Heterogeneous Technologies Research Articles

Automatic Detection of Visual Changes between X-Ray Images to Support Antifraud Customs Control at Ports - A Preliminary Study

One of the goals of customs authorities is to identify, at borders, cargos that do not match their declaration, contain illegal items, or pose a hazard to society. Customs X-ray inspection procedures enable the detection of suspicious cargos and are an excellent support tool for customs officials. The ISACC project, funded under the Interreg IPA Cross-border Cooperation Italy-Albania-Montenegro Programme aims at developing a web platform that integrates data, coming from heterogeneous technologies and systems, in order to provide a rich information base supporting customs authorities during antifraud controls. In this paper, we propose a preliminary study, based on the SIFT algorithm, for the automatic detection of visual changes between scanner X-Ray images, that are part of this information base.

Understanding the driving factors and finding the pathway to mitigating carbon emissions in China's Yangtze River Delta region

Technological progress is an effective tool for controlling carbon emissions. However, because the connection between technological progress and carbon emissions remains under-theorized, the literature often discusses the overall effect of technological progress, ignoring the heterogeneity of technology. To better understand the driving factors of carbon emissions, we develop a new theoretical model based on the Green Solow model, in which technology is divided into production, energy conservation, and energy substitution technologies. Dynamic panel models are then applied to show the driving influence of different factors affecting carbon emissions in the Yangtze River Delta (YRD) region between 2000 and 2017. The results indicate that total technological progress is conducive to reducing carbon emissions. The heterogeneity analysis indicates a positive reduction effect on carbon emissions for energy substitution and energy conservation technologies, but not for production technology. Interestingly, production technology significantly drives carbon emissions. However, the results also suggest that to control carbon emissions, it is necessary to promote production technology. Further analysis suggests that production technology plays an important role in the effectiveness of energy conservation and energy substitution technologies in decreasing carbon emissions.

Uncertainty-Informed Operation Coordination in a Water-Energy Nexus

The widespread deployment of smart heterogeneous technologies and the growing complexity in our modern society calls for effective coordination of the interdependent lifeline networks. In particular, operation coordination of electric power and water infrastructures is urgently needed as the water system is one of the most energy-intensive networks, an interruption in which may quickly evolve into a dramatic societal concern. The closely-intertwined ecosystem of water and power infrastructures is commonly known as water-energy nexus. This paper develops a novel analytic for uncertainty-aware day-ahead operation optimization of the interconnected power and water systems (PaWS). Joint probabilistic constraint (JPC) programming is employed to capture the uncertainties in wind resources and water demand forecasts. The proposed integrated stochastic model is presented as a non-linear non-convex optimization problem, where the non-linear hydraulic constraints in the water network are linearized using piece-wise linearization technique, and the non-convexity is efficiently tackled with a Boolean solution methodology to convert the proposed model with JPCs to a tractable mixed-integer linear programming (MILP) formulation that can be quickly solved to optimality. The suggested framework is applied to a 15-node commercial-scale water network jointly operated with a power transmission system using a modified IEEE 57-bus test system. The numerical results demonstrate the of the proposed stochastic framework, resulting in cost reduction (13% on average when compared to the traditional setting) and energy saving of the integrated model under different realizations of uncertain renewable energy sources (RESs) and water demand scenarios. Additionally, the scalability of the proposed model is tested on a modified IEEE 118-bus test system connected to five water networks.

Cultural Differences and Bilateral Trade: An Empirical Study Based on Industrial Data from OECD and BRIICS Countries

ABSTRACT This study extends the cross-sectional gravity function in the Eaton and Kortum model to a panel-data model based on 36 OECD and six BRIICS countries from 2010 to 2018 and introduce heterogeneous technology to measure the competitiveness of each country by interaction fixed effects. The results illustrate that the total cultural distance between countries significantly impedes bilateral trade, as it increases trade costs. The conclusions are robust with instrumental variables, alternative measurement of cultural differences, and extended time window estimation. And the effects present heterogeneity in sub-dimensions of cultural distance and sub-industries.

Boosting, sorting and complexity—urban scaling of innovation around the world

AbstractIt is widely understood that innovations tend to be concentrated in cities, which is evidenced by innovative output increasing disproportionately with city size. Yet, given the heterogeneity of countries and technologies, few studies explore the relationship between population and innovation numbers. For instance, in the USA, innovative output scaling is substantial and is particularly pronounced for complex technologies. Whether this is a universal pattern of complex technologies and a potential facilitator of scaling, is unknown. Our analysis compared urban scaling in urban areas across 33 countries and 569 technologies. Considerable variation was identified between countries, which is rooted in two fundamental mechanisms (sorting and boosting). The sorting of innovation-intensive technologies is found to drive larger innovation counts among cities. Among most countries, this mechanism contributes to scaling more than city size boosting innovation within specific technologies. While complex technologies are concentrated in large cities and benefit from the advantages of urbanization, their contribution to the urban scaling of innovations is limited.

Computational pathology to improve biomarker testing in breast cancer: how close are we?

The recent advancements in breast cancer precision medicine have highlighted the urgency for the precise and reproducible characterization of clinically actionable biomarkers. Despite numerous standardization efforts, biomarker testing by conventional methodologies is challenged by several issues such as high inter-observer variabilities, the spatial heterogeneity of biomarkers expression, and technological heterogeneity. In this respect, artificial intelligence-based digital pathology approaches are being increasingly recognized as promising methods for biomarker testing and subsequently improved clinical management. Here, we provide an overview on the most recent advances for artificial intelligence-assisted biomarkers testing in breast cancer, with a particular focus on tumor-infiltrating lymphocytes, programmed death-ligand 1, phosphatidylinositol-3 kinase catalytic alpha, and estrogen receptor 1. Challenges and solutions for this integrative analysis in pathology laboratories are also provided.

Technological heterogeneity and time-varying efficiency of sharing accommodation: Evidence from the Canary Islands

The production of services in the accommodation sharing industry is heterogeneous in the sense that listings with different strategic management could adopt distinct technologies. This paper analyses the time-varying efficiency of the peer-to-peer accommodation sector using the input distance stochastic frontier model with random coefficients to accommodate both multi-input and multi-output technology and the technological heterogeneity among listings. An empirical analysis is conducted based on data from Airbnb and HomeAway listings in the Canary Islands (Spain), before, during and after the COVID-19 lockdown (source: AirDNA), in the period January 2019-September 2020 (monthly data). The results show technological heterogeneity between listings and time-varying inefficiency which negatively depends on productivity. Moreover, multi-unit hosts are clearly more efficient than single-unit hosts. A mean efficiency of around 78% during the study period was estimated.

On hypothesis testing in latent class and finite mixture stochastic frontier models, with application to a contaminated normal-half normal model

Latent class and finite mixture stochastic frontier models have been proposed as a means of allowing either for technological heterogeneity or more flexible distributions of noise and inefficiency. As in the wider literature on latent class and finite mixture models, we are interested in class enumeration, particularly testing against homogeneity. We apply a modified likelihood ratio test for homogeneity in a stochastic frontier setting, based on established results for non-Gaussian latent class and finite mixture models, and provide evidence from Monte Carlo experiments which suggest the applicability of results regarding a modified likelihood ratio test to the stochastic frontier setting. We demonstrate an application to testing a model with a contaminated normal noise term against a model with a normally distributed noise term, finding that the former is preferred, with significant implications for efficiency prediction.

Automatic Emotion Recognition in Clinical Scenario: A Systematic Review of Methods

Automatic emotion recognition has powerful opportunities in the clinical field, but several critical aspects are still open, such as heterogeneity of methodologies or technologies tested mainly on healthy people. This systematic review aims to survey automatic emotion recognition systems applied in real clinical contexts, to deeply analyse clinical and technical aspects, how they were addressed, and relationships among them. The literature review was conducted on: IEEEXplore, ScienceDirect, Scopus, PubMed, ACM. Inclusion criteria were the presence of an automatic emotion recognition algorithm and the enrollment of at least 2 patients in the experimental protocol. The review process followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Moreover, the works were analysed according to a reference model to deeply examine both clinical and technical topics. 52 scientific papers passed inclusion criteria. Most clinical scenarios involved neurodevelopmental, neurological and psychiatric disorders with the aims of diagnosing, monitoring, or treating emotional symptoms. The most adopted signals are video and audio, while supervised shallow learning is mostly used for emotion recognition. A poor study design, tiny samples, and the absence of a control group emerged as methodological weaknesses. Heterogeneity of performance metrics, datasets and algorithms challenges results comparability, robustness, reliability and reproducibility.

Technology heterogeneity and sustainability efficiency: Empirical evidence from Peruvian coffee production

This article uses a non-parametric non-convex metafrontier approach to estimate farm sustainability efficiency while considering heterogeneity in production technologies stemming from differences in the production environment under which farming takes place. Sustainability efficiency measures reflect farmers’ ability to increase production of desirable agricultural outputs, reduce fertilizer-induced nitrous oxide emissions, and create employment opportunities for women. This is the first attempt to measure efficiency in terms of firms’ contribution to employment opportunities for women, a social and developmental issue gaining much public attention. The empirical application uses data on 1109 Peruvian coffee farms over the period 2017–2019. Sample farms operate in two natural regions of Peru – namely Sierra, and Selva – where farming systems differ because of variations in resource endowments and socioeconomic conditions. Results indicate the presence of interregional heterogeneity in production technologies of sample farms. Sierra coffee farms outperformed coffee farms located in the Selva region in all three dimensions of sustainability efficiency, suggesting that it is the latter that are in greater need of efficiency improvement interventions. Results further show that both Sierra and Selva coffee farms performed worst with respect to environmental efficiency, implying a greater scope for reducing nitrous oxide emissions with existing production technology and resources.

Accounting for intra-industry technological heterogeneity in the measurement of operations efficiency

In operations management literature, efficiency is usually measured using parallel shifts of production functions. This practice is based on the assumption that operations technologies are similar across decision-making units. Relaxing this assumption is essential as firms endowed with heterogeneous operational technologies develop distinctive operational resources and capabilities that vary systematically within an industry, resulting in non-parallel shifts of production functions. By relaxing the assumption of parallel production functions, we focus on technological differences as a measure of inefficiency in production and use non-parametric local linear estimates. Our approach based on Bayesian methods and stochastic dominance is novel in that it models for non-parallel production curve slopes that account for unknown frontier technology which is not observed but can be estimated using intra-industry variation in individual firm operational technologies. The proposed approach makes an important contribution to operations management research by relaxing a non-trivial assumption of parallel shifts of production functions in efficiency analysis.

Inequality in Fossil Fuel Power Plants in China: A Perspective of Efficiency and Abatement Cost

Quantifying the shadow price (SP) of CO2 emissions is the key to achieving China’s “double carbon” targets. Considering technology heterogeneity, this study applies stochastic frontier analysis combined with meta-frontier technology to estimate the environmental technical efficiency (ETE) and SP of CO2 emissions for China’s fossil fuel power plants from 2005 to 2015. This approach overcomes the lack of statistical inference and consistency of traditional methods and improves the reliability of results. The main results are as follows: (a) the average ETE of China’s power plants is 0.9444, indicating that inefficient production accounts for 5.66%. The difference in efficiency between the central and local groups is significant. (b) The national average SP of CO2 is 266.8 US dollars per ton, which is much higher than the carbon price in the emission trading system. This result implies the need to design a carbon trading price mechanism. (c) The distribution of SP shows obvious corporation and geographical characteristics that are closely related to the level of regional economic development. Finally, the findings provide policy implications for the improvement of the efficiency and abatement of costs of power plants and the determination of carbon prices.

Unearthing marine ecological efficiency and technology gap of China’s coastal regions: A global meta-frontier super SBM approach

With the promotion of the maritime power strategy and progressively increasing and severe environmental problems, marine ecological efficiency is fast becoming an essential object of research in achieving sustainable development. By applying the meta-frontier super SBM model and the global Malmquist-Luenberger index, this paper aims to explore the marine ecological efficiency of coastal regions in China and the technology gaps between different regions during 2006–2017. On this basis, the changes in marine ecological efficiency were decomposed to investigate the driving factors. The results indicate that the marine ecological efficiency of China’s coastal regions was still ineffective, and there was a significant gap between the group production technology and the potential optimal production technology. Also, there was a significant regional technological heterogeneity. The Yangtze River Delta region had optimal production technology level, while the Beibu Gulf region distinctly had a sizeable technological gap with the other three regions. Besides, the primary factor affecting marine ecological efficiency was technological progress. Finally, the results of this paper passed the robustness check. Based on these conclusions, some specific policy suggestions are provided for China’s coastal regions.

Comparing Hospital Efficiency: An Illustrative Study of Knee and Hip Replacement Surgeries in Spain.

WHO's Health Systems Performance Assessment framework suggests monitoring a set of dimensions. This study aims to jointly assess productivity and quality using a treatment-based approach, specifically analyzing knee and hip replacement, two prevalent surgical procedures performed with consolidated technology and run in most acute-care hospitals. Focusing on the analysis of these procedures sets out a novel approach providing clues for hospital management improvements, covering an existing gap in the literature. The Malmquist index under the metafrontier context was used to estimate the productivity in both procedures and its decomposition in terms of efficiency, technical and quality change. A multilevel logistic regression was specified to obtain the in-hospital mortality as a quality factor. All Spanish public acute-care hospitals were classified according to their average severity attended, dividing them into three groups. Our study revealed a decrease in productivity mainly due to a decrease in the technological change. Quality change remained constant during the period with highest variations observed between one period to the next according to the hospital classification. The improvement in the technological gap between different levels was due to an improvement in quality. These results provide new insights of operational efficiency after incorporating the quality dimension, specifically highlighting a decreasing operational performance, confirming that the technological heterogeneity is a critical question when measuring hospital performance.

Environmental Performance of China’s Industrial System Considering Technological Heterogeneity and Interaction

The industrial sector, the backbone of China’s economic development, is a key field that requires environmental management. The purpose of this study is to propose an improved data envelopment analysis (DEA) model to analyze the performance of provincial industrial systems (ISs) from 2011 to 2020 in China. To comprehensively characterize the operational framework of ISs, this study proposes an improved meta-frontier network DEA model. Unlike the existing models, the one proposed in this study not only considers the technical heterogeneity of ISs, but also reflects the interaction between IS subsystems. The empirical analysis yields valuable research findings. First, the overall environmental performance of Chinese ISs is generally low, with an average performance of 0.50, showing a U-shaped trend during the study period. Furthermore, significant regional differences are observed in the environmental performance of Chinese ISs. Second, the average performance of the production subsystem is 0.75, while the average performance of the pollution control subsystem (PTS) is 0.44. The low performance of the PTS pulls down the overall performance of Chinese ISs. Third, the technological level of Chinese ISs is low, with about 50% improvement potential. Finally, targeted suggestions to promote the green development of ISs are proposed on the basis of the empirical results.

Analysis of CO2 emission performance of China’s thermal power industry: a meta-frontier Malmquist-Luenberger approach with fixed-sum CO2 emissions

This study combines the general equilibrium efficient frontier data envelopment analysis (GEEFDEA) approach, which handles fixed-sum CO2 emissions, with the meta-frontier Malmquist-Luenberger productivity index (MMLPI). We use this novel technique to measure the CO2 emission performance (CEP) of 30 of China’s provincial-level thermal power industries during 2006–2020, both statically and dynamically, and reveal the drivers of CEP changes. Our proposed approach considers the fixed-sum feature of CO2 emissions and also captures the impact of technology heterogeneity. The empirical results show that the CEP of China’s thermal power industry was good during the sample period, showing average annual increases of 2.42%, mainly due to technical efficiency gains and technological progress. The CEP of most provinces grew at various rates, between 0.23% and 8.38%; and the drivers of CEP changes differ between provinces. Policy implications are discussed, such as the need to strengthen technology innovation and optimize production processes to improve CEP.

Transportation carbon emission reduction potential and mitigation strategy in China

Effectively reducing transportation carbon emissions is greatly significant to achieve the carbon peaking and neutral goals of China. On the basis of considering regional technology heterogeneity, we employ the parametric meta-frontier approach to analyze the carbon emission performance and reduction potential of the transportation sector in China. Then, we further decompose the emission reduction potential's contributors into removing management inefficiencies and filling technology gaps. The estimated potential carbon emission reductions from transportation sector in China are 12.3 million tons, accounting for 8.4 % of the annual transportation carbon emissions. Specifically, the eastern regions, especially Shandong, Shanghai, and Liaoning have the greatest carbon emission reduction potential; while Qinghai, Jiangxi, and Ningxia have the smallest potential. As the major contributors to the potential emission reductions, filling technology gaps and removing management inefficiencies account for 57.5 % and 42.5 % of the total potential, respectively. Moreover, removing management inefficiencies dominate for the eastern region and filling technology gaps for the central and western regions. Finally, we provide provincial-specific emission mitigation strategies based on the identification of the reduction potential and its contributors. Our policy implications help decision-makers to facilitate the low-carbon development of transportation sector.

Impact of recycled aggregate properties on concrete performance

One of the ways for construction sector to contribute to sustainability is to reuse and to recycle the huge amount of construction and demolition waste (CDW) it generates. Recycled concrete aggregate (RCA) is recognized by EN 206 standard as a legitimate concrete ingredient, but their full potential is far to be used, because of several reasons: availability of natural resources, heterogeneity of CDW, technology and costs issues and mistrust in performances. In Bulgaria, in addition, the national amendment to EN 206 is very restrictive because of lack of national know-how. This study aims to fill the gap and assess the impact of RCA on concrete performance. RCA from three different CDW sources is tested. RCA differs in porosity, water absorption and mechanical characteristics. The performance of recycled aggregate concrete with 30% and 50% replacement of coarse aggregate by RCA is compared to that of natural aggregate concrete. Mix design with two cement quantities and two water/cement ratios are investigated. The higher water absorption of RCA is taken into consideration while producing fresh concrete. The results demonstrate that the quality of primary concrete has certain effect on strength characteristics, E-modulus and water permeability. However, RCA up to 30% does not modify significantly the behaviour of both fresh and hardened concrete. RCA of 50% does not worsen the properties of the concrete, either, but some reduction of performance can be observed. In conclusion, RCA presents a solution for both natural resources preservation and appropriate CDW management.

Exploiting Short Block and Concatenated Codes for Reliable Communications Within the Coexistence of 5G-NR-U and WiFi

Unlicensed spectrum offers opportunities for cellular mobile network operators, where traffic can be offloaded from licensed to unlicensed bands. Modern heterogeneous technologies such as 5G and WiFi can simultaneously operate on ISM and UNII bands under strict coexistence rules. While satisfying harmonious coexistence has largely been studied in LTE/4G, an emerging issue for future deployment is to reduce latency and to guarantee reliable communications, in the direction of achieving URLLC. This work mainly focuses on the critical issues arising in the coexistence of LBT systems, sharing common infrastructure of 5G NR-U and WiFi when operating under imperfect energy detection sensing. We consider the application of short, concatenated and product erasure correcting codes to recover missing data due to collisions in LBT-based systems. The goal is to enhance spectrum utilization with reduced delay and to achieve reliable communications under various sensing impairments, with code parameters such as block length, rate and minimum distance. Using concatenation, we construct a series of sophisticated erasure block codes with less decoding complexity. Furthermore, we derive a closed-form expression using Gaussian approximation of spectrum utilization efficiency. The results are compared with the various LDPC correcting ensembles under various levels of user activities. We provide detailed comparisons of global throughput and failure probability of codes under varied number of coexisting users. Our results show that the proposed codes can achieve over 20% higher efficiency at 0.1 false alarm probability and 30% less failure probability under high contention scenarios.

ФУНКЦИОНАЛЬНОСТЬ СЕТИ КИБЕРБЕЗОПАСНОСТИ КРИТИЧЕСКОЙ ИНФОРМАЦИОННОЙ ИНФРАСТРУКТУРЫ

The analysis of modern approaches to countering computer attacks on critical information infrastructure (CII), presented in the form of distributed information resources, shows that there is an objective need for technological development of this direction. In this aspect, the most promising solution to this problem seems to be the use of the concept of "Cybersecurity Mesh" (cybersecurity networks), introduced by Gartner without precise instructions on practical implementation and possible technological solutions. This paper presents the results of a study of functional requirements for systems implemented in accordance with the above concept, on the basis of which a new architecture of CII cybersecurity will be set in the future. The features of its application proposed by the authors of the concept are considered in detail, on the basis of which the requirements for the functional structure of possible technological requirements have been developed. It consists of four basic levels that allow you to respond flexibly to emerging integration and security challenges. These levels include: intelligent information security and analytics, distributed identity structure, consolidated policy and state management, consolidated interactive dashboard. To meet the specified functional requirements, a technological model for building a cybersecurity network is proposed in the form of an organic combination of three fairly heterogeneous technologies: 5G mobile communications, Secure Access Edge (SASE - Secure Access Service Edge) and advanced detection and response (XDR) into a consolidated cloud platform. The results of the studies of the functionality of the concept of a cybersecurity network can be considered as a methodology for ensuring the security of CII, implying a transition from building a single secure digital perimeter around all its devices or nodes to point protection of each remote access point. This publication can be useful for experts in the security forces of CII facilities, as well as to employees of educational institutions in the implementation of appropriate training, retraining and advanced training programs for such specialists.