Predictive analytical modeling of cutting forces generated by high-speed machining of ductile and hard metals

This paper proposes an analytical cutting forces model based on an extension of the Oxley's machining theory (OMT) to high-speed machining of ductile and hard metals. In this model, the materials' behavior was modeled using the Marusich's constitutive equation (MCE). Furthermore, The OMT was modified to be able to capture the effects of the cutting tool edge radius and the burnishing phenomenon by implementing a variable rake angle equation and the Briks criterion, respectively. The predictive model was validated using experimental data obtained during the orthogonal machining of two aluminum alloys (AA6061-T6 and AA7075-T651) and induction-hardened AISI4340 steel (58-60 HRC). The results showed that the predicted and experimental cutting forces were in reasonable agreement for all tested materials. The strain rate constant in the primary shear zone (C₀) was found to be significantly sensitive to the cutting conditions and work material, and its effect on the predicted data was highlighted and discussed in depth. On one hand, it was found that AA6061-T6 is less sensitive to the strain rate compared to the AA7075-T651. On the other hand, all tested materials were found to be more sensitive to the strain rate at low cutting speeds and/or cutting feeds.     

Optimal business process deployment cost in cloud resources

Cloud computing is the fastest emerging technology that proposes several resources under various pricing strategies that are specified based on temporal constraints. The main aim of cloud computing is to enhance the performance level and minimize operating costs. Thus, organizations looking towards optimizing their spending on IT infrastructure find such pricing strategies very attractive, especially, to deploy their business process models. However, discovering the optimal deployment cost of a business process in cloud resources proposed under various pricing strategies becomes a highly challenging problem. So, the objective of the present paper is to present an approach that assists business process designers in finding an optimal assignment or scheduling based on the variety of pricing strategies. We use linear programming models with an objective function under a set of constraints. Besides, we propose an extension of the famous cloud simulator provided in the market, CloudSim, to simulate the cloud resources consumed to deploy a business process model. The experimental results show the feasibility, effectiveness, and performance of our approach.

     

Regioregular poly(3‐alkylthiophenes): Synthesis,characterization, and application in conductive fabrics

Poly(3‐dodecylthiophene) (P3DDT) and poly(3‐decylthiophene) (P3DT) with high contents of head‐to‐tail linkages (86 and 85%, respectively) were synthesized in high yields by a facile oxidative polymerization with ferric chloride in chloroform at room temperature. We believe that the low concentration and ultraslow addition of monomers to ferric chloride contributed to the high regioregularity. Differential scanning calorimetry thermograms indicated that the formed polymers consisted of crystalline, quasiordered, and disordered phases, which is a common feature of highly regioregular polymers. We prepared conductive fabrics with specific resistance of 30 and 100 Ω/sq by impregnating polyamide fabrics in a chloroform solution of P3DDT and P3DT, respectively. © 2004 Wiley Periodicals, Inc. J Appl Polym Sci 93: 2131–2135, 2004     

Continuous aggregate nearest neighbor queries

This paper addresses the problem of continuous aggregate nearest-neighbor (CANN) queries for moving objects in spatio-temporal data stream management systems. A CANN query specifies a set of landmarks, an integer k, and an aggregate distance function f (e.g., min, max, or sum), where f computes the aggregate distance between a moving object and each of the landmarks. The answer to this continuous query is the set of k moving objects that have the smallest aggregate distance f. A CANN query may also be viewed as a combined set of nearest neighbor queries. We introduce several algorithms to continuously and incrementally answer CANN queries. Extensive experimentation shows that the proposed operators outperform the state-of-the-art algorithms by up to a factor of 3 and incur low memory overhead.     

Visual audience gatekeeping on social media platforms: A critical investigation on visual information diffusion before and during the Russo–Ukrainian War

Gatekeepers, including prerogative elites and institutions, possess multifaceted tools for controlling information. Historically, these gatekeepers have systematically instrumentalized visual information to shape audience perceptions in alignment with specific agendas. However, the advent of social media platforms has disrupted these power dynamics, empowering audiences through user-driven visual information exchanges. This has led to visual audience gatekeeping whereby users act as audience gatekeepers by selectively disseminating visual content, thus shaping information diffusion. While this democratisation of gatekeeping holds considerable promise for user empowerment, it also presents risks. These risks stem from the inherently persuasive yet manipulative qualities of visual content, compounded by users' susceptibility to unconscious biases, especially during polarising events. Therefore, we critically investigated visual audience gatekeeping in the context of the Russo–Ukrainian War, specifically focusing on a Reddit subforum devoted to Russia-related discussions. We find that visual audience gatekeeping operates within a paradigm that reflects the social reality the audience embraces. Audience gatekeepers disseminate visual information both to reproduce and defend an idealised conception of this social reality. Collectively, they produce a visual echo chamber characterised by low information diversity, which, in turn, reinforces and perpetuates the incumbent paradigm. However, heightened social tensions can trigger a paradigm shift and amplify the reproduction and defence processes, increasing the potential for the diffusion of more radical and extreme visual narratives. Based on our findings, we propose a theoretical model of visual audience gatekeeping, which has important implications for research on visuals, gatekeeping and social media platforms.     

Similarity queries: their conceptual evaluation, transformations, and processing

Many application scenarios can significantly benefit from the identification and processing of similarities in the data. Even though some work has been done to extend the semantics of some operators, for example join and selection, to be aware of data similarities, there has not been much study on the role and implementation of similarity-aware operations as first-class database operators. Furthermore, very little work has addressed the problem of evaluating and optimizing queries that combine several similarity operations. The focus of this paper is the study of similarity queries that contain one or multiple first-class similarity database operators such as Similarity Selection, Similarity Join, and Similarity Group-by. Particularly, we analyze the implementation techniques of several similarity operators, introduce a consistent and comprehensive conceptual evaluation model for similarity queries, and present a rich set of transformation rules to extend cost-based query optimization to the case of similarity queries.     

A household’s power load response to a change in the electricity pricing scheme: An expanded microeconomic-physical approach

Energy economists are interested in how changes in electricity prices prompt a response in end-user electricity demand. If historical prices are low or seldom change, it becomes difficult to estimate price elasticities statistically, especially in the short-run. Thus, a framework that merges the physical equations that govern how electricity is consumed, and a utility-maximizing household the responds to varying expenditures on electricity, is used.We have parameterized the physical component to a house in Saudi Arabia. Three electricity pricing schemes are analyzed: progressive tariffs, time-of-use prices, and real-time prices. We show that for a household with a low preference for electricity, slight price increases do warrant adjustment in indoor temperature in the hot summer months and lower consumer electronics use. Since we adopt a dwelling in Saudi Arabia, the response measure that is most exercised is the thermostat set-point adjustment. A subdued response is found for households that have adopted higher energy efficiency, or have high preference for electricity.