Journal articles on the topic 'Explosives – Detection – Technological innovations'
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F. Santarelli, Maria, Vincenzo Positano, Nicola Martini, Giuseppe Valvano, and Luigi Landini. "Technological Innovations in Magnetic Resonance for Early Detection of Cardiovascular Diseases." Current Pharmaceutical Design 22, no. 1 (December 21, 2015): 77–89. http://dx.doi.org/10.2174/1381612822666151109112240.
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Maziejuk, Mirosław, Monika Szyposzyńska, Aleksandra Spławska, Monika Wiśnik-Sawka, and Michał Ceremuga. "Detection of Triacetone Triperoxide (TATP) and Hexamethylene Triperoxide Diamine (HMTD) from the Gas Phase with Differential Ion Mobility Spectrometry (DMS)." Sensors 21, no. 13 (July 2, 2021): 4545. http://dx.doi.org/10.3390/s21134545.
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One of the significant problems in the modern world is the detection of improvised explosives made of materials synthesized at home. Such compounds include triacetone triperoxide (TATP) and hexamethylene triperoxide diamine (HMTD). An attempt was made to construct an instrument allowing for the simultaneous detection of both compounds despite the large difference of vapor pressure: very high for TATP and very low for HMTD. The developed system uses differential ion mobility spectrometry (DMS) in combination with a specially designed gas sample injection system. The created system of detectors allowed for the detection of a high concentration of TATP and a very low concentration of HMTD. TATP detection was possible despite the presence of impurities—acetone remaining from the technological process and formed as a coproduct of diacetone diperoxide (DADP) synthesis. Ammonia added to the carrier gas improved the possibility of detecting the abovementioned explosives, reducing the intensity of the acetone signal. The obtained results were then compared with the detection capabilities of drift tube ion mobility spectrometer (DT-IMS), which has not made possible such detection as DMS.
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Barrass, Lucy, Abigail Roberts, Oluwatomi Arisa, Emily Robertson, Aoife Oliver, Oshin Sharma, Janet Kinnersley, Dawn Craig, and Anne Oyewole. "OP57 The Identification Of Technological Innovations To Address The Challenge Of Antimicrobial Resistance Using Horizon Scanning Approaches." International Journal of Technology Assessment in Health Care 38, S1 (December 2022): S22. http://dx.doi.org/10.1017/s0266462322001106.
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IntroductionInappropriate prescribing of antibiotics is a significant driver of antimicrobial resistance (AMR) which is a global health challenge. Technological innovations present an opportunity to reduce demand for antimicrobials through infection prevention, detection, and management. The National Institute for Health and Care Research (NIHR) Innovation Observatory (IO) has developed horizon scanning methods to identify promising innovations (devices/diagnostics/digital) and anticipate technological trends. Together these insights build a comprehensive landscape and presents a significant opportunity for decision-makers and HTAs to consider the clinical, financial, infrastructural, and logistical provisions to improve preparedness for the potential adoption of these future innovations.MethodsThe IO developed a detailed dataset of technologies by formulating search strategies for AMR, based on a comprehensive list of terms and input from expert panels. Primary and secondary sources were systematically scanned using a combination of traditional scanning methods, automated and novel artificial intelligence (AI)/machine learning techniques. Sources included clinical trial registries, MedTech news, academic sources, funding agencies, commercial sites, and regulatory authorities.ResultsOur global dataset identified over 3000 innovative preventative, detection, and monitoring technologies mapped across AMR clinical pathways (including sepsis, respiratory tract infections). Development activity largely concentrated in the United States of America and United Kingdom. Emerging trends included the application of novel materials to prevent infections (e.g., catheter coatings) and novel analytical techniques (e.g., biosensors, microfluidics, breath analysis) to support optimal patient treatment. Data analysis revealed a high proportion of technologies were diagnostic innovations addressing unmet needs such as rapid and accurate detection (including drug-resistant infections).ConclusionsThe rapid development and application of technological interventions presents an opportunity to strengthen national AMR strategies worldwide, through the adoption of new innovations. Improvements in exiting technologies, along with technological advancements have the potential to support appropriate prescribing of antimicrobials and thus address the rise in AMR.
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MOWLAWI, ALI ASGHAR, and MAJED YAZDANI. "MONTE CARLO SIMULATION OF SOIL MOISTURE EFFECTS ON ANTI-TANK LANDMINES DETECTION BY NEUTRON BACKSCATTERING TECHNIQUE." International Journal of Modern Physics B 23, no. 32 (December 30, 2009): 5907–13. http://dx.doi.org/10.1142/s0217979209049735.
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The detection of landmines using available technologies is a time consuming, expensive, and extremely dangerous job, so that there is a need for technological breakthroughs in this field. One of the safest and most effective technologies to landmine and explosive detection is the neutron backscattering technique. The slowing-down of fast neutrons to the thermal energy is a direct measure of the concentration of hydrogen, one of the main elements present in explosive materials. The elastic scattering of fast neutrons is affected by the strong resonances in the cross-section of the three other elements of explosives: nitrogen, oxygen, and carbon. In this work, Monte Carlo estimations of the soil moisture effects on landmine detection are presented.
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Bogue, Robert. "Remote chemical sensing: a review of techniques and recent developments." Sensor Review 38, no. 4 (September 17, 2018): 453–57. http://dx.doi.org/10.1108/sr-12-2017-0267.
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Purpose This paper aims to provide technical details of the techniques used for the remote detection of chemical compounds in a number of applications and also to highlight key research themes. Design/methodology/approach Following a short introduction, this first considers remote gas detection using the DIAL technique. Remote gas cloud imaging is then discussed, and this is followed by a review of chemical warfare agent detection technologies. A selection of research activities and product developments aimed at remotely detecting explosives are considered and, finally, brief concluding comments are drawn. Findings Remote gas sensing is now a practical reality, and products are available which can remotely detect, identify, quantify and in some cases visualise a wide range of toxic and environmentally threatening gases. These satisfy numerous industrial, environmental and military applications. Remotely detecting explosives poses a significant technological challenge, and despite some commercialisation, it remains the topic of an extensive research effort, much involving LIBS and Raman techniques. Importantly, much of this work also has potential in non-military applications, with several developments being shown to detect various industrially important compounds. Originality/value This provides a technical insight into the techniques and products used in a range of remote chemical sensing applications.
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Sickle, G. A. Van. "A review of innovations in disease and insect management and control." Forestry Chronicle 68, no. 6 (December 1, 1992): 742–46. http://dx.doi.org/10.5558/tfc68742-6.
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Insects, diseases and fire annually cause losses equal to one-third of the allowable annual cut in British Columbia and can directly affect exports and movement of forest products. While salvage, at least partial, of the merchantable mortality has been the traditional practice, innovations in forecasting, detection and control are increasing forest management options. Examples are given of technological advances in nursery production, data analysis and interpretation using geographic information systems (GIS) and models, insect pheromones and biological controls, and quarantine requirements imposed by concerns for potential pests.
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Gouveia-Carvalho, Júlio, Wilson Talhão Antunes, Tiago Gonçalves, Victor Lobo, Filipe Duarte, Bernardino Veríssimo, Alfredo Baptista, and Mário Monteiro Marques. "Chemical and Radiological Sensors Integration in Unmanned Aerial Systems with ATEX Compliance." Key Engineering Materials 893 (July 20, 2021): 17–27. http://dx.doi.org/10.4028/www.scientific.net/kem.893.17.
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Chemical, biological, radiological and nuclear (CBRN) threats pose many challenges to address in terms of reconnaissance, detection, personnel protection and countermeasures comprising a common set of techniques and procedures that fit in the concept of “all hazard” approach. The scientific and technological developments that led to the use of unmanned aerial systems (UAS) in an ubiquitous manner, enables its integration in CBRN operations, as sensors platforms for detection. In this scope, the GammaEx project targets to validate the concepts of operation using a specifically developed UAS with ATmosphères EXplosives (ATEX) compliance, equipped with chemical and radiological sensors for detection in CBRN scenarios. This paper aims to review the main concepts and challenges involving the sensors integration in UAS for specific CBRN environments considering the ATEX compliance, followed by the GammaEx project description and the presentation of the preliminary results of the laboratory and field comparative assays concerning the specifically developed sensors for the project and the commercial of the shelf sensors, follow on activities and future trends.
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Oriana, Villarroel-Molina, De-Pablos-Heredero Carmen, Barba Cecilio, Rangel Jaime, and García Antón. "The Importance of Network Position in the Diffusion of Agricultural Innovations in Smallholders of Dual-Purpose Cattle in Mexico." Land 10, no. 4 (April 12, 2021): 401. http://dx.doi.org/10.3390/land10040401.
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The dual-purpose bovine production system (DP) is the most widespread small-scale model in Latin American tropics, where it constitutes a key tool in terms of food security. Most DPs are subsistence farms oriented to self-consumption, with a very low technology adoption rate. Hence, the main challenge is how to improve the technological level without compromising the system sustainability by applying land-sharing practices. Thus, through networks methodology, this paper analysed how farmers adopt reproductive technologies. The sample consisted of 383 very small farms of dual-purpose cattle. Seven reproduction technologies oriented to improve reproductive efficiency were evaluated: Breeding soundness evaluation in bulls, semen fertility evaluation, evaluation of female body condition, oestrus detection, pregnancy diagnosis, seasonal or continuous mating, and breeding policy. Social Network Analysis (SNA) allowed identifying adoption patterns, as the joint adoption of semen fertility evaluation, estrus detection, and pregnancy diagnosis, which were consider complementary technologies. Similarly, breeding soundness evaluation in bulls was found to be the most widely adopted technology. The results showed that these farmers presented a very low level of reproduction technology adoption rate and suggested that farmer’s affiliation with organizations such as the Livestock Groups for Technological Validation and Transfer (GGAVATT), and its network position had a significant impact on the level of technological adoption. In the first stage of adoption, this work highlighted the importance of centralized models from the GGAVATT to the farmers, related to the knowledge and absorption dynamic capabilities. In a later stage, decentralized models through technological leaders are a priority, related to integration and innovation dynamic capabilities.
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Johnson, J. Bruce, Susan D. Allen, Jonathan Merten, Lewis Johnson, Daniel Pinkham, and Scott W. Reeve. "Standoff Methods for the Detection of Threat Agents: A Review of Several Promising Laser-Based Techniques." Journal of Spectroscopy 2014 (2014): 1–13. http://dx.doi.org/10.1155/2014/613435.
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Detection of explosives, explosive precursors, or other threat agents presents a number of technological challenges for optical sensing methods. Certainly detecting trace levels of threat agents against a complex background is chief among these challenges; however, the related issues of multiple target distances (from standoff to proximity) and sampling time scales (from passive mines to rapid rate of march convoy protection) for different applications make it unlikely that a single technique will be ideal for all sensing situations. A number of methods for spanning the range of optical sensor technologies exist which, when integrated, could produce a fused sensor system possessing a high level of sensitivity to threat agents and a moderate standoff real-time capability appropriate for portal screening of personnel or vehicles. In this work, we focus on several promising, and potentially synergistic, laser-based methods for sensing threat agents. For each method, we have briefly outlined the technique and report on the current level of capability.
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Burhan, Nik Ahmad Sufian, Razli Che Razak, Saifuzzaman Ibrahim, Muhamad Rosli Selamat, and Muhamad Ridhwan Rosli. "Social Classes of Intelligence, Economic Growth and Technological Achievement: Robust Regression and Outlier Detection." Journal of Interdisciplinary Economics 30, no. 2 (March 29, 2018): 148–63. http://dx.doi.org/10.1177/0260107918761923.
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A previous study has shown that the intellectual class, which is represented by the 95th percentile intelligence quotient (IQ) at a normal distribution, displayed the strongest impact upon economic growth. Meanwhile, those with average ability (50th percentile IQ) exhibited the second strongest impact, and followed by the non-intellectual class (5th percentile IQ). In addition, the researchers discovered that only the intellectual class was significant for technological progress. As such, this article re-analysed the dataset employed in prior study via robust regression. As a result, after eliminating several outliers, the levels of IQ for the intellectual class and the average ability group displayed equal impacts on economic growth, and the impacts were larger than that of non-intellectual. Furthermore, the IQ of the average ability group was significant for technological achievement, although not as strong as the intellectual class. Besides, the number of professional researchers employed in the research and development (R&D) sector did not reflect similar paramount effects as the impact of the average ability IQ in generating technological development. Thus, based on the conclusions drawn, this study suggests that the R&D sector should employ professionals who possess not only high academic qualifications, but also exceptional levels of cognitive skills, especially to spark new innovations. JEL: J24, O31, O47, Z13
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Thayalasekaran, Sreedhari, Leonardo Frazzoni, Giulio Antonelli, Lorenzo Fuccio, Franco Radaelli, Alida Andrealli, Carlo Senore, Alessandro Repici, Cesare Hassan, and Pradeep Bhandari. "Endoscopic technological innovations for neoplasia detection in organized colorectal cancer screening programs: a systematic review and meta-analysis." Gastrointestinal Endoscopy 92, no. 4 (October 2020): 840–47. http://dx.doi.org/10.1016/j.gie.2020.06.046.
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SM, Shashidhara, and Sangameswara P. Raju. "FPGA Based Embedded System Development for Rolling Bearings Fault Detection of Induction Motor." International Journal of Reconfigurable and Embedded Systems (IJRES) 2, no. 3 (November 1, 2013): 127. http://dx.doi.org/10.11591/ijres.v2.i3.pp127-134.
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Bearing fault diagnosis is crucial in condition monitoring of any rotating machine. Early fault detection in machines can save millions of dollars in maintenance cost. Different methods are used for fault analysis such as short time Fourier transforms (STFT), Wavelet analysis (WA), Model based analysis, cepstrum analysis etc. Recently, there have been outstanding technological developments related to digital systems, in both hardware and software. These innovations enable the development of new designing methodologies that aim to the ease the future modifications, upgrades and expansions of the system. This paper presents a study of rolling bearing fault diagnosis of induction motor based on reconfigurable logic. A case study using FPGA, its design, as well as its implementation and testing, are presented.
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Bannikova, Natalia, Natalia Telnova, and Victoria Markarova. "Innovation activity in agriculture and the issues of its assessment." Western Balkan Journal of Agricultural Economics and Rural Development 3, no. 1 (2021): 1–10. http://dx.doi.org/10.5937/wbjae2101001b.
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The article describes the level of innovative activities of Russian agricultural businesses based on currently accepted indicators and justifies the limitations for their application in agriculture, taking into account its peculiar features. As an example the article considers a large agro-holding, which conducts active innovative activities aimed at the development of precision agriculture. The article shows the potential of correlation-regression analysis for the detection of the influence of particular technological innovations on the obtained result, as well as the potential of timeseries analysis for the assessment of major agriculturally-significant climatic risks.
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Wang, Meng, Yirong Zhang, Ruijie Wang, Zhibin Wang, Bingyou Yang, and Haixue Kuang. "An Evolving Technology That Integrates Classical Methods with Continuous Technological Developments: Thin-Layer Chromatography Bioautography." Molecules 26, no. 15 (July 31, 2021): 4647. http://dx.doi.org/10.3390/molecules26154647.
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Thin-layer chromatography (TLC) bioautography is an evolving technology that integrates the separation and analysis technology of TLC with biological activity detection technology, which has shown a steep rise in popularity over the past few decades. It connects TLC with convenient, economic and intuitive features and bioautography with high levels of sensitivity and specificity. In this study, we discuss the research progress of TLC bioautography and then establish a definite timeline to introduce it. This review summarizes known TLC bioautography types and practical applications for determining antibacterial, antifungal, antitumor and antioxidant compounds and for inhibiting glucosidase, pancreatic lipase, tyrosinase and cholinesterase activity constitutes. Nowadays, especially during the COVID-19 pandemic, it is important to identify original, natural products with anti-COVID potential compounds from Chinese traditional medicine and natural medicinal plants. We also give an account of detection techniques, including in situ and ex situ techniques; even in situ ion sources represent a major reform. Considering the current technical innovations, we propose that the technology will make more progress in TLC plates with higher separation and detection technology with a more portable and extensive scope of application. We believe this technology will be diffusely applied in medicine, biology, agriculture, animal husbandry, garden forestry, environmental management and other fields in the future.
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Soler, L. S., D. E. Silva, C. Messias, T. C. Lima, B. M. P. Bento, J. J. de Souza, J. Doblas, D. Moraes, and C. Almeida. "PROMISING ADVANCES OF AMAZONIAN MONITORING SYSTEMS THROUGHOUT VANGUARD TECHNOLOGY AND SCIENTIFIC KNOWLEDGE." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B3-2021 (June 29, 2021): 843–49. http://dx.doi.org/10.5194/isprs-archives-xliii-b3-2021-843-2021.
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Abstract. PRODES and DETER project together turned 33 years-old with an undeniably contribution to the state-of-art in mapping and monitoring tropical deforestation in Brazil. Monitoring systems all over the world have taken advantage of big data repositories of remote sensing data as they are becoming freely available together with artificial intelligence. Thus, considering the advent of new generation remote sensing data hubs, online platforms of big data that can fill in spatial and temporal resolutions gaps in current deforestation mapping, this work aims to present recent innovations at INPE´s deforestation monitoring systems in Brazil and how they are gauging new realms of technological levels. Recent innovations at INPE´s monitoring systems are: 1) the development of TerraBrasilis platform of data access and analysis; 2) the adoption of new sensors and cloud detection strategies; 3) the complementary use of multi-sensor images; 4) the complementary adoption of SAR C-band images using cloud data to sample and process Sentinel-1. Future innovations are: 1) development of a Brazilian data cube to be used in deep learning techniques of image classification; 2) Routine uncertainty analysis of PRODES data. Automatization might fasten mapping process, but the real challenge is to succeed in automatization maintaining data quality and historical series. The hyper-availability of remote sensing data, the initiative of a Brazilian Data Cube and promising machine learning techniques applied to land cover change detection, allowed INPE to reinforce its central role in tropical forest monitoring.
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Lippi, Giuseppe, Mario Plebani, and Emmanuel Favaloro. "Technological Advances in the Hemostasis Laboratory." Seminars in Thrombosis and Hemostasis 40, no. 02 (January 17, 2014): 178–85. http://dx.doi.org/10.1055/s-0033-1364206.
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Automation is conventionally defined as the use of machines, control systems, and information technologies to optimize productivity. Although automation is now commonplace in several areas of diagnostic testing, especially in clinical chemistry and immunochemistry, the concept of extending this process to hemostasis testing has only recently been advanced. The leading drawbacks are still represented by the almost unique biological matrix because citrated plasma can only be used for clotting assays and few other notable exceptions, and by the highly specific pretreatment of samples, which is particularly distinct to other test systems. Despite these important limitations, a certain degree of automation is also now embracing hemostasis testing. The more relevant developments include the growing integration of routine hemostasis analyzers with track line systems and workcells, the development of specific instrumentation tools to enhance reliability of testing (i.e., signal detection with different technologies to increase test panels, plasma indices for preanalytical check of interfering substances, failure patterns sensors for identifying insufficient volume, clots or bubbles, cap-piercing for enhancing operator safety, automatic reflex testing, automatic redilution of samples, and laser barcode readers), preanalytical features (e.g., positive identification, automatic systems for tube(s) labeling, transillumination devices), and postphlebotomy tools (pneumatic tube systems for reducing turnaround time, sample transport boxes for ensuring stability of specimens, monitoring systems for identifying unsuitable conditions of transport). Regardless of these important innovations, coagulation/hemostasis testing still requires specific technical and clinical expertise, not only in terms of measurement procedures but also for interpreting and then appropriately utilizing the derived information. Thus, additional and special caution has to be used when designing projects of automation that include coagulation/hemostasis testing because peculiar and particular requirements must be taken into account.
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Prabhakaran, Dorairaj, Vamadevan S. Ajay, and Nikhil Tandon. "Strategic Opportunities for Leveraging Low-cost, High-impact Technological Innovations to Promote Cardiovascular Health in India." Ethnicity & Disease 29, Suppl 1 (February 21, 2019): 145–52. http://dx.doi.org/10.18865//ed.29.s1.145.
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Accelerated epidemiological transition in India over the last 40 years has resulted in a dramatic increase in the burden of cardiovascular diseases and the related risk factors of diabetes and hypertension. This increase in disease burden has been accompanied by pervasive health disparities associated with low disease detection rates, inadequate awareness, poor use of evidence-based interventions, and low adherence rates among patients in rural regions in India and those with low socioeconomic status.Several research groups in India have developed innovative technologies and care-delivery models for screening, diagnosis, clinical management, remote-monitoring, self-management, and rehabilitation for a range of chronic conditions. These innovations can leverage advances in sensor technology, genomic tools, artificial intelligence, big-data analytics, and so on, for improving access to and delivering quality and affordable personalized medicine in primary care. In addition, several health technology start-ups are entering this booming market that is set to grow rapidly. Innovations outside biomedical space (eg, protection of traditional wisdom in diet, lifestyle, yoga) are equally important and are part of a comprehensive solution.Such low-cost, culturally tailored, robust innovations to promote health and reduce disparities require partnership among multi-sectors including academia, industry, civil society, and health systems operating in a conducive policy environment that fosters adequate public and private investments.In this article, we present the unique opportunity for India to use culturally tailored, low-cost, high-impact technological innovations and strategies to ameliorate the perennial challenges of social, policy, and environmental challenges including poverty, low educational attainment, culture, and other socioeconomic factors to promote cardiovascular health and advance health equity. Ethn Dis. 2019;29(Suppl 1):145- 152; doi:10.18865/ed.29.S1.145.
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Prabhakaran, Dorairaj, Vamadevan S. Ajay, and Nikhil Tandon. "Strategic Opportunities for Leveraging Low-cost, High-impact Technological Innovations to Promote Cardiovascular Health in India." Ethnicity & Disease 29, Suppl 1 (February 21, 2019): 145–52. http://dx.doi.org/10.18865/ed.29.s1.145.
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Accelerated epidemiological transition in India over the last 40 years has resulted in a dramatic increase in the burden of cardiovascular diseases and the related risk factors of diabetes and hypertension. This increase in disease burden has been accompanied by pervasive health disparities associated with low disease detection rates, inadequate awareness, poor use of evidence-based interventions, and low adherence rates among patients in rural regions in India and those with low socioeconomic status.Several research groups in India have developed innovative technologies and care-delivery models for screening, diagnosis, clinical management, remote-monitoring, self-management, and rehabilitation for a range of chronic conditions. These innovations can leverage advances in sensor technology, genomic tools, artificial intelligence, big-data analytics, and so on, for improving access to and delivering quality and affordable personalized medicine in primary care. In addition, several health technology start-ups are entering this booming market that is set to grow rapidly. Innovations outside biomedical space (eg, protection of traditional wisdom in diet, lifestyle, yoga) are equally important and are part of a comprehensive solution.Such low-cost, culturally tailored, robust innovations to promote health and reduce disparities require partnership among multi-sectors including academia, industry, civil society, and health systems operating in a conducive policy environment that fosters adequate public and private investments.In this article, we present the unique opportunity for India to use culturally tailored, low-cost, high-impact technological innovations and strategies to ameliorate the perennial challenges of social, policy, and environmental challenges including poverty, low educational attainment, culture, and other socioeconomic factors to promote cardiovascular health and advance health equity. Ethn Dis. 2019;29(Suppl 1):145- 152; doi:10.18865/ed.29.S1.145.
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Hasanaliyeva, Gultakin, Melissa Si Ammour, Thaer Yaseen, Vittorio Rossi, and Tito Caffi. "Innovations in Disease Detection and Forecasting: A Digital Roadmap for Sustainable Management of Fruit and Foliar Disease." Agronomy 12, no. 7 (July 19, 2022): 1707. http://dx.doi.org/10.3390/agronomy12071707.
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In a quickly growing world, there is increasing demand for a secure food supply, a reduction in the intensive use of natural resources, and the enhancement of sustainability for future long-term maintenance. In this regard, plant health, including fruit and foliar diseases, which can cause a vast amount of crop loss, potentially has a huge effect on food security. The integration of new, innovative technological tools and data management techniques into the traditional agricultural practices is a promising approach to combat future food shortages. The use of the same principles of precision agriculture to “do the right thing, at the right time, in the right place” will allow for providing detailed, real-time information that will help farmers to protect their crops and choose healthier, as well as more productive, farming methods. The presented narrative review reports on several items of innovation, including monitoring and surveillance, diagnostic, and decision-making tools, with a specific focus devoted to digital solutions that can be applied in agriculture in order to improve the quality and the speed of the decision-making process and specifically, to set up a digital collaboration that can be crucial under certain circumstances to reach sustainability goals, particularly in the Near East and North Africa (NENA) Region, where an effective and rapid solution for phytosanitary control is needed.
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Zulkarnaen. "SMART SPRAYER DISINSFEKTAN BERBASIS MIKROKONTROLER ATMEGA328." TEKNIMEDIA: Teknologi Informasi dan Multimedia 1, no. 1 (May 23, 2020): 22–27. http://dx.doi.org/10.46764/teknimedia.v1i1.10.
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During the pandemic covid 19 we are experiencing at this time, various technological innovations are created as the first step in breaking the chain of corona virus. One way that can be implemented in breaking the covid pandemic chain of 19, especially in public areas is by spraying a disinfectant liquid that can be done continuously. Optimization of spraying disinfectant liquid can be done by utilizing technology that is able to work automatically. This research makes a disinfectant sprayer chamber as a technological innovation. Automation of disinfectant sprayers can be done by utilizing the ATemega328 microcontroller as an automatic machine to activate the sprayer pump based on the detection of objects that are around it with the help of an ultrasonic sensor. Determination of the distance reading of the object greatly determines the performance of the ultrasonic sensor in providing input to the microcontroller. The smart sprayer system is capable of activating a 12Volt DC pump with a voltage of 5 amperes. This smart sprayer disinfectant control system can be applied to the gate or hallway at the center of the crowd.
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Sharma, Himani, and Navdeep Kanwal. "Video interframe forgery detection: Classification, technique & new dataset." Journal of Computer Security 29, no. 5 (August 26, 2021): 531–50. http://dx.doi.org/10.3233/jcs-200105.
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Multimedia communication as well as other related innovations are gaining tremendous growth in the modern technological era. Even though digital content has traditionally proved to be a piece of legitimate evidence. But the latest technologies have lessened this trust, as a variety of video editing tools have been developed to modify the original video. Therefore, in order to resolve this problem, a new technique has been proposed for the detection of duplicate video sequences. The present paper utilizes gray values to extract Hu moment features in the current frame. These features are further used for classification of video as authentic or forged. Afterwards there was also need to validate the proposed technique using training and test dataset. But the scarcity of training and test datasets, however, is indeed one of the key problems to validate the effectiveness of video tampering detection techniques. In this perspective, the Video Forensics Library for Frame Duplication (VLFD) dataset has been introduced for frame duplication detection purposes. The proposed dataset is made of 210 native videos, in Ultra-HD and Full-HD resolution, captured with different cameras. Every video is 6 to 15 seconds in length and runs at 30 frames per second. All the recordings have been acquired in three different scenarios (indoor, outdoor, nature) and in landscape mode(s). VLFD includes both authentic and manipulated video files. This dataset has been created as an initial repository for manipulated video and enhanced with new features and new techniques in future.
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Gatuha, George, and Tao Jiang. "Android Based Naive Bayes Probabilistic Detection Model for Breast Cancer and Mobile Cloud Computing: Design and Implementation." International Journal of Engineering Research in Africa 21 (December 2015): 197–208. http://dx.doi.org/10.4028/www.scientific.net/jera.21.197.
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Mobile phone technology initiatives are revolutionizing healthcare delivery in Africa and other developing countries. M-health services have transformed maternal health, management of communicable diseases such as Ebola and prevention of chronic diseases. Technological innovations in m-health have improved healthcare efficiency and effectiveness as well as extending health services to remote locations in rural African communities. This paper describes a ubiquitous m- health system that is based on the user centric paradigm of Mobile Cloud Computing (MCC) and android medical-data mining techniques. The development of ultra-fast 4G mobile networks and sophisticated smartphones and tablets has brought the cloud computing paradigm to the mobile domain.The system’s client side is based on an android platform for breast bio-data collection; a data mining technique based on Naïve Bayes probabilistic classifier (NBC) algorithm for predicting malignancy in breast tissue and the server-side MCC data storage. Experimental results indicate that the android Naïve Bayes classifier achieves 96.4% accuracy on Wisconsin Breast Cancer (WBC) data from UCI machine learning database.
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Et.al, Anuraag Velamati. "Traffic Sign Classification Using Convolutional Neural Networks and Computer Vision." Turkish Journal of Computer and Mathematics Education (TURCOMAT) 12, no. 3 (April 11, 2021): 4244–50. http://dx.doi.org/10.17762/turcomat.v12i3.1715.
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The world is quickly and continuously advancing towards better technological advancements that will make life quite easier for us, human beings [22]. Humans are looking for more interactive and advanced ways to improve their learning. One such dream is making a machine think like a computer, which lead to innovations like AI and deep learning [25]. The world is running at a higher pace in the domain of AI, deep learning, robotics and machine learning Using this knowledge and technology, we could develop anything right now [36]. As a part of sub-domain, the introduction of Convolution Neural Networks made deep learning extensively strong in the domain of image classification and detection [1]..The research that we have conducted is one of its kind. Our research used Convolution Neural Network, TensorFlow and Keras.
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Shashidhar, R., B. N. Arunakumari, A. S. Manjunath, Neelu Jyoti Ahuja, Vinh Truong Hoang, Kiet Tran-Trung, and Assaye Belay. "Computer Vision and the IoT-Based Intelligent Road Lane Detection System." Mathematical Problems in Engineering 2022 (September 22, 2022): 1–8. http://dx.doi.org/10.1155/2022/4755113.
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Many technical improvements have recently been made in the field of road safety, as accidents have been increasing at an alarming rate, and one of the major causes of such accidents is a driver’s lack of attention. To lower the incidence of accidents and keep safe, technological innovations should be made. One way to accomplish this is with IoT-based lane detection systems, which function by recognizing the lane borders on the road and then prompting the turning of the road. Because of the various road conditions that one can encounter when driving, lane detection is a difficult problem. An image processing-based method for lane detection has been proposed in this paper. In this regard, each frame from the video is extracted and image processing techniques are applied for the detection of lanes. The frame which is extracted from the video is then subjected to a Gaussian filter for the removal of noise. Subsequently, color masking has been used to process the frame to detect only the road lanes, whose edges are obtained by applying the canny edge detection algorithm. Afterward, the Hough transform has been applied to the region of interest to extrapolate the lines. Finally, the path is plotted along the lines, and turns are predicted by using the concept of vanishing points.
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Aksenov, Aleksey. "MANAGING INNOVATION WITH ARTIFICIAL INTELLIGENCE." Actual directions of scientific researches of the XXI century: theory and practice 8, no. 2 (December 29, 2020): 47–53. http://dx.doi.org/10.34220/2308-8877-2020-8-2-47-53.
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Artificial intelligence is changing companies and how they manage innovation. Rapid technological development and the replacement of human labor with artificial intelligence can force management to rethink the entire innovation process of the company. Using the ideas of the Carnegie School and the behavioral theory of the firm, the implications for innovation management of artificial intelligence technologies and artificial intelligence systems based on machine learning were considered. A diagram is presented showing the extent to which artificial intelligence can replace humans. It is shown what aspects should be taken into account when transforming into a digital organization of innovations. It is noted that artificial intelligence plays a constructive role where the time-tested advantages of innovation management resources are suppressed, impossible due to digitization. The clear potential of artificial intelligence lies in creating a more systematic approach by integrating artificial intelligence into organizations seeking to innovate. The results of the study point to areas in which artificial intelligence systems can already be fruitfully applied in organizational innovation, namely, in cases where the development of new innovations is primarily constrained by the limitations of information processing. Artificial intelligence systems that rely on anomaly detection, for example, can be useful when firms grapple with processing constraints in search of new opportunities.
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Khasawneh, Natheer, Esraa Faouri, and Mohammad Fraiwan. "Automatic Detection of Tomato Diseases Using Deep Transfer Learning." Applied Sciences 12, no. 17 (August 24, 2022): 8467. http://dx.doi.org/10.3390/app12178467.
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Global food production is being strained by extreme weather conditions, fluctuating temperatures, and geopolitics. Tomato is a staple agricultural product with tens of millions of tons produced every year worldwide. Thus, preserving the tomato plant from diseases will go a long way in reducing economical loss and boost output. Technological innovations have great potential in facilitating disease detection and control. More specifically, artificial intelligence algorithms in the form of deep learning methods have established themselves in many real-life applications in a wide range of disciplines (e.g., medicine, agriculture, or facial recognition, etc.). In this paper, we aim at applying deep transfer learning in the classification of nine tomato diseases (i.e., bacterial spot, early blight, late blight, leaf mold, mosaic virus, septoria leaf spot, spider mites, target spot, and yellow leaf curl virus) in addition to the healthy state. The approach in this work uses leaf images as input, which is fed to convolutional neural network models. No preprocessing, feature extraction, or image processing is required. Moreover, the models are based on transfer learning of well-established deep learning networks. The performance was extensively evaluated using multiple strategies for data split and a number of metrics. In addition, the experiments were repeated 10 times to account for randomness. The ten categories were classified with mean values of 99.3% precision, 99.2% F1 score, 99.1% recall, and 99.4% accuracy. Such results show that it is highly feasible to develop smartphone-based applications that can aid plant pathologists and farmers to quickly and accurately perform disease detection and subsequent control.
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Silva, Gonçalo, Jenny Tomlinson, Nawaporn Onkokesung, Sarah Sommer, Latifa Mrisho, James Legg, Ian P. Adams, et al. "Plant pest surveillance: from satellites to molecules." Emerging Topics in Life Sciences 5, no. 2 (March 15, 2021): 275–87. http://dx.doi.org/10.1042/etls20200300.
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Plant pests and diseases impact both food security and natural ecosystems, and the impact has been accelerated in recent years due to several confounding factors. The globalisation of trade has moved pests out of natural ranges, creating damaging epidemics in new regions. Climate change has extended the range of pests and the pathogens they vector. Resistance to agrochemicals has made pathogens, pests, and weeds more difficult to control. Early detection is critical to achieve effective control, both from a biosecurity as well as an endemic pest perspective. Molecular diagnostics has revolutionised our ability to identify pests and diseases over the past two decades, but more recent technological innovations are enabling us to achieve better pest surveillance. In this review, we will explore the different technologies that are enabling this advancing capability and discuss the drivers that will shape its future deployment.
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Bhattacharjee, Kasturi, Obaidur Rehman, Vatsalya Venkatraman, and Harsha Bhattacharjee. "Artificial intelligence in cataract: What’s new?" Global Journal of Cataract Surgery and Research in Ophthalmology 1 (April 29, 2022): 36–42. http://dx.doi.org/10.25259/gjcsro_4_2022.
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Artificial intelligence (AI) is a technological advancement that provides thinking and processing capacity to machines. It is a complex technology with multiple algorithms and formulas. AI has transformed the face of several industries, including the healthcare sector. Ophthalmology being a highly technology-driven branch of healthcare can benefit vastly from the application of AI. Newer technologies are cropping up with each passing day to enhance our diagnostic and management modalities. From huge machines, now, AI has even come down to applications on the small screen of smartphones. Through this study, we summarise the various AI-driven developments in the world of cataract that have occurred in the past 3 years. Ranging from cataract detection, cataract grading, IOL power calculation, to acting as an aid in the surgical arena, this study intends to cover all recent AI-based innovations and advancements.
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Aguila, Enrik T., Andrawus Beany, and Rajvinder Singh. "Advanced mucosal imaging in colonoscopy: technical details and clinical applications." Mini-invasive Surgery 6 (2022): 55. http://dx.doi.org/10.20517/2574-1225.2022.35.
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Over the past decades, the significant development in endoscopic imaging has revolutionized digestive endoscopy. Real-time optical diagnosis has become possible using different tools and techniques (dye-based and virtual chromoendoscopy) such as narrow band imaging, flexible spectral imaging color enhancement, i-Scan, blue-laser imaging and linked-color imaging. Polyp detection and characterization, and prediction of depth of invasion of colorectal cancers have improved remarkably. Confocal laser endomicroscopy and endocytoscopy have allowed the evaluation of lesions on a cellular level. Not far from the horizon are newer technological innovations such as artificial intelligence and texture and color enhancement imaging that are now being studied for their potential to further improve mucosal visualization, optical diagnosis and virtual histology. This review gives an overview of image-enhanced endoscopy (IEE) and discusses its clinical applications and future directions in the lower gastrointestinal (GI) tract.
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Singh, Anoop, Aamir Ahmed, Asha Sharma, and Sandeep Arya. "Graphene and Its Derivatives: Synthesis and Application in the Electrochemical Detection of Analytes in Sweat." Biosensors 12, no. 10 (October 21, 2022): 910. http://dx.doi.org/10.3390/bios12100910.
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Wearable sensors and invasive devices have been studied extensively in recent years as the demand for real-time human healthcare applications and seamless human–machine interaction has risen exponentially. An explosion in sensor research throughout the globe has been ignited by the unique features such as thermal, electrical, and mechanical properties of graphene. This includes wearable sensors and implants, which can detect a wide range of data, including body temperature, pulse oxygenation, blood pressure, glucose, and the other analytes present in sweat. Graphene-based sensors for real-time human health monitoring are also being developed. This review is a comprehensive discussion about the properties of graphene, routes to its synthesis, derivatives of graphene, etc. Moreover, the basic features of a biosensor along with the chemistry of sweat are also discussed in detail. The review mainly focusses on the graphene and its derivative-based wearable sensors for the detection of analytes in sweat. Graphene-based sensors for health monitoring will be examined and explained in this study as an overview of the most current innovations in sensor designs, sensing processes, technological advancements, sensor system components, and potential hurdles. The future holds great opportunities for the development of efficient and advanced graphene-based sensors for the detection of analytes in sweat.
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Bwambok, David K., Noureen Siraj, Samantha Macchi, Nathaniel E. Larm, Gary A. Baker, Rocío L. Pérez, Caitlan E. Ayala, et al. "QCM Sensor Arrays, Electroanalytical Techniques and NIR Spectroscopy Coupled to Multivariate Analysis for Quality Assessment of Food Products, Raw Materials, Ingredients and Foodborne Pathogen Detection: Challenges and Breakthroughs." Sensors 20, no. 23 (December 7, 2020): 6982. http://dx.doi.org/10.3390/s20236982.
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Quality checks, assessments, and the assurance of food products, raw materials, and food ingredients is critically important to ensure the safeguard of foods of high quality for safety and public health. Nevertheless, quality checks, assessments, and the assurance of food products along distribution and supply chains is impacted by various challenges. For instance, the development of portable, sensitive, low-cost, and robust instrumentation that is capable of real-time, accurate, and sensitive analysis, quality checks, assessments, and the assurance of food products in the field and/or in the production line in a food manufacturing industry is a major technological and analytical challenge. Other significant challenges include analytical method development, method validation strategies, and the non-availability of reference materials and/or standards for emerging food contaminants. The simplicity, portability, non-invasive, non-destructive properties, and low-cost of NIR spectrometers, make them appealing and desirable instruments of choice for rapid quality checks, assessments and assurances of food products, raw materials, and ingredients. This review article surveys literature and examines current challenges and breakthroughs in quality checks and the assessment of a variety of food products, raw materials, and ingredients. Specifically, recent technological innovations and notable advances in quartz crystal microbalances (QCM), electroanalytical techniques, and near infrared (NIR) spectroscopic instrument development in the quality assessment of selected food products, and the analysis of food raw materials and ingredients for foodborne pathogen detection between January 2019 and July 2020 are highlighted. In addition, chemometric approaches and multivariate analyses of spectral data for NIR instrumental calibration and sample analyses for quality assessments and assurances of selected food products and electrochemical methods for foodborne pathogen detection are discussed. Moreover, this review provides insight into the future trajectory of innovative technological developments in QCM, electroanalytical techniques, NIR spectroscopy, and multivariate analyses relating to general applications for the quality assessment of food products.
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Nozari, Hamed, Agnieszka Szmelter-Jarosz, and Javid Ghahremani-Nahr. "Analysis of the Challenges of Artificial Intelligence of Things (AIoT) for the Smart Supply Chain (Case Study: FMCG Industries)." Sensors 22, no. 8 (April 11, 2022): 2931. http://dx.doi.org/10.3390/s22082931.
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In today’s competitive world, supply chain management is one of the fundamental issues facing businesses that affects all an organization’s activities to produce products and provide services needed by customers. The technological revolution in supply chain logistics is experiencing a significant wave of new innovations and challenges. Despite the current fast digital technologies, customers expect the ordering and delivery process to be faster, and as a result, this has made it easier and more efficient for organizations looking to implement new technologies. “Artificial Intelligence of Things (AIoT)”, which means using the Internet of Things to perform intelligent tasks with the help of artificial intelligence integration, is one of these expected innovations that can turn a complex supply chain into an integrated process. AIoT innovations such as data sensors and RFID (radio detection technology), with the power of artificial intelligence analysis, provide information to implement features such as tracking and instant alerts to improve decision making. Such data can become vital information to help improve operations and tasks. However, the same evolving technology with the presence of the Internet and the huge amount of data can pose many challenges for the supply chain and the factors involved. In this study, by conducting a literature review and interviewing experts active in FMCG industries as an available case study, the most important challenges facing the AIoT-powered supply chain were extracted. By examining these challenges using nonlinear quantitative analysis, the importance of these challenges was examined and their causal relationships were identified. The results showed that cybersecurity and a lack of proper infrastructure are the most important challenges facing the AIoT-based supply chain.
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Ali, Saqib, Saqlain Bin Syed Gilani, Juzer Shabbir, Khalid S. Almulhim, Amr Bugshan, and Imran Farooq. "Optical coherence tomography’s current clinical medical and dental applications: a review." F1000Research 10 (April 22, 2021): 310. http://dx.doi.org/10.12688/f1000research.52031.1.
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Optical coherence tomography (OCT) is a non-invasive investigative technique that is used to obtain high-resolution three-dimensional (3D) images of biological structures. This method is useful in diagnosing diseases of specific organs like the eye, where a direct biopsy cannot be conducted. Since its inception, significant advancements have been made in its technology. Apart from its initial application in ophthalmology for retinal imaging, substantial technological innovations in OCT brought by the research community have enabled its utilization beyond its original scope and allowed its application in many new clinical areas. This review presents a summary of the clinical applications of OCT in the field of medicine (ophthalmology, cardiology, otology, and dermatology) and dentistry (tissue imaging, detection of caries, analysis of dental polymer composite restorations, imaging of root canals, and diagnosis of oral cancer). In addition, potential advantages and disadvantages of OCT are also discussed.
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PÁEZ-AVILÉS, CRISTINA, ESTEVE JUANOLA-FELIU, ISLAM BOGACHAN-TAHIRBEGI, MÓNICA MIR, MANEL GONZÁLEZ-PIÑERO, and JOSEP SAMITIER. "INNOVATION AND TECHNOLOGY TRANSFER OF MEDICAL DEVICES FOSTERED BY CROSS-DISCIPLINARY COMMUNITIES OF PRACTITIONERS." International Journal of Innovation Management 19, no. 06 (December 2015): 1540012. http://dx.doi.org/10.1142/s1363919615400125.
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Commercialisation of emerging technological innovations such as medical devices can be a time-consuming and lengthy process resulting in a market entrance failure. To tackle this general problem, major challenges are being analysed, principally focusing on the role of Communities of Practitioners (CoPs) in the process of effective transfer of high-value emerging technologies from academia to market. Taking a case study approach, this document describes the role of a cross-disciplinary CoP in the technology transfer process within a convergence scenario. The case presented is a sensor array for ischemia detection developed by different practitioners from diverse organisations: university, research institution, hospital, and a scientific park. The analysis also involves the innovation ecosystem where all stakeholders are taken into account. This study contributes to a better understanding of the managerial implications of CoP fostering technology transfer and innovation, principally focused on the current need for new biomedical technologies and tools.
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Kasap Cuceoglu, Muserref, Ozge Basaran, Ozge Soyer, and Seza Ozen. "Hypersensitivity to Biological Treatments in Juvenile Idiopathic Arthritis: How Should It Be Managed?" Journal of Clinical Medicine 11, no. 24 (December 8, 2022): 7291. http://dx.doi.org/10.3390/jcm11247291.
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Juvenile idiopathic arthritis (JIA) is one of the most frequent diseases in the practice of pediatric rheumatology. JIA treatments have been modified and improved with the use of biological drugs along with technological innovations. However, different types of hypersensitivity reactions to biological drugs have also been reported. Anaphylaxis and infusion reactions occurring during the intravenous infusion require a critical approach in the acute period. On the other hand, the detection of drug-related late-type reactions and the development of antibodies to the agent highlight the need for an understanding of the drug-induced etiology to prevent the patient from continuing the treatment with the culprit drug. The chronic disease process, concomitant immune dysregulation, and multiple drug use may result in these hypersensitivity reactions. In this review, the hypersensitivity reactions to the biological treatments used in patients with juvenile idiopathic arthritis and the management of these conditions are discussed.
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Laudicella, Riccardo, Lucia Baratto, Fabio Minutoli, Sergio Baldari, and Andrei Iagaru. "Malignant Cutaneous Melanoma: Updates in PET Imaging." Current Radiopharmaceuticals 13, no. 1 (March 13, 2020): 14–23. http://dx.doi.org/10.2174/1874471012666191015095550.
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Background: Cutaneous malignant melanoma is a neoplasm whose incidence and mortality are dramatically increasing. 18F-FDG PET/CT gained clinical acceptance over the past 2 decades in the evaluation of several glucose-avid neoplasms, including malignant melanoma, particularly for the assessment for distant metastases, recurrence and response to therapy. Objective: To describe the advancements of nuclear medicine for imaging melanoma with particular attention to 18F-FDG-PET and its current state-of-the-art technical innovations. Methods: A comprehensive search strategy was used based on SCOPUS and PubMed databases. From all studies published in English, we selected the articles that evaluated the technological insights of 18FFDG- PET in the assessment of melanoma. Results: State-of-the-art silicon photomultipliers based detectors (“digital”) PET/CT scanners are nowadays more common, showing technical innovations that may have beneficial implications for patients with melanoma. Steady improvements in detectors design and architecture, as well as the implementation of both software and hardware technology (i.e., TOF, point spread function, etc.), resulted in significant improvements in PET image quality while reducing radiotracer dose and scanning time. Conclusion: Recently introduced digital PET detector technology in PET/CT and PET/MRI yields higher intrinsic system sensitivity compared with the latest generation analog technology, enabling the detection of very small lesions with potential impact on disease outcome.
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Karim, Jihan Audini. "Molecular dan Genomic Biomarker sebagai Deteksi Dini pada Diagnosis Kanker Prostat." Jurnal Ilmiah Kedokteran Wijaya Kusuma 9, no. 2 (October 1, 2020): 156. http://dx.doi.org/10.30742/jikw.v9i2.803.
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Prostate cancer is a noncutaneous malignancy in men, a heterogeneous disease with varying clinical outcomes. The modern clinical approach to prostate cancer emphasizes the need for treatment to avoid overdiagnosis and overtreatment. Advances in understanding of the pathogenesis of prostate cancer, coupled with technological innovations, have facilitated the development and validation of a number of molecular biomarkers, representing a variety of tested macromolecules from a wide variety of patient samples, to aid clinical management of prostate cancer, including early detection, diagnosis, prognostication, and selection. targeted therapy. Prostate cancer is asymptomatic in the early stages of the disease, there are various clinical-pathological signs and disease progression, and is characterized mostly by indolent cancer types. Therefore, it is imperative to develop individualized approaches for early detection, disease stratification (indolent vs. aggressive) and prediction of treatment response for prostate cancer. This article is a review article in which researchers review the current state of use of genomic biomarkers for early detection of prostate cancer, demonstrating the function of molecular biomarkers in clinical practice. The result of this review article is that the available genomic and proteomic tests can increase the predictive value of the PCa risk classification system based on clinical variables.
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Iqbal, Umair, Muhammad Zain Bin Riaz, Jiahong Zhao, Johan Barthelemy, and Pascal Perez. "Drones for Flood Monitoring, Mapping and Detection: A Bibliometric Review." Drones 7, no. 1 (January 1, 2023): 32. http://dx.doi.org/10.3390/drones7010032.
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Floods are one of the most often occurring and damaging natural hazards. They impact the society on a massive scale and result in significant damages. To reduce the impact of floods, society needs to keep benefiting from the latest technological innovations. Drones equipped with sensors and latest algorithms (e.g., computer vision and deep learning) have emerged as a potential platform which may be useful for flood monitoring, mapping and detection activities in a more efficient way than current practice. To better understand the scope and recent trends in the domain of drones for flood management, we performed a detailed bibliometric analysis. The intent of performing the bibliometric analysis waws to highlight the important research trends, co-occurrence relationships and patterns to inform the new researchers in this domain. The bibliometric analysis was performed in terms of performance analysis (i.e., publication statistics, citations statistics, top publishing countries, top publishing journals, top publishing institutions, top publishers and top Web of Science (WoS) categories) and science mapping (i.e., citations by country, citations by journals, keyword co-occurrences, co-authorship, co-citations and bibliographic coupling) for a total of 569 records extracted from WoS for the duration 2000–2022. The VOSviewer open source tool has been used for generating the bibliographic network maps. Subjective discussions of the results explain the obtained trends from the bibliometric analysis. In the end, a detailed review of top 28 most recent publications was performed and subjected to process-driven analysis in the context of flood management. The potential active areas of research were also identified for future research in regard to the use of drones for flood monitoring, mapping and detection activities.
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Prezzi, Jairo A. "TRENDS IN PIPELINE LEAK DETECTION SYSTEMS USING SONIC TECHNOLOGY." International Oil Spill Conference Proceedings 2008, no. 1 (May 1, 2008): 211–15. http://dx.doi.org/10.7901/2169-3358-2008-1-211.
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ABSTRACT Acoustic sensing is a relatively well known method for detecting leaks, particularly in transport pipelines. This methodology is based on the rarefaction phenomenon which occurs around the leak spot as a result of a sudden rupture of the pipe wall. The physical forces involved in the phenomenon generate a pressure disturbance that propagates through the fluid, upstream and downstream the pipe. The key feature behind acoustic technology, when applied to LDS, is the systems capability to monitor pressure disturbances and accurately recognize and pinpoint characteristic “leak waveforms” superimposed on the background noise. This is usually achieved by a combination of mechanical, hardware and software filtering techniques. Although real applications have demonstrated the effectiveness of acoustic technology over a quite broad range of scenarios, it has experienced few innovations along the past years. The relative technological stagnation and the experience achieved in several LDS installations in Brazil, encouraged Aselco, a Brazilian company focused on LDS applications, to invest in developing new strategies around the classical acoustic concept. The R&D project started in early 2006 jointly with NETeF, Thermal and Fluids Engineering Centre, at University of São Paulo at São Carlos. A 1. 2Km pipeline was built at NETeF'S lab in order to simulate leaks under mono or multiphase flow conditions. Among the project goals was the development of a new generation of systems dedicated to leak detection encompassing more elaborated algorithms to identify leak acoustic signatures. The core R&D is still centered on the acoustic concept, but under a different approach such as DSP-Digital Signal Processing, pattern recognition through neural network analysis. Another line of development is toward multivariate systems, which bring together both acoustic and hydraulic modeling algorithms running on the same platform. The experimental data obtained, proposed system architecture and characteristics are hereby discussed. Also, the prospective aspects and application of the new technology are objects of analysis.
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Asari, M. Sofyan, Desyderius Minggu, and Isa Mahfudi. "The IMPLEMENTATION OF SYSTEM DOOR ACCES USING FACE RECOGNITION AND FINGER PRINT FOR MUNITIONS WAREHOUSE WITH A BASE HAAR CASSCADE." Jurnal Telkommil 2, Oktober (October 25, 2021): 75–81. http://dx.doi.org/10.54317/kom.v2ioktober.184.
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Abstract: Technology in the military world has been growing with the existence of technological innovations that are used to secure munitions warehouses. This is done to reduce the negligence of the munitions warehouse guard personnel if they lose the key from the munitions warehouse it can be monitored in real-time to find out who is around the munitions warehouse door. Thus, face recognition and fingerprint technology were created as a system for securing munitions warehouses, as well as the function is to be a CCTV. So, they can be monitored in real-time. This research method uses an experimental method to obtain quantitative data to prove the hypothesis data that use the Haar Cascade. The results of this study indicate that this security system has a very important role to limit access to and from the munitions warehouse and reduce the occurrence of theft or misuse of munitions. In the tests carried out, the minimum detection distance was 20 cm and the maximum distance that was able to detect was 110 cm. this is influenced by the focus of the camera and testing of the intensity of light in the morning, afternoon, evening, and night can be detected except detection at night without light and must use a fingerprint.
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Putra, Arie Setya, Hamdan Sukri, and Khozainuz Zuhri. "Sistem Monitoring Realtime Jaringan Irigasi Desa (JIDES) Dengan Konsep Jaringan Sensor Nirkabel." IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) 8, no. 2 (October 31, 2018): 221. http://dx.doi.org/10.22146/ijeis.39783.
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Self-sufficiency programs in the new government era program to regain food self-sufficiency that was once achieved. This is found in one of the new government initiatives, namely to realize national independence by mobilizing strategic sectors of the domestic economy, one of which is in the agricultural sector through efforts to build and realize food sovereignty. Based on this and in an effort to realize food sovereignty, the author made technological innovations in the form of prototype design of the village-based irrigation network monitoring system so that it can be accessed from various types of devices and can be accessed anywhere while the technology developed uses a single board computer (SBC) with sensor devices that have a detection distance of 2–300 cm and with a network model based on mesh topology which has a transmission distance of approximately 1200 meters outdoor between node points. Data transmission results between node points indicate that the water level data update time is every 60 seconds with the sending time to the server database on average every 60 seconds.
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Kiohara Acyoli Bastos, Paulo Henrique, Felipe Streitenberger Ivo, and Olympio Lucchini Coutinho. "Microwave photonic radar warning receiver: airborne antenna over fiber optic." Revista Brasileira de Aplicações de Vácuo 39, no. 3 (December 28, 2020): 224–32. http://dx.doi.org/10.17563/rbav.v39i3.1183.
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Electronic warfare had great importance mainly in the Second World War. Radar was one of the greatest inventions in the area at that time, reinventing the way war was viewed until then. Nowadays, modern combat aircraft has sophisticated warfare systems. One of them is known as radar warning receiver (RWR), responsible for alerting pilots to possible radar detection and guiding the direction in which it is being radiated. Technological innovations allowed the interaction of the microwave and optoelectronics area, leading to an area known as microwave photonics (MWP). This article presents a photonic link to replace the copper cables used by RWR systems, applying photonic technology in order to improve performance and benefit from the intrinsic characteristics that optical fiber offers to the system, offering a totally passive remote system, in which only one phase modulator is connected to the RWR antenna. The results obtained for a totally photonic link by experiment were satisfactory. As expected, a gain above the unit was obtained. However, the observed noise figure was higher than expected, which ended up resulting in a lower signal noise ratio.
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Bourou, Stavroula, Andreas El Saer, Terpsichori-Helen Velivassaki, Artemis Voulkidis, and Theodore Zahariadis. "A Review of Tabular Data Synthesis Using GANs on an IDS Dataset." Information 12, no. 9 (September 14, 2021): 375. http://dx.doi.org/10.3390/info12090375.
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Recent technological innovations along with the vast amount of available data worldwide have led to the rise of cyberattacks against network systems. Intrusion Detection Systems (IDS) play a crucial role as a defense mechanism in networks against adversarial attackers. Machine Learning methods provide various cybersecurity tools. However, these methods require plenty of data to be trained efficiently, which may be hard to collect or to use due to privacy reasons. One of the most notable Machine Learning tools is the Generative Adversarial Network (GAN), and it has great potential for tabular data synthesis. In this work, we start by briefly presenting the most popular GAN architectures, VanillaGAN, WGAN, and WGAN-GP. Focusing on tabular data generation, CTGAN, CopulaGAN, and TableGAN models are used for the creation of synthetic IDS data. Specifically, the models are trained and evaluated on an NSL-KDD dataset, considering the limitations and requirements that this procedure needs. Finally, based on certain quantitative and qualitative methods, we argue and evaluate the most prominent GANs for tabular network data synthesis.
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Pulungan, Ali Basrah, and Zhafranul Nafis. "Rancangan Alat Pendeteksi Benda dengan Berdasarkan Warna, Bentuk, dan Ukuran dengan Webcam." JTEIN: Jurnal Teknik Elektro Indonesia 2, no. 1 (February 11, 2021): 49–54. http://dx.doi.org/10.24036/jtein.v2i1.111.
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Along with the times, technology is also developing so rapidly, one of the innovations in technological development is the use of webcams. the use of a webcam can be developed as a sensor in detecting an object through several stages of image processing. The use of a webcam aims to simplify an automation system so that it can be used to perform several tasks at once. Therefore, the author intends to design and manufacture an object detector with measurement parameters of the object's color, shape and size. This tool uses a webcam as a sensing sensor, and uses programming in PYTHON to recognize objects to be detected, and uses a servo motor to drive object actuators. The results of this tool have been tested and are able to detect objects properly based on predetermined color, shape and size. This tool is also able to separate objects that meet specifications from objects that do not meet specifications. Object detection using a webcam and an object separating actuator can work well.
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Nakajima, Tomohiko, Yuki Fujio, Tohru Sugahara, and Tetsuo Tsuchiya. "Flexible Ceramic Film Sensors for Free-Form Devices." Sensors 22, no. 5 (March 3, 2022): 1996. http://dx.doi.org/10.3390/s22051996.
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Recent technological innovations, such as material printing techniques and surface functionalization, have significantly accelerated the development of new free-form sensors for next-generation flexible, wearable, and three-dimensional electronic devices. Ceramic film sensors, in particular, are in high demand for the production of reliable flexible devices. Various ceramic films can now be formed on plastic substrates through the development of low temperature fabrication processes for ceramic films, such as photocrystallization and transferring methods. Among flexible sensors, strain sensors for precise motion detection and photodetectors for biomonitoring have seen the most research development, but other fundamental sensors for temperature and humidity have also begun to grow. Recently, flexible gas and electrochemical sensors have attracted a lot of attention from a new real-time monitoring application that uses human breath and perspiration to accurately diagnose presymptomatic states. The development of a low-temperature fabrication process of ceramic film sensors and related components will complete the chemically stable and reliable free-form sensing devices by satisfying the demands that can only be addressed by flexible metal and organic components.
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Teppati Losè, L., F. Matrone, F. Chiabrando, F. Giulio Tonolo, A. Lingua, and P. Maschio. "NEW DEVELOPMENTS IN LIDAR UAS SURVEYS. PERFORMANCE ANALYSES AND VALIDATION OF THE DJI ZENMUSE L1." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B1-2022 (May 30, 2022): 415–22. http://dx.doi.org/10.5194/isprs-archives-xliii-b1-2022-415-2022.
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Abstract. Thanks to the latest technological developments LiDAR (Light Detection And Ranging) sensors are no longer an exclusive feature of manned airborne platforms but they are close to becoming a commercial solution in the UAS (Uncrewed Aerial Systems) domain. The release on the market of the Zenmuse L1 by DJI (Dà-Jiāng Innovations) is a step further in this direction, thanks also to a substantial work of enhancement made by the Chinese company not only on the hardware side, but also on the software one. The research presented in this work is focused on the use of the L1 LiDAR for the 3D survey of built heritage, analysing the results of different tests to highlight first considerations on its performances and the point cloud quality. Considering its recent release, this sensor is still yet to be thoroughly analysed and validated and its performances to be assessed. LiDAR data has been acquired on a selected test site, documented also with traditional Terrestrial Laser Scanner (TLS) and UAS photogrammetry. The latter techniques (supported also by a topographic survey) will thus be exploited to generate the ground reference and to assess the quality and accuracy of the L1 dataset.
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Shurupova, K. V., A. S. Abdel Fatah, and T. Yu Sklema. "Age discriminations in the workplace: impact differentiators." Uzhhorod National University Herald. Series: Law, no. 67 (January 16, 2022): 139–43. http://dx.doi.org/10.24144/2307-3322.2021.67.28.
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This article contains an analysis of international, national and labor legislation, respectively, in the field of discrimination on the grounds of age. Recommendations for improving legal regulation and application of practical innovations in this area are analyzed and introduced. Given these trends, the prevalence of discrimination in employment and not only on the basis of age, but also on many other factors, such as gender, social status or mental skills, which for many people this provision seems to some extent natural and correct, has allowed and has become a motivating factor in order to carefully study and pay attention to the factors that have increased the effectiveness of this fight against discrimination, the creation of a separate law enforcement act or regulation that will separately regulate discrimination in employment, as well as the development of certain thematic programs to form ideas and attitudes of people in the working team for different age groups, where additional attention will be paid to youth employment. The study also examines international experience in the attitude and methods of solving problems in the field of age discrimination, not only in the field of labor, but in general. The complexity and prevalence of the phenomenon has caused different views on the issue from both scientists and ours, so the paper defines the general concept of discrimination in the field of labor, assigned personal characteristics and separated by special characteristics from related legal categories, clarified methodological inequalities and imperfections that cause a cause-and-effect relationship with a negative indicator of combating this issue. A comparative research method on discrimination in employment on the basis of age, based on the experience of predecessors, namely the comparison of the then society in the modern technological society, where the problem of technological processes and new information resources is absent. In order to achieve a qualitative analysis of the issue, as the purpose of the work as a whole, special attention was paid to criticism and analysis of innovations in international standards of methodological prohibitions and rules to combat the above topic. The classification of types of non-discrimination in the field of labor, the analysis of the legal regulation of the mechanism of improvement of this problem, the special attention was paid to the detection and prevention of discriminatory manifestations in the field of labor in general.
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Permana, Iman. "PROTOTIPE RANCANG BANGUN PINTU BENDUNGAN OTOMATIS UNTUK IRIGASI PERTANIAN BERBASIS MIKROKONTROLER ARDUINO ATMEGA328." JURNAL FASILKOM 10, no. 2 (August 13, 2020): 97–102. http://dx.doi.org/10.37859/jf.v10i2.2086.
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Technology as a result of human inventions to facilitate the work of increasingly advanced human technology and the development of various kinds of innovations especially developments in the field of microcontroller technological inventions penetrated various aspects ranging from transportation medicine and agriculture The large number of residents who use hydropower dams as water storage Open and close water dam gates automatically are buildings and structures that can function to open and close the flow of water to the river upstream according to the water level at the headwaters or dams. This tool uses the principle water level control work for water level detection using ultrasonic sensors with the design of this tool can then make it easier in terms of monitoing in opening and opening the water dam door automatically so as to facilitate in regulating the flow of water discharge without having to use a guard by adding an LCD to make it easier to show water level information and alarms on dams that can change in an uncertain period of time and then discharge reportsthe height of the water can be seen through the web so that it can facilitate and reduce a human error factor human error
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Belay, Alemu Moges, Sanket Puranik, Francisco Díaz-González, and Heidi Tuiskula. "A Systemic Approach to Investigate the Gaps between Distribution System Operators Need and Technology Developers’ Perception—A Case Study of an Intelligent Low-Voltage Grid Management System with Storage." Applied Sciences 11, no. 12 (June 9, 2021): 5348. http://dx.doi.org/10.3390/app11125348.
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The purpose of the paper is to introduce a new bi-directional approach to assess the gap between the customer needs and technology developers’ perception on the value propositions of innovations which includes storages. The paper used two methods; the first comprehensive sense and respond analysis investigated technology developers’ perceptions using the value propositions defined under the EU-funded H2020 RESOLVD project. The second method focused on customers and collected a survey which covered challenges, value propositions and preparedness to adopt new technology. The H2020 RESOLVD project has developed an intelligent low-voltage grid management system with storage. The results from the sense and respond analysis showed that most of the value propositions aligned with the responses from the broader survey which are needed within five years (e.g., improved power quality of grid, fault detection, reduced technical loss). However, the cybersecurity perception differed between developers and distribution system operators (DSOs). The customer survey highlighted that certain value propositions of technological solutions are needed more urgently than others, and therefore, technology developers should prioritize these in further developments. Regarding the use of flexibility to manage the LV grid, unclear regulations were expressed as a key barrier, thereby affecting business feasibility around battery storage.
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Kuras, Agnieszka, Maximilian Brell, Kristian Hovde Liland, and Ingunn Burud. "Multitemporal Feature-Level Fusion on Hyperspectral and LiDAR Data in the Urban Environment." Remote Sensing 15, no. 3 (January 20, 2023): 632. http://dx.doi.org/10.3390/rs15030632.
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Technological innovations and advanced multidisciplinary research increase the demand for multisensor data fusion in Earth observations. Such fusion has great potential, especially in the remote sensing field. One sensor is often insufficient in analyzing urban environments to obtain comprehensive results. Inspired by the capabilities of hyperspectral and Light Detection and Ranging (LiDAR) data in multisensor data fusion at the feature level, we present a novel approach to the multitemporal analysis of urban land cover in a case study in Høvik, Norway. Our generic workflow is based on bitemporal datasets; however, it is designed to include datasets from other years. Our framework extracts representative endmembers in an unsupervised way, retrieves abundance maps fed into segmentation algorithms, and detects the main urban land cover classes by implementing 2D ResU-Net for segmentation without parameter regularizations and with effective optimization. Such segmentation optimization is based on updating initial features and providing them for a second iteration of segmentation. We compared segmentation optimization models with and without data augmentation, achieving up to 11% better accuracy after segmentation optimization. In addition, a stable spectral library is automatically generated for each land cover class, allowing local database extension. The main product of the multitemporal analysis is a map update, effectively detecting detailed changes in land cover classes.