Search results for: access network

Authors: Tuji Jemal Ahmed

Abstract:

Food security and utilization are critical aspects of ensuring the well-being and prosperity of a nation. This paper examines the current state of food security and utilization in Ethiopia, focusing on the challenges, opportunities, and strategies employed to address the issue. Ethiopia, a country in East Africa, has made significant progress in recent years to improve food security and utilization for its population. However, persistent challenges such as recurrent droughts, limited access to resources, and low agricultural productivity continue to pose obstacles to achieving sustainable food security. The paper begins by providing an overview of the concept of food security, emphasizing its multidimensional nature and the importance of access, availability, utilization, and stability. It then explores the specific factors influencing food security and utilization in Ethiopia, including natural resources, climate variability, agricultural practices, infrastructure, and socio-economic factors. Furthermore, the paper highlights the initiatives and interventions implemented by the Ethiopian government, non-governmental organizations, and international partners to enhance food security and utilization. These efforts include agricultural extension programs, irrigation projects, investments in rural infrastructure, and social safety nets to protect vulnerable populations. The study also examines the role of technology and innovation in improving food security and utilization in Ethiopia. It explores the potential of sustainable agricultural practices, such as conservation agriculture, improved seed varieties, and precision farming techniques. Additionally, it discusses the role of digital technologies in enhancing access to market information, financial services, and agricultural inputs for smallholder farmers. Finally, the paper discusses the importance of collaboration and partnerships between stakeholders, including government agencies, development organizations, research institutions, and communities, in addressing food security and utilization challenges. It emphasizes the need for integrated and holistic approaches that consider both production and consumption aspects of the food system.

Keywords: food security, utilization, Ethiopia, challenges

Procedia PDF Downloads 81

Authors: Weikang Gong, Chunhua Li

Abstract:

Dynamics plays an essential role in function exertion of proteins. Elastic network model (ENM), a harmonic potential-based and cost-effective computational method, is a valuable and efficient tool for characterizing the intrinsic dynamical properties encoded in biomacromolecule structures and has been widely used to detect the large-amplitude collective motions of proteins. Gaussian network model (GNM) and anisotropic network model (ANM) are the two often-used ENM models. In recent years, many ENM variants have been proposed. Here, we propose a small but effective modification (denoted as modified mENM) to the multiscale ENM (mENM) where fitting weights of Kirchhoff/Hessian matrixes with the least square method (LSM) is modified since it neglects the details of pairwise interactions. Then we perform its comparisons with the original mENM, traditional ENM, and parameter-free ENM (pfENM) on reproducing dynamical properties for the six representative proteins whose molecular dynamics (MD) trajectories are available in http://mmb.pcb.ub.es/MoDEL/. In the results, for B-factor prediction, mENM achieves the best performance among the four ENM models. Additionally, it is noted that with the weights of the multiscale Kirchhoff/Hessian matrixes modified, interestingly, the modified mGNM/mANM still has a much better performance than the corresponding traditional ENM and pfENM models. As to dynamical cross-correlation map (DCCM) calculation, taking the data obtained from MD trajectories as the standard, mENM performs the worst while the results produced by the modified mENM and pfENM models are close to those from MD trajectories with the latter a little better than the former. Generally, ANMs perform better than the corresponding GNMs except for the mENM. Thus, pfANM and the modified mANM, especially the former, have an excellent performance in dynamical cross-correlation calculation. Compared with GNMs (except for mGNM), the corresponding ANMs can capture quite a number of positive correlations for the residue pairs nearly largest distances apart, which is maybe due to the anisotropy consideration in ANMs. Furtherly, encouragingly the modified mANM displays the best performance in capturing the functional motional modes, followed by pfANM and traditional ANM models, while mANM fails in all the cases. This suggests that the consideration of long-range interactions is critical for ANM models to produce protein functional motions. Based on the analyses, the modified mENM is a promising method in capturing multiple dynamical characteristics encoded in protein structures. This work is helpful for strengthening the understanding of the elastic network model and provides a valuable guide for researchers to utilize the model to explore protein dynamics.

Keywords: elastic network model, ENM, multiscale ENM, molecular dynamics, parameter-free ENM, protein structure

Procedia PDF Downloads 115

Authors: Giselle Maggie-Fer Castañeda Lozano

Abstract:

The main objective of this research was to explore the role of neural network architectures in simulating behavioral phenomena as a potential explanation for selective associations, specifically related to biological constraints on learning. Biological constraints on learning refer to the limitations observed in conditioning procedures, where learning is expected to occur. The study involved simulations of five different experiments exploring various phenomena and sources of biological constraints in learning. These simulations included the interaction between response and reinforcer, stimulus and reinforcer, specificity of stimulus-reinforcer associations, species differences, neuroanatomical constraints, and learning in uncontrolled conditions. The overall results demonstrated that by manipulating neural network architectures, conditions can be created to model and explain diverse biological constraints frequently reported in comparative psychology literature as learning typicities. Additionally, the simulations offer predictive content worthy of experimental testing in the pursuit of new discoveries regarding the specificity of learning. The implications and limitations of these findings are discussed. Finally, it is suggested that this research could inaugurate a line of inquiry involving the use of neural networks to study biological factors in behavior, fostering the development of more ethical and precise research practices.

Keywords: comparative psychology, connectionism, conditioning, experimental analysis of behavior, neural networks

Procedia PDF Downloads 67

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

Abstract:

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 195

Authors: Mohana Basu, Snehamanju Basu

Abstract:

Urbanization has an immense impact on the holistic development of a region. In that same context, the level of women empowerment plays a significant role in the development of any region, particularly a region belonging to a developing country. The present study investigates the status of women empowerment in the Asansol Durgapur Planning Area of the state of West Bengal, India by investigating the status of women and their access to various facilities and awareness about the various governmental and non-governmental schemes meant for their elevation. Through this study, an attempt has been to made to understand the perception of the respondents on the context of women's empowerment. The study integrates multiple sources of qualitative and quantitative data collected from various reports, field-based measurements, questionnaire survey and community based participatory appraisals. Results reveal that women of the rural parts of the region are relatively disempowered due to the various restrictions imposed on them and enjoy lower socioeconomic clout than their male counterparts in spite of the several remedial efforts taken by the government and NGOs to elevate their position in the society. A considerable gender gap still exists regarding access to education, employment and decision-making power in the family and significant differences in attitude towards women are observable in the rural and urban areas. Freedom of women primarily vary according to their age group, educational level, employment and income status and also on the degree of urbanization. Asansol Durgapur Planning Area is primarily an industrial region where huge employment generation scope exists. But these disparities are quite alarming and indicate that economic development does not always usher in socially justifiable rights and access to resources for both men and women alike in its awake. In this backdrop, this study will attempt to forward relevant suggestions which can be followed for betterment of the status of women.

Keywords: development, disempowered, economic development, urbanization, women empowerment

Procedia PDF Downloads 135

Authors: Viacheslav Shkuratskyy, Aminu Bello Usman, Michael O’Dea, Saifur Rahman Sabuj

Abstract:

This paper examines relationships between solar activity and earthquakes; it applied machine learning techniques: K-nearest neighbour, support vector regression, random forest regression, and long short-term memory network. Data from the SILSO World Data Center, the NOAA National Center, the GOES satellite, NASA OMNIWeb, and the United States Geological Survey were used for the experiment. The 23rd and 24th solar cycles, daily sunspot number, solar wind velocity, proton density, and proton temperature were all included in the dataset. The study also examined sunspots, solar wind, and solar flares, which all reflect solar activity and earthquake frequency distribution by magnitude and depth. The findings showed that the long short-term memory network model predicts earthquakes more correctly than the other models applied in the study, and solar activity is more likely to affect earthquakes of lower magnitude and shallow depth than earthquakes of magnitude 5.5 or larger with intermediate depth and deep depth.

Keywords: k-nearest neighbour, support vector regression, random forest regression, long short-term memory network, earthquakes, solar activity, sunspot number, solar wind, solar flares

Procedia PDF Downloads 70

Authors: Pengchao Wei, Xiangzhong Fang

Abstract:

Noise is ubiquitous in this world. Denoising is an essential technology, especially in image semantic segmentation, where noises are generally categorized into two main types i.e. feature noise and label noise. The main focus of this paper is aiming at modeling label noise, investigating the behaviors of different types of label noise on image semantic segmentation tasks using K-Nearest-Neighbor and Convolutional Neural Network classifier. The performance without label noise and with is evaluated and illustrated in this paper. In addition to that, the influence of feature noise on the image semantic segmentation task is researched as well and a feature noise reduction method is applied to mitigate its influence in the learning procedure.

Keywords: convolutional neural network, denoising, feature noise, image semantic segmentation, k-nearest-neighbor, label noise

Procedia PDF Downloads 215

Authors: Khushalini N. Ulman, Samane Maroufi, Veena H. Sahajwalla

Abstract:

Globally, electronic waste (e-waste) continues to grow at an alarming rate. Several technologies have been developed to recover valuable materials from e-waste, however, their efficiency can be increased with a better knowledge of the e-waste components. Random access memory cards (RAMs) are considered as high value scrap for the e-waste recyclers. Despite their high precious metal content, RAMs are still recycled in a conventional manner resulting in huge loss of resources. Our research work highlights the precious metal rich components of a RAM. Inductively coupled plasma (ICP) analysis of RAMs of six different generations have been carried out and the trends in their metal content have been investigated. Over the past decade, the copper content of RAMs has halved and their tin content has increased by 70 %. The stricter environmental laws have facilitated ~96 % drop in the lead content of RAMs. To comprehend the fundamentals of thermal transformation of RAMs, our research provides their detailed kinetic study. This can assist the e-waste recyclers in optimising their metal recovery processes. Thus, understanding the chemical and thermal behaviour of RAMs can open new avenues for efficient e-waste recycling.

Keywords: electronic waste, kinetic study, recycling, thermal transformation

Procedia PDF Downloads 142

Authors: Zina Saheb, Ezz El-Masry, Jean-François Bousquet

Abstract:

This paper presents an enhanced efficiency simultaneous dual band energy harvesting system for wireless body area network. A bulk biasing is used to enhance the efficiency of the adapted rectifier design to reduce V_th of MOSFET. The presented circuit harvests the radio frequency (RF) energy from two frequency bands: 1 GHz and 2.4 GHz. It is designed with TSMC 65-nm CMOS technology and high quality factor dual matching network to boost the input voltage. Full circuit analysis and modeling is demonstrated. The simulation results demonstrate a harvester with an efficiency of 23% at 1 GHz and 46% at 2.4 GHz at an input power as low as -30 dBm.

Keywords: energy harvester, simultaneous, dual band, CMOS, differential rectifier, voltage boosting, TSMC 65nm

Procedia PDF Downloads 398

Authors: Eileen Y. Wong, Katherine Jin, Anat Talmon

Abstract:

Background: Help seeking behaviors are highly contingent on socio-cultural factors such as ethnicity. Both Latino and Asian Americans underutilize mental health services compared to their White American counterparts. This difference may be related to the composite of one’s social support system, which includes family cohesion and social networks. Previous studies have found that Latino families are characterized by higher levels of family cohesion and social support, and Asian American families with greater family cohesion exhibit lower levels of help seeking behaviors. While both are broadly considered collectivist communities, within-culture variability is also significant. Therefore, this study aims to investigate the relationship between help seeking behaviors in the two cultures with levels of family cohesion and strength of social network. We also consider such relationships in light of previous traumatic events and diagnoses, particularly post-traumatic stress disorder (PTSD), to understand whether clinically diagnosed individuals differ in their strength of network and help seeking behaviors. Method: An adult sample (N = 2,990) from the National Latino and Asian American Study (NLAAS) provided data on participants’ social network, family cohesion, likelihood of seeking professional help, and DSM-IV diagnoses. T-tests compared Latino American (n = 1,576) and Asian American respondents (n = 1,414) in strength of social network, level of family cohesion, and likelihood of seeking professional help. Linear regression models were used to identify the probability of help-seeking behavior based on ethnicity, PTSD diagnosis, and strength of social network. Results: Help-seeking behavior was significantly associated with family cohesion and strength of social network. It was found that higher frequency of expressing one’s feelings with family significantly predicted lower levels of help-seeking behaviors (β = [-.072], p = .017), while higher frequency of spending free time with family significantly predicted higher levels of help-seeking behaviors (β = [.129], p = .002) in the Asian American sample. Subjective importance of family relations compared to that of one’s peers also significantly predict higher levels of help-seeking behaviors (β = [.095], p = .011) in the Asian American sample. Frequency of sharing one’s problems with relatives significantly predicted higher levels of help-seeking behaviors (β = [.113], p < .01) in the Latino American sample. A PTSD diagnosis did not have any significant moderating effect. Conclusion: Considering the underutilization of mental health services in Latino and Asian American minority groups, it is crucial to understand ways in which help seeking behavior can be encouraged. Our findings suggest that different dimensions within family cohesion and social networks have differential impacts on help-seeking behavior. Given the multifaceted nature of family cohesion and cultural relevance, the implications of our findings for theory and practice will be discussed.

Keywords: family cohesion, social networks, Asian American, Latino American, help-seeking behavior

Procedia PDF Downloads 63

Authors: Marina Yurievna Aleksandrova

Abstract:

Research of the Holocaust retains value not only for history but also for sociology and psychology. One of the most important fields of study is how people were coping during and after this traumatic event. The aim of this paper is to identify the main contexts of the topic of love and to determine which contexts are more characteristic for different groups of victims of the Holocaust (gender, nationality, age). In this research, transcripts of interviews with Holocaust victims that were collected during 1946 for the "Voices of the Holocaust" project were used as data. Main contexts were analyzed with methods of network analysis and latent semantic analysis and classified by gender, age, and nationality with random forest. The results show that love is articulated and described significantly differently for male and female informants, nationality is shown results with lower values of quality metrics, as well as the age.

Keywords: Holocaust, latent semantic analysis, network analysis, text-mining, random forest

Procedia PDF Downloads 178

Authors: Petr Šimek

Abstract:

This work deals with the problem of synchronization of bus frames during transmission using USB (Universal Serial Bus). The principles for synchronization between USB and the non-deterministic CAN (Controller Area Network) bus will be described here. Furthermore, the work deals with ensuring the time sequence of communication frames when receiving from multiple communication bus channels. The structure of a general object for storing frames from different types of communication buses, such as CAN and LIN (Local Interconnect Network), will be described here. Finally, an evaluation of the communication throughput of bus frames for USB High speed will be performed. The creation of this architecture was based on the analysis of the communication of control units with a large number of communication buses. For the design of the architecture, a test HW with a USB-HS interface was used, which received previously known messages, which were compared with the received result. The result of this investigation is the block architecture of the control program for test HW ensuring correct data transmission via the USB bus.

Keywords: analysis, CAN, interface, LIN, synchronization, USB

Procedia PDF Downloads 56

Authors: Regina Kulugomba, Richard Blanchard, Harold Mapoma, Gregory Gamula, Stanley Mlatho

Abstract:

Malawi is a country with low energy access with only 10% of people having access to electricity and 97% of people relying on charcoal and fuel wood. The over dependence on the traditional biomass has brought in a number of negative consequences on people’s health and the environment. To curb the situation, the Government of Malawi (GoM), through its national policy of 2018 and charcoal strategies of 2007, identified biogas as a suitable alternative energy source for cooking. The GoM intends to construct tubular digesters across the country and one of the most crucial factors is the availability of livestock manure. The study was conducted to assess biogas potential from livestock manure by using Quantum Geographic information system (QGIS) software. Potential methane was calculated based on the population of livestock, amount of manure produced per capita and year, total solids, biogas yield and availability coefficient. The results of the study estimated biogas potential at 687 million m3 /year. Districts identified with highest biogas potential were Lilongwe, Ntcheu, Mangochi, Neno, Mwanza, Blantyre, Chiradzulu and Mulanje. The information will help investors and the Government of Malawi to locate potential sites for biogas plants installation.

Keywords: biogas, energy, feedstock, livestock

Procedia PDF Downloads 160

Authors: F. Nasser-Abu Alhija

Abstract:

In many countries, much efforts and resources are devoted to empowering and integrating minorities within the mainstream population. Major ventures in this route are crafted in higher education institutions where different outreach programs and methods such as lenient entry requirements, monitory incentives, learning skills workshops, tutoring and mentoring, are utilized. Although there is some information regarding these programs, their effectiveness still needs to be thoroughly examined. The Ethiopian community In Israel is one of the minority groups that has been targeted by sponsoring foundations and higher education institutions with the aim to ease the access, persistence and success of its young people in higher education and later in the job market. The evaluation study we propose to present focuses on the implementation of a program designed for this purpose. This program offers relevant candidates for study at a prestigious university a variety of generous incentives that include tuitions, livening allowance, tutoring, mentoring, skills and empowerment workshops and cultural meetings. Ten students were selected for the program and they started their studies in different subject areas before three and half years. A longitudinal evaluation has been conducted since the implementation of the program. Data were collected from different sources: participating students, program coordinator, mentors, tutors, program documents and university records. Questionnaires and interviews were used for collecting data on the different components of the program and on participants' perception of their effectiveness. Participants indicate that the lenient entry requirements and the monitory incentives are critical for starting their studies. During the first year, skills and empowering workshops, torturing and mentoring were evaluated as very important for persistence and success in studies. Tutoring was perceived as very important also at the second year but less importance is attributed to mentoring. Mixed results regarding integration in the Israeli culture emerged. The results are discussed with reference to findings from different settings around the world.

Keywords: access to higher education, minority groups, monitory incentives, torturing, mentoring

Procedia PDF Downloads 369

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

Abstract:

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 129

Authors: Frank Kuebler, Rolf Steinhilper

Abstract:

Artificial neural networks (ANN) as well as Design of Experiments (DOE) based regression analysis (RA) are mainly used for modeling of complex systems. Both methodologies are commonly applied in process and quality control of manufacturing processes. Due to the fact that resource efficiency has become a critical concern for manufacturing companies, these models needs to be extended to predict resource-consumption of manufacturing processes. This paper describes an approach to use neural networks as well as DOE based regression analysis for predicting resource consumption of manufacturing processes and gives a comparison of the achievable results based on an industrial case study of a turning process.

Keywords: artificial neural network, design of experiments, regression analysis, resource efficiency, manufacturing process

Procedia PDF Downloads 520

Authors: Seyed Sadegh Naseralavi, Najmeh Bemani

Abstract:

In this paper, different concrete codes including America, New Zealand, Mexico, Italy, India, Canada, Hong Kong, Euro Code and Britain are compared with the Iranian concrete design code. First, by using Adaptive Neuro Fuzzy Inference System (ANFIS), the codes having the most correlation with the Iranian ninth issue of the national regulation are determined. Consequently, two anticipated methods are used for comparing the codes: Artificial Neural Network (ANN) and Multi-variable regression. The results show that ANN performs better. Predicting is done by using only tensile steel ratio and with ignoring the compression steel ratio.

Keywords: adaptive neuro fuzzy inference system, anticipate method, artificial neural network, concrete design code, multi-variable regression

Procedia PDF Downloads 277

Authors: M. Saiful Islam, M. Mohandes, S. Rehman, S. Badran

Abstract:

Increasing necessity of wind power is directing us to have precise knowledge on wind resources. Methodical investigation of potential locations is required for wind power deployment. High penetration of wind energy to the grid is leading multi megawatt installations with huge investment cost. This fact appeals to determine appropriate places for wind farm operation. For accurate assessment, detailed examination of wind speed profile, relative humidity, temperature and other geological or atmospheric parameters are required. Among all of these uncertainty factors influencing wind power estimation, vertical extrapolation of wind speed is perhaps the most difficult and critical one. Different approaches have been used for the extrapolation of wind speed to hub height which are mainly based on Log law, Power law and various modifications of the two. This paper proposes a Artificial Neural Network (ANN) and Genetic Algorithm (GA) based hybrid model, namely GA-NN for vertical extrapolation of wind speed. This model is very simple in a sense that it does not require any parametric estimations like wind shear coefficient, roughness length or atmospheric stability and also reliable compared to other methods. This model uses available measured wind speeds at 10m, 20m and 30m heights to estimate wind speeds up to 100m. A good comparison is found between measured and estimated wind speeds at 30m and 40m with approximately 3% mean absolute percentage error. Comparisons with ANN and power law, further prove the feasibility of the proposed method.

Keywords: wind profile, vertical extrapolation of wind, genetic algorithm, artificial neural network, hybrid machine learning

Procedia PDF Downloads 485

Authors: Mohsen Azarmjoo, Mehdi Mehdizadeh Koupaei, Maryam Mehdizadeh Koupaei, Asghar Mahdlouei Azar

Abstract:

The increasing prevalence of wireless networks in our daily lives has made them indispensable. The aim of this research is to investigate the management of information transfer in wireless networks and the integration of renewable solar energy resources in a residential building. The focus is on the transmission of electricity and information through wireless networks, as well as the utilization of sensors and wireless fire alarm systems. The research employs a descriptive approach to examine the transmission of electricity and information on a wireless network with electric and optical telephone lines. It also investigates the transmission of signals from sensors and wireless fire alarm systems via radio waves. The methodology includes a detailed analysis of security, comfort conditions, and costs related to the utilization of wireless networks and renewable solar energy resources. The study reveals that it is feasible to transmit electricity on a network cable using two pairs of network cables without the need for separate power cabling. Additionally, the integration of renewable solar energy systems in residential buildings can reduce dependence on traditional energy carriers. The use of sensors and wireless remote information processing can enhance the safety and efficiency of energy usage in buildings and the surrounding spaces.

Keywords: renewable energy, intelligentization, wireless sensors, fire alarm system

Procedia PDF Downloads 51

Authors: Modesta E. Ezema, Chikwendu V. Alabekee, Victoria N. Ishiwu, Ifeyinwa NwosuArize, Chinedu I. Nwoye

Abstract:

The advent of wireless networking in computing technology cannot be overemphasized, it opened up easy accessibility to information resources, networking made easier and brought internet accessibility to our doorsteps, but despite all these, some mishap came in with it that is causing mayhem in today ‘s overall information security. The cyber criminals will always compromise the integrity of a message that is not encrypted or that is encrypted with a weak algorithm.In other to correct the mayhem, this study focuses on cryptosystem and cryptography. This ensures end to end crypt messaging. The study of various cryptographic algorithms, as well as the techniques and applications of the cryptography for efficiency, were all considered in the work., present and future applications of cryptography were dealt with as well as Quantum Cryptography was exposed as the current and the future area in the development of cryptography. An empirical study was conducted to collect data from network users.

Keywords: algorithm, cryptography, cryptosystem, network

Procedia PDF Downloads 340

Authors: Keunhong Chae, Seokho Yoon

Abstract:

Recently, the global navigation satellite system (GNSS) such as Galileo and GPS is employing more satellites to provide a higher degree of accuracy for the location service, thus calling for a more efficient signaling scheme among the satellites used in the overall GNSS network. In that the network throughput is improved, the spatial diversity can be one of the efficient signaling schemes; however, it requires multiple antenna that could cause a significant increase in the complexity of the GNSS. Thus, a diversity scheme called the cooperative signaling was proposed, where the virtual multiple-input multiple-output (MIMO) signaling is realized with using only a single antenna in the transmit satellite of interest and with modeling the neighboring satellites as relay nodes. The main drawback of the cooperative signaling is that the relay nodes receive the transmitted signal at different time instants, i.e., they operate in an asynchronous way, and thus, the overall performance of the GNSS network could degrade severely. To tackle the problem, several modified cooperative signaling schemes were proposed; however, all of them are difficult to implement due to a signal decoding at the relay nodes. Although the implementation at the relay nodes could be simpler to some degree by employing the time-reversal and conjugation operations instead of the signal decoding, it would be more efficient if we could implement the operations of the relay nodes at the source node having more resources than the relay nodes. So, in this paper, we propose a novel cooperative signaling scheme, where the data signals are combined in a unique way at the source node, thus obviating the need of the complex operations such as signal decoding, time-reversal and conjugation at the relay nodes. The numerical results confirm that the proposed scheme provides the same performance in the cooperative diversity and the bit error rate (BER) as the conventional scheme, while reducing the complexity at the relay nodes significantly. Acknowledgment: This work was supported by the National GNSS Research Center program of Defense Acquisition Program Administration and Agency for Defense Development.

Keywords: global navigation satellite network, cooperative signaling, data combining, nodes

Procedia PDF Downloads 277

Authors: Ajeni Ari

Abstract:

In addressing gender and transport, considerations of mobility disparities amongst users are important. Public transport (PT) policy and design do not efficiently account for the varied mobility practices between men and women, with literature only recently showing a movement towards gender inclusion in transport. Arrantly, transport policy and designs remain gender-blind to the variation of mobility needs. The global movement towards sustainability highlights the need for expeditious strategies that could mitigate biases within the existing system. At the forefront of such plan of action may, in part, be mandated inclusive infrastructural designs that stimulate user engagement with the transport system. Fundamentally access requires a means or an opportunity to entity, which for PT is an establishment of its physical environment and/or infrastructural design. Its practicality may be utilised with knowledge of shortcomings in tangible or intangible aspects of the service offerings allowing access to opportunities. To inform on existing biases in PT planning and design, this study analyses qualitative data to examine the opinions and lived experiences among transport user in Ireland. Findings show that infrastructural design plays a significant role in users’ engagement with the service. Paramount to accessibility are service provisions that cater to both user interactions and those of their dependents. Apprehension to use the service is more so evident with women in comparison to men, particularly while carrying out household duties and caring responsibilities at peak times or dark hours. Furthermore, limitations are apparent with infrastructural service offerings that do not accommodate the physical (dis)ability of users, especially universal design. There are intersecting factors that impinge on accessibility, e.g., safety and security, yet essentially, infrastructural design is an important influencing parameter to user perceptual conditioning. Additionally, data discloses the need for user intricacies to be factored in transport planning geared towards gender inclusivity, including mobility practices, travel purpose, transit time or location, and system integration.

Keywords: public transport, accessibility, women, transport infrastructure

Procedia PDF Downloads 74

Authors: Hasanein Hasan, Mohammed Al-Taie, Basil Shanshool, Khalaf Abd-Ali

Abstract:

This approach aims to deal with establishing and operating Iraqi Fibre-To-The-Home (FTTH) projects. The problems they suffer from are organized sabotage, vandalism, accidental damage and poor planning. It provides practical solutions that deal with the aforementioned problems. These solutions consist of both technical and financial clarifications that ensure the achievement of the FTTH network’s stability for the purpose of equipping citizens, private sector companies, and governmental institutions with services, data transmission, the Internet, and other services. They aim to solve problems and obstacles accompanying the operation and maintenance of FTTH projects implemented by the Informatics and Telecommunications Public Company (ITPC)/ Iraqi Ministry of Communications (MoC). This approach takes the FTTH network of AlMaalif-AlMuaslat districts/ Baghdad-Iraq as a case study.

Keywords: CCTV, FTTH, ITPC, MoC, NVR, PTZ

Procedia PDF Downloads 75

Authors: Rachel Gugu Mkhasibe

Abstract:

Incorporation of technology as a pedagogy has many benefits. For instance, improvement of pedagogy, increased information access, increased cooperation, and collaboration. However, as good as it may be, this integration of technology as a pedagogy has not been widely adopted in most historically Black higher education institutions especially those in developing countries. For example, the socioeconomic background of students in historically black universities, the weak financial support available from these universities, as well as a large population of students struggle to access the recommended modern physical resources such as iPads, laptops, mobile phones, to name a few. This contributes to an increase in the increase of educational inequalities. The qualitative research approach was utilized in this work to gather detailed data about the obstacles created by the integration of technology as a pedagogy. Interviews were conducted to generate data from 20 academics from 10 Leve two students from one of the historically disadvantaged higher education Institutions in South Africa. The findings revealed that although both students and academics had overwhelming support of the integration of technology as a pedagogy in their institution, the environment which they found themselves in compromise the incorporation of technology as a pedagogy. Therefore, this paper recommends that Department of Higher Education and University Management should intervene and budget for technology to be provided in all the institutions of higher education regardless of where the institutions are situated.

Keywords: collaboration, integration, pedagogy, technology

Procedia PDF Downloads 77

Authors: Dania Aljouhi

Abstract:

September 26th, 2017, is a historic date for all women in Saudi Arabia. On that day, Saudi Arabia announced the decree on allowing Saudi women to drive. With the advent of vision 2030 and its goal to empower women and increase their participation in Saudi society, we see how Saudis’ Twitter users deliberate the 2017 decree from different social, cultural, religious, economic and political factors. This topic bridges social media 'Twitter,' gender and social-cultural studies to offer insights into how Saudis’ tweets reflect a broader discourse on Saudi women in the age of social media. The present study aims to explore the meanings and themes that emerge by Saudis’ Twitter users in response to the 2017 royal decree on women driving. The sample used in the current study involves (n= 1000) tweets that were collected from Sep 2017 to March 2019 to account for the Saudis’ tweets before and after implementing the decree. The paper uses semantic and thematic network analysis methods to examine the Saudis’ Twitter discourse on the women driving issue. The paper argues that Twitter as a platform has mediated the discourse of women driving among the Saudi community and facilitated social changes. Finally, framing theory (Goffman, 1974) and Networked framing (Meraz & Papacharissi 2013) are both used to explain the tweets on the decree of allowing Saudi women to drive based on # Saudi women-driving-cars.

Keywords: Saudi Arabia, women, Twitter, semantic network analysis, framing

Procedia PDF Downloads 149

Authors: Nadia Nisha Musa, Nur Atirah Hasmi, Hasnun Nita Ismail, Zulfadli Mahfodz

Abstract:

In Malaysian Education System, subject related to biodiversity has started in the curriculum from Foundation Study until tertiary education. Biodiversity become the focus of attention due to awareness on global warming which potentially leads to a loss of biodiversity. A loss in biodiversity means a loss in medicinal discoveries and reduces food supply. It is of great important to ensure that young generations become aware of biodiversity conservation. The more interactive approaches are needed to build society with a high awareness for biodiversity conservation. To address this challenge, the goal of this study is to enhance intrinsic motivation of biological students via ARCS model of instruction. Self-access learning materials such as tutorial, module and fieldwork were designed with ARCS elements to a sample size of 70 university students from the beginning of the semester. Both paper and online surveys were used to collect data from the respondents. The results showed that elements of attention, relevance, confidence and satisfaction have a positive impact on intrinsic motivation of students and their academic performance.

Keywords: intrinsic motivation, ARCS model of instruction, biodiversity, self-access learning

Procedia PDF Downloads 219

Authors: Zhi-Jun Lu, Qi Lu, Meng Wu, Qian Xiang, Jun Gu

Abstract:

The analysis of perforated steel members is a 3D problem in nature, therefore the traditional analytical expressions for the ultimate load of thin-walled steel sections cannot be used for the perforated steel member design. In this study, finite element method (FEM) and artificial neural network (ANN) were used to simulate the process of stub column tests based on specific codes. Results show that compared with those of the FEM model, the ultimate load predictions obtained from ANN technique were much closer to those obtained from the physical experiments. The ANN model for the solving the hard problem of complex steel perforated sections is very promising.

Keywords: artificial neural network (ANN), finite element method (FEM), perforated sections, thin-walled Steel, ultimate load

Procedia PDF Downloads 347

Authors: Adrien Marque, Daniel Delahaye, Pierre Maréchal, Isabelle Berry

Abstract:

Wind direction and uncertainty are crucial in aircraft or unmanned aerial vehicle trajectories. By computing wind covariance matrices on each spatial grid point, these spatial grids can be defined as images with symmetric positive definite matrix elements. A data pre-processing step, a specific convolution, a specific max-pooling, and a specific flatten layers are implemented to process such images. Then, the neural network is applied to spatial grids, whose elements are wind covariance matrices, to solve classification problems related to the feasibility of unmanned aerial vehicles based on wind direction and wind uncertainty.

Keywords: wind direction, uncertainty level, unmanned aerial vehicle, convolution neural network, SPD matrices

Procedia PDF Downloads 40

Authors: Saad Chahba, Rabia Sehab, Ahmad Akrad, Cristina Morel

Abstract:

Nowadays, the electric machines used in urban electric vehicles are, in most cases, three-phase electric machines with or without a magnet in the rotor. Permanent Magnet Synchronous Machine (PMSM) and Induction Machine (IM) are the main components of drive trains of electric and hybrid vehicles. These machines have very good performance in healthy operation mode, but they are not redundant to ensure safety in faulty operation mode. Faced with the continued growth in the demand for electric vehicles in the automotive market, improving the reliability of electric vehicles is necessary over the lifecycle of the electric vehicle. Multiphase electric machines respond well to this constraint because, on the one hand, they have better robustness in the event of a breakdown (opening of a phase, opening of an arm of the power stage, intern-turn short circuit) and, on the other hand, better power density. In this work, a diagnosis approach using a neural network for an open circuit fault or more of a five-phase induction machine is developed. Validation on the simulator of the vehicle drivetrain, at reduced power, is carried out, creating one and more open circuit stator phases showing the efficiency and the reliability of the new approach to detect and to locate on-line one or more open phases of a five-induction machine.

Keywords: electric vehicle drivetrain, multiphase drives, induction machine, control, open circuit (OC) fault diagnosis, artificial neural network

Procedia PDF Downloads 202

Authors: Afaf Alharbi, Qianni Zhang

Abstract:

The identification of malignant tissue in histopathological slides holds significant importance in both clinical settings and pathology research. This paper introduces a methodology aimed at automatically categorizing cancerous tissue through the utilization of a multiple-instance learning framework. This framework is specifically developed to acquire knowledge of the Bernoulli distribution of the bag label probability by employing neural networks. Furthermore, we put forward a neural network based permutation-invariant aggregation operator, equivalent to attention mechanisms, which is applied to the multi-instance learning network. Through empirical evaluation of an openly available colon cancer histopathology dataset, we provide evidence that our approach surpasses various conventional deep learning methods.

Keywords: attention multiple instance learning, MIL and transfer learning, histopathological slides, cancer tissue classification

Procedia PDF Downloads 103