Product System Research Articles

Chemoinformatics-driven classification of Angiosperms using sulfur-containing compounds and machine learning algorithm

BackgroundPhytochemicals or secondary metabolites are low molecular weight organic compounds with little function in plant growth and development. Nevertheless, the metabolite diversity govern not only the phenetics of an organism but may also inform the evolutionary pattern and adaptation of green plants to the changing environment. Plant chemoinformatics analyzes the chemical system of natural products using computational tools and robust mathematical algorithms. It has been a powerful approach for species-level differentiation and is widely employed for species classifications and reinforcement of previous classifications.ResultsThis study attempts to classify Angiosperms using plant sulfur-containing compound (SCC) or sulphated compound information. The SCC dataset of 692 plant species were collected from the comprehensive species-metabolite relationship family (KNApSAck) database. The structural similarity score of metabolite pairs under all possible combinations (plant species-metabolite) were determined and metabolite pairs with a Tanimoto coefficient value > 0.85 were selected for clustering using machine learning algorithm. Metabolite clustering showed association between the similar structural metabolite clusters and metabolite content among the plant species. Phylogenetic tree construction of Angiosperms displayed three major clades, of which, clade 1 and clade 2 represented the eudicots only, and clade 3, a mixture of both eudicots and monocots. The SCC-based construction of Angiosperm phylogeny is a subset of the existing monocot-dicot classification. The majority of eudicots present in clade 1 and 2 were represented by glucosinolate compounds. These clades with SCC may have been a mixture of ancestral species whilst the combinatorial presence of monocot-dicot in clade 3 suggests sulphated-chemical structure diversification in the event of adaptation during evolutionary change.ConclusionsSulphated chemoinformatics informs classification of Angiosperms via machine learning technique.

An Operational Atmospheric Correction Framework for Multi-Source Medium-High-Resolution Remote Sensing Data of China

Land surface reflectance (LSR) data form the basis of quantitatively remotely sensed applications. For accurate LSR retrieval, atmospheric correction has been investigated by many researchers and implemented in typical processing systems, including common atmospheric correction software for various types of datasets and automatic operating systems for application to certain individual data sources. In recent years, China has launched multiple medium–high-resolution satellites but has not provided standard LSR products partly because of the lack of an appropriate operational system. In this paper, a multi-source remote sensing LSR product system for medium- and high-resolution data is proposed, called the “Operational Atmospheric Correction Framework for multi-source Medium-high-resolution Remote Sensing data of China” (ACFrC). The AC algorithm, processing flow, and design of the multi-source LSR system were described in detail. A practical atmospheric correction algorithm was proposed specially for data in only the visible and near-infrared (VNIR) bands. The entire processing chain was divided into modules for multi-source data ingestion, apparent reflectance calculation, cloud and water identification, atmospheric correction, and standard LSR product generation. To date, most types of multi-source data have been tested using the ACFrC system, with reasonable results being obtained. From the preliminary results, the 313 scenes of LSR products from the GaoFen-2 (GF-2) satellite over China for the period from 2015 to 2018 were cross-compared with Landsat-8 LSR acquired on the same day, showing an overall uncertainty less than 0.112 × LSR + 0.0112. Further, the ACFrC data processing efficiency was found to be suitable for automatic operation. System improvement is ongoing and future refinements will include online cloud parallel computing functionality and services, more robust algorithms, and other radiometric processing functions.

Validation of a Multi-Residue Analysis Method for 287 Pesticides in Citrus Fruits Mandarin Orange and Grapefruit Using Liquid Chromatography-Tandem Mass Spectrometry.

Since the introduction of the positive list system (PLS) for agricultural products in the Republic of Korea, the demand for a quick, easy multi-residue analysis method increased continuously. Herein, the quick, easy, cheap, effective, rugged, and safe (QuEChERS) technique combined with liquid chromatography−tandem mass spectrometry was employed to optimize a method for the multi-residue analysis of 287 pesticide residues in mandarin orange and grapefruit. Method validation was conducted in terms of selectivity, limit of quantitation (LOQ), linearity, accuracy, precision, and matrix effect. All the compounds at low spiking levels (1, 2.5, 5, or 10 mg/kg) could be quantified at LOQs lower than 0.01 mg/kg (PLS level). The linearity of the matrix-matched calibration curve for each compound is in the range 0.5−50 μg/L, and its coefficient of determination (R2) is >0.990. Satisfactory recovery values of 70−120% with a relative standard deviation of ≤20% are obtained for all compounds in the mandarin orange and grapefruit samples. A negligible matrix effect (−20−20%) is observed for more than 94.8% and 85.4% of the pesticides in mandarin orange and grapefruit, respectively. Therefore, this analytical method can contribute to pesticide residue analyses of citrus fruits for routine laboratory testing.

Reducing the Risks of Home Dialysis Innovation and Uptake: The Case for Human-Centered Product Design.

Reducing the Risks of Home Dialysis Innovation and Uptake: The Case for Human-Centered Product Design.

Investigate an imperfect green production system considering rework policy via Teaching-Learning-Based Optimizer algorithm

Green products have achieved a wide reputation in the current competitive market in the last few decades. Again, the imperfect production rate during production imposes a minor issue in generating optimal revenue for a manufacturing firm. Primarily focusing on these two factors, the current study demonstrates an imperfect production inventory system of green products by considering two activities regarding business accommodation of imperfectly manufactured products: (i) rework and (ii) salvage. The primary purpose of this work is to study the optimal policy of a manufacturing firm based on production control, the greenness of the products, and the rework or salvage of defective products. Here, consumers’ demand is green level and selling price dependent. Further, production costs are green-level and production rate dependent. The average profits of the system (corresponding to both cases) appear to be highly non-linear. They necessitate the employment of a meta-heuristic algorithm (viz., the Teaching-Learning-Based Optimizer Algorithm). From the numerical example, it is observed that the reworked policy appears to be more profitable than the salvage policy for the firm. Finally, a sensitivity analysis is carried out to draw some fruitful conclusions.

RANCANG BANGUN SISTEM INFORMASI PENJUALAN BERBASIS WEB DENGAN FRAMEWORK CODEIGNITER PADA APOTEK ZALTA FARMA SAMARINDA KALIMANTAN TIMUR

Zalta Farma Drugstore is a health institution in selling drug. The administration system was conventional that every transaction was manually written thus causing some problems such as error in calculation, unvalidated information, and difficulties in writing report. The aims of this research were to design and to know the implementation of information system of sale product based on website at this drugstore. The development method of this system used SDLC method with application development system such as flowchart, diagram, context, DFD, and a purposed database designing (ERD). Moreover, the used Text Editor software was Visual Studio Code in PHP programming language using framework code igniter and database using MySQL.
 The result was an information system of sale product based on website that used by Zalta Farma Drugstore. This system helps people in transaction thus the monthly report was produced every month

Studies towards the Synthesis of (+)-Dictyoxetane.

The dolabellane-type diterpene dictyoxetane represents a significant challenge to synthetic organic chemistry. Methodology directed towards the total synthesis of naturally occurring (+)-dictyoxetane is reported. Catalytic asymmetric synthesis of the trans-hydrindane ring system is achieved through chemoselective deoxygenation of the Hajos-Parrish ketone. An alternative to the Garst-Spencer furan annulation is developed for the synthesis of a 2,5-dimethyl, tetrasubstituted furan, employing a tandem 5-exo-dig alcohol to alkyne cyclisation/aromatisation reaction as a key step. The (4+3) cycloaddition reaction of an oxyallyl cation with a tetrasubstituted furan is established on a cyclohexanone-derived model system, and a range of related (4+3) cycloadditions investigated on a homochiral, trans-hydrindane-fused furan, where regio- and diastereoselectivity is required for the natural product synthesis. In an alternative (4+2) Diels-Alder approach, a C2 -symmetric vinyl sulfoxide-based chiral ketene equivalent is used to prepare oxanorbornenes with the same oxygen bridge stereochemistry found in the 2,7-dioxatricyclo[4.2.1.03,8 ]nonane ring system of the natural product.

Life cycle impacts of concentrated solar power generation on land resources and soil carbon losses in the United States

Endpoint impacts related to the transformation of land—including that related to energy infrastructure—have yet to be fully quantified and understood in life cycle assessment (LCA). Concentrated solar power (CSP) which generates electricity by using mirrors to concentrate incoming shortwave radiation onto a receiver, may serve as an alternate source of reliable baseload power in the coming years. As of 2019 (baseline year of the study), the United States (U.S.) had 1.7 GW of installed capacity across a total of eight CSP sites. In this study, we (1) develop an empirical, spatially explicit methodology to categorize physical elements embodied in energy infrastructure using a LCA approach and manual image annotation, (2) use this categorization scheme to quantify land- and ecosystem service-related endpoint impacts, notably potential losses in soil carbon, owing to energy infrastructure development and as a function of electricity generated (i.e., megawatt-hour, MWh); and (3) validate and apply this method to CSP power plants within the U.S. In the Western U.S., CSP projects are sited in Arizona, California, and Nevada. Project infrastructure can be disaggregated into the following physical elements: mirrors (“heliostats”), generators, internal roads, external roads, substations, and water bodies. Of these elements, results reveal that mirrors are the most land intensive element of CSP infrastructure (>90%). Median land transformation and capacity-based land-use efficiency are 0.4 (range of 0.3–6.8) m2/MWh and 40 (range of 11–48) W/m2, respectively. Soil grading and other site preparation disturbances may result in the release of both organic and inorganic carbon—the latter representing the majority stocks in deeper caliche layers—thus leading to potentially significant losses of stored carbon. We estimate three scenarios of soil carbon loss into the atmosphere across 30 years, based on land transformation in m2per megawatt-hour (m2/MWh) and carbon stock in kilograms of carbon per megawatt-hour (kg C/MWh). Results reveal that potential belowground CO2released may range from 7 to 137% of total life cycle CO2emissions. While this study takes a simplistic approach to estimating loss of carbon, the broad methodology provides a valuable baseline for improving comparative analyses of land-related endpoint impacts across energy technologies and other product systems.

Modeling circularity as Functionality Over Use-Time to reflect on circularity indicator challenges and identify new indicators for the circular economy

The Circular Economy describes an economic system that creates value without causing unrecoverable waste, a growing problem of the Anthropocene. The question remains what solutions to reversing this course could look like and how indicators should be designed to measure their capabilities to constitute a circular economy. These indicators should allow for a nexus approach, i.e., consider synergies and trade-offs with other important social, environmental, and economic factors. Earlier research shows a research gap in indicators able to assess value change and retention, i.e., the preservation of specific functions instead of products in general. Aiming to fill this gap, in this article, we discuss using the concept of functionality from Life Cycle Assessment over the time product systems are used to measure circularity. We create a Functionality Over Use-Time (FOUT) graph and use it to illustrate the challenges of existing circularity indicators. The challenges are grouped into four clusters: 1) multi-cyclic longevity; 2) up- & downcycling effects; 3) measuring disruptive change instead of incremental change; 4) integration into sustainability assessment. We discuss how considering FOUT could solve these challenges and propose two novel indicators derived from the approach: A functional circularity indicator and a cross-functional circularity indicator. The functional circularity indicator measures the integral surface of functionality over the use-time of the original product's materials. The cross-functional circularity indicator measures the time a product's functionality is reduced by half. Finally, FOUT modeling and the indicators are exemplified in a comparative case study of a steel-reinforced concrete double wall and a Carbon Reinforced Concrete double wall. Further case studies are needed for future research, including FOUT indicator integration in Life Cycle Sustainability Assessment and a detailed representation of the 10R in FOUT modeling.

Determining the impacts and recovery potentials of a modular designed residential building using the novel LCA-C2C–PBSCI method

Assessing the circularity and impact potentials of buildings has become a growing concern in the scientific community. Life cycle assessment (LCA) is a key tool used to evaluate the environmental impact potentials of buildings, but its adoption for assessing circularity is faced with several limitations. In this study, the novel LCA-cradle-to-cradle-predictive building systemic circularity indicator (LCA-C2C–PBSCI) method is adopted to evaluate the impact and recovery potentials of a modular designed residential building in China. Case scenarios based on the forecasted recyclable percentages of materials and recyclability plan of the case building were modeled and assessed using the PBSCI. The impact potentials of the case scenarios were also concurrently assessed using the LCA-C2C aspect of the method. It was found that, the average product utility, mass of materials and the adopted recyclability plan of the case building influences the rate of recyclability at end-of-life (EoL). Also, the chosen EoL allocation approach, the predicted mass recyclable and the adopted disposal scenarios hugely influence the impact potentials of the case building. The recommended scenario for the case building was one which had a high recoverable potential (85.3% of mass recyclable), but low impact potentials (432.021 kg CO2/m2). The adoption of this iterative method for assessing the impacts and recovery potentials of buildings does not only provide a means to formulate decisions based on the environmental impacts of materials or product system only, but also a way to consider the technical, social, and economic implications of such decisions towards the attainment of sustainable development.

Vectorization Analysis of Cultural Creative Design Based on the Recognition Model of Virtual Reality Technology

In order to solve the problem of large color matching errors exhibited in the previous color matching system, this study proposes a special color automatic matching system for cultural and creative products based on virtual reality technology. In this study, virtual reality technology (Technology) is applied to the proposed system design. Based on the three-tier architecture, the system framework is designed. The architecture includes a data access layer, a business logic layer, and a presentation layer. The hardware includes a spectrophotometer, a central processing unit, a storage device, and a virtual reality somatosensory interaction device, and the four key devices are introduced in detail. The software part takes the BP neural network algorithm as the core, trains and processes the three color values, constructs the automatic color matching model of cultural and creative products according to the training results, and realizes the logical operation and analysis of the system software. The experimental results show that although there is still a certain error between the color matching of the cultural and creative products output by the system and the actual color matching of the test samples, the maximum absolute error of the matching is relatively small, both of which are less than 0.05, which proves the effectiveness of the research to a certain extent. The error between the 6 groups of actual matching samples and the predicted matching samples is <1.5, which proves that the color difference is related to human vision, indicating that the matched samples have no color difference and achieve the expected effect. Although there are some errors between the designed system and the expected color matching, the error is small, so the color difference does not affect the visual presentation effect.

Application Prospect of Data Mining Technology in Intelligent Manufacturing

In recent years, with the application of sensors, data acquisition equipment and other modules with sensing ability in the service of complex products, the operation and maintenance system of complex products has become increasingly digital and intelligent. New-generation information technologies such as big data, cloud computing, Internet of Things, mobile Internet, augmented reality (AR) and virtual reality (VR) have also been rapidly applied in the operation and maintenance of complex products. Real-time, multi-source, and massive data has become the basis for decision-making. Data-driven intelligent services have become the development direction of modern manufacturing services. This paper introduces the connotation of intelligent manufacturing and the characteristics of industrial big data, analyzes the application status of data mining technology in intelligent manufacturing, and envisages the future application trend.

Blockchain-Based Anti-Counterfeiting Management System for Traceable Luxury Products

In recent years, counterfeit luxury products have become a major concern for consumers worldwide. The reason for the proliferation of counterfeit products is that the manufacturing and distribution process is not transparent to consumers and this information can be easily falsified or altered by others. To solve this problem, this paper proposes the development of a management system using blockchain and smart contract technology to solve the problems of data forgery and data tampering, while tracking the information related to luxury products and ensuring the accuracy and authenticity of the relevant data, to achieve the purpose of luxury product anti-counterfeiting. When using Hyperledger Fabric to deploy the blockchain and execute smart contracts, all information related to the production and logistics process of luxury goods will be uploaded to the blockchain. No human intervention is required to create a complete, traceable, tamper-proof, and trusted repository. Compared to previous work, this paper combines blockchain technology with specific processes in the supply chain, employing a variety of security methods to secure the communication process. Moreover, our proposed solution is more flexible in transmission, with more secure protocols also making data harder to tamper with and falsify, thereby solving the problem of forgery and tracking of luxury products.

A Capability Maturity Model for STP aware Software Development

There has been an increase in the importance of software Security, Trust, and Privacy (STP). Product systems must be designed with trustworthy STP protection methods while still rendering the required benefits of applications to its consumers. As a result of this large skill gap, colleges and the software sector have found themselves in a state of supply- and-demand conflict. STP-aware software development requires a new practice Capability Maturity Model (CMM) to address this issue. In order to help colleges progressively increase their students' capacity to apply what they have learned in the classroom, this contribution provides a model that consists of 4 levels: Awareness, Curriculum, Project, and Enterprise, for STP-aware software development. Software development that is STP-aware has been shown to be quite beneficial in the development of programming talent's practice capabilities for learners.

KMS States of Quasi-Free Dynamics on C*-Algebras of Product Systems over Right LCM Monoids

Abstract We generalise recent results of Afsar, Larsen, and Neshveyev for product systems over quasi-lattice orders by showing that the equilibrium states of quasi-free dynamics on the Nica–Toeplitz $C^{\ast }$-algebras of product systems over right LCM monoids must satisfy a positivity condition encoded in a system of inequalities satisfied by their restrictions to the coefficient algebra. We prove that the reduction of this positivity condition to a finite subset of inequalities is valid for a wider class of monoids that properly includes finite-type Artin monoids, answering a question left open in their work. Our main technical tool is a combinatorially generated tree modelled on a recent construction developed by Boyu Li for dilations of contractive representations. We also obtain a reduction of the positivity condition to inequalities arising from a certain minimal subset that may not be finite but has the advantage of holding for all Noetherian right LCM monoids, and we present an example, arising from a finite-type Artin monoid, that exhibits a gap in its inverse temperature space.

Constructing a personalized recommender system for life insurance products with machine‐learning techniques

SummaryThe collaborative filtering (CF) recommendation algorithm predicts the purchases of specific users based on their characteristics and purchase history. This study empirically analyzes the possibility of applying CF to the insurance industry using real customer data from South Korea. Using three different CF models, we examined the relevance of applying the CF model to insurance products under various situations by comparing them with logistic‐regression‐based recommendation models. Through experiments, we empirically show that CF models apply to the insurance industry, especially when customer purchase information is added to the model.

Used-Part-Collection Programs in Manufacturing Systems for Products With Reusable Parts: Roles of Risk Aversion and Platforms

Many consumer products, e.g., printer’s cartridges, milk’s glass bottles, etc., are sold with reusable parts, which can be formally collected under a used-part-collection (UPC) program. In today’s markets with high volatility, risk is present for UPC operations. In this article, building via standard consumer utility-based models, we uncover the value of the UPC program in a production system. In the basic model, we consider the case when the manufacturer is risk averse. For both the cases with and without UPC, the optimal product pricing and quality decisions are determined and the respective manufacturer’s utility and consumer surplus are derived. The values of UPC to the manufacturer and consumers are found. We find that: 1) both quality improvement and UPC can be beneficial to consumers under some situations and 2) the optimal quality level, the optimal utility, and the consumer surplus are independent of the return fee. In the extended models, we explore two cases, namely, the case when consumers are risk averse, and the case with a collection platform, which can enhance the collection rate. We find that no matter what the level of consumers’ risk averse is, it reduces consumers’ benefits. Moreover, a higher platform’s power is beneficial to the manufacturer and consumers but may reduce the platform’s profit.

Sustainability assessment of product systems in dire straits due to ISO 14040–14044 standards: Five key issues and solutions

AbstractQuintessential for a more sustainable society is adequate sustainability assessment to guide us. In the case of environmental impact assessment of product systems, life cycle assessment (LCA) is the main method, with associated variants covering other sustainability pillars. At the core of LCA practice are the standards set up by the International Organization for Standardization (ISO), namely ISO 14040–14044. However, I point out five key issues with these standards: (1) the presence of inconsistencies on crucial matters as pointed out in the literature; (2) a lack in major update since two decades; (3) mismanagement of notified issues; (4) lacking representativeness; and (5) a low or unclear relevance. I provide solutions for these but overall plea for a societal intervention to put this method back on track.

Evaluation of the implementation of the halal assurance system for mininori products at cv panda food, special region of yogyakarta

Halal is one of the essential requirements for seasonal consumers in consuming food products. CV Panda Food is one of the snack manufacturers that requires a halal certification for products to be distributed. This observation aims to determine whether the raw materials used have received a halal certificate and to analyze the suitability of the Halal Assurance System (SJH) application based on the HAS 23000 standard. The methods used in data collection are observation, interviews, direct practice, documentation, and literature study. The evaluation was carried out by checklist analysis and adjusted to 11 HAS 23000 LPPOM MUI requirements. The results are that all raw materials have received Halal approval from the MUI. After conducting a suitability analysis of the CV Panda Food Halal Assurance System implementation, there are still deficiencies; the requirement that must be corrected first are written procedures for critical activities, training, halal management team, and halal policies.

Analisis Sistem Akuntansi dan Pengendalian Internal Produk Tabungan Emas Pada PT Pegadaian (Persero) Cabang Pasar Mawar

Gold can be an alternative investment, one of which will be very profitable and safest, because the investment value does not have an impact on inflation, prices continue to increase. The price flexibility of buying and selling transactions makes people choose to invest in gold. This study aims to analyze the accounting system for opening accounts for gold savings products, accounting systems for product disbursement and closing accounts for gold savings products, and the application of internal control in the accounting system for gold savings products at PT Pegadaian (Persero) Pasar Mawar Branch. This research is descriptive with a qualitative analysis approach, with data collection methods using literature study techniques and documentation and observations (observations). This study concludes that the gold savings product uses an accounting system, namely the Pegadaian Application Support System Integrated Online (PASSION). The product disbursement accounting system is carried out with two methods of disbursing savings products in the form of gold and cash. The gold savings product account can be closed at any time without any conditions for depositing a nominal balance. The five components contained in internal control are Control Environment, Risk Assessment, Control Activities, Information and Communication, and Monitoring.