Hasil untuk "Industry"

Sairul Alam, Riri Ramadhani Putri, Sri Hartini

The production process of wedang uwuh at MSMEs XYZ frequently encounters interruptions caused by a scarcity of raw materials from a limited supplier base. This research employs the House of Risk (HOR) method to identify risks, prioritize risk agents, and formulate mitigation solutions. During the initial phase of HOR, 27 risk events and 30 risk agents were found, with 15 priority risk agents determined by a cumulative Aggregate Risk Potential (ARP) value of 81%. During the second phase of HOR, 24 mitigation strategies were developed, with the foremost five being: (PA14) routine equipment inspection and maintenance; (PA1) systematic sales documentation; (PA4) partnership with large farmers/suppliers; (PA11) standard operating procedures in the mixing process; and (PA13) formulation of adaptable contracts with suppliers concerning volume and delivery timelines. The execution of these mitigation techniques is anticipated to improve operational efficiency and supply chain resilience at XYZ MSMEs in addressing current concerns.

MA Changqing, LI Xuyang, LI Feng et al.

This study aims to accurately perceive the position and posture information of hydraulic supports in a disturbed environment. To address this, a precise perception method for the position and posture of hydraulic supports based on multi-sensor fusion was proposed. Firstly, nine-axis attitude sensors were deployed on four components of the hydraulic support, including top beam, shield beam, rear linkage, and base, to measure roll, pitch, and yaw angles using gyroscopes, accelerometers, and magnetometers. Then, the position and posture data was filtered using the Unscented Kalman Filter (UKF) algorithm and Improved Gradient Descent (IGD) algorithm (IGD-UKF algorithm), reducing interference from disturbance factors. Finally, an adaptive weighted fusion algorithm was employed to merge the filtered yaw and roll angle data of the top beam and base of hydraulic supports, eliminating data deviations caused by external vibrations, noise, and other factors. Perception experiments were conducted on the position and posture of top beam, shield beam, rear linkage, and base under various working conditions. The disturbances included the lowering and raising of top beam and base, as well as left-leaning, right-leaning, left-deviating and right-deviating of hydraulic supports. The study found that the data curves processed by the IGD-UKF algorithm exhibited smoother fluctuations, significantly suppressing oscillations and reducing amplitude. The yaw angle error of hydraulic supports ranged from 0.001 8° to 0.025 1°, with an average absolute error of 0.004 8°. The roll angle error ranged from 0.001 4° to 0.028 1°, with an average absolute error of 0.004 7°. The results indicate that the precise perception of the position and posture of hydraulic supports in a disturbed environment is achieved.

Madison L. Dirks, Joseph Hale, Eric Theiste et al.

Glycomacropeptide (GMP) is isolated from whey and used as an ingredient in phenylketonuria-safe foods because it does not contain phenylalanine. GMP is highly glycosylated and has several sites where <i>N</i>-acetylneuraminic acid (NANA) is bound. In the dairy industry, quantification of NANA from dairy proteins is accomplished by colorimetric, fluorometric, enzymatic, and chromatographic procedures; there is no uniformly accepted industry-wide standard method. In this investigation, NANA quantification methods were evaluated using GMP, and a comparison was made based on the length of time to complete the assay, protein-specificity, linearity, precision, and accuracy. From the methods evaluated, the chromatography protocol was determined to have the greatest benefit for use as a dairy industry standard to measure NANA on GMP. The average mass percent of NANA in 10 statistically independent replicates from a commercial GMP product was measured to be 6.18% ± 0.12%, with a relative standard deviation of 1.94%, which was the lowest of all the methods tested. The accuracy of the chromatographic approach was validated using spike and recovery experiments that provided an average recovery of 90.25%.

Ardian Kelmendi, George Pappas

The automotive industry increasingly relies on 3D modeling technologies to design and manufacture vehicle components with high precision. One critical challenge is optimizing the placement of latches that secure the dashboard side paneling, as these placements vary between models and must maintain minimal tolerance for movement to ensure durability. While generative artificial intelligence (AI) has advanced rapidly in generating text, images, and video, its application to creating accurate 3D CAD models remains limited. This paper proposes a novel framework that integrates a PointNet deep learning model with Python-based CAD automation to predict optimal clip placements and surface thickness for dashboard side panels. Unlike prior studies that focus on general-purpose CAD generation, this work specifically targets automotive interior components and demonstrates a practical method for automating part design. The approach involves generating placement data—potentially via generative AI—and importing it into the CAD environment to produce fully parameterized 3D models. Experimental results show that the prototype achieved a 75% success rate across six of eight test surfaces, indicating strong potential despite the limited sample size. This research highlights a clear pathway for applying generative AI to part design automation in the automotive sector and offers a foundation for scaling to broader design applications.

Stuart D. C. Walsh, Laura Easton, Changlong Wang et al.

Australia has ambitions to become a major global hydrogen producer by 2030. The establishment of Australia’s and the world’s hydrogen economy, however, will depend upon the availability of affordable and reliable hydrogen storage. Geological hydrogen storage is a practical solution for large scale storage requirements ensuring hydrogen supply can always meet demand, and excess renewable electricity can be stored for later use, improving electricity network reliability. Hosting thick, underground halite (salt) deposits and an abundance of onshore depleted gas fields, Australia is well placed to take advantage of geological hydrogen storage options to support its ambition of building a global hydrogen hub export industry. Using the Bluecap modelling software, we identify regions in Australia that are potentially profitable for large scale hydrogen production and storage. We use the results of this work to suggest high-potential regions for hydrogen development, supporting policymaker and investor decisions on the locations of new infrastructure and hydrogen projects in Australia.

Wei Wang, Yuhan Feng, Ruotong Wu et al.

With the development of agriculture and industry, the increase in nitrogen (N) deposition has caused widespread concern among scientists. Although emission reduction policies have slowed N releases in Europe and North America, the threat to biodiversity cannot be ignored. Arbuscular mycorrhizal (AM) fungi play an important role in the establishment and maintenance of plant communities in forest ecosystems, and both their distribution and diversity have vital ecological functions. Therefore, we analyzed the effects of long-term N addition on AM fungi and understory herbaceous plants in a Korean pine plantation in northern China. The soil properties, community structure, and diversity of AM fungi and understory herbaceous plants were detected at different concentrations of NH4NO3 (0, 20, 40, 80 kg N ha−1 year−1) after 7 years. The results showed that long-term N deposition decreased soil pH, increased soil ammonium content, and caused significant fluctuations in P elements. N deposition improved the stability of soil aggregates by increasing the content of glomalin-related soil protein (GRSP) and changed the AM fungal community composition. The Glomus genus was more adaptable to the acidic soil treated with the highest N concentration. The species of AM fungi, understory herbaceous plants, and the biomass of fine roots were decreased under long-term N deposition. The fine root biomass was reduced by 78.6% in the highest N concentration treatment. In summary, we concluded that long-term N deposition could alter soil pH, the distribution of N, P elements, and the soil aggregate fractions, and reduce AM fungal and understory herb diversity. The importance of AM fungi in maintaining forest ecosystem diversity was verified under long-term N deposition.

Liming LIN, Qinfei WANG, Houmei YU et al.

In order to understand the freezing characteristics and metabolites of cassava root, the edible cassava variety “South China 9” was taken as the research object, by measuring the freezing-law and related influencing factors at the head, middle and tail of cassava root, combined with non-targeted metabolomics to analyze the differential metabolite. The results showed that: The freezing temperature was from −0.6 to −1.1 ℃ in different parts of root, but the freezing time was different. The highest values of soluble solid content and starch content in different parts appeared in the head, which were 7.00% and 26.84% respectively, but there was no significant difference among different parts (P>0.05), while the highest value of water content appeared in the tail, which was 64.07%. Correlation analysis showed that freezing point was negatively correlated with soluble solids and water content, and positively correlated with starch content. Compared with control, 41 differential metabolites were screened under low treatment by the non-targeted metabolomics, and the enrichment degree of phenylalanine metabolic pathway was the highest, with a total of 9 significant differential metabolites. In this pathway, the expression of hippuric acid and benzoic acid was up-regulated, which might be related to the response of root tubers to low temperature. The results provide theoretical reference for low-temperature storage in the future.

Hasanul Banna, Md Rabiul Alam

This paper examines the nexus between digital financial inclusion (DFI) and levels of bank risk-taking, using a sample of 283 commercial banks (Islamic and conventional) from six countries over the period 2011 to 2019 and deploying panel-corrected standard errors, two-stage least squares-instrumental variables and dynamic panel two-step generalized method of moments estimators. The findings suggest that Islamic banks take more risks than their counterpart conventional banks. The empirical evidence also indicates that an increase in the DFI index score reduces the overall level of bank risktaking and increases that of banking stability for commercial and conventional banks compared to Islamic ones. A strong association between DFI and bank risk-taking suggests that DFI not only reduces the default risk, leverage risk and portfolio risk of banks, but also increases financial mobility in the sample countries. Consequently, an inclusive digitalised banking industry ensures sustainable economic growth, which is likely to help maintain financial sustainability in times of crisis such as the Covid-19 pandemic. Our results are shown to be robust by various robustness checks. The study contributes to both the Islamic and conventional banking, as well as the digital financial inclusion, literature. The findings of the study provide various policy implications for policymakers and standard-setters in the countries examined.

Liang Xiao, Kunhui Ye, Junhong Zhou et al.

Collusive bidding has been an insidious issue in the construction industry. Bidders initiate collusive networks of various sizes to win market shares. The popularity of collusive bidding networks affects market fairness and erodes the interests of market players. Although considerable research efforts were made to diagnose collusive bidding networks, there remains a gap in knowledge regarding the relationships bid riggers use to engage in the networks. Therefore, this study used the social network method, where two hundred sixteen collusion cases were collected from China to test these relationships. The results show that collusive bidding networks were characterized by sparseness, a small scale, a high concentration, and strong randomness. Three types of collusive bidding networks were also detected: contractual, spontaneous, and shadow. Furthermore, these collusive bidding networks had discrepancies regarding participants’ identities, forms of collusive bids, and the determination of bid winners. It was found that the proposed social network model of deliberating bid riggers’ relationships lays a solid foundation for the detection of collusive bidding in the construction sector.

Jing Qian, Qiming Zhou, Xi Chen et al.

Investigation of urban expansion can provide a better understanding of the urbanization process and its driving forces, which is critical for environmental management and land use planning. Total of 514 sampling points from the aerial photos and field sampling were applied to assess the image accuracy. A Conversion of Land Use and its Effect at Small Region Extent (CLUE-S) model was established to simulate the urbanization process at the township level in the North Xinjiang Economic Zone (NXEZ) of western China. Historical land use and land cover changes with multi-temporal remote sensing data were retrieved, and the underlying driving forces were explored by training the CLUE-S model. Moreover, future changes in urban development were simulated under different scenarios. Results showed that the overall accuracy reaches larger than 80% for the years of 2002, 2005, and 2007, and the corresponding kappa coefficient is bigger than 0.8. The NXEZ is at a premature development stage compared with urban clusters in eastern China. Before 1999, the driving force in this region was primary industry development. In recent years, secondary industries started to show significance in urbanization. These findings indicate that the industrial base and economic development in the NXEZ are still relatively weak and have not taken a strong leading role. When industry and population become the main driving factors, the regional economy will enter a new stage of leap-forward development, which in turn will stimulate a new round of rapid urbanization.

Bárbara Castillo-Abdul, Luis M. Romero-Rodríguez, Ana Larrea-Ayala

This research analyses the contents of the videos of the ten Spanish children's YouTube channels with the highest number of followers and video plays to identify correlations between the thematic axes of the videos and the increase in digital engagement data. Little is known about the topics that the most popular Spanish-language YouTube influencers share with preteens and young adults' audience. In response, this exploratory study will use content analysis to examine this gap and contrast the themes that its videos reflect against others. For this purpose, interpretive-based content analysis is carried out based on an analysis sheet validated by expert judgment. Among the main results, it is shown that most of the children who are the lead character of the channel are currently between 10 and 12 years old, having created the channels an average of five years ago, which shows how early many YouTubers are starting in this industry. There are also differences in the thematic axes of the channels' videos according to the gender of the children's influencers, with a higher representation of male YouTubers devoted to gameplays, while their female peers have a more significant presence in videos in the lifestyle category. It is concluded that there is a need to supervise the contents accessed by children on this platform since it can deepen not only gender gaps but also become a wrong reference of role models.

Vadim Kapp, Marvin Carl May, Gisela Lanza et al.

This paper presents a framework to utilize multivariate time series data to automatically identify reoccurring events, e.g., resembling failure patterns in real-world manufacturing data by combining selected data mining techniques. The use case revolves around the auxiliary polymer manufacturing process of drying and feeding plastic granulate to extrusion or injection molding machines. The overall framework presented in this paper includes a comparison of two different approaches towards the identification of unique patterns in the real-world industrial data set. The first approach uses a subsequent heuristic segmentation and clustering approach, the second branch features a collaborative method with a built-in time dependency structure at its core (TICC). Both alternatives have been facilitated by a standard principle component analysis PCA (feature fusion) and a hyperparameter optimization (TPE) approach. The performance of the corresponding approaches was evaluated through established and commonly accepted metrics in the field of (unsupervised) machine learning. The results suggest the existence of several common failure sources (patterns) for the machine. Insights such as these automatically detected events can be harnessed to develop an advanced monitoring method to predict upcoming failures, ultimately reducing unplanned machine downtime in the future.

Е. Yu. Dmitrieva, О. V. Suintuirenko

The article gives data of the problem of import substitution and conversion to the reindustrialization of the Russian economy on a new technological basis as a part of a comparative analysis by industry. A set of priority tasks, problem-oriented nature, on information support of processes of import substitution and conversion of military production is shown. Factors impeding the solution of information support tasks, as well as economic problems determining the development of import substitution and conversion processes in the Russian economy, are considered.

Jing Wang, Shaojuan Ma, Peng Hao et al.

In this paper, the Hopf bifurcation and control of the magnetic bearing system under an uncertain parameter are investigated. Firstly, the two-degree-of-freedom magnetic bearing system model with uncertain parameter is established. The method of orthogonal polynomial approximation is used to obtain the equivalent magnetic bearing model which is deterministic. Secondly, combining mathematical analysis tools and numerical simulations, the Hopf bifurcation of the equivalent model is analyzed. Finally, a hybrid feedback control method (linear feedback control method combined with nonlinear stochastic feedback control method) is introduced to control the Hopf bifurcation behavior of the magnetic bearing system.

Febi Fatimah, R. Deni Muhammad Danial, Faizal Mulia Z

The purpose of this study was to analyze the practice of income smoothing in food and beverage industry companies. Income smoothing is the intentional reduction of earnings fluctuations in an effort to stabilize profits to be considered normal for a company. This data is obtained from www.idx.co.id. The population in this study were food and beverage companies listed on the Indonesia Stock Exchange for the period of 2014-2016. The sampling technique used was using the purposive sampling method from 16 samples to 10 samples used. The data analysis technique of this research is descriptive statistical analysis techniques. To calculate income smoothing using the Eckel Index formula. The results of this study indicate that 6 companies carry out income smoothing practices and 4 companies do not.

Akihiro Yoshida, Tatsuru Higurashi, Masaki Maruishi et al.

Abstract The studies of browsing behavior have gained increasing attention in web analysis for providing better service. Most of the conventional approaches focus on simple indices such as average dwell time and conversion rate. These indices make similar evaluations to websites even if their features are significantly different. Moreover, such statistical indices are not sensitive to the dynamics of users’ interests. In this paper, we propose a new framework for measuring a website’s attractiveness that takes into account both the distribution and dynamics of users’ interests. Within the framework, we define a new index for the website, called Attractiveness Factor, which evaluates the degree of users’ attention. It consists of three procedures: First, we capture the transition of users’ interests during browsing by solving a nonnegative matrix factorization and constrained network flow problems. To accommodate multiple types of interests of a user, we applied a soft clustering as opposed to a hard clustering to model attributes of users and websites. Second, for each website, the feature of each cluster is obtained by fitting the dwell time distribution with Weibull distribution. Finally, we calculate Attractiveness Factor of a website by applying the results of clustering and fitting. Attractiveness Factor depends on the distribution of the dwell time of users interested in the website, which reflects the change of interest of users. Numerical experiments with real web access data of Yahoo Japan News are conducted by solving extremely large-scale optimization problems. They show that Attractiveness Factor captures more exceptional information about browsing behavior more effectively than well-used indices. Attractive factors give low ratings to category pages; however, it can assign high ratings to websites that attract many people, such as hot topic news about the 2018 FIFA World Cup, Japan’s new imperial era’ REIWA,’ and North Korea—the United States Hanoi Summit. Moreover, we demonstrate that Attractiveness Factor can detect the tendency of users’ attention to each website at a given time interval of the day.

Peter Binfield

PeerJ Inc (the open access publisher of both 'PeerJ' and 'PeerJ PrePrints') announced itself in mid-2012, and started publishing articles in February 2013. Although to the casual observer, PeerJ might be thought of as ‘just another open access (OA) publisher’, in fact (as evidenced by several industry awards) it is building an environment which has publishing at its core, but which also addresses the needs of the academic community in several additional ways. In this article, one of the co-founders of PeerJ describes innovations such as their ‘individual-centric’ business model; their ‘optional open peer-review’ system; the PeerJ contribution points; the visual design; and several important aspects of their philosophy which together are creating a publishing system suitable for the needs of the 21st-century academic.

Wardah Naim, Trevor Tombe

If anything is to blame for a higher dollar having negative effects on the Central Canadian manufacturing sector, you are not likely to find it in any “Dutch Disease” supposedly caused by Alberta’s oil sands. Contrary to popular belief, the higher value of the Canadian dollar may even help Central Canadian manufacturers grow stronger, cut costs, and create jobs. The idea that a booming, commodity-driven dollar is hurting Canadian goods exports, afflicting the country with so-called Dutch Disease, may be popular among certain politicians, including federal Opposition leader Thomas Mulcair and former Premier of Ontario Dalton McGuinty, but is not supported by the facts. It turns out that the simple economic theory these politicians have in mind is incomplete. A more thorough, data-driven look at the nation’s manufacturing sector reveals that Canadian businesses rely very heavily on imported materials and equipment as inputs in the manufacturing process. Canadian industry overall has one of the highest import ratios for such intermediate goods in the OECD, roughly twice as high as that of the U.S., the European Union and Japan. Compared to all other sectors, manufacturers are the heaviest users of imported materials and equipment, with more than 40 per cent of their inputs coming from other countries. A higher dollar may make it more expensive for foreign buyers to purchase Canadian manufactured goods, but that effect appears to be more than offset by the savings that Canadian producers enjoy with a higher dollar that makes possible cheaper imported-inputs and lower cost of production, which have a lowering effect on prices. The net result is that Canadian manufacturers actually get more benefit from a higher dollar, and the regions that get the biggest boost from it are the Central Canadian provinces of Ontario and Quebec. Policy-makers looking to aid the Canadian economy as a whole, and the manufacturing sector in particular, should stop worrying about Dutch Disease and, rather, welcome a higher Canadian dollar. But more than that, they should design policies that are better tailored for an economy that relies so heavily on imported intermediate inputs. Policy efforts would be far better put to eliminating tariffs and other trade barriers that make imported inputs more expensive, and thus hamper Canadian competitiveness. Policies should also focus on improving productivity, by inviting foreign investment, rather than subtly discouraging it through vehicles such as the Investment Canada Act. And certainly, anything that forces businesses to “buy local,” as Ontario’s Green Energy Act requires, will only stand in the way of Canadian businesses taking advantage of our higher dollar by importing lower-cost inputs from abroad. If policy-makers want to help Canadian factories, they shouldn’t complain about Alberta but instead focus on improving their domestic economic policies instead.

Mitsuaki Hosono, Yasuo Nakayama

Since mid-1990s, the Japanese government has encouraged university-industry collaboration to foster innovations for economic growth. Learning from the American licensing model of technology transfer, Japanese Bay-Dole Act and TLO (Technology Licensing Organization) Act were enacted in late 1990s. In addition, the corporatization of Japanese National Universities (JNUs) in 2004 spurred their technology-transfer activities to obtain external funds. As a result, more than 50 TLOs has been established since FY1998, and also the number of patent application and licensed patents were increased at JUNs rapidly after FY2004. However, the licensing income has been stayed poor and some of TLOs were abolished. There are few evidences that the introduction of licensing model of technology transfer into Japan could contribute to innovation properly. Therefore, this study will try to clarify if licensing model of technology transfer work in Japan by analyzing the Japanese National University (JNU) patent. There are 20,485 applied patent, which invented by JNU’s researcher(s) from FY2004 to 2007. 38% of them were applied by solely by JNUs and 52% were by JNU and Private Firms etc. In the Japanese Patent Act, jointly applied patents are not licensed to the third party without the consent of co-applicant(s). Hence, more than half of the patent invented by JNU researchers is not basically used for patent licensing. Consequently, JNUs and TLOs face difficulties in patent licensing under the current Patent Act.

A. A. Adams

Conflation of academic copyright issues with respect to books (whether text books, research monographs or popularisations) and research articles, is rife in the academic publishing industry. A charitable interpretation is that this is because to publishers they are all effectively the same: a product produced for commercial benefit. An uncharitable interpretation is that this is a classic Fear Uncertainty and Doubt approach, in an attempt to delay the inevitable move to Open Access (OA) to research articles. To authors, however, research articles and books are generally very different things. Research articles are produced without the expectation of direct financial return, whereas books generally include some consideration of financial return. Taylor’s “Copyright and research: an academic publisher’s perspective” (SCRIPT-ed 4:2) falls wholesale into this mental trap and in particular his lauding of the position paper of the Association of American Professional and Scholarly Publishers, shows a lack of understanding of the continuing huge loss to scholarship of a lack of OA to research articles. It should be regarded as a categorical imperative for scholars to embrace OA to research articles.