Search results for: resistive random access memory (RRAM)

Authors: Khayra Zerrouki, Noureddine Djebli, Esra Eroglu, Afife Mat, Ozhan Gul

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Neurodegenerative diseases of the human brain comprise a variety of disorders that affect an increasing percentage of the population. Alzheimer’s disease (AD) is a complex, multifactorial, heterogeneous mental illness, which is characterized by an age-dependent loss of memory and an impairment of multiple cognitive functions, but this 10 last years it concerns the population most and most young. Hypericum perforatum has traditionally been used as an external anti-inflammatory and healing remedy for the treatment of swellings, wounds and burns, diseases of the alimentary tract and psychological disorders. It is currently of great interest due to new and important therapeutic applications. In this study, the chemical composition of methanolic extract of Hypericum perforatum (HPM) was analysed by using high performance liquid chromatography – diode array detector (HPLC-DAD). The in vitro antioxidant activity of HPM was evaluated by using several antioxidant tests. HSM exhibits inhibitory capacity against posphatidylcholine liposome peroxidation, induced with iron and ascorbic acid, scavenge DPPH and superoxide radicals and act as reductants. The cytotoxic activity of HSM was also determined by using MTT cell viability assay on HeLa and NRK-52E cell lines. The in vivo activity studies in Swiss mice were determined by using behavioral, memory tests and histological study. According to tests results HPM that may be relevant to the treatment of cognitive disorders. The results of chemical analysis showed a hight level of hyperforin and quercitin that had an important antioxidant activity proved in vitro with the DPPH, anti LPO and SOD; this antioxidant activity was confirmed in vivo after the non-toxic results by means of improvement in behavioral and memory than the reducing shrunken in pyramidal cells of mice brains.

Keywords: AlCl3, alzheimer, mice, neuroprotective, neurotoxicity, phytotherapy

Procedia PDF Downloads 497

Authors: Huang Bai-Cheng

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When deploying the Oriented Fast and Rotated Binary Robust Independent Elementary Feature (BRIEF) (ORB) extraction algorithm on field-programmable gate arrays (FPGA), the access of global storage for 31×31 pixel patches of the features has become the bottleneck of the system efficiency. Therefore, a feature zone strategy has been proposed. Zones are searched as features are detected. Pixels around the feature zones are extracted from global memory and distributed into patches corresponding to feature coordinates. The proposed FPGA structure is targeted on a Xilinx FPGA development board of Zynq UltraScale+ series, and multiple datasets are tested. Compared with the streaming pixel patch extraction method, the proposed architecture obtains at least two times acceleration consuming extra 3.82% Flip-Flops (FFs) and 7.78% Look-Up Tables (LUTs). Compared with the non-streaming one, the proposed architecture saves 22.3% LUT and 1.82% FF, causing a latency of only 0.2ms and a drop in frame rate for 1. Compared with the related works, the proposed strategy and hardware architecture have the superiority of keeping a balance between FPGA resources and performance.

Keywords: feature extraction, real-time, ORB, FPGA implementation

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Authors: Vanphanom Sychareun, Viengnakhone Vongxay, Kongmany Chaleunvong, Pascale Hancart Petitet

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Background: Lao PDR still has challenges in preventing and managing health against risk of emerging and re-emerging diseases, particularly HIV/AIDS, tuberculosis and malaria among pregnant women. Community-based intervention for mothers requires more evidences on awareness of such diseases and access to rapid diagnostic tests. The study aims to determine the awareness of pregnant women regarding HIV, TB and Malaria, the access to rapid diagnostic test of such diseases among pregnant women of local community and their factors related. Method: This is a cross sectional study using quantitative approach to explore the awareness of pregnant women on HIV/AIDS/TB and Malaria in Savannakhet province, Lao PDR in three remote districts (Phin, Thapangthong and Atsaphone) of Savannakhet province. The study targeted group was pregnant women at the community level. Sample size for primary data collection of pregnant women was 189. Face-to-face administered questionnaires were applied. Descriptive and inferential statistics were applied to determine the associated factors with awareness of pregnant women on HIV/AIDS/TB and Malaria. This study is under the HEALTH project/ Expertise France. Result: Most of our participants were pregnant at 28 – 42 weeks (50.3%); ranged 4 – 38 weeks. Mean age of pregnant women was 24.3 years old (range: 14 - 48 years old); 15.9% of whom were at age below 19 years. Around 94.2% of respondents works were farming, 54.5% were illiterate, 74.0% were Mon-Kmer ethnic, and 60% had income lower than average. Only 56.6% that have access to ANC, 39.1% started the access to ANC during the first trimester and only 19.6% had visited the ANC for at least four times. Almost pregnant women (and 92.1% and 93.1%) had low to moderate knowledge of HIV and TB respectively, while three-fourth of pregnant women (74.6%) had low to moderate knowledge of malaria. Slightly higher than half of participants (53.4% and 52.9%) had easy access to HIV and TB respectively ; while 72.5% had easy access to malaria. Majority of participants knew where to get tested for malaria (73.5%) and TB (54.5%), but 73.5% did not know where to get tested for HIV. Very few pregnant women (1.6%, 2.1% and 8.5%) experienced having tested for HIV/TB/malaria. respectively. Factors associated with awareness on HIV were occupation as staff, business (OR:5.9; 95% CI:1.2-28.1), upper secondary education (OR: 14.6; 95% CI:3.1-69.2); Mone-Khmer ethnic (OR: 0.4, 95% CI: 0.2-0.8); and attending ANC more than 4 times (OR:4.1, 95%:1.7-9.7). Factors associated with awareness on TB were occupation as staff, business (OR:2.4; 95% CI: 0.7-8.0), upper secondary education (OR: 6.2; 95% CI: 1.9-20.5); Mone-Khmer ethnic (OR: 0.5, 95% CI:0.3-0.9); attending ANC more than 4 times (OR:2.8, 95%:1.2-6.4). Factors associated with awareness on malaria were upper secondary education (OR: 18.1; 95% CI: 2.3-142.9); Mone-Khmer ethnic (OR: 0.2, 95% CI:0.1-0.4); attending ANC more than 4 times (OR:3.6, 95%:1.5-8.8). Conclusion: A very low awareness on HIV, TB and malaria among pregnant women in rural community of Savannakhet triggers the requirement of comprehensive public health intervention on awareness and access to prevention against emerging diseases for all pregnant women. Future intervention should focus on providing more knowledge to pregnant women during ANC and encouraging them to attend ANC more than 4 times.

Keywords: pregnant women, HIV, tuberculosis, malaria, awareness, Laos

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Authors: Srishti Bhatt, Vaibhav Bhavsar, Adil Hussain, Aashay Mhaske, S. C. Bali, T. S. Srikanth

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Shape Memory Alloys (SMA) are widely known for their unique shape recovery properties. SMA based actuation systems have high-force to weight ratio, light weight and also bio-compatible material. Which is why they are being used in different fields of aerospace, robotics, automotive and biomedical industries. However, in the automotive industry plenty of patents are available but commercially viable products are very few in market. This could be due to SMA material limitations like small stroke, direct dependability of lifecycle on stroke, pull load of the wire and high cycle time. In automotive sector, SMA being considered as an actuator which is required to have high stroke and constraint arises to accommodate a long length of wire (to compensate maximum 4 % strain as per better fatigue life cycle) not only increases complexity but also adds on the cost. More than 200 different types of actuators are used in an automobile, few of them whose efficiency can highly increase by replacing them with SMA based actuators which include latch lock mechanism, glove box, Head lamp leveling, side mirror and rear mirror leveling, tailgate opener and fuel lid cap actuator. To overcome the limitation of available space for required stroke of an actuator which leads to study the effect of different loading positions on SMA wires, different orientations of SMA wire by using pulleys and lever based systems to achieve maximum stroke. This investigation summarizes the loading under the V shape orientation the required stroke and carrying load capacity in more compact in comparison with straight orientation of wire. Similarly, the U shape orientation its showing higher load carrying capacity but reduced stroke which is aligned with concept of bundled wire method. Life-cycle of these orientations were also evaluated.

Keywords: actuators, automotive, nitinol, shape memory alloy, SMA wire orientations

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Authors: Dzunisani Sibuyi

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This article demonstrates how corruption is revealed in Mandla Langa’s Memory of Stones (2000) through the deployment of narrational strategies by applying narrative theories by Gerard Genette’s Narrative Discourse and Narrative Discourse Revisited, as well as Mikhail Bakhtin’s Dialogic Imagination to the text. This is accomplished by analysing Langa’s use of extradiegetic-heterodiegetic and intradiegetic-homodiegetic narrational strategies respectively employed by the anonymous narrator and character narrator Mpanza. The narration provided by these narrators is multi-voiced in its approach to the events depicting corruption from various completing and explanatory perspectives. In addition, Langa also employs narrative techniques of narrating times such as simultaneous, subsequent, and interpolated narration to highlight corruption taking place, which is highlighted by situating the story in its presentness moments coinciding with the corruption action. As a result, by emphasising the events portraying the plight of the main characters and their struggle to resist and defeat corrupt leaders, the narration strategically reveals corruption.

Keywords: narrational strategies, narrating voice, dialogism, corruption, Gérard Genette, Mandla Langa, Mikhail Bakhtin, time(s) of the narration

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Authors: Komal Babbar

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Multiuser Detection is the intelligent estimation/demodulation of transmitted bits in the presence of Multiple Access Interference. The authors have presented the Bit-error rate (BER) achieved by linear multi-user detectors: Matched filter (which treats the MAI as AWGN), Decorrelating and MMSE. In this work, authors investigate the bit error probability analysis for Matched filter, decorrelating, and MMSE. This problem arises in several practical CDMA applications where the receiver may not have full knowledge of the number of active users and their signature sequences. In particular, the behavior of MAI at the output of the Multi-user detectors (MUD) is examined under various asymptotic conditions including large signal to noise ratio; large near-far ratios; and a large number of users. In the last section Authors also shows Matlab Simulation results for Multiuser detection techniques i.e., Matched filter, Decorrelating, MMSE for 2 users and 10 users.

Keywords: code division multiple access, decorrelating, matched filter, minimum mean square detection (MMSE) detection, multiple access interference (MAI), multiuser detection (MUD)

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Authors: Hamdi Amroun, Yacine Benziani, Mehdi Ammi

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In this paper, we want to determine whether the accurate prediction of nicotine concentration can be obtained by using a network of smart objects and an e-cigarette. The approach consists of, first, the recognition of factors influencing smoking cessation such as physical activity recognition and participant’s behaviors (using both smartphone and smartwatch), then the prediction of the configuration of the e-cigarette (in terms of nicotine concentration, power, and resistance of e-cigarette). The study uses a network of commonly connected objects; a smartwatch, a smartphone, and an e-cigarette transported by the participants during an uncontrolled experiment. The data obtained from sensors carried in the three devices were trained by a Long short-term memory algorithm (LSTM). Results show that our LSTM-based model allows predicting the configuration of the e-cigarette in terms of nicotine concentration, power, and resistance with a root mean square error percentage of 12.9%, 9.15%, and 11.84%, respectively. This study can help to better control consumption of nicotine and offer an intelligent configuration of the e-cigarette to users.

Keywords: Iot, activity recognition, automatic classification, unconstrained environment

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Authors: Yu-Ping Chiu, Dung-Ying Lin

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Traditional staff scheduling methods, relying on employee experience, often lead to inefficiencies and resource waste. The challenges of transferring scheduling expertise and adapting to changing labor regulations further complicate this process. Manual approaches become increasingly impractical as companies accumulate complex scheduling rules over time. This study proposes an algorithmic optimization approach to address these issues, aiming to expedite scheduling while ensuring strict compliance with labor regulations and company policies. The method focuses on generating optimal schedules that minimize weighted company objectives within a compressed timeframe. Recognizing the limitations of conventional commercial software in modeling and solving complex real-world scheduling problems efficiently, this research employs Tabu Search with both long-term and short-term memory structures. The study will present numerical results and managerial insights to demonstrate the effectiveness of this approach in achieving intelligent and efficient staff scheduling.

Keywords: intelligent memory structures, mixed integer programming, meta-heuristics, staff scheduling problem, tabu search

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Authors: Peter Okpamen

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Food security concentrates on the collective efforts of all nations to produce enough food to feed their people. Recently, though the emphasis shifted from food availability to accessibility constraints, which entails the difficulties undernourished people face in gaining access to food even when it is available. Broadly speaking, access to food depends on an individual’s access to resources, markets and food transfers. The opportunities to obtain food through these channels are entitlements, which when denied constitute food insecurity. Evidence shows that a significant percentage of Nigerians are undernourished with adverse implications for the fight against poverty. The greatest danger or consequence of food insecurity is malnutrition. Food insecurity as both an agent and consequence of poverty also increases the economic, political and social tensions in the country. The undernourished in Nigeria are marginalised in several ways to the extent that they are often ill; and because of illness, their work capacity is reduced with attendant reduction in their income. Without adequate income, they cannot save nor invest enough resources to take care of their basic needs. In this paper therefore, we used the political economy approach and statistical analysis to demonstrate that poverty alleviation in Nigeria would be a mirage if food security problems are not adequately resolved.

Keywords: alleviation, demographic, food insecurity, undernourished

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Authors: Kailash C. Madan

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We study the steady state behaviour of a batch arrival single server queue in which the first service with general service times is compulsory and the second service with general service times is optional. We term such a two phase service as generalized Coxian-2 service. Just after completion of a service the server must take a vacation of random length of time with general vacation times. We obtain steady state probability generating functions for the queue size as well as the steady state mean queue size at a random epoch of time in explicit and closed forms. Some particular cases of interest including some known results have been derived.

Keywords: batch arrivals, compound Poisson process, generalized Coxian-2 service, steady state

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Authors: Mustapha Abdulkadir Gana, Jibrin Attahiru Alhassan, Adamu Musa Baba

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The exponential growth of information sources, resources and the continued Communication Technology (ICT) sophistication of libraries all over the world call for capable and ICT compliant librarians in Nigeria, this article assesses the digital literacy skills of librarians in tertiary institutions in Niger state. The survey research method was applied in the study using a random sampling technique to draw the sample. Fifty-eight copies of the questionnaire were administered while forty-nine copies were completed, returned, and used in the study, which represents 84% of the response rate. Two research questions were answered, and data were analyzed using Statistical Package for the Social Sciences (SPSS). The finding uncovered that the librarians lack the requisite digital literacy skills to access the wealth of digital information resources available. The study recommends some steps to turn around the situations amongst; librarians must be empowered with all necessary digital literacy skills, embark on rigorous training and retraining programs, workshops, conferences, and seminars, there should also be a coherent training policy for the librarians on a sustainable basis to increase their requisite digital literacy skills.

Keywords: digital, information, literacy, skills

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Authors: Yaping Zhao, Yimin Zhang

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In the present paper, the stationary random vibration of a uniform cantilever beam is investigated. Two types of damping mechanism, i.e. the external and internal viscous dampings, are taken into account simultaneously. The excitation form is the support motion, and it is ideal white. Because two type of damping mechanism are considered concurrently, the product of the modal damping ratio and the natural frequency is not a constant anymore. As a result, the infinite definite integral encountered in the process of computing the mean square response is more complex than that in the existing literature. One signal progress of this work is to have calculated these definite integrals accurately. The precise solution of the mean square response is thus obtained in the infinite series form finally. Numerical examples are supplied and the numerical outcomes acquired confirm the validity of the theoretical analyses.

Keywords: random vibration, cantilever beam, mean square response, white noise

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Authors: Yolina A. Petrova, Georgi I. Petkov

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The paper presents a symbolic model for category learning and categorization (called RoleMap). Unlike the other models which implement learning in a separate working mode, role-governed category learning and categorization emerge in RoleMap while it does its usual reasoning. The model is based on several basic mechanisms known as reflecting the sub-processes of analogy-making. It steps on the assumption that in their everyday life people constantly compare what they experience and what they know. Various commonalities between the incoming information (current experience) and the stored one (long-term memory) emerge from those comparisons. Some of those commonalities are considered to be highly important, and they are transformed into concepts for further use. This process denotes the category learning. When there is missing knowledge in the incoming information (i.e. the perceived object is still not recognized), the model makes anticipations about what is missing, based on the similar episodes from its long-term memory. Various such anticipations may emerge for different reasons. However, with time only one of them wins and is transformed into a category member. This process denotes the act of categorization.

Keywords: analogy-making, categorization, category learning, cognitive modeling, role-governed categories

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Authors: Yuheng Tao

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Rapid urbanization has brought the consequences of incompatible and excessive homogeneity of urban system, and urban color planning has become one of the most effective ways to restore the characteristics of cities. Among the many urban color design research, the establishment of urban theme colors has rarely been discussed. This study took the "New Taipei City Environmental Aesthetic Color” project as a research case and conducted mixed-method research that included expert interviews and quantitative survey data. This study introduces how theme colors were selected by the experts and investigates public’s perception and preference of the selected theme colors. Several findings include 1) urban memory plays a significant role in determining urban theme colors; 2) When establishing urban theme colors, areas/cities with relatively weak urban memory are given priority to be defined; 3) Urban theme colors that imply cultural attributes are more widely accepted by the public; 4) A representative city theme color helps conserve culture rather than guiding innovation. In addition, this research rearranges the urban color symbolism and specific content of urban theme colors and provides a more scientific urban theme color selection scheme for urban planners.

Keywords: urban theme color, urban color attribute, public perception, public preferences

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Authors: Jose A. Pomilio, Olavo Bet, Mateus P. Vieira

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The power converter that feeds high-frequency, high-voltage transformers must be carefully designed due to parasitic components, mainly the secondary winding capacitance and the leakage inductance, that introduces resonances in relatively low-frequency range, next to the switching frequency. This paper considers applications in which the load (resistive) has an unpredictable behavior, changing from open to short-circuit condition faster than the output voltage control loop could react. In this context, to avoid over voltage and over current situations, that could damage the converter, the transformer or the load, it is necessary to find an operation point that assure the desired output voltage in spite of the load condition. This can done adjusting the frequency response of the transformer adding an external inductance, together with selecting the switching frequency to get stable output voltage independently of the load.

Keywords: high-voltage transformer, resonant converter, soft-commutation, external inductance

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Authors: Sajjad Asefi, Hossein Afrakhte

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This paper presents the evaluation of reliability indices of an electrical distribution system using Monte Carlo simulation technique accounting Time To Switch (TTS) for each section. In this paper, the distribution system has been assumed by accounting random repair time omission. For simplicity, we have assumed the reliability analysis to be based on exponential law. Each segment has a specified rate of failure (λ) and repair time (r) which will give us the mean up time and mean down time of each section in distribution system. After calculating the modified mean up time (MUT) in years, mean down time (MDT) in hours and unavailability (U) in h/year, TTS have been added to the time which the system is not available, i.e. MDT. In this paper, we have assumed the TTS to be a random variable with Log-Normal distribution.

Keywords: distribution system, Monte Carlo simulation, reliability, repair time, time to switch (TTS)

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Authors: Somaya A. Abd El Mottaleb, Ahmed Abd El Aziz, Heba A. Fayed, Moustafa H. Aly

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In this paper, we present the performance of spectral amplitude coding optical code division multiple access using different detectors at different transmission distances using single photodiode detection technique. Modified double weight codes are used as signature codes. Simulation results show that the system using avalanche photo detector can move distance longer than that using positive intrinsic negative photo detector.

Keywords: avalanche photodiode, modified double weight, multiple access technique, single photodiode.

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Authors: Golam Saklayen, Sheikh Rashel al Ahmed, Ferdous Rahman, Ismail Abu Bakar

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Investigation on Lanthanum Fluoride LaF3 layer embedding Silicon Nanocrystals (Si-NCs) fabricated using a novel one-step chemical method has been reported in this presentation. Application of this material has been tested for low-voltage operating non-volatile memory and Schottkey-junction solar cell. Colloidal solution of Si-NCs in hydrofluoric acid (HF) was prepared from meso-porous silicon by ultrasonic vibration (sonication). This solution prevents the Si-NCs to be oxidized. On a silicon (Si) substrate, LaCl3 solution in HCl is allowed to react with the colloidal solution of prepared Si-NCs. Since this solution contains HF, LaCl3 reacts with HF and produces LaF3 crystals that deposits on the silicon substrate as a layer embedding Si-NCs. This a novel single step chemical way of depositing LaF3 insulating layer embedding Si-NCs. The X-Ray diffraction of the deposited layer shows a polycrystalline LaF3 deposition on silicon. A non-stoichiometric LaF3 layer embedding Si-NCs was found by EDX analysis. The presence of Si-NCs was confirmed by SEM. FTIR spectroscopy of the deposited LaF3 powder also confirmed the presence of Si-NCs. The size of Si-NCs was found to be inversely proportional to the ultrasonic power. After depositing proper contacts on the back of Si and LaF3, the devices have been tested as a non-volatile memory and solar cell. A memory window of 525 mV was obtained at a programming and erasing bias of 2V. The LaF3 films with Si NCs showed strong absorption and was also found to decrease optical transmittance than pure LaF3 film of same thickness. The I-V characteristics of the films showed a dependency on the incident light intensity where current changed under various light illumination. Experimental results show a lot of promise for Si-NCs-embedded LaF3 layer to be used as an insulating layer in MIS devices as well as an photoactive material in Schottkey junction solar cells.

Keywords: silicon nanocrystals (Si NCs), LaF3, colloidal solution, Schottky junction solar cell

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Authors: Ella Sèdé Maforikan

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Accurate land cover mapping is essential for effective environmental monitoring and natural resources management. This study focuses on assessing the classification performance of two satellite datasets and evaluating the impact of different input feature combinations on classification accuracy in the Beterou catchment, situated in the northern part of Benin. Landsat-8 and Sentinel-2 images from June 1, 2020, to March 31, 2021, were utilized. Employing the Random Forest (RF) algorithm on Google Earth Engine (GEE), a supervised classification categorized the land into five classes: forest, savannas, cropland, settlement, and water bodies. GEE was chosen due to its high-performance computing capabilities, mitigating computational burdens associated with traditional land cover classification methods. By eliminating the need for individual satellite image downloads and providing access to an extensive archive of remote sensing data, GEE facilitated efficient model training on remote sensing data. The study achieved commendable overall accuracy (OA), ranging from 84% to 85%, even without incorporating spectral indices and terrain metrics into the model. Notably, the inclusion of additional input sources, specifically terrain features like slope and elevation, enhanced classification accuracy. The highest accuracy was achieved with Sentinel-2 (OA = 91%, Kappa = 0.88), slightly surpassing Landsat-8 (OA = 90%, Kappa = 0.87). This underscores the significance of combining diverse input sources for optimal accuracy in land cover mapping. The methodology presented herein not only enables the creation of precise, expeditious land cover maps but also demonstrates the prowess of cloud computing through GEE for large-scale land cover mapping with remarkable accuracy. The study emphasizes the synergy of different input sources to achieve superior accuracy. As a future recommendation, the application of Light Detection and Ranging (LiDAR) technology is proposed to enhance vegetation type differentiation in the Beterou catchment. Additionally, a cross-comparison between Sentinel-2 and Landsat-8 for assessing long-term land cover changes is suggested.

Keywords: land cover mapping, Google Earth Engine, random forest, Beterou catchment

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Authors: M. Uysal, M. Yilmaz, I. Tiryakioğlu

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Digital Terrain Model (DTM) is a digital numerical representation of the Earth's surface. DTMs have been applied to a diverse field of tasks, such as urban planning, military, glacier mapping, disaster management. In the expression of the Earth' surface as a mathematical model, an infinite number of point measurements are needed. Because of the impossibility of this case, the points at regular intervals are measured to characterize the Earth's surface and DTM of the Earth is generated. Hitherto, the classical measurement techniques and photogrammetry method have widespread use in the construction of DTM. At present, RADAR, LiDAR, and stereo satellite images are also used for the construction of DTM. In recent years, especially because of its superiorities, Airborne Light Detection and Ranging (LiDAR) has an increased use in DTM applications. A 3D point cloud is created with LiDAR technology by obtaining numerous point data. However recently, by the development in image mapping methods, the use of unmanned aerial vehicles (UAV) for photogrammetric data acquisition has increased DTM generation from image-based point cloud. The accuracy of the DTM depends on various factors such as data collection method, the distribution of elevation points, the point density, properties of the surface and interpolation methods. In this study, the random data reduction method is compared for DTMs generated from image based point cloud data. The original image based point cloud data set (100%) is reduced to a series of subsets by using random algorithm, representing the 75, 50, 25 and 5% of the original image based point cloud data set. Over the ANS campus of Afyon Kocatepe University as the test area, DTM constructed from the original image based point cloud data set is compared with DTMs interpolated from reduced data sets by Kriging interpolation method. The results show that the random data reduction method can be used to reduce the image based point cloud datasets to 50% density level while still maintaining the quality of DTM.

Keywords: DTM, Unmanned Aerial Vehicle (UAV), uniform, random, kriging

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Authors: Maja Jokić, Andrea Mervar, Stjepan Mateljan

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Peer review journals, as the main communication channel among researchers, fully achieve their objective if they are available to the global research community, which is accomplished through open access. In the EU countries, the idea of open access has spread over the years through various projects, initiatives, and strategic documents. Consequently, in this paper we want to analyze, using various bibliometric indicators, visibility, and significance of open access peer review journals compared to the conventional (non-open access) ones. We examine the sample of open access (OA) journals in 28 EU countries in addition to open access journals in three EU candidate countries (Bosnia and Herzegovina, FYR Macedonia and Serbia), all indexed by Scopus (N=1,522). These journals comprise 42% of the total number of OA journals indexed by Scopus. The distribution of OA journals in our sample according to the subject fields indicates that the largest share has OA journals in Health Sciences, 29% followed by Social Sciences and Physical Sciences with 25%, and 21% in Life Sciences. At the same time, the distribution according to countries (N=31) shows the dominance of EU15 countries with the share of 68.3% (N=1041) while post-socialist European countries (EU11 plus three candidate EU countries) have the share of 31.6% (N=481). Bibliometric indicators are derived from the SCImago Journal Ranking database. The analysis of OA journals according to their quartile scores (that reflect the relation between number of articles and their citations) shows that the largest number of OA journals from our sample was in the third quartile in 2015. For comparison, the majority of all academic journals indexed in Scopus from the countries in our sample were in the same year in the first quartile. The median of SJR indicator (SCImago Journal Rankings) for 2015 that measures the journal's prestige, amounted 0.297 for OA journals from the sample, while it was modestly lower for all OA journals, 0.284. The value of the same indicator for all journals indexed by Scopus (N=11,086) from our group of countries was 0.358, which is significantly different from the one for OA journals. Apart from the number of OA journals we also confirm significant differences between EU15 and post-socialist countries in bibliometric status of OA journals. The median SJR indicator for 2015 for EU15 countries was 0.394, while for post-socialist countries it amounted to 0.226. The changes in bibliometric indicators: quartile score, SJR (SCImago Journal Rankings), SNIP (Sources Normalised Impact by Paper) and IPP (Impact per Publication) of OA journals during 2012-2015 period, as well as H-index for the main four subject fields (Life Sciences, Physical Sciences, Social Sciences and Health Sciences) in the whole sample as well as in two main groups of European countries, show increasing trend of acceptance and visibility of OA journals within the academic community. More comprehensive insights into the visibility of OA journals could be reached by using additional qualitative research methods such as for example, interviews with researchers.

Keywords: bibliometric analysis, European countries, journal evaluation, open access journals

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Authors: Durvi Yogesh Vagani

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This research paper explores the effectiveness of Research-informed teaching and Case-based teaching in enhancing the retention and recall of memory during discussions among university students. Additionally, it investigates the impact of using Artificial Intelligence (AI) tools on the quality of research conducted by students and its correlation with better recollection. The study hypothesizes that Case-based teaching will lead to greater recall and storage of information. The research gap in the use of AI in educational settings, particularly with actual participants, is addressed by leveraging a multi-method approach. The hypothesis is that the use of AI, such as ChatGPT and Bard, would lead to better retention and recall of information. Before commencing the study, participants' attention levels and IQ were assessed using the Digit Span Test and the Wechsler Adult Intelligence Scale, respectively, to ensure comparability among participants. Subsequently, participants were divided into four conditions, each group receiving identical information presented in different formats based on their assigned condition. Following this, participants engaged in a group discussion on the given topic. Their responses were then evaluated against a checklist. Finally, participants completed a brief test to measure their recall ability after the discussion. Preliminary findings suggest that students who utilize AI tools for learning demonstrate improved grasping of information and are more likely to integrate relevant information into discussions compared to providing extraneous details. Furthermore, Case-based teaching fosters greater attention and recall during discussions, while Research-informed teaching leads to greater knowledge for application. By addressing the research gap in AI application in education, this study contributes to a deeper understanding of effective teaching methodologies and the role of technology in student learning outcomes. The implication of the present research is to tailor teaching methods based on the subject matter. Case-based teaching facilitates application-based teaching, and research-based teaching can be beneficial for theory-heavy topics. Integrating AI in education. Combining AI with research-based teaching may optimize instructional strategies and deepen learning experiences. This research suggests tailoring teaching methods in psychology based on subject matter. Case-based teaching suits practical subjects, facilitating application, while research-based teaching aids understanding of theory-heavy topics. Integrating AI in education could enhance learning outcomes, offering detailed information tailored to students' needs.

Keywords: artificial intelligence, attention, case-based teaching, memory recall, memory retention, research-informed teaching

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Authors: Manuela Nayantara Jeyaraj

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'Digital Divide' is a concept that has existed in this paradigm ever since the discovery of the first-generation technologies. Before the turn of the century, it was basically used to describe the gap between those with telephone communication access and those without it. At present, it is plainly descriptive in itself to illustrate the cavity among those with Internet access and those without. Though the concept of digital divide has been merely lying in sight for as long as time itself, the friction it caused has not yet been fully realized to solve major crisis situations. Unlike well-developed countries, Sri Lanka is still in the verge of moving farther away from a developing country in the race towards reaching a developed state. Access to technological resources varies from region to region, even within the island itself, with one region having a considerable percentage of its community exposed to the Internet and its related technologies, and the other unaware of such. Thus, this paper intends to analyze the roots for the still-extant gap instigated based on the concept of ‘Digital Divide’ and explores the plausible potentials that could be brought about by narrowing this prevailing percentage among the population, specifically entrenching the advantages reaped towards an economic augmentation and culture or lifestyle revolution on the path towards development.

Keywords: communication, digital divide, society, Sri Lanka

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Authors: Mariem Saied, Jens Gustedt, Gilles Muller

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We present Dido, a source-to-source auto-generation and optimization framework for multi-dimensional stencil computations. It enables a large programmer community to easily and safely implement stencil codes on distributed-memory parallel architectures with Ordered Read-Write Locks (ORWL) as an execution and communication back-end. ORWL provides inter-task synchronization for data-oriented parallel and distributed computations. It has been proven to guarantee equity, liveness, and efficiency for a wide range of applications, particularly for iterative computations. Dido consists mainly of an implicitly parallel domain-specific language (DSL) implemented as a source-level transformer. It captures domain semantics at a high level of abstraction and generates parallel stencil code that leverages all ORWL features. The generated code is well-structured and lends itself to different possible optimizations. In this paper, we enhance Dido to handle both Jacobi and Gauss-Seidel grid traversals. We integrate temporal blocking to the Dido code generator in order to reduce the communication overhead and minimize data transfers. To increase data locality and improve intra-node data reuse, we coupled the code generation technique with the polyhedral parallelizer Pluto. The accuracy and portability of the generated code are guaranteed thanks to a parametrized solution. The combination of ORWL features, the code generation pattern and the suggested optimizations, make of Dido a powerful code generation framework for stencil computations in general, and for distributed-memory architectures in particular. We present a wide range of experiments over a number of stencil benchmarks.

Keywords: stencil computations, ordered read-write locks, domain-specific language, polyhedral model, experiments

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Authors: Thomas Chinwe Urama, Patrick Oseloka Ezepue, Peters Chimezie Nnanwa

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This paper investigates the universal financial dynamics in two dominant stock markets in Sub-Saharan Africa, through an in-depth analysis of the cross-correlation matrix of price returns in Nigerian Stock Market (NSM) and Johannesburg Stock Exchange (JSE), for the period 2009 to 2013. The strength of correlations between stocks is known to be higher in JSE than that of the NSM. Particularly important for modelling Nigerian derivatives in the future, the interactions of other stocks with the oil sector are weak, whereas the banking sector has strong positive interactions with the other sectors in the stock exchange. For the JSE, it is the oil sector and beverages that have greater sectorial correlations, instead of the banks which have the weaker correlation with other sectors in the stock exchange.

Keywords: random matrix theory, cross-correlations, emerging markets, option pricing, eigenvalues eigenvectors, inverse participation ratios and implied volatility

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Authors: Jalil Boudjadar

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Dynamic Voltage and Frequency Scaling (DVFS) multicore platforms are promising execution platforms that enable high computational performance, less energy consumption and flexibility in scheduling the system processes. However, the resulting interleaving and memory interference together with per-core frequency tuning make real-time guarantees hard to be delivered. Besides, energy consumption represents a strong constraint for the deployment of such systems on energy-limited settings. Identifying the system configurations that would achieve a high performance and consume less energy while guaranteeing the system schedulability is a complex task in the design of modern embedded systems. This work studies the trade-off between energy consumption, cores utilization and memory bottleneck and their impact on the schedulability of DVFS multicore time-critical systems with a hierarchy of shared memories. We build a model-based framework using Parametrized Timed Automata of UPPAAL to analyze the mutual impact of performance, energy consumption and schedulability of DVFS multicore systems, and demonstrate the trade-off on an actual case study.

Keywords: time-critical systems, multicore systems, schedulability analysis, energy consumption, performance analysis

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Authors: Anastasiya Paltarzhitskaya

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Subjective time plays an important role in consciousness processes and self-awareness at the moment. The concept of intrinsic neural timescales (INT) explains the difference in perceiving various time intervals. The capacity to experience the present builds on the fundamental properties of temporal cognition. The challenge that both philosophy and neuroscience try to answer is how the brain differentiates the present from the past and future. In our work, we analyze papers which describe mechanisms involved in the perception of ‘present’ and ‘non-present’, i.e., future and past moments. Taking into account that we perceive time intervals even during rest or relaxation, we suppose that the default-mode network activity can code time features, including the present moment. We can compare some results of time perceptual studies, where brain activity was shown in states with different flows of time, including resting states and during “mental time travel”. According to the concept of mental traveling, we employ a range of scenarios which demand episodic memory. However, some papers show that the hippocampal region does not activate during time traveling. It is a controversial result that is further complicated by the phenomenological aspect that includes a holistic set of information about the individual’s past and future.

Keywords: temporal consciousness, time perception, memory, present

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Authors: Magdalena Bury-Kaminska, Aneta Szudy-Szczyrek, Aleksandra Nowaczynska, Olga Jankowska-Lecka, Marek Hus, Klaudia Kot

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Introduction: The aim of the research was to determine the changes in cognitive functioning in patients with plasma cell myeloma by comparing patients’ state before the treatment and during chemotherapy as well as to determine the biological factors that can be used to predict patients’ cognitive state. Methods: The patients underwent the research procedure twice: before chemotherapy and after 4-6 treatment cycles. A psychological test and measurement of the following biological variables were carried out: TNF-α (tumor necrosis factor), IL-6 (interleukin 6), IL-10 (interleukin 10), BDNF (brain-derived neurotrophic factor). The following research methods were implemented: the Montreal Cognitive Assessment (MoCA), Battery of Tests for Assessing Cognitive Functions PU1, experimental and clinical trials based on the Choynowski’s Memory Scale, Stroop Color-Word Interference Test (SCWT), depression measurement questionnaire. Results: The analysis of the research showed better cognitive functions of patients during chemotherapy in comparison to the phase before it. Moreover, neurotrophin BDNF allows to predict the level of selected cognitive functions (semantic fluency and execution control) already at the diagnosis stage. After 4-6 cycles, it is also possible to draw conclusions concerning the extent of working memory based on the level of BDNF. Cytokine TNF-α allows us to predict the level of letter fluency during anti-cancer treatment. Conclusions: It is possible to presume that BDNF has a protective influence on patients’ cognitive functions and working memory and that cytokine TNF-α co-occurs with a diminished execution control and better material grouping in terms of phonological fluency. Acknowledgment: This work was funded by the National Science Center in Poland [grant no. 2017/27/N/HS6/02057.

Keywords: chemobrain, cognitive impairment, non−central nervous system cancers, hematologic diseases

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Authors: Ramesh Bhat, Ammu Somanath, A. K. Nayanatara

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Background: The increasing prevalence of overweight and obesity is a critical public health problem for women. The negative effect of stress on memory and cognitive functions has been widely explored for decades in numerous research projects using a wide range of methodology. Deterioration of memory and other brain functions are hallmarks of Alzheimer’s disease. Estrogen fluctuations and withdrawal have myriad direct effects on the central nervous system that have the potential to influence cognitive functions. Aim: The present study aims to compare the effect of stress on the cognitive functions in overweight/obese women before and after menopause. Material and Methods: A total of 142 female subjects constituting women before menopause between the age group of 18–44 years and women after menopause between the age group of 45–60 years were included in the sample. Participants were categorized into overweight/obese groups based on the body mass index. The Perceived Stress Scale (PSS) the major tool was used for measuring the perception of stress. Based on the stress scale measurement each group was classified into with stress and without stress. Addenbrooke’s cognitive Examination-III was used for measuring the cognitive functions. Results: Premenopausal women with stress showed a significant (P<0.05) decrease in the cognitive parameters such as attention and orientation Fluency, language and visuospatial ability. Memory did not show any significant change in this group. Whereas, in the postmenopausal stressed women all the cognitive functions except fluency showed a significant (P<0.05) decrease after menopause stressed group. Conclusion: Stress is a significant factor on the cognitive functions of obese and overweight women before and after menopause. Practice of Yoga, Encouragement in activities like gardening, embroidery, games and relaxation techniques should be recommended to prevent stress. Insights into the neurobiology before and after menopause can be gained from future studies examining the effect on the HPA axis in relation to cognition and stress.

Keywords: cognition, stress, premenopausal, body mass index

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Authors: Morfaw Bernice Njinju

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The contribution of exporting and small businesses to an economy cannot be overemphasized. However, small firms in developing economies are characterized by resource deficiencies, which hinders their exporting abilities. As a result, export promotion programs are designed by the government as external resources that small firms can access to overcome export barriers and improve their exporting. Nevertheless, doubts still exist as to whether firms are aware of these programs and the extent to which they are utilizing it. To analyse the level of awareness and usage of these programs, the questionnaire was developed from the review of the literature. A pilot study was conducted to determine the ease of completing the questionnaire by respondent before incorporating feedback to produce the final questionnaire. Data were collected from 200 small businesses in Cameroon in the manufacturing and agricultural sector through random sampling and analysed using regression analysis. The results indicated that different programs had different levels of awareness than others. Programs to provide training to improve product quality was found to have the highest level of awareness while those providing findings had low levels of awareness. Despite these different levels of awareness, usage was very low, as firms do not want to open up to government scrutiny of their business. Implications to policy, practice, and direction for further research are also discussed.

Keywords: export promotion programs, exporting, small businesses, Cameroon

Procedia PDF Downloads 108