Search results for: blue-green landscape network

Authors: Dararat Tongdee, Surapong Chirarattananon, Somchai Maneewan, Chantana Punlek

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Recently, the Internet of Things (IoT) is the important technology that connects devices to the network and people can access real-time communication. This technology is used to report, collect, and analyze the big data for achieving a purpose. For a smart building, there are many IoT technologies that enable management and building operators to improve occupant thermal comfort, indoor air quality, and building energy efficiency. In this research, we propose monitoring and controlling performance of a smart dedicated outdoor air system (SDOAS) based on IoT platform. The SDOAS was specifically designed with the desiccant unit and thermoelectric module. The designed system was intended to monitor, notify, and control indoor environmental factors such as temperature, humidity, and carbon dioxide (CO₂) level. The SDOAS was tested under the American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE 62.2) and indoor air quality standard. The system will notify the user by Blynk notification when the status of the building is uncomfortable or tolerable limits are reached according to the conditions that were set. The user can then control the system via a Blynk application on a smartphone. The experimental result indicates that the temperature and humidity of indoor fresh air in the comfort zone are approximately 26 degree Celsius and 58% respectively. Furthermore, the CO₂ level was controlled lower than 1000 ppm by indoor air quality standard condition. Therefore, the proposed system can efficiently work and be easy to use for buildings.

Keywords: internet of things, indoor air quality, smart dedicated outdoor air system, thermal comfort

Procedia PDF Downloads 199

Authors: Kawthar F. Albasri, Abdullah M. AlHudaithi, Dana B. AlTurairi, Abdullaziz S. AlQuraini, Adoub Y. AlDerazi, Reem A. Hubail, Haitham A. Jahrami

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Several studies have found that medical students have a significant prevalence of anxiety. The purpose of this review paper is to carefully evaluate the current research on anxiety among medical students in the MENA region and, as a result, estimate the prevalence of these disturbances. Multiple databases, including the CINAHL (Cumulative Index to Nursing and Allied Health Literature), Cochrane Library, Embase, MEDLINE (Medical Literature Analysis and Retrieval System Online), PubMed, PsycINFO (Psychological Information Database), Scopus, Web of Science, UpToDate, ClinicalTrials.gov, WHO Global Health Library, EbscoHost, ProQuest, JAMA Network, and ScienceDirect, were searched. The retrieved article reference lists were rigorously searched and rated for quality. A random effects meta-analysis was performed to compute estimates. The current meta-analysis revealed an alarming estimated pooled prevalence of anxiety (K = 46, N = 27023) of 52.5% [95%CI: 43.3%–61.6%]. A total of 62.0% [95% CI 42.9%; 78.0%] of the students (K = 18, N = 16466) suffered from anxiety during the COVID-19 pandemic, while 52.5% [95% CI 43.3%; 61.6%] had anxiety before COVID-19. Based on the GAD-7 measure, a total of 55.7% [95%CI 30.5%; 78.3%] of the students (K = 10, N = 5830) had anxiety, and a total of 54.7% of the students (K = 18, N = 12154) [95%CI 42.8%; 66.0%] had anxiety using the DASS-21 or 42 measure. Anxiety is a common issue among medical students, making it a genuine problem. Further research should be conducted post-COVD 19, with a focus on anxiety prevention and intervention initiatives for medical students.

Keywords: anxiety, medical students, MENA, meta-analysis, prevalence

Procedia PDF Downloads 73

Authors: Pardhasaradhi Gudla, Imanual A.

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The generated electrical power in offshore needs to be transmitted to grid which is located in onshore by using subsea cables. Long subsea cables produce reactive power, which should be compensated in order to limit transmission losses, to optimize the transmission capacity, and to keep the grid voltage within the safe operational limits. Installation cost of wind farm includes the structure design cost and electrical system cost. India has targeted to achieve 175GW of renewable energy capacity by 2022 including offshore wind power generation. Due to sea depth is more in India, the installation cost will be further high when compared to European countries where offshore wind energy is already generating successfully. So innovations are required to reduce the offshore wind power project cost. This paper presents the optimized techniques to reduce the installation cost of offshore wind firm with respect to electrical transmission systems. This technical paper provides the techniques for increasing the current carrying capacity of subsea cable by decreasing the reactive power generation (capacitance effect) of the subsea cable. There are many methods for reactive power compensation in wind power plants so far in execution. The main reason for the need of reactive power compensation is capacitance effect of subsea cable. So if we diminish the cable capacitance of cable then the requirement of the reactive power compensation will be reduced or optimized by avoiding the intermediate substation at midpoint of the transmission network.

Keywords: offshore wind power, optimized techniques, power system, sub sea cable

Procedia PDF Downloads 194

Authors: Sajjad Akbar, Rabia Bashir

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With the growth of the number of users, the Internet usage has evolved. Due to its key design principle, there is an incredible expansion in its size. This tremendous growth of the Internet has brought new applications (mobile video and cloud computing) as well as new user’s requirements i.e. content distribution environment, mobility, ubiquity, security and trust etc. The users are more interested in contents rather than their communicating peer nodes. The current Internet architecture is a host-centric networking approach, which is not suitable for the specific type of applications. With the growing use of multiple interactive applications, the host centric approach is considered to be less efficient as it depends on the physical location, for this, Information Centric Networking (ICN) is considered as the potential future Internet architecture. It is an approach that introduces uniquely named data as a core Internet principle. It uses the receiver oriented approach rather than sender oriented. It introduces the naming base information system at the network layer. Although ICN is considered as future Internet architecture but there are lot of criticism on it which mainly concerns that how ICN will manage the most relevant content. For this Web Content Mining(WCM) approaches can help in appropriate data management of ICN. To address this issue, this paper contributes by (i) discussing multiple ICN approaches (ii) analyzing different Web Content Mining approaches (iii) creating a new Internet architecture by merging ICN and WCM to solve the data management issues of ICN. From ICN, Content-Centric Networking (CCN) is selected for the new architecture, whereas, Agent-based approach from Web Content Mining is selected to find most appropriate data.

Keywords: agent based web content mining, content centric networking, information centric networking

Procedia PDF Downloads 475

Authors: Xiang Li, Jian-Qiao Sun

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As the crucial component of city traffic network, intersections have significant impacts on urban traffic performance. Despite of the rapid development in transportation systems, increasing traffic volumes result in severe congestions especially at intersections in urban areas. Effective regulation of vehicle flows at intersections has always been an important issue in the traffic control system. This study presents a multi-objective optimization method at intersections with cellular automata to achieve better traffic performance. Vehicle conflicts and pedestrian interference are considered. Three categories of the traffic performance are studied including transportation efficiency, energy consumption and road safety. The left-turn signal type, signal timing and lane assignment are optimized for different traffic flows. The multi-objective optimization problem is solved with the cell mapping method. The optimization results show the conflicting nature of different traffic performance. The influence of different traffic variables on the intersection performance is investigated. It is observed that the proposed optimization method is effective in regulating the traffic at the intersection to meet multiple objectives. Transportation efficiency can be usually improved by the permissive left-turn signal, which sacrifices safety. Right-turn traffic suffers significantly when the right-turn lanes are shared with the through vehicles. The effect of vehicle flow on the intersection performance is significant. The display pattern of the optimization results can be changed remarkably by the traffic volume variation. Pedestrians have strong interference with the traffic system.

Keywords: cellular automata, intersection, multi-objective optimization, traffic system

Procedia PDF Downloads 580

Authors: Alisan Kayabolen, Dilek Keskin, Ferit Avcu, Andac Aykan, Fatih Zor, Aysen Tezcaner

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Adipose tissue engineering is a promising field for regeneration of soft tissue defects. However, only very thin implants can be used in vivo since vascularization is still a problem for thick implants. Another problem is finding a biocompatible scaffold with good mechanical properties. In this study, the aim is to develop a thick vascularized adipose tissue that will integrate with the host, and perform its in vitro and in vivo characterizations. For this purpose, a hydrogel of decellularized adipose tissue (DAT) and fibroin was produced, and both endothelial cells and adipocytes that were differentiated from adipose derived stem cells were encapsulated in this hydrogel. Mixing DAT with fibroin allowed rapid gel formation by vortexing. It also provided to adjust mechanical strength by changing fibroin to DAT ratio. Based on compression tests, gels of DAT/fibroin ratio with similar mechanical properties to adipose tissue was selected for cell culture experiments. In vitro characterizations showed that DAT is not cytotoxic; on the contrary, it has many natural ECM components which provide biocompatibility and bioactivity. Subcutaneous implantation of hydrogels resulted with no immunogenic reaction or infection. Moreover, localized empty hydrogels gelled successfully around host vessel with required shape. Implantations of cell encapsulated hydrogels and histological analyses are under study. It is expected that endothelial cells inside the hydrogel will form a capillary network and they will bind to the host vessel passing through hydrogel.

Keywords: adipose tissue engineering, decellularization, encapsulation, hydrogel, vascularization

Procedia PDF Downloads 528

Authors: Hafiz Muhammad Adeel Sharif, Tian Li, Changping Li

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Recently, the emission of nitrogen-sulphur oxides (NOₓ, SO₂) has become a global issue and causing serious threats to health and the environment. Catalytic reduction of NOx and SOₓ gases into friendly gases is considered one of the best approaches. However, regeneration of the catalyst, higher bond-dissociation energy for NOx, i.e., 150.7 kcal/mol, escape of intermediate gas (N₂O, a greenhouse gas) with treated flue-gas, and limited activity of catalyst remains a great challenge. Here, a cheap, binderless naturally-extracted bass-wood thin carbon electrode (TCE) is presented, which shows excellent catalytic activity towards NOx reduction. The bass-wood carbonization at 900 ℃ followed by thermal activation in the presence of CO2 gas at 750 ℃. The thermal activation resulted in an increase in epoxy groups on the surface of the TCE and enhancement in the surface area as well as the degree of graphitization. The TCE unique 3D strongly inter-connected network through hierarchical micro/meso/macro pores that allow large electrode/electrolyte interface. Owing to these characteristics, the TCE exhibited excellent catalytic efficiency towards NOx (~83.3%) under ambient conditions and enhanced catalytic response under pH and sulphite exposure as well as excellent stability up to 168 hours. Moreover, a temperature-dependent activity trend was found where the highest catalytic activity was achieved at 80 ℃, beyond which the electrolyte became evaporative and resulted in a performance decrease. The designed electrocatalyst showed great potential for effective NOx-reduction, which is highly cost-effective, green, and sustainable.

Keywords: electrocatalyst, NOx-reduction, bass-wood electrode, integrated wet-scrubbing, sustainable

Procedia PDF Downloads 77

Authors: Ma Yuzhe, Burra Venkata Durga Kumar

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The computer is a great invention. As people use computers more and more frequently, the demand for PCs is growing, and the performance of computer hardware is also rising to face more complex processing and operation. However, the operating system, which provides the soul for computers, has stopped developing at a stage. In the face of the high price of UNIX (Uniplexed Information and Computering System), batch after batch of personal computer owners can only give up. Disk Operating System is too simple and difficult to bring innovation into play, which is not a good choice. And MacOS is a special operating system for Apple computers, and it can not be widely used on personal computers. In this environment, Linux, based on the UNIX system, was born. Linux combines the advantages of the operating system and is composed of many microkernels, which is relatively powerful in the core architecture. Linux system supports all Internet protocols, so it has very good network functions. Linux supports multiple users. Each user has no influence on their own files. Linux can also multitask and run different programs independently at the same time. Linux is a completely open source operating system. Users can obtain and modify the source code for free. Because of these advantages of Linux, it has also attracted a large number of users and programmers. The Linux system is also constantly upgraded and improved. It has also issued many different versions, which are suitable for community use and commercial use. Linux system has good security because it relies on a file partition system. However, due to the constant updating of vulnerabilities and hazards, the using security of the operating system also needs to be paid more attention to. This article will focus on the analysis and discussion of Linux security issues.

Keywords: Linux, operating system, system management, security

Procedia PDF Downloads 109

Authors: Jung Park, Anca Mazare, Klaus Von Der Mark, Patrik Schmuki

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In clinical application of TiO2 implants on tooth and hip replacement, migration, adhesion and differentiation of neighboring mesenchymal stem cells onto implant surfaces are critical steps for successful bone regeneration. In a recent decade, accumulated attention has been paid on nanoscale electrochemical surface modifications on TiO2 layer for improving bone-TiO2 surface integration. We generated, on titanium surfaces, self-assembled layers of vertically oriented TiO2 nanotubes with defined diameters between 15 and 100 nm and here we show that mesenchymal stem cells finely sense TiO2 nanotubular geometry and quickly decide their cell fate either to differentiation into osteoblasts or to programmed cell death (apoptosis) on TiO2 nanotube layers. These cell fate decisions are critically dependent on nanotube size differences (15-100nm in diameters) of TiO2 nanotubes sensing by integrin clustering. We further demonstrate that nanoscale topography-sensing is feasible not only in mesenchymal stem cells but rather seems as generalized nanoscale microenvironment-cell interaction mechanism in several cell types composing bone tissue network including osteoblasts, osteoclast, endothelial cells and hematopoietic stem cells. Additionally we discuss the synergistic effect of simultaneous stimulation by nanotube-bound growth factor and nanoscale topographic cues on enhanced bone regeneration.

Keywords: TiO2 nanotube, stem cell fate decision, nano-scale microenvironment, bone regeneration

Procedia PDF Downloads 432

Authors: Mohammad Derakhshani, Saeed Reza Allahkarama, Michael Isakhani-Zakaria, Masoud Samadian, Hojjat Sharifi Rasaey

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In order to investigate the effects of stray current from DC traction systems (subway) on cathodically protected gas pipelines, the subway and the gas network maps in the city of Tehran were superimposed and a comprehensive map was prepared. 213 intersections and about 100150 meters of parallel sections of gas pipelines were found with respect to the railway right of way which was specified for field measurements. The potential measurements data were logged for one hour in each test point. 24-hour potential monitoring was carried out in selected test points as well. Results showed that dynamic stray current from subway on pipeline potential appears as fluctuations in its static potential that is visible in the diagrams during night periods. These fluctuations can cause the pipeline potential to exit the safe zone and lead to corrosion or overprotection. In this study, a maximum potential shift of 100 mv in the pipe-to-soil potential was considered as a criterion for dynamic stray current effective presence. Results showed that a potential fluctuation range between 100 mV to 3 V exists in measured points on pipelines which exceeds the proposed criterion and needs to be investigated. Corrosion rates influenced by stray currents were calculated using coupons. Results showed that coupon linked to the pipeline in one of the locations at region 1 of the city of Tehran has a corrosion rate of 4.2 mpy (with cathodic protection and under influence of stray currents) which is about 1.5 times more than free corrosion rate of 2.6 mpy.

Keywords: stray current, DC traction, subway, buried Pipelines, cathodic protection list

Procedia PDF Downloads 822

Authors: Arnaldo G. de Oliveira, Jr, Matthieu Tubino

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The transesterification process of triglycerides with alcohols that occurs during the biodiesel synthesis causes continuous changes in several physical properties of the reaction mixture, such as refractive index, viscosity and density. Amongst them, density can be an useful parameter to monitor the reaction, in order to predict the composition of the reacting mixture and to verify the conversion of the oil into biodiesel. In this context, a system was constructed in order to continuously determine changes in the density of the reacting mixture containing soybean oil, methanol and sodium methoxide (30 % w/w solution in methanol), stirred at 620 rpm at room temperature (about 27 °C). A polyethylene pipe network connected to a peristaltic pump was used in order to collect the mixture and pump it through a coil fixed on the plate of an analytical balance. The collected mass values were used to trace a curve correlating the mass of the system to the reaction time. The density variation profile versus the time clearly shows three different steps: 1) the dispersion of methanol in oil causes a decrease in the system mass due to the lower alcohol density followed by stabilization; 2) the addition of the catalyst (sodium methoxide) causes a larger decrease in mass compared to the first step (dispersion of methanol in oil) because of the oil conversion into biodiesel; 3) the final stabilization, denoting the end of the reaction. This density variation profile provides information that was used to predict the composition of the mixture over the time and the reaction rate. The precise knowledge of the duration of the synthesis means saving time and resources on a scale production system. This kind of monitoring provides several interesting features such as continuous measurements without collecting aliquots.

Keywords: biodiesel, density measurements, online continuous monitoring, synthesis

Procedia PDF Downloads 576

Authors: Raymond Xu, Ashley Hua, Andrew Wang, Yuru Lin

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During COVID-19, the depression rate has increased dramatically. Young adults are most vulnerable to the mental health effects of the pandemic. Lower-income families have a higher ratio to be diagnosed with depression than the general population, but less access to clinics. This research aims to achieve early depression detection at low cost, large scale, and high accuracy with an interdisciplinary approach by incorporating clinical practices defined by American Psychiatric Association (APA) as well as multimodal AI framework. The proposed approach detected the nine depression symptoms with Natural Language Processing sentiment analysis and a symptom-based Lexicon uniquely designed for young adults. The experiments were conducted on the multimedia survey results from adolescents and young adults and unbiased Twitter communications. The result was further aggregated with the facial emotional cues analyzed by the Convolutional Neural Network on the multimedia survey videos. Five experiments each conducted on 10k data entries reached consistent results with an average accuracy of 88.31%, higher than the existing natural language analysis models. This approach can reach 300+ million daily active Twitter users and is highly accessible by low-income populations to promote early depression detection to raise awareness in adolescents and young adults and reveal complementary cues to assist clinical depression diagnosis.

Keywords: artificial intelligence, COVID-19, depression detection, psychiatric disorder

Procedia PDF Downloads 131

Authors: Maayan Nakash

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The modern workplace is undergoing a revolution, with Generation Z (Gen-Z) at the forefront of this transformative shift. However, empirical investigations specifically targeting the workplace preferences of this generation remain limited. Through direct examination of their tendencies via a survey approach, this study offers vital insights for aligning organizational policies and practices. The results presented in this paper are part of a comprehensive study that explored Gen Z's viewpoints on various employment market aspects, likely to decisively influence the design of future work environments. Data were collected via an online survey distributed among a cohort of 461 individuals from Gen-Z, born between the mid-1990s and 2010, consisting of 241 males (52.28%) and 220 females (47.72%). Responses were gauged using Likert scale statements that probed preferences for teamwork versus individual work, virtual versus personal interactions, and open versus private workspaces. Descriptive statistics and analytical analyses were conducted to pinpoint key patterns. We discovered that a high proportion of respondents (81.99%, n=378) exhibited a preference for teamwork over individual work. Correspondingly, the data indicate strong support for the recognition of team-based tasks as a tool contributing to personal and professional development. In terms of communication, the majority of respondents (61.38%) either disagreed (n=154) or slightly agreed (n=129) with the exclusive reliance on virtual interactions with their organizational peers. This finding underscores that despite technological progress, digital natives place significant value on physical interaction and non-mediated communication. Moreover, we understand that they also value a quiet and private work environment, clearly preferring it over open and shared workspaces. Considering that Gen-Z does not necessarily experience high levels of stress within social frameworks in the workplace, this can be attributed to a desire for a space that allows for focused engagement with work tasks. A One-Sample Chi-Square Test was performed on the observed distribution of respondents' reactions to each examined statement. The results showed statistically significant deviations from a uniform distribution (p<.001), indicating that the response patterns did not occur by chance and that there were meaningful tendencies in the participants' responses. The findings expand the theoretical knowledge base on human resources in the dynamics of a multi-generational workforce, illuminating the values, approaches, and expectations of Gen-Z. Practically, the results may lead organizations to equip themselves with tools to create policies tailored to Gen-Z in the context of workspaces and social needs, which could potentially foster a fertile environment and aid in attracting and retaining young talent. Future studies might include investigating potential mitigating factors, such as cultural influences or individual personality traits, which could further clarify the nuances in Gen-Z's work style preferences. Longitudinal studies tracking changes in these preferences as the generation matures may also yield valuable insights. Ultimately, as the landscape of the workforce continues to evolve, ongoing investigations into the unique characteristics and aspirations of emerging generations remain essential for nurturing harmonious, productive, and future-ready organizational environments.

Keywords: workplace, future of work, generation Z, digital natives, human resources management

Procedia PDF Downloads 53

Authors: Mirjana Ruppel, Rajendra Persad, Amit Bahl, Sanja Dogramadzi, Chris Melhuish, Lyndon Smith

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Multimodal image registration is a profoundly complex task which is why deep learning has been used widely to address it in recent years. However, two main challenges remain: Firstly, the lack of ground truth data calls for an unsupervised learning approach, which leads to the second challenge of defining a feasible loss function that can compare two images of different modalities to judge their level of alignment. To avoid this issue altogether we implement a generative adversarial network consisting of two registration networks GAB, GBA and two discrimination networks DA, DB connected by spatial transformation layers. GAB learns to generate a deformation field which registers an image of the modality B to an image of the modality A. To do that, it uses the feedback of the discriminator DB which is learning to judge the quality of alignment of the registered image B. GBA and DA learn a mapping from modality A to modality B. Additionally, a cycle-consistency loss is implemented. For this, both registration networks are employed twice, therefore resulting in images ˆA, ˆB which were registered to ˜B, ˜A which were registered to the initial image pair A, B. Thus the resulting and initial images of the same modality can be easily compared. A dataset of liver CT and MRI was used to evaluate the quality of our approach and to compare it against learning and non-learning based registration algorithms. Our approach leads to dice scores of up to 0.80 ± 0.01 and is therefore comparable to and slightly more successful than algorithms like SimpleElastix and VoxelMorph.

Keywords: cycle consistency, deformable multimodal image registration, deep learning, GAN

Procedia PDF Downloads 131

Authors: Yibeltal Chanie Manie, Zebider Asire Munyelet

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5G and 6G technology offers enhanced quality of service with high data transmission rates, which necessitates the implementation of the Internet of Things (IoT) in 5G/6G architecture. In this paper, we proposed the integration of free space optical communication (FSO) with fiber sensor networks for IoT applications. Recently, free-space optical communications (FSO) are gaining popularity as an effective alternative technology to the limited availability of radio frequency (RF) spectrum. FSO is gaining popularity due to flexibility, high achievable optical bandwidth, and low power consumption in several applications of communications, such as disaster recovery, last-mile connectivity, drones, surveillance, backhaul, and satellite communications. Hence, high-speed FSO is an optimal choice for wireless networks to satisfy the full potential of 5G/6G technology, offering 100 Gbit/s or more speed in IoT applications. Moreover, machine learning must be integrated into the design, planning, and optimization of future optical wireless communication networks in order to actualize this vision of intelligent processing and operation. In addition, fiber sensors are important to achieve real-time, accurate, and smart monitoring in IoT applications. Moreover, we proposed deep learning techniques to estimate the strain changes and peak wavelength of multiple Fiber Bragg grating (FBG) sensors using only the spectrum of FBGs obtained from the real experiment.

Keywords: optical sensor, artificial Intelligence, Internet of Things, free-space optics

Procedia PDF Downloads 63

Authors: Abdulkader Helwan

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Iris cancer, so called intraocular melanoma is a cancer that starts in the iris; the colored part of the eye that surrounds the pupil. There is a need for an accurate and cost-effective iris cancer detection system since the available techniques used currently are still not efficient. The combination of the image processing and artificial neural networks has a great efficiency for the diagnosis and detection of the iris cancer. Image processing techniques improve the diagnosis of the cancer by enhancing the quality of the images, so the physicians diagnose properly. However, neural networks can help in making decision; whether the eye is cancerous or not. This paper aims to develop an intelligent system that stimulates a human visual detection of the intraocular melanoma, so called iris cancer. The suggested system combines both image processing techniques and neural networks. The images are first converted to grayscale, filtered, and then segmented using prewitt edge detection algorithm to detect the iris, sclera circles and the cancer. The principal component analysis is used to reduce the image size and for extracting features. Those features are considered then as inputs for a neural network which is capable of deciding if the eye is cancerous or not, throughout its experience adopted by many training iterations of different normal and abnormal eye images during the training phase. Normal images are obtained from a public database available on the internet, “Mile Research”, while the abnormal ones are obtained from another database which is the “eyecancer”. The experimental results for the proposed system show high accuracy 100% for detecting cancer and making the right decision.

Keywords: iris cancer, intraocular melanoma, cancerous, prewitt edge detection algorithm, sclera

Procedia PDF Downloads 503

Authors: Tariq Mahmood, Faiza Lehrasab, Faraz Akrim, Muhammad Sajid nadeem, Muhammad Mushtaq, Unza waqar, Ayesha Sheraz, Shaista Andleeb

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Brown bear (Ursus arctos), a member of the family Ursidae, is distributed in a wide range of habitats in North America, Europe and Asia. Suspectedly, the global distribution range of brown bears is decreasing at the moment due to various factors. The carnivore species is categorized as ‘Least Concern’ globally by the IUCN Red List of Threatened Species. However, there are some fragmented, small populations that are on the verge of extinction, as is in Pakistan, where the species is listed as ‘Critically Endangered’, with a declining population trend. Importantly, the global historical distribution range of brown bears is undocumented. Therefore, in the current study, we reconstructed and estimated the historical distribution range of brown bears using QGIS software and also analyzed the network of protected areas in the past and current ranges of the species. Results showed that brown bear was more widely distributed in historic times, encompassing 52.6 million km² area as compared to their current distribution of 38.8 million km², resulting in a total range contraction of up to approximately 28 %. In the past, a total of N = 62,234 protected Areas, covering approximately 3.89 million km² were present in the distribution range of the species, while now a total of N= 33,313 Protected Areas, covering approximately 2.75 million km² area, are present in the current distribution range of the brown bear. The brown bear distribution range in the protected areas has also contracted by 1.15 million km² and the total percentage reduction of PAs is 29%.

Keywords: brown bear, historic distribution, range contraction, protected areas

Procedia PDF Downloads 60

Authors: Foluke E. Sola-Ojo, Ibraheem A. Abubakar, Semiu F. Bello, Isiaka H. Fatima, Sule Bisola, Adesina M. Olusegun, Adeniyi C. Adeola

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The domesticated pigeon, Columba livia domestica, has many valuable characteristics, including high nutritional value and fast growth rate. There is a lack of information on its genetic diversity in Nigeria; thus, the genetic variability in mitochondrial cytochrome oxidase subunit I (COI) sequences of 150 domestic pigeons from four different locations was examined. Three haplotypes (HT) were identified in Nigerian populations; the most common haplotype, HT1, was shared with wild and domestic pigeons from Europe, America, and Asia, while HT2 and HT3 were unique to Nigeria. The overall haplotype diversity was 0.052± 0.025, and nucleotide diversity was 0.026± 0.068 across the four investigated populations. The phylogenetic tree showed significant clustering and genetic relationship of Nigerian domestic pigeons with other global pigeons. The median-joining network showed a star-like pattern suggesting population expansion. AMOVA results indicated that genetic variations in Nigerian pigeons mainly occurred within populations (99.93%), while the Neutrality tests results suggested that the Nigerian domestic pigeons’ population experienced recent expansion. This study showed a low genetic diversity and population differentiation among Nigerian domestic pigeons consistent with a relatively conservative COI sequence with few polymorphic sites. Furthermore, the COI gene could serve as a candidate molecular marker to investigate the genetic diversity and origin of pigeon species. The current data is insufficient for further conclusions; therefore, more research evidence from multiple molecular markers is required.

Keywords: Nigeria pigeon, COI, genetic diversity, genetic variation, conservation

Procedia PDF Downloads 197

Authors: Aisultan Shoiynbek, Darkhan Kuanyshbay, Paulo Menezes, Akbayan Bekarystankyzy, Assylbek Mukhametzhanov, Temirlan Shoiynbek

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Speech emotion recognition (SER) has received increasing research interest in recent years. It is a common practice to utilize emotional speech collected under controlled conditions recorded by actors imitating and artificially producing emotions in front of a microphone. There are four issues related to that approach: emotions are not natural, meaning that machines are learning to recognize fake emotions; emotions are very limited in quantity and poor in variety of speaking; there is some language dependency in SER; consequently, each time researchers want to start work with SER, they need to find a good emotional database in their language. This paper proposes an approach to create an automatic tool for speech emotion extraction based on facial emotion recognition and describes the sequence of actions involved in the proposed approach. One of the first objectives in the sequence of actions is the speech detection issue. The paper provides a detailed description of the speech detection model based on a fully connected deep neural network for Kazakh and Russian. Despite the high results in speech detection for Kazakh and Russian, the described process is suitable for any language. To investigate the working capacity of the developed model, an analysis of speech detection and extraction from real tasks has been performed.

Keywords: deep neural networks, speech detection, speech emotion recognition, Mel-frequency cepstrum coefficients, collecting speech emotion corpus, collecting speech emotion dataset, Kazakh speech dataset

Procedia PDF Downloads 27

Authors: Amadou Fall Dia, Maurras Ulbricht Togbe, Aliou Boly, Zakia Kazi Aoul, Elisabeth Metais

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Existing RDF (Resource Description Framework) Stream Processing (RSP) systems allow continuous processing of RDF data issued from different application domains such as weather station measuring phenomena, geolocation, IoT applications, drinking water distribution management, and so on. However, processing window phase often expires before finishing the entire session and RSP systems immediately delete data streams after each processed window. Such mechanism does not allow optimized exploitation of the RDF data streams as the most relevant and pertinent information of the data is often not used in a due time and almost impossible to be exploited for further analyzes. It should be better to keep the most informative part of data within streams while minimizing the memory storage space. In this work, we propose an RDF graph summarization system based on an explicit and implicit expressed needs through three main approaches: (1) an approach for user queries (SPARQL) in order to extract their needs and group them into a more global query, (2) an extension of the closeness centrality measure issued from Social Network Analysis (SNA) to determine the most informative parts of the graph and (3) an RDF graph summarization technique combining extracted user query needs and the extended centrality measure. Experiments and evaluations show efficient results in terms of memory space storage and the most expected approximate query results on summarized graphs compared to the source ones.

Keywords: centrality measures, RDF graphs summary, RDF graphs stream, SPARQL query

Procedia PDF Downloads 203

Authors: Hiroaki Fukuda

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This paper shows a concurrent development process for modern web application, called Rich Internet Application (RIA), and describes its effect using a non-trivial application development. In the last years, RIAs such as Ajax and Flex have become popular based mainly on high-speed network. RIA provides sophisticated interfaces and user experiences, therefore, the development of RIA requires two kinds of engineer: a developer who implements business logic, and a designer who designs interface and experiences. Although collaborative works are becoming important for the development of RIAs, shared resources such as source code make it difficult. For example, if a design of interface is modified after developers have finished business logic implementations, they need to repeat the same implementations, and also tests to verify application’s behavior. MVC architecture and Object-oriented programming (OOP) enables to dividing an application into modules such as interfaces and logic, however, developers and/or designers have to write pieces of code (e.g., event handlers) that make these modules work as an application. On the other hand, Aspect-oriented programming (AOP) is ex- pected to solve complexity of application software development nowadays. AOP provides methods to separate crosscutting concerns that are scattered pieces of code from primary concerns. In this paper, we provide a concurrent development process for RIAs by introducing AOP concept. This process makes it possible to reduce shared resources between developers and designers, therefore they can perform their tasks concurrently. In addition, we describe experiences of development for a practical application using our proposed development process to show its availability.

Keywords: aspect-oriented programming, concurrent, development process, rich internet application

Procedia PDF Downloads 301

Authors: Veronika Zivicova, Petr Broz, Zdenek Fik, Alzbeta Mifkova, Jan Plzak, Zdenek Cada, Herbert Kaltner, Jana Fialova Kucerova, Hans-Joachim Gabius, Karel Smetana Jr.

Abstract:

The possibility to determine genome-wide expression profiles of cells and tissues opens a new level of analysis in the quest to define dysregulation in malignancy and thus identify new tumor markers. Toward this long-term aim, we here address two issues on this level for head and neck cancer specimen: i) defining profiles in different regions, i.e. the tumor, the transition zone and normal control and ii) comparing complete data sets for seven individual patients. Special focus in the flanking immunohistochemical part is given to adhesion/growth-regulatory galectins that upregulate chemo- and cytokine expression in an NF-κB-dependent manner, to these regulators and to markers of differentiation, i.e. keratins. The detailed listing of up- and down-regulations, also available in printed form (1), not only served to unveil new candidates for testing as marker but also let the impact of the tumor in the transition zone become apparent. The extent of interindividual variation raises a strong cautionary note on assuming uniformity of regulatory events, to be noted when considering therapeutic implications. Thus, a combination of test targets (and a network analysis for galectins and their downstream effectors) is (are) advised prior to reaching conclusions on further perspectives.

Keywords: galectins, genome scale sequencing, squamous cell carcinoma, transition zone

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Authors: G. Shahzadi, A. Soulaimani

Abstract:

This research work aims to identify the physical parameters of the constitutive soil model in the design of a rockfill dam by inverse analysis. The best parameters of the constitutive soil model, are those that minimize the objective function, defined as the difference between the measured and numerical results. The Finite Element code (Plaxis) has been utilized for numerical simulation. Polynomial and neural network-based response surfaces have been generated to analyze the relationship between soil parameters and displacements. The performance of surrogate models has been analyzed and compared by evaluating the root mean square error. A comparative study has been done based on objective functions and optimization techniques. Objective functions are categorized by considering measured data with and without uncertainty in instruments, defined by the least square method, which estimates the norm between the predicted displacements and the measured values. Hydro Quebec provided data sets for the measured values of the Romaine-2 dam. Stochastic optimization, an approach that can overcome local minima, and solve non-convex and non-differentiable problems with ease, is used to obtain an optimum value. Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and Differential Evolution (DE) are compared for the minimization problem, although all these techniques take time to converge to an optimum value; however, PSO provided the better convergence and best soil parameters. Overall, parameter identification analysis could be effectively used for the rockfill dam application and has the potential to become a valuable tool for geotechnical engineers for assessing dam performance and dam safety.

Keywords: Rockfill dam, parameter identification, stochastic analysis, regression, PLAXIS

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Authors: Deng Tingting

Abstract:

The coordinated and integrated development of regions is an inevitable requirement for China to move towards high-quality, sustainable development. As one of the regions with the best economic foundation and the strongest economic strength in western China, it is a typical area with national importance and strong network connection characteristics in terms of the comprehensive effect of linking the inland hinterland and connecting the western and national urban networks. The integrated development of the Chengdu-Chongqing economic circle is of great strategic significance for the rapid and high-quality development of the western region. In the context of new urbanization, this paper takes 16 urban units within the economic circle as the research object, based on the 5-year panel data of population, regional economy, and spatial construction and development from 2016 to 2020, using the entropy method and Theil index to analyze the three target layers, and cause analysis. The research shows that there are temporal and spatial differences in the Chengdu-Chongqing economic circle, and there are significant differences between the core city and the surrounding cities. Therefore, by reforming and innovating the regional coordinated development mechanism, breaking administrative barriers, and strengthening the "polar nucleus" radiation function to release the driving force for economic development, especially in the gully areas of economic development belts, not only promote the coordinated development of internal regions but also promote the coordinated and sustainable development of the western region and take a high-quality development path.

Keywords: Chengdu-Chongqing economic circle, new urbanization, coordinated regional development, Theil Index

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Authors: Syed Jawad Hussain, Abir Touati, Farid Touati

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Free-Space Optics (FSO) is a wireless technology that enables the optical transmission of data though the air. FSO is emerging as a promising alternative or complementary technology to fiber optic and wireless radio-frequency (RF) links due to its high-bandwidth, robustness to EMI, and operation in unregulated spectrum. These systems are envisioned to be an essential part of future generation heterogeneous communication networks. Despite the vibrant advantages of FSO technology and the variety of its applications, its widespread adoption has been hampered by rather disappointing link reliability for long-range links due to atmospheric turbulence-induced fading and sensitivity to detrimental climate conditions. Qatar, with modest cloud coverage, high concentrations of airborne dust and high relative humidity particularly lies in virtually rainless sunny belt with a typical daily average solar radiation exceeding 6 kWh/m2 and 80-90% clear skies throughout the year. The specific objective of this work is to study for the first time in Qatar the effect of solar irradiation on the deliverability of the FSO Link. In order to analyze the transport media, we have ported Embedded Linux kernel on Field Programmable Gate Array (FPGA) and designed a network sniffer application that can run into FPGA. We installed new FSO terminals and configure and align them successively. In the reporting period, we carry out measurement and relate them to weather conditions.

Keywords: free space optics, solar irradiation, field programmable gate array, FSO outage

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Authors: Rahel Birhane Eshetu

Abstract:

This research investigates the complex landscape of project management practices and operational challenges in conflict-affected areas, with a specific focus on Kewot Woreda in the North Shewa Zone of the Amhara region in Ethiopia. The study aims to identify essential project management methodologies, the significant operational hurdles faced, and the adaptive strategies employed by project managers in these challenging environments. Utilizing a mixed-methods approach, the research combines qualitative and quantitative data collection. Initially, a comprehensive literature review was conducted to establish a theoretical framework. This was followed by the administration of questionnaires to gather empirical data, which was then analyzed using statistical software. This sequential approach ensures a robust understanding of the context and challenges faced by project managers. The findings reveal that project managers in conflict zones encounter a range of escalating challenges. Initially, they must contend with immediate security threats and the presence of displaced populations, which significantly disrupt project initiation and execution. As projects progress, additional challenges arise, including limited access to essential resources and environmental disruptions such as natural disasters. These factors exacerbate the operational difficulties that project managers must navigate. In response to these challenges, the study highlights the necessity for project managers to implement formal project plans while simultaneously adopting adaptive strategies that evolve over time. Key adaptive strategies identified include flexible risk management frameworks, change management practices, and enhanced stakeholder engagement approaches. These strategies are crucial for maintaining project momentum and ensuring that objectives are met despite the unpredictable nature of conflict environments. The research emphasizes that structured scope management, clear documentation, and thorough requirements analysis are vital components for effectively navigating the complexities inherent in conflict-affected regions. However, the ongoing threats and logistical barriers necessitate a continuous adjustment to project management methodologies. This adaptability is not only essential for the immediate success of projects but also for fostering long-term resilience within the community. Concluding, the study offers actionable recommendations aimed at improving project management practices in conflict zones. These include the adoption of adaptive frameworks specifically tailored to the unique conditions of conflict environments and targeted training for project managers. Such training should focus on equipping managers with the skills to better address the dynamic challenges presented by conflict situations. The insights gained from this research contribute significantly to the broader field of project management, providing a practical guide for practitioners operating in high-risk areas. By emphasizing sustainable and resilient project outcomes, this study underscores the importance of adaptive management strategies in ensuring the success of projects in conflict-affected regions. The findings serve not only to enhance the understanding of project management practices in Kewot Woreda but also to inform future research and practice in similar contexts, ultimately aiming to promote stability and development in areas beset by conflict.

Keywords: project management practices, operational challenges, conflict zones, adaptive strategies

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Authors: Mohd Iz'aan Paiz Bin Zamri, Anis Salwa Mohd Khairuddin, Norrima Mokhtar, Rubiyah Yusof

Abstract:

Effective statistical feature extraction and classification are important in image-based automatic inspection and analysis. An automatic wood species recognition system is designed to perform wood inspection at custom checkpoints to avoid mislabeling of timber which will results to loss of income to the timber industry. The system focuses on analyzing the statistical pores properties of the wood images. This paper proposed a fuzzy-based feature extractor which mimics the experts’ knowledge on wood texture to extract the properties of pores distribution from the wood surface texture. The proposed feature extractor consists of two steps namely pores extraction and fuzzy pores management. The total number of statistical features extracted from each wood image is 38 features. Then, a backpropagation neural network is used to classify the wood species based on the statistical features. A comprehensive set of experiments on a database composed of 5200 macroscopic images from 52 tropical wood species was used to evaluate the performance of the proposed feature extractor. The advantage of the proposed feature extraction technique is that it mimics the experts’ interpretation on wood texture which allows human involvement when analyzing the wood texture. Experimental results show the efficiency of the proposed method.

Keywords: classification, feature extraction, fuzzy, inspection system, image analysis, macroscopic images

Procedia PDF Downloads 426

Authors: Pankhudi Khandelwal

Abstract:

The revenue models of digital giants such as Facebook and Google, use targeted advertising for revenues. Such a model requires huge amounts of consumer data. While the data protection law deals with the protection of personal data, however, this data is acquired by the companies on the basis of consent, performance of a contract, or legitimate interests. This paper analyses the role that competition law can play in evading these loopholes for the protection of data and privacy of online consumers. Digital markets have certain distinctive features such as network effects and feedback loop, which gives incumbents of these markets a first-mover advantage. This creates a situation where the winner takes it all, thus creating entry barriers and concentration in the market. It has been also seen that this dominant position is then used by the undertakings for leveraging in other markets. This can be harmful to the consumers in form of less privacy, less choice, and stifling innovation, as seen in the cases of Facebook Cambridge Analytica, Google Shopping, and Google Android. Therefore, the article aims to provide a legal framework wherein the data protection law and competition law can come together to provide a balance in regulating digital markets. The issue has become more relevant in light of the Facebook decision by German competition authority, where it was held that Facebook had abused its dominant position by not complying with data protection rules, which constituted an exploitative practice. The paper looks into the jurisdictional boundaries that the data protection and competition authorities can work from and suggests ex ante regulation through data protection law and ex post regulation through competition law. It further suggests a change in the consumer welfare standard where harm to privacy should be considered as an indicator of low quality.

Keywords: data protection, dominance, ex ante regulation, ex post regulation

Procedia PDF Downloads 183

Authors: Jamaiah H. Yahaya, Aziz Deraman, Abdul Razak Hamdan, Yusmadi Yah Jusoh

Abstract:

One of the most essential issues in software products is to maintain it relevancy to the dynamics of the user’s requirements and expectation. Many studies have been carried out in quality aspect of software products to overcome these problems. Previous software quality assessment models and metrics have been introduced with strengths and limitations. In order to enhance the assurance and buoyancy of the software products, certification models have been introduced and developed. From our previous experiences in certification exercises and case studies collaborating with several agencies in Malaysia, the requirements for user based software certification approach is identified and demanded. The emergence of social network applications, the new development approach such as agile method and other varieties of software in the market have led to the domination of users over the software. As software become more accessible to the public through internet applications, users are becoming more critical in the quality of the services provided by the software. There are several categories of users in web-based systems with different interests and perspectives. The classifications and metrics are identified through brain storming approach with includes researchers, users and experts in this area. The new paradigm in software quality assessment is the main focus in our research. This paper discusses the classifications of users in web-based software system assessment and their associated factors and metrics for quality measurement. The quality model is derived based on IEEE structure and FCM model. The developments are beneficial and valuable to overcome the constraints and improve the application of software certification model in future.

Keywords: software certification model, user centric approach, software quality factors, metrics and measurements, web-based system

Procedia PDF Downloads 405

Authors: Sanjivrao Katakam, Thanumoorthi I., Antony Gerald, Ratan Kulkarni, Shaju Nair

Abstract:

With increasing energy costs and its impact on the business, sustainability today has evolved from a social expectation to an economic imperative. Therefore, finding methods to reduce cost has become a critical directive for Industry leaders. Effective energy management is the only way to cut costs. However, Energy Management has been a challenge because it requires a change in old habits and legacy systems followed for decades. Today exorbitant levels of energy and operational data is being captured and stored by Industries, but they are unable to convert these structured and unstructured data sets into meaningful business intelligence. It must be noted that for quick decisions, organizations must learn to cope with large volumes of operational data in different formats. Energy analytics not only helps in extracting inferences from these data sets, but also is instrumental in transformation from old approaches of energy management to new. This in turn assists in effective decision making for implementation. It is the requirement of organizations to have an established corporate strategy for reducing operational costs through visibility and optimization of energy usage. Energy analytics play a key role in optimization of operations. The paper describes how today energy data analytics is extensively used in different scenarios like reducing operational costs, predicting energy demands, optimizing network efficiency, asset maintenance, improving customer insights and device data insights. The paper also highlights how analytics helps transform insights obtained from energy data into sustainable solutions. The paper utilizes data from an array of segments such as retail, transportation, and water sectors.

Keywords: energy analytics, energy management, operational data, business intelligence, optimization

Procedia PDF Downloads 364