Search results for: subjective probability

Authors: Roza Afarin, Saeed Mozaffari

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The aim of this paper is image encryption using Genetic Algorithm (GA). The proposed encryption method consists of two phases. In modification phase, pixels locations are altered to reduce correlation among adjacent pixels. Then, pixels values are changed in the diffusion phase to encrypt the input image. Both phases are performed by GA with binary chromosomes. For modification phase, these binary patterns are generated by Local Binary Pattern (LBP) operator while for diffusion phase binary chromosomes are obtained by Bit Plane Slicing (BPS). Initial population in GA includes rows and columns of the input image. Instead of subjective selection of parents from this initial population, a random generator with predefined key is utilized. It is necessary to decrypt the coded image and reconstruct the initial input image. Fitness function is defined as average of transition from 0 to 1 in LBP image and histogram uniformity in modification and diffusion phases, respectively. Randomness of the encrypted image is measured by entropy, correlation coefficients and histogram analysis. Experimental results show that the proposed method is fast enough and can be used effectively for image encryption.

Keywords: correlation coefficients, genetic algorithm, image encryption, image entropy

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Authors: Eunice Oluwakemi Chukwuma-Nwuba

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Nigeria is a developing country with an increasing rate of graduate unemployment. This has triggered successive government administrations to promote the variety of programmes to address the situation. However, none of these efforts yielded the desired outcome. Accordingly, in 2006 the government included entrepreneurship module in the curriculum of universities as a compulsory general programme for all undergraduate courses. This is in the hope that the programme will help to promote entrepreneurial mind-set and new venture creation among graduates and as a result reduce the rate of graduate unemployment. The study explores the effectiveness of entrepreneurship education in promoting entrepreneurship. This study is significant in view of the endemic graduate unemployment in Nigeria and the social consequences such as youth restiveness and militancy. It is guided by the theory of planned behaviour. It employed the two-stage structural equation modelling (AMOS) to model entrepreneurial intentions as a function of innovative teaching methods, traditional teaching methods and culture Personal attitude and subjective norm are proposed to mediate the relationships between the exogenous and the endogenous variables. The first stage was tested using multi-group confirmatory factor analysis (MGCFA) framework to confirm that the two groups assign the same meaning to the scale items and to obtain goodness-of-fit indices. The multi-group confirmatory factor analysis included the tests of configural, metric and scalar invariance. With the attainment of full configural invariance and partial metric and scalar invariance, the second stage – the structural model was applied hypothesising that, the entrepreneurial intentions of graduates (respondents who have participated in the compulsory entrepreneurship programme) will be higher than those of undergraduates (respondents who are yet to participate in the programme). The study uses the quasi-experimental design. The samples comprised 409 graduates (experimental group) and 402 undergraduates (control group) from six federal universities in Nigeria. Our findings suggest that personal attitude is positively related with entrepreneurial intentions, largely confirming prior literature. However, unlike previous studies, our results indicate that subjective norm has significant direct and indirect impact on entrepreneurial intentions indicating that reference people of the participants have important roles to play in their decision to be entrepreneurial. Furthermore, unlike the assertions in prior studies, the result suggests that traditional teaching methods have indirect effect on entrepreneurial intentions supporting that since personal characteristics can change in an educational situation, an education purposively directed at entrepreneurship might achieve similar results if not better. This study has implication for practice and theory. The research extends to the theoretical understanding of the formation of entrepreneurial intentions and explains the role of the reference others in relation to how graduates perceive entrepreneurship. Further, the study adds to the body of knowledge on entrepreneurship education in Nigeria universities and provides a developing country perspective. It proposes further research in the exploration of entrepreneurship education and entrepreneurial intentions of graduates from across the country’s universities as necessary and imperative.

Keywords: entrepreneurship education, entrepreneurial intention, structural equation modeling, theory of planned behaviour

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Authors: Preeda Sansakorn, Min An

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In order to be capable of dealing with uncertainties, subjectivities, including vagueness arising in building construction projects, the application of fuzzy reasoning technique based on fuzzy set theory is proposed. This study contributes significantly to the development of a fuzzy reasoning safety risk assessment model for building construction projects that could be employed to assess the risk magnitude of each hazardous event identified during construction, and a third parameter of probability of consequence is incorporated in the model. By using the proposed safety risk analysis methodology, more reliable and less ambiguities, which provide the safety risk management project team for decision-making purposes.

Keywords: safety risk assessment, building construction safety, fuzzy reasoning, construction risk assessment model, building construction projects

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Authors: Li Zhou, Yanmei Fang

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With current technology, images and videos can be obtained more easily than ever. It is so easy to manipulate these digital multimedia information when obtained, and that the content or source of the image and video could be easily tampered. In this paper, we propose to identify the image and video frame by the texture-based approach, e.g. Markov Transition Probability (MTP), which is in space domain, DCT domain and DWT domain, respectively. In the experiment, image and video frame database is constructed, and is used to train and test the classifier Support Vector Machine (SVM). Experiment results show that the texture-based approach has good performance. In order to verify the experiment result, and testify the universality and robustness of algorithm, we build a random testing dataset, the random testing result is in keeping with above experiment.

Keywords: multimedia forensics, video frame, LBP, MTP, SVM

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Authors: Rik van Leeuwen, Ger Koole

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Within hospitality, marketing departments use segmentation to create tailored strategies to ensure personalized marketing. This study provides a data-driven approach by segmenting guest profiles via hierarchical clustering based on an extensive set of features. The industry requires understandable outcomes that contribute to adaptability for marketing departments to make data-driven decisions and ultimately driving profit. A marketing department specified a business question that guides the unsupervised machine learning algorithm. Features of guests change over time; therefore, there is a probability that guests transition from one segment to another. The purpose of the study is to provide steps in the process from raw data to actionable insights, which serve as a guideline for how hospitality companies can adopt an algorithmic approach.

Keywords: hierarchical cluster analysis, hospitality, market segmentation

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Authors: Su-Ping Liu, Yue Tian, Yifan Shen

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This study investigates the effect of corporate governance on earnings management when firms have reported a long stream of earnings increases (hereafter referred to as earnings beaters). We expect that good quality of corporate governance decreases the probability of income-increasing earnings management. We employ transparent tools to capture firms’ opportunistic management behavior, specifically, the repurchase of stock. In addition, we use corporate governance proxies to measure the degree of corporate governance, including board size, board independence, CEO duality, and the frequency of meeting. The results hold after the controlling of variables that suggested in prior literature. We expect that the simple technique, that is, firms’ degree of corporate governance, to be used as an inexpensive first step in detecting earnings management.

Keywords: corporate governance, earnings management, earnings patterns, stock repurchase

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Authors: Nulu Nanono

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Background: The Ugandan national health policy and the national population policy all recognize the need to increase access to quality, affordable, acceptable and sustainable contraceptive services for all people but provision and utilization of quality services remains low. Two contraceptive methods are categorized as long-acting temporary methods: intrauterine contraceptive devices (IUCDs) and implants. Copper-containing IUCDs, generally available in Ministry of Health (MoH) family planning programs and is effective for at least 12 years while Implants, depending on the type, last for up to three to seven years. Uganda’s current policy and political environment are favorable towards achieving national access to quality and safe contraceptives for all people as evidenced by increasing government commitments and innovative family planning programs. Despite the increase of modern contraception use from 14% to 26%, long acting reversible contraceptive (LARC) utilization has relatively remained low with less than 5% using IUDs & Implants which in a way explains Uganda’s persistent high fertility rates. Main question/hypothesis: The purpose of the study was to examine relationship between the demographic, socio-economic characteristics of women, health facility factors and long acting reversible contraception utilization. Methodology: LARC utilization was investigated comprising of the two questions namely are you or your partner currently doing something or using any method to delay or avoid getting pregnant? And which method or methods are you using? Data for the study was sourced from the 2016 Uganda Performance Monitoring and Accountability 2020 Survey comprising of 3816 female respondents aged 15 to 49 years. The analysis was done using the Chi-squared tests and the probit regression at bivariate and multivariate levels respectively. The model was further tested for validity and normality of the residuals using the Sharipo wilks test and test for kurtosis and skewness. Results: The results showed the model the age, parity, marital status, region, knowledge of LARCs, availability of LARCs to be significantly associated with long acting contraceptive utilization with p value of less than 0.05. At the multivariate analysis level, women who had higher parities (0.000) tertiary education (0.013), no knowledge about LARCs (0.006) increases their probability of using LARCs. Furthermore while women age 45-49, those who live in the eastern region reduces their probability of using LARCs. Knowledge contribution: The findings of this study join the debate of prior research in this field and add to the body of knowledge related to long acting reversible contraception. An outstanding and queer finding from the study is the non-utilization of LARCs by women who are aware and have knowledge about them, this may be an opportunity for further research to investigate the attribution to this.

Keywords: contraception, long acting, utilization, women (15-49)

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Authors: Minghui Zhang, Sirine Fkaier, Sabri Fernana, Svetlana Kiseleva, Denis Kiselev

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The real-time identification of bacteria and fungi is difficult because they emit much weaker signals than pollen. In 2020, Plair developed Rapid-E+, which extends abilities of Rapid-E to detect smaller bioaerosols such as bacteria and fungal spores with diameters down to 0.3 µm, while keeping the similar or even better capability for measurements of large bioaerosols like pollen. Rapid-E+ enables simultaneous measurements of (1) time-resolved, polarization and angle dependent Mie scattering patterns, (2) fluorescence spectra resolved in 16 channels, and (3) fluorescence lifetime of individual particles. Moreover, (4) it provides 2D Mie scattering images which give the full information on particle morphology. The parameters of every single bioaerosol aspired into the instrument are subsequently analysed by machine learning. Firstly, pure species of microbes, e.g., Bacillus subtilis (a species of bacteria), and Penicillium chrysogenum (a species of fungal spores), were aerosolized in a bioaerosol chamber for Rapid-E+ training. Afterwards, we tested microbes under different concentrations. We used several steps of data analysis to classify and identify microbes. All single particles were analysed by the parameters of light scattering and fluorescence in the following steps. (1) They were treated with a smart filter block to get rid of non-microbes. (2) By classification algorithm, we verified the filtered particles were microbes based on the calibration data. (3) The probability threshold (defined by the user) step provides the probability of being microbes ranging from 0 to 100%. We demonstrate how Rapid-E+ identified simultaneously microbes based on the results of Bacillus subtilis (bacteria) and Penicillium chrysogenum (fungal spores). By using machine learning, Rapid-E+ achieved identification precision of 99% against the background. The further classification suggests the precision of 87% and 89% for Bacillus subtilis and Penicillium chrysogenum, respectively. The developed algorithm was subsequently used to evaluate the performance of microbe classification and quantification in real-time. The bacteria and fungi were aerosolized again in the chamber with different concentrations. Rapid-E+ can classify different types of microbes and then quantify them in real-time. Rapid-E+ enables classifying different types of microbes and quantifying them in real-time. Rapid-E+ can identify pollen down to species with similar or even better performance than the previous version (Rapid-E). Therefore, Rapid-E+ is an all-in-one instrument which classifies and quantifies not only pollen, but also bacteria and fungi. Based on the machine learning platform, the user can further develop proprietary algorithms for specific microbes (e.g., virus aerosols) and other aerosols (e.g., combustion-related particles that contain polycyclic aromatic hydrocarbons).

Keywords: bioaerosols, laser-induced fluorescence, Mie-scattering, microorganisms

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Authors: Jiantao Weng, Yujie Zhao

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With the improvement of living quality and demand for nighttime activities in China, the current situation of outdoor lighting environment at night needs to be assessed. Lighting environment at night plays an important role to guarantee night safety. Two typical residential communities in Hangzhou were selected. A comprehensive test method of outdoor lighting environment at night was established. The road, fitness area, landscape, playground and entrance were included. Field measurements and questionnaires were conducted in these two residential communities. The characteristics of residents’ habits and the subjective evaluation on different aspects of outdoor lighting environment at night were collected via questionnaire. A safety evaluation system on the outdoor lighting environment at night in the residential community was established. The results show that there is a big difference in illumination in different areas. The lighting uniformities of roads cannot meet the requirement of lighting standard in China. Residents pay more attention to the lighting environment of the fitness area and road than others. This study can provide guidance for the design and management of outdoor lighting environment at night.

Keywords: residential community, lighting environment, night, field measurement

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Authors: Alexander K. Guo

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PM2.5 poses a large threat to people’s health and the environment and is an issue of large concern in Beijing, brought to the attention of the government by the media. In addition, both the United States Embassy in Beijing and the government of China have increased monitoring of PM2.5 in recent years, and have made real-time data available to the public. This report utilizes hourly historical data (2008-2016) from the U.S. Embassy in Beijing for the first time. The first objective was to attempt to fit probability distributions to the data to better predict a number of days exceeding the standard, and the second was to uncover any yearly, seasonal, monthly, daily, and hourly patterns and trends that may arise to better understand of air control policy. In these data, 66,650 hours and 2687 days provided valid data. Lognormal, gamma, and Weibull distributions were fit to the data through an estimation of parameters. The Chi-squared test was employed to compare the actual data with the fitted distributions. The data were used to uncover trends, patterns, and improvements in PM2.5 concentration over the period of time with valid data in addition to specific periods of time that received large amounts of media attention, analyzed to gain a better understanding of causes of air pollution. The data show a clear indication that Beijing’s air quality is unhealthy, with an average of 94.07µg/m3 across all 66,650 hours with valid data. It was found that no distribution fit the entire dataset of all 2687 days well, but each of the three above distribution types was optimal in at least one of the yearly data sets, with the lognormal distribution found to fit recent years better. An improvement in air quality beginning in 2014 was discovered, with the first five months of 2016 reporting an average PM2.5 concentration that is 23.8% lower than the average of the same period in all years, perhaps the result of various new pollution-control policies. It was also found that the winter and fall months contained more days in both good and extremely polluted categories, leading to a higher average but a comparable median in these months. Additionally, the evening hours, especially in the winter, reported much higher PM2.5 concentrations than the afternoon hours, possibly due to the prohibition of trucks in the city in the daytime and the increased use of coal for heating in the colder months when residents are home in the evening. Lastly, through analysis of special intervals that attracted media attention for either unnaturally good or bad air quality, the government’s temporary pollution control measures, such as more intensive road-space rationing and factory closures, are shown to be effective. In summary, air quality in Beijing is improving steadily and do follow standard probability distributions to an extent, but still needs improvement. Analysis will be updated when new data become available.

Keywords: Beijing, distribution, patterns, pm2.5, trends

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Authors: Dorit Lemberger

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Wittgenstein directly used the term "metaphor" only infrequently and with reservations, but his writings include a number of metaphors that have become imprinted in the philosophical memory of Western thought. For example, the ladder in his book Tractatus, or in Philosophical investigations - the ancient city, the beetle in a box, the fly in the fly-bottle, and the duck-rabbit. In light of Wittgenstein's stressing, throughout his investigations, that the only language that exists is ordinary language, and that there is no "second-order" language, the question should be asked: How do these metaphors function, specifically, and in general, how are we to relate to language use that exceeds the normal? Wittgenstein did not disregard such phenomena, but he proposed viewing them in a different way, that would enable understanding them as uses in ordinary language, without necessarily exceeding such language. Two important terms that he coined in this context are "secondary sense" and "experience of meaning". Each denotes language use as reflective of a subjective element characteristic of the speaker, such as intent, experience, or emphasis of a certain aspect. More recent Wittgenstein scholars added the term "quasi-metaphor", that refers to his discussion of the possibility of aesthetic judgment. This paper will examine how, according to Wittgenstein, these terms function without exceeding ordinary language, and will illustrate how they can be applied, in an analysis of the poem "Butterfly" by Nelly Sachs.

Keywords: metaphor, quasi-metaphor, secondary sense, experience of meaning

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Authors: Rusne Kregzdaite, Erika Godlevska, Morta Vidunaite

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The main aim of this research is to explore existing methodologies for artists’ labour force and create artists’ socio-economic and creative conditions in an assessment model. Artists have dual aims in their creative working process: 1) income and 2) artistic self-expression. The valuation of their conditions takes into consideration both sides: the factors related to income and the satisfaction of the creative process and its result. The problem addressed in the study: tangible and intangible artists' criteria used for assessments creativity conditions. The proposed model includes objective factors (working time, income, etc.) and subjective factors (salary covering essential needs, self-satisfaction). Other intangible indicators are taken into account: the impact on the common culture, social values, and the possibility to receive awards, to represent the country in the international market. The empirical model consists of 59 separate indicators, grouped into eight categories. The deviation of each indicator from the general evaluation allows for identifying the strongest and the weakest components of artists’ conditions.

Keywords: artist conditions, artistic labour force, cultural policy, indicator, assessment model

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Authors: Gamith Mendis

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Even though the doctors are knowledgeable, there's a gap between knowing and being ethical. This is a barrier to establish an ethical doctor-patient relationship. Current health system has oriented in a way that gives a meaning to both the doctor and the patient through intermediate entities. For the doctor, the meaning of the doctor-patient relationship is given through the financial benefits, promotions, and social status. For the patient, the meaning is given through curing of the disease. It is obvious that both are independent entities between the doctor and the patient. As the philosophers like Husserl and Heidegger have pointed out, our subjective world will give the immediate meaningfulness to us. We should seek this immediate meaningfulness of the doctor-patient relationship. The present research has used the existential methodology as guided self-reflections on the lived experiences of a doctor and his students. In this approach, two important aspects have been understood. The first is, establishing the fact that being ethical is itself giving meaningfulness to the doctor’s being without any mediate entities. Simply, it is enjoying being an honest being. The second is by being-with-the-patient while treating the disease; both the doctor and the patient can enjoy the meaningfulness of their human relationship. The medical students and the doctors should focus on this meaningfulness. For that, this discussion should be actively incorporated into the medical curriculum with programs of practical guidance to medical students and should be discussed in patient-care reviews in the health setting within a satisfactory framework.

Keywords: doctor-patient relationship, medical education, medical ethics, medical humanities, qualitative health research

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Authors: HoYoung Son, Ki Young Kim, Woo Young Jung

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This study investigated the change of weir structure performances when durability of concrete, which is the main material of weir structure, decreased due to their aging by mean of seismic fragility analysis. In the analysis, it was assumed that the elastic modulus of concrete was reduced by 10% in order to account for their aged deterioration. Additionally, the analysis of seismic fragility was based on Monte Carlo Simulation method combined with a 2D nonlinear finite element in ABAQUS platform with the consideration of deterioration of concrete. Finally, the comparison of seismic fragility of model pre- and post-deterioration was made to study the performance of weir. Results show that the probability of failure in moderate damage for deteriorated model was found to be larger than pre-deterioration model when peak ground acceleration (PGA) passed 0.4 g.

Keywords: weir, FEM, concrete, fragility, aging

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Authors: Kimaya Subhash Gaikwad, S. B. Waykar

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The mobile ad-hoc network (MANET) is collection of various types of nodes. In MANET various protocols are used for communication. In OLSR protocol, a node is selected as multipoint relay (MPR) node which broadcast the messages. As the MANET is open kind of network any malicious node can easily enter into the network and affect the performance of the network. The performance of network mainly depends on the components which are taking part into the communication. If the proper nodes are not selected for the communication then the probability of network being attacked is more. Therefore, it is important to select the more reliable and secure components in the network. MANET does not have any filtering so that only selected nodes can be used for communication. The openness of the MANET makes it easier to attack the communication. The most of the attack are on the Quality of service (QoS) of the network. This paper gives the overview of the various attacks that are possible on OLSR protocol and some solutions. The papers focus mainly on the OLSR protocol.

Keywords: communication, MANET, OLSR, QoS

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Authors: Mohsen Khaledian, Razali Ismail, Mehdi Saeidmanesh, Mahdiar Hosseinghadiry

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A semi-analytical model for impact ionization coefficient of graphene nanoribbon (GNR) is presented. The model is derived by calculating probability of electrons reaching ionization threshold energy Et and the distance traveled by electron gaining Et. In addition, ionization threshold energy is semi-analytically modeled for GNR. We justify our assumptions using analytic modeling and comparison with simulation results. Gaussian simulator together with analytical modeling is used in order to calculate ionization threshold energy and Kinetic Monte Carlo is employed to calculate ionization coefficient and verify the analytical results. Finally, the profile of ionization is presented using the proposed models and simulation and the results are compared with that of silicon.

Keywords: nanostructures, electronic transport, semiconductor modeling, systems engineering

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Authors: Samira Hamiditehrani

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Automated vehicles (AVs) are emerging technologies that could potentially offer a wide range of opportunities and challenges for the transportation sector. The advent of AV technology has also resulted in new business models in shared mobility services where many ride hailing and car sharing companies are developing on-demand AVs including shared automated vehicles (SAVs) and pooled automated vehicles (Pooled AVs). SAVs and Pooled AVs could provide alternative shared mobility services which encourage sustainable transport systems, mitigate traffic congestion, and reduce automobile dependency. However, the success of on-demand AVs in addressing major transportation policy issues depends on whether and how the public adopts them as regular travel modes. To identify conditions under which individuals may adopt on-demand AVs, previous studies have applied human behavior and technology acceptance theories, where Theory of Planned Behavior (TPB) has been validated and is among the most tested in on-demand AV research. In this respect, this study has three objectives: (a) to propose and validate a theoretical model for behavioral intention to use SAVs and Pooled AVs by extending the original TPB model; (b) to identify the characteristics of early adopters of SAVs, who prefer to have a shorter and private ride, versus prospective users of Pooled AVs, who choose more affordable but longer and shared trips; and (c) to investigate Canadians’ intentions to adopt on-demand AVs for regular trips. Toward this end, this study uses data from an online survey (n = 3,622) of workers or adult students (18 to 75 years old) conducted in October and November 2021 for six major Canadian metropolitan areas: Toronto, Vancouver, Ottawa, Montreal, Calgary, and Hamilton. To accomplish the goals of this study, a base bivariate ordered probit model, in which both SAV and Pooled AV adoptions are estimated as ordered dependent variables, alongside a full structural equation modeling (SEM) system are estimated. The findings of this study indicate that affective motivations such as attitude towards AV technology, perceived privacy, and subjective norms, matter more than sociodemographic and travel behavior characteristic in adopting on-demand AVs. Also, the results of second objective provide evidence that although there are a few affective motivations, such as subjective norms and having ample knowledge, that are common between early adopters of SAVs and PooledAVs, many examined motivations differ among SAV and Pooled AV adoption factors. In other words, motivations influencing intention to use on-demand AVs differ among the service types. Likewise, depending on the types of on-demand AVs, the sociodemographic characteristics of early adopters differ significantly. In general, findings paint a complex picture with respect to the application of constructs from common technology adoption models to the study of on-demand AVs. Findings from the final objective suggest that policymakers, planners, the vehicle and technology industries, and the public at large should moderate their expectations that on-demand AVs may suddenly transform the entire transportation sector. Instead, this study suggests that SAVs and Pooled AVs (when they entire the Canadian market) are likely to be adopted as supplementary mobility tools rather than substitutions for current travel modes

Keywords: automated vehicles, Canadian perception, theory of planned behavior, on-demand AVs

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Authors: Bander Alzahrani, Mohammed Alreshoodi

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Information-centric networking (ICN) using architectures such as the Publish-Subscribe Internet Technology (PURSUIT) has been proposed as a new networking model that aims at replacing the current used end-centric networking model of the Internet. This emerged model focuses on what is being exchanged rather than which network entities are exchanging information, which gives the control plane functions such as routing and host location the ability to be specified according to the content items. The forwarding plane of the PURSUIT ICN architecture uses a simple and light mechanism based on Bloom filter technologies to forward the packets. Although this forwarding scheme solve many problems of the today’s Internet such as the growth of the routing table and the scalability issues, it is vulnerable to brute force attacks which are starting point to distributed- denial-of-service (DDoS) attacks. In this work, we design and analyze a novel source-routing and information delivery technique that keeps the simplicity of using Bloom filter-based forwarding while being able to deter different attacks such as denial of service attacks at the ingress of the network. To achieve this, special forwarding nodes called Edge-FW are directly attached to end user nodes and used to perform a security test for malicious injected random packets at the ingress of the path to prevent any possible attack brute force attacks at early stage. In this technique, a core entity of the PURSUIT ICN architecture called topology manager, that is responsible for finding shortest path and creating a forwarding identifiers (FId), uses a cryptographically secure hash function to create a 64-bit hash, h, over the formed FId for authentication purpose to be included in the packet. Our proposal restricts the attacker from injecting packets carrying random FIds with a high amount of filling factor ρ, by optimizing and reducing the maximum allowed filling factor ρm in the network. We optimize the FId to the minimum possible filling factor where ρ ≤ ρm, while it supports longer delivery trees, so the network scalability is not affected by the chosen ρm. With this scheme, the filling factor of any legitimate FId never exceeds the ρm while the filling factor of illegitimate FIds cannot exceed the chosen small value of ρm. Therefore, injecting a packet containing an FId with a large value of filling factor, to achieve higher attack probability, is not possible anymore. The preliminary analysis of this proposal indicates that with the designed scheme, the forwarding function can detect and prevent malicious activities such DDoS attacks at early stage and with very high probability.

Keywords: forwarding identifier, filling factor, information centric network, topology manager

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Authors: Sibo Lu, Zhongkai Qian

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This study endeavors to articulate a spectrum of capitalist transformation from a politico-economic perspective, categorizing the development of capitalism into pre-modern, modern, and post-modern stages while examining the transitions between these states. It critically engages with the concepts of pre-modernity, modernity, and post-modernity, typically aligned with cultural studies, to shed light on their objective changes in the politico-economic realm. Post-modernity, in this context, is associated with the transition to high-value-added services and economic growth in ‘developed’ countries amidst globalization, framing a ‘neoliberal’ economic transformation. The paper scrutinizes the neoliberal economic shifts in the latter half of the 20th century as part of the post-modern state, arguing against viewing post-modernity merely as a cultural or subjective interpretative stance. Instead, it is posited as a concrete politico-economic phase marked by the dominance of post-Fordist systems. Through integrating insights from the political economy with continental philosophy, this research provides a nuanced analysis of capitalism's evolution, challenging conventional class analyses under the capitalist system and fostering a broader understanding of socio-economic paradigms.

Keywords: post marxism, critical theory, political economy, capitalism transformation

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Authors: Asowata Osamede, Trudy Sutherland

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The purpose of this paper is to assess the available power from a Renewable Energy Source (off-grid photovoltaic (PV) panel) in the Southern Hemisphere using anisotropic model. Direct solar radiation is the driving force in photovoltaics. In a basic PV panels in the Southern Hemisphere, Power conversion is eminent, and this is achieved by the PV cells converting solar energy into electrical energy. In this research, the results was determined for a 6 month period from September 2022 through February 2023. Preliminary results, which include Normal Probability plot, data analysis - R2 value, effective conversion-time per week and work-time per day, indicate a favorably comparison between the empirical results and the simulation results.

Keywords: power-conversion, mathematical model, PV panels, DC-DC converters, direct solar radiation

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Authors: Asma Ben Yaghlane, Mohamed Naceur Azaiez, Mehdi Mrad

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We investigate the large scale of networks in the context of network survivability under attack. We use appropriate techniques to evaluate and the attacker-based- and the defender-based-network survivability. The attacker is unaware of the operated links by the defender. Each attacked link has some pre-specified probability to be disconnected. The defender choice is so that to maximize the chance of successfully sending the flow to the destination node. The attacker however will select the cut-set with the highest chance to be disabled in order to partition the network. Moreover, we extend the problem to the case of selecting the best p paths to operate by the defender and the best k cut-sets to target by the attacker, for arbitrary integers p,k > 1. We investigate some variations of the problem and suggest polynomial-time solutions.

Keywords: defense/attack strategies, large scale, networks, partitioning a network

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Authors: Babar Khan, Wang Zhijie

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Machine Vision has been playing a significant role in Industrial Automation, to imitate the wide variety of human functions, providing improved safety, reduced labour cost, the elimination of human error and/or subjective judgments, and the creation of timely statistical product data. Despite the intensive research, there have not been any attempts to classify fabric prints based on printed texture and colour, most of the researches so far encompasses only black and white or grey scale images. We proposed a biologically inspired processing architecture to classify fabrics w.r.t. the fabric print texture and colour. We created a texture descriptor based on the HMAX model for machine vision, and incorporated colour descriptor based on opponent colour channels simulating the single opponent and double opponent neuronal function of the brain. We found that our algorithm not only outperformed the original HMAX algorithm on classification of fabric print texture and colour, but we also achieved a recognition accuracy of 85-100% on different colour and different texture fabric.

Keywords: automatic classification, texture descriptor, colour descriptor, opponent colour channel

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Authors: Saeed Yazdani, F. Nekoofar

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Considering the importance and scarcity of water resources, the efficient management of water resources is of great importance. In the agriculture sector, farmers are facilitated with various practices and technologies to encounter water insufficiency. This study aims to assess socio-economic factors affecting the application of water-saving technologies. A Logit method was employed to examine the impact of different variables on the use of water-saving technology. The required data was gathered from a sample of 204 farmers in 2021 in Alborz Province in Iran. The results indicate that different variables such as crop price variability, water sources, farm size, income, education, experience, membership in cooperatives have positive effects, and variables such as age and number of plots have negative effects on the probability of applying modern water-saving technologies.

Keywords: socio-economics, water, irrigation, water saving technologies, scarcity

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Authors: Arunee Wongkhao, Suparat Niwitpong, Sa-aat Niwitpong

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In this paper, we propose two new confidence intervals for the difference between the inverse of normal means with known coefficients of variation. One of these two confidence intervals for this problem is constructed based on the generalized confidence interval and the other confidence interval is constructed based on the closed form method of variance estimation. We examine the performance of these confidence intervals in terms of coverage probabilities and expected lengths via Monte Carlo simulation.

Keywords: coverage probability, expected length, inverse of normal mean, coefficient of variation, generalized confidence interval, closed form method of variance estimation

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Authors: Zhi Liu, Xian Peng, Monika Domanska, Lingyun Kang, Sannyuya Liu

Abstract:

Massive Open education has become increasingly popular among worldwide learners. An increasing number of course reviews are being generated in Massive Open Online Course (MOOC) platform, which offers an interactive feedback channel for learners to express opinions and feelings in learning. These reviews typically contain subjective emotion and topic information towards the courses. However, it is time-consuming to artificially detect these opinions. In this paper, we propose an emotion-oriented topic detection model to automatically detect the students’ opinioned aspects in course reviews. The known overall emotion orientation and emotional words in each review are used to guide the joint probabilistic modeling of emotion and aspects in reviews. Through the experiment on real-life review data, it is verified that the distribution of course-emotion-aspect can be calculated to capture the most significant opinioned topics in each course unit. This proposed technique helps in conducting intelligent learning analytics for teachers to improve pedagogies and for developers to promote user experiences.

Keywords: Massive Open Online Course (MOOC), course reviews, topic model, emotion recognition, topical aspects

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Authors: Patricia Silva, Iolanda Costa Galinha, Cristina Costa-Lobo

Abstract:

The present research aims to evaluate, in the context of formal learning, the influence of affections, through subjective well-being, as well as the influence of personality, in the metacognition levels. There are few studies that analyze the influence of affection and personality on metacognition. The sample of this study consists of 300 Portuguese adolescents, male and female, aged between 15 and 17 years. The main variables of this study are affections, personality, ascertained through neuroticism and extraversion, and metacognition, namely the knowledge of cognition and the regulation of cognition. Initially, the sociodemographic questionnaire was constructed and administered to characterize the sample in its variables. To evaluate the affective experience in adolescents was administered PANAS-N, that is a measure of self-assessment of positive and negative affectivity in children and adolescents. To evaluate the personality, in its variables extroversion and neuroticism, the NEO-FFI was applied. The Metacognitive Awareness Inventory, MAI, was used to assess knowledge of cognition and regulation of cognition. The data analysis was performed using the statistical software IBM SPSS 22.0. After analyzing and discussing the results, a set of theoretical interdisciplinary reflection, between the sciences of education and psychology, is concretized, contributing to the reflection on psychoeducational intervention, opening the way for future studies.

Keywords: affections, personality, metacognition, psychoeducational intervention

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Authors: Sabah Mohammed, Jinan Fiaidhi, Darien Sawyer

Abstract:

Describing clinical cases according to a clinical charting standard that enforces interoperability and enables connected care services can save lives in the event of a medical emergency or provide efficient and effective interventions for the benefit of the patients through the integration of bedside and bench side clinical research. This article presented a multi-tenant extension to the problem-oriented medical record that we have prototyped previously upon using the GraphQL Application Programming Interface to represent the notion of a problem list. Our implemented extension enables physicians and patients to collaboratively describe the patient case via using multi chatbots to collaboratively describe the patient case using the SOAP charting standard. Our extension also connects the described SOAP patient case with the HL7 FHIR (Health Interoperability Resources) medical record for connecting the patient case to the bench data.

Keywords: problem-oriented medical record, graphQL, chatbots, SOAP

Procedia PDF Downloads 91

Authors: Eric Mensah, Carlos Mensah

Abstract:

The road maintenance backlogs created as a result of deferred maintenance especially in developing countries has caused considerable deterioration of many road assets. This is usually due to difficulties encountered in selecting and prioritising maintainable roads based on objective criteria rather than some political or other less important criteria. In order to ensure judicious use of limited resources for road maintenance, five factors were identified as the most important criteria for road management within the study area. This was based on the judgements of 40 experts. The results were further used to develop weightings using the Multi-Criteria Decision Process (MCDP) to analyse and select road alternatives according to maintenance goal. Using Geographical Information Systems (GIS), maintainable roads were grouped using the Jenk’s natural breaks to allow for further prioritised in order of importance for display on a dashboard of maps, charts, and tables. This reduces the problems of subjective maintenance and road selections, thereby reducing wastage of resources and easing the maintenance process through an object organised spatial decision support system.

Keywords: decision support, geographical information systems, multi-criteria decision process, weighted sum

Procedia PDF Downloads 376

Authors: Dingyang Hu, Dan Liu

Abstract:

DNN (Deep Neural Network) deep learning models are widely used in classification, prediction, and other task scenarios. To address the difficulties of generic adversarial perturbation generation for deep learning models under black-box conditions, a generic adversarial ingestion generation method based on a saliency map (CJsp) is proposed to obtain salient image regions by counting the factors that influence the input features of an image on the output results. This method can be understood as a saliency map attack algorithm to obtain false classification results by reducing the weights of salient feature points. Experiments also demonstrate that this method can obtain a high success rate of migration attacks and is a batch adversarial sample generation method.

Keywords: adversarial sample, gradient, probability, black box

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Authors: Zhongfei Cai, Hui He, Changsheng Li

Abstract:

This paper studied in the automatic repeat request (ARQ) transmission technique in Mars detection telecommunications system. An ARQ method applied to proximity-1 space link protocol was proposed by this paper. In order to ensure the efficiency of data reliable transmission, this ARQ method combined these different ARQ maneuvers characteristics. Considering the Mars detection communication environments, this paper analyzed the characteristics of the saturation throughput rate, packet dropping probability, average delay and energy efficiency with different ARQ algorithms. Combined thus results with the theories of ARQ transmission technique, an ARQ transmission project in Mars detection telecommunications system was established. The simulation results showed that this algorithm had excellent saturation throughput rate and energy efficiency with low complexity.

Keywords: ARQ, mars, CCSDS, proximity-1, deepspace

Procedia PDF Downloads 340