Recommender systems suggest items of interest to users based on their preferences. These preferences are typically generated from user ratings of the items. If there are no ratings for a certain user or item, it is said that there is a cold start pro...
Successful and rapid startup of proton exchange membrane fuel cells (PEMFCs) at subfreezing temperatures (also called cold start) is of great importance for their commercialization in automotive and portable devices. In order to maintain good proton...
We added microencapsulated phase change materials (MPCMs) into the homemade antifreeze fluid to take advantage of the latent heat of phase change materials, and explored the possibility of solving the cold start problem of proton exchange membrane fu...
Presented in this paper is an in-depth analysis of the impact of engine start during various stages of engine warm up (cold, intermediate, and hot start stages) on the performance and emissions of a heavy-duty diesel engine. The experiments were perf...
This paper studies the problem of cold-start recommendation with graph contrastive learning. Graph contrastive learning has achieved state-of-the-art performance for the recommendation. However, it lacks robustness in cold-start scenarios due to nois...
Reducing diesel engine emissions under cold start conditions has become much more valuable as environmental issues become more important. Regarding diesel engine emissions under cold start conditions, this review summarizes the emission mechanisms an...
In this study, the cold-start process of a polymer electrolyte fuel cell has been numerically investigated under various ambient temperatures and operating currents, ranging from subzero to 283 K. The water desorbed from the electrolyte, when the cel...
With the rise of online advertising, e-commerce industries, and new media platforms, recommendation systems have become an essential product form that connects users with a vast number of candidates. A major challenge in recommendation systems is the...
The cold-start problem has always been a key challenge in the recommendation research field. As a popular method to learn a learner that can rapidly adapt to a new task through a small number of updates, meta-learning is considered to be a feasible a...
The cold-start problem remains a significant challenge in recommendation systems, particularly in scenarios involving new users or items with insufficient historical interaction data, which severely limits the effectiveness of personalised recommenda...
Decentralized power generation by combined heat and power plants becomes increasingly popular as a measure to advance the energy transition. In this context, a substantial advantage of small combined heat and power plants is based on the relatively l...
This article analyzes the influence of the ignition retardation on the fuel consumption, the cumulative tailpipe hydrocarbon emissions, and the temperature inside the three-way catalytic converter in a gasoline direct injection engine operated under...
Dynamic scheduling can improve the latency and memory efficiency of deep neural network inference on edge devices, but it often introduces cold-start overhead when a newly deployed model requires online profiling and policy adaptation before reaching...
Recommender systems are tools that help users in the decision-making process of choosing items that may be relevant for them among a vast amount of other items. One of the main problems of recommender systems is the cold start problem, which occurs w...
Traditional recommendation models grapple with challenges such as the scarcity of similar user or item references and data sparsity, rendering the cold-start problem particularly formidable. Meta-learning has emerged as a promising avenue to address...
22 November 2024
The primary functions of an energy harvesting system include the harvesting, transformation, management, and storage of energy. Until now, various types of energy, with different power levels, have been harvested and stored by the energy harvesting s...
With the emergence of cloud-native computing, serverless computing has become a popular way to deploy intensive applications due to its scalability and flexibility, and it has been increasingly applied in the field of big data processing on service p...
During the cold-start process of a PEMFC, the supply of air and hydrogen in the gas supply system has a great influence on the cold-start performance. The cold-start of a PEMFC is a complex nonlinear coupling process, and the traditional control stra...
The cold start property is one of the main factors restricting the fuel cell application in the automotive field. The constant voltage cold start method of the fuel cell works under low start voltage and produces high heat, which can shorten the star...
The cold-start problem in sequence recommendations presents a critical and challenging issue for portable sensing devices. Existing content-aware approaches often struggle to effectively distinguish the relative importance of content features and typ...
The cold start of fuel cells limits their wide application. Since the water produced by fuel cells takes up more space when it freezes, it may affect the internal structure of the stack, causing collapse and densification of the pores inside the cata...
Personalized recommender systems have become essential in modern e-commerce by improving product discovery and enhancing user experience. However, recommendation performance is often limited by sparse user–item interactions and cold-start scena...
This paper proposes an ultra-low voltage delay element for battery-assistance DC energy harvesting systems. By inserting a low voltage level shifter (VLS), a wider voltage range is obtained to bias the body of the delay element. Thus, both the voltag...
This paper addresses the thermal management of a solid polymer electrolyte battery system, which is currently the only commercialized solid-state battery chemistry. These batteries aim to increase the range of electric vehicles by facilitating a lith...
With the widespread adoption of diesel engine technology, the problem of pollutant emissions has become increasingly prominent. Especially in the cold start stage of the diesel engine, the instantaneous pollutant emissions may be several times or eve...
Combining drugs, a phenomenon often referred to as polypharmacy, can induce additional adverse effects. The identification of adverse combinations is a key task in pharmacovigilance. In this context, in silico approaches based on machine learning are...
Gas components, like carbon monoxide (CO) and dioxide (CO2), can be measured on a wet- or dry-basis depending on whether the water is left or removed from the sample before analysis. The dry concentrations of gaseous components in the exhaust from in...
Cold start is one of the major issues that hinders the commercialization of polymer electrolyte membrane fuel cells (PEMFCs). In this study, a 2D transient multi-physics model is developed to simulate the cold start processes in a PEMFC. The phase ch...
Subzero automotive cold-starts of proton exchange membrane fuel cell (PEMFC) stacks require accelerated thermal rises to achieve nominal operating conditions and close-to-instantaneous usable output power. Advances in the material, structure and oper...
2 September 2025
In today’s world, with rapidly developing technology, it has become possible to perform many transactions over the internet. Consequently, providing better service to online customers in every field has become a crucial task. These advancements...
Item-based collaborative filtering is one of the most popular techniques in the recommender system to retrieve useful items for the users by finding the correlation among the items. Traditional item-based collaborative filtering works well when there...
This paper proposes an on−chip, ultra−low−power cold−start circuit for a low−voltage, fast start−up of a boost converter for autonomous thermal energy harvesting from slight temperature differences. An improved cha...
This paper focuses on the new users cold-start issue in the context of recommender systems. New users who do not receive pertinent recommendations may abandon the system. In order to cope with this issue, we use active learning techniques. These meth...
Recommender systems aim to forecast users’ rank, interests, and preferences in specific products and recommend them to a user for purchase. Collaborative filtering is the most popular approach, where the user’s past purchase behavior cons...
In order to realize the low temperature and rapid cold start-up of a proton exchange membrane fuel cell stack, a dynamic model containing 40 single proton exchange membrane fuel cells is established to estimate the melting time of the proton exchange...
The cold-start problem remains a critical challenge in personalized advertising, where users with limited or no interaction history often receive suboptimal recommendations. This study introduces a novel, three-stage framework that systematically int...
A domain that has gained popularity in the past few years is personalized advertisement. Researchers and developers collect user contextual attributes (e.g., location, time, history, etc.) and apply state-of-the-art algorithms to present relevant ads...
Personalized recommender systems are used not only in e-commerce companies but also in various web applications. These systems conventionally use collaborative filtering (CF) and content-based filtering approaches. CF operates using memory-based or m...
Recommender system (RS) can be used to provide personalized recommendations based on the different tastes of users. Item-based collaborative filtering (IBCF) has been successfully applied to modern RSs because of its excellent performance, but it is...
Proton Exchange Membrane Fuel Cells (PEMFCs) are highly valued for their zero emissions, low noise, and environmentally friendly characteristics. However, they face substantial difficulties when starting up in low-temperature conditions. Coolant-assi...
This paper presents an innovative thermally coupled system architecture with a parallel coolant-heated metal hydride tank (MHT) designed to satisfy the hydrogen supply requirements of proton exchange membrane fuel cell s(PEMFCs). This design solves a...
In light of the indispensable role of diesel engines in critical sectors such as heavy transportation, agricultural machinery, and shipping and the gradual depletion of fossil fuels, the strategic value of blended fuels has become increasingly promin...
Rapid heating strategies are essential for the cold-start of lithium-ion batteries at subzero temperatures to avoid severe performance losses. This study explores different external and battery-powered heating strategies and evaluates the time requir...
When new purchasers or products are added in the supply chain management system, the recommendation system will face severe challenges of data sparsity and cold start. A knowledge graph that can enrich the representations of both procurement managers...
In this study, the cold-start failure processes of a polymer electrolyte fuel cell have been investigated numerically for different initial membrane water content
Nowadays, recommendation systems have been successfully adopted in variant online services such as e-commerce, news, and social media. The recommenders provide users a convenient and efficient way to find their exciting items and increase service pro...
Recommender systems position themselves as powerful tools in the support of relevance and personalization, presenting remarkable potential in the area of marketing. The cold-start customer problematic presents a challenge within this topic, leading t...
How to effectively predict outcomes when initial time series data are limited remains unclear. This study investigated the efficiency of Bayesian model selection to address the lack of initial data for time series analysis, particularly in cold-start...
(1) Background: Cancer drug resistance can be influenced by microRNAs (miRNAs), which can alter gene expression and cellular pathways that determine how cancer cells respond to treatment. Potential miRNA–drug response associations can be identi...
Computerized adaptive testing (CAT) systems face major challenges at the beginning of test administration, when limited response data produces unstable ability estimates and poor item selection. This cold-start problem reduces measurement precision a...
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