Search results for: internet of things based light system

Authors: Hamed Chavoshi Pour, Javad Sadeghinejad

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The spinal cord is a long structure that starts at the end of the medulla oblongata and is located within the vertebral canal. Physiologically, the spinal cord connects the brain with the peripheral nervous system for sensory and motor activities. The cervical spinal cord is an area of particular interest in medicine and veterinary medicine due to the high prevalence of diseases in this region. This study describes the morphometric features of the cervical spinal cord in rabbits using design-unbiased stereology. The cervical spinal cords of five male rabbits were dissected, and slabs were taken according to systematic uniform random sampling. Each slab was embedded in paraffin and cut into a 6-µm thick section, and stained with cresyl violet 0.1% for stereological estimations. The total spinal cord volume, volume fraction of grey and white matter, and also dorsal and ventral horns were estimated using point counting and Cavalieri's estimator. The total cervical spinal cord volume was 0.98 ± 0.07 cm³. The relative volume of white matter and grey matter was 70.6 ± 1.7% and 29.31 ± 1.67%, respectively. The dorsal horn and ventral horn volume were 13.86 ± 1.36% and 14.9 ± 0.62% of the whole cervical spinal cord. This knowledge of rabbit spinal cord findings may serve as a foundation for a translational model in spinal cord experimental research and provide basic findings for the diagnosis and treatment of spinal cord disorders.

Keywords: stereology, spinal cord, rabbit, cervical

Procedia PDF Downloads 62

Authors: M. Aeysha Parvin, J. Asha, J. Jenifer

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This letter presents a novel frequency-shift keying(FSK) receiver using PLL-based FSK demodulator, thereby achieving high sensitivity and low power consumption. The proposed receiver comprises a power amplifier, mixer, 3-stage ring oscillator, PLL based demodulator. Moreover, the proposed receiver is fabricated using 0.12µm CMOS process and consumes 0.7Mw. Measurement results demonstrate that the proposed receiver has a sensitivity of -93dbm with 1Mbps data rate in receiving a 2.4 GHz FSK signal.

Keywords: CMOS FSK receiver, phase locked loop (PLL), 3-stage ring oscillator, FSK signal

Procedia PDF Downloads 483

Authors: Kewei Xu, Jens Friedrich, Kevin Dwinger, Wei Fan, Xijin Zhang

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Parallel Compressor Model (PCM) is a simplified approach to predict compressor performance with inlet distortions. In PCM calculation, it is assumed that the sub-compressors’ outlet static pressure is uniform and therefore simplifies PCM calculation procedure. However, if the compressor’s outlet duct is not long and straight, such assumption frequently induces error ranging from 10% to 15%. This paper provides a revised calculation method of PCM that can correct the error. The revised method employs energy equation, momentum equation and continuity equation to acquire needed parameters and replace the equal static pressure assumption. Based on the revised method, PCM is applied on two compression system with different blades types. The predictions of their performance in non-uniform inlet conditions are yielded through the revised calculation method and are employed to evaluate the method’s efficiency. Validating the results by experimental data, it is found that although little deviation occurs, calculated result agrees well with experiment data whose error ranges from 0.1% to 3%. Therefore, this proves the revised calculation method of PCM possesses great advantages in predicting the performance of the distorted compressor with limited exhaust duct.

Keywords: parallel compressor model (pcm), revised calculation method, inlet distortion, outlet unequal pressure distribution

Procedia PDF Downloads 318

Authors: Rama Seth, Luise Noring, Pratim Majumdar

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Based on an extensive literature review, this paper presents distinct approaches to value, quantify and trade ecosystem services, with particular emphasis on services provided by mangroves and wetlands. Building on diverse monetary and market-based systems for the improved allocation of natural resources, such trading and exchange-based methods can help tackle the degradation of ecosystem services in a more targeted and structured manner than achievable with stand-alone policy and administrative regulations. Using various threads of literature, the paper proposes a platform that serves as the skeletal foundation for developing an efficient global market for ecosystem services trading. The paper bridges a significant research and practice gap by recommending how to establish an equilibrium in the biosphere via trading mechanisms while also discovering other research gaps and future research potential in the domain of ecosystem valuation.

Keywords: environment, economics, mangroves, wetlands, markets, ESG, global capital, climate investments, valuation, ecosystem services

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Authors: Nikhil Jain, Bin Yu

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The material behavior of graphene, a single layer of carbon lattice, is extremely sensitive to its dielectric environment. We demonstrate improvement in electronic performance of graphene nanowire interconnects with full encapsulation by lattice-matching, chemically inert, 2D layered insulator hexagonal boron nitride (h-BN). A novel layer-based transfer technique is developed to construct the h-BN/MLG/h-BN heterostructures. The encapsulated graphene wires are characterized and compared with that on SiO2 or h-BN substrate without passivating h-BN layer. Significant improvements in maximum current-carrying density, breakdown threshold, and power density in encapsulated graphene wires are observed. These critical improvements are achieved without compromising the carrier transport characteristics in graphene. Furthermore, graphene wires exhibit electrical behavior less insensitive to ambient conditions, as compared with the non-passivated ones. Overall, h-BN/graphene/h-BN heterostructure presents a robust material platform towards the implementation of high-speed carbon-based interconnects.

Keywords: two-dimensional nanosheet, graphene, hexagonal boron nitride, heterostructure, interconnects

Procedia PDF Downloads 441

Authors: Han-Jeong Hwang, Jae-Hyun Jo, Fatemeh Alimardani

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An accurate diagnosis of psychiatric diseases is a challenging issue, in particular when distinct symptoms for different diseases are overlapped, such as delusions appeared in bipolar mood disorder (BMD) and schizophrenia (SCH). In the present study, we propose a useful way to discriminate BMD and SCH using electroencephalography (EEG). A total of thirty BMD and SCH patients (15 vs. 15) took part in our experiment. EEG signals were measured with nineteen electrodes attached on the scalp using the international 10-20 system, while they were exposed to a visual stimulus flickering at 16 Hz for 95 s. The flickering visual stimulus induces a certain brain signal, known as steady-state visual evoked potential (SSVEP), which is differently observed in patients with BMD and SCH, respectively, in terms of SSVEP amplitude because they process the same visual information in own unique way. For classifying BDM and SCH patients, machine learning technique was employed in which leave-one-out-cross validation was performed. The SSVEPs induced at the fundamental (16 Hz) and second harmonic (32 Hz) stimulation frequencies were extracted using fast Fourier transformation (FFT), and they were used as features. The most discriminative feature was selected using the Fisher score, and support vector machine (SVM) was used as a classifier. From the analysis, we could obtain a classification accuracy of 83.33 %, showing the feasibility of discriminating patients with BMD and SCH using EEG. We expect that our approach can be utilized for psychiatrists to more accurately diagnose the psychiatric disorders, BMD and SCH.

Keywords: bipolar mood disorder, electroencephalography, schizophrenia, machine learning

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Authors: Tobias Beyer, Christoph Friedrich

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Modern simulation methodology using finite element models is nowadays a recognized tool for product design/optimization. Likewise, manufacturing process design is increasingly becoming the focus of simulation methodology in order to enable sustainable results based on reduced real-life tests here as well. In this article, two process simulations -radial riveting and roller burnishing- used for mechanical joining of components are explained. In the first step, the required boundary conditions are developed and implemented in the respective simulation models. This is followed by process space validation. With the help of the validated models, the interdependencies of the input parameters are investigated and evaluated by means of sensitivity analyses. Limit case investigations are carried out and evaluated with the aid of the process simulations. Likewise, a comparison of the two joining methods to each other becomes possible.

Keywords: FEM, model-based process development, process simulation, radial riveting, roller burnishing, sensitivity analysis

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Authors: Reza Dinarvand, Mahdi Sadeghian, Somaye Sadeghian

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Prediction of the ultimate bearing capacity of piles (Qu) is one of the basic issues in geotechnical engineering. So far, several methods have been used to estimate Qu, including the recently developed artificial intelligence methods. In recent years, optimization algorithms have been used to minimize artificial network errors, such as colony algorithms, genetic algorithms, imperialist competitive algorithms, and so on. In the present research, artificial neural networks based on colonial competition algorithm (ANN-ICA) were used, and their results were compared with other methods. The results of laboratory tests of short piles in clayey soils with parameters such as pile diameter, pile buried length, eccentricity of load and undrained shear resistance of soil were used for modeling and evaluation. The results showed that ICA-based artificial neural networks predicted lateral bearing capacity of short piles with a correlation coefficient of 0.9865 for training data and 0.975 for test data. Furthermore, the results of the model indicated the superiority of ICA-based artificial neural networks compared to back-propagation artificial neural networks as well as the Broms and Hansen methods.

Keywords: artificial neural network, clayey soil, imperialist competition algorithm, lateral bearing capacity, short pile

Procedia PDF Downloads 133

Authors: Dhvanidevi N. Jadeja, Daya S. Kaul, Anurag A. Kandya

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Municipal Solid Waste (MSW) collection in a city is performed in less effective manner which results in the poor management of the environment and natural resources. Municipal corporation does not possess efficient waste management and recycling programs because of the complex task involving many factors. Solid waste collection system depends upon various factors such as manpower, number and size of vehicles, transfer station size, dustbin size and weight, on-road traffic, and many others. These factors affect the collection cost, energy and overall municipal tax for the city. Generally, different types of waste are scattered throughout the city in a heterogeneous way that poses changes for efficient collection of solid waste. Efficient waste collection and transportation strategy must be effectively undertaken which will include optimization of routes, volume of waste, and manpower. Being these optimized, the overall cost can be reduced as the fuel and energy requirements would be less and also the municipal waste taxes levied will be less. To carry out the optimization study of collection system various data needs to be collected from the Ahmedabad municipal corporation such as amount of waste generated per day, number of workers, collection schedule, road maps, number of transfer station, location of transfer station, number of equipment (tractors, machineries), number of zones, route of collection etc. The ArcGis Network Analyst is introduced for the best routing identification applied in municipal waste collection. The simulation consists of scenarios of visiting loading spots in the municipality of Ahmedabad, considering dynamic factors like network traffic changes, closed roads due to natural or technical causes. Different routes were selected in a particular area of Ahmedabad city, and present routes were optimized to reduce the length of the routes, by using ArcGis Network Analyst. The result indicates up to 35% length minimization in the routes.

Keywords: collection routes, efficiency, municipal solid waste, optimization

Procedia PDF Downloads 122

Authors: Huang Dennis, Aurelio Aziel, Burra Venkata Durga Kumar

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Nowadays, smartphones and mobile operating systems have been popularly widespread in our daily lives. As people use smartphones, they tend to store more private and essential data on their devices, because of this it is very important to develop more secure mobile operating systems and cloud storage to secure the data. However, several factors can cause security risks in mobile operating systems such as malware, malicious app, phishing attacks, ransomware, and more, all of which can cause a big problem for users as they can access the user's private data. Those problems can cause data loss, financial loss, identity theft, and other serious consequences. Other than that, during the pandemic, people will use their mobile devices more and do all sorts of transactions online, which may lead to more victims of online scams and inexperienced users being the target. With the increase in attacks, researchers have been actively working to develop several countermeasures to enhance the security of operating systems. This study aims to provide an overview of the security and privacy issues in mobile operating systems, identifying the potential risk of operating systems, and the possible solutions. By examining these issues, we want to provide an easy understanding to users and researchers to improve knowledge and develop more secure mobile operating systems.

Keywords: mobile operating system, security, privacy, Malware

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Authors: Shivalaxmi Arumugham

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Child sexual abuse (CSA) has taken several forms, particularly with the advent of internet technologies that provide pedophiles access to their targets anonymously at an affordable rate. To combat CSA which has far-reaching consequences on the physical and psychological health of the victims, a special act, the Protection of Children from Sexual Offences (POCSO) Act, was formulated amongst the existing laws. With its latest amendment criminalizing various online activities about child pornography also known as child sexual abuse materials in 2019, tremendous pressure is speculated on law enforcement to identify offenders online. Effective investigations of CSA cases help in not only to detect perpetrators but also in preventing the re-victimization of children. Understanding the vulnerability of the child population and that the offenders continue to develop stealthier strategies to operate, it is high time that traditional investigation, where the focus is on apprehending and prosecuting the offender, must make a paradigm shift to proactively investigate to prevent victimization at the first place. One of the proactive policing techniques involves understanding the psychology of the offenders and children and operating undercover to catch the criminals before a real child is victimized. With the fundamental descriptive approach to research, the article attempts to identify the multitude of issues associated with the investigation of child sexual abuse cases currently in practice in India. Then, the article contextualizes the various covert operations carried out by numerous law enforcement agencies across the globe. To provide this comprehensive overview, the paper examines various reports, websites, guidelines, protocols, judicial pronouncements, and research articles. Finally, the paper presents the challenges and ethical issues that are to be considered before getting into undercover operations either in the guise of a pedophile or as a child. The research hopes to contribute to the making of standard operating protocols for investigation officers and other relevant policymakers in this regard.

Keywords: child sexual abuse, cybercrime against children, covert police operations, investigation of CSA

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Authors: Giovanni Meloni

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Recent results are presented from experiments carried out at the Advanced Light Source (ALS) at the Chemical Dynamics Beamline of Lawrence Berkeley National Laboratory using multiplexed synchrotron photoionization mass spectrometry. The reaction mixture and a buffer gas (He) are introduced through individually calibrated mass flow controllers into a quartz slow flow reactor held at constant pressure and temperature. The gaseous mixture effuses through a 650 μm pinhole into a 1.5 mm skimmer, forming a molecular beam that enters a differentially pumped ionizing chamber. The molecular beam is orthogonally intersected by a tunable synchrotron radiation produced by the ALS in the 8-11 eV energy range. Resultant ions are accelerated, collimated, and focused into an orthogonal time-of-flight mass spectrometer. Reaction species are identified by their mass-to-charge ratios and photoionization (PI) spectra. Comparison of experimental PI spectra with literature and/or simulated curves is routinely done to assure the identity of a given species. With the aid of electronic structure calculations, potential energy surface scans are performed, and Franck-Condon spectral simulations are obtained. Examples of these experiments are discussed, ranging from new intermediates characterization to reaction mechanisms elucidation and biofuels oxidation pathways identification.

Keywords: mass spectrometry, reaction intermediates, synchrotron photoionization, oxidation reactions

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Authors: Mohd Nizam Osman

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This study explores issues and challenges of information and communication technology (ICT) adoption and application for business-related performance of Agro-based small and medium-scale enterprises (SMEs) in the state of Selangor, Malaysia. Globally, SMEs have championed the socio-economic development of nations across the globe, including Malaysia. Thus, the objectives of this study explore issues and challenges of agro-based SMEs' adoption and usage of ICT, the business-related performance of SMEs via the adoption of ICT, and the impact of incentives on SMEs' adoption and use of ICT. The study was conducted in Selangor, Malaysia. A qualitative research approach was deployed for the study. Data for the study emanated from semi-structured interviews and field note observation of 14 informants who are registered as small-scale business owners and operators. Based on thematic analysis, data were triangulated to ensure consistency and validation of findings for the study. Findings revealed that SMEs are faced with a lack of funding, low expertise, and lack of storage, leading to an unsustainable supply of goods and services. Although effective communication, ease of business activities/transactions, and information search by way of research were among the business performance experienced by SMEs' adoption of ICT. Further findings showed that loan conditions and personal and business interests hindered SMEs' reception and access to programs, schemes, and incentives geared at aiding the continuous growth and development of agro-based SMEs. The study suggests the need for policy change in terms of diversification of channels of funding and access to funds to enable credit guarantee schemes and peer or community-based financing. Consequently, the study recommends the engagement of SMEs in policy decision-making to ascertain the type of incentives relevant to their business operations. Likewise, from a technological standpoint, the study suggests the expansion of the framework of technology acceptance with focuses on affordability, type of users, and level of usage.

Keywords: ICT adoption, business related performance, agro-based SMEs, ICT application for SMEs

Procedia PDF Downloads 64

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

Procedia PDF Downloads 100

Authors: Hebah M. Musalem, Jeylan El-Mansoury, Lin M. Tuleimat, Selwa Alhazza, Abdul-Aziz A. Al Zoba

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Background: Amblyopia is a condition that affects the visual system triggering a decrease in visual acuity without a known underlying pathology. It is due to abnormal vision development in childhood or infancy. Most importantly, vision loss is preventable or reversible with the right kind of intervention in most of the cases. Strabismus, sensory defects, and anisometropia are all well-known causes of amblyopia. However, ocular misalignment in Strabismus is considered the most common form of amblyopia worldwide. The risk of developing amblyopia increases in premature children, developmentally delayed or children who had brain lesions affecting the visual pathway. The prevalence of amblyopia varies between 2 to 5 % in the world according to the literature. Objective: To determine the different causes of Amblyopia in pediatric patients seen in ophthalmology clinic of a tertiary care center, i.e. King Faisal Specialist Hospital and Research Center (KFSH&RC). Methods: This is a hospital based, random retrospective, based on reviewing patient’s files in the Ophthalmology Department of KFSH&RC in Riyadh city, Kingdom of Saudi Arabia. Inclusion criteria: amblyopic pediatric patients who attended the clinic from 2015 to 2016, who are between 6 months and 18 years old. Exclusion Criteria: patients above 18 years of age and any patient who is uncooperative to obtain an accurate vision or a proper refraction. Detailed ocular and medical history are recorded. The examination protocol includes a full ocular exam, full cycloplegic refraction, visual acuity measurement, ocular motility and strabismus evaluation. All data were organized in tables and graphs and analyzed by statistician. Results: Our preliminary results will be discussed on spot by our corresponding author. Conclusions: We focused on this study on utilizing various examination techniques which enhanced our results and highlighted a distinguished correlation between amblyopia and its’ causes. This paper recommendation emphasizes on critical testing protocols to be followed among amblyopic patient, especially in tertiary care centers.

Keywords: amblyopia, amblyopia causes, amblyopia diagnostic criterion, amblyopia prevalence, Saudi Arabia

Procedia PDF Downloads 144

Authors: Jeroen Rotteveel, Zeger De Groot

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The small satellite community is more and more aware of the need to start operating responsibly and sustainably in order to secure the use of outer space in the long run. On the technical side, many debris mitigation techniques have been investigated and demonstrated on board small satellites, showing that technically, a lot of things can be done to curb the growth of space debris and operate more responsible. However, in the absence of strict laws and constraints, one cannot help but wonder what the incentive is to incur significant costs (paying for debris mitigation systems and the launch mass of these systems) and to lose performance onboard resource limited small satellites (mass, volume, power)? Many small satellite developers are operating under tight budgets, either from their sponsors (in case of academic and research projects) or from their investors (in case of startups). As long as it is not mandatory to act more responsibly, we might need to consider the implementation of incentives to stimulate developers to accommodate deorbiting modules, etc. ISISPACE joined the NetZeroSpace initiative in 2021 with the aim to play its role in secure the use of low earth orbit for the next decades by facilitating more sustainable use of space. The company is in a good position as both a satellite builder, a rideshare launch provider, and a technology development company. ISISPACE operates under one of the stricter space laws in the world in terms of maximum orbital lifetime and has been active in various debris mitigation and debris removal in-orbit demonstration missions in the past 10 years. ISISPACE proposes to introduce together with launch partners and regulators an incentive scheme for CubeSat developers to baseline debris mitigation systems on board their CubeSats in such a way that is does not impose too many additional costs to the project. Much like incentives to switch to electric cars or install solar panels on your house, such an incentive can help to increase market uptake of behavior or solutions prior to legislation or bans of certain practices. This can be achieved by: Introducing an extended launch volume in CubeSat deployers to accommodate debris mitigation systems without compromising available payload space for the payload of the main mission Not charging the fee for the launch mass for the additional debris mitigation module Whenever possible, find ways to further co-fund the purchase price, or otherwise reduce the cost of flying debris mitigation modules onboard the CubeSats. The paper will outline the framework of such an incentive scheme and provides ISISPACE’s way forward to make this happen in the near future.

Keywords: netZerospace, cubesats, debris mitigation, small satellite community

Procedia PDF Downloads 140

Authors: Mohammadhadi Mirmohammadi, Reza Safian, Hossein Haddad

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This paper presents an innovative solution for complex multi-objective optimization problem which is a part of efforts toward maximizing rolling mill throughput and minimizing processing costs in tandem cold rolling. This computational intelligence based optimization has been applied to the rolling schedules of tandem cold rolling mill. This method involves the combination of two derivative-free optimization procedures in the form of nested loops. The first optimization loop is based on Improving Hit and Run method which focus on balance of power, force and reduction distribution in rolling schedules. The second loop is a real-coded genetic algorithm based optimization procedure which optimizes energy consumption and productivity. An experimental result of application to five stand tandem cold rolling mill is presented.

Keywords: derivative-free optimization, Improving Hit and Run method, real-coded genetic algorithm, rolling schedules of tandem cold rolling mill

Procedia PDF Downloads 682

Authors: Michael Smalenberger

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Intelligent tutoring systems (ITS) are computer-based platforms which can incorporate artificial intelligence to provide step-by-step guidance as students practice problem-solving skills. ITS can replicate the benefits of one-on-one tutoring, foster transactivity in collaborative environments, and lead to substantial learning gains when used to supplement the instruction of a teacher or when used as the sole method of instruction. Developments improving the ease of ITS creation have recently increased their proliferation, leading many K-12 schools and institutions of higher education in the United States to regularly use ITS within classrooms. We investigated how students perceive their experience using an ITS. In this study, 111 undergraduate students used an ITS in a college-level introductory statistics course and were subsequently asked for feedback on their experience. Results show that their perceptions were generally favorable of the ITS, and most would seek to use an ITS both for STEM and non-STEM courses in the future. Along with detailed transaction-level data, this feedback also provides insights on the design of user-friendly interfaces, guidance on accessibility for students with impairments, the sequencing of exercises, students’ expectation of achievement, and comparisons to other tutoring experiences. We discuss how these findings are important for the creation, implementation, and evaluation of ITS as a mode and method of teaching and learning.

Keywords: college statistics course, intelligent tutoring systems, in vivo study, student perceptions of tutoring

Procedia PDF Downloads 88

Authors: Naik Muhammad, Zahid Ullah, Dong-Ho Choi

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Submerged floating tunnel (SFT) is a new solution for the transportation infrastructure through sea straits, fjords, and inland waters, and can be a good alternative to long span suspension bridges. SFT is a massive cylindrical structure that floats at a certain depth below the water surface and subjected to extreme environmental conditions. The identification of dominant structural response of SFT becomes more important due to intended environmental conditions for the design of SFT. The time domain dynamic problem of SFT moored by vertical and inclined mooring cables/anchors is formulated. The dynamic time history analysis of SFT subjected to hydrodynamic and seismic excitations is performed. The SFT is modeled by finite element 3D beam, and the mooring cables are modeled by truss elements. Based on the dynamic time history analysis the displacements and internal forces of SFT were calculated. The response of SFT is presented for hydrodynamic and seismic excitations. The transverse internal forces of SFT were the maximum compared to vertical direction, for both hydrodynamic and seismic cases; this indicates that the cable system provides very small stiffness in transverse direction as compared to vertical direction of SFT.

Keywords: submerged floating tunnel, hydrodynamic analysis, time history analysis, seismic response

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Authors: Mandana Hoseini

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During last decades, intensive selection for higher growth rate in broiler chickens has accelerated daily body weight gain, which this has changed/increased the trends and amounts of nutrient requirements in the diet. As a result, considerable studies have been focused on the better determination of protein/amino acids requirements in modern broiler diets. One approach to minimize dietary crude protein inclusion levels is substitution of some of the dietary crude protein with synthetic amino acids. In addition, using synthetic forms of limiting essential amino acids in the diet could help better coincidence of dietary protein with ideal protein concept, which this in turn, minimizes nitrogen dissipation and environmental pollution. Threonine is usually considered as the third limiting amino acid in broiler diets. Recent studies have been demonstrated that dietary supplemental threonine would optimize growth performance, immune system, intestinal morphology, as well as oxidative defense in broiler chickens. In this review, threonine metabolism and its effects in relation with different aspects of broiler performance have been discussed.

Keywords: immune system, intestine, performance, requirement, threonine

Procedia PDF Downloads 91

Authors: Prabhsharan Singh, Rahul Sindhu, Piyush Sikka

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The steering system is an integral part and medium through which the driver communicates with the vehicle and terrain, hence the most suitable steering geometry as per requirements must be chosen. The function of the chosen steering geometry of an All-Terrain Vehicle (ATV) is to provide the desired understeer gradient, minimum tire slippage, expected weight transfer during turning as these are requirements for a good steering geometry of a BAJA ATV. This research paper focuses on choosing the best suitable steering geometry for BAJA ATV tracks by reasoning the working principle and using fundamental trigonometric functions for obtaining these geometries on the same vehicle itself, namely Ackermann, Anti- Ackermann, Parallel Ackermann. Full vehicle analysis was carried out on Adams Car Analysis software, and graphical results were obtained for various parameters. Steering geometries were achieved by using a single versatile knuckle for frontward and rearward tie-rod placement and were practically tested with the help of data acquisition systems set up on the ATV. Each was having certain characteristics, setup, and parameters were observed for the BAJA ATV, and correlations were created between analytical and practical values.

Keywords: all-terrain vehicle, Ackermann, Adams car, Baja Sae, steering geometry, steering system, tire slip, traction, understeer gradient

Procedia PDF Downloads 138

Authors: M. S. Said, J. A. Ghani, Izzati Osman, Z. A. Latiff, S. A .F. Syed Mohd

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Metal matrix composites have demand for light-weight structural and functional materials. MMCs have been shown to offer improvements in strength, rigidity, temperature stability, wear resistance, reliability and control of physical properties such as density and coefficient of thermal expansion, thereby providing improved engineering performance in comparison to the un-reinforced matrix. Experiment were conducted at various cutting speed, feed rate and difference cutting tools according to Taguchi method using a standard orthogonal array L9. The volume of AlN reinforced particle was 10% in MMC. The milling process was carried out under dry cutting condition using uncoated carbide, TiN and TiCN tool insert. The parameters used were the cutting speed of (230,300,370 m/min) the federate used were (0.4, 0.6, 0.8 mm/tooth) while the depth of cut is constant (0.3 mm). The tool diameter is 20mm. From the project, the surface roughness mechanism was investigated in detail using Mitutoyo portable surface roughness measurements surftest SJ-310. This machining will be fabricated on MMC with 150mm length, 100mm width and 30mm thick. The results showed using S/N ratio, concluded that a combination of low cutting speed, medium feed rate and uncoated insert give a remarkable surface finish. From the ANOVA result showed the feed rate was major contributing factor (43.76%) following type of insert (40.89%).

Keywords: MMC, milling operation and surface roughness, Taguchi method

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Authors: Wadzani Dauda Palnam, Alao S. Emmanuel Laykay, Afiniki Bawa Zarafi, Olufunmilola Alabi, Dora N. Iortsuun

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Onion production is affected by several diseases including fusariosis. Study was conducted to investigate the histopathological features of different onion tissues infected with Fusarium equiseti by inoculation with soil drench, root dip and mycelia paste methods. This was carried out by fixation, dehydration, clearing, wax embedding, sectioning, staining and mounting of leaf and root sections for microscopical examination at 400x. Once infection occurred in the roots, the pathogen moved through the vascular system to colonize the whole plant. At first, it grew in the intercellular spaces of the root cortex but soon invaded the cells, followed by colonization of the cells by its hyphae and microconidia. At later stages of infection, the cortex tissue became completely disorganized and decomposed as the pathogen advance to the shoot system via the vessel elements; this may be responsible for the early wilting symptom of infected plants arising from the severe water stress due to blockage of the xylem tissues.

Keywords: onion, histopathology, infection, fusaria, inoculation

Procedia PDF Downloads 264

Authors: Yanting Cao, Kazumitsu Nawata

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As smartphones upgrading, their software and hardware are getting smarter, so the smartphone-based human activity recognition will be described as more refined, complex, and detailed. In this context, we analyzed a set of experimental data obtained by observing and measuring 30 volunteers with six activities of daily living (ADL). Due to the large sample size, especially a 561-feature vector with time and frequency domain variables, cleaning these intractable features and training a proper model becomes extremely challenging. After a series of feature selection and parameters adjustment, a well-performed SVM classifier has been trained.

Keywords: smart sensors, human activity recognition, artificial intelligence, SVM

Procedia PDF Downloads 133

Authors: Bruno S. Soria, Mauricio R. Policena, Andre J. Souza

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The state of the cutting tool is an important factor to consider during machining to achieve a good surface quality. The vibration generated during material cutting can also directly affect the surface quality and life of the cutting tool. In this work, the effect of mechanical broken failure (MBF) on carbide insert tools during face milling of AISI 304 stainless steel was evaluated using three levels of feed rate and two spindle speeds for each tool condition: three carbide inserts have perfect geometry, and three other carbide inserts have MBF. The axial and radial depths remained constant. The cutting forces were determined through a sensory system that consists of a piezoelectric dynamometer and data acquisition system. Discrete Wavelet Transform was used to separate the static part of the signals of force and vibration. The roughness of the machined surface was analyzed for each machining condition. The MBF of the tool increased the intensity and force of vibration and worsened the roughness factors.

Keywords: face milling, stainless steel, tool condition monitoring, wavelet discrete transform

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Authors: Omoruyi G. Idemudia, Alexander P. Sadimenko

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The need for the development of new sustainable bioactive compounds with unique properties that can become potential replacement for commonly used medicinal drugs has continued to gain tremendous research concerns because of the problems of disease resistant to these medicinal drugs and their toxicity effects. NOS-donor heterocycles are particularly of interest as they have showed good pharmacological activities in the midst of their interesting chelating properties towards metal ions, an important characteristic for transition metal based drugs design. These new compounds have also gained application as dye sensitizers in solar cell panels for the generation of renewable solar energy, as greener water purification polymer for supply and management of clean water and as catalysts which are used to reduce the amount of pollutants from industrial reaction processes amongst others, because of their versatile properties. Di-ketone acylpyrazolones and their azomethine schiff bases have been employed as pharmaceuticals as well as analytical reagents, and their application as transition metal complexes have being well established. In this research work, a new 4-propyl-3-methyl-1-phenyl-2-pyrazolin-5-one-thiosemicarbazone was synthesized from the reaction of 4-propyl-3-methyl-1-phenyl-2-pyrazolin-5-one and thiosemicarbazide in methanol. The pure isolate of the thiosemicarbazone was further reacted with aqueous solutions of palladium and platinum salts to obtain their metal complexes, in an effort towards the discovery of transition metal based synthetic drugs. These compounds were characterized by means of analytical, spectroscopic, thermogravimetric analysis TGA, as well as x-ray crystallography. 4-propyl-3-methyl-1-phenyl-2-pyrazolin-5-one thiosemicarbazone crystallizes in a triclinic crystal system with a P-1 (No. 2) space group according to x-ray crystallography. The tridentate NOS ligand formed a tetrahedral geometry on coordinating with metal ions. Reported compounds showed varying antioxidant free radical scavenging activities against 2, 2-diphenyl-1-picrylhydrazyl DPPH radical at 100, 200, 300, 400 and 500 µg/ml concentrations. The platinum complex have shown a very good antioxidant property against DPPH with an IC50 of 76.03 µg/ml compared with standard ascorbic acid (IC50 of 74.66 µg/ml) and as such have been identified as a potential anticancer candidate.

Keywords: acylpyrazolone, free radical scavenging activities, tridentate ligand, x-ray crystallography

Procedia PDF Downloads 170

Authors: Hui-Chuan Lu

Abstract:

In a perfect secret-sharing scheme, a dealer distributes a secret among a set of participants in such a way that only qualified subsets of participants can recover the secret and the joint share of the participants in any unqualified subset is statistically independent of the secret. The access structure of the scheme refers to the collection of all qualified subsets. In a graph-based access structures, each vertex of a graph G represents a participant and each edge of G represents a minimal qualified subset. The average information ratio of a perfect secret-sharing scheme realizing a given access structure is the ratio of the average length of the shares given to the participants to the length of the secret. The infimum of the average information ratio of all possible perfect secret-sharing schemes realizing an access structure is called the optimal average information ratio of that access structure. We study the optimal average information ratio of the access structures based on bipartite graphs. Based on some previous results, we give a bound on the optimal average information ratio for all bipartite graphs of girth at least six. This bound is the best possible for some classes of bipartite graphs using our approach.

Keywords: secret-sharing scheme, average information ratio, star covering, deduction, core cluster

Procedia PDF Downloads 349

Authors: Ayman Baklizi

Abstract:

This paper discusses the problem of testing hypotheses about the lifetime distributions of a matched pair based on censored data. A distribution free test based on a runs statistic is proposed. Its null distribution and power function are found in a simple convenient form. Some properties of the test statistic and its power function are studied.

Keywords: censored data, distribution free, matched pair, runs statistics

Procedia PDF Downloads 275

Authors: Yan Cheng, Yijun Shao, James Rudolph, Charlene R. Weir, Beth Sahlmann, Qing Zeng-Treitler

Abstract:

Supervised predictive models require labeled data for training purposes. Complete and accurate labeled data, i.e., a ‘gold standard’, is not always available, and imperfectly labeled data may need to serve as an alternative. An important question is if the accuracy of the labeled data creates a performance ceiling for the trained model. In this study, we trained several models to recognize the presence of delirium in clinical documents using data with annotations that are not completely accurate (i.e., weakly-supervised learning). In the external evaluation, the support vector machine model with a linear kernel performed best, achieving an area under the curve of 89.3% and accuracy of 88%, surpassing the 80% accuracy of the training sample. We then generated a set of simulated data and carried out a series of experiments which demonstrated that models trained on imperfect data can (but do not always) outperform the accuracy of the training data, e.g., the area under the curve for some models is higher than 80% when trained on the data with an error rate of 40%. Our experiments also showed that the error resistance of linear modeling is associated with larger sample size, error type, and linearity of the data (all p-values < 0.001). In conclusion, this study sheds light on the usefulness of imperfect data in clinical research via weakly-supervised learning.

Keywords: weakly-supervised learning, support vector machine, prediction, delirium, simulation

Procedia PDF Downloads 179

Authors: Salim Khan

Abstract:

The attainment of the carbon neutrality objective and Sustainable Development Goal 13 (SDG-13) target, which pertains to climate actions, received widespread attention in developing and emerging nations. Given the increasing pace of urbanization, technological advancements, and rapid growth, it is imperative to examine the linear and nonlinear effects of urbanization and economic growth and the linear impact of information and communication technology (ICT) on carbon emissions (CO2e). This study employs the Dynamic System GMM (DSGMM) and Panel Quantile Regression (PQR) methodologies to investigate the causal relationship between urbanization, ICT, economic growth, and their interplay on CO2e in 39 BRI countries from 2001 to 2020. The study's findings indicate that the impact of urbanization on CO2e exhibits linear and nonlinear patterns. The specific nonlinear impact of urbanization leads to a decrease in CO2e, hence facilitating the achievement of carbon neutrality and contributing to SDG-13. The study highlights the importance of ICT in achieving SDG-13 by reducing CO2e, emphasizing the need for informatization. Simultaneously, the findings support the Environmental Kuznets Curve (EKC) hypothesis and support the pollution haven theory. Finally, based on empirical findings, significant policy implications are suggested for achieving SGD 13 and carbon neutrality.

Keywords: urbanization, ICT, CO2 emission, EKC, pollution haven, BRI

Procedia PDF Downloads 5