bluuebunny/crossref_metadata_2025 huggingface dataset:
Evaluation of Field Performance and Energy Consumption of a Medium-sized Combine Harvester for Harvesting Glutinous Rice in Malaysia
Authors: Mat Nawi Nazmi , Muhammad Isa Bomoi , Abd Aziz Samsuzana , Mohd Kassim Mohamad Saufi
Published: April 2024

A medium-sized combine harvester has been recently deployed to harvest newly introduced high-value glutinous rice in Malaysia. Thus, efficient utilisation of combine harvesters during harvest is essential to minimise operating costs and grain loss. This study evaluated a medium-sized combine harvester’s performance and energy consumption for harvesting glutinous rice. The experiment was carried out on a one-hectare paddy field with three sub-plots using a central composite design (CCD). A time-motion study was conducted during the harvesting operation to determine the combine harvester’s performance parameters, which included field operating speed (FS), field efficiency (FE), theoretical field capacity (TFC), effective field capacity (EFC), grain throughput capacity (GTC), fuel consumption (FC) and field machine index (MI). The energy expended during the operation, which included machinery energy (ME), fuel energy (FCE), human energy (HE), and total energy (TE) input, were also computed. The average FS, FE, TFC, EFC, FC, and MI values were 2.42 km/h, 59.78%, 0.56 ha/h, 0.33 ha/h, 14.89 l/ha, and 0.30, respectively. The mean values of ME, FCE, HE, and TE were 305.35, 711.69, 3.62, and 1020.66 MJ/ha, respectively. The combine harvester achieved an average grain throughput capacity (GTC) of 1796.91 kg/h, demonstrating its effectiveness in handling glutinous rice harvesting. The average time distribution for the harvesting operation, such as effective harvesting time, turning/reversing time, and unloading time, was 1.85 h/ha, 0.38 h/ha, and 1.05 h/ha, respectively. Based on the results, it is concluded that the medium-sized combine harvester is technically and economically suitable for harvesting glutinous rice.
Effect of Maturity Stages on Physical Properties of Cocoa (Theobroma cacao L.) Pods
Authors: Oluwamayokun Soyoye Babatunde , Mat Nawi Nazmi , Zulkifli Mohamad Ariffin , Chen Guangnan , Madian Nurfadzilah , Mokhtar Ahmad Faiz , Adam Siti Nooradzah , Al Riza Dimas Firmanda
Published: April 2024

Cocoa is one of the main plantation crops in Malaysia. Significant efforts have been made to modernise the industry using mechanisation and automation technologies. Thus, determination of the physical properties of cocoa pods at different maturity stages is paramount for an appropriate design and development of a post-harvest machinery system for pod breaking, sorting and grading. This study investigated the effect of five different maturity stages (unripe, under-ripe, ripe, very-ripe and over-ripe) on the physical properties of cocoa pods. A total of 80 cocoa pods (Clone PBC140) were used as samples, where 16 pods represented each maturity stage. For the unripe stage, the largest mean dimensional values were 172.45, 89.3 and 111.18 mm for the pods’ length, diameter and geometric mean diameter, respectively. The highest mean values of 0.66 and 0.54 for the over-ripe stage were recorded for sphericity and aspect ratio, respectively. The geometric mean diameter, weight and firmness were found to be inversely proportional to the maturity stages. The advanced maturity stages experience greater colour intensity, as reflected in the chroma (C*) and higher L*, a* and b* values. This study has found that the colour and texture of the cocoa pods change throughout their maturity. In conclusion, the results reported in this study can be used as a reference for designing and developing a machinery system for post-harvest fruit processing.
Round-the-Clock and Continuous Generation of Hydrogen and Oxygen
Authors: Shoikhedbrod Michael
Published: April 2024

The main methods of industrial hydrogen production are: steam restructuring of methane and natural gas; coal gasification; biotechnology; water electrolysis. The most efficient method for producing pure hydrogen and oxygen is to produce pure hydrogen and oxygen in a photoelectrochemical cell. A photoelectrochemical cell produces hydrogen and oxygen directly from solar energy. In a photoelectrochemical cell, a combined anode, made from silicon semiconductor and metal mesh with large cells, submerged in water electrolyte solution, agitated by four photons of light, forms an oxygen molecule, which in the form of a gas bubble lifts from the surface of anode to the free surface of the water electrolyte solution. Two hydrogen cations, formed because of the dissociation of water, reaching the cathode, form a gaseous hydrogen molecule, which, turn into an electrolysis bubble, lifts from surface of cathode to the free surface of the water electrolyte solution. The article presents a new method for round-the-clock and continuous generation of hydrogen and oxygen, using a developed photoelectrolyzer-generator, taking a horizontally located combine anode, made from silicon semiconductor and metal mesh with large cells and burnt graphite cathode (electrolysis base) at the bottom of the photoelectrolyzer-generator; a membrane from fire hose material, located between electrodes; device, regulating the gap between the electrodes. Round-the-clock and continuous production of hydrogen and oxygen in the photoelectrolyzer-generator is ensured by using lamp, including LED with a daylight battery charger as a useful electrical load, which brightens the combined anode, made from silicon semiconductor and metal mesh with large cells at night until the morning and by continuously filling the photoelectrolyzer-generator with water.
Production of Thermoplastic Composites reinforced with Posidonia Oceanica Fibers
Authors: Slimani Faouzi , Ghanmi Ines , Ghanmi Samir , Guedri Mohamed
Published: April 2024

This study investigates the development and characterization of a new biocomposite and biodegradable material based on natural fibers. This new biocomposite is composed of commercially available biodegradable polylactic acid (PLA) as a matrix and Posidonia Oceanica (PO) fibers collected from the coasts of Tunisia as reinforcement. This new material is produced by heating and pressing the two components in a special device. The use of PO, or sea balls, will allow exploiting one of the marine residues abundant on Tunisian beaches, instead of exploited industrially, and to preserve the beaches from debris given the impact of tourist activity in the Tunisian economy. The PLA/PO coupling allowed obtaining a biocomposite with promising mechanical properties. The improvement in maximum stress and strain after the addition of PO is one of the highlights of the results of this work.
Investigating the Impact of Domestic Sewage on Asphalt Concrete Pavement Strength
Authors: Ahmed Afzal , Ali Sajjad , Ahmed Ashar , Khan Farah
Published: April 2024

This study evaluates the impact of exposing asphalt pavement to sewage and fresh water. In total, 87 samples were prepared, where half of them were immersed in sewage and the others were immersed in freshwater. The Marshall mix design method was adopted for the preparation of samples. Three immersed samples were tested for stability and flow every 24 hours in both fresh water and sewage, comparing the results with a control sample. The samples immersed in fresh water lost their stability and flow after 11 days, while the ones immersed in sewage water lost their stability and flow after 9 days. Furthermore, the loss in stability for samples immersed in fresh water and sewage after 14 days was found to be 38.8 and 55.6%, respectively. The results revealed that sewage water affects asphalt concrete pavement more severely than freshwater. Finally, it was concluded that proper drainage and adequate supplemental sewerage systems are necessary to maintain the desired strength of the pavement throughout its design life.
Optimal Artificial Neural Network-based Fabric Defect Detection and Classification
Authors: Sajitha Nesamony , Priya Srinivasan Prasanna
Published: April 2024

Automated Fabric Defect (FD) detection plays a crucial role in industrial automation within fabric production. Traditionally, the identification of FDs heavily relies on manual assessment, facilitating prompt repairs of minor defects. However, the efficiency of manual recognition diminishes significantly as labor working hours increase. Consequently, there is a pressing need to introduce an automated analysis method for FD recognition to reduce labor costs, minimize errors, and improve fabric quality. Many researchers have devised defect detection systems utilizing Machine Learning (ML) approaches, enabling swift, accurate, and efficient identification of defects. This study presents the Optimal Artificial Neural Network-based Fabric Defect Detection and Classification (OANN-FDDC) technique. The OANN-FDDC technique exploits handcrafted features with a parameter-tuning strategy for effectively detecting the FD process. To obtain this, the OANN-FDDC technique employs CLAHE and Bilateral Filtering (BF) model-based contrast augmentation and noise removal. Besides, the OANN-FDDC technique extracts shape, texture, and color features. For FD detection, the ANN method is utilized. To improve the detection results of the ANN method, the Root Mean Square Propagation (RMSProp) optimization technique is used for the parameter selection process. The simulation outputs of the OANN-FDDC technique were examined on an open fabric image database. The experimental results of the OANN-FDDC technique implied a better outcome than the 96.97% of other recent approaches.
An FPGA Accelerator for Real Time Hyperspectral Images Compression based on JPEG2000 Standard
Authors: Ghodhbani Refka , Saidani Taoufik , Horrigue Layla , Algarni Asaad M. , Alshammari Muteb
Published: April 2024

Lossless hyperspectral images have the advantage of reducing the data size, hence saving on storage and transmission costs. This study presents a dynamic pipeline hardware design for compressing and decompressing images using the Joint Photographic Experts Group-Lossless (JPEG2000) algorithm. The proposed architecture was specifically tailored for implementation on a Field Programmable Gate Array (FPGA) to accomplish efficient image processing. The introduction of a pipeline pause mechanism effectively resolves the issue of coding errors deriving from parameter modifications. Bit-plane coding was employed to enhance the efficacy of image coding calculations, leading to a reduction of parameter update delays. However, the context and decision creation procedure were streamlined, resulting in a significant enhancement in throughput. A hardware module utilizing the parallel block compression architecture was developed for JPEG2000 compression/decompression, allowing for configurable block size and bringing about enhanced image, compression/decompression, throughput, and reduced times. Verification results were obtained by implementing the proposed JPEG 2000 compression on a Zynq-7000 system-on-chip. The purpose of this system was to enable on-board satellite processing of hyperspectral image cubes with a specific focus on achieving lossless compression. The proposed architecture outperformed previous approaches by using fewer resources and achieving a higher compression ratio and clock frequency.
Rational Pile Design using Computer-based Program Coding in Matlab: A Case Study
Authors: Hoa Cao Van
Published: April 2024

Scientific approaches to pile design have made significant progress in recent years. However, despite these advancements, estimating the axial resistance and settlement of piles still heavily relies on empirical correlations. The design of resource-efficient and environmentally friendly piles is a pressing need. Yet, there is no explicit theoretical or practical experience to guide pile design rationally. Typically, determining a pile's resistance and settlement is treated as separate problems without considering the interactions between the pile and the soil. Additionally, soil data are inconsistent due to the heterogeneous and isotropic character of the soil in the half-space under the foundation. In this study, the modified Fellenius Unified method was coded in Matlab and applied to analyze pile behavior, considering the resistance and settlement of each pile, as well as interactions between piles and the soil simultaneously. The results showed that this approach is promising for practical applications. Moreover, its implementation in the evaluation of pile design for an apartment project in Binh Duong, Vietnam, suggests that the pile's length can be reduced even further than it currently is.
Effect of Ground Granulated Blast Slag and Temperature Curing on the Strength of Fly Ash-based Geopolymer Concrete
Authors: Kumar Anil , Rajkishor . , Kumar Niraj , Chhotu Anil Kumar , Kumar Bhushan
Published: April 2024

Concrete is used most extensively after water to meet construction requirements. Since the population is increasing day by day, the demand for concrete will always increase, hence, the demand for cement will also increase. The production of cement requires a lot of energy and emits greenhouse gases into the environment. Therefore, an alternative material for cement concrete is required. Geopolymer concrete (GPC) is an alternative to cement made of aluminosilicate materials such as fly ash, Ground Granulated Blast Slag (GGBS), silica fume, metakaolin, etc. If these materials are activated with an alkaline activator, then a bond that is responsible for the strength develops. GPC made with fly ash needs temperature curing to develop its strength, which limits its use on a large scale. In this study, a mix ratio of GPC equivalent to conventional M20 concrete was obtained at ambient curing conditions. The effect of temperature curing was also studied. GPC was prepared in three different mixes. In each mix, the binder content was changed by varying the fly ash and GGBS content. Two sets of cube, beam, and cylindrical samples were prepared from each mixture. One set was cured at ambient temperatures and the other at increased temperatures. The temperature-cured specimens provided higher strength than the ambient-cured. If a strength equivalent to conventional M20 concrete is required for ambient curing, then the mix should be 70% fly ash and 30% GGBS, and the ratio of binder, fine aggregate, and coarse aggregate should be 1:1.5:3.
Thermal and Mechanical Properties Enhancement of Cement Mortar using Phosphogypsum Waste: Experimental and Modeling Study
Authors: Ragab Ehab M. , Awwad Tarek M. , Becheikh Nidhal
Published: April 2024

This research presents an in-depth investigation into the application of phosphogypsum (PG), a by-product of phosphate fertilizer plants and chemical industries, as a replacement material for cement in mortar, with a focus on enhancing its thermal and mechanical properties. The influence of PG as a partial replacement for cement on the compressive strength of mortar after 3, 7, and 28 days is investigated. Utilizing the Box-Behnken design within Response Surface Methodology, this study analyzed factors, such as sulfuric acid concentration, washing time, calcination temperature, and PG to cement ratio. Results indicate that optimal PG levels enhance mortar strength, particularly at 28 days, through sustained ettringite formation and microstructure optimization. Sulfuric acid concentration and calcination temperature were identified as the most significant elements influencing compressive strength, with the latter improving PG quality and reactivity. A PG to cement ratio up to 10% was found beneficial, while washing time had a negligible effect. The research highlights a critical synergy between the sulfuric acid concentration applied during the purification of PG and the calcination temperature. A significant improvement of 21% in compressive strength was achieved, underscoring the combined effect of chemical and thermal treatment on PG's efficacy in mortar. The increased sulfuric acid concentration is presumed to purify the PG by removing impurities, thus improving its reactivity. Concurrently, calcination alters the PG's crystalline structure and diminishes its organic composition. This interdependent optimization is instrumental in enhancing the structural integrity of PG-modified mortar. The potential for raw PG to be used as an insulating material is more pronounced at higher replacement rates (10%), while sulphuric acid treated PG (SCPG) and heat treated PG (HTPG) seem to be unable to provide a clear insulative advantage.
Unveiling Shadows: Harnessing Artificial Intelligence for Insider Threat Detection
Authors: Yilmaz Erhan , Can Ozgu
Published: April 2024

Insider threats pose a significant risk to organizations, necessitating robust detection mechanisms to safeguard against potential damage. Traditional methods struggle to detect insider threats operating within authorized access. Therefore, the use of Artificial Intelligence (AI) techniques is essential. This study aimed to provide valuable insights for insider threat research by synthesizing advanced AI methodologies that offer promising avenues to enhance organizational cybersecurity defenses. For this purpose, this paper explores the intersection of AI and insider threat detection by acknowledging organizations' challenges in identifying and preventing malicious activities by insiders. In this context, the limitations of traditional methods are recognized, and AI techniques, including user behavior analytics, Natural Language Processing (NLP), Large Language Models (LLMs), and Graph-based approaches, are investigated as potential solutions to provide more effective detection mechanisms. For this purpose, this paper addresses challenges such as the scarcity of insider threat datasets, privacy concerns, and the evolving nature of employee behavior. This study contributes to the field by investigating the feasibility of AI techniques to detect insider threats and presents feasible approaches to strengthening organizational cybersecurity defenses against them. In addition, the paper outlines future research directions in the field by focusing on the importance of multimodal data analysis, human-centric approaches, privacy-preserving techniques, and explainable AI.
Unbalanced Distribution Network Cross-Country Fault Diagnosis Method with Emphasis on High-Impedance Fault Syndrome
Authors: Ponukumati Balamurali Krishna , Behera Anil Kumar , Subhadarshini Lipsa , Sinha Pampa , Maharana Manoj Kumar , Pavan Kumar Arapirala Venkata
Published: April 2024

Unusual fault scenarios can occur on the utility grid in a power system network. Cross-Country Faults (CCFs) connected to the High-Impedance Fault (HIF) syndrome are more prone to occur in forested areas due to thunderstorms, cyclones, and improper vegetation management and tree pruning. Finding and categorizing CCFs associated with HIF syndrome is a great challenge. This study employed the cross-correlation method to reconstruct the signals produced by CCFs with HIF, which were shown to be complicated, aperiodic, asymmetric, and nonlinear. A decreased sensitivity to random noise means that a given modification might not affect equally all component peaks. This allows for more precise signal recovery. The maximum voltage cross-correlation coefficients were carefully evaluated as distinguishing elements in the development of a suggested fault detection technique. The proposed concept was evaluated on a modified imbalanced IEEE 240 bus system under different case studies. These case studies cover a wide range of scenarios, such as the switching of a capacitor bank, feeder energization, and the effects of nonlinear loads under noisy conditions.
Using a Chaotic Digital System to Generate Random Numbers for Secure Communication on 5G Networks
Authors: Alrikabi Haider Th. Salim , Aljazaery Ibtisam A. , Alaidi Abdul Hadi Mohammed
Published: April 2024

There are several encryption system applications in 5G networks where rapid response is needed, particularly in the military, health sector, traffic, and vehicular movement. This article presents a proposed data security system for 5G networks that fortifies the security of the network through the use of synchronized chaotic systems to produce pseudo-random numbers. The technique by which random numbers are generated during the encryption procedures is closely associated with 5G network security. Many synchronized chaotic systems are used to produce chaotic random models which are used as encryption bases for a wide variety of data. In this study, the encryption was carried out using a variety of data, including two and three-dimensional color images and audio signals of varying lengths, in addition to the use of Fast Fourier Transform (FFT) for encryption of the ingredient energy wave. The results revealed that the algorithm deployed in the process of encryption performed well. Simulations were performed in MATLAB.
A Study on the Influence of FDM Parameters on the Tensile Behavior of Samples made of PET-G
Authors: Zisopol Dragos Gabriel , Minescu Mihail , Iacob Dragos Valentin
Published: April 2024

This experimental study investigated the influence of FDM 3D printing parameters on the tensile behavior of PET-G-made parts. In this context, 27 test specimens were produced using FDM on the Anycubic 4 Max Pro 2.0 printer with layer heights applied in one pass Lh = 0.10/0.15/0.20 mm and filling percentages Id = 50/75/100 %. All these samples were tensile tested on the Barrus White 20 kN universal testing machine. The experimental results determined maximum tensile strength, elongation percentage at break, and Young's modulus. The two parameters considered, Id and Lh, influence the maximum tensile strength, the elongation percentage at break, and Young's modulus. The findings demonstrated that the filling percentage has a strong influence on the maximum tensile strength and the elongation percentage at the break of the PET-G samples, and Lh has a decisive influence on Young's modulus.
A Spectrotemporal EEG Mapping Approach for Decoding Imagined Marathi Language Phonemes
Authors: Mhapankar Umesh , Shah Milind
Published: April 2024

Individuals facing verbal communication impairments resulting from brain disorders like paralysis or autism encounter significant challenges when unable to articulate speech. This research proposes the design and development of a wearable system capable of decoding imagined speech using electroencephalogram (EEG) signals obtained during the mental process of speech generation. The system’s main objective is to offer an alternative communication method for individuals who can hear and think but face challenges in articulating their thoughts verbally. The design suggested includes user-friendliness, wearability, and comfort for seamless integration into daily life. A minimal number of electrodes are strategically placed on the scalp to minimize invasiveness. Achieving precise localization of the cortical areas responsible for generating the EEG patterns during imagined speech is vital for accurate decoding. Literature studies are utilized to determine the cortical positions associated with speech processing. Due to the inherent limitations in EEG spatial resolution, meticulous experiments are conducted to map the scalp positions onto their corresponding cortical counterparts. Specifically, we focus on identifying the scalp location over the superior temporal gyrus (T3) using the internationally recognized 10-20 electrode placement system by employing a circular periphery movement with a 2 cm distance increment. Our research involves nine subjects spanning various age groups, with the youngest being 23 and the oldest 65. Each participant undergoes ten iterations, during which they imagine six Marathi syllables. Our work contributes to the development of wearable assistive technology, enabling mute individuals to communicate effectively by translating their imagined speech into actionable commands. This innovation ultimately enhances their social participation and overall well-being.
Advancing IoT Cybersecurity: Adaptive Threat Identification with Deep Learning in Cyber-Physical Systems
Authors: Atheeq C. , Sultana Ruhiat , Sabahath Syeda Asfiya , Mohammed Murtuza Ahmed Khan
Published: April 2024

Securing Internet of Things (IoT)-enabled Cyber-Physical Systems (CPSs) can be challenging because security solutions intended for typical IT/OT systems may not be as effective in a CPS setting. The goal of this study is to create a mechanism for identifying and attributing two-level ensemble attacks that are specifically designed for use against Industrial Control Systems (ICSs). An original ensemble deep representation learning model is combined with decision tree algorithm to identify assaults on unbalanced ICS environments at the first level. An attack attribution network, which constitutes a collection of deep neural networks, is formed at the second level. The proposed model is tested using real-world datasets, notably those pertaining to water purification and gas pipelines. The results demonstrate that the proposed strategy outperforms other strategies with comparable computing complexity and that the recommended model outperforms the existing mechanisms.
The Role of Machine Learning in Managing and Organizing Healthcare Records
Authors: Alghamdi Ahmed Mohammed , Al-Khasawneh Mahmoud Ahmad , Alarood Ala , Alsolami Eesa
Published: April 2024

With the exponential growth of medical data, Machine Learning (ML) algorithms are becoming increasingly important to the management and organization of healthcare information. This study aims to explore the role that ML can play in optimizing the management and organization of healthcare records, by identifying the challenges, advantages, and limitations associated with this technology. Consequently, the current study will contribute to the understanding of how ML might be applied to the healthcare industry in a variety of circumstances. Using the findings of this study, healthcare professionals, researchers, and policymakers will be able to make informed decisions regarding the adoption and implementation of ML techniques for regulating healthcare records. The findings of this paper revealed that ML can play an important role in efficiently directing and classifying healthcare records using different perspectives.
A Systematic Literature Review on Construction Management Productivity Enhancement by utilizing Business Information Modeling
Authors: Saja Abd Alrazaq Khamees , Sawsan Rasheed Mohammed
Published: April 2024

The systematic review of Business Information Modeling (BIM) plays a crucial role in understanding its significance and impact. This review allows for a comprehensive examination of the existing literature, highlighting the benefits, challenges, and success factors associated with BIM. There is a scarcity of studies dealing with this subject, and so a question about the most important advantages that will be obtained by the construction industry, especially the construction companies, as a result of the BIM application arises. Relevant previous studies were reviewed and their quality was evaluated using a systematic methodology. The current study was characterized by the use of the SWOT (Strengths, Weaknesses, Opportunities, and Threats) analysis technique. As far as is known, the current study is the first of its kind in the field of Iraqi project management. The results suggest that the BIM benefits include firm's growth, organizational performance, enhanced market value, employee motivation, and service quality.
Magnesium Oxide (MgO) as a Sustainable Catalyst for Biodiesel Production from Waste Cooking Oil: A Comparative Study with KOH
Authors: Eladeb Aboulbaba
Published: April 2024

The present study investigates the efficiency of magnesium oxide (MgO) as a heterogeneous catalyst in the production of biodiesel from waste cooking oil (WCO), putting an emphasis on its environmental benefits, cost-effectiveness, and operational efficacy. Through a series of experiments, we optimized the reaction conditions, including catalyst concentration, reaction temperature, and ethanol to WCO molar ratio, to achieve a high biodiesel yield. The results indicate that an optimal MgO concentration of 3 wt%, a reaction temperature of 65 °C, and a molar ratio of 9:1 result in the highest biodiesel production efficiency. Additionally, MgO demonstrated significant reusability without a decrease in performance, underscoring its economic and environmental advantages. Comparative analysis revealed that MgO outperforms conventional KOH catalysts in terms of yield, purity, and sustainability. Our study suggests future research directions, including the optimization of MgO preparation methods and the exploration of co-catalyst systems to further enhance biodiesel production from WCO. This research contributes to the development of sustainable biodiesel production methods, aligning with global energy and environmental goals.
A Study on the Influence of FDM Parameters on the Compressive Behavior of PET-G Parts
Authors: Zisopol Dragos Gabriel , Minescu Mihail , Iacob Dragos Valentin
Published: April 2024

This article presents the results of a study on the influence of Fused Deposition Modeling (FDM) 3D printing parameters on the compressive behavior of test specimens made of PET-G. In this context, 45 test specimens, made by FDM on the Anycubic 4 Max Pro 2.0 printer, were compressive tested on a universal testing machine Barrus White 20 kN, with the height of the layer applied in one pass being Lh = 0.10/0.15/0.20 mm and filling percentage Id = 50/75/100%. The two considered variable parameters, Lh and Id influence the compression resistance of the PET-G parts, with Id having a more significant influence. The scope and novelty of this work is to find the optimal parameters for maximum compressive strength (Cs) of PET-G samples made of FDM.
Optimizing the Supercritical Carbon Dioxide Extraction of Hibiscus Flower Essential Oil using Response Surface Analysis
Authors: Alanazi Tahani Y. A.
Published: April 2024

The development of Supercritical Fluid Extraction (SFE) has opened the door to the harvesting of plants for a wide range of chemical compounds. This study distilled essential oil from hibiscus flowers utilizing the supercritical CO2 method. Different extraction parameters, including pressure (100-300 bar) and temperature (300-350 K), were studied to visualize how they affected oil recovery. Response surface analysis was used to fine-tune the extraction process. The chemical composition of the recovered oil was analyzed by Gas Chromatography-Mass Spectrometry (GC-MS). According to the findings, 13.11% per 80 g of dry flowers is the ideal oil extracted from Hibiscus flowers, using SFE at 200 bar pressure and 325 K extraction temperature. Six compounds were provisionally identified in the extracted oil from hibiscus flowers under optimum SFE conditions.
Deep Learning, Ensemble and Supervised Machine Learning for Arabic Speech Emotion Recognition
Authors: Ismaiel Wahiba , Alhalangy Abdalilah , Mohamed Adil O. Y. , Musa Abdalla Ibrahim Abdalla
Published: April 2024

Today, automatic emotion recognition in speech is one of the most important areas of research in signal processing. Identifying emotional content in Arabic speech is regarded as a very challenging and intricate task due to several obstacles, such as the wide range of cultures and dialects, the influence of cultural factors on emotional expression, and the scarcity of available datasets. This study used a variety of artificial intelligence models, including Xgboost, Adaboost, KNN, DT, and SOM, and a deep-learning model named SERDNN. ANAD was employed as a training dataset, which contains three emotions, "angry", "happy", and "surprised", with 844 features. This study aimed to present a more efficient and accurate technique for recognizing emotions in Arabic speech. Precision, accuracy, recall, and F1-score metrics were utilized to evaluate the effectiveness of the proposed techniques. The results showed that the Xgboost, SOM, and KNN classifiers achieved superior performance in recognizing emotions in Arabic speech. The SERDNN deep learning model outperformed the other techniques, achieving the highest accuracy of 97.40% with a loss rate of 0.1457. Therefore, it can be relied upon and deployed to recognize emotions in Arabic speech.
Advancements in Vaccine Drug Delivery Systems: A Comprehensive Review
Authors: Punam Narwade  , Vaishnavi Bora  , Dr Aijaz Sheikh  , Dr. K, R, Biyani
Published: April 2024

Vaccine drug delivery systems have undergone significant advancements, revolutionizing the landscape of preventive medicine. This review provides a comprehensive overview of various types of vaccine delivery systems, highlighting their mechanisms, advantages, and applications. Traditional vaccine administration methods, such as intramuscular and subcutaneous injections, are being supplemented by novel approaches aimed at improving efficacy, safety, and patient compliance. These include nanoparticle-based carriers, liposomes, microneedle patches, mucosal delivery systems, and DNA/RNA-based vaccines. Each delivery platform offers distinct advantages, such as targeted antigen delivery, controlled release kinetics, enhanced immunogenicity, and needle-free administration. Moreover, the emergence of mRNA vaccines has garnered significant attention for their potential to rapidly respond to emerging infectious diseases. Additionally, the integration of adjuvants and immunomodulatory agents further enhances the immune response, paving the way for next-generation vaccines. Understanding the diverse landscape of vaccine delivery systems is crucial for optimizing immunization strategies, overcoming existing challenges, and combating infectious diseases more effectively in the future.
Vivências da Pós-Graduação: As competências adquiridas na perspectiva dos egressos
Authors: Borsatto Catiane , Barros Igor Ribeiro , Larentis Fabiano , Giacomello Cintia Paese , Lazzari Fernanda
Published: April 2024

Por meio dos Programas de Pós-Graduação, espera-se a formação de pessoas capazes que, dentro e fora das instituições de ensino, possam transformar os conhecimentos científicos em atuações profissionais significativas e inovadoras para a sociedade. Desta forma, este estudo objetiva analisar as competências adquiridas por egressos após a conclusão do curso de pós-graduação stricto sensu. Para tanto, através de um estudo qualitativo genérico, utilizou-se como técnica de coleta de dados a entrevista narrativa com nove egressos de um curso de mestrado na área de administração e, como método de análise dos dados, optou-se pela análise de conteúdo. Os resultados demonstram o surgimento de catorze competências adquiridas durante o período de dois anos de trajetória acadêmica, que juntas, compreendem os três eixos que compõem o conceito de competência: biografia e socialização, formação educacional e experiência profissional. Apesar de cada curso de pós-graduação ter seu formato e nível de aprendizado, ao final, as habilidades e competências desenvolvidas acabam ajudando o egresso a tomar decisões de forma mais eficiente e com sabedoria, para atuar tanto na organização quanto na academia.
Ocean state rising: Storm simulation and vulnerability mapping to predict hurricane impacts for Rhode Island’s critical infrastructure
Authors: Adams Samuel , Becker Austin , McElroy Kyle , Hallisey Noah , Stempel Peter , Ginis Isaac , Crowley Deborah
Published: April 2024

Predicting the consequences of a major coastal storm is increasingly difficult as the result of global climate change and growing societal dependence on critical infrastructure (CI). Past storms are no longer a reliable predictor of future weather events, and the traditional approach to vulnerability assessment presents accumulated loss in largely quantitative terms that lack the specificity local emergency managers need to develop effective plans and mitigation strategies. The Rhode Island Coastal Hazards Modeling and Prediction (RI-CHAMP) system is a geographic information system (GIS)-based modeling tool that combines high-resolution storm simulations with geolocated vulnerability data to predict specific consequences based on local concerns about impacts to CI. This case study discusses implementing RI-CHAMP for the State of Rhode Island to predict impacts of wind and inundation on its CI during a hurricane, tropical storm, or nor’easter. This paper addresses the collection and field verification of vulnerability data, along with RI-CHAMP’s process for integrating those data with storm models. The project deeply engaged end-users (emergency managers, facility managers, and other stakeholders) in developing RI-CHAMP’s ArcGIS Online dashboard to ensure it provides specific, actionable data. The results of real and synthetic storm models are presented along with discussion of how the data in these simulations are being used by state and local emergency managers, facility owners, and others.
Leveraging technology in emergency management: An opportunity to improve compounding and cascading hazards linked to climate change
Authors: Hertelendy Attila
Published: April 2024

The Intergovernmental Panel on Climate (IPCC) Sixth Assessment report concluded that we will see an increase in frequency of extreme environmental events around the world including, hurricanes, droughts, and wildfires.1 The report further describes cascading hazards when one hazard triggers another in a series such as extreme heat triggering a collapse of the power grid. The IPCC also discusses compounding hazards as multiple disasters occur at the same time for example a hurricane occurring at the same time as COVID-19 and a mass casualty event prompting a Urban Search & Rescue (USAR) response such as the Surfside and the Florida condo collapse.2 Studies suggest that there are gaps relating to Hazard Mitigation Plans (HMP) in addressing cascading events.3,4
Faktor-Faktor Yang Mempengaruhi Independensi Hakim Di Pengadilan
Authors: Nurwandri Andri , Syam Nur Fadhilah , Fadhillah Dimas Ari , Larasari Suryani , Nurmala Nurmala , Tambunan Nani Astuti , Sulina Sulina
Published: April 2024

The purpose of this writing is to contribute ideas to the public regarding the problems of the independence of judges as executors of judicial power, and is a legal instrument for judges in carrying out their function of adjudicating and deciding a case presented to them so that they are free from all interference and/or influence from other power environments, whether from the organ environment. executive power as well as from within the organs of legislative power. This article uses a normative research type, and providing the results of this research suggests that judges in deciding cases in Indonesia still exist to explore and find a sense of justice in society, even with a religious norms approach where it is known that Indonesian society is quite obedient to religious norms.
Penguatan Civic Skill: Sebagai Kemampuan Berpikir Kritis Siswa Untuk Mencegah Fomo yang Menjadi Trend Baru Dalam Bermedia Sosial
Authors: Purba Griyani Elisabeth , Sembiring Nike Margaretha Br , Purba Rani Oktavia , Simanullang Tessa Lonika , Batubara Abdinur
Published: April 2024

Penelitian ini membahas tentang penguatan civic skill sebagai kemampuan berpikir kritis siswa untuk mencegah FOMO (Fear of Missing Out) yang menjadi tren baru dalam bermedia sosial. Civic skill merupakan kemampuan untuk berpartisipasi aktif dalam masyarakat, dan dalam konteks ini, fokus pada kemampuan siswa untuk secara kritis mengevaluasi informasi yang mereka temui di media sosial. FOMO adalah kecemasan akan kehilangan momen atau pengalaman yang sedang terjadi di media sosial, yang dapat berdampak negatif pada kesejahteraan mental individu. Dalam konteks ini, penelitian ini mengusulkan strategi penguatan civic skill sebagai upaya untuk mengurangi dampak negatif dari FOMO. Melalui pendekatan pembelajaran yang mempromosikan pemikiran kritis, siswa akan dilengkapi dengan keterampilan untuk mengevaluasi informasi yang mereka temui di media sosial, mengidentifikasi konten yang berpotensi memicu FOMO, dan mengembangkan strategi untuk mengelola perasaan tersebut. Diharapkan bahwa penelitian ini dapat memberikan kontribusi dalam pengembangan pendidikan yang mempersiapkan generasi muda untuk menjadi pengguna media sosial yang cerdas dan kritis, serta mampu mengatasi dampak negatif dari tren seperti FOMO.
Titelthema Kupplungen: Kupplungssensor AIQ-Detect - Upgrade your uptime
Authors:   Benedikt Lipphard
Published: April 2024

Aktuell führt Flender denKupplungssensor AIQ Detect in denMarkt ein. Es handelt sich dabei umeine bahnbrechende Neuerung zurÜberwachung semi-elastischerKupplungen von Flender. Der digitaleVerschleißanzeiger revolutioniert dieWartungspraktiken: Er liefert EchtzeitEinblicke in den Zustand dieser kritischenKomponenten und gewährleistet sooptimale Leistung und Zuverlässigkeit.
Steuerung für Pick-And-Place-Einheiten: Schnelle Werkzeugwahl per Touch
Authors:   Hans-Joachim Müller
Published: April 2024

Wenn viele unterschiedliche Werkstücke auf einer Maschine verarbeitet werdensollen, spielen Umrüstzeiten eine wichtige Rolle. Großen Zeitgewinn versprichtder Pick-and-Place-Roboter „Seibot“ der Erfurter Firma Seitec. Er ist ausgerüstetmit Komponenten aus dem Automatisierungsbaukasten Movi-C vonSEW-Eurodrive. Das Besondere: für alle Robotergeometrien kommt immer diegleiche, standardisierte Schnittstelle zwischen der Robotersteuerung mit demSoftwaremodul Movikit Robotics und der übergeordneten Steuerung zum Einsatz.
Wellenfedern in Wälzlagerbaugruppen: Optimal vorspannen und Toleranzen ausgleichen
Authors:   Marco Sturm
Published: April 2024

Das zielsichere Einstellen derVorspannungen und der präziseToleranzausgleich sind zentrale Aspekte beider Konstruktion dynamischer WälzlagerBaugruppen. Bei steigendenQualitätsanforderungen können hierWellenfedern aus gewalztem Flachdrahteine interessante Lösung darstellen.Welche Vorteile sie gegenüber anderenFedertypen bieten, erklärt ein führenderAnbieter von Smalley-Sicherungsringenund Wellenfedern.
Condition-Monitoring-System: Ein EYE darauf haben
Authors:   André Sitzmann
Published: April 2024

In der industriellen Fertigung ist die präventive Wartung von Maschinen und Anlagenvon entscheidender Bedeutung. Durch die kontinuierliche Überwachung vonBetriebsparametern vom Ölmonitoring bis zur Schwingungsanalyse könnenpotenzielle Schäden frühzeitig erkannt werden, bevor sie zu kostspieligenMaschinenausfällen führen. Für Antriebssysteme bietet die Eye-Produktreihe vonSumitomo Drive Technologies eine integrierte Lösung zur Zustandsüberwachung undOptimierung von Maschinen und Anlagen.
Additive Fertigung mit CNC-Technologie verbinden: Präzision und Dynamik für komplexe Bauteilgeometrien
Authors:   Stefan Ziegler
Published: April 2024

Laserauftragschweißen wird häufig zumBeschichten rotationssymmetrischerBauteile eingesetzt. Mit dem 5-achsigenpE3D-System erweitert Ponticon nundas Einsatzspektrum, sodass eineBeschichtung und additive Fertigungbeliebiger Geometrien möglich wird.Die Ansteuerung und Koordination vonTripod, Dreh-/Schwenktisch und Lasererwies sich als besonders anspruchsvollund konnte mit Technologien vonBeckhoff realisiert werden.
Guidelines for obesity clinic consultations in primary healthcare clinics
Authors: Kang Jee-Hyun , Kim Kyoung-Kon
Published: April 2024

Background: The prevalence of obesity and its public health implications underscore the necessity for prioritizing its prevention and care in primary healthcare clinics.Current Concepts: The establishment of dedicated obesity clinics requires a comprehensive initial assessment of patients, ideally facilitated by a pre-consultation questionnaire. The initial assessment of patients includes a detailed patient interview, thorough physical examination, body composition analysis, and evaluation of visceral adiposity. Identifying potential causes of secondary obesity, particularly drug-induced obesity, is imperative before the initiation of treatment. The primary goal of obesity management transcends weight reduction alone and should encompass the improvement of overall health status, addressing concurrent comorbidities. Individualized treatment goals are established after a thorough assessment. Although the cornerstone of obesity management is the promotion of a healthier lifestyle, personalized approaches tailored to the circumstances of each patient are advocated for long term sustainability. Dietary and exercise recommendations should be personalized and introduced progressively. Pharmacotherapy can significantly potentiate lifestyle modification efforts for weight reduction. However, the selection of pharmacological agents must be reasonable, considering factors as comorbid conditions, severity of obesity, previous weight gain history, and economic constraints related to treatment. Dosing regimens should be meticulously calibrated and adjusted as necessary, with vigilant monitoring of the therapeutic efficacy and potential adverse reactions.Discussion and Conclusion: Effective obesity management in primary healthcare clinics involves thorough assessment, goal setting, recommendation of individualized lifestyle modifications, and careful implementation of suitable pharmacotherapy.
Amerikan Fundamentalizminde Televaizliğin Önemi: Pat Robertson Örneği
Authors: Abaydın Huriye
Published: April 2024

Fundamentalistler 20. asrın başında Amerika’daki evanjelikler arasında aşırı liberalleşmeye ve özellikle de Kutsal Kitap üzerinde yapılan yoğun kritiklere tepki olarak ortaya çıkan bir gruptur. İsimlerinin fundamentalist olarak anılması 20. yüzyıl başında yazılan The Fundamentals adlı eser sebebiyledir. Kutsal Kitap’ı literal olarak okuyan fundamentalistlerin ayırıcı bir özelliği de binyılcı anlayışa sahip olmalarıdır. Modernlik karşıtı bir hareket şeklinde ortaya çıkmalarına rağmen fundamentalistlerin modern dönemin önemli göstergelerinden medyayı çok iyi kullanmaları önceden olmayan televanjelist kavramını ortaya çıkarmıştır. Bu grup ilk başlarda radyo, daha sonra televizyon ve son dönemlerde interneti yetkin olarak kullanmıştır. Özellikle seyirciyle birlikte yapılan programlarda detaylı tasvirlerle Yeni Ahit okumaları, dua saatleri ve etkili vaazlar verilir. Bu kişiler arasında önde gelen bir isim Pat Robertson, kurduğu uydu ağıyla ve yaptığı kesintisiz yayınlarla kısa sürede büyük kitlelere ulaşmış ve Amerika’da dini yayıncılık alanında önemli bir isim olmuştur.