Simpler Components Research Articles

Selection of the Transport Mode Using the AHP Method Within Distribution Logistics of Motor Fuels

To remain competitive and respond to rapidly changing markets, we need to increase flexibility in today's global marketplace. In this respect, the selection of the appropriate mode of transport is one of the most important functions to be performed by logistics. The selection of the appropriate mode of transport is a multi-criteria problem involving both quantitative and qualitative criteria. This paper deals with the selection of the mode of transport using the Analytic Hierarchy Process method (AHP). AHP is a method of decomposing a complex unstructured situation into simpler components to create a hierarchical system problem. This paper describes a general model of selection of transport mode using AHP including its application to a manufacturing company that selects the appropriate mode of transport from three potential transport modes. The aim of this paper is to create a useful decision support tool for selection of the transport mode using the AHP method within distribution logistics of motor fuels. This tool helps companies to make the right decision on the choice of transport mode by taking into account different importance of the different criteria that influence the decision-making process.

Progress and prospect of the zinc–iodine battery

The zinc–iodine battery has the advantages of high energy density and low cost owing to the flexible multivalence changes of iodine and natural abundance of zinc resources. Compared with the flow battery, it has simpler components and more convenient installation, yet it still faces challenges in practical applications. How to select suitable materials as the cathode and electrolyte to control the process of energy storage reaction and inhibit the self-transformation of by-products, together with the corrosion resistance of metallic zinc are crucial factors. Herein, the principles of the zinc–iodine flow battery and zinc–iodine battery are described, and the unprecedented progresses are highlighted. This mini review is anticipated to provide valuable guidance for the further development of the zinc–iodine battery. The zinc–iodine flow battery and zinc–iodine battery are cost-effective and environmentally friendly electrochemical energy storage devices. They deliver high energy density owing to the flexible multivalence changes of iodine. In this mini review, the prominent problems of their modules (e.g. electrode, electrolyte) together with the common improvement strategies are described, which may provide valuable guidance for their further development.

A Survey of Automated Programming Hint Generation: The HINTS Framework

Automated tutoring systems offer the flexibility and scalability necessary to facilitate the provision of high-quality and universally accessible programming education. To realise the potential of these systems, recent work has proposed a diverse range of techniques for automatically generating feedback in the form of hints to assist students with programming exercises. This article integrates these apparently disparate approaches into a coherent whole. Specifically, it emphasises that all hint techniques can be understood as a series of simpler components with similar properties. Using this insight, it presents a simple framework for describing such techniques, the Hint Iteration by Narrow-down and Transformation Steps framework, and surveys recent work in the context of this framework. Findings from this survey include that (1) hint techniques share similar properties, which can be used to visualise them together, (2) the individual steps of hint techniques should be considered when designing and evaluating hint systems, (3) more work is required to develop and improve evaluation methods, and (4) interesting relationships, such as the link between automated hints and data-driven evaluation, should be further investigated. Ultimately, this article aims to facilitate the development, extension, and comparison of automated programming hint techniques to maximise their educational potential.

A novel hybrid deep learning model for taxi demand forecasting based on decomposition of time series and fusion of text data

Accurate taxi demand forecasting is significant to estimate the change of demand to further make informed decisions. Although deep learning methods have been widely applied for taxi demand forecasting, they neglect the complexity of taxi demand data and the impact of event occurrences, making it hard to effectively model the taxi demand in highly dynamic areas (e.g., areas with frequent event occurrences). Therefore, to achieve accurate and stable taxi demand forecasting in highly dynamic areas, a novel hybrid deep learning model is proposed in this study. First, to reduce the complexity of taxi demand time series, the seasonal-trend decomposition procedures based on loess is employed to decompose the time series into three simpler components (i.e., seasonal, trend, and remainder components). Then, different forecasting methods are adopted to handle different components to obtain robust forecasting results. Moreover, considering the instability and nonlinearity of the remainder component, this study proposed to fuse the event features (in particular, text data) to capture the unusual fluctuation patterns of remainder component and solve its extreme value problem. Finally, genetic algorithm is applied to determine the optimal weights for integrating the forecasting results of three components to obtain the final taxi demand. The experimental results demonstrate the better accuracy and reliability of the proposed model compared with other baseline forecasting models.

Present and Future Prospect of Algae: A Potential Candidate for Sustainable Pollution Mitigation

Pollution control and mitigation are critical to protect the ecosystem and make everyone's life safer and healthier. Different pollution mitigation strategies and measures are implemented to remove pollutants, which broadly involve physical, chemical, and biological methods. Biological methods are found to be more sustainable, effective, and eco-friendlier than the other two methods. These methods mainly use microbes like bacteria, fungi, algae, and plants, and their products like enzymes and metabolic products to remove pollutants. Due to their unique photosynthetic ability and simple growth requirements, Algae can be grown using simpler components like CO2, sunlight, and media, making them a potential candidate to be used as a pollution mitigator. Algae can indicate and remove pollutants like CO2, SO2, NO2, and particulate matter from the air; these pollutants and particulate matter are either used for their growth or these are accumulated inside them.. Algal species have shown the efficient removal of heavy metals, organic pollutants, explosives, petroleum contaminants, pesticides, polycyclic aromatic hydrocarbons (PAHs), and plastics from different water sources. There is a lot of scope in using algae to remove organic and inorganic pollutants in wastewater treatment plants. Algae hold great potential to remove radioactive pollutants from natural resources and involve removal mechanisms like biosorption and bioaccumulation. Algae can be used with different adsorbent materials to develop adsorption systems for the adsorption of radionuclides and heavy metals. This review elucidates different algal species, their cultural conditions, the removal efficiency of different types of pollutants from the air, water, soil, and their role in genetic engineering and the algae's potential for waste mitigation.

Blood Pressure Regulation Evolved from Basic Homeostatic Components.

Blood pressure (BP) is determined by several physiological factors that are regulated by a range of complex neural, endocrine, and paracrine mechanisms. This study examined a collection of 198 human genes related to BP regulation, in the biological processes and functional prisms, as well as gene expression in organs and tissues. This was made in conjunction with an orthology analysis performed in 19 target organisms along the phylogenetic tree. We have demonstrated that transport and signaling, as well as homeostasis in general, are the most prevalent biological processes associated with BP gene orthologs across the examined species. We showed that these genes and their orthologs are expressed primarily in the kidney and adrenals of complex organisms (e.g., high order vertebrates) and in the nervous system of low complexity organisms (e.g., flies, nematodes). Furthermore, we have determined that basic functions such as ion transport are ancient and appear in all organisms, while more complex regulatory functions, such as control of extracellular volume emerged in high order organisms. Thus, we conclude that the complex system of BP regulation evolved from simpler components that were utilized to maintain specific homeostatic functions that play key roles in existence and survival of organisms.

PENDEKATAN PRINCIPAL COMPONENT ANALYSIS PADA DATA DEMAM BERDARAH DENGUE DI PROVINSI MALUKU UTARA

North Maluku Province is one of the provinces with many cases of Dengue Hemorrhagic Fever (DHF) in Eastern Indonesia. Various factors cause the increase of DHF such as environment, personal hygiene and inadequate health infrastructure in North Maluku Province The purpose of this research is to group the multivariable of dengue cases into several simpler components using the Principal Component Analysis (PCA) method. The PCA method is a statistical technique for reducing a large number of variables to become simpler. The results showed that 1 variable did not meet the KMO value so that the variable was eliminated. All variables after eliminating one of the variables are tested to meet the KMO and MSA values. All predictors in this study form 1 predictor component variable used are non-labor force population (X1), medical personnel (X2), vulnerable age population (X3), workforce population (X4), villages with health facilities (X5), health facility (X6).

A Generalized Approach to the Steady-State Efficiency Analysis of Torque-Adding Transmissions Used in Renewable Energy Systems

The paper presents a general approach to the steady-state efficiency analysis of one degree of freedom (1-DOF) speed increasers with one or two inputs, and one or two outputs, applicable to wind, hydro and marine-current power generating systems. The mechanical power flow, and the efficiency of this type of complex speed increasers, are important issues in the design and development of new power-generating systems. It is revealed that speed increases, with in-parallel transmission of the mechanical power from the wind or water rotors to the electric generator, have better efficiency than serial transmissions, but their efficiency calculus is still a challenging problem, solved in the paper by applying the decomposition method of complex speed increasers into simpler component planetary gear sets. Therefore, kinematic, steady-state torque and efficiency equations are derived for a generic 1-DOF speed increasers with two inputs and two outputs, obtained by connecting in parallel two gear mechanisms. These equations allow any speed increaser to be analysed with two inputs and one output, with one input and two outputs, and with one input and one output. We discuss a novel design of a patent-pending planetary-gear speed increaser, equipped with a two-way clutch, which can operate (in combination with the pitch adjustment of the rotors blades) in four distinct configurations. It was found that the mechanical efficiency of this speed increaser in the steady-state regime is influenced by the interior kinematic ratios, the input-torque ratio and by the meshing efficiency of its individual gear pairs. The efficiency of counter-rotating dual-rotor systems was found to be the highest, followed by systems with counter-rotating electric generator, and both have higher efficiency than conventional systems with one rotor and one electric generator with fixed-stator.

The role of spatial and spatial-temporal analysis in children's causal cognition of continuous processes.

Past research has largely ignored children’s ability to conjointly manipulate spatial and temporal information, but there are indications that the capacity to do so may provide important support for reasoning about causal processes. We hypothesised that spatial-temporal thinking is central to children’s ability to identify the invisible mechanisms that tie cause and effect together in continuous casual processes, which are focal in primary school science and crucial to understanding of the natural world. We investigated this in two studies (N = 107, N = 124), employing two methodologies, one shorter, the other more in depth. Further tasks assessed spatial-temporal (flow of liquid, extrapolation of relative speed, distance-time-velocity), spatial (two mental rotation, paper folding), verbal (expressive vocabulary), and nonverbal (block design) ability. Age dependent patterns were detected for both causal and predictor tasks. Two spatial-temporal tasks were unique and central predictors of children’s causal reasoning, especially inference of mechanism. Nonverbal ability predicted the simpler components of causal reasoning. One mental rotation task predicted only young children’s causal thinking. Verbal ability became significant when the sample included children from a wide range of socioeconomic backgrounds. Causal reasoning about continuous processes, including inferences of causal mechanism, appears to be within the reach of children from school entry age, but mechanism inference is uncommon. Analytic forms of spatial-temporal capacity seem to be important requirements for children to progress to this rather than merely perceptual forms.

A Low-Cost Platform for Laparoscopic Simulation Training.

With the new requirement for Fundamentals of Laparoscopic Surgery certification among graduating obstetrics and gynecology residents, there has been an increased interest in simulation training. The Fundamentals of Laparoscopic Surgery curriculum uses a commercial laparoscopic box trainer to practice and assess laparoscopic skills. We created a low-cost, space-efficient, portable and versatile training platform that allows for the breakdown of complex tasks, and we studied its user acceptability. A rectangular piece of pine wood purchased at a hardware store was used as a base; metal eye hooks were used as ports, and a blueprint was created to simulate placement of Fundamentals of Laparoscopic Surgery inserts. In addition to the Fundamentals of Laparoscopic Surgery skills, this platform can be used for any laparoscopic task (such as hysterectomy or cuff closure). Additionally, this platform can be used with or without a camera to allow for task breakdown into simpler components for faster learning. A usability and acceptability survey was administered to a convenient sample of faculty and trainees. Trainees and faculty responded favorably to the model. Residents, fellows, and attendings felt that the laparoscopic platform closely simulated the feel of performing live laparoscopy surgery. This is a novel low-cost laparoscopic platform to add to the gynecologic surgical education simulation toolkit.

Багатокритеріальний синтез організаційної структури білінгової інформаційної системи методом аналізу ієрархій

Правильний вибір БС критичний для прибутковості підприємства сфери обслуговування. На певному етапі зростання компанії білінг перетворюється з надійного і швидкого помічника в зборі та обробці інформації в інструмент для розширення і вдосконалення сервісу на існуючій технічній базі, а значить, для залучення нових клієнтів. Від надійності та швидкості роботи БС залежить якість обслуговування клієнтів і можливості, які отримує фірма-постачальник, що, в кінцевому рахунку, впливає на прибутковість підприємства сфери обслуговування. В роботі наведено багатокритеріальний синтез організаційної структури білінгової інформаційної системи методом аналізу ієрархій (МАІ). Метод призначений для прийняття багатокритеріальних проектних рішень в умовах слабкої структурованості організаційно-технічних систем і невизначеності вихідної інформації, заданої набором кількісних і якісних залежностей. Обґрунтованість і достовірність прийнятих рішень багато в чому залежать від узгодженості експертних думок, які формалізовано виражаються через властивості зв'язності і транзитивності між експертними оцінками вихідного факторного простору. Закладений в основу МАІ принцип декомпозиції складної проблеми сукупністю більш простих складових, дозволяє здійснити побудову найбільш оптимального варіанту організаційної структури білінгової інформаційної системи відповідного призначення.

Risk-based life assessment of prediction models on suspension system for various road profiles

This study aims to assess the risk-based fatigue life from each decomposition signals for various roads through the probabilistic analysis on the suspension system. Cyclic loading in fatigue failure and fatigue life-reliability was the main concern in the design and durability analysis. Different types of road surface signals, namely, rural, urban and highway roads were measured by a road test. These signals were decomposed using the Hilbert-Huang transform that contains the simpler component for describing the information from the original signal based on each decomposition mode. The degree of decomposition can be determined from the IMF level. The decomposition signals were then used in predicting the fatigue life of the given component. Akaike’s information criterion was used to determine suitable distribution of the experimental data. Fatigue life was calculated using the mean-cycle-to-failure (McTF) and the result was used to evaluate risk areas for each road surface. The McTF of rural, urban and highway road surfaces for the Morrow model were obtained at 2.4768 × 104, 1.5585 × 108 and 1.5491 × 106 cycles per block, respectively. The McTF of the Morrow model is the safe region that predicts the longer fatigue life compared to in the Coffin-Manson and SWT model. The risk was predicted to be 1.456 × 10–3 (rural), 1.221 × 10–3 (urban) and 1.890 × 10–3 (highway) failures per cycles per block based on the hazard rate function. Hence, high-risk and low-risk were found to occur at above and below of each risk prediction value of the various roads. Risk-based life cycle assessment from decomposition signals has the capability in assessing the fatigue life and risk area of the component under strain loading.

Statistical reprogramming of macroscopic self-assembly with dynamic boundaries

Self-assembly is a ubiquitous process that can generate complex and functional structures via local interactions among a large set of simpler components. The ability to program the self-assembly pathway of component sets elucidates fundamental physics and enables alternative competitive fabrication technologies. Reprogrammability offers further opportunities for tuning structural and material properties but requires reversible selection from multistable self-assembling patterns, which remains a challenge. Here, we show statistical reprogramming of two-dimensional (2D), noncompact self-assembled structures by the dynamic confinement of orbitally shaken and magnetically repulsive millimeter-scale particles. Under a constant shaking regime, we control the rate of radius change of an assembly arena via moving hard boundaries and select among a finite set of self-assembled patterns repeatably and reversibly. By temporarily trapping particles in topologically identified stable states, we also demonstrate 2D reprogrammable stiffness and three-dimensional (3D) magnetic clutching of the self-assembled structures. Our reprogrammable system has prospective implications for the design of granular materials in a multitude of physical scales where out-of-equilibrium self-assembly can be realized with different numbers or types of particles. Our dynamic boundary regulation may also enable robust bottom-up control strategies for novel robotic assembly applications by designing more complex spatiotemporal interactions using mobile robots.

Development of road sector’s lend valuation method for aims of asset management

The object of research is the land management processes of the road sector. The studies are based on the use of a multistructure approach, the basic principles of the theory of complex systems and the methodology of AHP (Analytic Hierarchy Process) by Thomas Saaty. The main hypothesis of the study is the application of a multi-structure approach to valuing assets, which are not comprehensively evaluated in the study, but are considered as complex objects and are divided into simpler levels, components and elements that can be evaluated separately. The features of the valuation of land of the road sector are considered, and the main stages of the evaluation sequence are identified. It has been established that the land valuation is the main component of the valuation of the asset of the road sector, which is located on it. The results of a theoretical study make it possible to develop an algorithm for valuing land of the road sector for asset management purposes. The developed algorithm has a clear sequence in the formation of the methodology for the land valuation of the road economy, it makes it possible to justify the adoption of managerial decisions regarding the land plot, which are consistent with the goals and correspond to the nature of the tasks of the functioning and development of the road sector. The testing of the developed algorithm is performed on a real example. It is found that the algorithm allows to optimize the process of valuation and management of road assets, which is especially important within limited financial resources. The choice of land valuation options is based on criteria of economic efficiency, based on the main limitations and features of land valuation of the road sector. The results of the calculations can be a weighty basis for the formulation of managerial goals for the assets of the road sector and will form the basis for further scientific studies of the process of valuation of assets under financial constraints.

The Truth behind the Zeros: A New Approach to Principal Component Analysis of the Neuropsychiatric Inventory

Psychiatric syndromes in dementia are often derived from the Neuropsychiatric Inventory (NPI) using principal component analysis (PCA). The validity of this statistical approach can be questioned, since the excessive proportion of zeros and skewness of NPI items may distort the estimated relations between the items. We propose a novel version of PCA, ZIBP-PCA, where a zero-inflated bivariate Poisson (ZIBP) distribution models the pairwise covariance between the NPI items. We compared the performance of the method to classical PCA under zero-inflation using simulations, and in two dementia-cohorts (N = 830, N = 1349). Simulations showed that component loadings from PCA were biased due to zero-inflation, while the loadings of ZIBP-PCA remained unaffected. ZIBP-PCA obtained a simpler component structure of “psychosis,” “mood” and “agitation” in both dementia-cohorts, compared to PCA. The principal components from ZIBP-PCA had component loadings as follows: First, the component interpreted as “psychosis” was loaded by the items delusions and hallucinations. Second, the “mood” component was loaded by depression and anxiety. Finally, the “agitation” component was loaded by irritability and aggression. In conclusion, PCA is not equipped to handle zero-inflation. Using the NPI, PCA fails to identify components with a valid interpretation, while ZIBP-PCA estimates simple and interpretable components to characterize the psychopathology of dementia.

Similarities in biological processes can be used to bridge ecology and molecular biology.

Much of the research in biology aims to understand the origin of diversity. Naturally, ecological diversity was the first object of study, but we now have the necessary tools to probe diversity at molecular scales. The inherent differences in how we study diversity at different scales caused the disciplines of biology to be organized around these levels, from molecular biology to ecology. Here, we illustrate that there are key properties of each scale that emerge from the interactions of simpler components and that these properties are often shared across different levels of organization. This means that ideas from one level of organization can be an inspiration for novel hypotheses to study phenomena at another level. We illustrate this concept with examples of events at the molecular level that have analogs at the organismal or ecological level and vice versa. Through these examples, we illustrate that biological processes at different organization levels are governed by general rules. The study of the same phenomena at different scales could enrich our work through a multidisciplinary approach, which should be a staple in the training of future scientists.

Anthocyanin and Nutritional Contents of Fermented Lebui Bean (Cajanus sp.) through SSF Method and Induced by Rhizopus sp. and Saccharomyces sp

Anthocyanins are bioactive compounds that were very important to support health and prevent oxidation. The existence of anthocyanin in plants, one of which is characterized by the presence of their striking colors in the plant. Lebui bean (Cajanus sp.) have a deep black color and identified to contain anthocyanins and phenolic compounds. However, these two important bioactive compounds are not obtained in free conditions, because they were still bound in cells and cell walls through the glycoside bond, also bound to other chemical bonds in the cell. Therefore, a method needed to break the bioactive compounds from their bonds. The easiest, cheapest, and most applicable method is fermentation. Fermentation is a method of processing food that utilizes microbial functions to degrade the compounds contained in the material to produce simpler components, while at the same time breaking various binding chains between components in the material, including solid state fermentation (SSF) method. Through fermentation, it is expected that bioactive compounds including anthocyanins will be cut off and released from the bonds of glycosides and form free compounds that have functional properties. Therefore, this study aims to obtained the type of microbes (Rhizopus sp. and Saccharomyces sp.) with the most optimal fermentation time to produce fermented bean powder which has the best anthocyanin content and nutritional component. A nested design with two factor was used. The main factor is the type of microbes (Rhizopus sp. and Saccharomyces sp.) and the second factor is the fermentation time (1, 2, and 3 day) nested on the main factor. Fermentation carried out for two days using Rhizopus sp. is the best treatment. Fermentation treatment by Rhizopus sp. for 1 to 3 days, produced an average level of anthocyanin in dry bases conditions is 129,81-153,55 ppm whether by Saccharomyces sp. was in the range of 107,12-128,11 ppm. Fermented lebui bean powder induced by Rhizopus sp. for 2 days fermentation has highest protein content and lowest fat content. The nutritional content of this best treatment is protein, fat, water, ash, and carbohydrate content i.e 22,39%, 0,41%, 6,73%, 3,18%, and 67,29%, respectively.

Imaging and Studying Standing Waves with a Homemade Melde-type Apparatus and Information and Communication Technology (ICT)

Wave physics phenomena can be observed in everyday life and represent a fundamental prerequisite to many domains of classical and modern physics. Lots of studies demonstrate that novices have to face important learning difficulties in approaching this topic. The study of string vibrations’ modes allows an educational introduction to basic concepts, but common laboratory approaches employ dedicated experimental setups usually requiring some expensive components (wave or vibration generators, motion detectors) that often are not present in school laboratories. The problem of low-cost solutions for the Melde apparatus has been addressed many years ago. Some recent papers propose low-cost solutions in which standing waves on a Slinky spring obtained with non-reproducible hand movements are analyzed by means of video analysis software. In this context, we projected a modern revisitation of the historical experiment proposed for the first time by Melde in 1859, employing low-cost materials and commonly used information and communication technology (ICT) devices in order to generate and analyze standing waves on a string (see next section). This experimental setup was proposed to a group of 26 students (17–18 years old) in the fourth year of an Italian high school. Students were involved in four sessions (about four hours each) of inquiry-based laboratorial activities, in which they recorded various standing wave configurations on a string with their smartphones and analyzed the obtained videos using the freeware Tracker®, whose potential value is well known in literature. The experimental setup is described and an example of data analysis and obtained results is shown. Finally, students were asked to develop their own Melde-type apparatus; in the last section we present a very interesting alternative solution developed by a group of them, which offers almost the same educational features on a reduced scale using even simpler components.

Retarding parallel components of a Mueller matrix

Mueller matrix polarimetry constitutes a nondestructive powerful tool for the analysis of material samples that is used today in an enormous variety of applications. Depolarizing samples exhibit, in general, a complicated physical behavior that requires appropriate mathematical formulation through models involving decomposition theorems in terms of simpler components. In this work, the general conditions for identifying retarding incoherent components of a given Mueller matrix M are obtained. It is found that when the coherency matrix C associated with M has rank C = 3,4 it is always possible to identify one or two retarding incoherent components respectively, while in the case where rank C =2, such retarding component only can be achieved if and only if the diattenuation and the polarizance of M are equal. Since the Mueller matrices associated with retarders have a simple structure, the results obtained open new perspectives for the exploitation of polarimetric techniques in optics, remote sensing and other areas.

Affine interpolation in a lie group framework

Affine transformations are of vital importance in many tasks pertaining to motion design and animation. Interpolation of affine transformations is non-trivial. Typically, the given affine transformation is decomposed into simpler components which are easier to interpolate. This may lead to unintuitive results, while in some cases, such solutions may not work. In this work, we propose an interpolation framework which is based on a Lie group representation of the affine transformation. The Lie group representation decomposes the given transformation into simpler and meaningful components, on which computational tools like the exponential and logarithm maps are available in closed form. Interpolation exists for all affine transformations while preserving a few characteristics of the original transformation. A detailed analysis and several experiments of the proposed framework are included.