Search results for: mobile node dynamics

Authors: Mohkammad Nur Cahyadi, Hepi Hapsari Handayani, Agus Budi Raharjo, Ronny Mardianto, Daud Wahyu Imani, Arizal Bawazir, Luki Adi Triawan

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PDAM (local water company) determines customer charges by considering the customer's building or house. Charges determination significantly affects PDAM income and customer costs because the PDAM applies a subsidy policy for customers classified as small households. Periodic updates are needed so that pricing is in line with the target. A thorough customer survey in Surabaya is needed to update customer building data. However, the survey that has been carried out so far has been by deploying officers to conduct one-by-one surveys for each PDAM customer. Surveys with this method require a lot of effort and cost. For this reason, this research offers a technology called moblie mapping, a mapping method that is more efficient in terms of time and cost. The use of this tool is also quite simple, where the device will be installed in the car so that it can record the surrounding buildings while the car is running. Mobile mapping technology generally uses lidar sensors equipped with GNSS, but this technology requires high costs. In overcoming this problem, this research develops low-cost mobile mapping technology using a webcam camera sensor added to the GNSS and IMU sensors. The camera used has specifications of 3MP with a resolution of 720 and a diagonal field of view of 78⁰. The principle of this invention is to integrate four camera sensors, a GNSS webcam, and GPS to acquire photo data, which is equipped with location data (latitude, longitude) and IMU (roll, pitch, yaw). This device is also equipped with a tripod and a vacuum cleaner to attach to the car's roof so it doesn't fall off while running. The output data from this technology will be analyzed with artificial intelligence to reduce similar data (Cosine Similarity) and then classify building types. Data reduction is used to eliminate similar data and maintain the image that displays the complete house so that it can be processed for later classification of buildings. The AI method used is transfer learning by utilizing a trained model named VGG-16. From the analysis of similarity data, it was found that the data reduction reached 50%. Then georeferencing is done using the Google Maps API to get address information according to the coordinates in the data. After that, geographic join is done to link survey data with customer data already owned by PDAM Surya Sembada Surabaya.

Keywords: mobile mapping, GNSS, IMU, similarity, classification

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Authors: Elsayeda M. Elgaml, Dina M. Ibrahim, Elsayed A. Sallam

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Association rule mining is one of the most important fields of data mining and knowledge discovery. In this paper, we propose an efficient multiple support frequent pattern growth algorithm which we called “MSFP-growth” that enhancing the FP-growth algorithm by making infrequent child node pruning step with multiple minimum support using maximum constrains. The algorithm is implemented, and it is compared with other common algorithms: Apriori-multiple minimum supports using maximum constraints and FP-growth. The experimental results show that the rule mining from the proposed algorithm are interesting and our algorithm achieved better performance than other algorithms without scarifying the accuracy.

Keywords: association rules, FP-growth, multiple minimum supports, Weka tool

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Authors: Mohamed Elhakeem, A. N. Thanos Papanicolaou, Christopher Wilson, Yi-Jia Chang

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In this study, a physically-based, modelling framework was developed to predict saturated hydraulic conductivity (KSAT) dynamics in the Clear Creek Watershed (CCW), Iowa. The modelling framework integrated selected pedotransfer functions and watershed models with geospatial tools. A number of pedotransfer functions and agricultural watershed models were examined to select the appropriate models that represent the study site conditions. Models selection was based on statistical measures of the models’ errors compared to the KSAT field measurements conducted in the CCW under different soil, climate and land use conditions. The study has shown that the predictions of the combined pedotransfer function of Rosetta and the Water Erosion Prediction Project (WEPP) provided the best agreement to the measured KSAT values in the CCW compared to the other tested models. Therefore, Rosetta and WEPP were integrated with the Geographic Information System (GIS) tools for visualization of the data in forms of geospatial maps and prediction of KSAT variability in CCW due to the seasonal changes in climate and land use activities.

Keywords: saturated hydraulic conductivity, pedotransfer functions, watershed models, geospatial tools

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Authors: Radhe Tado, Ashish B. Deoghare, K. M. Pandey

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The aim of this study is to estimate the effect of blood flow through the coronary artery in human heart so as to assess the coronary artery disease.Velocity, wall shear stress (WSS), strain rate and wall pressure distribution are some of the important hemodynamic parameters that are non-invasively assessed with computational fluid dynamics (CFD). These parameters are used to identify the mechanical factors responsible for the plaque progression and/or rupture in left coronary arteries (LCA) in coronary arteries.The initial step for CFD simulations was the construction of a geometrical model of the LCA. Patient specific artery model is constructed using computed tomography (CT) scan data with the help of MIMICS Research 19.0. For CFD analysis ANSYS FLUENT-14.5 is used.Hemodynamic parameters were quantified and flow patterns were visualized both in the absence and presence of coronary plaques. The wall pressure continuously decreased towards distal segments and showed pressure drops in stenotic segments. Areas of high WSS and high flow velocities were found adjacent to plaques deposition.

Keywords: angiography, computational fluid dynamics (CFD), time-average wall shear stress (TAWSS), wall pressure, wall shear stress (WSS)

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Authors: Hassan Nour, Nouh Mounadi, Oussama Abchir, Belaidi Salah, Samir Chtita

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Cholinesterase enzymes are biological catalysts essential for the transformation of acetylcholine, which is a neurotransmitter implicated in memory and learning, into acetic acid and choline, altering the neurotransmission process in Alzheimer’s disease patients. Therefore, inhibition of cholinesterase enzymes is a relevant strategy for the symptomatic treatment of Alzheimer’s disease. The current investigation aims to explore potential cholinesterase (ChE) inhibitors through a comprehensive computational approach. Forty-nine phytoconstituents extracted from Cannabis sativa L. were in-silico screened using molecular docking and pharmacokinetic and toxicological analysis to evaluate their possible inhibitory effect on the cholinesterase enzymes. Two phytoconstituents belonging to cannabinoid derivatives were revealed to be promising candidates for Alzheimer's therapy by acting as cholinesterase inhibitors. They have exhibited high binding affinities towards the cholinesterase enzymes and showed their ability to interact with key residues involved in cholinesterase enzymatic activity. In addition, they presented good ADMET profiles allowing them to be promising oral drug candidates. Furthermore, molecular dynamics (MD) simulations were executed to explore their interaction stability under mimetic biological conditions and thus support our findings. To corroborate the docking results, the binding free energy corresponding to the more stable ligand-ChE complexes was re-estimated by applying the MM-PBSA method. MD and MM-PBSA studies affirmed that the ligand-ChE recognition is a spontaneous reaction leading to stable complexes. The conducted investigations have led to great findings that would strongly guide the pharmaceutical industries toward the rational development of potent anti-Alzheimer agents.

Keywords: Alzheimer’s disease, molecular docking, Cannabis sativa L., cholinesterase inhibitors, molecular dynamics, ADMET, MM-PBSA

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Authors: Gagnesh Kumar, Prashant Gupta

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This paper investigates the performance of the bundle of single wall carbon nanotubes (SWCNT) for low-power and high-speed interconnects for future VLSI applications. The power dissipation, delay and power delay product (PDP) of SWCNT bundle interconnects are examined and compared with that of the Cu interconnects at 22 nm technology node for both intermediate and global interconnects. The results show that SWCNT bundle consume less power and also faster than Cu for intermediate and global interconnects. It is concluded that the metallic SWCNT has been regarded as a viable candidate for intermediate and global interconnects in future technologies.

Keywords: carbon nanotube, SWCNT, low power, delay, power delay product, global and intermediate interconnects

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Authors: Bruno Biagianti, Angela Tseng, Kathy Wannaviroj, Allison Corlett, Megan DuBois, Kyu Lee, Suma Jacob

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Background: ASD is characterized by pervasive Sensory Processing Abnormalities (SPA) and social cognitive deficits that persist throughout the course of the illness and have been linked to functional abnormalities in specific neural systems that underlie the perception, processing, and representation of sensory information. SPA and social cognitive deficits are associated with difficulties in interpersonal relationships, poor development of social skills, reduced social interactions and lower academic performance. Importantly, they can hamper the effects of established evidence-based psychological treatments—including PEERS (Program for the Education and Enrichment of Relationship Skills), a parent/caregiver-assisted, 16-weeks social skills intervention—which nonetheless requires a functional brain capable of assimilating and retaining information and skills. As a matter of fact, some adolescents benefit from PEERS more than others, calling for strategies to increase treatment response rates. Objective: We will present interim data on CICADAS (Care Improving Cognition for ADolescents on the Autism Spectrum)—a clinician-assisted, closed-loop technology mobile application for adolescents with ASD. Via ten mobile assessments, CICADAS captures data on sensory processing abnormalities and associated cognitive deficits. These data populate a machine learning algorithm that tailors the delivery of ten neuroplasticity-based social cognitive training (NB-SCT) exercises targeting sensory processing abnormalities. Methods: In collaboration with the Autism Spectrum and Neurodevelopmental Disorders Clinic at the University of Minnesota, we conducted a fully remote, three-arm, randomized crossover trial with adolescents with ASD to document the acceptability of CICADAS and evaluate its potential as a stand-alone treatment or as a treatment enhancer of PEERS. Twenty-four adolescents with ASD (ages 11-18) have been initially randomized to 16 weeks of PEERS + CICADAS (Arm A) vs. 16 weeks of PEERS + computer games vs. 16 weeks of CICADAS alone (Arm C). After 16 weeks, the full battery of assessments has been remotely administered. Results: We have evaluated the acceptability of CICADAS by examining adherence rates, engagement patterns, and exit survey data. We found that: 1) CICADAS is able to serve as a treatment enhancer for PEERS, inducing greater improvements in sensory processing, cognition, symptom reduction, social skills and behaviors, as well as the quality of life compared to computer games; 2) the concurrent delivery of PEERS and CICADAS induces greater improvements in study outcomes compared to CICADAS only. Conclusion: While preliminary, our results indicate that the individualized assessment and treatment approach designed in CICADAS seems effective in inducing adaptive long-term learning about social-emotional events. CICADAS-induced enhancement of processing and cognition facilitates the application of PEERS skills in the environment of adolescents with ASD, thus improving their real-world functioning.

Keywords: ASD, social skills, cognitive training, mobile app

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Authors: Mohamed Saeed Ahmed Salman

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The aim of this Current Study is to reveals the impact of Transformational Leadership on Organizational Innovation in Mobile Jordanian Communication Companies, (Zain; Orange; Umniah and Xpress). The study depends on descriptive and analytical mothodize using the practical manner, study sample consists of Head of section and Experts from all Specializations in Mobile Jordanian Communication Companies amounted (120). A major study finding all Transformational Leadership Behaviors was median extent. The innovation adoption and innovation abilities availability was high extent. Besides there is a significant statistical impact of Transformational Leadership Behaviors, (Idealized Influence; Intellectual Stimulation; Individualized Consideration and Empowerment), on Organizational Innovation (innovation adoption & innovation abilities availability). It can be said that organizational creativity is the adoption of new ideas and behaviors that are applied in the organization, whether this is in creating new products or services, or new technology that is used at work. Transformational leadership is a process that occurs when one or more people engage with others in a way that enables leaders and followers to raise each other to higher levels of morals, motivations, and behaviors (desires, needs, ambitions, and followers' core values). An effective leader under transformational leadership is one who has a high ability to communicate, motivate, delegate, and listen to others, and is characterized by great flexibility in solving problems and dealing greatly with variables. The difference between creativity and innovation, in conclusion, innovation, invention, and creativity are three important elements for any institution or organization, and there is a fine line that separates them, which is that creativity works to generate new ideas, while invention makes them tangible, and innovation makes them valuable.

Keywords: leadership, organizational, transformational, creativity

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Authors: Sylvia Chan-Olmsted, Lisa-Charlotte Wolter

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With the continuous proliferation of media platforms, there have been tremendous changes in media consumption behaviors. From the perspective of sports sponsorship, while there is now a multitude of platforms to create brand associations, the changing media landscape and shift of message control also mean that sports sponsors will have to take into account the nature of and consumer responses toward these emerging digital media to devise effective marketing strategies. Utilizing the personal interview methodology, this study is qualitative and exploratory in nature. A total of 18 experts from European and American academics, sports marketing industry, and sports leagues/teams were interviewed to address three main research questions: 1) What are the major changes in digital technologies that are relevant to sports sponsorship; 2) How have digital media influenced the channels and platforms of sports sponsorship; and 3) How have these technologies affected the goals, strategies, and measurement of sports sponsorship. The study found that sports sponsorship has moved from consumer engagement, engagement measurement, and consequences of engagement on brand behaviors to micro-targeting one on one, engagement by context, time, and space, and activation and leveraging based on tracking and databases. From the perspective of platforms and channels, the use of mobile devices is prominent during sports content consumption. Increasing multiscreen media consumption means that sports sponsors need to optimize their investment decisions in leagues, teams, or game-related content sources, as they need to go where the fans are most engaged in. The study observed an imbalanced strategic leveraging of technology and digital infrastructure. While sports leagues have had less emphasis on brand value management via technology, sports sponsors have been much more active in utilizing technologies like mobile/LBS tools, big data/user info, real-time marketing and programmatic, and social media activation. Regardless of the new media/platforms, the study found that integration and contextualization are the two essential means of improving sports sponsorship effectiveness through technology. That is, how sponsors effectively integrate social media/mobile/second screen into their existing legacy media sponsorship plan so technology works for the experience/message instead of distracting fans. Additionally, technological advancement and attention economy amplify the importance of consumer data gathering, but sports consumer data does not mean loyalty or engagement. This study also affirms the benefit of digital media as they offer viral and pre-event activations through storytelling way before the actual event, which is critical for leveraging brand association before and after. That is, sponsors now have multiple opportunities and platforms to tell stories about their brands for longer time period. In summary, digital media facilitate fan experience, access to the brand message, multiplatform/channel presentations, storytelling, and content sharing. Nevertheless, rather than focusing on technology and media, today’s sponsors need to define what they want to focus on in terms of content themes that connect with their brands and then identify the channels/platforms. The big challenge for sponsors is to play to the venues/media’s specificity and its fit with the target audience and not uniformly deliver the same message in the same format on different platforms/channels.

Keywords: digital media, mobile media, social media, technology, sports sponsorship

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Authors: Jian Yang, Atsushi Yagi

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Tree-grass coexistence system is of great importance for forest ecology. Mathematical models are being proposed to study the dynamics of tree-grass coexistence and the stability of the systems. However, few of the models concentrates on spatial dynamics of the tree-grass coexistence. In this study, we modified an age-structured continuous-space population model for forests, obtaining an age-structured continuous-space population model for the tree-grass competition model. In the model, for thermal competitions, adult trees can out-compete grass, and grass can out-compete seedlings. We mathematically studied the model to make sure tree-grass coexistence solutions exist. Numerical experiments demonstrated that a fraction of area that trees or grass occupies can affect whether the coexistence is stable or not. We also tried regulating the mortality of adult trees with other parameters and the fraction of area trees and grass occupies were fixed; results show that the mortality of adult trees is also a factor affecting the stability of the tree-grass coexistence in this model.

Keywords: population-structured models, stabilities of ecosystems, thermal competitions, tree-grass coexistence systems

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Authors: Marco Barassi, Nicola Spagnolo

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This paper uses a DCC-GARCH model framework to examine mean and volatility spillovers (i.e. causality in mean and variance) dynamics between financial centers and the stock market indexes of the BRICS countries. In addition, tests for changes in the transmission mechanism are carried out by first testing for structural breaks and then setting a dummy variable to control for the 2008 financial crises. We use weekly data for nine countries, four financial centers (Germany, Japan, UK and USA) and the five BRICS countries (Brazil, Russia, India, China and South Africa). Furthermore, we control for monetary policy using domestic interest rates (90-day Treasury Bill interest rate) over the period 03/1/1990 - 04/2/2014, for a total of 1204 observations. Results show that the 2008 financial crises changed the causality dynamics for most of the countries considered. The same pattern can also be observed in conditional correlation showing a shift upward following the turbulence associated to the 2008 crises. The magnitude of these effects suggests a leading role played by the financial centers in effecting Brazil and South Africa, whereas Russia, India and China show a higher degree of resilience.

Keywords: financial crises, DCC-GARCH model, volatility spillovers, economics

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Authors: S.Balaji, R.Sujatha, M. Ramakrishnan

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Signcryption is a cryptographic primitive that fulfills both the functions of digital signature and public key encryption simultaneously in low cost when compared with the traditional signature-then-encryption approach. In this paper, we propose a novel mouse movement based key generation technique to generate secret keys which is secure against the outer and insider attacks. Tag Key Encapsulation Mechanism (KEM) process is implemented using True Random Number Generator (TRNG) method. This TRNG based key is used for data encryption in the Data Encapsulation Mechanism (DEM). We compare the statistical reports of the proposed system with the previous methods which implements TKEM based on pseudo random number generator

Keywords: pseudo random umber generator, signcryption, true random number generator, node deployment

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Authors: Nenashev Yaroslav, Russkin Oleg

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The mixing process is one of the most important and critical stages in many industrial sectors, such as chemistry, pharmaceuticals, and the food industry. When designing equipment with mixing impellers, technology developers often encounter working environments with complex physical properties and rheology. In such cases, the use of computational fluid dynamics tools is an excellent solution to mitigate risks and ensure the stable operation of the equipment. The research focuses on one of the designed reactors with mixing impellers intended for polymer synthesis. The study describes an approach to modeling reactors of similar configurations, taking into account the complex properties of the mixed liquids using the computational fluid dynamics (CFD) method. To achieve this goal, a complex 3D model was created, accurately replicating the functionality of chemical equipment. The model allows for the assessment of the hydrodynamic behavior of the reaction mixture inside the reactor, consideration of heat release due to the reaction, and the heat exchange between the reaction mixture and the cooling medium. The results indicate that the choice of the type and size of the mixing device significantly affects the efficiency of the mixing process inside the chemical reactor.

Keywords: CFD, mixing, blending, chemical reactor, non-Newton liquids, polymers

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Authors: Jie Zhang, Qianyu Guo, Tieyi Zhang, Zhiyong Feng, Xiaohong Li

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With the widespread popularity of mobile devices and the development of artificial intelligence (AI), deep learning (DL) has been extensively applied in Android apps. Compared with traditional Android apps (traditional apps), deep learning based Android apps (DL-based apps) need to use more third-party application programming interfaces (APIs) to complete complex DL inference tasks. However, existing methods (e.g., FlowDroid) for detecting sensitive information leakage in Android apps cannot be directly used to detect DL-based apps as they are difficult to detect third-party APIs. To solve this problem, we design DLtrace; a new static information flow analysis tool that can effectively recognize third-party APIs. With our proposed trace and detection algorithms, DLtrace can also efficiently detect privacy leaks caused by sensitive APIs in DL-based apps. Moreover, using DLtrace, we summarize the non-sequential characteristics of DL inference tasks in DL-based apps and the specific functionalities provided by DL models for such apps. We propose two formal definitions to deal with the common polymorphism and anonymous inner-class problems in the Android static analyzer. We conducted an empirical assessment with DLtrace on 208 popular DL-based apps in the wild and found that 26.0% of the apps suffered from sensitive information leakage. Furthermore, DLtrace has a more robust performance than FlowDroid in detecting and identifying third-party APIs. The experimental results demonstrate that DLtrace expands FlowDroid in understanding DL-based apps and detecting security issues therein.

Keywords: mobile computing, deep learning apps, sensitive information, static analysis

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Authors: Ebrahim Alrashed

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Wireless sensor networks are vulnerable to attacks from adversaries attempting to disrupt their operations. Sink-hole attacks are a type of attack where an adversary node drops data forwarded through it and hence affecting the reliability and accuracy of the network. Since sensor nodes have limited battery power, it is essential that any solution to the sinkhole attack problem be very energy-aware. In this paper, we present a reliable and energy efficient scheme to forward data from source nodes to the base station while under sink-hole attack. The scheme also detects sink-hole attack nodes and avoid paths that includes them.

Keywords: energy-aware routing, reliability, sink-hole attack, WSN

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Authors: Thulodin Mat Lazim, Aminuddin Saat, Ammar Fakhir Abdulwahid, Zaid Sattar Kareem

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Film cooling is one of the cooling systems investigated for the application to gas turbine blades. Gas turbines use film cooling in addition to turbulence internal cooling to protect the blades outer surface from hot gases. The present study concentrates on the numerical investigation of film cooling performance for a row of twisted cylindrical holes in modern turbine blade. The adiabatic film effectiveness and the heat transfer coefficient are determined numerical on a flat plate downstream of a row of inclined different cross section area hole exit by using Computational Fluid Dynamics (CFD). The swirling motion of the film coolant was induced the twisted angle of film cooling holes, which inclined an angle of α toward the vertical direction and surface of blade turbine. The holes angle α of the impingement mainstream was changed from 90°, 65°, 45°, 30° and 20°. The film cooling effectiveness on surface of blade turbine wall was measured by using 3D Computational Fluid Dynamics (CFD). Results showed that the effectiveness of rectangular twisted hole has the effectiveness among other cross section area of the hole at blowing ratio (0.5, 1, 1.5 and 2).

Keywords: turbine blade cooling, film cooling, geometry shape of hole, turbulent flow

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Authors: Saleh Alzahrani, Halim Boussabaine

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The majority of Public Private Partnership (PPP) are developed based on the rationale that the design, construction, operation, and financing of a public project is to be awarded to a private party within a single contractual framework. PPP project risks normally include the development and construction of a new asset as well as its operation for decades. Undoubtedly the most serious consequences of risks during the construction period are price and time overruns. These events are amongst the most broadly used scenarios in value for money analysis risks. The sources of risk change over the life cycle of a PPP project. In traditional procurement, the public sector normally has to cover all price distress from these risks. At least there is plenty evidence to suggest that price distress is a norm in some of the projects that are delivered under traditional procurement. This paper will find the impact of construction risk factors into actual construction price into PPP projects. The paper will present a brief literature review on PPP risk pricing strategies, and then using system dynamics (SD) to analyses of the risks associated with the estimated project price. Based on the finding from these analyses a risk pricing association model is presented and discussed. The paper concludes with thoughts for future research.

Keywords: Public Private Partnership (PPP), Risk, Risk Pricing, System Dynamics (SD), construction price

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Authors: Devanjan Bhattacharya, Jitka Komarkova

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The research describes the implementation of a novel and stand-alone system for dynamic hazard warning. The system uses all existing infrastructure already in place like mobile networks, a laptop/PC and the small installation software. The geospatial dataset are the maps of a region which are again frugal. Hence there is no need to invest and it reaches everyone with a mobile. A novel architecture of hazard assessment and warning introduced where major technologies in ICT interfaced to give a unique WebGIS based dynamic real time geohazard warning communication system. A never before architecture introduced for integrating WebGIS with telecommunication technology. Existing technologies interfaced in a novel architectural design to address a neglected domain in a way never done before–through dynamically updatable WebGIS based warning communication. The work publishes new architecture and novelty in addressing hazard warning techniques in sustainable way and user friendly manner. Coupling of hazard zonation and hazard warning procedures into a single system has been shown. Generalized architecture for deciphering a range of geo-hazards has been developed. Hence the developmental work presented here can be summarized as the development of internet-SMS based automated geo-hazard warning communication system; integrating a warning communication system with a hazard evaluation system; interfacing different open-source technologies towards design and development of a warning system; modularization of different technologies towards development of a warning communication system; automated data creation, transformation and dissemination over different interfaces. The architecture of the developed warning system has been functionally automated as well as generalized enough that can be used for any hazard and setup requirement has been kept to a minimum.

Keywords: geospatial, web-based GIS, geohazard, warning system

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Authors: Suruchi Saini, Hitender Kumar Tyagi

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With the rapid progress of the nanotechnology industry, it is becoming increasingly important to have compact semiconductor devices to function and offer the best results at various technology nodes. While performing the scaling of the device, several short-channel effects occur. To minimize these scaling limitations, some device architectures have been developed in the semiconductor industry. FinFET is one of the most promising structures. Also, the double-gate 2D Fin field effect transistor has the benefit of suppressing short channel effects (SCE) and functioning well for less than 14 nm technology nodes. In the present research, the MuGFET simulation tool is used to analyze and explain the electrical behaviour of a double-gate 2D Fin field effect transistor. The drift-diffusion and Poisson equations are solved self-consistently. Various models, such as Fermi-Dirac distribution, bandgap narrowing, carrier scattering, and concentration-dependent mobility models, are used for device simulation. The transfer and output characteristics of the double-gate 2D Fin field effect transistor are determined at 10 nm technology node. The performance parameters are extracted in terms of threshold voltage, trans-conductance, leakage current and current on-off ratio. In this paper, the device performance is analyzed at different structure parameters. The utilization of the Id-Vg curve is a robust technique that holds significant importance in the modeling of transistors, circuit design, optimization of performance, and quality control in electronic devices and integrated circuits for comprehending field-effect transistors. The FinFET structure is optimized to increase the current on-off ratio and transconductance. Through this analysis, the impact of different channel widths, source and drain lengths on the Id-Vg and transconductance is examined. Device performance was affected by the difficulty of maintaining effective gate control over the channel at decreasing feature sizes. For every set of simulations, the device's features are simulated at two different drain voltages, 50 mV and 0.7 V. In low-power and precision applications, the off-state current is a significant factor to consider. Therefore, it is crucial to minimize the off-state current to maximize circuit performance and efficiency. The findings demonstrate that the performance of the current on-off ratio is maximum with the channel width of 3 nm for a gate length of 10 nm, but there is no significant effect of source and drain length on the current on-off ratio. The transconductance value plays a pivotal role in various electronic applications and should be considered carefully. In this research, it is also concluded that the transconductance value of 340 S/m is achieved with the fin width of 3 nm at a gate length of 10 nm and 2380 S/m for the source and drain extension length of 5 nm, respectively.

Keywords: current on-off ratio, FinFET, short-channel effects, transconductance

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Authors: Ionel Zagan, Vasile Gheorghita Gaitan, Adrian Brezulianu

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This paper presents the contributions in designing a mobile system named Tele-ECG implemented for remote monitoring of cardiac patients. For a better flexibility of this application, the authors chose to implement a local memory and multiple communication interfaces. The project described in this presentation is based on the ARM Cortex M0+ microcontroller and the ADAS1000 dedicated chip necessary for the collection and transmission of Electrocardiogram signals (ECG) from the patient to the microcontroller, without altering the performances and the stability of the system. The novelty brought by this paper is the implementation of a remote monitoring system for cardiac patients, having a real-time behavior and multiple interfaces. The microcontroller is responsible for processing digital signals corresponding to ECG and also for the implementation of communication interface with the main server, using GSM/Bluetooth SIMCOM SIM800C module. This paper translates all the characteristics of the Tele-ECG project representing a feasible implementation in the biomedical field. Acknowledgment: This paper was supported by the project 'Development and integration of a mobile tele-electrocardiograph in the GreenCARDIO© system for patients monitoring and diagnosis - m-GreenCARDIO', Contract no. BG58/30.09.2016, PNCDI III, Bridge Grant 2016, using the infrastructure from the project 'Integrated Center for research, development and innovation in Advanced Materials, Nanotechnologies, and Distributed Systems for fabrication and control', Contract No. 671/09.04.2015, Sectoral Operational Program for Increase of the Economic Competitiveness co-funded from the European Regional Development Fund.

Keywords: Tele-ECG, real-time cardiac monitoring, electrocardiogram, microcontroller

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Authors: Feng Tao, Ma Jing, Guo Xian, Wang Jing

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Named Data Networking (NDN) replaces IP address of traditional network with data name, and adopts dynamic cache mechanism. In the existing mechanism, however, only one-to-one search can be achieved because every data has a unique name corresponding to it. There is a certain mapping relationship between data content and data name, so if the data name is intercepted by an adversary, the privacy of the data content and user’s interest can hardly be guaranteed. In order to solve this problem, this paper proposes a one-to-many fuzzy search scheme based on order-preserving encryption to reduce the query overhead by optimizing the caching strategy. In this scheme, we use hash value to ensure the user’s query safe from each node in the process of search, so does the privacy of the requiring data content.

Keywords: NDN, order-preserving encryption, fuzzy search, privacy

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Authors: Hiroyuki Aoki

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The physical properties of polymer materials are dependent on the conformation and molecular motion of a polymer chain. Therefore, the structure and dynamic behavior of the single polymer chain have been the most important concerns in the field of polymer physics. However, it has been impossible to directly observe the conformation of the single polymer chain in a bulk medium. In the current work, the novel techniques to study the conformation and dynamics of a single polymer chain are proposed. Since a fluorescence method is extremely sensitive, the fluorescence microscopy enables the direct detection of a single molecule. However, the structure of the polymer chain as large as 100 nm cannot be resolved by conventional fluorescence methods because of the diffraction limit of light. In order to observe the single chains, we developed the labeling method of polymer materials with a photo-switchable dye and the super-resolution microscopy. The real-space conformational analysis of single polymer chains with the spatial resolution of 15-20 nm was achieved. The super-resolution microscopy enables us to obtain the three-dimensional coordinates; therefore, we succeeded the conformational analysis in three dimensions. The direct observation by the nanometric optical microscopy would reveal the detailed information on the molecular processes in the various polymer systems.

Keywords: polymer materials, single molecule, super-resolution techniques, conformation

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Authors: Yuhang Wang, Jorg Schluter, Sergiy Shelyag

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The high cost associated with high-resolution computational fluid dynamics (CFD) is one of the main challenges that inhibit the design, development, and optimisation of new combustion systems adapted for renewable fuels. In this study, we propose a physics-guided CNN-based model to predict turbulence evolution and mixing without requiring a traditional CFD solver. The model architecture is built upon U-Net and the inception module, while a physics-guided loss function is designed by introducing two additional physical constraints to allow for the conservation of both mass and pressure over the entire predicted flow fields. Then, the model is trained on the Large Eddy Simulation (LES) results of a natural turbulent mixing layer with two different Reynolds number cases (Re = 3000 and 30000). As a result, the model prediction shows an excellent agreement with the corresponding CFD solutions in terms of both spatial distributions and temporal evolution of turbulent mixing. Such promising model prediction performance opens up the possibilities of doing accurate high-resolution manifold-based combustion simulations at a low computational cost for accelerating the iterative design process of new combustion systems.

Keywords: computational fluid dynamics, turbulence, machine learning, combustion modelling

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Authors: Praveen Battula

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Any high performance car has the tendency to over steer and Understeer under slippery conditions, An Electronic Stability Control System is needed under these conditions to regulate the steering of the car. It uses Anti-Lock Braking System (ABS) and Traction Control and Wheel Speed Sensor, Steering Angle Sensor, Rotational Speed Sensors to correct the problems. The focus of this paper is to improve the driving dynamics and safety by controlling the forces applied on each wheel. ESC Control the Yaw Stability, traction controls the Roll Stability, where actually the vehicle slip rate and lateral acceleration is controlled. ESC uses differential braking on all four brakes independently to control the vehicle’s motion. A mathematical model is developed in Simulink for the FlexRay based Electronic Stability Control. Vehicle steering is developed using Neuro Fuzzy Logic Controller. 7 Degrees of Freedom Vehicle Model is used as a Plant Model using dSpace autobox. The Performance of the system is assessed using two different road Scenarios, Vehicle Control under standard maneuvering conditions. The entire system is set using Dspace Control Desk. Results are provided by comparison of how a Vehicle with and without Electronic Stability Control which shows an improved performance in control.

Keywords: ESC, flexray, chassis control, steering, neuro fuzzy, vehicle dynamics

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Authors: Aelina Franz

Abstract:

In recent years, the scientific community has witnessed a paradigm shift in the exploration of unconventional levitation methods, particularly in the domain of spherical combat platforms. This paper explores aerodynamics and levitational dynamics inherent in these spheres by examining interactions at the quantum level. Our research unravels the nuanced aerodynamic phenomena governing the levitation of spherical combat platforms. Through an analysis of the quantum fluid dynamics surrounding these spheres, we reveal the crucial interactions between air resistance, surface irregularities, and the quantum fluctuations that influence their levitational behavior. Our findings challenge conventional understanding, providing a perspective on the aerodynamic forces at play during the levitation of spherical combat platforms. Furthermore, we propose design modifications and control strategies informed by both classical aerodynamics and quantum information processing principles. These advancements not only enhance the stability and maneuverability of the combat platforms but also open new avenues for exploration in the interdisciplinary realm of engineering and quantum information sciences. This paper aims to contribute to levitation technologies and their applications in the field of spherical combat platforms. We anticipate that our work will stimulate further research to create a deeper understanding of aerodynamics and quantum phenomena in unconventional levitation systems.

Keywords: spherical combat platforms, levitation technologies, aerodynamics, maneuverable platforms

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Authors: Fabian Velasquez, John Espitia, Henry Hernadez, Sebastian Escobar, Jader Rodriguez

Abstract:

Non-centrifuged cane sugar (NCS) is a concentrated product obtained through the evaporation of water contain from sugarcane juice inopen heat exchangers (OE). The heat supplied to the evaporation stages is obtained from the cane bagasse through the thermochemical process of combustion, where the thermal energy released is transferred to OE by the flue gas. Therefore, the optimization of energy usage becomes essential for the proper design of the production process. For optimize the energy use, it is necessary modeling and simulation of heat transfer between the combustion gases and the juice and to understand the major mechanisms involved in the heat transfer. The main objective of this work was simulated heat transfer phenomena between the flue gas and open heat exchangers using Computational Fluid Dynamics model (CFD). The simulation results were compared to field measured data. Numerical results about temperature profile along the flue gas pipeline at the measurement points are in good accordance with field measurements. Thus, this study could be of special interest in design NCS production process and the optimization of the use of energy.

Keywords: mathematical modeling, design variables, computational fluid dynamics, overall thermal efficiency

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Authors: Yali Liu, Maria Avello Iturriagagoitia

Abstract:

Background: Fitness applications (apps) are one of the most popular mobile health (mHealth) apps. These apps can help prevent/control health issues such as obesity, which is one of the most serious public health challenges in the developed world in recent decades. Compared with the traditional intervention like face-to-face treatment, it is cheaper and more convenient to use fitness apps to interfere with physical activities and healthy behaviors. Nevertheless, fitness applications apps tend to have high abandonment rates and low levels of user engagement. Therefore, maintaining the endurance of users' usage is challenging. In fact, previous research shows a variety of strategies -goal-setting, self-monitoring, coaching, etc.- for promoting fitness and health behavior change. These strategies can influence the users’ perseverance and self-monitoring of the program as well as favoring their adherence to routines that involve a long-term behavioral change. However, commercial fitness apps rarely incorporate these strategies into their design, thus leading to a lack of engagement with the apps. Most of today’s mobile services and brands engage their users proactively via push notifications. Push notifications. These notifications are visual or auditory alerts to inform mobile users about a wide range of topics that entails an effective and personal mean of communication between the app and the user. One of the research purposes of this article is to implement the application of behavior change strategies through push notifications. Proposes: This study aims to better understand the influence that effective use of push notifications combined with the behavioral change strategies will have on users’ engagement with the fitness app. And the secondary objectives are 1) to discuss the sociodemographic differences in utilization of push notifications of fitness apps; 2) to determine the impact of each strategy in customer engagement. Methods: The study uses a combination of the Consumer Engagement Theory and UTAUT2 based model to conduct an online survey among current users of fitness apps. The questionnaire assessed attitudes to each behavioral change strategy, and sociodemographic variables. Findings: Results show the positive effect of push notifications in the generation of consumer engagement and the different impacts of each strategy among different groups of population in customer engagement. Conclusions: Fitness apps with behavior change strategies have a positive impact on increasing users’ usage time and customer engagement. Theoretical experts can participate in designing fitness applications, along with technical designers.

Keywords: behavioral change, customer engagement, fitness app, push notification, UTAUT2

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Authors: Hrishit Mitra, Saptarshi Mandal

Abstract:

The study of aerodynamics for Formula 1 cars is very crucial in determining their performance. In the current F1 industry, when each engine manufacturer exhibits a torque and peak speed that differ by less than 5%, the emphasis on maximizing performance is dependent heavily on the utilization of aerodynamics. This work examines the aerodynamic characteristics of an F1 car by utilizing computational fluid dynamics in order to substantiate the hypothesis that an F1 car can go upside down in a tunnel without any external assistance, only due to the downforce it produces. In addition to this, this study also suggests the implementation of a 'flexi-wing' front in F1 cars to optimize downforce and reduce drag. Furthermore, this paper provides a concise overview of the historical development of aerodynamics in F1, with a specific emphasis on the progression of aerodynamics and the impact of downforce on the dynamics of vehicles. Next, an examination of wings has been provided, comparing the performance of the suggested wing at high speeds and low speeds. Three simulations have been conducted: one to test the complete aerodynamics and validate the hypothesis discussed above, and two specifically focused on the flexi wing, one at high speed and one at low speed. The collected results have been examined to analyze the performance of the front flexi wing. Performance analysis was conducted from the measurement of downforce and drag coefficient, as well as the pressure and velocity distributions.

Keywords: high speed flexi wing, low speed flexi wing, F1 car aerodynamics, F1 car drag reduction

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Authors: Vidyarini Dwita, Rebecca Fanany

Abstract:

This study will discuss the growth of the market for smartphone technology in Indonesia. This country, with the world’s fourth largest population, has a reputation as the social media capital of the world, and this reputation is largely justified. The penetration of social media is high in Indonesia which has one of the largest global markets. Most Indonesian users of Facebook, Twitter and other social media platforms access the sites from their mobile phones. Indonesia is expected to continue to be a major market for digital mobile devices, such as smartphone and tablets that can access the internet. The aim of this study to describe the way responses of Indonesian consumers to smartphone advertising using English and Indonesian will impact on their perceptions of the prestige and product image of the advertised items and thus influence consumer intention to purchase the item. Advertising for smartphones and similar products is intense and dynamic and often draws on the social attitudes of Indonesians with respect to linguistic and cultural content and especially appeals to their desire to be part of global mainstream culture. The study uses a qualitative method based on in-depth interviews with 30 participants. Content analysis is employed to analyse the responses of Indonesian consumers to smartphone advertising that uses English and Indonesian text. Its findings indicate that consumers’ impressions of English and Indonesian slogans influence their attitudes toward smartphones, suggesting that linguistic context plays a role in influencing consumer purchases.

Keywords: consumer purchases, marketing communication, product image, smartphone advertising, sociolinguistic

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Authors: Maria Ezziani, Rabie Zine, Amine Amar, Ilhame Kissani

Abstract:

This paper introduces a predictive model for urban transportation engineering, which is vital for efficient traffic management. Utilizing comprehensive datasets and advanced statistical techniques, the model accurately forecasts travel times by considering temporal variations and traffic dynamics. Machine learning algorithms, including regression trees and neural networks, are employed to capture sequential dependencies. Results indicate significant improvements in predictive accuracy, particularly during peak hours and holidays, with the incorporation of traffic flow and speed variables. Future enhancements may integrate weather conditions and traffic incidents. The model's applications range from adaptive traffic management systems to route optimization algorithms, facilitating congestion reduction and enhancing journey reliability. Overall, this research extends beyond travel time estimation, offering insights into broader transportation planning and policy-making realms, empowering stakeholders to optimize infrastructure utilization and improve network efficiency.

Keywords: predictive analytics, traffic flow, travel time estimation, urban transportation, machine learning, traffic management

Procedia PDF Downloads 84