Search results for: system model

Authors: Norezzine Abdelaziz, Rebouh Nazih Yacer, Kezimana Parfait, Parpura D. I., Gadzhikurbanov A., Anastasios Dranidis

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The genetic variation of Shvicezebuvides cattle from three different farms in the Tajikistan Republic was studied using 10 microsatellite markers (SSR). The trials were laid out using a multi- locus analysis system for the analysis of cattle microsatellite locus. An estimated genetic variability of the examined livestock is given in the article. The results of our SSR analysis as well as the numbers and frequencies of common alleles in studied samples, we established a high genetic similarity of studied samples. These results can also be furthermore useful in the decision making for preservation and rational genetic resources usage of the Tajik Shvicezebuvides cattle.

Keywords: genetic characteristic, frequencies of the occurrence alleles, microsatellite markers, Swiss cattle

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Authors: Ishu Surender, M. Amez Khair, Ishan Singh

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Urbanization is a multidimensional phenomenon. It is an indication of the long-term process for the shift of economics to industrial from rural. The significance of urbanization in modernization, socio-economic development, and poverty eradication is relevant in modern times. This paper aims to study the urbanization index model in the capital of India, Delhi using aspects such as demographic aspect, infrastructural development aspect, and economic development aspect. The urbanization index of all the nine districts of Delhi will be determined using multiple parameters such as population density and the availability of health and education facilities. The definition of the urban area varies from city to city and requires periodic classification which makes direct comparisons difficult. The urbanization index calculated in this paper can be employed to measure the urbanization of a district and compare the level of urbanization in different districts.

Keywords: multiparameter, population density, multiple regression, normalized urbanization index

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Authors: Ismael Ávila, José Reynaldo F. Filho, Vasco Varanda Picchi

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The ever-growing consumer awareness of food provenance in Brazil is driving the creation of a trusted ecosystem around the animal protein supply chain. The traceability and accountability requirements of such an ecosystem demand a blockchain layer to strengthen the weak links in that chain. For that, direct involvement of the companies in the blockchain transactions, including as validator nodes of the network, implies formalizing a partnership with the consortium behind the ecosystem. Yet, their compliance standards usually require that a formal governance structure is in place before they agree with any membership terms. In light of such a strategic role of blockchain governance, the paper discusses a framework for tailoring a governance model for a blockchain-based solution aimed at the meat supply chain and evaluates principles and attributes in terms of their relevance to the development of a robust trust ecosystem.

Keywords: blockchain, governance, trust ecosystem, supply chain, traceability

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Authors: Yuang Guo, Dewancker Bart

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The primary energy consumption of buildings throughout China was approximately 814 million tons of coal equivalents in 2014, which accounts for 19.12% of China's total primary energy consumption. Also, the energy consumption of public buildings takes a bigger share than urban residential buildings and rural residential buildings among the total energy consumption. To improve the level of energy demand, various design parameters were chosen. Meanwhile, a series of simulations by Energy Plus (EP-Launch) is performed using a base case model established in Open Studio. Through the results, 16%-23% of total energy demand reductions can be found in the severe cold zone of China, and it can also provide a reference for the architectural design of other similar climate zones.

Keywords: energy consumption, design parameters, indoor thermal comfort, simulation study, severe cold climate zone

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Authors: Gabaikanngwe Ethel Mambo, Kinyanjui Godfrey Gichuhi

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The study analysed the Children’s Act of 2009 of Botswana in curbing child sexual abuse (CSA) in Francistown and its surroundings. The qualitative methodology was used to collect data. Retrospective reports of CSA were obtained from various departments dealing with children. The research findings revealed the ineffectiveness of the Children’s Act of 2009 in identifying and preventing CSA. The Act has failed to deter or prevent the offenders from committing crimes against children. The study demonstrated an increase in CSA cases that were never reported. Lack of skills by the justice system exacerbated sexual molestation. The study also revealed that most CSA cases were underreported. Lastly, the study demonstrated those child victims were sexually molested by someone known to them.

Keywords: sexual abuse, molestation, incest, child

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Authors: Ummu Salma Al Azizah, Herri Mulyono, Anisa Mauliata Suryana

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The significance of corporate governance regarding to the agency problem have been transparent. This study examine the impact of corporate governance on the performance of Islamic banking in Indonesia. By using fixed effect model and added some control variable, the current study try to explore the correlation between the theoretical framework on corporate governance, such as agency theory and risk management theory. The bank performance (Return on Asset and Return on Equity) which are operational performance and financial performance. And Corporate governance based on Board size, CEO duality, Audit committee and Shariah supervisory board. The limitation of this study only focus on the Islamic banks performance from year 2015 to 2020. The study fill the gap in the literature by addressing the issue of corporate governance on Islamic banks performance in Indonesia.

Keywords: corporate governance, financial performance, islamic banks, listed companies, Indonesia

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Authors: Robert Caulk

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A generalized framework for adaptive machine learning deployments in algorithmic trading is introduced, tested, and released as open-source code. The presented software aims to test the hypothesis that recent data contains enough information to form a probabilistically favorable short-term price prediction. Further, the framework contains various adaptive machine learning techniques that are geared toward generating profit during strong trends and minimizing losses during trend changes. Results demonstrate that this adaptive machine learning approach is capable of capturing trends and generating profit. The presentation also discusses the importance of defining the parameter space associated with the dynamic training data-set and using the parameter space to identify and remove outliers from prediction data points. Meanwhile, the generalized architecture enables common users to exploit the powerful machinery while focusing on high-level feature engineering and model testing. The presentation also highlights common strengths and weaknesses associated with the presented technique and presents a broad range of well-tested starting points for feature set construction, target setting, and statistical methods for enforcing risk management and maintaining probabilistically favorable entry and exit points. The presentation also describes the end-to-end data processing tools associated with FreqAI, including automatic data fetching, data aggregation, feature engineering, safe and robust data pre-processing, outlier detection, custom machine learning and statistical tools, data post-processing, and adaptive training backtest emulation, and deployment of adaptive training in live environments. Finally, the generalized user interface is also discussed in the presentation. Feature engineering is simplified so that users can seed their feature sets with common indicator libraries (e.g. TA-lib, pandas-ta). The user also feeds data expansion parameters to fill out a large feature set for the model, which can contain as many as 10,000+ features. The presentation describes the various object-oriented programming techniques employed to make FreqAI agnostic to third-party libraries and external data sources. In other words, the back-end is constructed in such a way that users can leverage a broad range of common regression libraries (Catboost, LightGBM, Sklearn, etc) as well as common Neural Network libraries (TensorFlow, PyTorch) without worrying about the logistical complexities associated with data handling and API interactions. The presentation finishes by drawing conclusions about the most important parameters associated with a live deployment of the adaptive learning framework and provides the road map for future development in FreqAI.

Keywords: machine learning, market trend detection, open-source, adaptive learning, parameter space exploration

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Authors: Faruk Ortes, Baris Sayin, Tarik Serhat Bozkurt, Cemil Akcay

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The technique using near-surface mounted (NSM) carbon fiber-reinforced polymer (CFRP) composites has proved to be an reliable strengthening technique. However, the effects of different parameters for the use of NSM CFRP are not fully developed yet. This study focuses on the development of a numerical modeling that can predict the behavior of reinforced concrete (RC) beams strengthened with NSM FRP rods exposed to bending loading and the efficiency of various parameters such as CFRP rod size and filling material type are evaluated by using prepared models. For this purpose, three different models are developed and implemented in the ANSYS® software using Finite Element Analysis (FEA). The numerical results indicate that CFRP rod size and filling material type are significant factors in the behavior of the analyzed RC beams.

Keywords: numerical model, FEA, RC beam, NSM technique, CFRP rod, filling material

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Authors: Terence Soule, Tami Al Ghamdi

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To study how to transfer knowledge from multiple source problems to the target problem, we modeled the Transfer Learning (TL) process using Genetic Algorithms as the model solver. TL is the process that aims to transfer learned data from one problem to another problem. The TL process aims to help Machine Learning (ML) algorithms find a solution to the problems. The Genetic Algorithms (GA) give researchers access to information that we have about how the old problem is solved. In this paper, we have five different source problems, and we transfer the knowledge to the target problem. We studied different scenarios of the target problem. The results showed combined knowledge from multiple source problems improves the GA performance. Also, the process of combining knowledge from several problems results in promoting diversity of the transferred population.

Keywords: transfer learning, genetic algorithm, evolutionary computation, source and target

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Authors: S. Turkan

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In this paper, the Turkey’s Top 500 Industrial Enterprises data in 2014 were analyzed by data envelopment analysis. Data envelopment analysis is used to detect efficient decision-making units such as universities, hospitals, schools etc. by using inputs and outputs. The decision-making units in this study are enterprises. To detect efficient enterprises, some financial ratios are determined as inputs and outputs. For this reason, financial indicators related to productivity of enterprises are considered. The efficient foreign weighted owned capital enterprises are detected via super efficiency model. According to the results, it is said that Mercedes-Benz is the most efficient foreign weighted owned capital enterprise in Turkey.

Keywords: data envelopment analysis, super efficiency, logistic regression, financial ratios

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Authors: Eeva Wallenius-Nareneva, Tuula Toivanen-Labiad

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Background: Oral health promotion event was organised for forty Afghanistan, Iraqi and Bangladeshi underage asylum seekers in Finland. The invitation to arrange this coaching occasion was accepted in the Degree Programme in Oral Hygiene in Metropolia. The personnel in the reception center found the need to improve oral health among the youngsters. The purpose was to strengthen the health literacy of the boys in their oral self-care and to reduce dental fears. The Finnish studies, especially the terminology of oral health was integrated to coaching with the help of interpreters. Cooperative learning was applied. Methods: Oral health was interactively discussed in four study group sessions: 1. The importance of healthy eating habits; - Good and bad diets, - Regular meals, - Acid attack o Xylitol. 2. Oral diseases − connection to general health; - Aetiology of gingivitis, periodontitis and caries, - Harmfulness of smoking 3. Tools and techniques for oral self-care; - Brushing and inter dental cleaning. 4. Sharing earlier dental care experiences; - Cultural differences, - Dental fear, - Regular check-ups. Results: During coaching deficiencies appeared in brushing and inter dental cleaning techniques. Some boys were used to wash their mouth with salt justifying it by salt’s antiseptic properties. Many brushed their teeth by vertical movements. The boys took feedback positively when a demonstration with model jaws revealed the inefficiency of the technique. The advantages of fluoride tooth paste were advised. Dental care procedures were new and frightening for many boys. Finnish dental care system was clarified. The safety and indolence of the treatments and informed consent were highlighted. Video presentations and the dialog lowered substantially the threshold to visit dental clinic. The occasion gave the students means for meeting patients from different cultural and language backgrounds. The information hidden behind the oral health problems of the asylum seekers was valuable. Conclusions: Learning dental care practices used in different cultures is essential for dental professionals. The project was a good start towards multicultural oral health care. More experiences are needed before graduation. Health education themes should be held simple regardless of the target group. The heterogeneity of the group does not pose a problem. Open discussion with questions leading to the theme works well in clarifying the target group’s knowledge level. Sharing own experiences strengthens the sense of equality among the participants and encourages them to express own opinions. Motivational interview method turned out to be successful. In the future coaching occasions must confirm active participation of everyone. This could be realized by dividing the participants to even smaller groups. The different languages impose challenges but they can be solved by using more interpreters. Their presence ensures that everyone understands the issues properly although the use of plain and sign languages are helpful. In further development, it would be crucial to arrange a rehearsal occasion to the same participants in two/three months’ time. This would strengthen the adaption of self-care practices and give the youngsters opportunity to pose more open questions. The students would gain valuable feedback regarding the effectiveness of their work.

Keywords: cooperative learning, interactive methods, motivational interviewing, oral health promotion, underage asylum seekers

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Authors: Ai Fujii, Kan Shimazaki

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Bicycle users must ride on the street according the law in Japan, but in practice, many bicycle users ride on the sidewalk. Drivers generally feel that bicycles riding in the street are in the way. In contrast, pedestrians generally feel that bicycles riding on the sidewalk are in the way. That seems to make sense. What, then, is the difference between riding a bicycle on the sidewalk or in the street by usual traveling means. We made 3D computer graphics models of pedestrians, a car, and a bicycle at an intersection. The bicycle was positioned to choose between advancing to the sidewalk or the street after a few seconds. We then made a 2D stimulus picture by changing the point of view of the 3DCG model pictures. Attitudes were surveyed using this 2D stimulus picture, and we compared attitudes between three groups, people traveling by car, on foot, or by bicycle. Here we report the survey result.

Keywords: bicycle, sidewalk, pedestrians, driver, intersection, safety

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Authors: Tushar Bhardwaj

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Internet of Things (IoT) possesses a dynamic network where the network nodes (mobile devices) are added and removed constantly and randomly, hence the traffic distribution in the network is quite variable and irregular. The basic but very important part in any network is route searching. We have many conventional route searching algorithms like link-state, and distance vector algorithms but they are restricted to the static point to point network topology. In this paper we propose a model that uses the Ant Colony Algorithm for route searching. It is dynamic in nature and has positive feedback mechanism that conforms to the route searching. We have also embedded the concept of Non-Deterministic Finite Automata [NDFA] minimization to reduce the network to increase the performance. Results show that Ant Colony Algorithm gives the shortest path from the source to destination node and NDFA minimization reduces the broadcasting storm effectively.

Keywords: routing, ant colony algorithm, NDFA, IoT

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Authors: Navah Z. Ratzon, Rachel Shichrur

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Background: Many studies have assessed and identified the risk factors of safe driving, but there is relatively little research-based evidence concerning the ability to improve the driving skills of drivers in general and in particular of bus drivers, who are defined as a population at risk. Accidents involving bus drivers can endanger dozens of passengers and cause high direct and indirect damages. Objective: To examine the effectiveness of a metacognitive-functional intervention program for the reduction of risk factors among professional drivers relative to a control group. Methods: The study examined 77 bus drivers working for a large public company in the center of the country, aged 27-69. Twenty-one drivers continued to the intervention stage; four of them dropped out before the end of the intervention. The intervention program we developed was based on previous driving models and the guiding occupational therapy practice framework model in Israel, while adjusting the model to the professional driving in public transportation and its particular risk factors. Treatment focused on raising awareness to safe driving risk factors identified at prescreening (ergonomic, perceptual-cognitive and on-road driving data), with reference to the difficulties that the driver raises and providing coping strategies. The intervention has been customized for each driver and included three sessions of two hours. The effectiveness of the intervention was tested using objective measures: In-Vehicle Data Recorders (IVDR) for monitoring natural driving data, traffic accident data before and after the intervention, and subjective measures (occupational performance questionnaire for bus drivers). Results: Statistical analysis found a significant difference between the degree of change in the rate of IVDR perilous events (t(17)=2.14, p=0.046), before and after the intervention. There was significant difference in the number of accidents per year before and after the intervention in the intervention group (t(17)=2.11, p=0.05), but no significant change in the control group. Subjective ratings of the level of performance and of satisfaction with performance improved in all areas tested following the intervention. The change in the ‘human factors/person’ field, was significant (performance : t=- 2.30, p=0.04; satisfaction with performance : t=-3.18, p=0.009). The change in the ‘driving occupation/tasks’ field, was not significant but showed a tendency toward significance (t=-1.94, p=0.07,). No significant differences were found in driving environment-related variables. Conclusions: The metacognitive-functional intervention significantly improved the objective and subjective measures of safety of bus drivers’ driving. These novel results highlight the potential contribution of occupational therapists, using metacognitive functional treatment, to preventing car accidents among the healthy drivers population and improving the well-being of these drivers. This study also enables familiarity with advanced technologies of IVDR systems and enriches the knowledge of occupational therapists in regards to using a wide variety of driving assessment tools and making the best practice decisions.

Keywords: bus drivers, IVDR, human risk factors, metacognitive-functional intervention

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Authors: Cheila Pereira, Sara C. Cunha, Miguel A. Faria, José O. Fernandes

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The increasing world population brings several concerns, one of which is food security and sustainability. To meet this challenge, aquaculture, the farming of aquatic animals and plants, including fish, mollusks, bivalves, and algae, has experienced sustained growth and development in recent years. Recent advances in this industry have focused on reducing its economic and environmental costs, for example, the substitution of protein sources in fish feed. Plant-based proteins are now a common approach, and while it is a greener alternative to animal-based proteins, there are some disadvantages, such as their putative content and intoxicants such as mycotoxins. These are naturally occurring plant contaminants, and their exposure in fish can cause health problems, stunted growth or even death, resulting in economic losses for the producers and health concerns for the consumers. Different works have demonstrated the presence of both AFB1 (aflatoxin B1) and ENNB1 (enniatin B1) in fish feed and their capacity to be absorbed and bioaccumulate in the fish organism after digestion, further reaching humans through fish ingestion. The aim of this work was to evaluate the bioaccessibility of both mycotoxins in samples of Sparus aurata muscle using a static digestion model based on the INFOGEST protocol. The samples were subjected to different cooking procedures – raw, grilled and fried – and different seasonings – none, thyme and ginger – in order to evaluate their potential reduction effect on mycotoxins bioaccessibility, followed by the evaluation of the intestinal transport of both compounds with an in vitro cell model composed of Caco-2/HT-29 co-culture monolayers, simulating the human intestinal epithelium. The bioaccessible fractions obtained in the digestion studies were used in the transport studies for a more realistic approach to bioavailability evaluation. Results demonstrated the effect of the use of different cooking procedures and seasoning on the toxin's bioavailability. Sparus aurata was chosen in this study for its large production in aquaculture and high consumption in Europe. Also, with the continued evolution of fish farming practices and more common usage of novel feed ingredients based on plants, there is a growing concern about less studied contaminants in aquaculture and their consequences for human health. In pair with greener advances in this industry, there is a convergence towards alternative research methods, such as in vitro applications. In the case of bioavailability studies, both in vitro digestion protocols and intestinal transport assessment are excellent alternatives to in vivo studies. These methods provide fast, reliable and comparable results without ethical restraints.

Keywords: AFB1, aquaculture, bioaccessibility, ENNB1, intestinal transport.

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Authors: Eman A. Al-Hilo, Hawraa H. Al-Waelly

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In this work, fractal compression (FIC) technique is introduced based on using moment features to block indexing the zero-mean range-domain blocks. The moment features have been used to speed up the IFS-matching stage. Its moments ratio descriptor is used to filter the domain blocks and keep only the blocks that are suitable to be IFS matched with tested range block. The results of tests conducted on Lena picture and Cat picture (256 pixels, resolution 24 bits/pixel) image showed a minimum encoding time (0.89 sec for Lena image and 0.78 of Cat image) with appropriate PSNR (30.01dB for Lena image and 29.8 of Cat image). The reduction in ET is about 12% for Lena and 67% for Cat image.

Keywords: fractal gray level image, fractal compression technique, iterated function system, moments feature, zero-mean range-domain block

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Authors: Stefan Papastefanou

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Artificial intelligence (AI) is an interdisciplinary field of computer science with the aim of creating intelligent machine behavior. Early approaches to AI have been configured to operate in very constrained environments where the behavior of the AI system was previously determined by formal rules. Knowledge was presented as a set of rules that allowed the AI system to determine the results for specific problems; as a structure of if-else rules that could be traversed to find a solution to a particular problem or question. However, such rule-based systems typically have not been able to generalize beyond the knowledge provided. All over the world and especially in IT-heavy industries such as the United States, the European Union, Singapore, and China, machine learning has developed to be an immense asset, and its applications are becoming more and more significant. It has to be examined how such products of machine learning models can and should be protected by IP law and for the purpose of this paper patent law specifically, since it is the IP law regime closest to technical inventions and computing methods in technical applications. Genetic breeding models are currently less popular than recursive neural network method and deep learning, but this approach can be more easily described by referring to the evolution of natural organisms, and with increasing computational power; the genetic breeding method as a subset of the evolutionary algorithms models is expected to be regaining popularity. The research method focuses on patentability (according to the world’s most significant patent law regimes such as China, Singapore, the European Union, and the United States) of AI inventions and machine learning. Questions of the technical nature of the problem to be solved, the inventive step as such, and the question of the state of the art and the associated obviousness of the solution arise in the current patenting processes. Most importantly, and the key focus of this paper is the problem of patenting inventions that themselves are developed through machine learning. The inventor of a patent application must be a natural person or a group of persons according to the current legal situation in most patent law regimes. In order to be considered an 'inventor', a person must actually have developed part of the inventive concept. The mere application of machine learning or an AI algorithm to a particular problem should not be construed as the algorithm that contributes to a part of the inventive concept. However, when machine learning or the AI algorithm has contributed to a part of the inventive concept, there is currently a lack of clarity regarding the ownership of artificially created inventions. Since not only all European patent law regimes but also the Chinese and Singaporean patent law approaches include identical terms, this paper ultimately offers a comparative analysis of the most relevant patent law regimes.

Keywords: algorithms, inventor, genetic breeding models, machine learning, patentability

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Authors: Parveen Banu Ansari, Venkatraman Chinnappan, Paramasivam Shankar

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Contract testing plays a pivotal role in the current landscape of microservices architecture. Testing microservices at the initial stages of development helps to identify and rectify issues before they escalate to higher levels, such as UI testing. By validating microservices through contract testing, you ensure the integration quality of APIs, enhancing the overall reliability and performance of the application. Contract testing, being a collaborative effort between testers and developers, ensures that the microservices adhere to the specified contracts or agreements. This proactive approach significantly reduces defects, streamlines the development process, and contributes to the overall efficiency and robustness of the application. In the dynamic and fast-paced world of digital applications, where microservices are the building blocks, embracing contract testing is indeed a strategic move for ensuring the quality and reliability of the entire system.

Keywords: validation, testing, contract, agreement, microservices

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Authors: James Moir

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The mainstay of Big Data is prediction in that it allows practitioners, researchers, and policy analysts to predict trends based upon the analysis of large and varied sources of data. These can range from changing social and political opinions, patterns in crimes, and consumer behaviour. Big Data has therefore shifted the criterion of success in science from causal explanations to predictive modelling and simulation. The 19th-century science sought to capture phenomena and seek to show the appearance of it through causal mechanisms while 20th-century science attempted to save the appearance and relinquish causal explanations. Now 21st-century science in the form of Big Data is concerned with the prediction of appearances and nothing more. However, this pulls social science back in the direction of a more rule- or law-governed reality model of science and away from a consideration of the internal nature of rules in relation to various practices. In effect Big Data offers us no more than a world of surface appearance and in doing so it makes disappear any context-specific conceptual sensitivity.

Keywords: big data, appearance, disappearance, surface, epistemology

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Authors: Maria Vueba, Tchilissila A. Simoes

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Angola has a deficient health system characterized by reduced human and material resources. Nurses are the main actors combating different types of diseases simultaneously dealing with a lack of essentials tools and means. In this study, we aimed to assess the organizational commitment and job satisfaction of 51 health professionals from a maternity ward in Lubango, Angola. Participants completed the Organizational Commitment Questionnaire and the Job Satisfaction Scale and demonstrated a strong commitment towards the maternal facility, despite the majority of them were not satisfied with their work. Moreover, the gender and years of service seemed to not influence the level of commitment and satisfaction among the professionals. These results show the need for organizational restructuration (i.e., wages, career progression, supervision) to increase job satisfaction in this institution.

Keywords: Africa, health professionals, organizational commitment, work satisfaction

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Authors: Mohammad Nadeem, Haider Banka, R. Venugopal

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Granulation or agglomeration is a size enlargement process to transform the fine particulates into larger aggregates since the fine size of available materials and minerals poses difficulty in their utilization. Though a long list of methods is available in the literature for the modeling of granulation process to facilitate the in-depth understanding and interpretation of the system, there is still scope of improvements using novel tools and techniques. Intelligent techniques, such as artificial neural network, fuzzy logic, self-organizing map, support vector machine and others, have emerged as compelling alternatives for dealing with imprecision and complex non-linearity of the systems. The present study tries to review the applications of intelligent techniques in the modeling of size enlargement process for fine materials.

Keywords: fine material, granulation, intelligent technique, modelling

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Authors: Musaab Hasan, Farkhund Iqbal, Patrick C. K. Hung, Benjamin C. M. Fung, Laura Rafferty

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In modern societies, the smart cities concept raised simultaneously with the projection towards adopting smart devices. A smart grid is an essential part of any smart city as both consumers and power utility companies benefit from the features provided by the power grid. In addition to advanced features presented by smart grids, there may also be a risk when the grids are exposed to malicious acts such as security attacks performed by terrorists. Considering advanced security measures in the design of smart meters could reduce these risks. This paper presents a security study for smart metering systems with a prototype implementation of the user interfaces for future works.

Keywords: security design, smart city, smart meter, smart grid, smart metering system

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Authors: Zhifu Li, Lei Li, Wanting Zhou, Yuanhang He

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This paper proposed a lightweight certificate-less authentication and key exchange protocol (Light-CL-PKC) based on elliptic curve cryptography and the Chinese Remainder Theorem for smart home scenarios. Light-CL-PKC can efficiently reduce the computational cost of both sides of authentication by forgoing time-consuming bilinear pair operations and making full use of point-addition and point-multiplication operations on elliptic curves. The authentication and key exchange processes in this system are also completed in a a single round of communication between the two parties. The analysis result demonstrates that it can significantly minimize the communication overhead of more than 32.14% compared with the referenced protocols, while the runtime for both authentication and key exchange have also been significantly reduced.

Keywords: authentication, key exchange, certificateless public key cryptography, elliptic curve cryptography

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Authors: Mohamed Shalaby, Yasser Kamal, Negm Shawky

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Mutually unbiased bases (MUBs) have an important role in the field of quantum computation and information. A complete set of these bases can be constructed when the system dimension is the power of the prime. Constructing such complete set in composite dimensions is still an open problem. Recently, the concept of weak mutually unbiased bases (WMUBs) in composite dimensions was introduced. A complete set of such bases can be constructed by combining the MUBs in each subsystem. In this paper, we present a comparative study between MUBs and WMUBs in the context of complex projective t-design. Explicit proofs are presented.

Keywords: complex projective t-design, finite quantum systems, mutually unbiased bases, weak mutually unbiased bases

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Authors: Alexandre Gurchumelia, Luca Sorriso-Valvo, David Burgess, Khatuna Elbakidze, Oleg Kharshiladze, Diana Kvaratskhelia

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The terrestrial magnetosheath is a highly turbulent medium, with a high level of magnetic1field fluctuations throughout a broad range of scales. These often include an inertial range where a2magnetohydrodynamic turbulent cascade is observed. The multifractal properties of the turbulent3cascade, strictly related to intermittency, are observed here during the transition from quasi-parallel to4quasi-perpendicular magnetic field with respect to the bow-shock normal. The different multifractal5behavior in the two regions is analyzed. A standard coarse-graining technique has been used6to evaluate the generalized dimensions and the corresponding multifractal spectrumf(α). A7p-model fit provided a quantitative measure of multifractality and intermittency, to be compared with8standard indicators: the width of the multifractal spectrum, the peak of the kurtosis, and its scaling9exponent. Results show a clear transition and sharp differences in the intermittency properties for the two regions.

Keywords: magnetos heath, turbulence, multifractal, instabilities

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Authors: Hyunwon Moon

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It is necessary to realize new biomedical wireless communication systems which send the signals collected from various bio sensors located at human body in order to monitor our health. Also, it should seamlessly connect to the existing wireless communication systems. A 5.8 GHz ISM band low power RF front-end receiver for a biomedical wireless communication system is implemented using a 0.5 µm SiGe BiCMOS process. To achieve low power RF front-end, the current optimization technique for selecting device size is utilized. The implemented low noise amplifier (LNA) shows a power gain of 9.8 dB, a noise figure (NF) of below 1.75 dB, and an IIP3 of higher than 7.5 dBm while current consumption is only 6 mA at supply voltage of 2.5 V. Also, the performance of a down-conversion mixer is measured as a conversion gain of 11 dB and SSB NF of 10 dB.

Keywords: biomedical, LNA, mixer, receiver, RF front-end, SiGe

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Authors: Mahmoud M. Othman, Y. G. Hegazy, A. Y. Abdelaziz

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This paper proposes a novel heuristic algorithm that aims to determine the best size and location of distributed generators in unbalanced distribution networks. The proposed heuristic algorithm can deal with the planning cases where power loss is to be optimized without violating the system practical constraints. The distributed generation units in the proposed algorithm is modeled as voltage controlled node with the flexibility to be converted to constant power factor node in case of reactive power limit violation. The proposed algorithm is implemented in MATLAB and tested on the IEEE 37 -node feeder. The results obtained show the effectiveness of the proposed algorithm.

Keywords: distributed generation, heuristic approach, optimization, planning

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Authors: Bernard Polednik, Adam Piotrowicz, Lukasz Guz, Marzenna Dudzinska

Abstract:

Transportation is considered to be responsible for increased exposure of road users – i.e., drivers, car passengers, and pedestrians as well as inhabitants of houses located near roads - to pollutants emitted from vehicles. Accurate estimates are, however, difficult as exposure depends on many factors such as traffic intensity or type of fuel as well as the topography and the built-up area around the individual routes. The season and weather conditions are also of importance. In the case of inhabitants of houses located near roads, their exposure depends on the distance from the road, window tightness and other factors that decrease pollutant infiltration. This work reports the variations of particle concentrations along a selected road in Lublin, Poland. Their impact on the exposure for road users as well as for inhabitants of houses located near the road is also presented. Mobile and fixed-site measurements were carried out in peak (around 8 a.m. and 4 p.m.) and off-peak (12 a.m., 4 a.m., and 12 p.m.) traffic times in all 4 seasons. Fixed-site measurements were performed in 12 measurement points along the route. The number and mass concentration of particles was determined with the use of P-Trak model 8525, OPS 3330, DustTrak DRX model 8533 (TSI Inc. USA) and Grimm Aerosol Spectrometer 1.109 with Nano Sizer 1.321 (Grimm Aerosol Germany). The obtained results indicated that the highest concentrations of traffic-related pollution were measured near 4-way traffic intersections during peak hours in the autumn and winter. The highest average number concentration of ultrafine particles (PN0.1), and mass concentration of fine particles (PM2.5) in fixed-site measurements were obtained in the autumn and amounted to 23.6 ± 9.2×10³ pt/cm³ and 135.1 ± 11.3 µg/m³, respectively. The highest average number concentration of submicrometer particles (PN1) was measured in the winter and amounted to 68 ± 26.8×10³ pt/cm³. The estimated doses of particles deposited in the commuters’ and pedestrians’ lungs within an hour near 4-way TIs in peak hours in the summer amounted to 4.3 ± 3.3×10⁹ pt/h (PN0.1) and 2.9 ± 1.4 µg/h (PM2.5) and 3.9 ± 1.1×10⁹ pt/h (PN0.1) or 2.5 ± 0.4 µg/h (PM2.5), respectively. While estimating the doses inhaled by the inhabitants of premises located near the road one should take into account different fractional penetration of particles from outdoors to indoors. Such doses assessed for the autumn and winter are up to twice as high as the doses inhaled by commuters and pedestrians in the summer. In the winter traffic-related ultrafine particles account for over 70% of all ultrafine particles deposited in the pedestrians’ lungs. The share of traffic-related PM10 particles was estimated at approximately 33.5%. Concluding, the results of the particle concentration measurements along a road in Lublin indicated that the concentration is mainly affected by the traffic intensity and weather conditions. Further detailed research should focus on how the season and the metrological conditions affect concentration levels of traffic-related pollutants and the exposure of commuters and pedestrians as well as the inhabitants of houses located near traffic routes.

Keywords: air quality, deposition dose, health effects, vehicle emissions

Procedia PDF Downloads 91

Authors: Magno Enrique Mendoza Meza

Abstract:

This paper deals with the comparison of three control techniques: the hysteresis on-off control (HyOOC), the hybrid on-off control (HOOC) and the simple Structured Treatment Interruptions (sSTI). These techniques are applied to the mathematical model developed by Kirschner and Webb. To compare these techniques we use a cost functional that minimize the wild-type virus population and the mutant virus population, but the main objective is to minimize the systemic cost of treatment and maximize levels of healthy CD4+ T cells. HyOOC, HOOC, and sSTI are applied to the drug therapies using a reverse transcriptase and protease inhibitors; simulations show that these controls maintain the uninfected cells in a small, bounded neighborhood of a pre-specified level. The controller HyOOC and HOOC are designed by appropriate choice of virtual equilibrium points.

Keywords: virus dynamics, on-off control, hysteresis, multi-drug therapies

Procedia PDF Downloads 391

Authors: Burcu Kaya, Jan-Martin Kaiser, Karl-Friedrich Becker, Tanja Braun, Klaus-Dieter Lang

Abstract:

Quality of the molded packages is strongly influenced by the process parameters of the transfer molding. To achieve a better package quality and a stable transfer molding process, it is necessary to understand the influence of the process parameters on the package quality. This work aims to comprehend the relationship between the process parameters, and to identify the optimum process parameters for the transfer molding process in order to achieve less voids and wire sweep. To achieve this, a DoE is executed for process optimization and a regression analysis is carried out. A systematic approach is represented to generate models which enable an estimation of the number of voids and wire sweep. Validation experiments are conducted to verify the model and the results are presented.

Keywords: dielectric analysis, electronic packages, epoxy molding compounds, transfer molding process

Procedia PDF Downloads 377