladder cancer. Therefore, it was believed that GCS may be an effective target for the treatment of bladder cancer in the future, and further research was needed for specific conditions.
Numerical Simulation Research on Cutting Rock with a PDC Cutter Assisted by an Impact Force
Authors: Wang Yong , Ni Hongjian , Wang Ruihe , Huang Bin , Liu Shubin , Zhang Heng
Published: January 2022

Extensive studies have been carried out on cutting rock with a PDC cutter, but cutting rock assisted by impact force is rarely studied. In this paper, cutting rock using conical and cylindrical PDC cutters assisted by impact force were researched with the explicit dynamic model. The laws of cutting rock using a cylindrical cutter assisted by impact force are the same as those of a conical cutter. There are thresholds of impact frequency and amplitude when they are single variables. When impact frequency is lower than the threshold frequency, the impact frequency is the dominant frequency in the frequency spectrum of weight on bit (WOB), and the amplitude of dominant frequency and removal volume decreases with the increase of impact frequency. When the impact frequency is higher than the threshold frequency, there is no dominant frequency in the frequency spectrum of WOB, and the removal volume behaves the same. When the impact force is lower than the threshold amplitude, there is no dominant frequency in the frequency spectrum of WOB, and it does not affect the removal volume but the removal volume is positively correlated with the impact amplitude. When the impact amplitude is higher than the threshold amplitude, the removal volume is also positively correlated with the impact amplitude, and the removal volume assisted by low‐frequency (20 Hz and 40 Hz) impact force is higher. The frequency threshold and amplitude threshold of the conical cutter are smaller than those of the cylindrical cutter. Although the cutting depth and removal volume of the conical cutter are lower than those of the cylindrical cutter, the amplifications of cutting depth and removal volume of the conical cutter are higher than those of the cylindrical cutter when assisted by impact force.
Differentially Expressed Genes Reveal the Biomarkers and Molecular Mechanism of Osteonecrosis
Authors: Ma Huanzhi , Zhang Wei , Shi Jun
Published: January 2022

Osteonecrosis is one of the most refractory orthopedic diseases, which seriously threatens the health of old patients. High-throughput sequencing (HTS) and microarray analysis have confirmed as an effective way for investigating the pathological mechanism of disease. In this study, GSE7716, GSE74089, and GSE123568 were obtained from Gene Expression Omnibus (GEO) database and used to identify differentially expressed genes (DEGs) by R language. Subsequently, the DEGs were analyzed with Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment. Moreover, the protein-protein interaction (PPI) network of DEGs was analyzed by STRING database and Cytoscape. The results showed that 318 downregulated genes and 58 upregulated genes were observed in GSE7116; 690 downregulated genes and 1148 upregulated genes were screened from 34183 genes in GSE74089. The DEGs involved in progression of osteonecrosis involved inflammation, immunological rejection, and bacterial infection-related pathways. The GO enrichment showed that osteonecrosis was related with extracellular matrix, external encapsulating structure organization, skeletal system development, immune response activity, cell apoptosis, mononuclear cell differentiation, and serine/threonine kinase activity. Moreover, PPI network showed that the progression of osteonecrosis of the femoral head was related with CCND1, CDH1, ESR1, SPP1, LOX, JUN, ITGA, ABL1, and VEGF, and osteonecrosis of the jaw is related with ACTB, CXCR4, PTPRC, IL1B, CXCL8, TNF, JUN, PTGS2, FOS, and RHOA. In conclusion, this study identified the hub factors and pathways which might play important roles in progression of osteonecrosis and could be used as potential biomarkers for diagnosis and treatment of osteonecrosis.
Expression of Oxidative Phosphorylation Complexes and Mitochondrial Mass in Pediatric and Adult Inflammatory Bowel Disease
Authors: Schneider Anna M. , Özsoy Mihriban , Zimmermann Franz A. , Brunner Susanne M. , Feichtinger René G. , Mayr Johannes A. , Kofler Barbara , Neureiter Daniel , Klieser Eckhard , Aigner Elmar , Schütz Sebastian , Stummer Nathalie , Sperl Wolfgang , Weghuber Daniel
Published: January 2022

Introduction. Inflammatory bowel disease (IBD), which includes Crohn’s disease (CD) and ulcerative colitis (UC), is a multifactorial intestinal disorder but its precise etiology remains elusive. As the cells of the intestinal mucosa have high energy demands, mitochondria may play a role in IBD pathogenesis. The present study is aimed at evaluating the expression levels of mitochondrial oxidative phosphorylation (OXPHOS) complexes in IBD. Material and Methods. 286 intestinal biopsy samples from the terminal ileum, ascending colon, and rectum from 124 probands (34 CD, 33 UC, and 57 controls) were stained immunohistochemically for all five OXPHOS complexes and the voltage-dependent anion-selective channel 1 protein (VDAC1 or porin). Expression levels were compared in multivariate models including disease stage (CD and UC compared to controls) and age (pediatric/adult). Results. Analysis of the terminal ileum of CD patients revealed a significant reduction of complex II compared to controls, and a trend to lower levels was evident for VDAC1 and the other OXPHOS complexes except complex III. A similar pattern was found in the rectum of UC patients: VDAC1, complex I, complex II, and complex IV were all significantly reduced, and complex III and V showed a trend to lower levels. Reductions were more prominent in older patients compared to pediatric patients and more marked in UC than CD. Conclusion. A reduced mitochondrial mass is present in UC and CD compared to controls. This is potentially a result of alterations of mitochondrial biogenesis or mitophagy. Reductions were more pronounced in older patients compared to pediatric patients, and more prominent in UC than CD. Complex I and II are more severely compromised than the other OXPHOS complexes. This has potential therapeutic implications, since treatments boosting biogenesis or influencing mitophagy could be beneficial for IBD treatment. Additionally, substances specifically stimulating complex I activity should be tested in IBD treatment.
Recording of Falls in Elderly Fallers in Northern Greece and Evaluation of Aging Health-Related Factors and Environmental Safety Associated with Falls: A Cross-Sectional Study
Authors: Lytras Dimitrios , Sykaras Evaggelos , Iakovidis Paris , Kasimis Konstantinos , Myrogiannis Ioannis , Kottaras Anastasios
Published: January 2022

Background. Elderly falls constitute a global problem with huge social and economic aspects. Fall risk factors are both intrinsic (physical and psychological) and extrinsic (related with environmental safety). Aim. To record both intrinsic and extrinsic risk factors and their correlation in elderly fallers in order to suggest specific guidelines for their medical care and environmental modification inside and outside the home. Method. The study involved 150 elderly fallers (median age 70 (67-74)), who completed a record containing information on known risk factors related to their health status, as well as information on the conditions and causes that led to the fall. Each fall was considered an independent event, while measurements were performed regarding balance, strength, their functional ability, and the fear of a possible fall. Descriptive analysis and frequency analysis were used to record the health and activity status of the participants as well as the fall-related environmental factors. Severity of each fall event across a variety of locations was examined using the Kruskal-Wallis one-way analysis of variance. Multiple linear regression was applied to examine the effect of the mean values of functional tests and medical records on the number of fall events. Results. In the span of 12 months, a total of 304 fall events were recorded. Regarding location, 77.6% occurred indoors; more frequent were the bedroom (28.6%) and the bathroom (28%). The interior stairs (10.5%), the kitchen (4.9%), and the living room (3.3%) were the less frequent locations. Concerning danger, falling on the interior stairs caused the longest hospitalization, followed by the kitchen and the bathroom. Extrinsic factors that led to both indoor and outdoor falls were the administration of psychotropic medication, poor space ergonomics, lack of basic safety standards, and poor lighting conditions. Vision problems and dizziness resulted in more falls than other intrinsic factors. Furthermore, reduced performance in the FICSIT-4 test and the 30-Second Chair Stand Test, as well as high scores in the CONFbal–GREEK questionnaire and the Short FES-I, shows a linear relationship with an increased number of falls. Conclusions. Ergonomic interventions can help prevent indoor elderly falls. Poor construction and lack of adequate lighting mainly cause outdoor falls. Regular eye examinations, management of vertigo, improvement of the balance and strength of the lower limbs, and reduction of fear of impending falls are the intrinsic factors that help prevent falls the most.
Construction and Validation of a Risk Prediction Model for Acute Kidney Injury in Patients Suffering from Septic Shock
Authors: Yue Suru , Li Shasha , Huang Xueying , Liu Jie , Hou Xuefei , Wang Yufeng , Wu Jiayuan
Published: January 2022

Background. Acute kidney injury (AKI) is an important complication in critically ill patients, especially in sepsis and septic shock patients. Early prediction of AKI in septic shock can provide clinicians with sufficient information for timely intervention so that improve the patients’ survival rate and quality of life. The aim of this study was to establish a nomogram that predicts the risk of AKI in patients with septic shock in the intensive care unit (ICU). Methods. The data were collected from the Medical Information Mart for Intensive Care III (MIMIC-III) database between 2001 and 2012. The primary outcome was AKI in the 48 h following ICU admission. Univariate and multivariate logistic regression analyses were used to screen the independent risk factors of AKI. The performance of the nomogram was evaluated according to the calibration curve, receiver operating characteristic (ROC) curve, decision curve analysis, and clinical impact curve. Results. A total of 2415 patients with septic shock were included in this study. In the training and validation cohort, 1091 (64.48%) of 1690 patients and 475 (65.52%) of 725 patients developed AKI, respectively. The predictive factors for nomogram construction were gender, ethnicity, congestive heart failure, diabetes, obesity, Simplified Acute Physiology Score II (SAPS II), angiotensin-converting enzyme inhibitors (ACEI) or angiotensin receptor blockers (ARBs), bilirubin, creatinine, blood urea nitrogen (BUN), and mechanical ventilation. The model had a good discrimination with the area under the ROC curve of 0.756 and 0.760 in the training and validation cohorts, respectively. The calibration curve for probability of AKI in septic shock showed optimal agreement between prediction by nomogram and actual observation. Decision curve and clinical impact curve analysis indicated that the nomogram conferred high clinical net benefit. Conclusion. The proposed nomogram can quickly and effectively predict the risk of AKI at an early stage in patients with septic shock in ICU, which can provide information for timely and efficient intervention in patients with septic shock in the ICU setting.
Canities Subita after Extreme Trauma Showing Positive Staining for Anti-PD-L1 Antibodies: A New Clue into Etiopathogenesis?
Authors: Navarro-Triviño Francisco J. , Ruiz-Villaverde Ricardo , Manuel Ramos-Pleguezuelos Francisco , Vañó-Galván Sergio
Published: January 2022

Canities subita has been considered by some authors an acute episode of diffuse alopecia areata in which the sudden whitening is caused by the preferential loss of pigmented hair in this immune-mediated disorder. Clinically, the “salt and pepper” pattern of hair color is the most frequent manifestation of canities subita. However, the exact physiopathology of canities subita is not completely understood. A 69-year-old Caucasian man was referred for the sudden and asymptomatic whitening of the hair on the scalp and eyebrows, without an associated hair loss. The trigger was the death of his brother. Hair whitening appeared 24 h after the event. He reported a history of alopecia areata in plaques on the scalp, with spontaneous complete resolution in 2006. The physical examination showed full whitening hair on the scalp and eyebrows. Eyelashes were not affected. The pull test was negative, and the patient denied a significant hair loss in the last days. The histopathological study showed several follicle-sebaceous structures in the anagen, and one of them (inset) with a transforming hair bulb. The anterior bulb was surrounded by a lymphocytic inflammatory infiltrate in an advanced stage of transformation to the catagen and incipient scar changes. Immunohistochemistry staining showed a positive anti-PD-L1 antibody expressed in the inflammatory infiltrate. Based on the clinical and histological findings, a diagnosis of canities subita was made. The histopathological study showed a positive staining for anti-PD-L1 antibodies, supporting the role of the immune system in the development of this phenomenon. The interaction between melanogenesis and the lymphocytes warrants further research.
Sulfonylurea-Insensitive Permanent Neonatal Diabetes Caused by a Severe Gain-of-Function Tyr330His Substitution in Kir6.2
Authors: McClenaghan Conor , Rapini Novella , De Rose Domenico Umberto , Gao Jian , Roeglin Jacob , Bizzarri Carla , Schiaffini Riccardo , Tiberi Eloisa , Mucciolo Mafalda , Deodati Annalisa , Perri Alessandro , Vento Giovanni , Barbetti Fabrizio , Nichols Colin G. , Cianfarani Stefano
Published: January 2022

Background/Aims: Mutations in KCNJ11, the gene encoding the Kir6.2 subunit of pancreatic and neuronal KATP channels, are associated with a spectrum of neonatal diabetes diseases. Methods: Variant screening was used to identify the cause of neonatal diabetes, and continuous glucose monitoring was used to assess effectiveness of sulfonylurea treatment. Electrophysiological analysis of variant KATP channel function was used to determine molecular basis. Results: We identified a previously uncharacterized KCNJ11 mutation, c.988T>C [p.Tyr330His], in an Italian child diagnosed with sulfonylurea-resistant permanent neonatal diabetes and developmental delay (intermediate DEND). Functional analysis of recombinant KATP channels reveals that this mutation causes a drastic gain-of-function, due to a reduction in ATP inhibition. Further, we demonstrate that the Tyr330His substitution causes a significant decrease in sensitivity to the sulfonylurea, glibenclamide. Conclusions: In this subject, the KCNJ11 (c.988T>C) mutation provoked neonatal diabetes, with mild developmental delay, which was insensitive to correction by sulfonylurea therapy. This is explained by the molecular loss of sulfonylurea sensitivity conferred by the Tyr330His substitution and highlights the need for molecular analysis of such mutations.
Lightweight hardware fingerprinting solution using inherent memory in off-the-shelf commodity devices
Authors: Mispan Mohd Syafiq , Jidin Aiman Zakwan , Kamarudin Muhammad Raihaan , Nasir Haslinah Mohd
Published: January 2022

An emerging technology known as Physical unclonable function (PUF) can provide a hardware root-of-trust in building the trusted computing system. PUF exploits the intrinsic process variations during the integrated circuit (IC) fabrication to generate a unique response. This unique response differs from one PUF to the other similar type of PUFs. Static random-access memory PUF (SRAM-PUF) is one of the memory-based PUFs in which the response is generated during the memory power-up process. Non-volatile memory (NVM) architecture like SRAM is available in off-the-shelf microcontroller devices. Exploiting the inherent SRAM as PUF could wide-spread the adoption of PUF. Therefore, in this study, we evaluate the suitability of inherent SRAM available in ATMega2560 microcontroller on Arduino platform as PUF that can provide a unique fingerprint. First, we analyze the start-up values (SUVs) of memory cells and select only the cells that show random values after the power-up process. Subsequently, we statistically analyze the characteristic of fifteen SRAM-PUFs which include uniqueness, reliability, and uniformity. Based on our findings, the SUVs of fifteen on-chip SRAMs achieve 42.64% uniqueness, 97.28% reliability, and 69.16% uniformity. Therefore, we concluded that the available SRAM in off-the-shelf commodity hardware has good quality to be used as PUF.
Segregation of oil palm fruit ripeness using color sensor
Authors: Mustaffa Aiman , Arith Faiz , Peong Nurin Izzati Fauzi , Jaffar Nurul Rafiqah , Linggie Evelyn Larwy , Mustafa Ahmad Nizamuddin , Ali Fara Ashikin
Published: January 2022

Oil palm is an important industry that has contributed to income and support to the economic sector especially for Malaysia and Indonesia. However, most of the equipment in the oil palm industry is still operated manually. This work developed a system to separate bunches of oil palm fruit using color sensors according to maturity level. Fruit color plays a decisive point in determining fruit maturity. Here, a specific threshold point of red green blue (RGB) was obtained for the determination of the maturity level of oil palm fruit. Point values of < 120, 120 < x < 150 and > 150 represent the maturity levels of unripe, under ripe and ripe, respectively. This paper is the first to report the RGB points for use in the development of automated oil palm segregation system in the oil palm plantation industry. Thus, this paper will pave the way in producing an accurate and reliable oil palm separation system, which in turn has a positive effect in reducing human error. In the future, a set of sensors is proposed to detect a bunch of the oil palm fruits. This further can speed up the segregation process and more suitable for adaptation to the industry.
Characterization of silicon tunnel field effect transistor based on charge plasma
Authors: Abdul-kadir Firas Natheer , Taha Faris Hassan
Published: January 2022

The aim of the proposed paper is an analytical model and realization of the characteristics for tunnel field-effect transistor (TFET) based on charge plasma (CP). One of the most applications of the TFET device which operates based on CP technique is the biosensor. CP-TFET is to be used as an effective device to detect the uncharged molecules of the bio-sample solution. Charge plasma is one of some techniques that recently invited to induce charge carriers inside the devices. In this proposed paper we use a high work function in the source (ϕ=5.93 eV) to induce hole charges and we use a lower work function in drain (ϕ=3.90 eV) to induce electron charges. Many electrical characterizations in this paper are considered to study the performance of this device like a current drain (ID) versus voltage gate (Vgs), ION/IOFF ratio, threshold voltage (VT) transconductance (gm), and sub-threshold swing (SS). The signification of this paper comes into view enhancement the performance of the device. Results show that high dielectric (K=12), oxide thickness (Tox=1 nm), channel length (Lch=42 nm), and higher work function for the gate (ϕ=4.5 eV) tend to best charge plasma silicon tunnel field-effect transistor characterization.
Hunting strategy for multi-robot based on wolf swarm algorithm and artificial potential field
Authors: Hamed Oussama , Hamlich Mohamed , Ennaji Mohamed
Published: January 2022

The cooperation and coordination in multi-robot systems is a popular topic in the field of robotics and artificial intelligence, thanks to its important role in solving problems that are better solved by several robots compared to a single robot. Cooperative hunting is one of the important problems that exist in many areas such as military and industry, requiring cooperation between robots in order to accomplish the hunting process effectively. This paper proposed a cooperative hunting strategy for a multi-robot system based on wolf swarm algorithm (WSA) and artificial potential field (APF) in order to hunt by several robots a dynamic target whose behavior is unexpected. The formation of the robots within the multi-robot system contains three types of roles: the leader, the follower, and the antagonist. Each role is characterized by a different cognitive behavior. The robots arrive at the hunting point accurately and rapidly while avoiding static and dynamic obstacles through the artificial potential field algorithm to hunt the moving target. Simulation results are given in this paper to demonstrate the validity and the effectiveness of the proposed strategy.
A YOLO and convolutional neural network for the detection and classification of leukocytes in leukemia
Authors: Abas Shakir Mahmood , Abdulazeez Adnan Mohsin , Zeebaree Diyar Qader
Published: January 2022

The developing of deep learning systems that used for chronic diseases diagnosing is challenge. Furthermore, the localization and identification of objects like white blood cells (WBCs) in leukemia without preprocessing or traditional hand segmentation of cells is a challenging matter due to irregular and distorted of nucleus. This paper proposed a system for computer-aided detection depend completely on deep learning with three models computer-aided detection (CAD3) to detect and classify three types of WBC which is fundamentals of leukemia diagnosing. The system used modified you only look once (YOLO v2) algorithm and convolutional neural network (CNN). The proposed system trained and evaluated on dataset created and prepared specially for the addressed problem without any traditional segmentation or preprocessing on microscopic images. The study proved that dividing of addressed problem into sub-problems will achieve better performance and accuracy. Furthermore, the results show that the CAD3 achieved an average precision (AP) up to 96% in the detection of leukocytes and accuracy 94.3% in leukocytes classification. Moreover, the CAD3 gives report contain a complete information of WBC. Finally, the CAD3 proved its efficiency on the other dataset such as acute lymphoblastic leukemia image database (ALL-IBD1) and blood cell count dataset (BCCD).
Design secure multi-level communication system based on duffing chaotic map and steganography
Authors: Abd Aliaa Sadoon , Hussein Ehab Abdul Razzaq
Published: January 2022

Cryptography and steganography are among the most important sciences that have been properly used to keep confidential data from potential spies and hackers. They can be used separately or together. Encryption involves the basic principle of instantaneous conversion of valuable information into a specific form that unauthorized persons will not understand to decrypt it. While steganography is the science of embedding confidential data inside a cover, in a way that cannot be recognized or seen by the human eye. This paper presents a high-resolution chaotic approach applied to images that hide information. A more secure and reliable system is designed to properly include confidential data transmitted through transmission channels. This is done by working the use of encryption and steganography together. This work proposed a new method that achieves a very high level of hidden information based on non-uniform systems by generating a random index vector (RIV) for hidden data within least significant bit (LSB) image pixels. This method prevents the reduction of image quality. The simulation results also show that the peak signal to noise ratio (PSNR) is up to 74.87 dB and the mean square error (MSE) values is up to 0.0828, which sufficiently indicates the effectiveness of the proposed algorithm.
Elliptical curve cryptography image encryption scheme with aid of optimization technique using gravitational search algorithm
Authors: Navatejareddy Ramireddy , Jayabhaskar Muthukuru , Sathyanarayana Bachala
Published: January 2022

Image encryption enables users to safely transmit digital photographs via a wireless medium while maintaining enhanced anonymity and validity. Numerous studies are being conducted to strengthen picture encryption systems. Elliptical curve cryptography (ECC) is an effective tool for safely transferring images and recovering them at the receiver end in asymmetric cryptosystems. This method's key generation generates a public and private key pair that is used to encrypt and decrypt a picture. They use a public key to encrypt the picture before sending it to the intended user. When the receiver receives the image, they use their private key to decrypt it. This paper proposes an ECC-dependent image encryption scheme utilizing an enhancement strategy based on the gravitational search algorithm (GSA) algorithm. The private key generation step of the ECC system uses a GSA-based optimization process to boost the efficiency of picture encryption. The image's output is used as a health attribute in the optimization phase, such as the peak signal to noise ratio (PSNR) value, which demonstrates the efficacy of the proposed approach. As comparison to the ECC method, it has been discovered that the suggested encryption scheme offers better optimal PSNR values.
A comparative study for the assessment of Ikonos satellite image-fusion techniques
Authors: Medina Javier , Vera Nelson , Upegui Erika
Published: January 2022

IImage-fusion provide users with detailed information about the urban and rural environment, which is useful for applications such as urban planning and management when higher spatial resolution images are not available. There are different image fusion methods. This paper implements, evaluates, and compares six satellite image-fusion methods, namely wavelet 2D-M transform, gram schmidt, high-frequency modulation, high pass filter (HPF) transform, simple mean value, and PCA. An Ikonos image (Panchromatic-PAN and multispectral-MULTI) showing the northwest of Bogotá (Colombia) is used to generate six fused images: MULTIWavelet 2D-M, MULTIG-S, MULTIMHF, MULTIHPF, MULTISMV, and MULTIPCA. In order to assess the efficiency of the six image-fusion methods, the resulting images were evaluated in terms of both spatial quality and spectral quality. To this end, four metrics were applied, namely the correlation index, erreur relative globale adimensionnelle de synthese (ERGAS), relative average spectral error (RASE) and the Q index. The best results were obtained for the  MULTISMV image, which exhibited spectral correlation higher than 0.85, a Q index of 0.84, and the highest scores in spectral assessment according to ERGAS and RASE, 4.36% and 17.39% respectively.
Reference-free differential histogram-correlative detection of steganography: performance analysis
Authors: Abdali Natiq M. , Hussain Zahir M.
Published: January 2022

Recent research has demonstrated the effectiveness of utilizing neural networks for detect tampering in images. However, because accessing a database is complex, which is needed in the classification process to detect tampering, reference-free steganalysis attracted attention. In recent work, an approach for least significant bit (LSB) steganalysis has been presented based on analyzing the derivatives of the histogram correlation. In this paper, we further examine this strategy for other steganographic methods. Detecting image tampering in the spatial domain, such as image steganography. It is found that the above approach could be applied successfully to other kinds of steganography with different orders of histogram-correlation derivatives. Also, the limits of the ratio stego-image to cover are considered, where very small ratios can escape this detection method unless  modified.
Feature extraction to predict quality of segregating sweet tamarind using image processing
Authors: Tangwannawit Panana , Tangwannawit Sakchai
Published: January 2022

In this modern age, several new methods have been developed, especially in image processing for agriculture business, which consists of technologies derived from artificial intelligence (AI) capabilities called machine learning. Classify is a widely used method to analyze patterns, trends, as well as the body of knowledge from the data visualization. Image classification application improves discrimination and prediction efficiency. The objective of this research was to feature extraction of sweet tamarind and compare the algorithm for classification. This research used images from golden sweet tamarind species with the use of MATLAB and Python language. The steps of this research consisted of 1) preprocessing step for finding the distance to appropriate of the image quality, 2) feature extracting for finding the number of black pixels and the number of white pixels, perimeter, diameter, and centroid, and 3) classifying for algorithms' comparison. The results showed that the camera's distance to the image was 60 cm. The coefficient of determination was at 0.9956, and the Standard Error of Estimate was 7,424.736 pixels. The conclusion of classification found that the random forest had the highest accuracy at 92.00%, SD. = 8.06, precision = 90.12, recall = 92.86, and F1-score = 91.36.
Comparative study of low power wide area network based on internet of things for smart city deployment in Bandung city
Authors: Nashiruddin Muhammad Imam , Sihotang Maruli Tua Baja , Murti Muhammad Ary
Published: January 2022

Smart city implementation, such as smart energy and utilities, smart mobility & transportation, smart environment, and smart living in urban areas is expanding rapidly worldwide. However, one of the biggest challenges that need to be solved is the selection of the appropriate internet of things (IoT) connectivity technologies. This research will seek for the best candidate low power wide area network (LPWAN) technologies such as long-range wide area network (LoRaWAN), narrow-band internet of things (NB-IoT), and random phase multiple access (RPMA) for IoT smart city deployment in Bandung city is based on IoT network connectivity between with six technical evaluation criteria: gateway requirements, traffic/data projection, the best signal level area distribution, and overlapping zones. Bass model is carried out to determine the capacity forecast. While in coverage prediction, LoRaWAN and NB-IoT use the Okumura-Hata propagation, and Erceg-Greenstein (SUI) model is used for RPMA. Based on the simulation and performance evaluation results, RPMA outperforms LoRaWAN and NB-IoT. It required the least gateway number to cover Bandung city with the best signal levels and overlapping zones.
Employing opposite ratings users in a new approach to collaborative filtering
Authors: Fazziki Abdellah El , Alami Yasser El Madani El , Elhassouni Jalil , Aissaoui Ouafae El , Benbrahim Mohammed
Published: January 2022

Over the past few decades, various recommendation system paradigms have been developed for both research and industrial purposes to satisfy the needs and preferences of users when they deal with enormous data. The collaborative filtering (CF) is one of the most popular recommendation techniques, although it is still immature and suffers from some difficulties such asparsity, gray sheep and scalability impeding recommendation quality. Therefore, we propose a new CF approach to deal with the gray sheep problem in order to improve the predictions accuracy. To realize this goal, our solution aims to infer new users from real ones existing in datasets. This transformation allows for creating users with opposite preferences to the real ones. On the one hand, our approach permits to amplify the number of neighbors, especially in the case of users who have unusual behavior (gray sheep). On the other hand, it facilitates building a dense similar neighborhood. The basic assumption behind this is that if user X is not similar to user Y, then the imaginary user ¬X is similar to the user Y. The performance of our approach was evaluated using two datasets, MovieLens and FilmTrust. Experimental results have shown that our approach surpasses many traditional recommendation approaches.
Development of computer-based learning system for learning behavior analytics
Authors: Phodong Kanyalag , Supnithi Thepchai , Kongkachandra Rachada
Published: January 2022

This paper aims to analyze the learning behavior of Thai learners by using a computer-based learning system for English writing. Three main objectives were set: the development of a computer-based learning system, automatic behavior data collection, and learning behavior analytics. Firstly, the system is developed under a multidisciplinary idea that is designed to integrate two concepts between the self-regulated learning model and components of natural language processing. The integration design encourages self-learning in the digital learning environment and supports appropriate English writing by the provided component selection. Second, the system automatically collects the writing behavior of a group of Thai learners. The data collected are necessary input for the process of learning analytics. Third, the writing behaviors data were analyzed to find the learning behavioral patterns of the learners. For learning analytics, behavior sequential analysis was used to analyze the learning logs from the system. The 31 undergraduate students are participated to record writing behaviors via the system. The learning patterns in relation to grammatical skills were compared between three groups: basic, intermediate, and advanced levels. The learning behavior patterns of the three groups are different that use for reflecting learners and improving the learning materials or curriculum.
Systematic literature review on university website quality
Authors: Saleh Ala' Hasan , Yusoff Rasimah Che Mohd , Bakar Nur Azaliah Abu , Ibrahim Roslina
Published: January 2022

Website is a necessity for organizations to enable users worldwide to access their information and gain a competitive edge over others. The diversity of websites makes assessing website quality a difficult task. The aim of this paper is to identify the issues faced in the quality evaluation of university websites, the models and the factors used for evaluating university website quality. Systematic literature review was used to identify and synthesize related scholarly research papers. Findings show that there is a lack of study on university website quality compared to business websites; website designers did not have the appropriate knowledge on the interface design; and the website quality evaluation is complex since there is no specific evaluation model. Webqual 4.0 model was used to evaluate the quality of universities' websites. From 24 studies, initially 79 quality factors were extracted. After performing comparison, filtration and memoing, six quality factors were identified: information quality, specific content, usability, web appearance, service interaction quality, and functionality. This study makes a useful contribution in developing university website quality model by extending the Webqual 4.0 model.
K-NN supervised learning algorithm in the predictive analysis of the quality of the university administrative service in the virtual environment
Authors: Chamorro-Atalaya Omar Freddy , Romero Guillermo Morales , Andía Adrián Quispe , Salas Beatriz Caycho , Ramos Elizabeth Katerin Auqui , Salazar Primitiva Ramos , Huaraca Carlos Palacios
Published: January 2022

The objective of this study is to analyze and discuss the metrics of the predictive model using the K-nearest neighbor (K-NN) learning algorithm, which will be applied to the data on the perception of engineering students on the quality of the virtual administrative service, such as part of the methodology was analyzed the indicators of accuracy, precision, sensitivity and specificity, from the obtaining of the confusion matrix and the receiver operational characteristic (ROC) curve. The collected data were validated through Cronbach's Alpha, finding consistency values higher than 0.9, which allows to continue with the analysis. Through the predictive model through the Matlab R2021a software, it was concluded that the average metrics for all classes are optimal, presenting a precision of 92.77%, sensitivity 86.62%, and specificity 94.7%; with a total accuracy of 85.5%. In turn, the highest level of the area under the curve (AUC) is 0.98, which is why it is considered an optimal predictive model. Having carried out this study, it is possible to contribute significantly to the decision-making of the higher institution in relation to the improvement of the quality of the virtual administrative service.
Intelligent aquaculture system for pisciculture simulation using deep learning algorithm
Authors: Sapin Sherwin B. , Alibudbud Bryan A. , Molleno Paulo B. , Veluz Maureen B. , Asor Jonardo R.
Published: January 2022

The project aims to develop an intelligent system for simulating pisciculture in Taal Lake in the Philippines through geographical information system and deep learning algorithm. Records of 2018-2020 from the database of Bureau of fisheries and aquatic resources IV-A-protected area management board (BFAR IVA-PAMB) was collected for model development. Deep learning algorithm model was developed and integrated to the system for time series analysis and simulation. Different technologies including tensorflow.js were used to successfully developed the intelligent system. It is found on this paper that recurrent neural network (RNN) is a good deep learning algorithm for predicting pisciculture in Taal lake. Further, it is also shown in the initial visualization of the system that barangay Sampaloc in Taal has highest rate of fish production in Taal while Tilapia nilotica sp. is the major product of the latter.
Sliding mode control with observer for permanent magnet synchronous machine drives
Authors: Razali Muhammad Haziq Nashren , Lazi Jurifa Mat , Ibrahim Zulkifilie , Talib Md Hairul Nizam , Patakor Fizatul Aini
Published: January 2022

This paper aims to develop the sliding mode control (SMC) scheme in sensorless permanent magnet synchronous machine (PMSM) drives to replace conventional proportional integral (PI) speed control. The SMC is formulated based on the integral sliding surface of the speed error. And the error is corrected based on the concept of Lyapunov stability. The SMC is designed with the load torque observer so that the disturbance can be estimated as feedback to the controller. The vector control technique which is also known as field-oriented control (FOC) is also used to split the stator current into the magnetic field generating part which is the direct axis and the torque generating part which is the quadrature axis. This can be done by using Park and Clarke transformations. The performance of the proposed SMC is tested under changes in load-torque and without load for different speed commands. The results prove that the SMC produces robust performances under variations of speeds and load disturbances. The effectiveness of the proposed method is verified and simulated by using MATLAB/SIMULINK software.
Phenol Coefficient Test Combination Infusion of Cananga odorata – Averrhoa bilimbi L. Against Staphylococcus aureus and Salmonella typhi in Vitro
Authors: Budiarti Lia Yulia , Wydiamala Erida , Ulfa Najiya
Published: January 2022

Cananga odorata (kenanga) flowers and Averrhoa bilimbi L. (belimbing wuluh) fruit are plant parts that contain relatively the same antibacterial compounds, namely flavonoids, saponins, and tannins. Both of these plants can be developed as an alternative natural antiseptic preparation, which is made in the form of a combination infusion. The effectiveness of an antiseptic preparation is measured by the coefficient value of the phenol antiseptic substance compared to 5% phenol against several standard test bacteria. This study aims to determine the antibacterial activity of the combination infusion of Cananga odorata flower - Averrhoa bilimbi L. fruit against Staphylococcus aureus ATCC 25923 and Salmonella typhi ATCC 19430 based on the in vitro phenol coefficient test. The phenol coefficient test method was carried out conventionally. The coefficient value close to 1 can be said that the antiseptic preparation has good activity and is equivalent to the phenol coefficient value as a comparison. The results showed that the mean coefficient of the phenol coefficient of the combination infusion of Cananga odorata flower - Averrhoa bilimbi L. fruit was 0.91 against S. aureus and 0.83 against S. typhi. The conclusion of this study, the antibacterial activity of the combination infusion of Cananga odorata flower - Averrhoa bilimbi L. fruit against Staphylococcus aureus obtained a higher phenol coefficient value than Salmonella typhi.