Search results for: cloud service models

Authors: Mustapha Mahmoud Dif, Fouzia Benali-Toumi, Mohamed Benyahia, Sofiane Bouazza, Abbes Dellal, Slimane Baha

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L. multifida is applied to treat rheumatism and cold and has hypoglycemic and anti-inflammatory properties. The present study is to optimize the extraction of phenolic compounds in Algerian Lavandula multifida. The influences of parameters including temperature (decoction and maceration) and extraction time (15min to 45 min) on the flavonoids concentration are studied. The optimal conditions are determined and the quadratic response surfaces draw from the mathematical models. Total phenols were evaluated using Folin sicaltieu methods, total flavonoids were estimated using the Tri chloral aluminum method. The maximum concentration extracted, for total flavonoids, equal to 0.043 mg/g was achieved with decoction and extraction time of 41.55 min. However, for total phenol compounds highest concentration of 0.218 mg/g, is obtained with 45 min at 49.99°C.

Keywords: L multifidi, phenolic content, optimization, time, temperature

Procedia PDF Downloads 398

Authors: Danilo López, Edwin Rivas, Fernando Pedraza

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Currently, one of the major challenges in wireless networks is the optimal use of radio spectrum, which is managed inefficiently. One of the solutions to existing problem converges in the use of Cognitive Radio (CR), as an essential parameter so that the use of the available licensed spectrum is possible (by secondary users), well above the usage values that are currently detected; thus allowing the opportunistic use of the channel in the absence of primary users (PU). This article presents the results found when estimating or predicting the future use of a spectral transmission band (from the perspective of the PU) for a chaotic type channel arrival behavior. The time series prediction method (which the PU represents) used is ANFIS (Adaptive Neuro Fuzzy Inference System). The results obtained were compared to those delivered by the RNA (Artificial Neural Network) algorithm. The results show better performance in the characterization (modeling and prediction) with the ANFIS methodology.

Keywords: ANFIS, cognitive radio, prediction primary user, RNA

Procedia PDF Downloads 399

Authors: Ibtissem Hosni, Lilia Bennaceur Farah, Saber Mohamed Naceur

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In order to assess the water availability in the soil, it is crucial to have information about soil distributed moisture content; this parameter helps to understand the effect of humidity on the exchange between soil, plant cover and atmosphere in addition to fully understanding the surface processes and the hydrological cycle. On the other hand, aerodynamic roughness length is a surface parameter that scales the vertical profile of the horizontal component of the wind speed and characterizes the surface ability to absorb the momentum of the airflow. In numerous applications of the surface hydrology and meteorology, aerodynamic roughness length is an important parameter for estimating momentum, heat and mass exchange between the soil surface and atmosphere. It is important on this side, to consider the atmosphere factors impact in general, and the natural erosion in particular, in the process of soil evolution and its characterization and prediction of its physical parameters. The study of the induced movements by the wind over soil vegetated surface, either spaced plants or plant cover, is motivated by significant research efforts in agronomy and biology. The known major problem in this side concerns crop damage by wind, which presents a booming field of research. Obviously, most models of soil surface require information about the aerodynamic roughness length and its temporal and spatial variability. We have used a bi-dimensional multi-scale (2D MLS) roughness description where the surface is considered as a superposition of a finite number of one-dimensional Gaussian processes each one having a spatial scale using the wavelet transform and the Mallat algorithm to describe natural surface roughness. We have introduced multi-layer aspect of the humidity of the soil surface, to take into account a volume component in the problem of backscattering radar signal. As humidity increases, the dielectric constant of the soil-water mixture increases and this change is detected by microwave sensors. Nevertheless, many existing models in the field of radar imagery, cannot be applied directly on areas covered with vegetation due to the vegetation backscattering. Thus, the radar response corresponds to the combined signature of the vegetation layer and the layer of soil surface. Therefore, the key issue of the numerical estimation of soil moisture is to separate the two contributions and calculate both scattering behaviors of the two layers by defining the scattering of the vegetation and the soil blow. This paper presents a synergistic methodology, and it is for estimating roughness and soil moisture from C-band radar measurements. The methodology adequately represents a microwave/optical model which has been used to calculate the scattering behavior of the aerodynamic vegetation-covered area by defining the scattering of the vegetation and the soil below.

Keywords: aerodynamic, bi-dimensional, vegetation, synergistic

Procedia PDF Downloads 254

Authors: Medhin Haftom Hailu

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The advancement of information technology has significantly impacted Ethiopia's economy, driving innovation, productivity, job creation, and global connectivity. This research examined the impact of contemporary information and communication technologies on Ethiopian economic progress. The study examined eight variables, including mobile, internet, and fixed-line penetration rates, and five macroeconomic control variables. The results showed a positive and strong effect of ICT on economic growth in Ethiopia, with 1% increase in mobile, internet, and fixed line services penetration indexes resulting in an 8.03, 10.05, and 30.06% increase in real GDP. The Granger causality test showed that all ICT variables Granger caused economic growth, but economic growth Granger caused mobile penetration rate only. The study suggests that coordinated ICT infrastructure development, increased telecom service accessibility, and increased competition in the telecom market are crucial for Ethiopia's economic growth. Ethiopia is attempting to establish a digital economy through massive investment in ensuring ICT quality and accessibility. Thus, the research could enhance in understanding of the economic impact of ICT expansion for successful ICT policy interventions for future research.

Keywords: economic growth, cointegration and error correction, ICT expansion, granger causality, penetration

Procedia PDF Downloads 55

Authors: Mostefa Hamrat, Bensaid Boulekbache, Mohamed Chemrouk, Sofiane Amziane

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The paper presents the results of an experimental work on the flexural behaviour of two types of concrete in terms of the progressive cracking process until failure and the crack opening, and beam deflection, using Digital Image Correlation (DIC) technique. At serviceability limit states, comparisons of the building code equations and the equations developed by some researchers for the short-term deflections and crack widths have been made using the reinforced concrete test beams. The experimental results show that the addition of steel fibers increases the first cracking load and amplify the number of cracks that conducts to a remarkable decreasing in the crack width with an increasing in ductility. This study also shows that there is a good agreement between the deflection values for RC beams predicted by the major codes (Eurocode2, ACI 318, and the CAN/CSA-S806) and the experimental results for beams with steel fibers at service load. The most important added benefit of the DIC technique is that it allows detecting the first crack with a high precision easily measures the crack opening and follows the progressive cracking process until failure of reinforced concrete members.

Keywords: beams, digital image correlation (DIC), deflection, crack width, serviceability, codes provisions

Procedia PDF Downloads 319

Authors: Vareesha Masood, Ammara Gul, Nabeeha Areej, Muhammad Asif Masood, Hamna Imran

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The universal use of PDF files has prompted hackers to use them for malicious intent by hiding malicious codes in their victim’s PDF machines. Machine learning has proven to be the most efficient in identifying benign files and detecting files with PDF malware. This paper has proposed an approach using a decision tree classifier with parameters. A modern, inclusive dataset CIC-Evasive-PDFMal2022, produced by Lockheed Martin’s Cyber Security wing is used. It is one of the most reliable datasets to use in this field. We designed a PDF malware detection system that achieved 99.2%. Comparing the suggested model to other cutting-edge models in the same study field, it has a great performance in detecting PDF malware. Accordingly, we provide the fastest, most reliable, and most efficient PDF Malware detection approach in this paper.

Keywords: PDF, PDF malware, decision tree classifier, random forest classifier

Procedia PDF Downloads 72

Authors: A. C. Bennis, F. Dumas, F. Ardhuin, B. Blanke

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The mechanics of rip currents are complex, involving interactions between waves, currents, water levels and the bathymetry, that present particular challenges for numerical models. Here, the effects of a grid-spacing dependent horizontal mixing on the wave-current interactions are studied. Near the shore, wave rays diverge from channels towards bar crests because of refraction by topography and currents, in a way that depends on the rip current intensity which is itself modulated by the horizontal mixing. At low resolution with the grid-spacing dependent horizontal mixing, the wave motion is the same for both coupling modes because the wave deviation by the currents is weak. In high-resolution case, however, classical results are found with the stabilizing effect of the flow by feedback of waves on currents. Lastly, wave-current interactions and the horizontal mixing strongly affect the intensity of the three-dimensional rip velocity.

Keywords: numerical modeling, wave-current interactions, turbulence modeling, rip currents

Procedia PDF Downloads 449

Authors: Yung-Ching Chou, Albert Shangpao Yeh, Luke H. C. Hsiao

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Police used to be an honor job. However, the police are no longer concerned about the mission and public safety instead of the issue of retirement. The main reason is the amendment of 'Public Servants Retirement Act' in Taiwan was effective since January 2011. The purposes of change were to solve the problem of the financial crisis which caused by the Hugh deficit of the civil servants pension fund. The policy of the civil servants pension reform was not only seriously impact the motives of policy, but also negatively impact the workforce of police. This research conducted a secondary data of Baoanjingcha Fifth Police Corps during the period between 2011 and 2015. Secondly, the research interviewed six representatives from the retired police in order to explore the retirement motives. In short, there were several major findings and suggestions in the following: 1. The police won't choice to retire which the nature of task is simple. 2. The ranking level of positions positively correlated with the retired age of police. 3. The police officers who are categorized as 'hazardous work' first class personnel should decrease the standard of the retirement age and allow the option of a monthly pension. 4. The information of the retirees' rights, as well as protection, are correlated with the service as well professional of personnel officer. More findings, as well as suggestions, will be elaborated on the content of this paper.

Keywords: human resource management, pension policy change, police retirement rush, public servants retirement act

Procedia PDF Downloads 307

Authors: Jaemoon Lim

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To construct the lumped spring-mass model considering the occupants for the offset frontal crash, the SISAME software and the NHTSA test data were used. The data on 56 kph 40% offset frontal vehicle to deformable barrier crash test of a MY2007 Mazda 6 4-door sedan were obtained from NHTSA test database. The overall behaviors of B-pillar and engine of simulation models agreed very well with the test data. The trends of accelerations at the driver and passenger head were similar but big differences in peak values. The differences of peak values caused the large errors of the HIC36 and 3 ms chest g’s. To predict well the behaviors of dummies, the spring-mass model for the offset frontal crash needs to be improved.

Keywords: chest g’s, HIC36, lumped spring-mass model, offset frontal impact, SISAME

Procedia PDF Downloads 437

Authors: Shenlun Chen, Leonard Wee

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Tumor grading is an essential reference for colorectal cancer (CRC) staging and survival prognostication. The widely used World Health Organization (WHO) grading system defines histological grade of CRC adenocarcinoma based on the density of glandular formation on whole slide images (WSI). Tumors are classified as well-, moderately-, poorly- or un-differentiated depending on the percentage of the tumor that is gland forming; >95%, 50-95%, 5-50% and <5%, respectively. However, manually grading WSIs is a time-consuming process and can cause observer error due to subjective judgment and unnoticed regions. Furthermore, pathologists’ grading is usually coarse while a finer and continuous differentiation grade may help to stratifying CRC patients better. In this study, a deep learning based automatic differentiation grading algorithm was developed and evaluated by survival analysis. Firstly, a gland segmentation model was developed for segmenting gland structures. Gland regions of WSIs were delineated and used for differentiation annotating. Tumor regions were annotated by experienced pathologists into high-, medium-, low-differentiation and normal tissue, which correspond to tumor with clear-, unclear-, no-gland structure and non-tumor, respectively. Then a differentiation prediction model was developed on these human annotations. Finally, all enrolled WSIs were processed by gland segmentation model and differentiation prediction model. The differentiation grade can be calculated by deep learning models’ prediction of tumor regions and tumor differentiation status according to WHO’s defines. If multiple WSIs were possessed by a patient, the highest differentiation grade was chosen. Additionally, the differentiation grade was normalized into scale between 0 to 1. The Cancer Genome Atlas, project COAD (TCGA-COAD) project was enrolled into this study. For the gland segmentation model, receiver operating characteristic (ROC) reached 0.981 and accuracy reached 0.932 in validation set. For the differentiation prediction model, ROC reached 0.983, 0.963, 0.963, 0.981 and accuracy reached 0.880, 0.923, 0.668, 0.881 for groups of low-, medium-, high-differentiation and normal tissue in validation set. Four hundred and one patients were selected after removing WSIs without gland regions and patients without follow up data. The concordance index reached to 0.609. Optimized cut off point of 51% was found by “Maxstat” method which was almost the same as WHO system’s cut off point of 50%. Both WHO system’s cut off point and optimized cut off point performed impressively in Kaplan-Meier curves and both p value of logrank test were below 0.005. In this study, gland structure of WSIs and differentiation status of tumor regions were proven to be predictable through deep leaning method. A finer and continuous differentiation grade can also be automatically calculated through above models. The differentiation grade was proven to stratify CAC patients well in survival analysis, whose optimized cut off point was almost the same as WHO tumor grading system. The tool of automatically calculating differentiation grade may show potential in field of therapy decision making and personalized treatment.

Keywords: colorectal cancer, differentiation, survival analysis, tumor grading

Procedia PDF Downloads 123

Authors: Fredrick Ishengoma, Leonard Mselle, Hector Mongi

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The growing number of mobile phone subscribers in Tanzania offers the government a new channel for the delivery of information and government services to citizens, thus mobile Government (m-Government). In Tanzania, m-Government services usage is in the early stages, and factors that influence its adoption are yet to be known. This study seeks to identify and understand the critical success factors (CSFs) that influence citizens’ behavioural intention (BI) to adopt m-Government services in Tanzania. The study employed the mobile services acceptance model (MSAM) and extends it with external factors relevant in the Tanzanian context. A survey questionnaire was used to collect primary data from users of m-Government services in Dar es salaam and Dodoma cities, and 253 responses were received. Data were analyzed by IBM-SPSS AMOS 23.0 software using structural equation modeling (SEM). The findings of the study indicate that perceived usefulness, trust, perceived mobility, power distance, quality of service, awareness, perceived cost, personal initiatives, and characteristics significantly influence the BI to adopt m-Government services. However, perceived ease of use was found statistically insignificant to predict BI. Furthermore, the interplay between CSFs, discussion on theoretical and practical implications that follow from the results are presented.

Keywords: adoption, critical success factors, structural equation modeling, m-Government, MSAM, Tanzania

Procedia PDF Downloads 128

Authors: Thiraporn Chumphuming, Nuttida Boonmathi, Supattra Thanomsiang, Tawatchai Noree, Suthee Boonchaloem, Rinyaphat Kecharananta

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This research aims to study about the formats of low-cost airlines’ services in domestic route by surveying customers’ requirements and satisfactions in choosing low-cost airlines to travel domestically. Chiang Mai International Airport and other regions in Chiang Mai are the bases where the information is quantitatively collected. Passengers and questionnaires of 400 are the data base in which the researchers collected information from. Statistic units used are Percentage, Weighted Average, and Standard Deviation. The result of the study reveals that the group of 400 representative samples chooses Air Asia the most from overall six low-cost airlines that provide domestic services. Most of the representative samples book plane tickets for their traveling and they book tickets during the promotion time that provides cheap-priced tickets. Averagely, the price for a seat in one flight is around 501-1,000 Thai baht. The result of the satisfaction’s survey analyzed by the Marketing Mix Factors (7Ps) of low-cost airlines, which is divided into 4 parts including services before ticket reservations, services before boarding/purchasing tickets (ground), In-flight services, and Services after boarding they are satisfied with the baggage claim point informing, also gives the information that the passengers are highly satisfied with every process or the services.

Keywords: low-cost airline, service, satisfaction, customers' behavior

Procedia PDF Downloads 213

Authors: Ryan B. Simpson, Margaret A. Waskow, Aishwarya Venkat, Elena N. Naumova

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The Centers for Disease Control and Prevention (CDC) estimate that 31 known foodborne pathogens cause 9.4 million cases of these illnesses annually in US. Over 90% of these illnesses are associated with exposure to Campylobacter, Cryptosporidium, Cyclospora, Listeria, Salmonella, Shigella, Shiga-Toxin Producing E.Coli (STEC), Vibrio, and Yersinia. Contaminated products contain parasites typically causing an intestinal illness manifested by diarrhea, stomach cramping, nausea, weight loss, fatigue and may result in deaths in fragile populations. Since 1998, the National Outbreak Reporting System (NORS) has allowed for routine collection of suspected and laboratory-confirmed cases of food poisoning. While retrospective analyses have revealed common pathogen-specific seasonal patterns, little is known concerning the stability of those patterns over time and whether they can be used for preventative forecasting. The objective of this study is to construct a calendar of foodborne outbreaks of nine infections based on the peak timing of outbreak incidence in the US from 1996 to 2017. Reported cases were abstracted from FoodNet for Salmonella (135115), Campylobacter (121099), Shigella (48520), Cryptosporidium (21701), STEC (18022), Yersinia (3602), Vibrio (3000), Listeria (2543), and Cyclospora (758). Monthly counts were compiled for each agent, seasonal peak timing and peak intensity were estimated, and the stability of seasonal peaks and synchronization of infections was examined. Negative Binomial harmonic regression models with the delta-method were applied to derive confidence intervals for the peak timing for each year and overall study period estimates. Preliminary results indicate that five infections continue to lead as major causes of outbreaks, exhibiting steady upward trends with annual increases in cases ranging from 2.71% (95%CI: [2.38, 3.05]) in Campylobacter, 4.78% (95%CI: [4.14, 5.41]) in Salmonella, 7.09% (95%CI: [6.38, 7.82]) in E.Coli, 7.71% (95%CI: [6.94, 8.49]) in Cryptosporidium, and 8.67% (95%CI: [7.55, 9.80]) in Vibrio. Strong synchronization of summer outbreaks were observed, caused by Campylobacter, Vibrio, E.Coli and Salmonella, peaking at 7.57 ± 0.33, 7.84 ± 0.47, 7.85 ± 0.37, and 7.82 ± 0.14 calendar months, respectively, with the serial cross-correlation ranging 0.81-0.88 (p < 0.001). Over 21 years, Listeria and Cryptosporidium peaks (8.43 ± 0.77 and 8.52 ± 0.45 months, respectively) have a tendency to arrive 1-2 weeks earlier, while Vibrio peaks (7.8 ± 0.47) delay by 2-3 weeks. These findings will be incorporated in the forecast models to predict common paths of the spread, long-term trends, and the synchronization of outbreaks across etiological agents. The predictive modeling of foodborne outbreaks should consider long-term changes in seasonal timing, spatiotemporal trends, and sources of contamination.

Keywords: foodborne outbreak, national outbreak reporting system, predictive modeling, seasonality

Procedia PDF Downloads 109

Authors: Peter Adekunle, Clinton Aigbavboa, Matthew Ikuabe, Opeoluwa Akinradewo

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The future of machine learning (ML) in building may seem like a distant idea that will take decades to materialize, but it is actually far closer than previously believed. In reality, the built environment has been progressively increasing interest in machine learning. Although it could appear to be a very technical, impersonal approach, it can really make things more personable. Instead of eliminating humans out of the equation, machine learning allows people do their real work more efficiently. It is therefore vital to evaluate the factors influencing the implementation and challenges of implementing machine learning techniques in the South African built environment. The study's design was one of a survey. In South Africa, construction workers and professionals were given a total of one hundred fifty (150) questionnaires, of which one hundred and twenty-four (124) were returned and deemed eligible for study. Utilizing percentage, mean item scores, standard deviation, and Kruskal-Wallis, the collected data was analyzed. The results demonstrate that the top factors influencing the adoption of machine learning are knowledge level and a lack of understanding of its potential benefits. While lack of collaboration among stakeholders and lack of tools and services are the key hurdles to the deployment of machine learning within the South African built environment. The study came to the conclusion that ML adoption should be promoted in order to increase safety, productivity, and service quality within the built environment.

Keywords: machine learning, implementation, built environment, construction stakeholders

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Authors: Aliana Leong, T. C. Huan

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The purpose of Nostalgic themed tourism product is becoming popular in many countries. This study intends to investigate the role of nostalgia in destination image, experiential value and their effect on subsequent behavioral intention. The survey used stratified sampling method to include respondents from all the nearby Asian regions. The sampling is based on the data of inbound tourists provided by the Statistics and Census Service (DSEC) of government of Macau. The questionnaire consisted of five sections of 5 point Likert scale questions: (1) nostalgia, (2) destination image both before and after experience, (3) expected value, (4) experiential value, and (5) future visit intention. Data was analysed with structural equation modelling. The result indicates that nostalgia plays an important part in forming destination image and experiential value before individual had a chance to experience the destination. The destination image and experiential value share a bidirectional causal relationship that eventually contributes to future visit intention. The study also discovered that while experiential value is more effective in generating destination image, the later contribute more to future visit intention. The research design measures destination image and experiential value before and after respondents had experience the destination. The distinction between destination image and expected/experiential value can be examined because the longitudinal design of research method. It also allows this study to observe how nostalgia translates to future visit intention.

Keywords: nostalgia, destination image, experiential value, future visit intention

Procedia PDF Downloads 378

Authors: Yuzhi Cai

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This talk presents a Bayesian approach to quantile autoregressive (QAR) time series model estimation and forecasting. We establish that the joint posterior distribution of the model parameters and future values is well defined. The associated MCMC algorithm for parameter estimation and forecasting converges to the posterior distribution quickly. We also present a combining forecasts technique to produce more accurate out-of-sample forecasts by using a weighted sequence of fitted QAR models. A moving window method to check the quality of the estimated conditional quantiles is developed. We verify our methodology using simulation studies and then apply it to currency exchange rate data. An application of the method to the USD to GBP daily currency exchange rates will also be discussed. The results obtained show that an unequally weighted combining method performs better than other forecasting methodology.

Keywords: combining forecasts, MCMC, quantile modelling, quantile forecasting, predictive density functions

Procedia PDF Downloads 331

Authors: Louati Salma, Louhichi Awatef, Boujelbene Younes

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Analysis of the trade-off between competition and financial stability has been at the center of academic and policy debate for over two decades and especially since the 2007-2008 global financial crises. We use information on 10 OIC countries from 2005 to 2014 to investigate the influence of bank competition on individual bank stability and risk-taking. Alternatively, we explore whether the quality of prudential regulation may affect the nexus between competition and banking stability/risk-taking. We provide a particular attention to the Islamic banking system which principally involves with the Riba-free instruments as compared to the conventional interest-based system. We first run a dynamic panel regression (GMM), and then we apply a panel vector autoregressive (PVAR) methodology to compare both banking business models.

Keywords: Lerner index, Islamic banks, non-performing loans, prudential regulations, z-score

Procedia PDF Downloads 277

Authors: Benard Omogo

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The Kenyan Constitution 2010 introduced various commissions to devolve the powers that were previously centralized through the imperial Presidency. One of the commissions that directly determine the levels of remuneration and terms of service of Kenyan workers is the Salary and Remuneration Commission (SRC). Article 230 of the Kenyan Constitution 2010 mandates this commission to regularly review the remuneration and benefits of all the state officers and to advise the national and county governments on the remuneration and benefits of all other public officers. At the same time, article 54 of the Kenyan Labor Relations Act 2007 provides for the recognition of trade unions and collective bargaining agreements. The emerging challenges, therefore, originate from the conflicts of the mandate of the Salary and Remuneration Commission, whose advice is almost adopted as the order and this undermines the outcome of the Collective Bargaining Agreements. This has seen so many trade unions in Kenya being rendered irrelevant. This research paper is therefore going to sample the various trade unions of Kenya to assess the challenges that result from the position of the Salary and Remuneration Commission. We will also extend it by purposively sampling several trade unions in Africa to determine how they handle such challenges. The results from this paper will be useful to the Kenyan Lawmakers and Africa at large and may inform them to consider reviewing the laws and acts that relate to the trade unions for prosperity.

Keywords: salary, remuneration, collective, bargaining, labor laws

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Authors: Jonmichael Weaver, David Miller

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Dyneema is an ultra-high molecular weight polyethylene (UHMWPE) fiber created by DSM. This fiber has many applications due to the high tensile strength, low weight, and inability to absorb water. DSM manufactures a non-woven unidirectional cross-ply [0,90]2 lamina, using the Dyneema fiber. Using this lamina system, various thickness panels are created for a 40% lighter weight alternative to Kevlar for the same ballistics protection. Environmental effects on the ply/laminate system alter the material properties, resulting in diminished ultimate performance. Understanding the specific environmental parameters and characterizing the resulting material property degradation is essential for determining the safety and reliability of Dyneema in service. Two laminas were contrasted for their response to accelerated aging by UV, humidity, and temperature cycling. Both lamina contain the same fiber, SK-99, but differ in matrix composition, Dyneema HB-210 employs a polyurethane (PUR) based matrix, and HB-212 contains a rubber-based matrix. Each system was inspected using a scanning electron microscope (SEM) and evaluated by dynamic mechanical analysis (DMA) to characterize the material property changes alongside the corresponding composite damage and matrix failure mode over the aging parameters. Overall, resulting in the HB-212 degrading faster compared with the HB-210.

Keywords: dyneema, accelerated aging, polymers, ballistics protection, armor, DSM, kevlar, composites

Procedia PDF Downloads 138

Authors: Behzad Shahizare, N. Nik-Ghazali, Kannan M. Munisamy, Seyedsaeed Tabatabaeikia

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The main objective of this study is to clarify the effect of the adjustable outlet guide vane (OGV) on the axial fan. Three-dimensional Numerical study was performed to analyze the effect of adjustable guide vane for improving the airflow rate in axial fans. Grid independence test was done between five different meshes in order to choose the reliable mesh. In flow analyses, Reynolds averaged Navier-Stokes (RANS) equations was solved using three types of turbulence models named k-ɛ, k-ω and k-ω SST. The aerodynamic performances of the fan and guide vane were evaluated. Numerical method was validated by comparing with experimental test according to AMECA 210 standard. Results showed that, by using the adjustable guide vane the airflow rate is increased around 3% to 6 %. The maximum enhancement of the airflow rate was achieved when pressure was 374pa.

Keywords: axial fan, adjustable guide vane, CFD, turbo machinery

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Authors: Changgil Lee, Jooyoung Park, Seunghee Park

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In this study, bridge weigh-in-motion (BWIM) system was simulated under various driving conditions of vehicles to improve the performance of the BWIM system. Two driving conditions were considered. One was the number of the axle of the vehicles. Since the vehicles have different number of axle according to the types of the vehicle, the vehicles were modeled considering the number of the axle. The other was the speed of the vehicles because the speed of the vehicles is not consistent on the bridge. To achieve the goal, the dynamic characteristics of a bridge such as modal parameters were considered in numerical simulation by analyzing precision models. Also, the driving vehicles were modeled as mass-spring-damping systems reflecting the axle information.

Keywords: bridge weigh-in-motion (BWIM) system, driving conditions, precision analysis model, the number of axle, the speed of vehicle

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Authors: A. Alssbaiheen, S. Love

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Mobile government (m-government) is one of the promising technologies for developing the governance of developing countries. While developing countries often have less advanced internet infrastructure compared to the developed world, mobile phone penetration is very high in the Gulf Cooperation Council (GCC) countries and mobile internet use offers a means to transcend traditional logistical barriers to accessing government services. The study explores the challenges and opportunities of the mobile government in Saudi Arabia. Semi-structured interviews were conducted with a diverse cohort of Saudi mobile users. A total of 77 semi-structured interviews were collected and subsequently analysed using open, axial, and selective coding. The participants’ responses revealed that many opportunities exist for the development of m-government in Saudi Arabia, including high popular awareness of government initiatives in e-government, and willingness to use such services, largely due to the time-saving and convenience aspects it offers compared with traditional bureaucratic services. However, numerous barriers were identified, including the low quality and speed of the internet, service customization, and concerns about privacy data security. It was also felt that in addition to infrastructure challenges, the traditional bureaucratic attitude of government department would itself hinder the effective deployment and utilization of m-government services.

Keywords: awareness, barriers, challenges, government services, mobile government, m-government, opportunities

Procedia PDF Downloads 451

Authors: Nicole Pearcy, Jonathan J. Crofts, Nadia Chuzhanova

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In this paper, we employ a directed hypergraph model to investigate the extent to which environmental variability influences the set of available biochemical reactions within a living cell. Such an approach avoids the limitations of the usual complex network formalism by allowing for the multilateral relationships (i.e. connections involving more than two nodes) that naturally occur within many biological processes. More specifically, we extend the concept of network reciprocity to complex hyper-networks, thus enabling us to characterize a network in terms of the existence of mutual hyper-connections, which may be considered a proxy for metabolic network complexity. To demonstrate these ideas, we study 115 metabolic hyper-networks of bacteria, each of which can be classified into one of 6 increasingly varied habitats. In particular, we found that reciprocity increases significantly with increased environmental variability, supporting the view that organism adaptability leads to increased complexities in the resultant biochemical networks.

Keywords: complexity, hypergraphs, reciprocity, metabolism

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Authors: Svitov David, Alyamkin Sergey

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The usage of convolutional neural networks (CNNs) in conjunction with the margin-based softmax approach demonstrates the state-of-the-art performance for the face recognition problem. Recently, lightweight neural network models trained with the margin-based softmax have been introduced for the face identification task for edge devices. In this paper, we propose a distillation method for lightweight neural network architectures that outperforms other known methods for the face recognition task on LFW, AgeDB-30 and Megaface datasets. The idea of the proposed method is to use class centers from the teacher network for the student network. Then the student network is trained to get the same angles between the class centers and face embeddings predicted by the teacher network.

Keywords: ArcFace, distillation, face recognition, margin-based softmax

Procedia PDF Downloads 126

Authors: C. -L. Huang, J. -H. Ho

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Social media has become more and more important in our life. Many enterprises promote their services and products to fans via the social media. The positive or negative sentiment of feedbacks from fans is very important for enterprises to improve their products, services, and promotion activities. The purpose of this paper is to understand the sentiment of the fan’s responses by analyzing the responses posted by fans on Facebook. The entity and aspect of fan’s responses were analyzed based on a predefined ontology. The ontology for cell phone sentiment analysis consists of aspect categories on the top level as follows: overall, shape, hardware, brand, price, and service. Each category consists of several sub-categories. All aspects for a fan’s response were found based on the ontology, and their corresponding sentimental terms were found using lexicon-based approach. The sentimental scores for aspects of fan responses were obtained by summarizing the sentimental terms in responses. The frequency of 'like' was also weighted in the sentimental score calculation. Three famous cell phone fan pages on Facebook were selected as demonstration cases to evaluate performances of the proposed methodology. Human judgment by several domain experts was also built for performance comparison. The performances of proposed approach were as good as those of human judgment on precision, recall and F1-measure.

Keywords: opinion mining, ontology, sentiment analysis, text mining

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Authors: Mugabe Nzarama Gabriel

Abstract:

In Rwanda, many healthcare organizations are still using a paper based patients’ data record system although it still present weaknesses to share health patients’ information across different services when necessary. In developed countries, the EHR has been put in place to revolutionize the paper based record system but still the EHR has some challenges related to privacy, security, or interoperability. The purpose of this research was to assess the existing patients’ data record system in healthcare sector in Rwanda, see what an EHR can improve to the system in place and assess the acceptance of EHR as system which is interoperable, very secure and interoperable and see whether stakeholders are ready to adopt the system. The case based methodology was used and TAM theoretical framework to design the questionnaire for the survey. A judgmental sample across two cases, CHUB and Hopital de Nemba, has been selected and SPSS has been used for descriptive statistics. After a qualitative analysis, the findings showed that the paper based record is useful, gives complete information about the patient, protects the privacy of patients but it is still less secure and less interoperable. The respondents shown that they are ready to use the proposed EHR System and want it secure, capable of enforcing the privacy but still they are not all ready for the interoperability. A conclusion has been formulated; recommendations and further research have been proposed.

Keywords: EHR system, healthcare service, TAM, privacy, interoperability

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Authors: Zhaoming Yang, Qi Xiang, Qian He, Michael Havbro Faber, Enrico Zio, Huai Su, Jinjun Zhang

Abstract:

Resilience is one of the key factors for system safety assessment and optimization, and resilience studies of natural gas pipeline systems (NGPS), especially in terms of process descriptions, are still being explored. Based on the three main stages, which are function loss process, recovery process, and waiting process, the paper has built functions and models which are according to the practical characteristics of NGPS and mainly analyzes the characteristics of deterministic interruptions. The resilience of NGPS also considers the threshold of the system function or users' satisfaction. The outcomes, which quantify the resilience of NGPS in different evaluation views, can be combined with the max flow and shortest path methods, help with the optimization of extra gas supplies and gas routes as well as pipeline maintenance strategies, the quick analysis of disturbance effects and the improvement of NGPS resilience evaluation accuracy.

Keywords: natural gas pipeline system, resilience, process modeling, deterministic disturbance

Procedia PDF Downloads 99

Authors: Jayanta K. Behera, Ashwini K. Sinha

Abstract:

The study has pointed out the relationship of energetic particle precipitation (EPP) during high speed solar wind streams (HSS) to the ionization characteristics and subsequent NOx production in the polar atmosphere. Over the last few decades, it has been shown that production of NOx in the mesosphere region during the precipitation of charged particles (with energy range >30 KeV to 1 MeV) is directly related to the ozone loss in the polar middle atmosphere, extending from mesosphere to upper stratosphere. This study has dealt with the analysis of the interplanetary parameters such as interplanetary magnetic field (IMF), solar wind velocity (Vs), charged particle density (Ns), convection field enhancement (Ec) during such HSS events and their link to the rate of production of NOx in the mesosphere. Moreover, the analysis will be used to validate or, to modify the current ion-chemistry models which describe the ionization rate and NOx production in the polar atmosphere due to EPP.

Keywords: energetic particle precipitation (EPP), NOx, ozone depletion, polar vortex

Procedia PDF Downloads 436

Authors: Praniil Nagaraj

Abstract:

This paper proposes a method to collect homeless data using crowdsourcing and presents an approach to analyze the data, demonstrating its potential to strengthen existing and future policies aimed at promoting socio-economic equilibrium. The 2022 Annual Homeless Assessment Report (AHAR) to Congress highlighted alarming statistics, emphasizing the need for effective decision-making and budget allocation within local planning bodies known as Continuums of Care (CoC). This paper's contributions can be categorized into three main areas. Firstly, a unique method for collecting homeless data is introduced, utilizing a user-friendly smartphone app (currently available for Android). The app enables the general public to quickly record information about homeless individuals, including the number of people and details about their living conditions. The collected data, including date, time, and location, is anonymized and securely transmitted to the cloud. It is anticipated that an increasing number of users motivated to contribute to society will adopt the app, thus expanding the data collection efforts. Duplicate data is addressed through simple classification methods, and historical data is utilized to fill in missing information. The second contribution of this paper is the description of data analysis techniques applied to the collected data. By combining this new data with existing information, statistical regression analysis is employed to gain insights into various aspects, such as distinguishing between unsheltered and sheltered homeless populations, as well as examining their correlation with factors like unemployment rates, housing affordability, and labor demand. Initial data is collected in San Francisco, while pre-existing information is drawn from three cities: San Francisco, New York City, and Washington D.C., facilitating the conduction of simulations. The third contribution focuses on demonstrating the practical implications of the data processing results. The challenges faced by key stakeholders, including charitable organizations and local city governments, are taken into consideration. Two case studies are presented as examples. The first case study explores improving the efficiency of food and necessities distribution, as well as medical assistance, driven by charitable organizations. The second case study examines the correlation between micro-geographic budget expenditure by local city governments and homeless information to justify budget allocation and expenditures. The ultimate objective of this endeavor is to enable the continuous enhancement of the quality of life for the underprivileged. It is hoped that through increased crowdsourcing of data from the public, the Generosity Curve and the Need Curve will intersect, leading to a better world for all.

Keywords: crowdsourcing, homelessness, socio-economic policies, statistical analysis

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Authors: Jeong-Hwan Choi, Hyo-Sang Park, Tae-Hyung Lee

Abstract:

The transmission tower is one of the crucial lifeline structures in a modern society, and it needs to be protected against extreme loading conditions. However, the transmission tower is a very complex structure and, therefore, it is very difficult to simulate the actual damage and the collapse behavior of the tower structure. In this study, the actual collapse behavior of the transmission tower due to lateral loading conditions such as wind load is evaluated through the computational simulation. For that, a progressive collapse procedure is applied to the simulation. In this procedure, after running the simulation, if a member of the tower structure fails, the failed member is removed and the simulation run again. The 154kV transmission tower is selected for this study. The simulation is performed by nonlinear static analysis procedure, namely pushover analysis, using OpenSEES, an earthquake simulation platform. Three-dimensional finite element models of those towers are developed.

Keywords: transmission tower, OpenSEES, pushover, progressive collapse

Procedia PDF Downloads 333