Journal articles on the topic 'Communications engineering not elsewhere classified'
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Rastorguev, S. V. "Modelling of Intergenerational Communications." Humanities and Social Sciences. Bulletin of the Financial University 11, no. 6 (January 28, 2022): 6–10. http://dx.doi.org/10.26794/2226-7867-2021-11-6-6-10.
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The article presents the author’s approach to modelling intergenerational communications based on the concept of social exchanges . The macro-level model describes different balances of exchanges of material and non-material resources between three generations and within one generation. Modelling allows us to provide an empirical analysis of quantitative data that form one of the possible outcomes: donation, recipient, parity. Based on micro-level and macrolevel models, the author proposed a set of projects in the field of youth policy for the integration of generations. Projects were classified according to areas of public life.
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Phaiboon, Supachai, and Pisit Phokharatkul. "Accurate Empirical Path Loss Models with Route Classification for mmWave Communications." International Journal of Antennas and Propagation 2022 (October 20, 2022): 1–9. http://dx.doi.org/10.1155/2022/2780029.
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This paper presents accurate empirical path loss models with route classification for the high band frequency of 5 G wireless. Propagation path routes are mainly classified into line of sight (LOS) and non-line-of-sight (NLOS). The NLOS routes are classified into 2 separate routes, namely, Hard_NLOS and Soft_NLOS. Their path loss models include free-space loss (Lfs) and multiscreen diffraction loss (Lmsd) together with the reflection from the building blocks. However, these NLOS routes can be combined into a single formula. The path loss models were fitted with measured path loss data at frequencies of 28 GHz and 73 GHz. These models are compared with four 5G empirical models, namely 5GCM, 3GPP, METIS, and mmMAGIC. The results show that the separated route models provide good agreement, especially for the hard routes compared with those models and provide the minimum MAE of 4.45 dB, 4.34 dB, and 6.72 dB for the hard route, soft route, and an all-NLOS route, respectively, for the dual-band frequency.
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Pérez Tadeo, María, Martin Gammell, and Joanne O'Brien. "First Steps towards the Automated Detection of Underwater Vocalisations of Grey Seals (Halichoerus grypus) in the Blasket Islands, Southwest Ireland." Journal of Marine Science and Engineering 11, no. 2 (February 4, 2023): 351. http://dx.doi.org/10.3390/jmse11020351.
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Underwater vocalisations of grey seals (Halichoerus grypus) were recorded by static acoustic monitoring (SM2M, Wildlife Acoustics) in the vicinity of a colony located at White Strand beach on Great Blasket Island, southwest Ireland during the pre-breeding and breeding seasons. Grey seal vocalisations were first classified across nine different categories based on aural and visual characteristics of the spectrograms, providing an acoustic repertoire for grey seals. This classification was further investigated by applying a classification tree analysis, resulting in five of the initial nine groups being selected. Furthermore, a comparison of two common approaches for the detection and extraction of vocalisations from acoustic files was done using the software Raven Pro and PAMGuard. The outputs of this study will present an essential first step towards the development of a protocol for underwater acoustic monitoring of grey seals in Irish waters and elsewhere.
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Noor-ul-huda, Muhammad, Samabia Tehsin, Sairam Ahmed, Fuad A. K. Niazi, and Zeerish Murtaza. "Retinal images benchmark for the detection of diabetic retinopathy and clinically significant macular edema (CSME)." Biomedical Engineering / Biomedizinische Technik 64, no. 3 (May 27, 2019): 297–307. http://dx.doi.org/10.1515/bmt-2018-0098.
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Abstract Diabetes mellitus is an enduring disease related with significant morbidity and mortality. The main pathogenesis behind this disease is its numerous micro- and macrovascular complications. In developing countries, diabetic retinopathy (DR) is one of the major sources of vision impairment in working age population. DR has been classified into two categories: proliferative diabetic retinopathy (PDR) and non-proliferative diabetic retinopathy (NPDR). NPDR is further classified into mild, moderate and severe, while PDR is further classified into early PDR, high risk PDR and advanced diabetic eye disease. DR is a disease caused due to high blood glucose levels which result in vision loss or permanent blindness. High-level advancements in the field of bio-medical image processing have speeded up the automated process of disease diagnoses and analysis. Much research has been conducted and computerized systems have been designed to detect and analyze retinal diseases through image processing. Similarly, a number of algorithms have been designed to detect and grade DR by analyzing different symptoms including microaneurysms, soft exudates, hard exudates, cotton wool spots, fibrotic bands, neovascularization on disc (NVD), neovascularization elsewhere (NVE), hemorrhages and tractional bands. The visual examination of the retina is a vital test to diagnose DR-related complications. However, all the DR computer-aided diagnostic systems require a standard dataset for the estimation of their efficiency, performance and accuracy. This research presents a benchmark for the evaluation of computer-based DR diagnostic systems. The existing DR benchmarks are small in size and do not cover all the DR stages and categories. The dataset contains 1445 high-quality fundus photographs of retinal images, acquired over 2 years from the records of the patients who presented to the Department of Ophthalmology, Holy Family Hospital, Rawalpindi. This benchmark provides an evaluation platform for medical image analysis researchers. Furthermore, it provides evaluation data for all the stages of DR.
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Salhi, M. A., T. Kleine-Ostmann, and T. Schrader. "Propagation Channel Measurements in the mm- and Sub-mm Wave Range for Different Indoor Communication Scenarios." Journal of Infrared, Millimeter, and Terahertz Waves 42, no. 4 (March 24, 2021): 357–70. http://dx.doi.org/10.1007/s10762-021-00785-8.
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AbstractIncreasing data rates in wireless communications are accompanied with the need for new unoccupied and unregulated bandwidth in the electromagnetic spectrum. Higher carrier frequencies in the lower THz frequency range might offer the solution for future indoor wireless communication systems with data rates of 100 Gbit/s and beyond that cannot be located elsewhere. In this review, we discuss propagation channel measurements in an extremely broad frequency range from 50 to 325 GHz in selected indoor communication scenarios including kiosk downloading, office room communication, living rooms, and typical industrial environments.
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Neuts, Marcel F. "An explicit solution to a particular Markov chain of M/G/1 type." Journal of Applied Probability 31, A (1994): 337–42. http://dx.doi.org/10.2307/3214966.
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A Markov chain of M/G/1 type, which arose in a problem of communications engineering, is analyzed by a combination of matrix analysis and appropriate series expansions. The highly explicit results obtainable for this model owe much to analytic methods introduced by Professor Takács. Special features of the numerical implementation of the proposed solution are also discussed. The simplifications proper to this model can also be used in some related, more complex models to be discussed elsewhere.
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Neuts, Marcel F. "An explicit solution to a particular Markov chain of M/G/1 type." Journal of Applied Probability 31, A (1994): 337–42. http://dx.doi.org/10.1017/s0021900200107168.
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A Markov chain of M/G/1 type, which arose in a problem of communications engineering, is analyzed by a combination of matrix analysis and appropriate series expansions. The highly explicit results obtainable for this model owe much to analytic methods introduced by Professor Takács. Special features of the numerical implementation of the proposed solution are also discussed. The simplifications proper to this model can also be used in some related, more complex models to be discussed elsewhere.
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Bisio, G. "Exergy Analysis of Thermal Energy Storage With Specific Remarks on the Variation of the Environmental Temperature." Journal of Solar Energy Engineering 118, no. 2 (May 1, 1996): 81–88. http://dx.doi.org/10.1115/1.2848020.
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Energy storage is a key technology for many purposes and in particular for air conditioning plants and a successful exploitation of solar energy. Thermal storage devices are usually classified as either variable temperature (“sensible heat”) or constant temperature (“latent heat”) devices. For both models a basic question is to determine the efficiency suitably: Only exergy efficiency appears a proper way. The aim of this paper is to examine exergy efficiency in both variable and constant temperature systems. From a general statement of exergy efficiency by the present author, two types of actual definitions are proposed, depending on the fact that the exergy of the fluid leaving the thermal storage during the charge phase can be either totally lost or utilized elsewhere. In addition, specific remarks are made about the exergy of a system in a periodically varying temperature environment.
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Farid, A. M., and D. C. McFarlane. "Production degrees of freedom as manufacturing system reconfiguration potential measures." Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture 222, no. 10 (October 1, 2008): 1301–14. http://dx.doi.org/10.1243/09544054jem1056.
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In recent years, many design approaches have been developed for automated manufacturing systems in the fields of reconfigurable manufacturing systems (RMSs), holonic manufacturing systems (HMSs), and multi-agent systems (MASs). One of the principle reasons for these developments has been to enhance the reconfigurability of a manufacturing system, allowing it to adapt readily to changes over time. However, to date, reconfigurability assessment has been limited. Hence, the efficacy of these design approaches remains inconclusive. This paper is the first of two in this issue to address reconfigurability measurement. Specifically, it seeks to address ‘reconfiguration potential’ by analogy. Mechanical degrees of freedom have been used in the field of mechanics as a means of determining the independent directions of motion of a mechanical system. By analogy, manufacturing degrees of freedom can be used to determine independent ways of production. Furthermore, manufacturing degrees of freedom can be classified into their production and product varieties. This paper specifically focuses on the former to measure the product-independent aspects of manufacturing system ‘reconfiguration potential’. This approach will be added to complementary work on the measurement of ‘reconfiguration ease’ so as to form an integrated reconfigurability measurement process described elsewhere [1—5].
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Matthews, Peter C. "Pathological Habit Disorder?" Canadian Journal of Psychiatry 33, no. 9 (December 1988): 826–29. http://dx.doi.org/10.1177/070674378803300908.
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This paper outlines a diagnostic entity called ‘Pathological Habit Disorder’ which is suggested for inclusion in the DSM as an Axis II option. Specific areas of concern, either mental (Axis I) or physical (Axis III), would delineate the syndrome. Pathological Habit Disorder (PHD) points to treatment options where the syndrome is wholly or partly habit-driven. Whether the syndrome is habit-driven or not will remain a clinical judgement even though many conditions, previously thought immutable except by medication, are proving accessible to behavioural engineering. In the ICD system, PHD seems to fit in “Special Symptoms or Syndromes not elsewhere Classified”. It is demonstrably useful to have a diagnosis such as PHD and to incorporate it into the body of medical classification, recognizing current practices for dealing with unwelcome or damaging habits.
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Mehdiabadi, Amir, Vahid Shahabi, Saeed Shamsinejad, Mohammad Amiri, Cristi Spulbar, and Ramona Birau. "Investigating Industry 5.0 and Its Impact on the Banking Industry: Requirements, Approaches and Communications." Applied Sciences 12, no. 10 (May 19, 2022): 5126. http://dx.doi.org/10.3390/app12105126.
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Technology, along with political and economic factors, is one of the main drivers of the future of banking. Banking managers urgently need to know technological trends to make strategic decisions, know the future accurately, and make the most of existing opportunities. Industry 5.0 is the dream of modern banking, based on strategies for successful entry into the field in a completely different way. Using a complex literature survey, 49 indicators were identified to enter Industry 5.0 and were classified into three categories of insignificant indicators, essential indicators, and very necessary indicators. Then, based on the opinions of 10 experts from ten countries with modern banking in the world, the researchers focused on 14 essential indicators. To analyze the drawn space, structural-interpretive modeling and MICMAC analysis were used and the model was classified into nine levels. The results showed that low-level indices are the most influential (TMBE and HEMS) and higher-level indices are the most influenced (PZM and RNC). Finally, researchers analyzed how to use new technologies in the banking industry with the entry of the Industry 5.0 and revealed what the characteristics of the impact of these indicators on entering Industry 5.0 are.
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Pang, Liang, Xiao Chen, Yong Shi, Zhi Xue, and Rida Khatoun. "Localization of multiple jamming attackers in vehicular ad hoc network." International Journal of Distributed Sensor Networks 13, no. 8 (August 2017): 155014771772569. http://dx.doi.org/10.1177/1550147717725698.
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In vehicular ad hoc network, wireless jamming attacks are easy to be launched in the control channel and can cause serious influence on the network performance which may cause further safety accidents. In order to address the issue of wireless jamming attacks, a new technique which localizes the jamming attackers and prevents vehicles from jamming through human intervention is proposed. In this article, we propose a range-free approach to localize the source of the attacker and determine the number of jamming attackers. The data set is the locating information and the jamming detection information associated with each vehicle. Then, we formulate the problem of determining the number of attackers as a multiclass detection problem. We define the incorrectly classified area and use it to measure the distance between samples and centroids in fuzzy c-means algorithm. We further determine the number of jamming attackers through the coverage rate of beaconing circles and utilize weight-based fuzzy c-means to classify the data set. When the data set is classified as acceptable, we further explore the means of using particle swarm optimization algorithm to calculate the positional coordinates of each attacker. We simulate our techniques in MATLAB, and both urban traffic area and open area are considered in our simulation. The experimental results suggest that the proposed algorithm can achieve high precision when determining the number of attackers while the result of the classified performance is always satisfying. Our localization results lead to higher accuracy than other existing solutions. Also, when the data set is limited, the chances of taking accurate localization are higher than other measures.
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Barbosa, Álvaro. "Displaced Soundscapes: A Survey of Network Systems for Music and Sonic Art Creation." Leonardo Music Journal 13 (December 2003): 53–59. http://dx.doi.org/10.1162/096112104322750791.
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The introduction of various collaborative tools, made possible by the expansion of computer network systems and communications technology, has led to new methods of musical composition and improvisation. The author describes a number of recent music and sound art projects involving the use of network systems that enable geographically displaced creators to collaboratively generate shared soundscapes. Various system designs, ideas and concepts associated with this interaction paradigm are presented and classified by the author.
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Su, Xin, Inam Ullah, Xiaofeng Liu, and Dongmin Choi. "A Review of Underwater Localization Techniques, Algorithms, and Challenges." Journal of Sensors 2020 (January 13, 2020): 1–24. http://dx.doi.org/10.1155/2020/6403161.
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Recently, there has been increasing interest in the field of underwater wireless sensor networks (UWSNs), which is a basic source for the exploration of the ocean environment. A range of military and civilian applications is anticipated to assist UWSN. The UWSN is being developed by the extensive wireless sensor network (WSN) applications and wireless technologies. Therefore, in this paper, a review has been presented which unveils the existing challenges in the underwater environment. In this review, firstly, an introduction to UWSN is presented. After that, underwater localizations and the basics are presented. Secondly, the paper focuses on the architecture of UWSN and technologies used for underwater acoustic sensor network (UASN) localization. Various localization techniques are discussed in the paper classified by centralized and distributed localizations. They are further classified into estimated and prediction-based localizations. Also, various underwater localization algorithms are discussed, which are grouped by the algorithms based on range and range-free schemes. Finally, the paper focuses on the challenges existing in underwater localizations, underwater acoustic communications with conclusions.
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Jaber, Zaid Hashim, Dheyaa Jasim Kadhim, and Ahmed Sabah Al-Araji. "Medium access control protocol design for wireless communications and networks review." International Journal of Electrical and Computer Engineering (IJECE) 12, no. 2 (April 1, 2022): 1711. http://dx.doi.org/10.11591/ijece.v12i2.pp1711-1723.
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<p><span>Medium access control (MAC) protocol design plays a crucial role to increase the performance of wireless communications and networks. The channel access mechanism is provided by MAC layer to share the medium by multiple stations. Different types of wireless networks have different design requirements such as throughput, delay, power consumption, fairness, reliability, and network density, therefore, MAC protocol for these networks must satisfy their requirements. In this work, we proposed two multiplexing methods for modern wireless networks: Massive multiple-input-multiple-output (MIMO) and power domain non-orthogonal multiple access (PD-NOMA). The first research method namely Massive MIMO uses a massive number of antenna elements to improve both spectral efficiency and energy efficiency. On the other hand, the second research method (PD-NOMA) allows multiple non-orthogonal signals to share the same orthogonal resources by allocating different power level for each station. PD-NOMA has a better spectral efficiency over the orthogonal multiple access methods. A review of previous works regarding the MAC design for different wireless networks is classified based on different categories. The main contribution of this research work is to show the importance of the MAC design with added optimal functionalities to improve the spectral and energy efficiencies of the wireless networks.</span></p>
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Indraratna, B., P. Nutalaya, K. S. Koo, and N. Kuganenthira. "Engineering behaviour of a low carbon, pozzolanic fly ash and its potential as a construction fill." Canadian Geotechnical Journal 28, no. 4 (August 1, 1991): 542–55. http://dx.doi.org/10.1139/t91-070.
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Detailed laboratory investigations were conducted on Mae Moh fly ash from northern Thailand for the determination of its grain size distribution, mineralogy, pozzolanic activity, compaction and strength characteristics, and the collapse potential. On the basis of the experimental results, this fly ash is classified as ASTM class C, which is considered to be pozzolanic. It has good potential to be utilized as an effective fill for embankments (roads and dams), airfields, pavements, and building bricks, as well as for the stabilization of compressible or erodible foundations. Because of the fact that Mae Moh fly ash contains only a negligible amount of unburned carbon, its pozzolanic reactivity is accelerated, in comparison with the relatively inert, high-carbon fly ash produced elsewhere in Thailand and many other parts of Asia. It is also demonstrated that Mae Moh fly ash can be easily compacted to produce acceptable dry densities over a wide range of water contents. Curing with an adequate moisture supply in the presence of calcium oxide plays an important role in accelerating the pozzolanic reactions, hence improving the time-dependent-properties. This study further proposes that a curing period of 2–3 weeks is sufficient for this material to approach its maximum strength. Although the behaviour of one specific fly ash cannot generalize the wide array of other ashes, the test results obtained for Mae Moh fly ash may be applied to lignite ashes in the category of ASTM class C. Key words: fly ash, structural fill, compaction, compressive strength, shear strength, collapse potential, pozzolanic activity.
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Statscewich, Hank, Tom Weingartner, Seth Danielsen, Bruno Grunau, Greg Egan, and Jeb Timm. "A High-Latitude Modular Autonomous Power, Control, and Communication System for Application to High-Frequency Surface Current Mapping Radars." Marine Technology Society Journal 45, no. 3 (May 1, 2011): 59–68. http://dx.doi.org/10.4031/mtsj.45.3.7.
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AbstractHigh-frequency, shore-based radars (HFR) collect hourly, real-time surface current data over broad areas of the coastal ocean and yield insights on time-varying circulation, predict oil spill trajectories, evaluate circulation models, and, in case of a spill, provide responders with real-time data on spill evolution. HFR requires 7.5 kWh/day of power, but the lack of power availability inhibits HFR use in Alaska. We developed a modular, autonomous remote power module (RPM) for Arctic environments. The RPM design facilitates setup and transport to remote sites using small vehicles, and it contains subsystems for power generation, satellite communications, and power performance monitoring. The subsystems are powered by a battery bank (with a 5-day power reserve) charged primarily by wind and solar and secondarily by a biodiesel generator. The RPM is a stand-alone device for long-term deployments. It minimizes permit issues associated with diesel generators and logistics costs associated with refueling and maintenance. Performance data from a prototype RPM setup in Barrow, Alaska, in fall 2010 is provided. The system is designed for high latitudes but can be modified for remote coasts elsewhere.
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Bhosale, Mihir, B. K. Bhavathrathan, and Gopal R. Patil. "Red Light Running at Heterogeneous Saturated Intersections in Mumbai, India: On the Existence of Two Regimes and Causal Factors." Transportation Research Record: Journal of the Transportation Research Board 2619, no. 1 (January 2017): 75–84. http://dx.doi.org/10.3141/2619-08.
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This paper presents an analysis of red light running (RLR) conducted at saturated intersections in the city of Mumbai, India, where the traffic is highly heterogeneous with respect to vehicle classes and driver behavior. When all vehicles are considered, almost one in 17 drivers is seen to be jumping red signals there. Unlike the RLR behavior that has been previously reported from intersections elsewhere, a peculiarity observed here is that, within a single red phase, two distinguishable segments of RLR behavior exist. The authors classified them into two regimes: Regime 1, just after the onset of red, and Regime 2, just before the onset of the next green. About one-third of RLR events occur in Regime 1 and the rest in Regime 2. The authors fit different distributions on the time distribution of RLR events. The Kolmogorov–Smirnov test suggests that, at all intersections, exponential distribution fits best for RLR behaviors in Regime 1, and extreme value distribution fits for Regime 2. In addition to those two regimes, RLR at a lower rate is observed in the period between those regimes, and normal distribution fits there. To analyze the causal factors of RLR behavior in the two regimes, the authors developed models at a mesoscopic level specific to vehicle class and regime. Although the red-to-green ratio and the presence of policing prove to be relevant factors affecting RLR in both the regimes, the relative time for which the conflict area is free affects RLR in Regime 2 but not in Regime 1.
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Milinovic, Jelena, Francisco J. L. Rodrigues, Fernando J. A. S. Barriga, and Bramley J. Murton. "Ocean-Floor Sediments as a Resource of Rare Earth Elements: An Overview of Recently Studied Sites." Minerals 11, no. 2 (January 30, 2021): 142. http://dx.doi.org/10.3390/min11020142.
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The rare earth elements (REE), comprising 15 elements of the lanthanum series (La-Lu) together with yttrium (Y) and scandium (Sc), have become of particular interest because of their use, for example, in modern communications, renewable energy generation, and the electrification of transport. However, the security of supply of REE is considered to be at risk due to the limited number of sources, with dependence largely on one supplier that produced approximately 63% of all REE in 2019. As a result, there is a growing need to diversify supply. This has resulted in the drive to seek new resources elsewhere, and particularly on the deep-ocean floor. Here, we give a summary of REE distribution in minerals, versatile applications, and an update of their economic value. We present the most typical onshore methods for the determination of REE and examine methods for their offshore exploration in near real time. The motivation for this comes from recent studies over the past decade that showed ΣREE concentrations as high as 22,000 ppm in ocean-floor sediments in the Pacific Ocean. The ocean-floor sediments are evaluated in terms of their potential as resources of REE, while the likely economic cost and environmental impacts of deep-sea mining these are also considered.
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Subramaniam, Chitdrakantan, Syuhaida Ismail, Wan Nurul Mardiah Wan Mohd Rani, and Amir Mahdiyar. "Improving Project Communications Management Practices in the Construction Sector during the COVID-19 Pandemic: A Malaysian Scenario." Buildings 12, no. 9 (August 23, 2022): 1291. http://dx.doi.org/10.3390/buildings12091291.
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The construction industry remains an important economic sector that supports the growth of a nation. It is vital to maintain the industry’s momentum when facing the Coronavirus Disease 2019 (COVID-19) pandemic, or similar in the future, to ensure employability and decent jobs for every individual in the industry, especially foreign labourers who are always regarded as vulnerable. Improving existing project communications management practices is essential to suppressing infection among labourers; however, there are only a few efforts made to understand the current condition. This study explores the communications management barriers and the potential improvement measures amid the COVID-19 outbreak sweeping across the Malaysian construction industry. The findings disclose that out of eleven communication channels, only six communications management barrier variables with eight items, and three communications management improvement measure variables with seven items, are classified as highly critical, based on a systematic literature review (SLR), and a questionnaire survey on 100 foreign labourers and management team members, respectively, where the data gathered were analysed using the Rasch measurement model. The finding also suggests that site review meetings, team meeting discussions and project reports require immediate attention to ensure the construction industry remains robust without significant interruption during the course of the pandemic.
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Sato, Kimio, and Rikio Onodera. "General expressions for the numbers of spanning trees in interative graphs classified by contact patterns of cells." Electronics and Communications in Japan (Part I: Communications) 70, no. 4 (1987): 12–24. http://dx.doi.org/10.1002/ecja.4410700402.
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Ahmad, Hesham S., Maha D. Ayoush, and Majed S. Al-Alwan. "Causes of delay to public infrastructure projects according to engineers representing different contract parties." Built Environment Project and Asset Management 10, no. 1 (December 17, 2019): 153–79. http://dx.doi.org/10.1108/bepam-03-2019-0026.
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Purpose The purpose of this paper is to investigate the main causes of delay in public construction projects. This is motivated by feedback from public construction experts concerning substantive delays during the last decade. The study thus seeks to help decision makers in Jordan and elsewhere identify problems and develop mitigating strategies. Design/methodology/approach Causes of delay were identified from previous related studies and then augmented after consultation with experts. This resulted in 56 delay factors classified into eight groups. The sampling frame for the study was defined in terms of public construction projects (mostly related to roads) owned by the Ministry of Public Works and Housing in Jordan. A survey was conducted with engineers working as representatives of the owner, contractors or consultants to elicit and evaluate the importance of the 56 delay factors. Findings Overall, 113 completed questionnaire responses were returned and analyzed to rank the causes of delay using the relative importance index method. Owners and consultants showed more interest in factors related to themselves, while contractors showed highest interest in an external factor related to the owner of services. Four recommendations are put forward for decision makers to mitigate against delays. Originality/value This research investigates a relatively large number of delay factors compared to other studies and these are categorized into groups to facilitate thematic understanding. Further, compared to previous related research, this research fills a gap by exploring the opinions of different contract parties.
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Xiang, Shishi, Zhiyuan Niu, and Yuzhou Wu. "Research on Handicraft Design Based on Artificial Intelligence Technology in Complex Environments." Wireless Communications and Mobile Computing 2022 (April 6, 2022): 1–9. http://dx.doi.org/10.1155/2022/1538488.
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In this twenty-first century, research is taking new dimension with the unpredictable development in information technology. With the aid of this technology, handicraft designs can be classified and made by utilizing artificial intelligence techniques. The Chinese handicraft designs will have unique style in the presentation. Using the artificial intelligence techniques, the arc styles of the handicraft design can be identified and classified. In complex environment like epidemic or pandemic situations, every user has to focus on the minor variations in financial aspects. Implementation of artificial intelligent technology will aid the user to get updated with the market strategy for financial allocation to resources. In the market, each arc style may have different demands and the charges will improve the profit for the company and also the country. In this study, the intelligent computer-aided art and craft design (ICAACD) method is implemented on the financial dataset of China and analysis is performed. This proposed system is compared with the existing algorithms such as GNNA, RNNA, and CNNA, and it is observed that the proposed ICAACD method outperforms with the accuracy of 82%.
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Chang, Tsai-Rong, and Ming-Yen Tsai. "Classifying Conditions of Speckle and Wrinkle on the Human Face: A Deep Learning Approach." Electronics 11, no. 21 (November 6, 2022): 3623. http://dx.doi.org/10.3390/electronics11213623.
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Speckles and wrinkles are common skin conditions on the face, with occurrence ranging from mild to severe, affecting an individual in various ways. In this study, we aim to detect these conditions using an intelligent deep learning approach. First, we applied a face detection model and identified the face image using face positioning techniques. We then split the face into three polygonal areas (forehead, eyes, and cheeks) based on 81 position points. Skin conditions in the images were firstly judged by skin experts and subjectively classified into different categories, from good to bad. Wrinkles were classified into five categories, and speckles were classified into four categories. Next, data augmentation was performed using the following manipulations: changing the HSV hue, image rotation, and horizontal flipping of the original image, in order to facilitate deep learning using the Resnet models. We tested the training using these models each with a different number of layers: ResNet-18, ResNet-34, ResNet-50, ResNet-101, and ResNet-152. Finally, the K-fold (K = 10) cross-validation process was applied to obtain more rigorous results. Results of the classification are, in general, satisfactory. When compared across models and across skin features, we found that Resnet performance is generally better in terms of average classification accuracy when its architecture has more layers.
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MENOLLI, ANDRE, SHEILA REINEHR, and ANDREIA MALUCELLI. "ORGANIZATIONAL LEARNING APPLIED TO SOFTWARE ENGINEERING: A SYSTEMATIC REVIEW." International Journal of Software Engineering and Knowledge Engineering 23, no. 08 (October 2013): 1153–75. http://dx.doi.org/10.1142/s0218194013500356.
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Organizational learning assists the companies to improve significantly their processes by means of experiences reuse, making knowledge accessible to the whole organization. In software engineering it is important that the acquired knowledge is stored and systematically reused. This paper aims to present a systematic review, by identifying in which software engineering areas are the organizational learning studies concentrated, and how the organizational learning concepts are being applied in software engineering. This systematic review identified 2496 papers. After eliminating the duplicate titles and those not related to the review, 1184 papers remained. Applying the exclusion criteria, the number of papers was reduced to 68. These papers were analyzed and classified according to the software engineering areas defined in the SWEBOK, and the main organizational learning theories and techniques. It was observed that many software engineering researches apply organizational learning concepts without being aware of it.
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Raheem, Mariam Abdul-Zahra, and Ehab AbdulRazzaq Hussein. "Classification of EEG Signals Using Quantum Neural Network and Cubic Spline." International Journal of Electronics and Telecommunications 62, no. 4 (December 1, 2016): 401–8. http://dx.doi.org/10.1515/eletel-2016-0055.
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Abstract The main aim of this paper is to propose Cubic Spline-Quantum Neural Network (CS-QNN) model for analysis and classification of Electroencephalogram (EEG) signals. Experimental data used here were taken from seven different electrodes. The work has been done in three stages, normalization of the signals, extracting the features by Cubic Spline Technique (CST) and classification using Quantum Neural Network (QNN). The simulation results showed that five types of EEG signals were classified with an average accuracy for seven electrodes that is 94.3% when training 70% of the features while with an average accuracy of 92.84% when training 50% of the features.
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Chen, Shiwen, Junjian Yuan, Xiaopeng Xing, and Xin Qin. "Research on emitter individual identification technology based on Automatic Dependent Surveillance–Broadcast signal." International Journal of Distributed Sensor Networks 17, no. 2 (February 2021): 155014772199262. http://dx.doi.org/10.1177/1550147721992626.
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Aiming at the shortcomings of the research on individual identification technology of emitters, which is primarily based on theoretical simulation and lack of verification equipment to conduct external field measurements, an emitter individual identification system based on Automatic Dependent Surveillance–Broadcast is designed. On one hand, the system completes the individual feature extraction of the signal preamble. On the other hand, it realizes decoding of the transmitter’s individual identity information and generates an individual recognition training data set, on which we can train the recognition network to achieve individual signal recognition. For the collected signals, six parameters were extracted as individual features. To reduce the feature dimensions, a Bessel curve fitting method is used for four of the features. The spatial distribution of the Bezier curve control points after fitting is taken as an individual feature. The processed features are classified with multiple classifiers, and the classification results are fused using the improved Dempster–Shafer evidence theory. Field measurements show that the average individual recognition accuracy of the system reaches 88.3%, which essentially meets the requirements.
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Zhang, Li, Xiangrong She, Xianyu Ge, and Jieqing Tan. "Adaptive fitting algorithm of progressive interpolation for Loop subdivision surface." International Journal of Distributed Sensor Networks 14, no. 11 (November 2018): 155014771881235. http://dx.doi.org/10.1177/1550147718812355.
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Subdivision surface and data fitting have been applied in data compression and data fusion a lot recently. Moreover, subdivision schemes have been successfully combined into multi-resolution analysis and wavelet analysis. This makes subdivision surfaces attract more and more attentions in the field of geometry compression. Progressive interpolation subdivision surfaces generated by approximating schemes were presented recently. When the number of original vertices becomes huge, the convergence speed becomes slow and computation complexity becomes huge. In order to solve these problems, an adaptive progressive interpolation subdivision scheme is presented in this article. The vertices of control mesh are classified into two classes: active vertices and fixed ones. When precision is given, the two classes of vertices are changed dynamically according to the result of each iteration. Only the active vertices are adjusted, thus the class of active vertices keeps running down while the fixed ones keep rising, which saves computation greatly. Furthermore, weights are assigned to these vertices to accelerate convergence speed. Theoretical analysis and numerical examples are also given to illustrate the correctness and effectiveness of the method.
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Holik, Filip, Lars Halvdan Flå, Martin Gilje Jaatun, Sule Yildirim Yayilgan, and Jørn Foros. "Threat Modeling of a Smart Grid Secondary Substation." Electronics 11, no. 6 (March 8, 2022): 850. http://dx.doi.org/10.3390/electronics11060850.
Full textAbstract:
A full smart grid implementation requires the digitization of all parts of the smart grid infrastructure, including secondary electrical substations. Unfortunately, this introduces new security threats, which were not apparent before. This article uses a Smart Grid Threat Modeling Template implementing the STRIDE model to create a threat model of a digital secondary substation and its communication with the control center. Threats are classified by priority and need for further investigation. The tool was compared with a CORAS analysis, and was determined to be more time efficient. Denial of service (DoS) threats were classified as the most critical, and they were further evaluated in a precise simulation model created for this purpose. This model combines simulation with emulated communication, and enables verification of threat likelihoods and impacts. The results show that even publicly available tools can be easily used to disrupt grid communication and potentially cause loss of the entire grid’s observability and controllability.
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Kelly, Matthew, and Yuriy Kuleshov. "Flood Hazard Assessment and Mapping: A Case Study from Australia’s Hawkesbury-Nepean Catchment." Sensors 22, no. 16 (August 19, 2022): 6251. http://dx.doi.org/10.3390/s22166251.
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Floods are among the costliest natural hazards, in Australia and globally. In this study, we used an indicator-based method to assess flood hazard risk in Australia’s Hawkesbury-Nepean catchment (HNC). Australian flood risk assessments are typically spatially constrained through the common use of resource-intensive flood modelling. The large spatial scale of this study area is the primary element of novelty in this research. The indicators of maximum 3-day precipitation (M3DP), distance to river—elevation weighted (DREW), and soil moisture (SM) were used to create the final Flood Hazard Index (FHI). The 17–26 March 2021 flood event in the HNC was used as a case study. It was found that almost 85% of the HNC was classified by the FHI at ‘severe’ or ‘extreme’ level, illustrating the extremity of the studied event. The urbanised floodplain area in the central-east of the HNC had the highest FHI values. Conversely, regions along the western border of the catchment had the lowest flood hazard risk. The DREW indicator strongly correlated with the FHI. The M3DP indicator displayed strong trends of extreme rainfall totals increasing towards the eastern catchment border. The SM indicator was highly variable, but featured extreme values in conservation areas of the HNC. This study introduces a method of large-scale proxy flood hazard assessment that is novel in an Australian context. A proof-of-concept methodology of flood hazard assessment developed for the HNC is replicable and could be applied to other flood-prone areas elsewhere.
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Fetisova, M., and A. Kolomyceva. "FLEXIBLE APPROACH TO DESIGN OF A PRODUCTION FACILITY." Bulletin of Belgorod State Technological University named after. V. G. Shukhov 7, no. 2 (February 14, 2022): 47–54. http://dx.doi.org/10.34031/2071-7318-2021-7-2-47-54.
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The prerequisites for a high-quality solution of architectural and artistic problems in the design of industrial enterprises are determined. The planning system provides a systematic placement in space of the main structural elements of the composition (main roads and communications, individual zones and objects), and the preservation of the adopted structure during the development of the enterprise. Despite the further change in the building system as new capacities increase. General methods of organizing space are formed by various elements of building up industrial enterprises. The compositional solutions of industrial buildings can be classified depending on the methods of placing the standing equipment: buildings with an open facade; buildings with equipment; "bbuilding-installations". The improvement of the architectural and artistic qualities of the production environment is achieved through landscaping and landscaping of the territory, the color scheme of objects and complexes. The correct choice of the volume of buildings allows to reduce the area of the enclosing structures, which in turn reduces the energy loss of the building, to have a versatile orientation, better insolation and ventilation. Since here, technological, techno-economic and social factors are closely interconnected.
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Zhao, Liguo, Derong Zhu, Wasswa Shafik, S. Mojtaba Matinkhah, Zubair Ahmad, Lule Sharif, and Alisa Craig. "Artificial intelligence analysis in cyber domain: A review." International Journal of Distributed Sensor Networks 18, no. 4 (April 2022): 155013292210848. http://dx.doi.org/10.1177/15501329221084882.
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The application of Big Data Analytics is identified through the Cyber Research Alliance for cybersecurity as the foremost preference for future studies and advancement in the field of cybersecurity. In this study, we develop a repeatable procedure for detecting cyber-attacks in an accurate, scalable, and timely manner. An in-depth learning algorithm is utilized for training a neural network for detecting suspicious user activities. The proposed system architecture was implemented with the help of Splunk Enterprise Edition 6.42. A data set of average feature counts has been executed through a Splunk search command in 1-min intervals. All the data sets consisted of a minute trait total derived from a sparkling file. The attack patterns that were not anonymized or were indicative of the vulnerability of cyber-attack were denoted with yellow. The rule-based method dispensed a low quantity of irregular illustrations in contrast with the Partitioning Around Medoids method. The results in this study demonstrated that using a proportional collection of instances trained with the deep learning algorithm, a classified data set can accurately detect suspicious behavior. This method permits for the allocation of multiple log source types through a sliding time window and provides a scalable solution, which is a much-needed function.
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Zhao, Liguo, Derong Zhu, Wasswa Shafik, S. Mojtaba Matinkhah, Zubair Ahmad, Lule Sharif, and Alisa Craig. "Artificial intelligence analysis in cyber domain: A review." International Journal of Distributed Sensor Networks 18, no. 4 (April 2022): 155013292210848. http://dx.doi.org/10.1177/15501329221084882.
Full textAbstract:
The application of Big Data Analytics is identified through the Cyber Research Alliance for cybersecurity as the foremost preference for future studies and advancement in the field of cybersecurity. In this study, we develop a repeatable procedure for detecting cyber-attacks in an accurate, scalable, and timely manner. An in-depth learning algorithm is utilized for training a neural network for detecting suspicious user activities. The proposed system architecture was implemented with the help of Splunk Enterprise Edition 6.42. A data set of average feature counts has been executed through a Splunk search command in 1-min intervals. All the data sets consisted of a minute trait total derived from a sparkling file. The attack patterns that were not anonymized or were indicative of the vulnerability of cyber-attack were denoted with yellow. The rule-based method dispensed a low quantity of irregular illustrations in contrast with the Partitioning Around Medoids method. The results in this study demonstrated that using a proportional collection of instances trained with the deep learning algorithm, a classified data set can accurately detect suspicious behavior. This method permits for the allocation of multiple log source types through a sliding time window and provides a scalable solution, which is a much-needed function.
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Liu, Qiang, Baoyan Song, and Junlu Wang. "Second-degree branch structure blockchain expansion model." International Journal of Distributed Sensor Networks 18, no. 3 (March 2022): 155014772110647. http://dx.doi.org/10.1177/15501477211064755.
Full textAbstract:
The blockchain runs in a complex topological network which is affected by the principle of consensus, and data storage between nodes needs to maintain global consistency in the entire network, which causes the data storage inefficient. At the same time, the information exchange between large-scale communication node groups leads to the problems of bandwidth expropriation and excessive network load. In response to these problems, this article proposes a second-degree branch structure blockchain expansion model. First, a ternary storage structure is established. Data use the way of fully integrated storage, multi-cell storage, and fully split storage, and data are classified and stored in parallel between the structures. Second, a second-degree branch chain model is constructed. The main chain forks into multiple sub-chains, and a free competition chain structure and a Z-type chain structure are defined; a two-way rotation mechanism is introduced to realize the integration and transition between chain structures. Finally, a set of malicious attacks is simulated to realize the security constraints of the blockchain, to verify the security of the second-degree branch chain model. Experiment shows that the second-degree branch structure expansion model proposed in this article has great advantages in data storage efficiency and network load.
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Huh, Jun-Ho. "Implementation of lightweight intrusion detection model for security of smart green house and vertical farm." International Journal of Distributed Sensor Networks 14, no. 4 (April 2018): 155014771876763. http://dx.doi.org/10.1177/1550147718767630.
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With the current global food production capability, it is not difficult to anticipate that there will be a global food shortage when the world population grows beyond 10 billion by the end of the 21st century. Many projects are in motion to deal with this problem and some of them are considered to be quite feasible. Development and implementation of smart green houses and vertical farms are two major solutions for the expected crisis, but as other ICT-based systems, their security problems must be dealt with. Nevertheless, current network forensics is still unable to fully monitor and analyze computer network traffic to gather the evidences of malicious attacks or intrusions. Although major companies and government agencies have introduced various types of high-speed IDS into their networks, smaller firms or private organizations are unable to do so because of the cost involved. The lightweight IDS proposed in this study can be a suitable solution as this system can be operated with a common PC and peripherals. This system also underwent a test bed experiment and proved its efficiency. Jpcap library was used to capture transport packets which were then classified using typical communications protocols. The packet headers were subjected to analysis and the results were stored in database for later applications.
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He, Ming, Qiuli Chen, Fei Dai, and Xiang Zheng. "Topological configuration and optimization in underwater acoustic sensor networks: A survey." International Journal of Distributed Sensor Networks 14, no. 8 (August 2018): 155014771879535. http://dx.doi.org/10.1177/1550147718795359.
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Marine environmental monitoring, marine resource development, and maritime rights and interests protection had put great demands on underwater acoustic sensor networks. At the same time, it was found that the configuration and optimization of the underwater acoustic sensor network had important influence on the network performance and service quality in the uncertain marine environment. According to the characteristics of dynamic evolution of network topology and combining with different practical application scenarios, this article studied and discussed the model description, configuration mechanism, and optimization strategy of underwater acoustic sensor network. First, the classical underwater acoustic sensor network models were divided and discussed from three aspects: dimension, sensor types, and dynamic and static states. The characteristics of the six models are compared and analyzed. Second, according to the characteristics of six different models, the configuration mechanism and optimization strategy are discussed and classified. The configuration mechanism of models was studied from the aspects about determinism, self-adaptation, and group intelligence. The optimization strategy of models was discussed from the aspects about coverage, connectivity, energy consumption, time delay, data quality, and so on, and the relations and differences between different methods were compared and analyzed. Finally, the five future researches direction were expected, in order to provide a clear idea for further research in this field.
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Zhang, Jiahao, Fangmin He, Wei Li, Yi Li, Qing Wang, Songhu Ge, Jinling Xing, Hongbo Liu, Yaxing Li, and Jin Meng. "Self-Interference Cancellation: A Comprehensive Review from Circuits and Fields Perspectives." Electronics 11, no. 2 (January 6, 2022): 172. http://dx.doi.org/10.3390/electronics11020172.
Full textAbstract:
Increased demand for higher spectrum efficiency, especially in the space-limited chip, base station, and vehicle environments, has spawned the development of full-duplex communications, which enable the transmitting and receiving to occur simultaneously at the same frequency. The key challenge in this full-duplex communication paradigm is to reduce the self-interference as much as possible, ideally, down to the noise floor. This paper provides a comprehensive review of the self-interference cancellation (SIC) techniques for co-located communication systems from a circuits and fields perspective. The self-interference occurs when the transmitting antenna and the receiving antenna are co-located, which significantly degrade the system performance of the receiver, in terms of the receiver desensitization, signal masking, or even damage of hardwares. By introducing the SIC techniques, the self-interference can be suppressed and the weak desired signal from the remote transmitter can be recovered. This, therefore, enables the full-duplex communications to come into the picture. The SIC techniques are classified into two main categories: the traditional circuit-domain SICs and the novel field-domain SICs, according to the method of how to rebuild and subtract the self-interference signal. In this review paper, the field-domain SIC method is systematically summarized for the first time, including the theoretical analysis and the application remarks. Some typical SIC approaches are presented and the future works are outlooked.
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Lim, Myung-Jin, Moung-Ho Yi, and Ju-Hyun Shin. "Intrinsic Emotion Recognition Considering the Emotional Association in Dialogues." Electronics 12, no. 2 (January 8, 2023): 326. http://dx.doi.org/10.3390/electronics12020326.
Full textAbstract:
Computer communication via text messaging or Social Networking Services (SNS) has become increasingly popular. At this time, many studies are being conducted to analyze user information or opinions and recognize emotions by using a large amount of data. Currently, the methods for the emotion recognition of dialogues requires an analysis of emotion keywords or vocabulary, and dialogue data are mostly classified as a single emotion. Recently, datasets classified as multiple emotions have emerged, but most of them are composed of English datasets. For accurate emotion recognition, a method for recognizing various emotions in one sentence is required. In addition, multi-emotion recognition research in Korean dialogue datasets is also needed. Since dialogues are exchanges between speakers. One’s feelings may be changed by the words of others, and feelings, once generated, may last for a long period of time. Emotions are expressed not only through vocabulary, but also indirectly through dialogues. In order to improve the performance of emotion recognition, it is necessary to analyze Emotional Association in Dialogues (EAD) to effectively reflect various factors that induce emotions. Therefore, in this paper, we propose a more accurate emotion recognition method to overcome the limitations of single emotion recognition. We implement Intrinsic Emotion Recognition (IER) to understand the meaning of dialogue and recognize complex emotions. In addition, conversations are classified according to their characteristics, and the correlation between IER is analyzed to derive Emotional Association in Dialogues (EAD) and apply them. To verify the usefulness of the proposed technique, IER applied with EAD is tested and evaluated. This evaluation determined that Micro-F1 of the proposed method exhibited the best performance, with 74.8% accuracy. Using IER to assess the EAD proposed in this paper can improve the accuracy and performance of emotion recognition in dialogues.
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Alruily, Meshrif. "Classification of Arabic Tweets: A Review." Electronics 10, no. 10 (May 12, 2021): 1143. http://dx.doi.org/10.3390/electronics10101143.
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Text classification is a prominent research area, gaining more interest in academia, industry and social media. Arabic is one of the world’s most famous languages and it had a significant role in science, mathematics and philosophy in Europe in the middle ages. During the Arab Spring, social media, that is, Facebook, Twitter and Instagram, played an essential role in establishing, running, and spreading these movements. Arabic Sentiment Analysis (ASA) and Arabic Text Classification (ATC) for these social media tools are hot topics, aiming to obtain valuable Arabic text insights. Although some surveys are available on this topic, the studies and research on Arabic Tweets need to be classified on the basis of machine learning algorithms. Machine learning algorithms and lexicon-based classifications are considered essential tools for text processing. In this paper, a comparison of previous surveys is presented, elaborating the need for a comprehensive study on Arabic Tweets. Research studies are classified according to machine learning algorithms, supervised learning, unsupervised learning, hybrid, and lexicon-based classifications, and their advantages/disadvantages are discussed comprehensively. We pose different challenges and future research directions.
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Kwon, Min-Cheol, and Sunwoong Choi. "Recognition of Daily Human Activity Using an Artificial Neural Network and Smartwatch." Wireless Communications and Mobile Computing 2018 (June 13, 2018): 1–9. http://dx.doi.org/10.1155/2018/2618045.
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Human activity recognition using wearable devices has been actively investigated in a wide range of applications. Most of them, however, either focus on simple activities wherein whole body movement is involved or require a variety of sensors to identify daily activities. In this study, we propose a human activity recognition system that collects data from an off-the-shelf smartwatch and uses an artificial neural network for classification. The proposed system is further enhanced using location information. We consider 11 activities, including both simple and daily activities. Experimental results show that various activities can be classified with an accuracy of 95%.
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Ruzicka, Michal, Lukas Jabloncik, Petr Dejdar, Adrian Tomasov, Vladimir Spurny, and Petr Munster. "Classification of Events Violating the Safety of Physical Layers in Fiber-Optic Network Infrastructures." Sensors 22, no. 23 (December 6, 2022): 9515. http://dx.doi.org/10.3390/s22239515.
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Fiber-optic network infrastructures are crucial for the transmission of data over long and short distances. Fiber optics are also preferred for the infrastructure of in-building data communications. In this study, we use polarization analysis to ensure the security of the optical fiber/cables of the physical layer. This method exploits the changes induced by mechanical vibrations to polarization states, which can be easily detected using a polarization beam splitter and a balancing photodetector. We use machine learning to classify selected events that violate the safety of the physical layer, such as manipulation or temporary disconnection of connectors. The results show the resting state can be accurately distinguished from selected security breaches for a fiber route subjected to environmental disturbances, where individual events can be classified with nearly 99% accuracy.
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Erginli, Mustafa, and Ibrahim Cil. "Deep-Learning-Based Floor Path Model for Route Tracking of Autonomous Vehicles." Systems 10, no. 3 (June 15, 2022): 83. http://dx.doi.org/10.3390/systems10030083.
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Real-time route tracking is an important research topic for autonomous vehicles used in industrial facilities. Traditional methods such as copper line tracking on the ground, wireless guidance systems, and laser systems are still used in route tracking. In this study, a deep-learning-based floor path model for route tracking of autonomous vehicles is proposed. A deep-learning floor path model and algorithm have been developed for highly accurate route tracking, which avoids collisions of vehicles and follows the shortest route to reach the destination. The floor path model consists of markers. Routes in the floor path model are created by using these markers. The floor path model is transmitted to autonomous vehicles as a vector by a central server. The server dispatches the target marker address to the vehicle to move. The vehicle calculates all possible routes to this address and chooses the shortest one. Marker images on the selected route are processed using image processing and classified with a pre-trained deep-CNN model. If the classified image and the image on the selected route are the same, the vehicle proceeds toward its destination. While the vehicle moves on the route, it sends the last classified marker to the server. Other autonomous vehicles use this marker to determine the location of this vehicle. Other vehicles on the route wait to avoid a collision. As a result of the experimental studies we have carried out, the route tracking of the vehicles has been successfully achieved.
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Liu, Qi, Li Hou, Sana Shaukat, Usman Tariq, Rabia Riaz, and Sanam Shahla Rizvi. "Perceptions of spatial patterns of visitors in urban green spaces for the sustainability of smart city." International Journal of Distributed Sensor Networks 17, no. 8 (August 2021): 155014772110340. http://dx.doi.org/10.1177/15501477211034069.
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Urban green spaces are really vital for the well-being of human in urban areas. In urban planning for green space site selection, the study of the bond among the usage of green spaces and their categories that really influence their use can provide useful references. A spatial and temporal research on the allocation of visitors in 157 green areas was carried out in Shanghai to know which green spaces are denser or crowdsourced by utilizing social media big data. We evaluated the association with statistical testing and Kernel Density Estimation among the spatial pattern of the visitor spread in urban green areas. We used check-in data from social media to test this study comparing the number of humans who visit various green parks. We have classified green areas into various categories and our main findings are focused on their characteristics: (1) famous category of green parks according to visitors’ preferences, (2) Differences in the number of visitors by daytime, and (3) crowdsourced area based upon number of check-ins. The main aim of this article is to remind policy makers of the value of providing local people access to green areas and to empower cities with a framework for contacting green parks with the purpose of increasing the comfort of urban people with the architecture of smart city.
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Yoon, Jiyoung, Eun Jung Hur, and Minsun Kim. "An Analysis of the Factors on the Problem-Solving Competencies of Engineering Employees in Korea." Sustainability 12, no. 4 (February 24, 2020): 1677. http://dx.doi.org/10.3390/su12041677.
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The purpose of this study is to analyze the effect of the factors on the problem-solving competency of engineering graduates. To this end, we use the 2016 Korean survey data among the Program for the International Assessment of Adult Competencies (PIAAC) survey data conducted by the Organization for Economic Co-operation and Development (OECD). In summary of the study’s major results, older people and females have lower problem-solving competencies (Model 1); higher literacy and numeracy competencies lead to higher problem-solving competencies (Model 2); and those with more experiences of sharing work-related information have higher problem-solving competencies. However, those who give more presentations have lower problem-solving competencies (Model 3), and those who make frequent use of Information and Communications Technology (ICT) to send or receive e-mails or conduct real-time discussions have higher problem-solving competencies (Model 4). These results present implications from the two perspectives of “sustainability” and “integration.” Sustainability is further classified into the following two perspectives: (1) sustainability from the longitudinal viewpoint of middle school, high school, and then job education, and (2) sustainability from the cross-sectional perspective of sustainable organization cultures. In addition, the implications of integration are based on common growth with other related core competencies besides problem-solving competencies.
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Ouai, Atallah, Lakhdar Mokrani, Mohamed Machmoum, and Azeddine Houari. "Power Quality Improvement of a Solar Energy Conversion System by a Coordinated Active and LCL Filtering." Periodica Polytechnica Electrical Engineering and Computer Science 65, no. 4 (October 29, 2021): 373–81. http://dx.doi.org/10.3311/ppee.17215.
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Power converters play an essential role in Photovoltaic (PV) system to maximize the power transfer to the electrical grid. However, the generated harmonics in the grids due to these power converters and nonlinear loads are considered one of the encountered problems to overcome. This paper presents a decoupled control of PV field real power and reactive power injected to the high voltage network via a PWM inverter by using fuzzy logic controllers. Elsewhere, a procedure based on a coordinated active and LCL filtering is proposed to mitigate the harmonic current introduced by a nonlinear load and the inverter itself in such a way to enhance the power quality injected into the grid. The results obtained in the present study show the good performance of the suggested hybrid filtering approach and demonstrate that almost all harmonics orders of the grid current are well mitigated; the current Total Harmonic Distortion (THD) meets its standard and consequently the power quality is considerably enhanced.
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Islam, Shafiqul, Motasimul Hasan, Sumon Rana, Mst Shamima Sultana, Md Shahnawas Biswas, Md Nouroz, and Musannah Ashfaq. "Endovascular Management of Spontaneous Indirect Carotid- Cavernous Fistula." Bangladesh Journal of Neurosurgery 11, no. 2 (September 7, 2022): 128–33. http://dx.doi.org/10.3329/bjns.v11i2.61458.
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Carotid cavernous fistulas (CCF) are abnormal communications inducing shunting of blood between the carotid arterial system and the cavernous sinus (CS), resulting in flow reversal in the veins draining through the CS.1 CCFs can be classified as spontaneous or traumatic according to the etiology and direct or indirect (dural) according to the anatomical features2. The authors have dealt a case of a spontaneous indirect Carotid-Cavernous Fistula in a young male of 30 on the right side. The patient presented with headache and bulging of right eye. On examination there was pulsatile proptosis on the right side with conjunctival congestion. CT angiography revealed CCF on the right side with dilated, tortuous right ophthalmic and common facial vein. DSA revealed indirect Carotid-Cavernous Fistula fed by right middle meningeal artery (MMA), accessory meningeal artery and branch of right ophthalmic artery(OA) drained by right ophthalmic vein with abnormal communication via right common facial vein. Patient underwent transarterial embolization with ONYXR . DSA revealed total obliteration of fistula. Headache subsided and proptosis reduced immediately after embolization on procedure table with intact neurology. Almost two months down the follow up revealed complete recovery of proptosis and conjunctival congestion with no further headache. Bang. J Neurosurgery 2022; 11(2): 128-133
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Li, JieYing, and ChenXi Zheng. "Emotion Classification Method of Financial News Based on Artificial Intelligence." Wireless Communications and Mobile Computing 2022 (August 18, 2022): 1–11. http://dx.doi.org/10.1155/2022/8047582.
Full textAbstract:
With the continuous development of economy, the economic development model is constantly changing. Especially since China’s entry into WTO, the scale of economic development has reached a new height. The continuous development of economy makes the financial news module evolve towards specialization. However, with the emergence of Internet of Things technology, a large number of data appear in the network, which brings some difficulties to the classification and analysis of data economy. Emotion classification refers to the complexity and diversity of people’s emotions. It can be classified from different observation angles. Because the core content of emotion is value, human emotion should be classified mainly according to the different characteristics of the movement and change of value relationship it reflects. This paper is aimed at studying the emotional classification method of financial news based on artificial intelligence and expecting to use artificial intelligence technology and classification method to classify financial news. It allows more people to know the implied information of financial information and promotes economic development. Artificial intelligence is a branch of computer science. It attempts to understand the essence of intelligence and produce a new intelligent machine that can respond in a similar way to human intelligence. This paper mainly summarizes the topic selection characteristics and subdivision topic selection characteristics of financial data news through quantitative and qualitative methods and explores the classification of financial news. In this paper, a simplified classification algorithm based on convolution function is proposed for the classification of traditional financial news networks. The experimental results show that the classification accuracy of artificial intelligence method is improved by 4% compared with the traditional emotion classification method, and the classification accuracy of positive emotion is lower than that of negative emotion by 2%.
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Chen, Peng, Yonghong Xie, Pei Jin, and Dezheng Zhang. "A wireless sensor data-based coal mine gas monitoring algorithm with least squares support vector machines optimized by swarm intelligence techniques." International Journal of Distributed Sensor Networks 14, no. 5 (May 2018): 155014771877744. http://dx.doi.org/10.1177/1550147718777440.
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As the integral part of the new generation of information technology, the Internet of things significantly accelerates the intelligent sensing and data fusion in different industrial processes including mining, assisting people to make appropriate decision. These days, an increasing number of coal mine disasters pose a serious threat to people’s lives and property especially in several developing countries. In order to assess the risks arisen from gas explosion or gas poisoning, wireless sensor data should be processed and classified efficiently. Due to the fact that the “negative samples” of coal mine safety data are scarce, least squares support vector machine is introduced to deal with this problem. In addition, several swarm intelligence techniques such as particle swarm optimization, artificial bee colony algorithm, and genetic algorithm are applied to optimize the hyper parameters of least squares support vector machine. Using the popular deep neural networks, convolutional neural network and long short-term memory model, as comparisons, a number of experiments are carried out on several UCI machine learning datasets with different features. Experimental results show that least squares support vector machine optimized by swarm intelligence techniques can effectively handle classification task on different datasets especially on those datasets with limited samples and mixed attributes. The application of least squares support vector machine optimized by swarm intelligence techniques on real coal mine data demonstrates that this algorithm can process the data accurately and timely, therefore can warn of the accidents early in mining workplace.
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Chen, Fan-Lun, and Kun-Hsing Liu. "Method for rapid deployment of low-cost sensors for a nationwide project in the Internet of things era: Air quality monitoring in Taiwan." International Journal of Distributed Sensor Networks 16, no. 8 (August 2020): 155014772095133. http://dx.doi.org/10.1177/1550147720951334.
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When the air quality problem of PM2.5 first raised public attention and an emerging low-cost sensor technology appeared suitable as a monitoring measure for said problem, Taiwan’s Environmental Protection Administration devised a nationwide project involving large-scale sensor deployment for effective pollution monitoring and management. However, the conventional siting optimization methods were inadequate for deploying thousands of sensors. Therefore, this study develops a rapid deployment method. The current results may serve as a reference for the Taiwan government for use in the aforementioned nationwide project, which is an environmental Internet of things–based plan involving 10,200 sensors to be deployed throughout the country. The four monitoring targets are classified as types of industry, traffic areas, communities, and remoteness, and a three-phase implementation structure is devised in the method. The open-source geographic information system software named QGIS was used to implement the proposed method with relevant spatial data from local open-data resources, which generated new, necessary geographic features and estimated sensor deployment quantity in Taiwan. The deployment result of the 10,200 sensors is 4790 in the type of industry, 708 of the traffic area, 3935 of the communities, and 767 of remoteness. The proposed method could serve as a useful foundation for the sensor deployment of environmental Internet of things. Policymakers may apply this method to budget allocation or integrate this method alongside conventional siting methods for the modification of deployment results based on the local monitoring requirements.
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Zagoya-López, Joel, Luis Adrián Zúñiga-Avilés, Adriana H. Vilchis-González, and Juan Carlos Ávila-Vilchis. "Foot/Ankle Prostheses Design Approach Based on Scientometric and Patentometric Analyses." Applied Sciences 11, no. 12 (June 17, 2021): 5591. http://dx.doi.org/10.3390/app11125591.
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There are different alternatives when selecting removable prostheses for below the knee amputated patients. The designs of these prostheses vary according to their different functions. These prostheses designs can be classified into Energy Storing and Return (ESAR), Controlled Energy Storing and Return (CESR), active, and hybrid. This paper aims to identify the state of the art related to the design of these prostheses of which ESAR prostheses are grouped into five types, and active and CESR are categorized into four groups. Regarding patent analysis, 324 were analyzed over the last six years. For scientific communications, a bibliometric analysis was performed using 104 scientific reports from the Web of Science in the same period. The results show a tendency of ESAR prostheses designs for patents (68%) and active prostheses designs for scientific documentation (40%).