Balance Of Processes Research Articles

Assessing canopy rainfall partitioning by Mediterranean dryland shrubs under extreme rainfall

AbstractIntense rain events have become more frequent in some regions due to climate change, and this trend is particularly concerning in dryland regions where the ecological and geomorphological impacts of rainfall are intimately tied to its intensity. The interception of rainfall by vegetation is a critical process in the water balance of drylands; thus, this study estimated the canopy interception capacity and interception rates as well as stemflow of three typical Mediterranean shrub species (Rosmarinus officinalis, Thymus vulgaris, and Macrochloa tenacissima) of three size classes in Spain under a simulated extreme rainfall rate (~8 mm min−1, historical return period of >100 years). Given that these plants' canopy structures markedly differ from taller woody plants (i.e., trees), a novel method was developed to assess the stemflow fraction. Results showed significant differences in interception amount, rates, and storage capacity among the shrub species, with variations in plant morphology, such as shrub height and canopy diameter, being the key factors determining interception capacity. R. officinalis had the highest interception fraction per unit canopy area, or ‘specific interception,’ (18.4%). In contrast, the lowest specific interception fraction was measured for M. tenacissima (6.5%). Thymus vulgaris was characterized by the highest stemflow yields per unit canopy area (4.85 mm) and fraction (up to 29.6% of rainfall), which was the lowest for M. tenacissima (1.09 mm, ~1%–4%). Strong linear correlations were found between canopy interception and shrub canopy diameter (|r| > −0.51, max = −0.90), when observations were grouped for size class. These linear correlations between shrub morphology and partitioning enabled multiple‐regression linear models to be developed that predicted canopy interception and stemflow with good accuracy (r2 > 0.64, with a maximum of 0.82) from shrub height, canopy diameter, dry biomass, size class, and species. Despite these measurements being conducted under one extreme storm depth and intensity, the results provide: (i) values of rainfall partitioning for important shrub species in Mediterranean dryland environments; and (ii) a simple but reliable model that may be further developed (e.g., embedding variable rainfall values as weather input or incorporating other morphological parameters) and may be integrated into complex hydrological models.

Balanced Scorecard Internal Process Perspective: Applying Data Analytics to Monitor Police Department Performance

ABSTRACT Employers expect graduates to perform data analytics using both organizational and publicly available data. Interestingly, few teaching cases provide students with needed exposure to data analytics in managerial or governmental accounting. In this case, students assume the role of a managerial accountant employed at Municipal Consulting, LLC. Students assist the Police Commissioner in using a Balanced Scorecard approach to analyze how her department responds to crime patterns and to develop next year’s budget. This case requires students to critique, analyze, and evaluate Internal Business Process Perspective Balanced Scorecard measures supported by publicly available data using data visualization software. The case includes instructions for both Tableau and Power BI. The case covers three skills: (1) extract, transform, and load data; (2) develop data visualization software experience; and (3) analyze data. The case is designed for senior level undergraduate and graduate courses in managerial, data analytics, and governmental accounting.

IMERG Precipitation Improves the SMAP Level-4 Soil Moisture Product

Abstract The NASA Soil Moisture Active Passive (SMAP) mission Level-4 Soil Moisture (L4_SM) product provides global, 9-km resolution, 3-hourly surface and root-zone soil moisture from April 2015 to the present with a mean latency of 2.5 days from the time of observation. The L4_SM algorithm assimilates SMAP L-band (1.4 GHz) brightness temperature (Tb) observations into the NASA Catchment land surface model as the model is driven with observation-based precipitation. This paper describes and evaluates the use of satellite- and gauge-based precipitation from the NASA Integrated Multi-satellitE Retrievals for the Global Precipitation Measurement (IMERG) products in the L4_SM algorithm beginning with L4_SM Version 6. Specifically, IMERG is used in two ways: (i) The L4_SM precipitation reference climatology is primarily based on IMERG-Final (Version 06B) data, replacing the Global Precipitation Climatology Project Version 2.2 data used in previous L4_SM versions, and (ii) the precipitation forcing outside of North America and the high latitudes is corrected to match the daily totals from IMERG, replacing the gauge-only, daily product or uncorrected weather analysis precipitation used there in earlier L4_SM versions. The use of IMERG precipitation improves the anomaly time series correlation coefficient of L4_SM surface soil moisture (versus independent satellite estimates) by 0.03 in the global average and by up to ∼0.3 in parts of South America, Africa, Australia, and East Asia, where the quality of the gauge-only precipitation product used in earlier L4_SM versions is poor. The improvements also reduce the time series standard deviation of the Tb observation-minus-forecast residuals from 5.5 K in L4_SM Version 5 to 5.1 K in Version 6. Significance Statement Soil moisture links the land surface water, energy, and carbon cycles. NASA Soil Moisture Active Passive (SMAP) satellite observations and observation-based precipitation data are merged into a numerical model of land surface water and energy balance processes to generate the global, 9-km resolution, 3-hourly Level-4 Soil Moisture (L4_SM) data product. The product is available with ∼2.5-day latency to support Earth science research and applications, such as flood prediction and drought monitoring. We show that a recent L4_SM algorithm update using satellite- and gauge-based precipitation inputs from the NASA Integrated Multi-satellitE Retrievals for the Global Precipitation Measurement (IMERG) products improves the temporal variations in the estimated soil moisture, particularly in otherwise poorly instrumented regions in South America, Africa, Australia, and East Asia.

Hypoandrogenism and reproductive function — a problem-oriented approach to pregnancy planning. Literature review

The author considers pre‑pregnancy care program in women with endocrine imbalances as a complex problem that requires involvement of a multidisciplinary team of doctors in the examination process, including endocrinologists, therapists, gastroenterologists, and if needed, immunologists, nutritionists and hematologists. This approach is stipulated by the frequency of accompanying somatic pathology and the burdened obstetric and gynecological history of such women, in particular, menstrual cycle disorders, infertility, miscarriage, spontaneous abortions, a high percentage of hyperplastic diseases and inflammatory processes of the female genitalia. Disorders of hormonal homeostasis in women with endocrinopathies result in the pro‑inflammatory orientation of their immunity, oxidative stress, which disrupts both the folliculogenesis process and leads to metabolic and morphological changes in the receptor organs of both the female genitalia and other organs of the endocrine system (thyroid gland, adrenal glands), forming a vicious cycle of pathological processes in the endocrine balance of female steroids, which, in turn, is accompanied by disturbances in the homeostasis system of the entire organism. Based on the literature data, the authors made conclusions about the stages of examination of women with hypoandrogenism in the pre‑gravid stage. Speaking about natural pregnancy, the first stage, according to the authors, is to determine the main location of the pathology — the central mechanism (disruption of the hypothalamic‑pituitary‑ovarian‑thyroid‑adrenal chain), genetic enzymatic polymorphisms, deficiency/insufficiency of vitamin D and their elimination. At the second stage, there is a need to determine the state of organs — receptors (endometrium, endocervical glands, vaginal epithelium), the state of detoxification organs and their correction. The third stage is to ensure conditions for full‑fledged ovulation and transport of gametes. The fourth stage is early pregnancy support, prevention, early diagnosis and treatment of vaginal infections. The pregnant woman is monitored together with a specialist in the detected comorbid pathology (geneticist, hematologist, gastroenterologist, therapist, endocrinologist, psychotherapist, etc.). Further research is needed to develop a clear algorithm for pre‑pregnancy care program in women with hypoandrogenism depending on reproductive age, obstetrical and gynecological history, methods of overcoming infertility.

A dataset of soil carbon flux in Xishuangbanna tropical rainforest ecosystem from 2003 to 2008

Long-term and large-scale carbon flux data supports research on key processes of the global carbon and water cycle. Soil is the largest carbon pool in the terrestrial ecosystem. Small variations in soil carbon can significantly impact the carbon budgets of terrestrial ecosystems. Tropical forest is a crucial carbon sink in the world. However, there have been some reports indicating a decrease in soli carbon levels, potentially approaching neutrality, as a result of soil carbon degradation caused by global changing. Thus, the long-term and continuous observation of soil carbon flux is of great significance for evaluating the role of soil carbon in the tropical carbon cycle. ChinaFLUX Observation and Research Network (ChinaFLUX) has not only conducted the observation and research on carbon flux by using vorticity correlation technology, but also carried out the long-term observation and research on surface CO2 flux by using the box method. In this dataset, we collected and sorted out the soil CO2 emission flux data and conventional meteorological data of Xishuangbanna tropical rain forest ecosystem from January 2003 to August 2008 according to the static box observation method and data quality control management of greenhouse gas emissions. The dataset consists of three types of files at daily, monthly and yearly scales, covering surface CO2 flux, pressure, atmospheric temperature, soil temperature (5 cm) and soil water content (5 cm). It is expected to provide essential data for estimating carbon balance and understanding carbon cycle processes at both tropical and global scales.

Incentive strategy of dual innovation balance in green manufacturing innovation ecosystem: Based on hierarchical structure of innovation subject.

Exploratory innovation is a pivotal way to seize future opportunities in green manufacturing innovation ecosystems, and exploitative innovation is conducive to expanding existing markets and resources, so it is essential to discuss the balanced incentive strategy of dual innovation for the sustainable development of ecosystems. Based on the hierarchical structure, this paper divides the core subjects in the green manufacturing innovation ecosystem into the application layer, the support layer, and the scientific research layer, constructs the differential game model of the no-incentive scenario, the cost-sharing scenario, and the collaborative scenario, and discusses the incentive strategies of the three types of subjects and the ecosystem in the evolution process of the dual innovation balance. The conclusions are as follows: (1) The level of dual innovation balance effort of the three types of subjects decreases with the increase of resource costs and environmental construction costs and increases with the increase of innovation balance capacity; (2) Cost sharing from the application layer to the support layer and the scientific research layer can enhance the effort level of both, which in turn enhances the optimal benefits for the three types of subjects and the ecosystem as a whole; (3) In the collaborative scenario, the level of effort and total ecosystem benefits of the innovation balance of the three types of subjects are strictly better than in the no incentive scenario, and the Pareto-optimality of the three subjects and the ecosystem will be realized after the coefficients of the distribution of benefits among the three types of subjects are determined. Based on this, this paper puts forward specific suggestions for the optimization of the structural relationship of the innovation body hierarchy, the exploitation of green manufacturing resources, and the macro-planning of the management department.

Efficient and selective gold recovery from e-waste by imidazolium-based poly(ionic liquid)s

Recycling gold from e-waste is not only beneficial to environmental protection, but also to resource sustainability. However, it remains a great challenge due to the limitations of high cost, lengthy balance process and the interference of coexisting metals. Herein, a family of low-cost, nitrogen-rich content and acid-stable imidazolium-based poly(ionic liquid)s, designated as P(nDVB-mVBIMCl)s, were synthesized for recovery of gold from e-waste. The obtained P(2DVB-8VBIMCl)s achieves outstanding adsorption capacity (820.5 mg·g−1) and rapid equilibrium time (15 min) and satisfactory reusability (more than 8 cycles). XPS, EDS and ion chromatography revealed that the excellent adsorption performance was attributed to synergistic effect of ion exchange and chemical reduction. In addition, the P(2DVB-8VBIMCl)s showed excellent selectivity for gold in actual e-waste leaching solution, exhibited satisfactory selectivity coefficient for Fe3+ (1.46 × 104) and Ni2+ (1.12 × 104), obtaining 23.4 karat high-purity gold after calcination. In addition, the P(2DVB-8VBIMCl)s shows its good economic feasibility. Overall, this work provides a feasible adsorbent, which becomes a promising candidate for industrial gold recovery from e-waste.

Financial Distress Classification Using Feedforward Neural Network Based on Altman and Ohlson Financial Ratios

The ever-changing economy requires companies to anticipate future conditions in order to avoid financial distress, a continuous decline in financial conditions. The research focused on comparing Altman and Ohlson’s financial ratio in classifying financial distress on Property and Real Estate companies using the Feedforward Neural Network. The data used is the financial report data of 19 Property and Real Estate companies listed on the Indonesian Stock Exchange in 2016-2022, with the initial status of financial conditions based on earnings per share. (EPS). The study also used the Synthetic Minority Oversampling Technique (SMOTE) method to address class imbalances. The best financial ratio is selected based on accuracy values and Area Under Curve (AUC). Altman’s financial ratio with the FFNN model architecture (5-2-1) with a balance of 60:40 yields an accuracy of 84.62% and an AUC of 0.8325. The Ohlson Financial ratio with the 60:40 data balancing process and the FFNN model architecture (9-4-1) yields an accuracy of 93.27% and an AUC of 0.9045. Thus, in predicting financial distress in companies in the Property and Real Estate sector, Ohlson’s financial ratio with the predictor variables Corporate Size (SIZE), Total Liabilities to Total Assets (TLTA), Working Capital to Total Acts (WCTA), Current Liability to Current Asset (CLCA), OENEG, Net Income to total assets (NITA), Cash Flows Operating to Total Responsibilities (CFOTL), Net Revenue (INTWO), and Net Incoming Change (CHIN) yielded the best results. This best ratio can be used as a consideration in using alternative financial ratio to classify financial distress.

Uniform Fe2 O3 Nanospheres Anchored on Multilayer Graphene as Anode Materials for High-Rate Ni-Fe Batteries.

Ni-Fe battery is one of prospective aqueous alkaline batteries due to its high safety, eco-friendliness and cost-effectiveness. However, the electrochemical performance of Fe-based anodes is limited due to the particle aggregation and low electric conductivity. In this work, iron powder is used as a precursor in a chemical bath deposition method. By optimizing the concentration of HNO3 , a balanced dissolution-crystallization process is achieved to obtain uniform Fe2 O3 nanospheres in size between 60 and 90 nm, which are separately anchored on ultrasonically prepared multilayer graphene (MLG). This composite delivers specific discharge capacities of 191.1 and 160.8 mAh g-1 at the current densities of 2 and 10 A g-1 , respectively. A Ni-Fe battery with the as-prepared Fe2 O3 /MLG as anode and Ni(OH)2 /MLG as cathode exhibits an energy density of 69.5 Wh kg-1 at a high power density of 3931.6 W kg-1 .

Transition phase in the static thrust generation of the biomimetic fin with low oscillating frequency

Biomimetic fin propulsion could be a promising solution for an efficient underwater propulsion mechanism. It could be designed to generate thrust for underwater locomotion efficiently. Many studies have proposed that the flexibility characteristics of the fin affect its effectiveness in thrust generation; for example, a flexible fin generates more thrust than a rigid fin. In this regard, the rigid fin may suffer a mechanical disadvantage in thrust generation. This study introduces the presence of thrust generation phases in biomimetic fins. The phases could be caused by the interaction of the fins and the surrounding fluid. To distinguish the phases clearly, the experimental setup in this study was designed for no-flow conditions. This study presents three phases of thrust generation: negative, transition, and positive. The existence of the negative and transition phases explains the mechanical disadvantages of the rigid fin. Within the range of evaluated fin frequencies, approximately 80% of the average net force of the rigid fin is in the negative and transition phases, compared to only 20% in flexible fins. In comparison to less flexible and rigid fins, a flexible fin could maximize positive thrust production three times higher at high frequency. The vector composition analysis and dye-injection flow visualization reveal the transition phase by emphasizing the balancing process between the surface friction of the fin and the inertial component of the force of the fluid and fin interaction. This study demonstrates the independence of the transition phase from the flexibility characteristics of the biomimetic fin. Because the bending characteristic of the flexible fin could direct more vectors in thrust generation, the fin could act as a thrust vectoring agent. The findings of this study could be used as a guide in designing and implementing high-performance fin propulsion in low-speed underwater locomotion.

Design Method of Three-Component Optic Fiber Balance Based on Fabry-Perot Displacement Sensor.

This article proposes a new type of three-component optic fiber balance based on Fabry-Perot displacement measurement technology based on the structure of the pulse wind tunnel balance. This paper systematically introduces the force measurement principle and design process of a three-component optic fiber balance and conducts relevant simulation analysis and experimental verification. The simulation results show that the Fabry-Perot sensor can achieve significant sensitivity to cavity length changes, and when used in existing balance structures, sensitivity gains can be achieved by changing the probe height without the need to modify the original structure of the balance. Finally, the feasibility of the design method was verified through calibration experiments: the optic fiber balance has high sensitivity and good linearity compared to simulation sensitivity, the error is less than 6%, and the calibration accuracy of each component is better than 0.13%, which is better than the existing traditional strain balance (0.37%). The pulse wind tunnel force measurement test has a short test time and a large model mass, and the balance needs to have a large stiffness to meet the short-term force measurement requirements. The introduction of more sensitive optic fiber balance force measurement technology is expected to solve the contradiction between the stiffness and sensitivity of force measurement systems.

Investigation of factors affecting modified asphalt binder development and performance using the poker chip test

With the surge in the use of modified asphalt binders throughout the world, it is important to examine these materials for performance outside of their linear viscoelastic (LVE) range. Modified asphalt binders, which are usually costlier, are expected to increase the service life of asphalt pavements. The current paper utilizes two approaches to evaluate the nonlinear viscoelastic and failure performance of eight binders including six novel modified asphalt binders. First, the poker chip test for cracking performance evaluation was conducted at different loading rates and aging levels. The results conclude the efficacy of the poker chip test to differentiate and rank the best performing modified asphalt binders. Furthermore, the impact of varying the loading rates, aging levels, modifications, and performance grades was also studied. These results indicated that loading rates ranging from 1 to 4 N/s can be used to differentiate modified binder performance with similar ranking, which allows a wider range of machines to be used to do this test. In addition, the impacts of aging were studied to introduce differentiation between modifiers which are sensitive to aging. Apart from this, the Multiple Stress Creep Recovery (MSCR) test was conducted to evaluate the rutting performance. MSCR results further augmented the confidence in initial rankings as polymer-modified binders showed superior performance to other modifier types. It was observed that the top two binders in terms of poker chip results also had the best MSCR performance. Hence, instead of balancing the performance, like is done for mixtures, between rutting and cracking, an optimum binder can be synthesized which has excellent performance against load-related cracking and permanent deformation. This sets the stage for a balanced binder selection and design process to be implemented into future specifications and research efforts.

Advancing the affordable and clean energy in large energy-consuming economies: The role of green transition, complexity-based, and geostrategy policies

With decreasing costs of the clean technologies, the balanced scales of the Sustainable Development Goal 7 targets, e.g., energy equity (EE), energy security (ES), and environmental sustainability (EVS), are quickly changing. This fundamental balancing process is a key requirement for a net-zero future. Accordingly, this research analyzes the regime-switching effect of Hydrogen economy as the green transition, sharing economy and economic complexity as the complexity-based, and geopolitical risks and energy prices as the geostrategy policies on the Goal 7 targets. To this end, a Markov-switching panel vector autoregressive method with regime-heteroskedasticity is applied to study advancing the Goal 7 in the world's twenty-five large energy consumers during 2004–2020. Concerning the parameters and statistics of the model, the results refer to the existence of two regimes associated with the Goal 7 corners, called “upward and downward” regimes for EE and “slightly upward and sharply upward” regimes for ES and EVS. It is revealed that the vulnerability of EE and ES targets is considerably reduced when the regime switches to the dominant regime that is “downward” and “slightly upward” regimes respectively, and that of the EVS target remains unaffected. Through the impulse-response analysis, the findings denote that the first hypothesis of the efficiency of the Hydrogen economy in promoting the Goal 7 targets is insignificant. However, the significant short-term and dynamic shock effects of the complexity-based and geostrategy policies on the Hydrogen economy are detected, which will be a feasible alternative assessment in advancing the Goal 7. Further, the complexity-based policies support the Goal 7 targets under different regimes, especially in the short- and medium-term. Hence, the second hypothesis regarding the effectiveness of the complexity-based policies in promoting Goal 7 targets is confirmed. The third hypothesis concerning the complexity of the impact of geostrategy policies on the Goal 7 targets is verified. Particularly, the switching process towards the Goal 7 may not necessarily be restricted by the geopolitical risks. Moreover, EE is supported through energy prices in the short-term under both regimes, while they are non-conductive to promote ES and EVS through time. Accordingly, the decision-makers should acknowledge adopting a regime-switching path forward for ensuring the time-varying balanced growth of the Goal 7 targets as the impact of the suggested policy instruments is asymmetric.

Математическое моделирование оценки доверия к сообщению в социальных сетях на русском языке

The problem of unreliable information is currently the most critical in the field of information dissemination in the Internet environment. The global transition of information sources to the Internet has led to the fact that information is distributed too quickly, and it is quite difficult to verify the accuracy of the information. This topic is raised when talking about the media, social networks, blogs, and other sources of information. The transmission of information has ceased to be a matter only for the media. Any Internet user can be a source of information. The development of free sources of information and the digitalization of sources have led to a loss of confidence in the official media. The consequence of this is the development of methods for automatically detecting false information. The objectives of this work are to study the possibility of building a model for automatically determining the level of trust in a message in a social network in Russian language and determine the most influential parameters. The considered method is aimed at a multi-sided analysis of the post, including parameters obtained from the text of the message, user data and the distribution of the message on the social network. To work with machine learning methods, a data sample was collected and marked up, on which machine learning models were trained. The data sample underwent a balancing process to obtain stable results. After training the models, five models were obtained trained on both balanced and conventional data samples. The results were obtained for models with a restriction on parameters to identify the most influential parameters. The results were machine learning models with high readings of metric values on test data and the most influential parameters were identified, which included parameters unique to the Russian language.

Diurnal Evolution and Estimates of Hourly Diffuse Radiation Based on Horizontal Global Radiation, in Cerrado-Amazon Transition, Brazil

In the Cerrado-Amazonian ecotone in the State of Mato Grosso, intensely altered by anthropic action, the knowledge and processes of energy conversion and energy balance are still incipient, making the monitoring and modeling of diffuse radiation essential for several applications. The objective of this study was to evaluate the seasonality of the diurnal evolution and estimate the hourly diffuse radiation (Hdh) and incident radiation in the horizontal plane between June 2011 and October 2016. The instantaneous measurements (5 min) of diffuse radiation underwent geometric, astronomical, and anisotropic corrections, with subsequent hourly integrations. The seasonality of diffuse radiation and its radiometric fractions was evaluated. The estimates were made considering total and seasonal data groupings (water stations in the region) and in different cloudiness classes (atmospheric transmissivity index—KTh). The diurnal behavior of diffuse radiation (Hdh) was similar to that of global radiation and at the top of the atmosphere, with maximum values at solar noon. The correlations between Kdh and KTh showed third-order polynomial behavior, with maximum observed values of Kdh ranging from 0.8 to 0.9, for KTh less than 0.2. Estimation equations based on radiometric fractions underestimated the values of diffuse radiation, with a better performance presented by models adjusted in annual data groupings. Among the parameterized models for estimating diffuse radiation obtained in the literature, those calibrated regionally in this study, together with those developed for tropical regions, presented better statistical performances.

The role of digital communication and display in interior design processes

In light of the intellectual and technological progress within the current developments of time, as well as the emergence of digital tools and means of display and communication, which had a major role in the shifts of the time of globalization in various commercial and economic fields, as well as areas of transferring the design image and its stages of development to customers and the convergence of views between the customer and the interior designer, which are the most important pillars of the design process As a whole, and accordingly, there is an urgent need for a process of intellectual balance between them through digital tools from the technical side and through social media from the intellectual side. Customer comments via social media, which facilitates the process of generating feedback for designers. The problem is embodied in the following question: "How can digital modeling tools and social media be employed in the field of interior design to obtain a contemporary design process?" And then its objectives, limits, and definition of its terminology, as the research sample was represented by the engineering offices registered with the Iraqi Engineers Association, and after reviewing previous studies and building the theoretical framework, the research dealt with two axes, the first (the concept of the design process and its variables’ connection with the variables of the era and technology), and the second (the role of the customers’ position in the process After building the theoretical framework and reaching a set of indicators, a questionnaire was built to be analyzed in the light of it, and after ensuring the validity and reliability of the tool, a random sample was selected from the number of answers obtained from the research community, and the statistical analysis method was used For the questionnaire, a set of statistical results were reached in order to influence a set of conclusions that can be generalized to the research community, and then a set of recommendations and research proposals.

PENILAIAN DAYA TARIK OBJEK WISATA ALAM AIR TERJUN GURUNG SEPANGIN DI DESA TEKUDAK KECAMATAN KALIS KABUPATEN KAPUAS HULU

Assessment of the attractiveness of natural attractions is a systematic and balanced process or activity to gather information about everything unique, of high attractive value for tourists who come to a tourist destination area. This research is expected to be included in the local government as a consideration in the framework of the management and development of natural attractions. The purpose of the research is to get the value of the attraction of natural attractions of Gurung Sepangin Waterfall. The research was conducted for approximately 3 weeks effectively in the field. The method used is a survey method with interview techniques and assisted by questionnaires as data collection instruments, sampling is carried out accidental sampling based on criteria that have been determined by researchers. The number of respondents was 30 people. Data processing uses guidelines for analysis of object operations and natural attractions (ADO-OTDWA) directorate general of PHKA in 2003 which has been modified according to the scores that have been determined for each criterion. The results of research on the assessment of natural attraction objects of Gurung Sepangin Waterfall have an area attraction value of 954.18 or entered into the classification category (B) means that it is quite potential to be developed into a natural tourist destination.

Prediction and analysis of likelihood of freeway crash occurrence considering risky driving behavior

The prediction of the likelihood of vehicle crashes constitutes an indispensable component of freeway safety management. Due to data collection limitations, studies have used mainly traffic flow-related variables to develop freeway crash prediction models but rarely have considered the effect of risky driving behavior on the likelihood of crashes. This study employed navigation software to collect driving behavior data and integrated multi-source data that include vehicle speed, traffic volume, and congestion index values. The study also employed the ‘synthesizing minority oversampling technique and edited nearest neighbor’ (SMOTE + ENN) coupled method for data balance processing. Three freeway crash likelihood prediction models were built based on the binomial logit, eXtreme Gradient Boosting (XGBoost), and support vector machine algorithms, respectively. The Shapley additive explanation (SHAP) algorithm was utilized to explore the effect of each feature variable on the likelihood of crashes. The results show that the prediction accuracy of the XGBoost model is the best of the three compared models. Under the optimal control-to-case ratio (1:1), the prediction accuracy of the XGBoost model reached 0.96 in this study, and the recall rate, specificity, and area-under-the-curve values were 0.86, 0.96, and 0.907, respectively. Comparative test results demonstrate that ranking risky driving behavior into three levels of intensity can effectively enhance the predictive accuracy of the XGBoost model. Moreover, the XGBoost model with its ten-minute time step outperformed the XGBoost model with its five-minute time step in terms of prediction accuracy. The results of the SHAP-based analysis show that the likelihood of highway crashes is high when the traffic congestion level is high and the distribution of the vehicle speed in the upstream roadway section is significant. Also, both sharp acceleration and sharp deceleration lead to greater likelihood of crashes. This paper aims to provide an effective framework for predicting and interpreting the likelihood of freeway crashes, thereby providing guidance for crash prevention, driver training, and the development of traffic regulations.

Deep Learning-based Resource Prediction and Mutated Leader Algorithm Enabled Load Balancing in Fog Computing

Load balancing plays a major part in improving the performance of fog computing, which has become a requirement in fog layer for distributing all workload in equal manner amongst the current Virtual machines (VMs) in a segment. The distribution of load is a complicated process as it consists of numerous users in fog computing environment. Hence, an effectual technique called Mutated Leader Algorithm (MLA) is proposed for balancing load in fogging environment. Firstly, fog computing is initialized with fog layer, cloud layer and end user layer. Then, task is submitted from end user under fog layer with cluster of nodes. Afterwards, load balancing process is done in each cluster and the resources for each VM are predicted using Deep Residual Network (DRN). The load balancing is accomplished by allocating and reallocating the task from the users to the VMs in the cloud based on the resource constraints optimally using MLA. Here, the load balancing is needed for optimizing resources and objectives. Lastly, if VMs are overloaded and then the jobs are pulled from associated VM and allocated to under loaded VM. Thus the proposed MLA achieved minimum execution time is 1.472ns, cost is $69.448 and load is 0.0003% respectively.

An Overview of Flashing Phenomena in Pressure Hydrometallurgy

Pressure hydrometallurgy has attracted much attention for its characteristics, such as the high adaptability of raw materials and environmental friendliness. Flashing (flash boiling or flash evaporation) refers to the phase change phenomenon from liquid to gas triggered by depressurization, which is an important connection between high-pressure processes and atmospheric ones in pressure hydrometallurgy. This paper takes the flashing process in zinc leaching and alumina Bayer processes as examples, describes the flashing process in pressure hydrometallurgy in detail for the first time, and shows the importance of the flashing process in energy recovery, solution concentration, and liquid balance, as well as increasing equipment life. According to solid holdup (the volume percentage of solid), this paper proposes to divide the flashing process into solution flashing (low solid holdup) and slurry flashing (high solid holdup). A further focus is put on reviewing the state of the art of related studies. The results reveal that the research on the flashing process in pressure hydrometallurgy is scarce and often oversimplified, e.g., ignoring the BPE (boiling point elevation) and NEA (non-equilibrium allowance) in solution flashing and the effect of solid particles in slurry flashing. Computational fluid dynamic (CFD) simulation is a promising tool for investigating the flashing process. Based on the progress made in other fields, e.g., seawater desalination, nuclear safety analysis, and engine fuel atomization, we suggest that solution flashing can be studied using the CFD–PBM (population balance model) coupled two-fluid model, since a wide size range of bubbles will be generated. For slurry flashing, the effect of solid holdup on the bubble nucleation rate and mechanism as well as other bubble dynamics processes should be accounted for additionally, for which a quantitative description is still lacking. Meanwhile, data for validating the numerical method are scarce because of the harsh experimental conditions, and further research is needed. In summary, this work presents an overview of the flashing processes in pressure hydrometallurgy and some guidelines for future numerical studies.