bluuebunny/crossref_metadata_2025 huggingface dataset:
Prediction of Concrete Compressive Strength Based on the BP Neural Network Optimized by Random Forest and ISSA
Authors: Chen Gang , Zhu Donglin , Wang Xiao , Zhou Changjun , Chen Xiangyu
Published: August 2022

In modern engineering construction, the compressive strength of concrete determines the safety of engineering structure. BP neural network (BPNN) tends to converge to different local minimum points, and the prediction accuracy is not high in the prediction of the compressive strength of concrete. Therefore, a prediction model based on the BPNN optimized by improved sparrow search algorithm (ISSA) and random forest (RF) is proposed to enhance the generalization ability and prediction accuracy of BPNN for compressive strength of concrete. In terms of algorithm improvement, three improvements are proposed for SSA: Latin hypercube sampling is introduced to initialize the location of sparrows and increase the diversity of sparrows; the somersault foraging strategy is used to enrich the optimal position of producers; and combining with the cyclone foraging mechanism, the position updating process of the scroungers is optimized to obtain a better foraging position. In terms of performance evaluation of the algorithm, the ablation experiment verifies that the three improved strategies have improved effects in SSA, and the performance of ISSA on the CEC2017 benchmark function is better than other peers. In terms of predictive index screening, the important features are selected as the input variables of the model by random forest. The prediction results show that compared with the RF-BPNN model and models optimized by other algorithms, RF-ISSA-BPNN model has the lowest prediction error, and the expected value fits the real value better.
[Retracted] Roles of International Environmental Law in China’s Environmental Productivity: Challenges and Implications
Authors: Tang Niyan
Published: August 2022

International environmental law is the basic charter for dealing with international environmental issues, and it plays an important role in international environmental governance. In recent years, China’s economy has achieved great development, but environmental problems are also very prominent. International environmental law provides a basic reference for China’s environmental governance, but it also brings challenges to the development of China’s environmental productivity to a certain extent. At the same time, due to the unique dominant position of international environmental law, it has played a certain restrictive role in the development of China’s environmental productivity. Based on this, in order to promote the sustainable development of China’s economy, this paper took China’s industrial and agricultural development as the research object. This paper has conducted research on China’s industrial and agricultural environmental productivity, aiming to explore the role of international environmental law in China’s environmental productivity. The article first analyzed the limitation of international environmental law on China’s environmental productivity, and then on this basis, the article conducted a numerical simulation of China’s industrial and agricultural environmental productivity. Finally, starting from the actual development situation, the paper aimed to find out the numerical deviation of China’s environmental productivity changes through quantitative analysis. In the course of the research on environmental productivity development, the article found a strong correlation between environmental productivity and international environmental law in China. The correlation between environmental productivity and international environmental law reaches 59.93% in South China and 61.02% in North China. Also, after a series of comparative analyses, the article finds that changes in climate characteristics can exacerbate the regulation of China by international environmental law and seriously affect China’s economic development. In this case, China’s economy declined by 2.6% year‐on‐year, which further pushed China to practice sustainable development strategies. This shows that it is essential to study the relationship between international environmental law and China’s environmental productivity.
Fractional Derivative and Optimal Control Analysis of Cholera Epidemic Model
Authors: Cheneke Kumama Regassa , Rao Koya Purnachandra , Edessa Geremew Kenassa
Published: August 2022

In this study, a cholera model with fractional derivative and optimal control analysis is presented. Numerical simulation analysis shows that increasing the order of fractional derivatives contributes to updating the memory of the population to control the effects of cholera infection through available controlling techniques. On the other hand, the optimal analysis gives an indication of applying controlling infection with available treatment and prevention techniques. It provides a better mechanism to prevent the happening of cholera infection. Moreover, cost‐effectiveness evaluation of cholera contamination intervention with feasible three or four combos of manipulate measures hygiene, vaccination, remedy of infectives, and chlorination indicates that hygiene, vaccination, and chlorination are the desired higher mixture to govern in addition propagation of cholera contamination. Numerical simulations are performed with the MATLAB platform and numerical solutions and results are discussed.
Well-Distributed Polysilsesquioxane-Modified Carbon Nanotubes for Thermal Conductive Insulating Silicone Rubbers
Authors: Han Long , Wang Zhaobo , Hua Jing , Geng Jieting
Published: August 2022

Despite carbon nanotubes (CNTs) have garnered tremendous research interests for enhancing the electrical and thermal conductivity of polymers, it is still a considerable challenge to achieve the uniform dispersion of carbon nanotubes in polymer matrix. Herein, inspired by the mussel-inspired chemistry, we adopted the strategy of coating CNTs with polydopamine. And the polysilsesquioxane-modified CNTs (CNTs-PSQ) were obtained based on the click chemistry reaction. The FT-IR, Raman, XRD, and TGA collectively demonstrated the successful modification of PSQ on the surface of CNTs. The incorporation of PSQ could significantly improve the dispersion of CNTs in the silicon rubbers, and a strong interfacial interaction was formed between CNTs-PSQ and silicon rubber matrix, as observed from TEM images of silicon rubber/CNTs-PSQ nanocomposites. Meanwhile, compared with the nanocomposites with neat CNTs, the ones with CNTs-PSQ exhibited simultaneously improved electrical conductivity and insulating performance. This strategy proposed for the preparation of PSQ-modified CNTs provides insights toward highly insulating and thermal conducting polymers.
Intelligent Scanning Detection System of Muscle Exercise Fatigue Based on Surface Electromyography
Authors: Wang Weiqi
Published: August 2022

In order to use the surface EMG signal to automatically detect the muscle fatigue state, a research method of the muscle exercise fatigue intelligent scanning detection system based on surface EMG was proposed, and the sEMG signal features of 10 subjects before and after fatigue were extracted. A time-varying parameter autoregressive model is established. By introducing the Legendre basis function, the parameter identification of the linear nonstationary process is transformed into the parameter identification of the linear time-invariant system. Combined with the correlation index, the optimal Legendre base function dimension of the time-varying system parameter estimation can be obtained, then the best model fitting effect can be obtained, and the time-invariant parameters are solved by the least square method. Using the rate of change of the first time-varying parameter (ARC1) of the autoregressive model before and after fatigue as an index to detect muscle fatigue sensitivity, a two-tailed

t

test was used to compare the mean power frequency (MPF) and the median frequency (MF) with the rate of change. The results showed that the change rates of ARC1, MPF, and MF before and after fatigue were

34.33
%
±
2.5
%

,

68
%
+
2.03
%

, and

22.80
%
+
2.19
%

, which were 41% and 25%, respectively. The rate of change of ACR1 was significantly higher than that of MPF and MF (

P
<
0.05

). When detecting muscle fatigue by sEMG signal, it has the advantages of short time and high sensitivity. It can be used for online real-time analysis of muscle fatigue, providing a potential analysis tool for limb muscle strain, rehabilitation, and ergonomics assessment.
Application of Probabilistic Random Matrix Management Mode in Student Information Management for Higher Education
Authors: Sun Yongqiang
Published: August 2022

Traditional management method of student information is not only slow in operation, poor in confidentiality, and low in work efficiency, but also prone to statistical errors and data loss, which can no longer meet the needs of new situations. Probabilistic random matrix management mode can effectively coordinate the development of various businesses and strengthen their information flow through horizontal and vertical management across functional departments. On the basis of summarizing and analyzing previous literature, this study expounded the research status and significance of student information management of higher education, elaborated the development background, current status, and future challenges of probabilistic random matrix management mode, introduced the methods and principles of probabilistic matrix factorization algorithm and random matrix factorization model, discussed the service and supervision functions of student information management, analyzed the incentive and guiding functions of student information management, conducted the process analysis of student information management for higher education based on probabilistic random matrix management mode, established student identity document and student status management modules, designed student scholarship, statistics, and data management modules, constructed a student information management system for higher education based on probabilistic random matrix management mode, and finally carried out a case application and its result analysis. The study results show that the probabilistic random matrix management mode is a combination of linear and flat organizational structures and has the advantages of short information lines, fast information feedback, and high operation efficiency; it can input the matrix form of prior data and use statistical probability knowledge to derive the probability density function of posterior feature vector and predict the recommendation result through feature vector. The probabilistic random matrix management mode first calculates student’s behavior sequence through their management information and then calculates the student’s preference sequence according to their behavior sequence and label information and subsequently calculates the similarity matrixes about the students and their information and finally integrates the obtained student similarity matrix into the probabilistic matrix factorization model.
Efficacy Evaluation of Inflammatory Mediators in the Treatment of Multiple Myeloma with Daratumumab
Authors: Meng Jie , Zhao Xiaoyu , Jiang Duanfeng , Liang Changjiu , Ji Xunxiu , Dong Min
Published: August 2022

Objective. This study aimed to investigate the regulatory ability and clinical therapeutic effect of daratumumab on inflammatory mediators in patients with multiple myeloma. Method. The Multiple Myeloma Public Genetic Data Array download GSE125361 dataset was collected. The GO analysis and KEGG analysis were performed on the differential genes to elucidate the multiple myeloma cytokine-related gene pathways. Daratumumab is a CD38 monoclonal antibody used to treat multiple myeloma. Patients with newly diagnosed multiple myeloma were treated with monoclonal antibodies containing CD38, and the control group was treated with a regimen without daratumumab. The serum levels of IL-2, IL-4, IL-6, IL-10, TNF-α, and IFN-γ were measured in the two groups before and after treatment and the therapeutic effects of the two groups were compared. Result. The KEGG analysis showed that the Th17 cell differentiation, apoptosis, and cytokine-cytokine receptor interaction pathways were differentially expressed in multiple myeloma. The expression levels of serum IL-2, IL-6, IL-10, and TNF-α in patients in the daratumumab group were lower than those in the control group after chemotherapy. The overall effective rate of patients treated with daratumumab after chemotherapy was higher than that of the control group. Conclusion. Daratumumab can effectively improve the levels of IL-2, IL-6, IL-10, and TNF-α in patients with multiple myeloma and improve the therapeutic effect.
Effect of Cultivar and Planting Date on Soybean Response to Dicamba
Authors: France Wesley , Norsworthy Jason , Roberts Trent , Ross Jeremy , Barber Tom , Gbur Edward
Published: August 2022

Off-target movement of dicamba has been blamed for damaging millions of hectares of soybean in the United States since registration of the herbicide for use in dicamba-resistant cotton and soybean. Understanding the effect of a low dose of dicamba on non-dicamba-resistant soybean across multiple cultivars, growth stages, and planting dates could help producers better understand the implication of current management practices on yield loss from dicamba in fields where non-dicamba-resistant soybean are grown. A field experiment was conducted in 2019 in Fayetteville and Stuttgart, Arkansas, to evaluate the impact of planting date on response of soybean to a low dose of dicamba. The hypothesis of the planting date experiment was that soybean injury and yield loss will differ depending on planting date and dicamba application timing. Additionally, an experiment was conducted in 2018 and 2019 in Fayetteville to assess whether cultivars differ in sensitivity to dicamba. The hypothesis of the cultivar experiment was that genetic differences of soybean cultivars will allow for differential tolerance to dicamba. In the cultivar experiment, “Eagle DrewSoy” was identified as having enhanced tolerance to dicamba based on reduced injury (47% at R1 and 26% at V3) over both experimental years and locations. Soybean height in this experiment was affected only by application timing. In the planting date experiment, planting after mid-June resulted in reduced yields from dicamba injury. Dicamba exposure reduced yield at the July planting date (61% reduction from nontreated) more severely when compared to dicamba-treated plots of other planting dates (94% average relative yield among other planting dates), indicating that the negative effects of dicamba are increasingly deleterious for soybean planted later in the growing season. Maximum injury manifestation was generally delayed at later planting dates, indicating that dicamba may have been metabolized more slowly.
Nonheritage Creative Product Design and Development and Marketing Strategies for Computer Vision and User Experience
Authors: Liu Chunyan , Pan Zhenzhen , Zhang Canlin , Miao Wei
Published: August 2022

With the rapid development of economic and culture, intangible cultural heritage has gradually moved towards the public, and at the same time, many cultural and creative products have been derived. In the face of fierce market competition, nonheritage and creative products gradually occupied a certain market share with their unique cultural heritage and won the love of some consumers. However, at the same time, the development of nonheritage and creative products cannot keep up with the market that is changing with each other, and the design and development of cultural and creative products are far behind market changes. Moreover, the recognition of some consumers cannot improve the booming development of nonheritage creative products, and the future development of nonheritage and creative products is facing a serious crisis. Computer vision has absolute advantages in image processing, which can help nonheritage products for development and design, and further improve the quality of the product. In the process of designing and developing a certain product, our commonly used research method is user experience. User experience strategies can help us design cultural and creative products that fit the characteristics of the times from the perspective of consumers. This article introduces the basic architecture and guidelines of the user experience strategy. In addition, the main research object of this article is nonheritage and creative products, which aims to explore how to use various design thinking methods to develop more valuable products. On this basis, this article integrates computer vision technology in the process of designing and development of nonheritage cultural and creative products and supplemented by user experience strategies to further innovate the design concept of cultural and creative products. Experiments show that the design and development of intangible cultural heritage products based on computer vision and user experience can effectively improve product quality, and the product qualification rate basically reaches 90%. At the same time, this move can further stimulate consumers' desire to purchase, and their purchase intention can reach up to 72%.
Cost-Effectiveness of Intravenous Iron Formulations in Patients with Iron Deficiency Anaemia and Inflammatory Bowel Disease, in a Swedish Regional Setting Using Real-World Tender Prices
Authors: Ramirez de Arellano Antonio , Norton Nicholas , Enkusson Dana , Oldsberg Linnea , Thomson Yvonne , Lilja Mathias , Aksan Aysegül
Published: August 2022

Aims. A widespread complication of inflammatory bowel disease (IBD) is iron deficiency anaemia (IDA), which affects quality of life (QoL) and is associated with frequent hospitalizations. The intravenous iron therapies, ferric carboxymaltose (FCM), ferric derisomaltose (FD), and iron sucrose (IS), have previously been shown to replenish haemoglobin (Hb) levels more effectively than oral iron. However, they differ in both costs and efficacy (response to treatment), leading to differences in acquisition by health-care payers. We investigated the cost-effectiveness of FCM versus FD and IS, in terms of additional cost per additional responder, for the treatment of IBD-associated IDA in multiple Swedish regional settings, using current tender prices. Methods and Materials. A microsimulation model estimated the additional cost per patient achieving a response, based on Hb normalization or an increase of ≥2 g/dL in Hb levels. Efficacy estimates were taken from a previously published network meta-analysis. Treatment costs (2021 SEK) included current tender prices in Swedish health-care regions. Resource use depended partly on dosing, which was based on patient characteristics simulated in the model. Results. The analysis showed that FCM was associated with the highest number of responders (81%) compared to FD (74%) and IS (75%), while costing less per responder than its comparators, in included regions. Conclusions. These results suggest that regional health-care budget holders should consider more than drug prices when choosing which IV formulations to acquire and that they should use all available tools when deciding how to fulfil the needs of their patients.
Investigation of electricity load shifting under various tariff design using ant colony optimization algorithm
Authors: Sulaima Mohamad Fani , Baharin Nurliyana Binti , Kadir Aida Fazliana Abdul , Obtained Norhafiz Bin Salim , Hassan Elia Erwani
Published: August 2022

A price-based program through a time of use tariff (TOU) program is one of the initiatives to offer sufficient benefit for both consumers and generations sides. However, without any strategy for implementing optimal load management, a new tariff design structure will lead to the miss perception by electricity consumers. Therefore, this study offers an investigation toward appropriate TOU tariff design to reflect load profiles. Concurrently, the ant colony optimization (ACO) algorithm was proposed to deal with the load shifting strategy to determine the best load profiles and reducing the consumers’ electricity cost. The sample load profiles data is obtained from various residential houses, such as single-story, double-story, semi-D, apartment, and bungalow houses. The significant comparison between baseline flat tariffs to several TOU tariffs has shown an improvement in the percentage of cost saving for approximately 7 to 40%. Furthermore, the identified load management was observed where the maximum load shifting weightage was set up to 30% to reflect the consumers’ effort towards energy efficiency (EE) program. The previously proposed TOU design was identified to be a suitable structure that can promote balancing of EE and demand response (DR) program effort in most consumers' houses category in Malaysia.
Estimation of channel distortion in orthogonal frequency division multiplexing system using pilot technique
Authors: Mary Joseph Nisha , Puttamadappa C.
Published: August 2022

Orthogonal frequency-division multiplexing (OFDM) is resistant to frequency selective fading due to the longer symbol duration. However, mobile applications channel timing fluctuations in one OFDM signal cause intercarrier-interference (ICI), which reduces performance. This research presented the support vector regression (SVR) model-based channel estimation technique for coherent optical communication systems. Due to the coherent optical orthogonal frequency-division-multiplexed (COOFDM) system, a channel model is developed that includes linear fibre dispersion effects, noise from optical amplifiers, and inter-carrier interference generated by laser phase noise. As a result, for such a system, an accurate channel estimate is essential. Based on this concept, derivation of channel estimation and phase estimation for the system of CO-OFDM. The proposed method is tested and evaluated using MATLAB software. Computer simulation results for several standard methods such as extreme learning machines (ELM) and artificial neural networks (ANN) validate the feasibility of the suggested methodology. The CO-OFDM system’s transmission experiments and computer simulations prove that the support vector machine-based model following pilot-assisted phase estimation gives the optimal performance. Therefore, results depicted that the channel estimation utilizing the SVR model gives good performance than the other methods, thus the proposed model gives an accurate CE process, respectively.
Monitoring system of photovoltaic panels using 433 MHz radio frequency module
Authors: Didi Zaidan , El Azami Ikram
Published: August 2022

In this article, we presented an innovative study that allows direct monitoring of the main parameters of photovoltaic panels. Our study focuses on the skills of radio frequency modules to send the main parameters of photovoltaic cells. In this paper, we used an Esp32 microcontroller in the radio frequency (RF) transmitter block and an Arduino Uno board in the receiver block, in addition, to measure current, we used a current sensor, and to measure voltage, we implemented a voltage divider. After that, we calculated the power and the energy. Note that the various measured and calculated values are stored and used via the ThingSpeak platform. In comparison with similar studies, our achievement presents an` effective and inexpensive solution because its operating principle is based on radio frequency transmission, so it works perfectly even in the absence of the internet. Finally, our study was very well tested without detecting any abnormalities, and the results obtained are a perfect witness to our success.
Fuzzy based back stepping controller for glucose level regulation under meal disturbance
Authors: Abd Mohammed Yousra , Shalal Habeeb Rokaia
Published: August 2022

Diabetes is one of the most common and critical diseases around the world, which need insulin injections to control the body’s glucose rate. A robust back stepping (BS) controller design based on fuzzy system is introduced in this paper to control the glucose level with the presence of meal disturbance. The controller’s design is based on Bergman’s mathematical model. Different fuzzy controller structures are implemented (fuzzy PI, fuzzy PD, and fuzzy PID) controllers along with BS controller named as (BS-fuzzy PI, BS-fuzzy PD, BS-fuzzy PID) controllers. Simulation results using MATLAB/Simulink show efficiency and robustness of the proposed design in terms of controlling the insulin concentration level in blood under meal disturbance and retaining the glucose level to its Basal value.
Hexagonal two layers-photonics crystal fiber based on surface plasmon resonance with gold coating biosensor easy to fabricate
Authors: Irawan Dedi , Ramadhan Khaikal , Saktioto Saktioto , Fitmawati Fitmawati , Hanto Dwi , Widiyatmoko Bambang
Published: August 2022

In this paper, we investigate a hexagonal two-layer photonic crystal fiber based on surface plasmon resonance (HT-PCF-SPR) which is easy to fabricate as a sensor for detecting the refractive index of analytes. After performing numerical simulations using COMSOL multiphysics based on the finite element method (FEM), it was found that the HT-PCF-SPR could detect the analyte's refractive index in the range 1.34-1.37 RIU and in the wavelength range from 730 nm to 810 nm. The plasmonic material used in the design is gold with a thickness of 40 nm which is located outside the layer and in two opposite air holes in the core. The HT-PCF-SPR design has good performance in detecting analytes, it is found that the sensitivity in detecting analytes is 2,000 nm/RIU, meaning that every 1 RIU shift of analyte shifts the wavelength by 2000 nm. Meanwhile, the sensor resolution obtained from the design is 6.67×10-5 RIU, and it is found that the larger the air hole, the greater the confinement loss value.
Novel method to classify varicocele using electronic nose
Authors: Koesoema Wijaya Raden Aa , Kusumaatmaja Ahmad , Rizal Dicky Mochammad
Published: August 2022

The prevalence of varicocele is estimated to be around 15-20% of the male population, and of these, about 35-40% are patients requiring infertility treatment. A varicocele is a dilation of the veins in the spermatic cord diagnosed by physical examination of the male genital area and assisted by scrotal ultrasound. The development of electronic nose technology provides an opportunity to detect disease characteristics of volatile organic compounds produced by biological materials. This study aims to utilize the metabolomic gas produced from the odor of the seminal fluid by using an electronic nose. The identification of the pattern of volatile organic compounds formed was labeled as unilateral varicocele, bilateral varicocele and clinical non varicocele as the basis for classification with supervised machine learning. In this study, the accuracy values were quite good for several algorithms, both in training accuracy and testing accuracy with an average accuracy value above 80%.
Predicting the value of sperm analysis using an electronic nose
Authors: Koesoema Wijaya Raden Aa , Kusumaatmaja Ahmad , Moch Rizal Dicky
Published: August 2022

Total motile sperm count and DNA fragmentation Index are two parameters in sperm analysis that have recently been used to determine the outcome of the management of cases of male infertility. Total Motile Sperm Count is one of the values considered better than the 2010 World Health Organization standard sperm analysis in terms of predictive value for the success of the spontaneous ongoing pregnancy rate. High DNA Fragmentation Index values were associated with lower pregnancy success and an increased risk of low fertilization rate or total fertilization failure. In this study, we developed a method to classify sperm analysis based on total motility sperm count and DNA Fragmentation Index values by using an electronic nose. In the total motility sperm count (TMSC) study, we use four algorithms with the result of accuracy values 95% and in the DNA fragmentation Index study, we get a fairly good accuracy value for two algorithms with the accuracy values 70%.
Fully automated model on breast cancer classification using deep learning classifiers
Authors: Jalil Jassim Ghrabat Mudhafar , Alaa Hussien Zaid , S. Khalefa Mustafa , Ameen Abduljabbar Zaid , Omollo Nyangaresi Vincent , A. Al Sibahee Mustafa , Wahab Abood Enas
Published: August 2022

Deep learning models on the same database have varied accuracy ratings; as such, additional parameters, such as pre-processing, data augmentation and transfer learning, can influence the models’ capacity to obtain higher accuracy. In this paper, a fully automated model is designed using deep learning algorithm to capture images from patients and pre-process, segment and classify the intensity of cancer spread. In the first pre-processing step, pectoral muscles are removed from the input images, which are then downsized. The removal of pectoral muscles after identification may become crucial in classification systems. Finally, the pectoral musclesaredeleted from the picture by using an area expanding segmentation. All mammograms are downsized to reduce processing time. Each stage of the fully automated model uses an optimisation approach to obtain highaccuracy results at respective stages. Simulation is conducted to test the efficacy of the model against state-of-art models, and the proposed fully automated model is thoroughly investigated. For a more accurate comparison, we include the model in our analysis. In a nutshell, this work offers a wealth of information as well as review and discussion of the experimental conditions used by studies on classifying breast cancer images.
Statistical properties of underwater acoustic noise in Lake Hamrin, Diyala, Iraq
Authors: Murad Thamer Easa , Al-Aboosi Yasin Yousif
Published: August 2022

The greatest challenge in underwater acoustic communication systems is the minimization of underwater impact noise. This article offers an empirical example for determining the statistical properties of underwater acoustic noise in the in Lake Hamrin. The data are measured from various depths reached in Lake Hamrin, Diyala, Iraq. In most communication systems, noise is assumed to be additive as well as Gaussian. Underwater acoustic noise (UWAN) isn't only thermal noise, it also includes other components to the UWAN: turbulence, wind and shipping noises. Thus, it should be assumed that the acoustic noise is colored noise instead of white noise. Intermittent noise in the oceans and seas frequently includes significant Non-Gaussian elements. The samples noise data are analyzed in actual time for various depths of 1 meter, 3 meter and 5 meter in order to limit the statistical properties of underwater acoustic noise in Lake Hamrin, Diyala, Iraq such as the autocorrelation function (ACF), the probability density function (PDF) and also power spectral density (PSD). The experimental results showed that the noise of the Tigris river is a color noise and does not follow the Gaussian distribution.
Binary decomposition-based image cipher algorithm with flexible method for key construction
Authors: Muhsin Wadi Salim , Hussein Abed Huda , Taher Malik Nada , Taha Abdullsadah Ahmed
Published: August 2022

Image security is still one of the important fields in multimedia processing because it’s used in our daily lives. Watermarking, steganography, and ciphering are three directions to keep an image secret. Encryption defined as the process of changing information (which called plaintext) into an unreadable secret format (which called cipher-text). A new ciphering algorithm based on binary decomposition and binary codes conversion is proposed in this paper. The key is constructed in a flexible way based on the size of a secret image using some logical operations to increase the security levels. Three test images in different sizes were used to evaluate the performance of the proposed algorithm. The results of the visual scene and statistical factors proved that the suggested method was ciphering the image with high security. The proposed work was validated to confirm its effectiveness. As conclusions, the uses of decomposition and simple binary operations have given high-level image security. Also, key construction is an important step to face several types of attackers.
Enhancement of automatic classification of arcus senilis-nonarcus senilis using convolutional neural networ
Authors: Bt Abdul Halim Nur Farahin , Bin Ramlee Ridza Azri , Bin Mas’ud Mohd Zaki , Jamaludin Amirul
Published: August 2022

Cholesterol is a type of lipid found in the human body and is susceptible to abnormalities. It can be detected via lipid profiling through blood sampling. In addition, cholesterol can be detected through the presence of a "sodium ring" in the eye iris called the corneal arcus (CA), presenting a new preliminary detection method that is less invasive. Therefore, this paper proposed a non-invasive method in detecting cholesterol based on convolutional neural network (CNN) model representation using 300 normal and 300 abnormal iris images from UBIRIS and medical web images. In this work, contrast-limited adaptive histogram (CLAHE) and unsharp masking process was applied first on CA images to enhance the quality of CA images. To detect the CA images, the dataset was trained and tested using three pre-trained CNN architectures; one is created from scratch, another are Resnet-50 and VGG-19 architectures that were fine-tuned to the CA images. The best result was exhibited by proposed pre-trained CNN model created from scratch with 10-fold cross-validation that produced high average detection accuracy at 98.81%. Thus, deeper network implementation is recommended in the future to further improve CA localization for optometrists used in their daily clinical tasks in detecting cholesterol.
A hybrid bat-genetic algorithm for improving the visual quality of medical images
Authors: N. Hussin Kholood , K. Nahar Ali , Kareem Khleaf Hussain
Published: August 2022

Efficient repression of noise in a medical image is a very significant issue. This paper proposed a method to denoise medical images by the use of a hybrid adaptive algorithm based on the bat algorithm (BA) and genetic algorithm (GA). Medical images can be often affected by different kinds of noise that decrease the precision of any automatic system for analysis. Therefore, the noise reduction methods are always utilized for increasing the Peak signal-to-noise ratio (PSNR) and the structural similarity index measure (SSIM) of images to optimize the originality. Gaussian noise and salt and pepper noise corrupted the used medical data, separately. The noise level to medical images was added noise variance from 0.1 to 0.5 to compare the performance of the de-noising techniques. In the analytical study, we apply different kinds of noise like Gaussian noise and salt-and-pepper noise to medical images for making these images noisy. The hybrid BA-GA model was applied on medical noisy images to eliminate noise and the performances have been determined by the statistical analyses such as PSNR, values are gotten 63.04 dB and 59.75 dB for CT and MRI images.
Passively Q-switched erbium doped fiber laser based on graphene and carbon nanotube saturable absorbers
Authors: Mohamed Mafroos Mahroof , Jameela Sapingi Husni Hani , Hamzah Azura
Published: August 2022

A passively Q-switched erbium-doped fiber laser (EDFL) was experimented on by employing graphene, single walled carbon nanotubes (SWCNT) and multi-walled carbon nanotube (MWCNT) saturable absorbers (SA). The SA film was obtained by embedding the graphene, SWCNT and MWCNT into polyvinyl alcohol (PVA). The graphene SA was prepared by dipping a PVA thin film into the graphene solution while carbon nanotubes SAs were prepared using the casting method and placed in the ring cavity to produce a stable pulse laser. Graphene, SWCNT and MWCNT SAs were operating at wavelengths of 1558.92 nm, 1557.98 nm and 1558.51 nm, respectively, whereas the continuous wave was 1560.72 nm at the input pump power of 56 mW. The pulse energy, output power, repetition rate and pulse width were compared in graphene, SWCNT and MWCNT SAs. The shortest pulse width retrieved in graphene, SWCNT and MWCNT were 3.90 µs, 3.62 µs 4.43 µs and produced at the repetition rate of 115.00 kHz, 130.70 kHz, and 89.13 kHz, respectively. In comparison to graphene and SWCNT SAs, MWCNT SAs exhibit the best performance in terms of output power of 2.19 mW and high pulse energy of 24.57 nJ in passively Q-switched EDFL.
A new design of a printed reconfigurable coplanar multiband antenna
Authors: Ouberri Fatima , Tajmouati Abdelali , Zbitou Jamal , Latrach Mohamed
Published: August 2022

The demand for multi-functional components has increased enormously in recent years. Advances in integrated technology have enabled researchers to adapt diverse applications operating at different frequencies in a single wireless device. A compact broadband coplanar waveguide (CPW)-fed square aperture monopole antenna with inverted-L grounded strips is first described. The proposed antenna has a small size of 60×60×0.74 mm3 and has excellent performances which include a good input impedance matching with a much wider operating bandwidth, an excitation of the circular polarization at 2.45 GHz, and a stable omnidirectional radiation pattern. Then, a multiband reconfigurable antenna design is developed from this structure. The frequency reconfigurable approach is obtained using a varactor diode. In this work, it is observed that frequency diversity can be obtained by varying the value of the capacity by leaving the dimensions antenna unchanged. The results are given using CST microwave studio and show good performances in terms of return loss, bandwidth, gain and radiation pattern and demonstrate that the proposed antenna offers a reconfigurable solution for multi-standard wireless communication applications.
The effects of optical fiber impairments on communication systems
Authors: Ali Riyam Saadi , Fattah Ali Y. , Hassib Mustafa D.
Published: August 2022

In this paper, the influence of physical layer impairments on fiber optic channels was evaluated using analytical modeling, and the findings were verified through simulation results. Light propagation inside standard single mode fiber (SSMF) is affected by both linear and nonlinear effects, which must be taken into account in order to develop an appropriate fiber channel model. The use of nonlinear fiber optics in the implementation of highcapacity optical networks is crucial. The "Optisystem 17.0" software package was used to simulate the suggested systems. It can be observed that increased input power tends to increase the effect of cross-phase modulation (XPM) and four wave mixing (FWM) in the nonlinear dispersive fibers. The impact of pulse broadening due to chromatic dispersion (CD), self-phase modulation (SPM), and cross-phase modulation (XPM) was investigated using Gaussian pulses as input signals.
Adaptive Wi-Fi offloading schemes in heterogeneous networks, the survey
Authors: Ruliyanta Ruliyanta , Riduan Ahmad Mohd , Md Isa Azmi Awang
Published: August 2022

At present, the need for data traffic is experiencing tremendous growth. The growth of smartphones technology offers new applications. On the other hand, the growth in cellular network access infrastructure has not been able to keep up with the increasing demand for data package services. For this reason, Wi-Fi offloading is needed, namely cellular users, using Wi-Fi access for their data needs. In 2016, global data communication traffic growth reached 63%. Many researchers have proposed the adaptive wireless fidelity (Wi-Fi) offloading (AAWO) algorithm to transfer data on heterogeneous networks. In this study, the proposed adaptive incentive scheme is classified, to obtain an adaptive scheme based on cost, energy, service quality, and others. From the survey results shown, there is no proposed adaptive algorithm based on the quality of experience (QoE). This provides an opportunity for further research where the Wi-Fi offloading scheme uses the perspective user or user experient options. In addition, open research uses artificial intelligence and machine learning methods as adaptive methods.
The use of information technology applications in the provision of health care to a COVID-19 patients
Authors: Ali Hassan Ihsan , Al-Azzawi Ahmed Adnan Mohammed , Talal Mohammed Layth
Published: August 2022

At the time of writing this study, the COVID-19 virus continues to spread through its multiple mutants, the latest of which is (Omicron). Therefore, it was necessary to use effective and unconventional treatments to reduce the spread of this virus and to deliver health care to its infected without the need to be exposed to the risk of infection. This research paper presents valuable solutions for communicating with COVID-19 patients through the use of information technology applications. This method contributes to reducing the consumption of medical resources, reducing contact with patients, and helping with social distancing, which contributes to reducing the spread of this virus. The process of using information technology means to provide medical advice and treatment to patients by telemedicine doctors has been clarified. More importantly, the results of this study presented the factors affecting the use of these applications in terms of social, technological, and organizational.
Development of data encryption standard algorithm based on magic square
Authors: Muhajer Kareem Suhad , S. Rahma Abdul Monem
Published: August 2022

Data encryption standard is one of the famous algorithms that used in many fields for security purpose but it s susceptible for many attacks. This paper+ proposes a new modification of data encryption standard (DES) algorithm called magic square data encryption standard (MSDES) algorithm in order to include a high-level security by increase the mixing between the plaintext (96 bit) and the key (48 bit). This modification is done by using magic square 3×3 and an additional key is created using linear first shift register (LFSR) in each round of the Feistel of DES. A colour image encryption is simulated and presented as the comparison between the original DES and MSDES algorithm. The proposed algorithm gets the best results in complexity, histogram, entropy, peak-signal-to-noise ratio-(PSNR) and coefficient-correlation.
A dynamic approach for parameter tuning in genetic algorithm using crossover and mutation ratios
Authors: Chattoraj Mrinmoyee , Vinayakamurthy Udaya Rani
Published: August 2022

Genetic algorithm uses the natural selection process for any search process. It is an optimization process where integration among different vital parameters like crossover and mutation plays a major role. The parameters have an impact on the algorithm by their probabilities. In this paper we would review the different strategies used for the selection of crossover and mutation ratios and suggest a dynamic approach for modifying the ratios during runtime. We start with a mutation ratio 0% and crossover ratio 100% where the mutation ratio slowly increases and the crossover ratio decreases (MICD). The final mutation ratio will be 0% and crossover ratio will be 100% at the end of the search process. We also do the reverse process of considering the mutation ratio to be maximum and crossover ratio to be minimum and slowly decrease the mutation ratio and increase the crossover ratio (MDCI). We compare the proposed method with two pre-existing parameter tuning methods and found that this dynamic approach of incrementing the mutation and decrementing the crossover value was more effective when the size of the population was large.
Measuring user emotional responses using Geneva Emotion Wheel towards learning management systems
Authors: Wan Ahmad Wan Nooraishya , Ahmad Rodzuan Ahmad Rizal , Luan Voon Mei
Published: August 2022

The learning management system (LMS) has been used widely in higher learning institutions for blended learning; this interaction involves user cognition and may induce emotional experience. Therefore, the user has to sustain a positive emotional experience towards using LMS to avoid difficulty in the learning process. However, the user emotions and the design elements that induced the emotions are yet to discover. This study aims to analyse user emotional responses to a learning management design and examine the emotional design features of a learning management system. Two versions of a higher learning institution LMS were used and investigated using Geneva Emotion Wheel (GEW). The findings show that both LMS versions lack-in activate the positive emotions, but prove the LMS designs reduce the activation of negative emotions. Furthermore, the emotional design elements that concern an LMS is explained.
A systematic review of structural equation modeling in augmented reality applications
Authors: Nguyen Vinh The , Hong Nguyen Chuyen Thi
Published: August 2022

The purpose of this study is to present a comprehensive review of the use of structural equation modeling (SEM) in augmented reality (AR) studies in the context of the COVID-19 pandemic. IEEE Xplore Scopus, Wiley Online Library, Emerald Insight, and ScienceDirect are the main five data sources for data collection from Jan 2020 to May 2021. The preferred reporting items for systematic reviews and meta-analyses (PRISMA) approach was used to conduct the analysis. At the final stage, 53 relevant publications were included for analysis. Variables such as the number of participants in the study, original or derived hypothesized model, latent variables, direct/indirect contact with users, country, limitation/suggestion, and keywords were extracted. The results showed that a variety of external factors were used to construct the SEM models rather than using the parsimonious ones. The reports showed a fair balance between the direct and indirect methods to contact participants. Despite the COVID-19 pandemic, few publications addressed the issue of data collection and evaluation methods, whereas video demonstrations of the augmented reality (AR) apps were utilized. The current work influences new AR researchers who are searching for a theory-based research model in their studies.
Online hand position detection and classification system using multiple classification algorithms
Authors: Jaleel Ahmed Etihad , Alabbasi Hesham Adnan
Published: August 2022

Hand position recognition is very significant for human-computer interaction. Different kinds of devices and technologies can be used for data acquisition; each has its specification and accuracy, one of these devices is Kinect V2 sensor. A three-dimensional location of the skeleton joints is taken from the Kinect device to create three types of data, the first is joint position raw data, the second is angles between joints, the third is combined of both types. These three types of data are used to train four classifiers, which are support vector machines, random forest, k nearest neighbors, and multilayer perceptron. The experiments are done on the datasets of 30,480 frames from 127 volunteers with saved trained models are used to predict and classify the eight positions of hand in a real-time system. The results show that our proposed approach performs well with highly efficient and accuracy reaching up to 99.07% in some cases and an average time spent on checking frame by frame sequentially very short period, and some cases, it reaches 0.59*10-3 seconds. This system can used in many applications such as controlling robots or devices, comparing physical exercises, or even monitoring elderly and patients, and more.