Numerous Forms Research Articles

A functional exercise program improves pain and health related quality of life in patients with fibromyalgia: a randomized controlled trial

Background/objectiveFibromyalgia is a non-inflammatory syndrome characterized by generalized muscle pain, with other symptoms. Numerous forms of physical training for this population have been studied through high-quality randomized clinical trials involving strength, flexibility, aerobic conditioning and multicomponent exercise interventions. This research evaluated the effectiveness of a functional exercise program at reducing pain, improving functional capacity, increasing muscle strength as well as improving flexibility, balance and quality of life in individuals with fibromyalgia.MethodsEighty-two women with fibromyalgia were randomized into two groups. The functional exercise group performed functional exercises in 45-minute sessions twice per week for 14 weeks. The stretching exercise group performed flexibility exercises with the same duration and frequency. Outcome measures were: visual analog scale for widespread pain; Fibromyalgia Impact Questionnaire for health-related quality of life; Timed Up and Go test for functional performance; one-repetition maximum for muscle strength, Sit and Reach test on Wells bench for flexibility; Berg Balance Scale for balance; SF-36 for general quality of life.ResultsAfter the intervention, the functional exercise group had a statistically significant reduction in pain (interaction p = 0.002), and improvement in health-related quality of life measured by the Fibromyalgia Impact Questionnaire (interaction p < 0.001) and in general health state domain of SF-36 (interaction p = 0.043) compared to the stretching exercise group. No significant differences between groups were found regarding improvements in functional capacity, muscle strength, flexibility or balance.ConclusionFunctional exercise training was effective at reducing pain and improving quality of life in patients with fibromyalgia compared to stretching exercises.Trial registrationClinicalTrials.gov Identifier: NCT03682588 First prospectively registered in March 2018.

Examining Stakeholders’ Prospects on the Implementation of Equity-Based Strategies in Public Secondary Schools in Tanzania

The desire to address equity issues in the education sector is a shared philosophy by a number of countries, including Tanzania. As a result, Tanzania as a country is striving to address the issue of equity in its education system through the implementation of various equity strategies. This paper therefore sought to examine stakeholders’ prospects on the implementation of equity-based strategies in public secondary schools in Tanzania. Precisely, the interest of the researchers was to explore what was being done in the selected public secondary schools to implement equity-based strategies. A mixed-methods research approach combining both qualitative and quantitative analysis approaches was employed. The study also used a multiple case study design, which allowed the selection of two case study areas i.e. Dodoma City representing the urban setting, and Kondoa district representing the rural setting. A total of One Hundred Forty-Four (144) participants from seven (7) public secondary schools were involved in the study. Data were collected through interviews and questionnaires. Quantitative data were analyzed through descriptive analysis and presented in numerical and graphical form while qualitative data were analyzed through inductive content analysis and presented in thematic form and narratives. Study findings revealed that the selected study schools were indeed implementing a number of activities towards the realization of equity and thus the prospects for implementing equity based strategies in these schools was found to be positive. For instance, activities such as the use of common and understandable language i.e., English and Kiswahili; ensuring that schools have qualified teaching staff, ensuring a supportive learning environment as well as strengthening and supporting school leadership were being implemented. Nevertheless, the study also noted that the implementation of some key factors critical for realization of equity in the schools such as incentive provision to teachers, use of appropriate technology and use of different learning styles was still weak and thus needed improvement.

‘We Must Find a Way to Remember Them Too’: British Second World War Conscientious Objectors in Post-War Culture

This article examines the ways in which British Second World War conscientious objectors (COs) have been commemorated, memorialized, and represented since 1945. Despite comprising nearly 60 000 men, the CO is strikingly absent in both the popular narrative of the Second World War and official, institutional commemorations of the conflict. This is not true of their First World War counterpart. This is unsurprising: the Second World War CO is largely at odds with popular British conceptions of the war as a ‘just’ conflict. Nevertheless, a broad and diverse set of initiatives have been established to commemorate the CO. The CO also features in numerous forms of post-war popular culture, including fiction, films, television programmes, and plays. It is these disparate remembrance practices and representations that this article brings together to help us explore both the memory of wartime conscientious objection and the broader cultural legacies of the Second World War.

Cardiovascular pathology in the handicapped patient

As is well known, the clinical definition of a handicapped patient is remarkably complex and extensive, encompassing numerous well-defined aetiological forms but also a wide range of cases in which the handicap is related to non-specific or unknown hereditary factors or to socio-economic and hygienic environmental factors.

Exploring botanical diversity, ecological traits, and edaphic determinants in Kala Chitta National Park, Pakistan: Implications for conservation and management

Globally, environmental degradation has prompted several countries to strengthen their protected area networks to halt biodiversity loss. National parks incorporate into their design, are based on scientific evidence, and offer a complete management mechanism to enable successful conservation for the most ecologically critical and vulnerable ecosystem. However, managing these protected areas effectively requires a grasp of the complex dynamics of plant ecosystems and edaphic factors. Nevertheless, Pakistan's protected areas have seen the least investigation of these relationships. To fill this knowledge gap, this study investigates the vegetation dynamics and edaphic factors that influence plant distribution in Kala Chitta National Park of Pakistan. A comprehensive botanical survey documented 203 plant species across 60 study sites, revealing a diverse flora comprising species from 160 genera and 54 families. The most abundant families were Poaceae (34 species) and Fabaceae (21 species), Amaranthaceae (13 species) and Asteraceae (15 species). The majority of species were herbaceous (49.2%), followed by grasses (16.7%) and shrubs (15.2%). Climbers and ferns constituted 1.4% and 1.9% of the total, respectively, with co-dominant habits of tall reed and sedge accounting for 2.9% of the vegetation. Ecologically, Therophytes emerged as the most numerous life forms (42.8%), followed by hemicryptophytes (17.7%) and megaphanerophytes (8.3%). Analysis of leaf spectra revealed Nanophylls as the dominant type (36.9%), followed by Microphylls (33%). Phytogeographical distribution highlighted three major clusters, with Asia Tropical, Asia Temperate, and Europe accounting for 45% of species. Four distinct plant communities were identified using TWINSPAN analysis: Senegalia-Dichanthium-Justica (SDJ), Neltuma-Lantana-Cannabis (NLC), Prosopis-Saccharum-Desmostachya (PSD), and Dodonaea-Alhagi-Oxalis (DAO). Each community exhibited unique species compositions and ecological gradients influenced by edaphic factors. PCA revealed associations between specific edaphic variables and plant communities, with available phosphorus (AP) and potassium (AK) linked to the NLC community. At the same time, total nitrogen (TN) was predominantly associated with the DAO community. These findings highlight the importance of soil conservation and sustainable land management practices for preserving biodiversity and ecosystem integrity within Kala Chitta National Park. Future research should focus on long-term monitoring of vegetation dynamics and collaborative conservation initiatives involving local stakeholders to promote ecosystem resilience in the face of environmental change.

Staff Perspectives on the Role of Public Libraries in Facilitating College Literacy

The decision-making process for potential college students in the United States is overwhelming because of the volume of information available and the complexity of higher education systems. Prospective students must consider institutional rankings, academic programs, and financial aid opportunities in addition to completing numerous forms. For some students, there exist personal and professional advisors and resources to assist with navigating the process. Others with less social and cultural capital must figure out the system with little or no assistance while facing other barriers. Public libraries can be a resource for the college-bound community; however, research shows that public libraries are not actively engaged in supporting this user group. To provide focused, quality information services to any demographic, it is important to understand the perspectives of public-facing information workers. Through a cross-sectional online questionnaire of library staff across four states, this study sought to learn staff perspectives on the role of public libraries in serving prospective college students. The survey received 160 responses of which 100 open-ended responses pertained to the role of public libraries. Qualitative inductive analysis point to three core themes on the role of public libraries in serving this population, that of connector, provider, and supporter. A fourth theme suggests staff see the role as one for others to meet. This article provides insight into past examinations of public library support of college literacy offering an opening to further discussions on serving this overlooked user group.

A Knowledge Graph-Based Consistency Detection Method for Network Security Policies

Network security policy is regarded as a guideline for the use and management of the network environment, which usually formulates various requirements in the form of natural language. It can help network managers conduct standardized network attack detection and situation awareness analysis in the overall time and space environment of network security. However, in most cases, due to configuration updates or policy conflicts, there are often differences between the real network environment and network security policies. In this case, the consistency detection of network security policies is necessary. The previous consistency detection methods of security policies have some problems. Firstly, the detection direction is single, only focusing on formal reasoning methods to achieve logical consistency detection and solve problems. Secondly, the detection policy field is not comprehensive, focusing only on a certain type of problem in a certain field. Thirdly, there are numerous forms of data structures used for consistency detection, and it is difficult to unify the structured processing and analysis of rule library carriers and target information carriers. With the development of intelligent graph and data mining technology, the above problems have the possibility of optimization. This article proposes a new consistency detection approach for network security policy, which uses an intelligent graph database as a visual information carrier, which can widely connect detection information and achieve comprehensive detection across knowledge domains, physical devices, and detection methods. At the same time, it can also help users grasp the security associations with the real network environment based on the graph algorithm of the knowledge graph and intelligent reasoning. Furthermore, these actual network situations and knowledge bases can help managers improve policies more tailored to local conditions. This article also introduces the consistency detection process of typical cases of network security policies, demonstrating the practical details and effectiveness of this method.

Design redistribution: the role and involvement of craftsmen in the embodiment of design in the Indonesian rattan furniture industry

ABSTRACT This article explores the roles and positions of craftsmen in the design development within the Indonesian rattan furniture industry. Positioned as subcontractors, craftsmen play an essential role in the design development process, particularly in the exploration and interpretation of sketch drawings into prototypes that meet buyers’ specifications and gain their approval. This research utilised a phenomenological approach to explore the experiences of craftsmen in creating prototypes conveyed solely through sketch drawings. Rattan furniture design is generally dynamic and organic, characterised by numerous curves and complex forms that are challenging to depict accurately. Sketch drawings are rough and often lack proper proportions, scalability, standardisation, and intricate details, leading to varying interpretations of the prototype sketch drawings. Based on their experience and creativity, the craftsmen create prototypes solely by referring to sketch drawings. Consequently, there has been a significant collaboration between contractors and craftsmen as subcontractors in the design process. This research is part of an initiative aimed at recognising craftsmen as marginalised participants in small business entities, highlighting their contributions and rights within the collaborative design process.

Evaluating the Effectiveness of Machine Learning-Based Intrusion Detection in Multi-Cloud Environments

In the dynamic landscape of cloud computing, multi-cloud environments have emerged as the prevalent ones due to offering a host of advantages including redundancy, flexibility, and increased security. These multi-cloud environments can, however, be vulnerable to stealthy cyber-attacks, thereby making it a challenging job to find efficient intrusion detection systems (IDS). The efficiency of the Machine Learning-based Intrusion Detection System in multi-cloud environments has been evaluated using a 1-D Convolutional Neural Network to classify network traffic based on the UNSW-NB15 dataset. The dataset included a wide variety of network features, and it was decided that it could be used directly after converting the categorical variables into their numerical forms and scaling them with MinMaxScaler. This was used for training and testing the 1D-CNN model, which had attained an accuracy of 84.02% during training and 82.79% on validation. Further, the performance of the model is elicited with metrics that include precision at 80.91%, recall at 82.79%, and an F1-score at 81.28%, showing its capability in identifying network intrusions effectively. The small difference between the accuracy of training and validation shows that overfitting was minimal; thus, the model will generalize well when applied to unseen data. This research underlines the possibility of using deep learning techniques, and particularly CNNs, for intrusion detection in complex multi-cloud infrastructures. Probably future work would be optimizing the model through hyperparameter tuning, using additional sources of data, and even exploring much more sophisticated architectures that will further improve the accuracy of intrusion detection.

Oily Wastewater Treatment by Using Fe3O4/Bentonite in Fixed-Bed Adsorption Column

Oily wastewater is a major environmental issue resulting from different industrial and manufacturing activities. Contaminated water with oil represents a significant environmental hazard that can harm numerous life forms. Several methodologies have been tested for the removal of oily wastewater from aqueous solutions, and adsorption in a flow-through reactor is an effective mechanism to reduce these effluents. This study focuses on evaluating the ability of Fe3O4/Bent material to adsorb gasoline emulsion from a solution using a fixed-bed column, and it involves analyzing the resulting breakthrough curves. The FT-IR, SEM, EDX, and XRD techniques were used to characterize Fe3O4/Bent. Various ranges of variables were examined, including bed height (2–4 cm), flow rate (3–3.8 mL/min), and initial concentration (200–1000 mg/L), to determine their impacts on the mass transfer zone (MTZ) length and the adsorption capacity (qe). It was shown that a higher bed height and a lower flow rate contributed to a longer time of breakthrough and exhaustion. At the same time, it was noted that under high initial gasoline concentrations, the fixed-bed system rapidly reached breakthrough and exhaustion. Models like the Yoon–Nelson and Thomas kinetic column models were employed to predict the breakthrough curves. Thomas and Yoon–Nelson’s breakthrough models provided a good fit for the breakthrough curves with a correlation coefficient of R2 &gt; 0.95. Furthermore, with a fixed-bed system, the Thomas and Yoon–Nelson models best describe the breakthrough curves for gasoline removal.

Synthesis of expert matrices in inductive system-analytical research based on fuzzy logic algorithm

The object of research is the process of inductive modeling of complex systems. The studies that were conducted related to the application of algorithms of the fuzzy logic theory were to coordinate the conclusions of top-level experts in system information-analytical research (SIAR) in the tasks of innovative design. The possibilities of constructing elements of expert matrices of results, as well as evaluating the effectiveness of such applications, are defined. Thanks to this, obtaining formal expert evaluations in numerical form became possible. Experimental studies have confirmed that the proposed approach to the application of fuzzy logic algorithms to the construction of matrices of expert evaluations of SIAR results is quite effective and simple to implement. In addition, this approach fits well into the general paradigm of the Group Method of Data Handling (GMDH). In particular, it was established that the possibility of «retraining» such a block without significant efforts of professional experts can have a positive result, as well as have a good effect on the economic and time parameters of the research project. The main calculation formulas for the algorithm for building a fuzzy system using a neural network in a system with two rules are given. The construction of a fuzzy information output system trained on expert evaluations in the Matlab system is shown. As a result, a technologically acceptable standard deviation of 0.28268 mg/l was obtained. It has been established that by accumulating a database (knowledge) and/or using an information monitoring system, it is possible to «additionally train» a fuzzy system periodically or according to the established quality criterion in the program mode, without involving experts in this process. Thus, there are reasons to assert the importance of using a fuzzy system as one of the tools in inductive SIAR procedures

Analisis Kesalahan Mahasiswa Dalam Menyelesaikan Soal Pembuktian Teorema Binomial Pada Sifat Simetrik

This research was conducted to observe students' error in working on problems proving the binomial theorem on the symmetric properties of binomial coefficients. This type of research is qualitative research. This research uses a test method, namely by working on questions followed by interviews. This research involved students from the Tadris Mathematics Study Program at Al Falah As Sunniyah Kencong Jember University in the second semester of the 2023/2024 academic year with a total of 17 students. The 17 students were grouped into 3 cognitive abilities, namely high, medium and low cognitive. The subjects of this research consisted of three students with each student representing each cognitive ability group. The results of the research show that the types of language interpretation errors are made by subjects with high and moderate cognitive abilities, namely not writing the correct sentences when drawing conclusions. Conceptual errors were made by subjects with medium and low cognitive abilities in the form of errors in the proof steps. Procedural errors were made by subjects with moderate and low cognitive abilities, namely not having carried out complete calculations when applying the theorem in numerical form. Technical errors were made by subjects with low cognitive abilities, namely writing the same steps repeatedly. Errors in drawing conclusions were made by subjects with high, medium and low cognitive abilities. The three subjects considered the verification process to be complete. All errors are caused by a lack of understanding of the concept, carelessness in the proof process and not being careful in reading the questions.

Oxidative stress-induced gene expression changes in prostate epithelial cells in vitro reveal a robust signature of normal prostatic senescence and aging

Oxidative stress has long been postulated to play an essential role in aging mechanisms, and numerous forms of molecular damage associated with oxidative stress have been well documented. However, the extent to which changes in gene expression in direct response to oxidative stress are related to actual cellular aging, senescence, and age-related functional decline remains unclear. Here, we ask whether H2O2-induced oxidative stress and resulting gene expression alterations in prostate epithelial cells in vitro reveal gene regulatory changes typically observed in naturally aging prostate tissue and age-related prostate disease. While a broad range of significant changes observed in the expression of non-coding transcripts implicated in senescence-related responses, we also note an overrepresentation of gene-splicing events among differentially expressed protein-coding genes induced by H2O2. Additionally, the collective expression of these H2O2-induced DEGs is linked to age-related pathological dysfunction, with their protein products exhibiting a dense network of protein–protein interactions. In contrast, co-expression analysis of available gene expression data reveals a naturally occurring highly coordinated expression of H2O2-induced DEGs in normally aging prostate tissue. Furthermore, we find that oxidative stress-induced DEGs statistically overrepresent well-known senescence-related signatures. Our results show that oxidative stress-induced gene expression in prostate epithelial cells in vitro reveals gene regulatory changes typically observed in naturally aging prostate tissue and age-related prostate disease.

Impact of Processing on the Bioactive Compounds and Antinutritional Factors of Lentil (Lens culinaris L.)—A Review

ABSTRACTLentil (Lens culinaris L.) is an ancient leguminous crop, with its seeds eaten in numerous forms in throughout the world. Along with macronutrients and micronutrients, it provides a range of non‐nutritional constituents, which are categorized as bioactive compounds. These compounds have immense roles in maintaining biological functions in plants and animal kingdom. Bioactive compounds in lentils consist of phenolic compounds, pigment, tocopherol, flavonoids, lectins, oxalic acid, phytic acid, and so forth. Some of these compounds are regarded as antinutritional factors (ANFs) because they prevent nutrients from being absorbed. Processing methods such as cooking, germination, fermentation, dehulling, milling, and extrusion can drastically reduce the amount of ANFs contained in lentils. The primary objective of dehulling and milling is not to reduce or eliminate the ANFs of lentils but to increase their feasibility for using in various food applications. However, the processing stresses may result good or bad effects on the bioactive molecules as well. For instance, the raw lentils may not contain any γ‐aminobutyric acid, but following germination and fermentation, it becomes abundant. In this article, we reviewed the studies on the impact assessment of processing techniques on the bioactive components of lentils. By combining existing literature, this review fills a knowledge gap on the ways that processing methods affect lentils' bioactive properties and offers valuable guidance for dietary applications and informed consumer choices. Lentils can cater to recent consumer trends for increasing preference of plant‐based proteins by offering nutrient‐dense and healthy dietary options.

CardioRiskNet: A Hybrid AI-Based Model for Explainable Risk Prediction and Prognosis in Cardiovascular Disease.

The global prevalence of cardiovascular diseases (CVDs) as a leading cause of death highlights the imperative need for refined risk assessment and prognostication methods. The traditional approaches, including the Framingham Risk Score, blood tests, imaging techniques, and clinical assessments, although widely utilized, are hindered by limitations such as a lack of precision, the reliance on static risk variables, and the inability to adapt to new patient data, thereby necessitating the exploration of alternative strategies. In response, this study introduces CardioRiskNet, a hybrid AI-based model designed to transcend these limitations. The proposed CardioRiskNet consists of seven parts: data preprocessing, feature selection and encoding, eXplainable AI (XAI) integration, active learning, attention mechanisms, risk prediction and prognosis, evaluation and validation, and deployment and integration. At first, the patient data are preprocessed by cleaning the data, handling the missing values, applying a normalization process, and extracting the features. Next, the most informative features are selected and the categorical variables are converted into a numerical form. Distinctively, CardioRiskNet employs active learning to iteratively select informative samples, enhancing its learning efficacy, while its attention mechanism dynamically focuses on the relevant features for precise risk prediction. Additionally, the integration of XAI facilitates interpretability and transparency in the decision-making processes. According to the experimental results, CardioRiskNet demonstrates superior performance in terms of accuracy, sensitivity, specificity, and F1-Score, with values of 98.7%, 98.7%, 99%, and 98.7%, respectively. These findings show that CardioRiskNet can accurately assess and prognosticate the CVD risk, demonstrating the power of active learning and AI to surpass the conventional methods. Thus, CardioRiskNet's novel approach and high performance advance the management of CVDs and provide healthcare professionals a powerful tool for patient care.

Bifurcation analysis and solitary wave solution of fractional longitudinal wave equation in magneto-electro-elastic (MEE) circular rod

In this study, we investigate the longitudinal wave equation (LWE) with the M−fractional derivative, which describes the propagation of longitudinal waves along a rod while incorporating interactions between mechanical, electrical, and magnetic fields within the material. Initially, we apply bifurcation analysis to examine the critical points or phase portraits where the system transitions to new behaviors, such as stability shifts or the emergence of chaos, and observe the mechanism of static soliton formation through a saddle-node bifurcation. Subsequently, we utilize a modified simple equation (MSE) technique to find solitary wave solutions. Depending on the relationships between free parameters, the solutions are expressed as hyperbolic, trigonometric, and exponential functions. The numerical form of the obtained solutions reveals complex phenomena, including dark and bright bell waves, kink periodic lump waves, kink periodic waves, periodic lump waves, interaction waves between kink and periodic waves, linked lump waves, and interactions of periodic and lump waves. Additionally, we compare our results with previously published work, demonstrating that the discussed methods are valuable tools for providing distinct, accurate soliton solutions relevant to nonlinear science and technology applications.

Inhibitory effects of SARS-CoV-2 penetration of host cells by garlic oil and juice extract are cultivar specific

The COVID-19 pandemic has been disastrous for global health and economy. In attempts to reduce susceptibility to SARS-CoV-2 infection, many people have turned towards traditional food remedies, such as garlic, which are thought to contain antimicrobial properties. Differences in composition between plant varieties and numerous forms of garlic preparations have contributed to the controversy as to its effectiveness herbal medicine. We sought to explore whether purified oil or juice extracted from different garlic plant varieties could prevent SARS-CoV-2 infection of cells and whether any antiviral effects were common among the varieties tested. Of over 20 garlic cultivars tested (10 in oil form and 10 in juice form), only one oil extract demonstrated strong inhibition of SARS-CoV-2 infection. Similarly, only one juice extract from a different cultivar exhibited this property, effectively limiting infection and even destroying the virion genome. It is crucial to note that these two cultivars were distinct from each other. Our findings support the fact that not all garlic plants exhibit antimicrobial effects, potentiating caution when using their extracts as herbal medicine.

Optimization of the Weir as a Micro Hydro Power Plant in Bayang Nyalo Padang, West Sumatra

The objective of this research is to guarantee that the building of PLTMH Bayang Nyalo achieves maximum energy output and utilizes possible renewable energy sources in a sustainable and efficient manner. This research is a study that aims to describe and analyze data using a quantitative technique. The quantitative research technique is used when study data is in numerical form. Quantitative descriptive research is a method used to examine obtained data by providing a detailed and accurate description of the data. This study aims to determine the optimal value for designing small-scale hydropower plants (PLTMH). In order to do research for this thesis, the author investigates the number of studies performed in the Bead Dam Nyalo Kec. Nagari Bayang North, South Coast Regency West Sumatra. The PLTMH project aims to harness the water flow from the subterranean river, which has a discharge rate of 14.67 liters per second. The power plant is designed to have a power capacity of 623.32 kW, using a high discharge waterfall with an effective height of 5 m. Based on the examination of technological elements, we have reached conclusions: The civil component of this PLTMH includes a gravity concrete dam that is prepared for operation, while the electrical components consist of a Cross flow Turbine. The development of mechanical transmission is ongoing.

Crucial future observations and directions for unveiling magnetopause dynamics and their geospace impacts

The dynamics of Earth’s magnetopause, driven by several different external/internal physical processes, plays a major role in the geospace energy budget. Given magnetopause motion couples across many space plasma regions, numerous forms of observations may provide valuable information in understanding these dynamics and their impacts. In-situ multi-point spacecraft measurements measure the local plasma environment, dynamics and processes; with upcoming swarms providing the possibility of improved spatiotemporal reconstruction of dynamical phenomena, and multi-mission conjunctions advancing understanding of the “mesoscale” coupling across the geospace “system of systems.” Soft X-ray imaging of the magnetopause should enable boundary motion to be directly remote sensed for the first time. Indirect remote sensing capabilities might be enabled through the field-aligned currents associated with disturbances to the magnetopause; by harnessing data from satellite mega-constellations in low-Earth orbit, and taking advantage of upgraded auroral imaging and ionospheric radar technology. Finally, increased numbers of closely-spaced ground magnetometers in both hemispheres may help discriminate between high-latitude processes in what has previously been a “zone of confusion.” Bringing together these multiple modes of observations for studying magnetopause dynamics is crucial. These may also be aided by advanced data processing techniques, such as physics-based inversions and machine learning methods, along with comparisons to increasingly sophisticated geospace assimilative models and simulations.

Critical review on resource scheduling in IaaS clouds: Taxonomy, issues, challenges, and future directions

AbstractIn a cloud computing environment, the primary goal of resource scheduling is to reduce the economic expenditures for cloud users and grow fiscal achievement for cloud providers. In this article, the study of numerous forms of resource scheduling algorithms is presented that has been applied in IaaS clouds. The selected research articles are classified into six categories, according to the nature of the algorithm used. Further, the authors pointed out several issues and challenges with the help of the resource scheduling algorithms, the comparative performance metrics, and the simulation tools used to validate the several algorithms. The enhancement illustrates better performance concerns decreasing the cost and time while improving the competence and utilization of resources for IaaS clouds. These algorithms are executed in numerous simulation tools and real environments similar to CloudSim, SimGrid, MATLAB, and test‐bed environments (practical implementation). This critical review and classification will serve as a foundation for further research in IaaS clouds in the Internet of Things (IoT) environments.