bluuebunny/crossref_metadata_2025 huggingface dataset:
Layout Model of Bike-Sharing Facilities in the Transfer-Influenced Area of a Subway Station
Authors: Zhong Hongming , Liu Zijian , Chen Jun , Hao Jun , Wang Wei
Published: November 2021

This paper aims to improve transfer utility between bike-sharing and subway. For this paper, the transfer costs of three combined travel modes were analyzed, including “Bike-sharing + Subway”, “Walking + Subway” and “Bus + Subway”, and a transfer cost function, including time cost and expense cost, was constructed. Cluster analysis was carried out on the origin and destination of bike-sharing in the transfer-influenced area. The sum of squares of errors and the service radius were used to verify the clustering results. Then the number of alternative facilities, the location of alternative facilities and the initial number of shared bikes were preliminarily predicted. Based on the initial scheme, a bi-level programming model of facility layout and configuration in bike-sharing was established, with the goal of improving ride volume and reducing the transfer cost and facility-operation costs to optimize the initial facility-allocation scheme. Then a heuristic algorithm was used to solve the model. Finally, a typical subway station was selected as a case, and the configuration process for facilities in bike-sharing is discussed in detail in the paper. The research results of this paper may provide reference for the planning and optimization adjustments of facilities for bike-sharing.
Performance Analysis of a Stand-Alone PV/WT/Biomass/Bat System in Alrashda Village in Egypt
Authors: El-Sattar Hoda Abd , Kamel Salah , Sultan Hamdy , Tostado-Véliz Marcos , Eltamaly Ali M. , Jurado Francisco
Published: November 2021

This paper presents an analysis and optimization of an isolated hybrid renewable power system to operate in the Alrashda village in the Dakhla Oasis, which is situated in the New Valley Governorate in Egypt. The proposed hybrid system is designed to integrate a biomass system with a photovoltaic (PV), wind turbine (WT) and battery storage system (Bat). Four different cases are proposed and compared for analyzing and optimizing. The first case is a configuration of PV and WT with a biomass system and battery bank. The second case is the integration of PV with a biomass system and battery bank. The third case is WT integrated with biomass and a battery bank, and the fourth case is a conventional PV, WT, and battery bank as the main storage unit. The optimization is designed to reduce component oversizing and ensure the dependable control of power supplies with the objective function of reducing the levelized cost of energy and loss of power supply probability. Four optimization algorithms, namely Heap-based optimizer (HBO), Franklin’s and Coulomb’s algorithm (CFA), the Sooty Tern Optimization Algorithm (STOA), and Grey Wolf Optimizer (GWO) are utilized and compared with each other to ensure that all load demand is met at the lowest energy cost (COE) for the proposed hybrid system. The obtained results revealed that the HBO has achieved the best optimal solution for the suggested hybrid system for case one and two, with the minimum COE 0.121171 and 0.1311804 $/kWh, respectively, and with net present cost (NPC) of $3,559,143 and $3,853,160, respectively. Conversely, STOA has achieved the best optimal solution for case three and four, with a COE of 0.105673 and 0.332497 $/kWh, and an NPC of $3,103,938 and $9,766,441, respectively.
Polymerization of Isobutylene in a Rotating Packed Bed Reactor: Experimental and Modeling Studies
Authors: Hou Wenhui , Wang Wei , Xiang Yang , Li Yingjiao , Chu Guangwen , Zou Haikui , Sun Baochang
Published: November 2021

Polymerization of isobutylene (IB) for synthesizing highly reactive polyisobutylene (HRPIB) is characterized by a complicated fast intrinsic reaction rate; therefore, the features of its products exhibit a strong dependence on mixing efficiency. To provide uniform and efficient mixing, a rotating packed bed was employed as a reactor for polymerization of IB. The effects of operating parameters including polymerization temperature (T), rotating speed (N) and relative dosage of monomers and initiating systems ([M]0/[I]0) on number-average molecular weight (Mn) of HRPIB were studied. HRPIB with Mn of 2550 g·mol−1 and exo-olefin terminal content of 85 mol% were efficiently obtained at suitable conditions as T of 283 K, N of 1600 rpm and [M]0/[I]0 of 49. Moreover, the Mn can be regulated by changing T, N and [M]0/[I]0. Based on the presumptive-steady-state analysis method and the coalescence–redispersion model, a model for prediction of the Mn was developed and validated, and the calculated Mn values agreed well with experimental results, with a deviation of ±10%. The results demonstrate that RPB is a promising reactor for synthesizing HRPIB, and the given model for Mn can be applied for the design of RPB and process optimization.
Monitoring of Recovery Process at Yeongildae Beach, South Korea, Using a Video System
Authors: Oh Jung-Eun , Jeong Weon-Mu , Ryu Kyong-Ho , Park Jin-Young , Chang Yeon-S.
Published: November 2021

Once a beach is eroded by storm waves, it is generally recovered under milder wave conditions. To prevent or reduce damage, it is therefore important to understand the characteristics of the site-specific recovery process. Here, we present the results, based on a data set from a video monitoring system and wave measurements, of the recovery process in a pocketed beach located inside a bay where the shoreline retreated harshly (~12 m, on average, of beach width) during Typhoon TAPAH (T1917) in September 2019. It took about 1.5 years for the beach to be recovered to the level before the typhoon. During this period, the erosion and accretion were repeated, with the pattern highly related to the wave power (Pw); most of the erosion occurred when Pw became greater than 30 kWatt/m, whereas the accretion prevailed when Pw was no greater than 10 kWatt/m. The recovery pattern showed discrepancies between different parts of the beach. The erosion during storm events was most severe in the southern part, whereas the northern shoreline did not significantly change even during TAPAH (T1917). In contrast, the recovery process occurred almost equally at all locations. This discrepancy in the erosion/accretion process was likely due to human intervention, as a shadow zone was formed in the northern end due to the breakwaters, causing disequilibrium in the sediment transport gradient along the shore. The results in this study could be applied in designing the protection plans from severe wave attacks by effectively estimating the size of coastal structures and by correctly arranging the horizontal placement of such interventions or beach nourishment. Although the application of these results should be confined to this specific site, the method using wave energy parameters as criteria can be considered in other areas with similar environments, for future planning of beach protection.
Optical Design and Optimization with Genetic Algorithm for High-Resolution Optics Applied to Underwater Remote-Sensing
Authors: Chou Chun-Feng , Tsai Cheng-Mu , Chen Chao-Hsien , Wong Yung-Hao , Fang Yi-Chin , Wen Chan-Chuan , Lee Hsiao-Yi , Le Hien-Thanh , Chang Shun-Hsyung , Liao Hsing-Yuan
Published: November 2021

In fields such as biology, archeology, and industry, underwater photogrammetry can be achieved using consumer-grade equipment. However, camera operations underwater differ considerably from those on land because underwater photogrammetry involves different optical phenomena. On the basis of the requirements and specifications of the marine vessel Polaris, we developed a novel underwater camera with prime and zoom lenses and a high resolving power. The camera can be used in the spectrum in shallow water and the blue–green spectrum in deep water. In the past, ordinary cameras would be placed in waterproof airtight boxes for underwater photography. These cameras were not optimized to the underwater spectrum and environment, resulting in no breakthroughs in resolving power. Furthermore, the use of the blue spectrum greatly increases during underwater and particularly deep-water surveying. Chromatic aberration and focus-point displacement generated by the shift from the shallow-water spectrum to the blue–green spectrum in deep water makes universal underwater photography even more difficult. Our proposed optical design aimed to overcome such challenges for the development of a high-resolution underwater surveying camera. We designed a prime lens and a zoom lens. We adopted a waterproof dome window on the outer surface as the basic structure and optimized it in accordance with the conditions of different water depths and spectra to obtain distortion within ±2% and high-resolution underwater imaging quality. For the zoom lens design, we employed a genetic algorithm in Zemax to attenuate chromatic aberration as a kind of extended optimization. This novel optical design that can be used in all waters is expected to greatly reduce the volume and weight of conventional underwater cameras by more than 50% and 60%, respectively, and increase their resolving power by 30–40%.
The Influence of Heat Input on the Surface Quality of Wire and Arc Additive Manufacturing
Authors: Zeng Jiayi , Nie Wenzhong , Li Xiaoxuan
Published: November 2021

Wire and arc additive manufacturing has unique process characteristics, which make it have great potential in many fields, but the large amount of heat input brought by this feature limits its practical application. The influence of heat input on the performance of parts has been extensively studied, but the quantitative description of the influence of heat input on the surface quality of parts by wire and arc additive manufacturing has not received enough attention. According to different heat input, select the appropriate process parameters for wire and arc additive manufacturing, reversely shape the profile model, select the appropriate function model to establish the ideal profile model according to the principle of minimum error, and compare the two models to analyze the effect of heat input on the surface quality of the parts manufactured by wire and arc additive manufacturing. The results show that, when the heat input is high or low, the standard deviation value and the root mean square value reach 1.908 and 1.963, respectively. The actual profile is larger than the ideal profile. When the heat input is moderate, the standard deviation value and the root mean square value are only 1.634 and 1.713, respectively, and the actual contour is in good agreement with the ideal contour. Combined with the analysis of the transverse and longitudinal sections, it is shown that the heat input has a high degree of influence on the surface quality of the specimen manufactured by wire and arc additive manufacturing, and higher or lower heat input is disadvantageous to it.
Bioactive Compounds from Zingiber montanum and Their Pharmacological Activities with Focus on Zerumbone
Authors: Devkota Hari Prasad , Paudel Keshav Raj , Hassan Md. Mahadi , Dirar Amina Ibrahim , Das Niranjan , Adhikari-Devkota Anjana , Echeverría Javier , Logesh Rajan , Jha Niraj Kumar , Singh Sachin Kumar , Hansbro Philip M. , Chan Yinghan , Chellappan Dinesh Kumar , Dua Kamal
Published: November 2021

The genus Zingiber consists of about 85 species and many of these species are used as food, spices, and medicines. One of the species, Zingiber montanum (J. Koenig) Link ex A. Dietr. is native to Southeast Asia and has been extensively used as traditional medicines and food. The aim of this review was to collect and critically analyze the scientific information about the bioactive compounds and pharmacological activities of Z. montanum with focus on one of the main components, zerumbone (ZER). Various studies have reported the analysis of volatile constituents of the essential oils from Z. montanum. Similarly, many phenylbutanoids, flavonoids and terpenes were also isolated from rhizomes. These essential oils, extracts and compounds showed potent antimicrobial, anti-inflammatory and antioxidant activities among others. Zerumbone has been studied widely for its anticancer, anti-inflammatory, and other pharmacological activities. Future studies should focus on the exploration of various pharmacological activities of other compounds including phenylbutanoids and flavonoids. Bioassay guided isolation may result in the separation of other active components from the extracts. Z. montanum could be a promising source for the development of pharmaceutical products and functional foods.
Target State Classification by Attention-Based Branch Expansion Network
Authors: Zhang Yue , Sun Shengli , Liu Huikai , Lei Linjian , Liu Gaorui , Lu Dehui
Published: November 2021

The intelligent laboratory is an important carrier for the development of the manufacturing industry. In order to meet the technical state requirements of the laboratory and control the particle redundancy, the wearing state of personnel and the technical state of objects are very important observation indicators in the digital laboratory. We collect human and object state datasets, which present the state classification challenge of the staff and experimental tools. Humans and objects are especially important for scene understanding, especially those existing in scenarios that have an impact on the current task. Based on the characteristics of the above datasets—small inter-class distance and large intra-class distance—an attention-based branch expansion network (ABE) is proposed to distinguish confounding features. In order to achieve the best recognition effect by considering the network’s depth and width, we firstly carry out a multi-dimensional reorganization of the existing network structure to explore the influence of depth and width on feature expression by comparing four networks with different depths and widths. We apply channel and spatial attention to refine the features extracted by the four networks, which learn “what” and “where”, respectively, to focus. We find the best results lie in the parallel residual connection of the dual attention applied in stacked block mode. We conduct extensive ablation analysis, gain consistent improvements in classification performance on various datasets, demonstrate the effectiveness of the dual-attention-based branch expansion network, and show a wide range of applicability. It achieves comparable performance with the state of the art (SOTA) on the common dataset Trashnet, with an accuracy of 94.53%.
HAZOP Analysis in Terms of Safety Operations Processes for Oil Production Units: A Case Study
Authors: Penelas Artur de J. , Pires José C. M.
Published: November 2021

The Hazard and Operability Study (HAZOP) methodology is considered one of the most effective techniques for risk analysis, developed fundamentally to provide regular processes with reduced risks that aim to guarantee the safety of activities and the operability of the production units. The study aims to apply the HAZOP methodology in process and safety operations in the oil production industry. A crude oil production unit was divided into smaller sections that were analysed. By applying the HAZOP methodology, 71 possibilities of relevant risks were identified. The environmental, health and economic impacts were estimated to establish safeguard priorities for them. The application of this methodology and the defined safeguards generated 47 recommendations to mitigate the detected problems. The study contributions were to demonstrate the efficacies of HAZOP methodology to identify potential hazards and evaluate the potential hazards obtained for malfunctioning of equipment and property in terms of the resultant impacts either new or existing process facilities, and as a useful tool to provide essential knowledge for the companies’ leaders, decision-maker, and operations managers.
Size-Segregated Particulate Mass and Carbonaceous Components in Roadside and Riverside Environments
Authors: Amin Muhammad , Handika Rizki Andre , Putri Rahmi Mulia , Phairuang Worradorn , Hata Mitsuhiko , Tekasakul Perapong , Furuuchi Masami
Published: November 2021

Air sampling for 12 h diurnal and nocturnal periods was conducted at two monitoring sites with different characteristics in Jambi City, Sumatra Island, Indonesia. The sampling was done at a roadside site and a riverside site from 2–9 August, and from 7–13 August in 2019, respectively. A cascade air sampler was used to obtain information on the status, characteristics and behavior of airborne particles with a particular focus on the ultrafine fraction (PM0.1). The number of light vehicles was best correlated with most PM size categories, while those of heavy vehicles and motorcycles with the 0.5–1 μm and with >10 μm for the nocturnal period, respectively. These findings suggest that there is a positive influence of traffic amount on the PM concentration. Using carbonaceous parameters related to heavy-vehicle emissions such as EC and soot-EC, HV emission was confirmed to account for the PM0.1 fraction more clearly in the roadside environment. The correlation between OC/EC and EC for 0.5–1 μm particles indicated that biomass burning has an influence on both in the diurnal period. A possible transboundary influence was shown as a shift in the PM0.1 fraction characteristic from “urban” to “biomass burning”.
Space–Time Trade-Off of Precursory Seismicity in New Zealand and California Revealed by a Medium-Term Earthquake Forecasting Model
Authors: Rastin Sepideh J. , Rhoades David A. , Christophersen Annemarie
Published: November 2021

The ‘Every Earthquake a Precursor According to Scale’ (EEPAS) medium-term earthquake forecasting model is based on the precursory scale increase (Ψ) phenomenon and associated scaling relations, in which the precursor magnitude MP is predictive of the mainshock magnitude Mm, precursor time TP and precursory area AP. In early studies of Ψ, a relatively low correlation between TP and AP suggested the possibility of a trade-off between time and area as a second-order effect. Here, we investigate the trade-off by means of the EEPAS model. Existing versions of EEPAS in New Zealand and California forecast target earthquakes of magnitudes M > 4.95 from input catalogues with M > 2.95. We systematically vary one parameter each from the EEPAS distributions for time and location, thereby varying the temporal and spatial scales of these distributions by two orders of magnitude. As one of these parameters is varied, the other is refitted to a 20-year period of each catalogue. The resulting curves of the temporal scaling factor against the spatial scaling factor are consistent with an even trade-off between time and area, given the limited temporal and spatial extent of the input catalogue. Hybrid models are formed by mixing several EEPAS models, with parameter sets chosen from points on the trade-off line. These are tested against the original fitted EEPAS models on a subsequent period of the New Zealand catalogue. The resulting information gains suggest that the space–time trade-off can be exploited to improve forecasting.
Classification for Breast Ultrasound Using Convolutional Neural Network with Multiple Time-Domain Feature Maps
Authors: Kim Hyungsuk , Park Juyoung , Lee Hakjoon , Im Geuntae , Lee Jongsoo , Lee Ki-Baek , Lee Heung Jae
Published: November 2021

Ultrasound (US) imaging is widely utilized as a diagnostic screening method, and deep learning has recently drawn attention for the analysis of US images for the pathological status of tissues. While low image quality and poor reproducibility are the common obstacles in US analysis, the small size of the dataset is a new limitation for deep learning due to lack of generalization. In this work, a convolutional neural network (CNN) using multiple feature maps, such as entropy and phase images, as well as a B-mode image, was proposed to classify breast US images. Although B-mode images contain both anatomical and textual information, traditional CNNs experience difficulties in abstracting features automatically, especially with small datasets. For the proposed CNN framework, two distinct feature maps were obtained from a B-mode image and utilized as new inputs for training the CNN. These feature maps can also be made from the evaluation data and applied to the CNN separately for the final classification decision. The experimental results with 780 breast US images in three categories of benign, malignant, and normal, showed that the proposed CNN framework using multiple feature maps exhibited better performances than the traditional CNN with B-mode only for most deep network models.
Interval Type-2 Fuzzy Logic Control-Based Frequency Control of Hybrid Power System Using DMGS of PI Controller
Authors: Rawat Swati , Jha Bhola , Panda Manoj Kumar , Kanti Jyotshana
Published: November 2021

The load frequency control of a microgrid is one of the emerging areas due to the changes in demand and supply in power system. So the controllers’ implementation must be changed accordingly. This paper proposes an interval type-2 fuzzy logic-based, dual-mode gain scheduling (DMGS) of the proportional and integral controller in which the gains of the PI controller werescheduled through the dynamic selector. This proposed controller was implemented ina hybrid microgrid power system in which nonconventional energy sources wereadded to each area of the conventional power plant, which madethe system much more prone to frequency variations. The controller was designed for three areas, consisting of a photovoltaic (PV) system, a wind power system, a fuel cell and a diesel engine/hydropower generator in which the generation rate constraint (GRC) was considered as a nonlinearity. The proposed power system was investigated under various load conditions in the MATLAB/SIMULINK environment. A comparative evaluation of changes in frequency, tie-line power fluctuations and variations in area control errors for the test system showed the effectiveness of the current approach over simple fuzzy PI and a conventional PI-controlling approach.
Four-Dimensional Investigation of Gravel Beach Ridge Accretion and 50 Years of Beach Recharge at Dungeness, UK, Using Historic Images, GPR and Lidar (HIGL)
Authors: Bristow Charlie S. , Buck Lucy , Inggrid Maria
Published: November 2021

Dungeness is a cuspate foreland on the south coast of England that is the largest shingle feature in Europe and includes hundreds of beach ridges. It is also the location of two nuclear power stations that were constructed in the 1960s. The dominant southwest waves cause longshore drift from west to east, eroding the southwest side of Dungeness, accompanied by accretion on the east side. A record of this eastward movement and sediment accretion is preserved by the shingle beach ridges. The power stations are located on the eroding southwestern side of the ness, and a system of beach recharge has been used to move shingle from the downdrift, east-facing shore to the updrift, southwest-facing shore to protect the power stations from coastal erosion. We use a novel combination of historic images, ground-penetrating radar (GPR), and Lidar (HIGL) to investigate accretion and beach ridges at Dungeness during the past 80 years. We report changes in accretion along the coast and use GPR to determine the thickness of beach gravels. The amount of accretion, represented by the width of the backshore, decreases downdrift from south to north. The number of beach ridges preserved also decreases from south to north. By combining the shingle thickness from GPR with elevation data from Lidar surveys and records of beach accretion measured from aerial images, we estimate the volume and mass of gravel that has accumulated at Dungeness. Historic rates of beach accretion are similar to recent rates, suggesting that the 55 years of beach recharge have had little impact on the longer-term accretion downdrift.
Plant-Based Bioactive Natural Products: Insights into Molecular Mechanisms of Action
Authors: Devkota Hari Prasad
Published: November 2021

Medicinal plants have been used for the maintenance of human health since ancient times in the form of food, spices, and traditional medicines [...]
Monitoring the Capillary Jet Breakage by Vibration Using a Fast-Video Camera
Authors: Chalella Mazzocato Marcella , Chevallier Sylvie , Fávaro-Trindade Carmen S. , Poncelet Denis
Published: November 2021

The production of beads by simple extrusion dropwise of an alginate solution in a calcium bath is a simple method. It may be done at room temperature without any toxic compound. However, simple extrusion drop by drop from a needle may result in large capsules and a low flow rate. The solution must be extruded as a jet to get a smaller size and higher flow rate, which breaks into droplets either by vibration or a cutting tool. The present contribution reports jet breakage observations into droplets under vibration by extruding an alginate solution varying some parameters during the study. The droplet formation was observed using a high-speed camera, and images were analyzed. The size, length before breakage, and droplet velocity were obtained by examining 50 droplets, and experiments were repeated three times. The high-speed camera allowed us to observe more precisely the capillary jet breakage. The study showed the importance of selecting a well-designed vibrating system, presented data while varying nozzle size, frequency, and flow rate to get optimum breakage keeping across all the same alginate solution. Further experiments would be interesting, modify the extruded solution concentration and composition, and find a precise criterion to identify optimum conditions.
New Insights into the Antioxidant Compounds of Achenes and Sprouted Buckwheat Cultivated in the Republic of Moldova
Authors: Dumitru Caterina , Dinica Rodica Mihaela , Bahrim Gabriela-Elena , Vizireanu Camelia , Baroiu Liliana , Iancu Alina Viorica , Draganescu Miruna
Published: November 2021

It is well known that both Fagopyrum esculentum species, buckwheat achenes and buckwheat germs, contain flavonoids, and that they can be considered functional foods. In the present study we have analyzed the total content of polyphenols (TPC) and flavonoids (TFC), as well as the antioxidant activity of buckwheat ahcenes originating from the Balti region, Republic of Moldova, and also of the buckwheat sprouts over seven days of germination. The content of phytochemicals in achenes and germinated buckwheat after three and seven days was determined by HPLC–MS analysis. Using the Folin–Ciocalteu method, we recorded an increase in TPC of 360%, and of 436% in TFC after seven days of buckwheat ahcene germination. We aimed to investigate the free radical scavenging properties of methanolic extracts from ahcenes and sprouted buckwheat. We identified and quantified flavonoids and lignans such as rutin, orientin, isoorientin, vitexin, quercetin, quercitrin, isorhamnetin, lutein, apigenin, catechins, coumestrol—which have countless beneficial effects on human health—using HPLC–MS. FTIR analysis also revealed the accumulation of phenolic compounds during germination. This is the first study on the identification and quantification of phytochemicals from buckwheat achenes and sprouts from the Balti region of the Republic of Moldova.
Phenolic Compound Composition and Biological Activities of Fractionated Soybean Pod Extract
Authors: Pabich Marzena , Marciniak Beata , Kontek Renata
Published: November 2021

The objective of this study was to determine the potential of dry extracts from soybean pods as a source of bioactive compounds. The phenolic compound composition of the extract (E) and fraction (F1-F3) as well as their respective lipophilicity were analyzed by UPLC-ESI-QTOF-MS. The biological activity as measured by antioxidant and cytotoxic activity was also evaluated. The in vitro anticancer potential of the ethanolic extract and fraction of soybean pods was measured through MTT assay using human colorectal carcinoma (HTC-116) and prostate cancer (PC-3) cell lines. The F2 fraction, with medium lipophilicity, produced the most pronounced cytotoxic effect in PC-3 cells. Analysis of Pearson’s correlation demonstrated a high relationship between the content of phenolic compounds, the antioxidant activity of the extract and fractions, and cytotoxic activity towards PC-3 cells. UPLC-ESI-QTOF-MS analysis of soybean pod extract resulted in putative identification of 50 polyphenols belonging to three different chemical families (phenolic acids, flavonoids, and other polyphenols), the first time such an analysis has been performed. Among the fractions with variable lipophilicity, fraction F2 was the most abundant in phenolic compounds. This was confirmed in the quantitative analysis, as a result of which the highest total content of phenolic compounds was found in the extract (E) and fraction F2. Soybean pods might be useful material for obtaining preparations with anti-radical and anti-cancer properties. They can also be an active food additive or a component in dietary supplements.
An Enhanced Evolutionary Student Performance Prediction Model Using Whale Optimization Algorithm Boosted with Sine-Cosine Mechanism
Authors: Thaher Thaer , Zaguia Atef , Al Azwari Sana , Mafarja Majdi , Chantar Hamouda , Abuhamdah Anmar , Turabieh Hamza , Mirjalili Seyedali , Sheta Alaa
Published: November 2021

The students’ performance prediction (SPP) problem is a challenging problem that managers face at any institution. Collecting educational quantitative and qualitative data from many resources such as exam centers, virtual courses, e-learning educational systems, and other resources is not a simple task. Even after collecting data, we might face imbalanced data, missing data, biased data, and different data types such as strings, numbers, and letters. One of the most common challenges in this area is the large number of attributes (features). Determining the highly valuable features is needed to improve the overall students’ performance. This paper proposes an evolutionary-based SPP model utilizing an enhanced form of the Whale Optimization Algorithm (EWOA) as a wrapper feature selection to keep the most informative features and enhance the prediction quality. The proposed EWOA combines the Whale Optimization Algorithm (WOA) with Sine Cosine Algorithm (SCA) and Logistic Chaotic Map (LCM) to improve the overall performance of WOA. The SCA will empower the exploitation process inside WOA and minimize the probability of being stuck in local optima. The main idea is to enhance the worst half of the population in WOA using SCA. Besides, LCM strategy is employed to control the population diversity and improve the exploration process. As such, we handled the imbalanced data using the Adaptive Synthetic (ADASYN) sampling technique and converting WOA to binary variant employing transfer functions (TFs) that belong to different families (S-shaped and V-shaped). Two real educational datasets are used, and five different classifiers are employed: the Decision Trees (DT), k-Nearest Neighbors (k-NN), Naive Bayes (NB), Linear Discriminant Analysis (LDA), and LogitBoost (LB). The obtained results show that the LDA classifier is the most reliable classifier with both datasets. In addition, the proposed EWOA outperforms other methods in the literature as wrapper feature selection with selected transfer functions.
Recovery of Post-Traumatic Temporomandibular Joint after Mandibular Fracture Immobilization: A Literature Review
Authors: Stelea Carmen Gabriela , Agop-Forna Doriana , Dragomir Raluca , Ancuţa Codrina , Törok Roland , Forna Norina Consuela , Iordache Cristina
Published: November 2021

Considered as one of the most common traumatic injuries of the maxillofacial region, mandibular fractures remain among the complex causes of temporomandibular joint disorders (TMDs). Due to the complexity of the temporomandibular joint, the management of TMDs represents a challenge in real-life practice; although many treatment modalities have already been proposed, ranging from conservative options to open surgical procedures, a consensus is still lacking in many aspects. Furthermore, despite continuous improvement of the management of mandible fractures, the duration of immobilization and temporary disability is not reduced, and the incidence of complications remains high. The aim of the present study is to (i) review anatomophysiological components of temporomandibular joint; (ii) review concepts of temporomandibular joint fractures; and (iii) describe methods of the recovery of the temporomandibular joint after mandibular fracture immobilization.
Development of a Simultaneous Analysis Method for Quality Control of a Traditional Herbal Formula, Daeshiho-Tang, Using 10 Marker Components
Authors: Seo Chang-Seob , Shin Hyeun-Kyoo
Published: November 2021

Daeshiho-tang (DSHT) is a traditional herbal formula consisting of six herbal medicines: Bupleurum falcatum L., Scutellaria baicalensis Georgi, Paonia lactiflora Pall., Pheum palmatum L., Poncirus trifoliata (L.) Raf., and Pinellia ternate (Thunb.) Makino. In this study, we developed a simultaneous analysis method based on high-performance liquid chromatography for the quality control of DSHT. Chromatographic separation of 10 marker components (gallic acid, albiflorin, paeoniflorin, naringin, benzoic acid, baicalin, poncirin, wogonoside, baicalein, and wogonin) was achieved using a water–acetonitrile system as the mobile phase with a SunFire C18 reversed-phase column. The developed analytical method was validated with respect to linearity, limit of detection, limit of quantitation, recovery, and precision. Among the 10 markers of DSHT in the established assay, baicalin, the main compound of Scutellaria baicalensis Georgi, was present in the highest concentration (36.86–46.17 mg/g). The validated assay will be useful for the quality control of DSHT.
Optimal Versus Equal Dimensions of Round Bales of Agricultural Materials Wrapped with Plastic Film—Conflict or Compliance?
Authors: Stankiewicz Anna
Published: November 2021

For the assumed bale volume, its dimensions (diameter, height), minimizing the consumption of the plastic film used for bale wrapping with the combined 3D method, depend on film and wrapping parameters. Incorrect selection of these parameters may result in an optimal bale diameter, which differs significantly from its height, while in agricultural practice bales with diameters equal or almost equal to the height dominate. The aim of the study is to formulate and solve the problem of selecting such dimensions of the bale with a given volume that the film consumption is minimal and, simultaneously, the bale diameter is equal or almost equal to its height. Necessary and sufficient conditions for such equilibria of the optimal bale dimensions are derived in the form of algebraic equations and inequalities. Four problems of the optimal bale dimension design guaranteeing assumed equilibrium of diameter and height are formulated and solved; both free and fixed bale volume are considered. Solutions of these problems are reduced to solving the sets of simple algebraic equations and inequalities with respect to two variables: integer number of film layers and continuous overlap ratio in bottom layers. Algorithms were formulated and examples regarding large bales demonstrate that they can handle the optimal dimensions’ equilibria problems.
Application of the Proposed Fiber Optic Time Differential BOCDA Sensor System for Impact Damage Detection of a Composite Cylinder
Authors: Choi Bo-Hun , Seo Dae-Cheol , Kwon Yong-Seok , Kwon Il-Bum
Published: November 2021

An optical-fiber-embedded composite cylinder was fabricated using the filament winding process with an interval of 12 mm in the longitudinal direction of the cylinder. The optical fiber was wound 160 turns around the cylinder, and the straight length was about 125 m. After a total of twelve impact events of 5, 10, 15, and 20 J, the residual strain in the cylinder was measured using the proposed time differential BOCDA sensor system. This method makes the traditionally used optical delay unnecessary while increasing the degrees of freedom of using the modulation rate, which determines the spatial resolution of this measurement system. The modulation rates of optical light in the system were applied up to 16 Gbps, which is an eight-fold increase compared to our previous experiments. Damage maps were obtained by mapping the measured residual strain onto the structure of the cylinder, and compared using three spatial resolutions of 20, 10, and 6.25 mm. In the measured damage map, expansion deformation due to impact was measured at all impact points, and the impact location on the map and the actual location on the cylinder were exactly the same. The map measured from the composite showed a clear point-symmetrical shape with an increase in sharpness as the measurement resolution increased. At the highest resolution, material expansion and compression were observed to alternate with respect to the center of impact, like the surface deformation of a liquid caused by a thrown object. Furthermore, considered together with our previous experiments, we confirmed that this phenomenon propagated from the surface of the composite material to the interior, where the optical fiber was embedded. The total amount of residual strain formed around each impact point was linearly proportional to the applied external impact energy.
Two-Phase Deep Learning-Based EDoS Detection System
Authors: Nhu Chien-Nguyen , Park Minho
Published: November 2021

Cloud computing is currently considered the most cost-effective platform for offering business and consumer IT services over the Internet. However, it is prone to new vulnerabilities. A new type of attack called an economic denial of sustainability (EDoS) attack exploits the pay-per-use model to scale up the resource usage over time to the extent that the cloud user has to pay for the unexpected usage charge. To prevent EDoS attacks, a few solutions have been proposed, including hard-threshold and machine learning-based solutions. Among them, long short-term memory (LSTM)-based solutions achieve much higher accuracy and false-alarm rates than hard-threshold and other machine learning-based solutions. However, LSTM requires a long sequence length of the input data, leading to a degraded performance owing to increases in the calculations, the detection time, and consuming a large number of computing resources of the defense system. We, therefore, propose a two-phase deep learning-based EDoS detection scheme that uses an LSTM model to detect each abnormal flow in network traffic; however, the LSTM model requires only a short sequence length of five of the input data. Thus, the proposed scheme can take advantage of the efficiency of the LSTM algorithm in detecting each abnormal flow in network traffic, while reducing the required sequence length of the input data. A comprehensive performance evaluation shows that our proposed scheme outperforms the existing solutions in terms of accuracy and resource consumption.
A Bipolar Voltage Gain Boost AC-AC Converter Based on Four Switching Transistors
Authors: Ashraf Naveed , Abbas Ghulam , Ullah Nasim , Otaibi Sattam Al , Althobaiti Ahmed , Zubair Muhammad , Farooq Umar
Published: November 2021

In numerous applications, such as the correction of grid voltage during voltage sag or swell events caused by system faults, it is necessary to ensure the stabilization of the output voltage with in-phase and out-phase features. This feature can also be employed in high-voltage-gain AC to DC conversion. AC voltage control schemes with one-stage conversion are viable approaches in this regard as only voltage regulation is needed. This conversion approach has strong potential for such applications as it is simple to realize. The voltage-correcting compensators are connected in series with the lines. The inputs of the AC voltage controllers employed in the voltage-correcting compensators may be connected to the faulty phase or other healthy phases. The number of AC voltage controllers used in a voltage compensator are one and two if its input power is drawn from the faulty and non-faulty phases, respectively. In the latter case, voltage gains and phase adjustment are major problems. There is no such issue in the first approach, where the voltage-correcting controller is connected to the line where the voltage variation is to be corrected. A high voltage gain more than the unity of both voltage polarities is required if the depth level of the correcting voltage is around 50% or more. The size and cost of a voltage-correcting controller depend on the number of switching transistors, as an isolated DC source with a gate-controlling circuit is a mandatory requirement for the switching operation of each transistor. Therefore, in the suggested research, an AC voltage controller having bipolar voltage gain is realized only with four switching transistors and six diodes, which reduces the overall size and cost significantly. The verification of the suggested topology is ensured by obtaining the simulation and real results from Simulink-based and practical-based platforms, respectively.
Pixel-Level Analysis for Enhancing Threat Detection in Large-Scale X-ray Security Images
Authors: Dumagpi Joanna Kazzandra , Jeong Yong-Jin
Published: November 2021

Threat detection in X-ray security images is critical for preserving public safety. Recently, deep learning algorithms have begun to be adopted for threat detection tasks in X-ray security images. However, most of the prior works in this field have largely focused on using image-level classification and object-level detection approaches. Adopting object separation as a pixel-level approach to analyze X-ray security images can significantly improve automatic threat detection. In this paper, we investigated the effects of incorporating segmentation deep learning models in the threat detection pipeline of a large-scale imbalanced X-ray dataset. We trained a Faster R-CNN (region-based convolutional neural network) model to localize possible threat regions in the X-ray security images on a balanced dataset to maximize detection of true positives. Then, we trained a DeepLabV3+ model to verify the preliminary detections by classifying each pixel in the threat regions, which resulted in the suppression of false positives. The two models were combined in one detection pipeline to produce the final detections. Experiment results demonstrate that the proposed method significantly outperformed previous baseline methods and end-to-end instance segmentation methods, achieving mean average precisions (mAPs) of 94.88%, 91.40%, and 89.42% across increasing scales of imbalance in the practical dataset.
Preparation and Characterization of Glass-Fiber-Reinforced Modified Polyphenylene Oxide by a Direct Fiber Feeding Extrusion Process
Authors: Ahn SeungJae , Lee Jae-Chul , Kim Ki-Young
Published: November 2021

Polyphenylene oxide (PPO) polymers have good mechanical, electrical, and thermal properties, but they have poor processability owing to their quite high melt viscosity. This hinders the manufacturing processes of fiber-reinforced thermoplastics that have enhanced mechanical and physical properties. Although PPO was modified by blending with polystyrene (PS) or polyamide to improve processability, the modified PPO (mPPO) still had a high melt viscosity compared with other polymers. Thus, the fiber-reinforced mPPO is manufactured by compounding with chopped fiber, while various methods are applied to manufacture the fiber-reinforced polypropylene and polyamide in order to improve properties. One of the methods is a direct fiber feeding method, which can keep the longer fiber length because of a direct and continuous roving yarn feeding without chopping. Therefore, the composite manufactured by the direct fiber feeding method is expected to improve the mechanical properties. Hence, this study aims to investigate the feasibility of a direct fiber feeding extrusion process for manufacturing glass-fiber-reinforced mPPO or GFmPPO. The manufactured GF/mPPO composites exhibited increased tensile and flexural properties as the fiber content increased up to 50 wt% of GF owing to the predominant effects of fiber content. Nevertheless, the larger core area in the cross-section micrograph of the tensile specimen of the GF/mPPO composite with 50 wt% of GF was observed to reduce the fiber efficiency factor for tensile strength. Meanwhile, the impact strength of the GF/mPPO composites decreased with increasing GF content. This is attributed to the insufficient fiber length for the impact strength. As the GF content increased, the glass transition temperature slightly decreased. This result was interpreted as being a result of thermal degradation during the extrusion process to manufacture the GF/mPPO masterbatch. The results of the dynamic mechanical analyses, e.g., storage modulus and tan δ, show the good correlation with the increased flexural modulus, the decreased glass transition temperature, and the impact strength as the GF content increased.
Spatial Pattern of Air Pollutant Concentrations and Their Relationship with Meteorological Parameters in Coastal Slum Settlements of Lagos, Southwestern Nigeria
Authors: Okimiji Oluwaseun Princess , Techato Kuaanan , Simon John Nyandansobi , Tope-Ajayi Opeyemi Oluwaseun , Okafor Angela Tochukwu , Aborisade Moses Akintayo , Phoungthong Khamphe
Published: November 2021

This study assessed the spatial disposition of air pollutants and their relationship with meteorological parameters in urban slum settlements of Lagos city. The gaseous pollutants were quantified using a gas analyzer, and the PM2.5 concentration and meteorological parameters were determined using an Air Metric Sampler and Wind Mate, respectively. SPSS for Windows and ArcGIS were used for data analysis. The results revealed that the seasonal variations in SO2, NO2, CO2, and PM2.5 showed a higher level of air pollutant concentration during the dry season than during the wet season. During the wet season, a significant correlation was observed between PM2.5 and temperature at the 1% level (0.957 **), and VOC and SO2 (0.907 *) at the 5% level; during the dry season, significant correlations were observed between NO2 and SO2 at the 1% level (0.9477 **), and PM2.5 and relative humidity (0.832 *) at the 5% level. Atmospheric pressure (72%), temperature (60%), and relative humidity (98.4) were the primary meteorological factors affecting air pollutants such as VOC, CO2, and SO2. The spatial dispersal of air pollutants revealed a high Z score and a moderate p-value, indicating hot spot locations throughout the five selected slum settlements. It is recommended that regular monitoring based on quantifiable economic costs that are beneficial to the well-being of the populace be investigated, and policy-based initiatives for air pollution control based on scientific evidence be advocated for.