Hasil untuk "Packaging"

Olivier Thom

Discrete sums of exponentials $g(w) = \sum a_β \mathrm{e}^{βw}$ with positive exponents may converge not normally in neighborhoods $H$ of $-\infty$ which do not contain half-planes. We study different notions of convergence for these series and in particular the intuitive notion of summation by packages. Indeed, joining in packages the terms in the sum $g(w)$ whose exponents are close together, and summing first inside each package may result in massive cancellations. We show that discrete sums $g(w)$ which are bounded in what we call logarithmic neighborhoods can always be summated by packages.

A. P. F. Coelho, E. F. Araujo, C. S. Silva et al.

Abstract Seeds are efficient routes for the dissemination of phytopathogens, mainly fungi. Reducing the water content and treating with fungicides are strategies to prevent these microorganisms from interfering with the quality of stored seeds. However, arabica coffee seeds are sensitive to desiccation and there are no recommended products for controlling fungi during storage. Some essential oils (EOs) have bactericidal, insecticidal and fungicidal action and can be used to treat seeds. The objective of this work was to evaluate the health quality of Arabica coffee seeds treated with different EOs during storage. For the Blotter health test, an experimental block design was adopted, with an 8 × 5 factorial, with six types of essential oil, a synthetic fungicide and a control, for five storage times (0, 3, 6, 9 and 12 months). After being treated, the seeds were packaged in plastic packaging (0.12 mm) and stored in a cold room (13 ±2 °C and 70% relative humidity) for up to 12 months. The genera of fungal flora associated with untreated seeds were Aspergillus, Cladosporium, Fusarium, Penicillium and Rhizopus, showing greater infestation than in seeds treated with OE and TECTO®. Essential oils from Rosmarinus officinalis, Cymbopogon citratus, Cymbopogon winterianus, Syzygium aromaticum, Eucalyptus globulus, and Melaleuca alternifolia partially controlled storage and field fungi in arabica coffee seeds, but were ineffective against Penicillium.

Delly Maulana, Catur Nugroho, Roro Retno Wulan et al.

The issue of waste in Indonesia and the global world is a crucial problem, and until now, it has not been resolved effectively and has not prioritized sustainable governance. Almost all regions are experiencing a handling crisis primarily from consumer waste, such as paper, food, electronics, plastics, metals, and packaging. This research aims to develop an effective waste management policy strategy at the municipal government level in Banten Province, Indonesia. Specifically, this research examines the strategy of changing people’s behavior through the perspective of social change behavior theory and rational-legal authority. This study employed a qualitative case-study approach, incorporating field observations, in-depth interviews, and focus group discussions. The findings indicate that waste management governance in Banten Province’s urban areas should operate optimally. The increasing waste production and the behavior of urban communities that still need to sort their waste have worsened waste management in the region. Therefore, there needs to be a policy strategy for waste management through changes in community behavior, which is implemented through promotion policies, campaigns, socialization, and educational activities for the community. Then, the city government should also provide clear waste bin facilities and management and consider individual preferences and local culture in changing people’s behavior in sustainable waste management.

Bartu Bisgin, Marwa Garsi, Andreas Welscher et al.

The increasing complexity of advanced semiconductor packages, driven by chiplet architectures and 2.5D/3D integration, challenges conventional failure localization methods such as lock-in thermography (LIT) and complicates current Failure Analysis (FA) workflows. Dense redistribution layers and buried interconnects limit the ability of established techniques to understand failure mechanisms non-destructively. In this work, we validate quantum diamond microscopy (QDM) based on nitrogen-vacancy (NV) centers in diamond as a non-destructive localization method through magnetic current path imaging at the package level. Using commercial Integrated Fan-Out Package-on- Package (InFO-PoP) devices from iPhones, we showcase a complete FA workflow that includes QDM to localize a short-type failure at an Integrated Passive Device (IPD) at the package backside. We showcase that the QDM results provide invaluable information on top of conventional techniques and can significantly enhance root-cause identification in package-level FA workflows. This work demonstrates the potential of QDM for broader integration into semiconductor chip and package analysis workflows.

Laetitia Bolte, Heiner Gers-Barlag, Guido Heinsohn et al.

Polyolefins such as high-density polyethylene (HDPE), low-density polyethylene (LDPE), and polypropylene (PP) are among the most widely used packaging materials in the cosmetic industry. Since these materials are in direct contact with cosmetic products, various components of the products are adsorbed to the packaging material’s surface and migrate within the amorphous regions of the polyolefin. This migration process, which occurs in both virgin and post-consumer recyclate (PCR) materials, can lead to deformation of the packaging. In this study, different types of virgin and PCR pellets were examined to investigate their interaction with cosmetic products and to understand the factors influencing the migration process. The migration of cosmetic oils was observed in all pellet samples, depending on the composition of the product and environmental conditions. The process was characterized by the weight gain of the plastic pellets and further identified through nuclear magnetic resonance (NMR) and infrared (IR) spectroscopy. Additionally, differential scanning calorimetry (DSC) and gel permeation chromatography (GPC) measurements were performed to analyze the polymer structure. Components with lower molecular weight (MW), high nonpolarity, and elevated temperatures were found to accelerate the migration process. Moreover, migration occurred more slowly from oil-in-water emulsions with larger droplet sizes compared to water-in-oil systems with smaller droplets. Among the different polyolefins, PP demonstrated a higher uptake of migrating components but at a slower migration rate compared to HDPE and LDPE. When comparing virgin and recycled polyolefins, it was observed that migration was consistently slower in virgin materials than in recycled ones. The ability of oils to migrate is influenced by the molecular structure of the polymers: high density, crystallinity, and low levels of branching reduce both the migration speed (MS) and the maximum saturation, as seen in virgin HDPE. In contrast, materials like LDPE, with a less dense polymer structure, exhibited higher MSs and saturation limits. As a control, polyethylene terephthalate (PET) was used, and it showed no migration due to the polymer’s high density.

Yingzhe Xiao, Qianxi Li, Zhen Zhang et al.

The development and application of virtual reality (VR) technology significantly enhances consumer immersion. Exploring a multi-sensory evaluation model for virtual packaging is valuable for integrating VR technology with packaging. This study developed a multi-sensory evaluation model for virtual packaging using the analytic hierarchy process (AHP). Eye-tracker experimentation was conducted to identify consumer attention indicators when interacting with virtual packaging. These indicators were quantified using Saaty’s nine-level importance scale and expert input, resulting in a comprehensive multi-sensory evaluation model. Subsequently, a VR shopping system focused on potato chips and cola as packaging design objects. This system was evaluated using the established model, and the results were analyzed. Based on the findings, improvements were made, and the system was re-evaluated using the modified model. The post-improvement evaluation demonstrated significantly enhanced sensory experiences. These results validate that the developed evaluation model effectively guides multi-sensory design approaches for packaging within a VR environment.

N. V. Kryvоruchkо, T. S. Kyrychenkо

Spreads are modern fat products whose production technology allows for a wide range of products with predefined properties. Having a similar texture and composition to natural butter, spreads contain more essential polyunsaturated fatty acids, and therefore exceed it in nutritional value. During the customs commodity expertise, it is important to identify the fatty product in order to provide reliable information to the consumer. For the customs identification of butter and spreads, the following differences may be taken into account: composition and origin, fat content and processing, emulsifiers and additional ingredients, low temperature hardness, purpose and use, labelling and packaging. The main identification tasks in the commodity expertise of these products are: product composition, detection of impurities, organoleptic characteristics, texture and consistency, chemical analysis, comparison with standards, determination of product origin. By performing these identification tasks, the expertise helps to ensure the quality and safety of products on the market and protects consumer rights. The article deals with the aspects of conducting a forensic commodity examination of butter and spreads, identifies certain aspects of falsification of the goods “butter” and “spread”, their identification and peculiarities of classification in the Ukrainian Classification of Goods for Foreign Economic Activity. The stages of forensic commodity examination of butter and spreads have been provided. General recommendations on the commodity assessment of the quality of these products for consumers and expert organisations have been identified.

Frank Reyes, Federico Bono, Aman Sharma et al.

Java projects frequently rely on package managers such as Maven to manage complex webs of external dependencies. While these tools streamline development, they also introduce subtle risks to the software supply chain. In this paper, we present Maven-Hijack, a novel attack that exploits the order in which Maven packages dependencies and the way the Java Virtual Machine resolves classes at runtime. By injecting a malicious class with the same fully qualified name as a legitimate one into a dependency that is packaged earlier, an attacker can silently override core application behavior without modifying the main codebase or library names. We demonstrate the real-world feasibility of this attack by compromising the Corona-Warn-App, a widely used open-source COVID-19 contact tracing system, and gaining control over its database connection logic. We evaluate three mitigation strategies, such as sealed JARs, Java Modules, and the Maven Enforcer plugin. Our results show that, while Java Modules offer strong protection, the Maven Enforcer plugin with duplicate class detection provides the most practical and effective defense for current Java projects. These findings highlight the urgent need for improved safeguards in Java's build and dependency management processes to prevent stealthy supply chain attacks.

Kantiya Petsong, Pensiri Kaewthong, Passakorn Kingwascharapong et al.

Abstract The aim of this study was to investigate the impact of jackfruit inner skin fibre (JS) incorporated with whey protein isolate (WPI) and soybean oil (SO) as a wall material for probiotic encapsulation to improve probiotic stability against freeze-drying and gastrointestinal (GI) tract conditions. Bifidobacterium bifidum TISTR2129, Bifidobacterium breve TISTR2130, and Lactobacillus acidophilus TISTR1338 were studied in terms of SCFA production and the antibiotic-resistant profile and in an antagonistic assay to select suitable strains for preparing a probiotic cocktail, which was then encapsulated. The results revealed that B. breve and L. acidophilus can be used effectively as core materials. JS showed the most influential effect on protecting probiotics from freeze-drying. WPI:SO:JS at a ratio of 3.9:2.4:3.7 was the optimized wall material, which provided an ideal formulation with 83.1 ± 6.1% encapsulation efficiency. This formulation presented > 50% probiotic survival after exposure to gastro-intestinal tract conditions. Up to 77.8 ± 0.1% of the encapsulated probiotics survived after 8 weeks of storage at refrigeration temperature. This study highlights a process and formulation to encapsulate probiotics for use as food supplements that could provide benefits to human health as well as an alternative approach to reduce agricultural waste by increasing the value of jackfruit inner skin.

ZHANG Yu, CHEN Lei

Taking the display design research on traditional festival food's packaging as a point of penetration, this paper discusses about its display features and way of expression in the context of cultural confidence. At first, the paper analyses and summarizes traditional festival food packaging's current situation. Then, it concludes the display features of traditional festival food packaging's design throughout elucidating its concept. Finally, it probes into the packaging display design's expression way. Traditional festival food's packaging should comply with the tendency of today's aesthetic idea and the consumer development. The packaging's display design features could be started with its way of telling, scene being produced and interaction with consumer. In the display, packaging's theme, way of telling and design strategy should be considered. It should emphasize the atmosphere being produced when the packaging is opened, and focus on consumer's interactive experience on visual and tactile aspects and with AR technology. In opening the packaging, it should help consumer gradually understand Chinese traditional festival and customs, and thus enhance their cultural confidence.

Adamya Shyam, Vikas Kumar, Venkateswara Rao Kagita et al.

Recommender systems aim to enhance the overall user experience by providing tailored recommendations for a variety of products and services. These systems help users make more informed decisions, leading to greater user engagement with the platform. However, the implementation of these systems largely depends on the context, which can vary from recommending an item or package to a user or a group. This requires careful exploration of several models during the deployment, as there is no comprehensive and unified approach that deals with recommendations at different levels. Furthermore, these individual models must be closely attuned to their generated recommendations depending on the context to prevent significant variation in their generated recommendations. In this paper, we propose a novel unified recommendation framework that addresses all four recommendation tasks, namely, personalized, group, package, and package-to-group recommendation, filling the gap in the current research landscape. The proposed framework can be integrated with most of the traditional matrix factorization-based collaborative filtering (CF) models. This research underscores the significance of including group and package information while learning latent representations of users and items for personalized recommendations. These components help in exploiting a rich latent representation of the user/item by enforcing them to align closely with their corresponding group/package representation. We consider two prominent CF techniques, namely Regularized Matrix Factorization and Maximum Margin Matrix factorization, as the baseline models and demonstrate their customization to various recommendation tasks. Experimental results on two publicly available datasets are reported, comparing them to other baseline approaches for various recommendation tasks.

Abbas Javan Jafari, Diego Elias Costa, Emad Shihab et al.

Managing project dependencies is a key maintenance issue in software development. Developers need to choose an update strategy that allows them to receive important updates and fixes while protecting them from breaking changes. Semantic Versioning was proposed to address this dilemma but many have opted for more restrictive or permissive alternatives. This empirical study explores the association between package characteristics and the dependency update strategy selected by its dependents to understand how developers select and change their update strategies. We study over 112,000 npm packages and use 19 characteristics to build a prediction model that identifies the common dependency update strategy for each package. Our model achieves a minimum improvement of 72% over the baselines and is much better aligned with community decisions than the npm default strategy. We investigate how different package characteristics can influence the predicted update strategy and find that dependent count, age and release status to be the highest influencing features. We complement the work with qualitative analyses of 160 packages to investigate the evolution of update strategies. While the common update strategy remains consistent for many packages, certain events such as the release of the 1.0.0 version or breaking changes influence the selected update strategy over time.

Rajesh K. Ahluwalia, Xiaohua Wang, Dionissios D. Papadias et al.

The main objective of this work was to investigate the potential of hydrogen and fuel cells replacing diesel and internal combustion engines in the ultraclass haul trucks deployed in the mining sector. Performance, range, durability, and cost are the main criteria considered for comparing the two fuels and engine options. Fuel cell system (FCS) performance is characterized in terms of heat rejection, efficiency, and fuel consumption for a hybrid platform equivalent to a 3500 hp diesel engine operating on a representative open pit mining duty cycle. A hybrid platform was chosen because the heat rejection, with a constrained radiator frontal area, limits the maximum fuel cell-rated power by about 50% compared to that of the diesel truck. The hybrid powertrain was 81–88% more efficient than the diesel powertrain on the truck duty cycle. A liquid hydrogen storage system is required for an equal range or time between refilling, but the packaging remains a challenge. Fuel cell and battery durability were evaluated for their performance degradation and lifetime. Achieving a fuel cell lifetime comparable to the time between major overhauls for diesel trucks necessitates the oversizing of the membrane-active area, catalyst overloading, and voltage clipping. For an equal lifetime, the battery must be oversized to control its depth of discharge and charge/discharge rates. A total cost of ownership (TCO) analysis considering the initial capital expenditures, as well as the lifetime cost of fuel, operation, and maintenance, indicates that fuel cells and hydrogen can compete with diesel. A breakeven fuel cost for TCO parity is obtained if H₂ is available at USD 5.79–6.85/kg vs. diesel at USD 3.25/gal and the FCS-specific cost is USD 323/kW_e relative to USD 250/kW for a diesel genset. Volume manufacturing is required for FCS cost reduction. High volume is possible through the standardization, modularity, and proliferation of class 8 long-haul truck systems across different heavy-duty applications.

Shenghong Ye, Haoyun Yan, Zhengyu Lin et al.

Consumers often feel embarrassed when buying products like condoms, hemorrhoid cream, and beriberi cream in crowded pharmacies. There is an interesting phenomenon in life: Some beriberi creams use the images of a “real foot”, while others use the images of a “cartoon foot.” Imagine if a young woman needed to go to a retail store for beriberi cream that would embarrass her, she would choose a “real foot image” or a “cartoon foot image” beriberi cream? It has been shown that the embarrassment of these products has a strong negative impact on consumer buying behavior. Previous researches have explored how changing packaging elements of embarrassing products (e.g., color/design/image placement) can effectively reduce consumer embarrassment. However, few have examined the impact of different image types of embarrassing product packaging (artificial vs. natural) with embarrassment. Therefore, this research explores the effect of image types (artificial vs. natural) on consumers’ willingness to purchase embarrassing products and reveals the mechanisms of the underlying effects. The results show that natural images can lead to lower purchase intention of embarrassing products when the advertisement uses first-person pronouns due to the mediating role played by negative body imagery. However, there is no significant difference in purchase intention between different image types in the third-person pronouns. Finally, this paper discusses its contributions and limitations.

Yuting XIA, Fei XIANG, Kao WU et al.

Konjac glucomannan is a natural polymer with a wide range of sources, low price, excellent film-forming, biocompatibility, degradability and renewability. In many researches on composite materials based on konjac glucomannan, konjac glucomannan-based antibacterial active packaging film has received extensive attention and shown broad application prospects in the field of food packaging. In this paper, the structure and properties of konjac glucomannan and the preparation method of the composite film, as well as the preparation, functional properties and the research progress of antibacterial active packaging film based on konjac glucomannan are reviewed.

Christian Julien Isac Gnimadi, Michael Aboah, Kokoutse Gawou

One of the major plastic pollution problems is the understanding of the ideology underpinning their disposal. Consequently, this research aims at evaluating the factors that influence respondents’ decisions on managing their plastic waste and investigate respondents’ awareness of the health and safety issues associated with inappropriate plastic waste disposal. This research used a descriptive design. 360 individuals were randomly selected in three districts within the Cape Coast Metropolis. The data collection instrument was a structured questionnaire. The results showed that the influential factors listed according to the decreasing value of factor loading are the idea that municipal authorities’ inadequate collection of wastes, lack of education, notion that plastics are more durable than paper, the long distances of the individual to a dustbin, the lack of information on the alternatives to reduce plastic waste, the increased number of people living in the area, the high amount of plastic packaging, the lack of adequate information on proper methods to dispose of plastic waste, the attitudinal problems, the lack of infrastructure for recycling the plastic waste and the weak enforcement of existing bye-laws on sanitation. The factor loading values are 0.84, 0.82, 0.80, 0.72 ,0.71, 0.68, 0.67, 0.66, 0.64, 0.61, 0.58 respectively.

Andreas Nordland, Klaus K. Holst

The R package polle is a unifying framework for learning and evaluating finite stage policies based on observational data. The package implements a collection of existing and novel methods for causal policy learning including doubly robust restricted Q-learning, policy tree learning, and outcome weighted learning. The package deals with (near) positivity violations by only considering realistic policies. Highly flexible machine learning methods can be used to estimate the nuisance components and valid inference for the policy value is ensured via cross-fitting. The library is built up around a simple syntax with four main functions policy_data(), policy_def(), policy_learn(), and policy_eval() used to specify the data structure, define user-specified policies, specify policy learning methods and evaluate (learned) policies. The functionality of the package is illustrated via extensive reproducible examples.

A. H. M. Nazmus Sakib, Promit Basak, Syed Doha Uddin et al.

Skeleton-based Motion Capture (MoCap) systems have been widely used in the game and film industry for mimicking complex human actions for a long time. MoCap data has also proved its effectiveness in human activity recognition tasks. However, it is a quite challenging task for smaller datasets. The lack of such data for industrial activities further adds to the difficulties. In this work, we have proposed an ensemble-based machine learning methodology that is targeted to work better on MoCap datasets. The experiments have been performed on the MoCap data given in the Bento Packaging Activity Recognition Challenge 2021. Bento is a Japanese word that resembles lunch-box. Upon processing the raw MoCap data at first, we have achieved an astonishing accuracy of 98% on 10-fold Cross-Validation and 82% on Leave-One-Out-Cross-Validation by using the proposed ensemble model.

Wentao Lei, Mingming Fan, Juliann Thang

With about 230 million packages delivered per day in 2020, fetching packages has become a routine for many city dwellers in China. When fetching packages, people usually need to go to collection sites of their apartment complexes or a KuaiDiGui, an increasingly popular type of self-service package pickup machine. However, little is known whether such processes are accessible to blind and low vision (BLV) city dwellers. We interviewed BLV people (N=20) living in a large metropolitan area in China to understand their practices and challenges of fetching packages. Our findings show that participants encountered difficulties in finding the collection site and localizing and recognizing their packages. When fetching packages from KuaiDiGuis, they had difficulty in identifying the correct KuaiDiGui, interacting with its touch screen, navigating the complex on-screen workflow, and opening the target compartment. We discuss design considerations to make the package fetching process more accessible to the BLV community.

Davide Dalle Pezze, Denis Deronjic, Chiara Masiero et al.

Continual Learning aims to learn from a stream of tasks, being able to remember at the same time both new and old tasks. While many approaches were proposed for single-class classification, multi-label classification in the continual scenario remains a challenging problem. For the first time, we study multi-label classification in the Domain Incremental Learning scenario. Moreover, we propose an efficient approach that has a logarithmic complexity with regard to the number of tasks, and can be applied also in the Class Incremental Learning scenario. We validate our approach on a real-world multi-label Alarm Forecasting problem from the packaging industry. For the sake of reproducibility, the dataset and the code used for the experiments are publicly available.