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It is commonly assumed that data volume and network energy consumption are directly proportional, a notion perpetuated by numerous studies and media coverage. This paper challenges this assumption, offering a comprehensive examination of network operations to explain why the relationship between energy consumption and data volume is nonlinear. The power model approach is explored as an alternative methodology for calculating network energy consumption providing a more reliable representation of network energy use. The power model demonstrates that simple energy intensity calculations, expressed as kilowatt hours per gigabyte of data, are insufficient for accurately estimating real‐world network energy consumption. [ABSTRACT FROM AUTHOR]

The paper examines traditional knowledge about the role of financial and physical resources in entrepreneurship. Based on Bourdieu's theory, we search for an answer to the question of which forms of economic capital are used by Croatian entrepreneurs in the computer programming industry and what their value in the context of accessing other forms of capital is. The study is based on a qualitative methodological approach. In-depth interview technique accompanied by unstructured observations was used in data collection. In addition to primary data, research includes the use of qualitative and quantitative secondary data. Research suggests that in the computer programming industry, economic capital is just one tool in the conversion game of entrepreneurial capital. Moreover, the interviewed entrepreneurs attach the least importance to it in business, favoring the value of intangible resources such as specialized knowledge, business connections and personal acquaintances. The company's start-up phase is characterized by the entrepreneur's reliance on personal savings, which is replaced by financing based on retained earnings in the later stages of business. Other forms of growth financing, such as bank loans and recapitalization of external investors, are used by a minority of larger companies, with a good base of symbolic capital. The results on capital conversions indicate relatively easy conversion of economic capital into cultural capital and symbolic capital, and less frequent use of economic capital to create social capital. Fresh insights into the entrepreneurs' perceptions provided by the study expand existing knowledge about entrepreneurship within the computer programming industry, suggesting that it is an industry with huge potential for young talents without a personal financial base that is commonly considered a precondition for entering entrepreneurship. [ABSTRACT FROM AUTHOR]

The study consists of an unreliable multiserver retrial queue with feedback where clients may resist to join the orbit and the service provider is erratic. In this model we have considered c service providers at a time and if all the c servers are busy, the incoming clients wait in the retrial orbit. The model is unfolded using Matrix Geometric Method (MGM) to obtain the rate matrix and stationary probabilities. The system with retrials is modelled and the performance measures and reliability indices are procured. These derived quotients are then visualised and validated with the help of tables and graphs. Further, the cost analysis of the model is carried out and the optimal cost for the system is obtained using Particle Swarm Optimization (PSO) algorithm for matrix method. The optimal repair and retrial rates are obtained using PSO technique which helps the computer and manufacturing industry to work towards better decision policies. [ABSTRACT FROM AUTHOR]

The financial system, a complex network, operates primarily through the exchange of capital, where the role of information is critical. This study utilizes the transfer entropy method to examine the strength and direction of information flow among different capital flow time series and investigate the community structure within the transfer networks. Moreover, the spreading dynamics of the capital flow transfer networks are observed, and the importance and traveling time of each node are explored. The results imply a dominant role for the food and drink industry within the Chinese market, with increased attention towards the computer industry starting in 2014. The community structure of the capital flow transfer networks significantly differs from those constructed from stock prices, with the main sector predominantly encompassing industry leaders favored by primary funds with robust capital flow connections. The average traveling time from sectors such as food and drink, coal, and utilities to other sectors is the shortest, and the dynamic flow between these sectors displays a significant role. These findings highlight that comprehension of information flow and community structure within the financial system can offer valuable insights into market dynamics and help to identify key sectors and companies. [ABSTRACT FROM AUTHOR]

Industrial defect detection is a hot topic in the field of computer vision and industry. Industrial defects are diverse and complex, and well‐known machine learning based methods can often not effectively extract features of industrial defects and achieve good detection results. To address the above problems, this paper introduces a deep learning model for industrial defect detection. First, a two‐branch decoupled head, which can facilitate model training through separating the prediction of category and regression is designed. Also, two inverted bottleneck structures are designed to enhance the ability of the model to extract features. Moreover, an attention‐enhanced feature fusion (AEFF) module is designed and integrated into the neck network to achieve effective feature fusion. Extensive experiments are conducted on three public datasets, namely the DeepPCB dataset, NEU‐DET dataset, and NRSD‐MN dataset. The obtained results demonstrate that the proposed model achieves competitive results compared to the state‐of‐the‐art methods. The proposed model achieves mAP@0.5:0.95, 71.78%, 36.04%, and 48.69% on the PCB dataset, NEU‐DET dataset, and the NRSD‐MN dataset, respectively. [ABSTRACT FROM AUTHOR]

Managing the continuous and fast-growing volume of information, the progress in the Internet-of-Things, and the evolution from digitalization to networking are huge technological chores. Si-based integrated chips face increasing demands as they strive to meet these challenges. However, there is growing recognition that information processing and computing based on molecules performing logic operations may play a decisive role in shaping the future of the computer industry. Molecular logic gates are molecular counterparts of electronic devices that, instead of exclusively by electrical signals, can be stimulated by diverse chemical or physical input signals that produce optical outputs according to a well-defined logical transfer function. Several materials have been applied for molecular logic, however, the Ln3+-based ones appear to be a commendable choice, as they can respond to both chemical and physical stimuli, presenting unique photophysical properties that make them quite popular for photonics applications. Here we critically review illustrative molecular logic systems based on Ln3+ ions and discuss their potential for integration in future molecular photonic–electronic hybrid logic computing systems. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this study is to explore the potential and growth of big data across several industries between 2016 and 2020. This study aims to analyze the behavior of interest in big data within the community and to identify areas with the greatest potential for future big data adoption. Design/methodology/approach: This research uses Google Trends to characterize the community's interest in big data. Community interest is measured on a scale of 0–100 from weekly observations over the past five years. A total of 16 industries were considered to explore the relative interest in big data for each industry. Findings: The findings revealed that big data has been of high interest to the community over the past five years, particularly in the manufacturing, computers and electronics industries. However, over the 2020s the interest in the theme decreased by more than 15%, especially in the areas where big data typically had the greatest potential interest. In contrast, areas with less potential interest in big data such as real estate, sport and travel have registered an average growth of less than 10%. Originality/value: To the best of the author's knowledge, this study is original in complementing the traditional survey approaches launched among the business communities to discover the potential of big data in specific industries. The knowledge of big data growth potential is relevant for players in the field to identify saturation and emerging opportunities for big data adoption. [ABSTRACT FROM AUTHOR]

Canada has just enacted legislation to give the broadcast regulator, the Canadian Radiotelevision and Telecommunications Commission (CRTC), authority to regulate online streaming platforms, both domestic and international. This legislation, known as Bill C-11 as it passed through an extensive parliamentary review process, was highly controversial. The bill empowers the CRTC to review and possibly amend the definition of “Canadian content.” It will also require that streaming services contribute financially to the production of Canadian content and will impose “discoverability” requirements on digital streaming platforms (like YouTube, Spotify, Netflix and others) to ensure that Canadian content is promoted. The CRTC will have broad leeway to issue and enforce regulations to achieve these ends. The U.S. high-tech and streaming industry does not like this legislation and has used various tactics to oppose it. Among these are arguments that C-11 violates commitments that Canada made to the United States in the Canada-U.S.-Mexico Agreement (CUSMA), the replacement for NAFTA, and that implementation of C-11 will result in U.S. trade retaliation. This paper analyzes the arguments to this effect put forth by the U.S. tech industry’s trade association, the Computer & Communications Industry Association (CCIA), and refutes them, particularly the argument that Canada will need to invoke CUSMA Article 32.6 (the cultural exception clause) to justify its actions. At the same time, the paper cautions that the CRTC needs to be careful with respect to imposing a requirement on foreign streamers to contribute to Canadian production if at the same time it denies them the ability to acquire and exploit the production they have helped finance when no such limitation is imposed on equivalent Canadian streaming services. [ABSTRACT FROM AUTHOR]

The benefits and opportunities offered by cloud computing are among the fastest-growing technologies in the computer industry. Additionally, it addresses the difficulties and issues that make more users more likely to accept and use the technology. The proposed research comprised of machine learning (ML) algorithms is Naïve Bayes (NB), Library Support Vector Machine (LibSVM), Multinomial Logistic Regression (MLR), Sequential Minimal Optimization (SMO), K Nearest Neighbor (KNN), and Random Forest (RF) to compare the classifier gives better results in accuracy and less fault prediction. In this research, the secondary data results (CPU-Mem Mono) give the highest percentage of accuracy and less fault prediction on the NB classifier in terms of 80/20 (77.01%), 70/30 (76.05%), and 5 folds cross-validation (74.88%), and (CPU-Mem Multi) in terms of 80/20 (89.72%), 70/30 (90.28%), and 5 folds cross-validation (92.83%). Furthermore, on (HDD Mono) the SMO classifier gives the highest percentage of accuracy and less fault prediction fault in terms of 80/20 (87.72%), 70/30 (89.41%), and 5 folds cross-validation (88.38%), and (HDD-Multi) in terms of 80/20 (93.64%), 70/30 (90.91%), and 5 folds cross-validation (88.20%). Whereas, primary data results found RF classifier gives the highest percentage of accuracy and less fault prediction in terms of 80/20 (97.14%), 70/30 (96.19%), and 5 folds cross-validation (95.85%) in the primary data results, but the algorithm complexity (0.17 seconds) is not good. In terms of 80/20 (95.71%), 70/30 (95.71%), and 5 folds cross-validation (95.71%), SMO has the second highest accuracy and less fault prediction, but the algorithm complexity is good (0.3 seconds). The difference in accuracy and less fault prediction between RF and SMO is only (.13%), and the difference in time complexity is (14 seconds). We have decided that we will modify SMO. Finally, the Modified Sequential Minimal Optimization (MSMO) Algorithm method has been proposed to get the highest accuracy & less fault prediction errors in terms of 80/20 (96.42%), 70/30 (96.42%), & 5 fold cross validation (96.50%). [ABSTRACT FROM AUTHOR]

This article revises the traditional view that the 1966 U.S. embargo was the main motivation for Plan Calcul, France's first large-scale information technology program. The government-supported, nationwide program imitated the U.S. "state-industry" model of technological development during the Cold War arms race. French information technology archives and the literature help chart what actions and investments the French government had undertaken several years earlier to establish a solid foundation for Plan Calcul. Often ignored when discussing the development of France's information technology industry, this early history shows why the French government decided to build an autonomous computer industry independent of U.S. technical and financial dominance. [ABSTRACT FROM AUTHOR]

A terrain data model using orientation rather than elevation permits more efficient analysis and stores its data in a multi-band raster. Representation techniques from the computer graphics industry are readily adopted with this data model. A common data model for terrain surfaces–the raster digital elevation model (DEM)–carries with it limitations by emphasizing height. Derived products such as relief shading require additional processing to determine orientation, even though they are used more frequently than those relying on elevation (e.g. hypsometric tinting). We show some of the benefits of encoding and analyzing terrain based on surface orientation, an approach that uses normal vectors stored as multi-band raster, the data storage convention in the computer graphics industry. A change in the data model and the conceptualization of the surface's defining characteristics allows relief shading methods to run faster than conventional tools. Processing efficiencies are especially useful for more advanced shading models that may employ hundreds of relief shading calculations. In addition, an orientation-focused approach to terrain permits cartographic techniques to parallel common computer graphics methods. This project explores one such method, normal-mapping, an effect that adds texture to conventional relief shading by perturbing surface normal vectors. [ABSTRACT FROM AUTHOR]

The Argentine software and computer services sector (SSI) has been active for two decades, driven by public policies and international outsourcing. However, growth in the sector has currently stagnated. This stalling is the result of the extractivism of capacities that operate in three ways: price-salaries, training and financial. The first explanation is the growing competition for costs resulting in contractions of wages and benefits. The second is capacity building that is geared to the requirements of international demand in standardized skills. The third is the financial valuation of the undertakings. This article builds a set of statistical information that enables this phenomenon for the Argentine case to be described and documented. [ABSTRACT FROM AUTHOR]

• Proposal for a new index of revealed comparative advantages, ideal for global value chains, since it is on a linear scale and without the traditional double counting. • Analysis of the changes between the new index of revealed comparative advantages and the previous one, referring to the computer and electronics industry. • Creating a balance between the new index of revealed comparative advantages and the new index of revealed technological advantages. Traditionally, comparative advantages have been measured by the volume of gross exports and with formulas that give asymmetric results. However, with the globalization of value chains, other indices have emerged to partially solve some of these problems. The objective of this study is to create a new index for a linear comparison of different economies around the world at the sectoral specialization level, and without the problem of double international counting originated in the global value chains. The methodology used focuses on the properties of the new index and on the comparison with a previous index that only solved the problem of double counting. The results confirm that the new indicator is more reliable than the other index, especially in more advanced sectors of global value chains. Therefore, it should be used to establish policies related to international trade by different economies and global organizations. [ABSTRACT FROM AUTHOR]

Long-term development in computer manufacturing is crucial to satisfying the demands for the software and hardware needed for artificial intelligence (AI) computation. However, the computer manufacturing sector is highly energy-intensive and resource-consuming, making company sustainability an issue. The framework developed in this study incorporates 15 sustainability criteria focusing predominantly on the economy, society, environment, and risk perspectives. A novel hybrid approach that integrates the ISVTNN (interval single-valued trapezoidal neutrosophic number), DEMATEL (decision-making trial and evaluation laboratory), and PGRA (probability-based grey relational analysis) techniques is proposed. This approach is applied to evaluate the interdependent weights of the criteria for a comprehensive calculation of the performance of the evaluated companies based on probabilities. The inclusion of ISVTNNs allows not only for the broader consideration of information uncertainty but also for more effective integration of experts' judgments. To verify the robustness of the proposed model, three sensitivity analyses were conducted. The results show no significant changes in the rankings of the evaluated companies, demonstrating the stability and reliability of the model. The proposed framework and methodology can serve as the foundation for assessing the sustainable performance of companies in the electronics manufacturing industry. This study indirectly strengthens the backbone of the AI system, by improving sustainability assessment in the computer manufacturing sector (which is integral to the foundation for AI computation). In the AI-driven era, it can be expected that hardware demands will skyrocket, making sustainable manufacturing the linchpin for long-term operational success, resilience, and industry growth. • Developed a novel group decision-making approach for assessing corporate sustainability performance. • Integrated ISVTNN to measure uncertainty and effectively amalgamate expert opinions. • The proposed ISVTNN PGRA retains fuzziness, calculating through probabilistic means. • Demonstrated approach efficacy across six electronics manufacturing enterprises. • Sensitivity analysis underscores the approach's robustness. [ABSTRACT FROM AUTHOR]

In recent years, with the rapid development of human motion simulation technology and virtual simulation technology, natural human-computer interaction has become the main form of research in the computer industry. Due to the research capabilities and practical value of mobile video technology, it is widely used in advanced fields, such as video animation production, rehabilitation medicine, sports training, and game software, effectively realizing the connection between the three-dimensional world and the simulation world. However, the application of motion imaging technology in teaching activities is not perfect. This article is based on dance teaching, adopts a dance movement analysis method based on vector matching, and uses artificial intelligence technology to create a virtual panoramic scene. Experimental data show that the average recognition rate of gestures is 89.8%, which can meet the gesture switching interaction of working conditions in virtual simulation of equipment operation. [ABSTRACT FROM AUTHOR]

This article seeks to reinstate the significance of microcomputer cloning in the history of computing, seeing it as a vernacular technical practice that is outside of the institutional domain yet entangled with it. While exploring the practices of Apple II cloning at the Cheonggyecheon electronics market, and its contribution to promoting the computer industry in South Korea during the early 1980s, the study examines how the vernacular technical practices of cloning moved beyond the imitative/innovative boundary. It has two parts. First, the cloning of Apple II computers is traced with a focus on cottage industry technicians at the electronics market and their East Asian translocal connections. Second, the entanglements of the vernacular with the institutional are analyzed in relation to how clones were sometimes superior to the original while retaining compatibility with it, which in turn made large firms rely on such vernacular practices. Arguing that the boundaries of copy/original, imitative/innovative, or vernacular/institutional were permeable, this study concludes that vernacular technical practices of cloning, although outside formal institutions and official histories, constitute a critical part of the computer industry and the history of computing. [ABSTRACT FROM AUTHOR]

The miniaturization of the silicon chips is reaching its physical limits, and the transistors are so small that current leakage will become an insurmountable problem. Additionally, the actual chip shortage makes clear the excessive world dependence on silicon, stressing the need for silicon‐free computing strategies. Quantum computing process information by manipulating photons, and computation performed by individual molecules are being proposed as alternatives, with potential benefits in terms of miniaturization, performance enhancement, and energy efficiency. Molecular logics can play a decisive role in the future of the computer industry, and the unique photonic characteristics of trivalent lanthanide ions make them suitable candidates to integrate future molecular logic applications. In this work, a Eu3+/Tb3+ co‐doped organic–inorganic hybrid is presented as an illustrative all‐photonic logic platform constructed through the decay dynamics of both lanthanide and hybrid host emissions. Besides combinatory AND, NAND, and INH logic gates, this system presents on‐choice Eu3+, Tb3+, or host emission enabling the development of reprogrammable and reconfigurable photonic molecular logic gates. All‐photonic temperature‐reprogrammable changes from AND to INH logic gates and a reconfiguration among INH and AND1 or AND2 gates, based on the excitation wavelength are demonstrated, showing a clear step forward toward mirroring electronic logic counterparts. [ABSTRACT FROM AUTHOR]

Since it was first proposed by Christensen, disruptive innovation theory has provoked considerable debate in academia and industry. Initially limited to low-end innovations, most of the controversy around the theory has focused on other types of innovations that the theory excludes. This article examines both high-end and low-end disruptive innovations. Instead of technological development, the focus of analysis is on market groups, known as adopter categories. Adopter groups have various characteristics and sizes that play a critical role in the diffusion process of disruptive innovation. In addition, high-end and low-end should be very different in terms of relative advantage, one of the innovation attributes influencing the rate of adoption. To successfully 'disrupt' an incumbent, an innovation should have the potential to cross a critical chasm between early niche markets and majority mainstream markets. We conducted case studies on the rigid disk drives and the computer industry to illustrate the analytical approach based on the innovation diffusion process theory and the characteristics of various adopter categories. [ABSTRACT FROM AUTHOR]

Maintaining the safe and efficient operation of network technology is an important development task of the computer industry. Topology constraint can optimize and combine the tracking results and select the target objects with better tracking performance to obtain the final tracking results and determine the target scale changes. Data mining technology can reduce the number of combinations to be detected, reduce the workload, and improve the timeliness and accuracy of the process of mining alarm association rules. Therefore, based on the summary and analysis of previous research results, this paper studied the network fault diagnosis of the embedded system method based on topology constraint and data mining. Firstly, a fault diagnosis topology model was established by constructing a topology search algorithm, which eliminated the filtering of association rules without topology relationship; the association rule-based data mining model was analyzed through the collection of network alarm data; the model algorithm was applied to the simulation experiment of network fault diagnosis of the embedded system and achieved good results. The results show that correcting rage of retrieval varies from 0.65 to 090 under different window sizes; the running time of the proposed method drops from 310 s to 35 s during 1–8 step/s of the sliding step, while the node degree ranges from 8 to 14 and diagnostic accuracy ranges from 0.97 to 0.94; the remaining alarm number increases from 0.5 to 3.5 threshold value, while the regular association number distributed in an interval of 40 to 140. The algorithm in this paper provides a reference for further research on network fault diagnosis of the embedded system. [ABSTRACT FROM AUTHOR]

Computer vision coupled to deep learning is a promising technique with multiple applications in the industry. In this work, the potential of this technique has been assessed in the classification of two varieties of almond trees (Prunus dulcis), Soleta and Pentacebas. For that, a convolutional neural network named VGG16 was used. The most appropriate configuration for model training was studied, which included the comparison between two different filling modes (reflect and nearest) in the data augmentation step, the evaluation of the batch size and the analysis of the image sizes. The robustness of the model was also checked, and information was obtained about how the model extracts the information from the images. The results showed that the reflect fill mode was more effective than the nearest one. The best results were obtained using batches with 30 and 40 images, with an image size of (224 × 224) pixels. The verification of the robustness proved the capability of the technique as a promising tool for plant varietal identification. Computer vision and deep learning are promising techniques with multiples usage in the industry. In this work, it was assessed the potential of this technique to classify two varieties of almond trees (Prunus dulcis), Soleta and Pentacebas. To reach that, it was studied the most suitable model configuration, then the robustness of the technique was evaluated. We demonstrate the capability of the computer vision together deep learning as an interesting tool for varietal identification. [ABSTRACT FROM AUTHOR]

Being a 16-year-old kid going to UC Berkeley right before the 1960s was not conducive to academic success. That was my situation: Having graduated from high school early with no strong academic motivation, being immature, and with the distractions of Cal, I dropped out after one year of classes and two more years of goofing off. In retrospect, this disaster (my parent's words) led to a 57-year (and still counting) successful career in the computer industry where I participated in and contributed to the evolution from a few large computers to billions of personal computing devices. [ABSTRACT FROM AUTHOR]

Due to the development of electronics industry, the complexity of the circuits has increased and the growth of integrated circuits is increasing exponentially. The manufacturing process of electronic equipment is also becoming more and more complex. Approach of artificial design and analysis of circuits is unable to meet the general requirements; therefore, computer simulation and analysis of circuits have become very important. On the other hand, with rapid development of computer industry, the computer has become a good option for circuit simulation. In order to solve the design and development problems of large-scale and very large-scale integrated circuits, Electronic Design Automation (EDA) technology came into existence, and the need for EDA has increased. The paper introduces different tools and functions of EDA technology and briefly discusses the general methods of electronic design using EDA packages and tools. A comparison is also made with the available EDA tools. [ABSTRACT FROM AUTHOR]

A digital modeling framework for motorcycles (DMF) involves applying advanced computer design, computer-assisted analysis, and computer-assisted development. Data processing technology simulated prototype product, fast prototype technology, standard technology, etc. It is an interdisciplinary, systematic technology in the entire process of product design, production, and manufacture. DMF solves single-model production and constrained capacity building to satisfy the industry's demand for individual and diverse motorcycle goods. DMF sets forward several approaches within it, including parametric technologies for design, technology dependent on experience, design application, and data integration trends. The DMF provides the basis for a synthesis of motorcycles' production and demand. The result illustrates that digital concept strategies and approaches can be used in the motorcycle industry in reality with the highest efficiency (97.32%), emission rate (25.16%), speed rate (95.23%), exhaust rate (41.32%), heat loss rate (6.18%), performance metrics rate (9.32%), and error rate (5.44%), compared to other popular methods. For the 100 motorcycles, the average charging capacity, speed, distance traveled, and implementation cost ratio are observed at 97.11%, 85–100 km/h, 80–100 km, and 9.32%, respectively. [ABSTRACT FROM AUTHOR]

The computer industry was a vivid place in the 1980s. IT systems and technologies thrived, and the market offered ever better, smaller, and more useful machines. Innovative technical solutions or intelligent designs that satisfied customers' needs are often listed as computer hardware milestones. Consequently, they became a permanent part of the computerisation history and can be considered hardware heritage artefacts. The purpose of the paper is to analyse the usability of selected portable computer systems. The foundation of the work is a literature review that includes technical specifications, industry reviews, and research papers. Archival materials were obtained from the Internet Archive. Studies have revealed that the main problems design engineers of portable computers had to tackle in the 1980s were the reduction of mass and size of the computer system, portable power (self-power), and the quality of the displayed image. [ABSTRACT FROM AUTHOR]

Chinese ceramics have a long history and have been deeply recognized by the world after centuries of changes. The current world ceramic industry is diversified. Under this background, there is a huge challenge to the development of Chinese ceramics. The update of materials, the participation of computers in ceramic design, and the demonstration of ingredients all constitute technological factors that cannot be ignored in the development of the ceramic industry. Therefore, this study uses the SWOT analysis method to analyze the development of Chinese ceramics, puts forward its advantages and disadvantages, opportunities, and threats, and under the background of advanced technology, and how to use computer software to demonstrate raw materials and color matching to make Chinese ceramics. The development achieves the goal of self-improvement and then completes the upgrade of its production process and production. Through the research of this study, it is found that the current development of China's ceramic industry should be good at using SWOT analysis, face up to its shortcomings and pressure from other ceramic production areas in the world, give full play to its advantages, maximize strengths and avoid weaknesses, and use technological innovation, combined with technical factors from other disciplines, to promote ceramic industry design and production capabilities and provide a reference for the current ceramic industry development. [ABSTRACT FROM AUTHOR]

The simulation of subtractive manufacturing processes has a long history in engineering. Corresponding predictions are utilized for planning, validation and optimization, e.g., of CNC-machining processes. With the up-rise of flexible robotic machining and the advancements of computational and algorithmic capability, the simulation of the coupled machine-process behaviour for complex machining processes and large workpieces is within reach. These simulations require fast material removal predictions and analysis with high spatial resolution for multi-axis operations. Within this contribution, we propose to leverage voxel-based concepts introduced in the computer graphics industry to accelerate material removal simulations. Corresponding schemes are well suited for massive parallelization. By leveraging the computational power offered by modern graphics hardware, the computational performance of high spatial accuracy volumetric voxel-based algorithms is further improved. They now allow for very fast and accurate volume removal simulation and analysis of machining processes. Within this paper, a detailed description of the data structures and algorithms is provided along a detailed benchmark for common machining operations. [ABSTRACT FROM AUTHOR]

We identify and measure two impacts of industry-level total factor productivity (TFP) growth on aggregate price change in the U.S. and Japan. The first is a standard effect from the definition of aggregate GDP. TFP change lowers aggregate prices ceteris paribus. The second is that a change in TFP in the production of investment goods lowers the cost of capital via lower investment prices. We call this the cost-of-capital effect and formulate an expanded growth accounting framework to capture both effects. We apply it to a harmonized dataset for the two countries and find that the standard effect has fallen since the peak around 2000 due to lower TFP growth and a diminished share of GDP. However, the cost-of-capital effect has risen in importance and offsets part of this decline in the standard effect. • TFP growth in Computer equipment contributes to aggregate TFP growth • This contribution is high in US and Japan, but decelerating since 2004 • Identify how TFP in computers lowers asset prices and cost of capital • Cost-of-capital effect lowers aggregate prices (GDP deflator) • Cost-of-capital effect is rising since 2004 [ABSTRACT FROM AUTHOR]

• A robust, portable CE sampler to detect common inorganic ions in situ. • Sampler based on peristaltic and vacuum pumps, a check valve, and a pinch valve. • CE is a promising technology for green analytical chemistry and citizen science. A compact, inexpensive sampler instrument for portable capillary electrophoresis (CE) was developed and tested to monitor common inorganic ions in drinking water samples. The sampler uses peristaltic and vacuum pumps and pinch and check valves to control liquid flows. The paper also addresses various aspects of CE associated with portability, open access instrumentation and prospects of CE for citizen science. The extensive use of items provided by the electronic and computer industry contributes to this trend. [ABSTRACT FROM AUTHOR]

• A sampler for portable capillary electrophoresis to detect GHB in situ. • Sampler based on peristaltic pumps, a check valve, and a pinch valve. • LOD with CCD for GHB 1.7 mg L−1, meets the cutoff testing value for GHB in saliva. A compact, inexpensive sampler instrument for portable capillary electrophoresis was developed for monitoring illegal drugs in human body fluids and evaluated for γ-hydroxybutyric acid (GHB) in simulated saliva samples. The sampler uses peristaltic pumps and pinch and check valves to activate liquid flows. This short communication addresses aspects of CE associated with portability, open access instrumentation, and prospects of CE for citizen science. The extensive use of items provided by the electronic and computer industry contributes to this trend. [ABSTRACT FROM AUTHOR]

Most of the publications in green analytical chemistry (GAC) deal with the benign solvents and procedures and all aspects of measures of the greenness of certain methods. The equally important instrumentation aspects in GAC have received much less attention. Instruments in contemporary analytical chemistry have a significant footprint. Capillary electrophoresis (CE) is a technology that offers an instrument whose ecological footprint could be much less than that of other popular analytical technologies. This paper describes the GAC features of CE with many examples. Those green features of CE include the capability of miniaturization and, thus, the possibility of making portable instruments that can be used in situ. In recent years, many groups have demonstrated increasing interest in developing simple, robust, and inexpensive portable CE instruments. This paper will address aspects of CE associated with portability, open access instrumentation, and prospects of CE for citizen science. The extensive use of items provided by the electronic and computer industry contributes to this trend. [Display omitted] • Instruments in contemporary analytical chemistry have a significant ecological footprint. • Capillary electrophoresis (CE)is a technology with a small ecological footprint. • CE is a promising technology for citizen science due to its simplicity and the wide availability of consumer electronics. [ABSTRACT FROM AUTHOR]