Search results for: collective animal behavior algorithm

Authors: Christian Angerer, Markus Lienkamp

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Electric vehicles offer a high variety of possible drivetrain topologies with up to 4 motors. Multi-motor-designs can have several advantages regarding traction, vehicle dynamics, safety and even efficiency. With a rising number of motors, the whole drivetrain becomes more complex. All permutations of gearings, drivetrain-layouts, motor-types and –sizes lead up in a very large solution space. Single elements of this solution space can be analyzed by simulation methods. In addition to longitudinal vehicle behavior, which most optimization-approaches are restricted to, also lateral dynamics are important for vehicle dynamics, stability and efficiency. In order to compete large solution spaces and to find an optimal result, genetic algorithm based optimization is state-of-the-art. As lateral dynamics simulation is way more CPU-intensive, optimization takes much more time than in case of longitudinal-only simulation. Therefore, this paper shows an approach how to create meta-models from a 14-degree of freedom vehicle model in order to enable a numerically efficient drivetrain-layout optimization process under consideration of lateral dynamics. Different meta-modelling approaches such as neural networks or DoE are implemented and comparatively discussed.

Keywords: driving dynamics, drivetrain layout, genetic optimization, meta-modeling, lateral dynamicx

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Authors: María Eugenia Peltzer, María Estela Rodríguez

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This work presents an approach to the cultural aspects of the Immigrants as part of the Cultural Intangible Heritage of Argentina. The intangible cultural heritage consists of the manifestations, practices, uses, representations, expressions, knowledge, techniques and cultural spaces that communities and groups recognize as an integral part of their cultural heritage. This heritage generates feelings of identity and establishes links with the collective memory, as well as being transmitted and recreated over time according to its environment, its interaction with nature and its history contributing to promote respect for cultural diversity and Human creativity. The Immigrants brings together those who came from other lands and their descendants, thus maintaining their traditions through time and linking the members of each cultural group with a strong sense of belonging through a communicative and effective process.

Keywords: cultural, immigration, memories, social

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Authors: Sven Tackenberg, Sönke Duckwitz, Andreas Petz, Christopher M. Schlick

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This paper introduces an extension to the well-established Resource-Constrained Project Scheduling Problem (RCPSP) to apply it to complex maintenance problems. The problem is to assign technicians to a team which has to process several tasks with multi-level skill requirements during a work shift. Here, several alternative activities for a task allow both, the temporal shift of activities or the reallocation of technicians and tools. As a result, switches from one valid work process variant to another can be considered and may be selected by the developed evolutionary algorithm based on the present skill level of technicians or the available tools. An additional complication of the observed scheduling problem is that the locations of the construction sites are only temporarily accessible during a day. Due to intensive rail traffic, the available time slots for maintenance and repair works are extremely short and are often distributed throughout the day. To identify efficient working periods, a first concept of a Bayesian network is introduced and is integrated into the extended RCPSP with pre-emptive and non-pre-emptive tasks. Thereby, the Bayesian network is used to calculate the probability of a maintenance task to be processed during a specific period of the shift. Focusing on the domain of maintenance of the railway infrastructure in metropolitan areas as the most unproductive implementation process at construction site, the paper illustrates how the extended RCPSP can be applied for maintenance planning support. A multi-criteria evolutionary algorithm with a problem representation is introduced which is capable of revising technician-task allocations, whereas the duration of the task may be stochastic. The approach uses a novel activity list representation to ensure easily describable and modifiable elements which can be converted into detailed shift schedules. Thereby, the main objective is to develop a shift plan which maximizes the utilization of each technician due to a minimization of the waiting times caused by rail traffic. The results of the already implemented core algorithm illustrate a fast convergence towards an optimal team composition for a shift, an efficient sequence of tasks and a high probability of the subsequent implementation due to the stochastic durations of the tasks. In the paper, the algorithm for the extended RCPSP is analyzed in experimental evaluation using real-world example problems with various size, resource complexity, tightness and so forth.

Keywords: maintenance management, scheduling, resource constrained project scheduling problem, genetic algorithms

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Authors: Mary Edokpa Fadal, Frances Agweda

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Considering the volatile and evolving nature of the political environment in the developing countries, it is important that the subject of effective leadership practices that focus on transformational and systematic political development and values be reviewed. If the attitude towards partisan politics and the played politics by political parties is relatively deviated from expected adherence to acceptance, safe, efficient and practical standard, the political parties will continue to struggle endlessly in an effort to maintain a system that works. The analysis is situated in the context of political parties and partisan political behavior in contemporary societies and developing nations. Recent research of empirical evidence shows that most of the political parties are more or less, not too active in playing their instrumental role in the political system, such as unifying, simplifying and stabilizing the political process. This is however traced to the problem of ethnic politics that have been dominated by tribalism. The rising clamor for political development needs re-structuring and correcting the abnormalities in the center of the polity to address the flaws in our political system. The paper argues that political parties and political actors are some of the vital instrument of attaining societal goals of democratic principles for peace and durability. Issues of ethnic and partisan politics are also discussed, as it relates to question pertaining to political ideologies. It is in the findings that this paper examines some of the issues that have been seen revolving the true practice of political parties and its activities towards the democratic trend of a society, that help to resolve questions surrounding the issues of politics and governance in developing countries. These issues are seen as an aberration that have characterized politics and political behavior especially in the aspect of transparency and fulfilling its purpose of existence. The paper argues that the transition of the developing nature of states largely depends on the political structures and party politics and the nature of constitutionalism following the democratic awakening. The paper concludes that politics and political behavior are all human factors that play a vital role in the development of contemporary societies. They drive the wheel of nations towards its goal attainment. This paper relies on documentary, primary sources of data collection and empirical analysis.

Keywords: development, ethnicity, partisan politics, political behavior, political parties

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Authors: Saad M. Darwish

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Recently, software quality issues have come to be seen as important subject as we see an enormous growth of agencies involved in software industries. However, these agencies cannot guarantee the quality of their products, thus leaving users in uncertainties. Software certification is the extension of quality by means that quality needs to be measured prior to certification granting process. This research participates in solving the problem of software assessment by proposing a model for assessment and certification of software product that uses a fuzzy inference engine to integrate both of process–driven and application-driven quality assurance strategies. The key idea of the on hand model is to improve the compactness and the interpretability of the model’s fuzzy rules via employing an ant colony optimization algorithm (ACO), which tries to find good rules description by dint of compound rules initially expressed with traditional single rules. The model has been tested by case study and the results have demonstrated feasibility and practicability of the model in a real environment.

Keywords: software quality, quality assurance, software certification model, software assessment

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Authors: Babak Nemat

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Background: Exercise behavior (EB) has a significant impact on infertility, but the magnitude of the effect is not easily determined. The aim of the present study was to assess the effect of social support and self-regulation, as external and internal factors, on changes in exercise behavior among infertile women. Methods: For a cross-sectional study conducted in Sanandaj (Iran) in 2023, we recruited infertile women (n=483) from 35 comprehensive healthcare centers by means of convenience sampling. Standardized face-to-face interviews were conducted using established and reliable instruments for the assessment of EB, social support, and self-regulation. Logistic regression models were applied to assess the association between EB, social support and self-regulation. Results: The majority of the participants (56.7%) had secondary infertility, while 70.8% of them did not perform any exercise. Self-regulation and social support were significantly higher in women with secondary infertility than in those with primary infertility (p < 0.01). Self-regulation was significantly lower in women whose height was below 160 centimeters (cm) (p<0.05). Social support was significantly higher among participants aged ≥ 35 years and weighing ≥ 60 kilograms (kg) (p < 0.01). The odds of EB adoption increased with self-regulation and social support (OR=1.05, 95% CI=1.02-1.09, p <0.01), (OR=1.06, 95% CI=1.02-1.11, p <0.01). Conclusion: Social support and self-regulation almost equally influenced EB in infertile women. Designing support and consultation programs can be considered in encouraging infertile women to exercise in future research.

Keywords: social support, regulation, infertility, women

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Authors: Daniela E. Marin, Cornelia Braicu, Gina C. Pistol, Roxana Cojocneanu-Petric, Ioana Berindan Neagoe, Mihail A. Gras, Ionelia Taranu

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Aristolochic acid (AA) is a carcinogenic, mutagenic, and nephrotoxic compound commonly found in the Aristolochiaceae family of plants. AA is frequently associated with urothelial carcinoma of the upper urinary tract in human and animals and is considered as being responsible for Balkan Endemic Nephropathy. The pig provides a good animal model because the porcine urological system is very similar to that of humans, both in aspects of physiology and anatomy. MicroRNA (miRNA) are small non-coding RNAs that have an impact on a wide range of biological processes by regulating gene expression at post-transcriptional level. The objective of this study was to analyze the miRNA profiling in the kidneys of AA intoxicated swine. For this purpose, ten TOPIGS-40 crossbred weaned piglets, 4-week-old, male and females with an initial average body weight of 9.83 ± 0.5 kg were studied for 28 days. They were given ad libitum access to water and feed and randomly allotted to one of the following groups: control group (C) or aristolochic acid group (AA). They were fed a maize-soybean-meal-based diet contaminated or not with 0.25mgAA/kg. To profile miRNA in the kidneys of pigs, microarrays and bioinformatics approaches were applied to analyze the miRNA in the kidney of control and AA intoxicated pigs. After normalization, our results have shown that a total of 5 known miRNAs and 4 novel miRNAs had different profiling in the kidney of intoxicated animals versus control ones. Expression of miR-32-5p, miR-497-5p, miR-423-3p, miR-218-5p, miR-128-3p were up-regulated by 0.25mgAA/kg feed, while the expression of miR-9793-5p, miR-9835-3p, miR-9840-3p, miR-4334-5p was down-regulated. The microRNA profiling in kidney of intoxicated animals was associated with modified expression of target genes as: RICTOR, LASP1, SFRP2, DKK2, BMI1, RAF1, IGF1R, MAP2K1, WEE1, HDGF, BCL2, EIF4E etc, involved in cell division cycle, apoptosis, cell differentiation and cell migration, cell signaling, cancer etc. In conclusion, this study provides new data concerning the microRNA profiling in kidney after aristolochic acid intoxications with important implications for human and animal health.

Keywords: aristolochic acid, kidney, microRNA, swine

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Authors: Vaibhav Singh Rajput, Ravi Kumar Jatoth, Nagu Bhookya, Bhasker Boda

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In this paper proportional, integral, derivative (PID) controller is used to control the pitch angle of the aircraft when the elevation angle is changed or modified. The pitch angle is dependent on elevation angle; a change in one corresponds to a change in the other. The PID controller helps in restricted change of pitch rate in response to the elevation angle. The PID controller is dependent on different parameters like Kp, Ki, Kd which change the pitch rate as they change. Various methodologies are used for changing those parameters for getting a perfect time response pitch angle, as desired or wished by a concerned person. While reckoning the values of those parameters, trial and guessing may prove to be futile in order to provide comfort to passengers. So, using some metaheuristic techniques can be useful in handling these errors. Hybrid GA-PSO is one such powerful algorithm which can improve transient and steady state response and can give us more reliable results for PID gain scheduling problem.

Keywords: pitch rate, elevation angle, PID controller, genetic algorithm, particle swarm optimization, phugoid

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Authors: Isabella Jabbour

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The world's population is expected to reach over 10 billion by 2050, creating a significant demand for food production, particularly in the agricultural industry. Cellular agriculture presents a solution to this challenge by producing meat that resembles traditionally produced meat, but with significantly less land use. Decellularized plant scaffolds, such as spinach leaves, have been shown to be a suitable edible scaffold for growing animal muscle, enabling cultured cells to grow and organize into three-dimensional structures that mimic the texture and flavor of conventionally produced meat. However, the use of freshwater to remove the intact extracellular material from these plants remains a concern, particularly when considering scaling up the production process. In this study, two protocols were used, 1X SDS and Boom Sauce, to decellularize spinach leaves with both distilled water and ocean water. The decellularization process was confirmed by histology, which showed an absence of cell nuclei, DNA and protein quantification. Results showed that spinach decellularized with ocean water contained 9.9 ± 1.4 ng DNA/mg tissue, which is comparable to the 9.2 ± 1.1 ng DNA/mg tissue obtained with DI water. These findings suggest that decellularized spinach leaves using ocean water hold promise as an eco-friendly and cost-effective scaffold for laboratory-grown meat production, which could ultimately transform the meat industry by providing a sustainable alternative to traditional animal farming practices while reducing freshwater use.

Keywords: cellular agriculture, plant scaffold, decellularization, ocean water usage

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Authors: M. Osipova

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Thanks to informational technologies development every sphere of economics is becoming more and more data-centralized as people are generating huge datasets containing information on any aspect of their life. Applying research of such data to human resources management allows getting scarce statistics on labor market state including salary expectations and potential employees’ typical career behavior, and this information can become a reliable basis for management decisions. The following article presents results of career behavior research based on freely accessible resume data. Information used for study is much wider than one usually uses in human resources surveys. That is why there is enough data for statistically significant results even for subgroups analysis.

Keywords: human resources management, salary expectations, statistics, turnover

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Authors: Maamar Ali Saud Al Tobi, Geraint Bevan, K. P. Ramachandran, Peter Wallace, David Harrison

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Centrifugal pumps are complex machines which can experience different types of fault. Condition monitoring can be used in centrifugal pump fault detection through vibration analysis for mechanical and hydraulic forces. Vibration analysis methods have the potential to be combined with artificial intelligence systems where an automatic diagnostic method can be approached. An automatic fault diagnosis approach could be a good option to minimize human error and to provide a precise machine fault classification. This work aims to introduce an approach to centrifugal pump fault diagnosis based on artificial intelligence and genetic algorithm systems. An overview of the future works, research methodology and proposed experimental setup is presented and discussed. The expected results and outcomes based on the experimental work are illustrated.

Keywords: centrifugal pump setup, vibration analysis, artificial intelligence, genetic algorithm

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Authors: Pui-Lai To, Yi-Jing Tsai

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As the advance of e-commerce technologies, the consumers buying behavior have changed. The focus on consumer buying behavior has already shifted from physical space to the cyberspace, which impulse buying is a major issue of concern. This study examines the stimulus effect of web environment on the consumer's emotional states, and in turn, affecting the urge of impulse buying based on a stimulus-organism-response (S-O-R) theory. Website ambiance and website service quality are the two stimulus variables. The study also explores the effects and the moderator effects of contextual variables and individual characteristic variables on the web environment, the emotional states and the urge of impulse buying. A total of 328 valid questionnaires were collected. Structural equation modeling was used to test the research hypothesis. This study found that both website ambiance and website service quality have a positive effect on consumer emotion, which in turn positively affect the urge of impulse buying. Consumer’s trait of impulse buying has a positive effect on the urge of impulse buying. Consumer’s hedonic motivation has a positive effect on both emotion state and the urge of impulse buying. On the other hand, the study found that money available for the consumer would positively affect consumer's emotion state and time available for the consumer would negatively affect the relationship between website service quality and consumer emotion. The result of this study validates Internet impulse buying behavior based on the S-O-R theory. This study also suggests that having a good website atmosphere and service quality is important to influencing consumers’ emotion and increasing the likelihood of consumer purchasing. The study could serve as a basis for the future research regarding online consumer behavior.

Keywords: emotion state, impulse buying, stimulus-organism-response, the urge of impulse buying

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Authors: Saul A. Torres Z., Eduardo Liceaga C., Alfredo Arias M.

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Agriculture in the world falls within the main sources of economic and global needs, so care of crop is extremely important for owners and workers; one of the major causes of loss of product is the pest infection of different types of organisms. We seek to develop a UAV for agricultural spraying at a maximum altitude of 5000 meters above sea level, with a payload of 100 liters of fumigant. For the developing the aerodynamic design of the aircraft is using computational tools such as the "Vortex Lattice Athena" software, "MATLAB"," ANSYS FLUENT"," XFoil " package among others. Also methods are being used structured programming, exhaustive analysis of optimization methods and search. The results have a very low margin of error, and the multi- objective problems can be helpful for future developments. The program has 10 functions developed in MATLAB, these functions are related to each other to enable the development of design, and all these functions are controlled by the principal code "Master.m".

Keywords: aerodynamics design, optimization, algorithm genetic, multi-objective problem, stability, vortex

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Authors: Alessandra Turini Bolsoni-Silva, Sonia Regina Loureiro

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It is important to evaluate such variables simultaneously and differentiating types of behavior problems: internalizing, externalizing and with comorbidity of internalizing and externalizing. The objective was to compare, correlate and predict teacher educational practices (educational social skills and negative practices) and children's behaviors (social skills and behavior problems) of children with internalizing, externalizing and combined internalizing and externalizing problems, controlling variables of child (gender and education). A total of 262 children were eligible to compose the participants, considering preschool age from 3 to 5 years old (n = 109) and school age from 6 to 11 (n = 153) years old, and their teachers who were distributed, in designs case-control, non-clinical, with internalizing, externalizing problems and internalizing and externalizing comorbidity, using the Teacher's Report Form (TRF) as a criterion. The instruments were applied with the teachers, after consent from the parents/guardians: a) Teacher’s Report Form (TRF); b) Educational Social Skills Interview Guide for Teachers (RE-HSE-Pr); (c) Socially Skilled Response Questionnaire – Teachers (QRSH-Pr). The data were treated by univariate and multivariate analyses, proceeding with comparisons, correlations and predictions regarding the outcomes of children with and without behavioral problems, considering the types of problems. As main results stand out: (a) group comparison studies: in the Inter group there is emphasis on behavior problems in affection interactions, which does not happen in the other groups; as for positive practices, they discriminate against groups with externalizing and combined problems and not in internalizing ones, positive educational practices – hse are more frequent in the G-Exter and G-Inter+Exter groups; negative practices differed only in the G-Exter and G-Inter+Exter groups; b) correlation studies: it can be seen that the Inter+Exter group presents a greater number of correlations in the relationship between behavioral problems/complaints and negative practices and between children's social skills and positive practices/contexts; c) prediction studies: children's social skills predict internalizing, externalizing and combined problems; it is also verified that the negative practices are in the multivariate model for the externalizing and combined ones. This investigation collaborates in the identification of risk and protective factors for specific problems, helping in interventions for different problems.

Keywords: development, educational practices, social skills, behavior problems, teacher

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Authors: Vojtěch Svěrák

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Climate change ethics have recently shifted away from individualistic paradigms towards concepts of shared or collective responsibility. Despite this evolving trend, a noticeable gap remains: a lack of research exclusively addressing the moral responsibility of specific unorganized social groups. The primary objective of the article is to fill this gap. The article employs the structuralist methodological approach proposed by some feminist philosophers, utilizing structural analysis to explain the existence of social groups. The argument is made for the integration of this framework with the so-called forward-looking Social Connection Model (SCM) of responsibility, which ascribes responsibilities to individuals based on their participation in social structures. The article offers an extension of this model to justify the responsibility of unorganized social groups. The major finding of the study is that although members of unorganized groups are loosely connected, collectively they instantiate specific external social structures, share social positioning, and the notion of responsibility could be based on that. Specifically, if the structure produces harm or perpetuates injustices, and the group both benefits from and possesses the capacity to significantly influence the structure, a greater degree of responsibility should be attributed to the group as a whole. This thesis is applied and justified within the context of climate change, based on the asymmetrical positioning of different social groups. Climate change creates a triple inequality: in contribution, vulnerability, and mitigation. The study posits that different degrees of group responsibility could be drawn from these inequalities. Two social groups serve as a case study for the article: first, the Pakistan lower class, consisting of people living below the national poverty line, with a low greenhouse gas emissions rate, severe climate change-related vulnerability due to the lack of adaptation measures, and with very limited options to participate in the mitigation of climate change. Second, the so-called polluter elite, defined by members' investments in polluting companies and high-carbon lifestyles, thus with an interest in the continuation of structures leading to climate change. The first identified group cannot be held responsible for climate change, but their group interest lies in structural change and should be collectively maintained. On the other hand, the responsibility of the second identified group is significant and can be fulfilled by a justified demand for some political changes. The proposed approach of group responsibility is suggested to help navigate climate justice discourse and environmental policies, thus helping with the sustainability transition.

Keywords: collective responsibility, climate justice, climate change ethics, group responsibility, social ontology, structural analysis

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Authors: Hiesik Kim, YongBeum Kim

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Internet of Things (IoT) applications are widely serviced and spread worldwide. Local wireless data transmission technique must be developed to speed up with some technique. Bluetooth wireless data communication is wireless technique is technique made by Special Inter Group(SIG) using the frequency range 2.4 GHz, and it is exploiting Frequency Hopping to avoid collision with different device. To implement experiment, equipment for experiment transmitting measured data is made by using Arduino as Open source hardware, Gas sensor, and Bluetooth Module and algorithm controlling transmission speed is demonstrated. Experiment controlling transmission speed also is progressed by developing Android Application receiving measured data, and controlling this speed is available at the experiment result. it is important that in the future, improvement for communication algorithm be needed because few error occurs when data is transferred or received.

Keywords: Arduino, Bluetooth, gas sensor, internet of things, transmission Speed

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Authors: Soha A. Bahanshal, Byung G. Kim

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Identification of patients at high risk for hospital readmission is of crucial importance for quality health care and cost reduction. Predicting hospital readmissions among diabetic patients has been of great interest to many researchers and health decision makers. We build a prediction model to predict hospital readmission for diabetic patients within 30 days of discharge. The core of the prediction model is a modified k Nearest Neighbor called Hybrid Fuzzy Weighted k Nearest Neighbor algorithm. The prediction is performed on a patient dataset which consists of more than 70,000 patients with 50 attributes. We applied data preprocessing using different techniques in order to handle data imbalance and to fuzzify the data to suit the prediction algorithm. The model so far achieved classification accuracy of 80% compared to other models that only use k Nearest Neighbor.

Keywords: machine learning, prediction, classification, hybrid fuzzy weighted k-nearest neighbor, diabetic hospital readmission

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Authors: Manisha Mukherjee, Diptarka Saha

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Reliable forecasts of univariate time series data are often necessary for several contexts. ARIMA models are quite popular among practitioners in this regard. Hence, choosing correct parameter values for ARIMA is a challenging yet imperative task. Thus, a stepwise algorithm is introduced to provide automatic and robust estimates for parameters (p; d; q)(P; D; Q) used in seasonal ARIMA models. This process is focused on improvising the overall quality of the estimates, and it alleviates the problems induced due to the unidimensional nature of the methods that are currently used such as auto.arima. The fast and automated search of parameter space also ensures reliable estimates of the parameters that possess several desirable qualities, consequently, resulting in higher test accuracy especially in the cases of noisy data. After vigorous testing on real as well as simulated data, the algorithm doesn’t only perform better than current state-of-the-art methods, it also completely obviates the need for human intervention due to its automated nature.

Keywords: time series, ARIMA, auto.arima, ARIMA parameters, forecast, R function

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Authors: C. A. Roberts, S. L. Mascaro, J. R. Gerrish, J. L. Horner

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Management-intensive Grazing (MiG) is a practice that rotates livestock through paddocks in a way that best matches the nutrient requirements of the animal to the yield and quality of the pasture. In the USA, MiG has been taught to livestock producers throughout the state of Missouri in 2- and 3-day workshops called “Missouri Grazing Schools.” The economic impact of these schools was quantified using IMPLAN software. The model included hectares of adoption, animal performance, carrying capacity, and input costs. To date, MiG, as taught in the Missouri Grazing Schools, has been implemented on more than 70,000 hectares in Missouri. The economic impact of these schools is presently $125 million USD per year added to the state economy. This magnitude of impact is the result not only of widespread adoption but also because of increased livestock carrying capacity; in Missouri, a capacity increase of 25 to 30% has been well documented. Additional impacts have been MiG improving forage quality and reducing the cost of feed and fertilizer. The environmental impact of MiG in the state of Missouri is currently being estimated. Environmental impact takes into account the reduction in the application of commercial fertilizers; in MiG systems, nitrogen is supplied by N fixation from legumes, and much of the P and K is recycled naturally by well-distributed manure. The environmental impact also estimates carbon sequestration and methane production; MiG can increase carbon sequestration and reduce methane production in comparison to default grazing practices and feedlot operations in the USA.

Keywords: agricultural education, forage quality, management-intensive grazing, nutrient cycling, stock density, sustainable agriculture

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Authors: Mustafa Kamoona, Mohamed El-Sharkawy

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Although the latest Wireless Local Area Network technology Wi-Fi 802.11i standard addresses many of the security weaknesses of the antecedent Wired Equivalent Privacy (WEP) protocol, there are still scenarios where the network security are still vulnerable. The first security model that 802.11i offers is the Personal model which is very cheap and simple to install and maintain, yet it uses a Pre Shared Key (PSK) and thus has a low to medium security level. The second model that 802.11i provide is the Enterprise model which is highly secured but much more expensive and difficult to install/maintain and requires the installation and maintenance of an authentication server that will handle the authentication and key management for the wireless network. A central issue with the personal model is that the PSK needs to be shared with all the devices that are connected to the specific Wi-Fi network. This pre-shared key, unless changed regularly, can be cracked using offline dictionary attacks within a matter of hours. The key is burdensome to change in all the connected devices manually unless there is some kind of algorithm that coordinate this PSK update. The key idea of this paper is to propose a new algorithm that proactively and effectively coordinates the pre-shared key generation, management, and distribution in the cheap WPA/WPA2 personal security model using only a DD-WRT router.

Keywords: Wi-Fi, WPS, TLS, DD-WRT

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Authors: Sahithi Yarlagadda

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The design of antenna is constrained by mathematical and geometrical parameters. Though there are diverse antenna structures with wide range of feeds yet, there are many geometries to be tried, which cannot be customized into predefined computational methods. The antenna design and optimization qualify to apply evolutionary algorithmic approach since the antenna parameters weights dependent on geometric characteristics directly. The evolutionary algorithm can be explained simply for a given quality function to be maximized. We can randomly create a set of candidate solutions, elements of the function's domain, and apply the quality function as an abstract fitness measure. Based on this fitness, some of the better candidates are chosen to seed the next generation by applying recombination and permutation to them. In conventional approach, the quality function is unaltered for any iteration. But the antenna parameters and geometries are wide to fit into single function. So, the weight coefficients are obtained for all possible antenna electrical parameters and geometries; the variation is learnt by mining the data obtained for an optimized algorithm. The weight and covariant coefficients of corresponding parameters are logged for learning and future use as datasets. This paper drafts an approach to obtain the requirements to study and methodize the evolutionary approach to automated antenna design for our past work on Vivaldi antenna as test candidate. The antenna parameters like gain, directivity, etc. are directly caged by geometries, materials, and dimensions. The design equations are to be noted here and valuated for all possible conditions to get maxima and minima for given frequency band. The boundary conditions are thus obtained prior to implementation, easing the optimization. The implementation mainly aimed to study the practical computational, processing, and design complexities that incur while simulations. HFSS is chosen for simulations and results. MATLAB is used to generate the computations, combinations, and data logging. MATLAB is also used to apply machine learning algorithms and plotting the data to design the algorithm. The number of combinations is to be tested manually, so HFSS API is used to call HFSS functions from MATLAB itself. MATLAB parallel processing tool box is used to run multiple simulations in parallel. The aim is to develop an add-in to antenna design software like HFSS, CSTor, a standalone application to optimize pre-identified common parameters of wide range of antennas available. In this paper, we have used MATLAB to calculate Vivaldi antenna parameters like slot line characteristic impedance, impedance of stripline, slot line width, flare aperture size, dielectric and K means, and Hamming window are applied to obtain the best test parameters. HFSS API is used to calculate the radiation, bandwidth, directivity, and efficiency, and data is logged for applying the Evolutionary genetic algorithm in MATLAB. The paper demonstrates the computational weights and Machine Learning approach for automated antenna optimizing for Vivaldi antenna.

Keywords: machine learning, Vivaldi, evolutionary algorithm, genetic algorithm

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Authors: M. Taheri Tehrani, H. Ajorloo

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In this paper, an intelligent multi-agent framework is developed for each router in which agents have two vital functionalities, traffic shaping and buffer allocation and are positioned in the ports of the routers. With traffic shaping functionality agents shape the traffic forward by dynamic and real time allocation of the rate of generation of tokens in a Token Bucket algorithm and with buffer allocation functionality agents share their buffer capacity between each other based on their need and the conditions of the network. This dynamic and intelligent framework gives this opportunity to some ports to work better under burst and more busy conditions. These agents work intelligently based on Reinforcement Learning (RL) algorithm and will consider effective parameters in their decision process. As RL have limitation considering much parameter in its decision process due to the volume of calculations, we utilize our novel method which invokes Principle Component Analysis (PCA) on the RL and gives a high dimensional ability to this algorithm to consider as much as needed parameters in its decision process. This implementation when is compared to our previous work where traffic shaping was done without any sharing and dynamic allocation of buffer size for each port, the lower packet drop in the whole network specifically in the source routers can be seen. These methods are implemented in our previous proposed intelligent simulation environment to be able to compare better the performance metrics. The results obtained from this simulation environment show an efficient and dynamic utilization of resources in terms of bandwidth and buffer capacities pre allocated to each port.

Keywords: principal component analysis, reinforcement learning, buffer allocation, multi- agent systems

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Authors: Cristina Vatamanu, Doina Cosovan, Dragos Gavrilut, Henri Luchian

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In the past few years, the amount of malicious software increased exponentially and, therefore, machine learning algorithms became instrumental in identifying clean and malware files through semi-automated classification. When working with very large datasets, the major challenge is to reach both a very high malware detection rate and a very low false positive rate. Another challenge is to minimize the time needed for the machine learning algorithm to do so. This paper presents a comparative study between different machine learning techniques such as linear classifiers, ensembles, decision trees or various hybrids thereof. The training dataset consists of approximately 2 million clean files and 200.000 infected files, which is a realistic quantitative mixture. The paper investigates the above mentioned methods with respect to both their performance (detection rate and false positive rate) and their practicability.

Keywords: ensembles, false positives, feature selection, one side class algorithm

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Authors: Joshua Paul Steimel, Michael Pappas, Ethan Hall

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Particle-particle interactions are critical in determining the state of an active matter system. Unique and ubiquitous non-equilibrium behavior like swarming, vortexing, spiraling, and much more is governed by interactions between active units or particles. In hybrid active-passive matter systems, the attraction between spinning active units in a 2D monolayer of passive particles is controlled by the mechanical behavior of the passive monolayer. We demonstrate here that the range and dynamics of this attraction can be controlled by changing the composition of the passive monolayer by adding dopant passive particles. These dopant passive particles effectively pin the movement of dislocation motion in the passive media and reduce the probability of defect motion required to erode the bridge of passive particles between active spinners, thus reducing the range of attraction. Additionally, by adding an out of plane component to the magnetic moment and creating a top-like motion a short range repulsion emerges between the top-like particle. At inter-top distances less than four particle diameters apart, the tops repel but beyond that, distance attract up to 13 particle diameters apart. The tops were also able to locally and transiently anneal the passive monolayer. Thus we demonstrate that by tuning several parameters of the hybrid active matter system, one can observe very different emergent behavior.

Keywords: active matter, colloids, ferromagnetic, annealing

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Authors: Jung-Ho Moon, Tae Kwon Ha

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Abstract—High temperature deformation behavior of cast Fe-20Cr-5Al alloy has been investigated in this study by performing tensile and compression tests at temperatures from 1100 to 1200oC. Rectangular ingots of which the dimensions were 300×300×100 in millimeter were cast using vacuum induction melting. Phase equilibrium was calculated using the FactSage®, thermodynamic software and database. Tensile strength of cast Fe-20Cr-5Al alloy was 4 MPa at 1200oC. With temperature decreased, tensile strength increased rapidly and reached up to 13 MPa at 1100oC. Elongation also increased from 18 to 80% with temperature decreased from 1200oC to 1100oC. Microstructure observation revealed that M23C6 carbide was precipitated along the grain boundary and within the matrix.

Keywords: 20 Cr-5Al ferritic stainless, high temperature deformation, aging treatment, microstructure, mechanical properties

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Authors: Ali H. Muhammad

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The present study examines some antecedents and consequences of employee job involvement in Kuwaiti business organization. The model presented in the current study suggests that job satisfaction and organizational commitments are determinates of job involvements. Employees who are satisfied with their jobs tend to be more attached to their jobs and view their jobs as an essential part of their existence. Similarly, employees who are committed to organizational goals, and identify with organizational values, tend to have high level of involvement. Furthermore, our model suggests that job involvement is positively related to work performance and organizational citizenship behavior. The negative consequences of job involvement include burnout and work family conflict. To test the hypotheses, a sample of 204 Kuwaiti employees representing 8 Kuwaiti work organizations is used. The sample covers a variety of business sectors in Kuwait, including manufacturing, services, and transportation. The data were analyzed using non-parametric tests, Pearson correlations, and structural equation modeling. Results indicate that job satisfaction and organizational commitment have significant positive effects on job involvement. Furthermore, findings reveal that job involvement is positively associated with performance, organization citizenship behavior, and work family conflict. Findings are discussed, and future areas of research are identified.

Keywords: job involvement, organizational citizenship behavior, work family conflict, burnout

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Authors: Iman Iraei, Mina Sharifi

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A method for object tracking in motion blurred images is proposed in this article. This paper shows that object tracking could be improved with this approach. We use mean shift algorithm to track different objects as a main tracker. But, the problem is that mean shift could not track the selected object accurately in blurred scenes. So, for better tracking result, and increasing the accuracy of tracking, wavelet transform is used. We use a feature named as blur extent, which could help us to get better results in tracking. For calculating of this feature, we should use Harr wavelet. We can look at this matter from two different angles which lead to determine whether an image is blurred or not and to what extent an image is blur. In fact, this feature left an impact on the covariance matrix of mean shift algorithm and cause to better performance of tracking. This method has been concentrated mostly on motion blur parameter. transform. The results reveal the ability of our method in order to reach more accurately tracking.

Keywords: mean shift, object tracking, blur extent, wavelet transform, motion blur

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Authors: Anum Ali, Kashaf ad Dooja, Asif Saleem

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The future smart cities trend will be towards Internet of Things (IoT); IoT creates dynamic connections in a ubiquitous manner. Smart cities offer ease and flexibility for daily life matters. By using small devices that are connected to cloud servers based on IoT, network traffic between these devices is growing exponentially, whose security is a concerned issue, since ratio of cyber attack may make the network traffic vulnerable. This paper discusses the latest machine learning approaches in related work further to tackle the increasing rate of cyber attacks, machine learning algorithm is applied to IoT-based network traffic data. The proposed algorithm train itself on data and identify different sections of devices interaction by using supervised learning which is considered as a classifier related to a specific IoT device class. The simulation results clearly identify the attacks and produce fewer false detections.

Keywords: IoT, traffic security, deep learning, classification

Procedia PDF Downloads 134

Authors: Julia Cristina Bonaldo, Christophe L. Martin, Severine Romero Baivier, Stephane Mazerat

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Alumina refractories are commonly used in steel and foundry industries. These refractories are prepared through a powder metallurgy route. They are a mixture of hard alumina particles and graphite platelets embedded into a soft carbonic matrix (binder). The powder can be cold pressed isostatically or uniaxially, depending on the application. The compact is then fired to obtain the final product. The quality of the product is governed by the microstructure of the composite and by the process parameters. The compaction behavior and the mechanical properties of the fired product depend greatly on the amount of each phase, on their morphology and on the initial microstructure. In order to better understand the link between these parameters and the macroscopic behavior, we use the Discrete Element Method (DEM) to simulate the compaction process and the fracture behavior of the fired composite. These simulations are coupled with well-designed experiments. Four mixes with various amounts of Al₂O₃ and binder were tested both experimentally and numerically. In DEM, each particle is modelled and the interactions between particles are taken into account through appropriate contact or bonding laws. Here, we model a bimodal mixture of large Al₂O₃ and small Al₂O₃ covered with a soft binder. This composite is itself mixed with graphite platelets. X-ray tomography images are used to analyze the morphologies of the different components. Large Al₂O₃ particles and graphite platelets are modelled in DEM as sets of particles bonded together. The binder is modelled as a soft shell that covers both large and small Al₂O₃ particles. When two particles with binder indent each other, they first interact through this soft shell. Once a critical indentation is reached (towards the end of compaction), hard Al₂O₃ - Al₂O₃ contacts appear. In accordance with experimental data, DEM simulations show that the amount of Al₂O₃ and the amount of binder play a major role for the compaction behavior. The graphite platelets bend and break during the compaction, also contributing to the macroscopic stress. Firing step is modeled in DEM by ascribing bonds to particles which contact each other after compaction. The fracture behavior of the compacted mixture is also simulated and compared with experimental data. Both diametrical tests (Brazilian tests) and triaxial tests are carried out. Again, the link between the amount of Al₂O₃ particles and the fracture behavior is investigated. The methodology described here can be generalized to other particulate materials that are used in the ceramic industry.

Keywords: cold compaction, composites, discrete element method, refractory materials, x-ray tomography

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Authors: Soltani Amir, Hu Jiaxin

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Determination of optimal parameters of a passive control system device is the primary objective of this study. Expanding upon the use of control devices in wind and earthquake hazard reduction has led to development of various control systems. The advantage of non-linearity characteristics in a passive control device and the optimal control method using LQR algorithm are explained in this study. Finally, this paper introduces a simple approach to determine optimum parameters of a nonlinear viscous damper for vibration control of structures. A MATLAB program is used to produce the dynamic motion of the structure considering the stiffness matrix of the SDOF frame and the non-linear damping effect. This study concluded that the proposed system (variable damping system) has better performance in system response control than a linear damping system. Also, according to the energy dissipation graph, the total energy loss is greater in non-linear damping system than other systems.

Keywords: passive control system, damping devices, viscous dampers, control algorithm

Procedia PDF Downloads 455