Search results for: number of late jobs

Authors: Tyng-Rong Roan, Fuji Foo, Wenwey Hseush

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Recent development of AI and edge computing plays a critical role to capture meaningful events such as detection of an unattended bag. One of the core problems is re-identification across multiple CCTVs. Immediately following the detection of a meaningful event is to track and trace the objects related to the event. In an extensive environment, the challenge becomes severe when the number of CCTVs increases substantially, imposing difficulties in achieving high accuracy while maintaining real-time performance. The algorithm that re-identifies cross-boundary objects for extensive tracking is referred to Extensive Re-Identification, which emphasizes the issues related to the complexity behind a great number of CCTVs. The Spatial-Temporal Awareness approach challenges the conventional thinking and concept of operations which is labor intensive and time consuming. The ability to perform Extensive Re-Identification through a multi-sensory network provides the next-level insights – creating value beyond traditional risk management.

Keywords: long-short-term memory, re-identification, security critical application, spatial-temporal awareness

Procedia PDF Downloads 99

Authors: V. Makis, L. Jafari

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In this paper, we develop an optimal Bayesian chart to control the expected number of defects per inspection unit in production processes with long production runs. We formulate this control problem in the optimal stopping framework. The objective is to determine the optimal stopping rule minimizing the long-run expected average cost per unit time considering partial information obtained from the process sampling at regular epochs. We prove the optimality of the control limit policy, i.e., the process is stopped and the search for assignable causes is initiated when the posterior probability that the process is out of control exceeds a control limit. An algorithm in the semi-Markov decision process framework is developed to calculate the optimal control limit and the corresponding average cost. Numerical examples are presented to illustrate the developed optimal control chart and to compare it with the traditional u-chart.

Keywords: Bayesian u-chart, economic design, optimal stopping, semi-Markov decision process, statistical process control

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Authors: Hisham Elmouazen, Xiaobing Zhang

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In regenerative-cooled rocket engines, understanding the coolant behaviour within cooling channels is essential to enhance engine performance and maintain chamber walls at low temperatures. However, modelling and testing the rocket engine's cooling channels is challenging due to the high temperature of the chamber walls, supercritical flow, and high Reynolds number. Therefore, a numerical analysis of five different V-rib cross-sections to optimize rocket engine cooling channels' performance is developed and validated in this work. Three-dimensional CFD simulations are employed by the Shear Stress Transport (k- ω) turbulent model at Reynolds number 42,500. The study findings illustrate that the V-ribbed channel performance is optimized by 59.5% relative to the plain/flat channel. Additionally, the chamber wall temperature is decreased to 726.4 K, and the right-angle trapezoidal V-rib (Case 4) improves thermal augmentation up to 74.3 % with a slightly high friction factor.

Keywords: computational fluid dynamics CFD, regenerative-cooled system, thermal performance, V-rib cross-sections

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Authors: Zhongmin Wang, Lin Wei, Hengshan Zhang, Tianhua Chen, Yimin Zhou

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The assembly line balancing problems are signficant in mass production systems. In order to deal with the uncertainties that practically exist but barely mentioned in the literature, this paper develops a mathematic model with an optimisation algorithm to solve the assembly line balancing problem with uncertainty operation time. The developed model is able to work with a variable number of workstations under the uncertain environment, aiming to obtain the minimal number of workstation and minimal idle time for each workstation. In particular, the proposed approach first introduces the concept of protection time that closely works with the uncertain operation time. Four dominance rules and the mechanism of determining up and low bounds are subsequently put forward, which serve as the basis for the proposed branch and bound algorithm. Experimental results show that the proposed work verified on a benchmark data set is able to solve the uncertainties efficiently.

Keywords: assembly lines, SALBP-UOT, uncertain operation time, branch and bound algorithm.

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Authors: Jean Yves Trepanier, Sami Ammar, Sagnik Banik

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Lattice Boltzmann Method has been advantageous in simulating complex boundary conditions and solving for fluid flow parameters by streaming and collision processes. This paper includes the study of three different test cases in a confined domain using the method of the Lattice Boltzmann model. 1. An SRT (Single Relaxation Time) approach in the Lattice Boltzmann model is used to simulate Lid Driven Cavity flow for different Reynolds Number (100, 400 and 1000) with a domain aspect ratio of 1, i.e., square cavity. A moment-based boundary condition is used for more accurate results. 2. A Thermal Lattice BGK (Bhatnagar-Gross-Krook) Model is developed for the Rayleigh Benard convection for both test cases - Horizontal and Vertical Temperature difference, considered separately for a Boussinesq incompressible fluid. The Rayleigh number is varied for both the test cases (10^3 ≤ Ra ≤ 10^6) keeping the Prandtl number at 0.71. A stability criteria with a precise forcing scheme is used for a greater level of accuracy. 3. The phase change problem governed by the heat-conduction equation is studied using the enthalpy based Lattice Boltzmann Model with a single iteration for each time step, thus reducing the computational time. A double distribution function approach with D2Q9 (density) model and D2Q5 (temperature) model are used for two different test cases-the conduction dominated melting and the convection dominated melting. The solidification process is also simulated using the enthalpy based method with a single distribution function using the D2Q5 model to provide a better understanding of the heat transport phenomenon. The domain for the test cases has an aspect ratio of 2 with some exceptions for a square cavity. An approximate velocity scale is chosen to ensure that the simulations are within the incompressible regime. Different parameters like velocities, temperature, Nusselt number, etc. are calculated for a comparative study with the existing works of literature. The simulated results demonstrate excellent agreement with the existing benchmark solution within an error limit of ± 0.05 implicates the viability of this method for complex fluid flow problems.

Keywords: BGK, Nusselt, Prandtl, Rayleigh, SRT

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Authors: Samhita Bharadwaj

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This is an empirical study of classifiers in Assamese and Bodo, two genetically unrelated languages of India. The objective of the paper is to address the language contact between Assamese and Bodo as reflected in classifiers. The data has been collected through fieldwork in Bodo recording narratives and folk tales and eliciting specific data from the speakers. The data for Assamese is self-produced as native speaker of the language. Assamese is the easternmost New-Indo-Aryan (henceforth NIA) language mainly spoken in the Brahmaputra valley of Assam and some other north-eastern states of India. It is the lingua franca of Assam and is creolised in the neighbouring state of Nagaland. Bodo, on the other hand, is a Tibeto-Burman (henceforth TB) language of the Bodo-Garo group. It has the highest number of speakers among the TB languages of Assam. However, compared to Assamese, it is still a lesser documented language and due to the prestige of Assamese, all the Bodo speakers are fluent bi-lingual in Assamese, though the opposite isn’t the case. With this context, classifiers, a characteristic phenomenon of TB languages, but not so much of NIA languages, presents an interesting case study on language contact caused by bilingualism. Assamese, as a result of its language contact with the TB languages which are rich in classifiers; has developed the richest classifier system among the IA languages in India. Yet, as a part of rampant borrowing of Assamese words and patterns into Bodo; Bodo is seen to borrow even Assamese classifiers into its system. This paper analyses the borrowed classifiers of Bodo and finds the route of this borrowing phenomenon in the number system of the languages. As the Bodo speakers start replacing the higher numbers from five with Assamese ones, they also choose the Assamese classifiers to attach to these numbers. Thus, the partial loss of number in Bodo as a result of language contact and bilingualism in Assamese is found to be the reason behind the borrowing of classifiers in Bodo. The significance of the study lies in exploring an interesting aspect of language contact in Assam. It is hoped that this will attract further research on bilingualism and classifiers in Assam.

Keywords: Assamese, bi-lingual, Bodo, borrowing, classifier, language contact

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Authors: Shogo Nagano, Yusuke Tanigaki, Hirokazu Fukuda

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Vegetables harvested early in the morning or late in the afternoon are valued in plant production, and so the time of harvest is important. The biological functions known as circadian clocks have a significant effect on this harvest timing. The purpose of this study was to non-destructively estimate the circadian clock and so construct a method for determining a suitable harvest time. We took eight samples of green busil (Perilla frutescens var. crispa) every 4 hours, six times for 1 day and analyzed all samples at the same time. A hyperspectral camera was used to collect spectrum intensities at 141 different wavelengths (350–1050 nm). Calculation of correlations between spectrum intensity of each wavelength and harvest time suggested the suitability of the hyperspectral camera for non-destructive estimation. However, even the highest correlated wavelength had a weak correlation, so we used machine learning to raise the accuracy of estimation and constructed a machine learning model to estimate the internal time of the circadian clock. Artificial neural networks (ANN) were used for machine learning because this is an effective analysis method for large amounts of data. Using the estimation model resulted in an error between estimated and real times of 3 min. The estimations were made in less than 2 hours. Thus, we successfully demonstrated this method of non-destructively estimating internal time.

Keywords: artificial neural network (ANN), circadian clock, green busil, hyperspectral camera, non-destructive evaluation

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Authors: Mark Salisbury

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The arrival of artificially intelligent avatars and the automation they bring is worrying many of us, not only for our livelihood but for the jobs that may be lost to our kids. We worry about what our place will be as human beings in this new economy where much of it will be conducted online in the metaverse – in a network of 3D virtual worlds – working with intelligent machines. The Future of Leadership was written to address these fears and show what our place will be – the right place – in this new economy of AI avatars, automation, and 3D virtual worlds. But to be successful in this new economy, our job will be to bring wisdom to our workplace and the marketplace. And we will use AI avatars and 3D virtual worlds to do it. However, this book is about more than AI and the avatars that we will work with in the metaverse. It’s about building Organizational intelligence (OI) -- the capability of an organization to comprehend and create knowledge relevant to its purpose; in other words, it is the intellectual capacity of the entire organization. To increase organizational intelligence requires a new kind of knowledge worker, a wisdom worker, that requires a new kind of leadership. This book begins your story for how to become a leader of wisdom workers and be successful in the emerging wisdom economy. After this presentation, conference participants will be able to do the following: Recognize the characteristics of the new generation of wisdom workers and how they differ from their predecessors. Recognize that new leadership methods and techniques are needed to lead this new generation of wisdom workers. Apply personal and professional values – personal integrity, belief in something larger than yourself, and keeping the best interest of others in mind – to improve your work performance and lead others. Exhibit an attitude of confidence, courage, and reciprocity of sharing knowledge to increase your productivity and influence others. Leverage artificial intelligence to accelerate your ability to learn, augment your decision-making, and influence others.Utilize new technologies to communicate with human colleagues and intelligent machines to develop better solutions more quickly.

Keywords: metaverse, generative artificial intelligence, automation, leadership, organizational intelligence, wisdom worker

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Authors: Nirupama Dixit, Anyaa Mittal, Neeru Sood

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Alzheimer’s disease (AD) is a progressive form of dementia, contributing to up to 70% of cases, mostly observed in elderly but is not restricted to old age. The pathophysiology of the disease is characterized by specific pathological changes in brain. The changes (i.e. accumulation of metal ions in brain, formation of extracellular β-amyloid (Aβ) peptide aggregates and tangle of hyper phosphorylated Tau protein inside neurons) damage the neuronal connections irreversibly. The current issues in improvement of life quality of Alzheimer's patient lies in the fact that the diagnosis is made at a late stage of the disease and the medications do not treat the basic causes of Alzheimer's. The targeted delivery of drug through the blood brain barrier (BBB) poses several limitations via traditional approaches for treatment. To overcome these drug delivery limitation, nanoparticles provide a promising solution. This review focuses on current strategies for efficient targeted drug delivery using nanoparticles and improving the quality of therapy provided to the patient. Nanoparticles can be used to encapsulate drug (which is generally hydrophobic) to ensure its passage to brain; they can be conjugated to metal ion chelators to reduce the metal load in neural tissue thus lowering the harmful effects of oxidative damage; can be conjugated with drug and monoclonal antibodies against BBB endogenous receptors. Finally this review covers how the nanoparticles can play a role in diagnosing the disease.

Keywords: Alzheimer's disease, β-amyloid plaques, blood brain barrier, metal chelators, nanoparticles

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Authors: Dilnee D. Suraweera, Tim Groom, Brian Chung, Brendan Bond, Andrew Schipp, Marc E. Nicolas

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Pyrethrum (Tanacetum cinerariifolium) is a perennial plant belongs to family Asteraceae. This is cultivated commercially for extraction of natural insecticide pyrethrins, which accumulates in their flower head achenes. Approximately 94% of the pyrethrins are produced within secretory ducts and trichomes of achenes of the mature pyrethrum flower. This is the most widely used botanical insecticide in the world and Australia is the current largest pyrethrum producer in the world. Rainfall in pyrethrum growing regions in Australia during pyrethrum flowering period, in late spring and early summer is significantly less. Due to lack of adequate soil moisture and under elevated temperature conditions during post-anthesis period, resulting in yield reductions. Therefore, understanding of yield responses of pyrethrum to irrigation is important for Pyrethrum as a commercial crop. Irrigation management has been identified as a key area of pyrethrum crop management strategies that could be manipulated to increase yield. Pyrethrum is a comparatively drought tolerant plant and it has some ability to survive in dry conditions due to deep rooting. But in dry areas and in dry seasons, the crop cannot reach to its full yield potential without adequate soil moisture. Therefore, irrigation is essential during the flowering period prevent crop water stress and maximise yield. Irrigation during the water deficit period results in an overall increased rate of water uptake and growth by the plant which is essential to achieve the maximum yield benefits from commercial crops. The effects of irrigation treatments applied at post-anthesis period on pyrethrum yield responses were studied in two irrigation methods. This was conducted in a first harvest commercial pyrethrum field in Waubra, Victoria, during 2012/2013 season. Drip irrigation and overhead sprinkler irrigation treatments applied during whole flowering period were compared with ‘rainfed’ treatment in relation to flower yield and pyrethrin yield responses. The results of this experiment showed that the application of 180mm of irrigation throughout the post-anthesis period, from early flowering stages to physiological maturity under drip irrigation treatment increased pyrethrin concentration by 32%, which combined with the 95 % increase in the flower yield to give a total pyrethrin yield increase of 157%, compared to the ‘rainfed’ treatment. In contrast to that overhead sprinkler irrigation treatment increased pyrethrin concentration by 19%, which combined with the 60 % increase in the flower yield to give a total pyrethrin yield increase of 91%, compared to the ‘rainfed’ treatment. Irrigation treatments applied throughout the post-anthesis period significantly increased flower yield as a result of enhancement of number of flowers and flower size. Irrigation provides adequate soil moisture for flower development in pyrethrum which slows the rate of flower development and increases the length of the flowering period, resulting in a delayed crop harvest (11 days) compared to the ‘rainfed’ treatment. Overall, irrigation has a major impact on pyrethrin accumulation which increases the rate and duration of pyrethrin accumulation resulting in higher pyrethrin yield per flower at physiological maturity. The findings of this study will be important for future yield predictions and to develop advanced agronomic strategies to maximise pyrethrin yield in pyrethrum.

Keywords: achene, drip irrigation, overhead irrigation, pyrethrin

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Authors: João F. A. Martos, Felipe J. Costa, Sergio N. P. Laiton, Bruno C. Lima, Israel S. Rêgo, Paulo P. G. Toro

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Nowadays, the scramjet is a topic that has attracted the attention of several scientific communities (USA, Australia, Germany, France, Japan, India, China, Russia), that are investing in this in this type of propulsion system due its interest to facilitate access to space and reach hypersonic speed, who have invested in this type of propulsion due to the interest in facilitating access to space. The Brazilian hypersonic scramjet aerospace vehicle 14-X B is a technological demonstrator of a hypersonic airbreathing propulsion system based on the supersonic combustion (scramjet) intended to be tested in flight into the Earth's atmosphere at 30 km altitude and Mach number 7. The 14-X B has been designed at the Prof. Henry T. Nagamatsu Laboratory of Aerothermodynamics and Hypersonics of the Institute for Advanced Studies (IEAv) in Brazil. The IEAv Hypersonic Shock Tunnel, named T3, is a ground-test facility able to reproduce the flight conditions as the Mach number as well as pressure and temperature in the test section close to those encountered during the test flight of the vehicle 14-X B into design conditions. A 1-m long stainless steel 14-X B model was experimentally investigated at T3 Hypersonic Shock Tunnel, for freestream Mach number 7. Static pressure measurements along the lower surface of the 14-X B model, along with high-speed schlieren photographs taken from the 5.5° leading edge and the 14.5° deflection compression ramp, provided experimental data that were compared to the analytical-theoretical solutions and the computational fluid dynamics (CFD) simulations. The results show a good qualitative agreement, and in consequence demonstrating the importance of these methods in the project of the 14-X B hypersonic aerospace vehicle.

Keywords: 14-X, CFD, hypersonic, hypersonic shock tunnel, scramjet

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Authors: Laetitia Dari

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The brand constitutes a source of differentiation between competitors. It highlights specific characteristics that create value for the enterprise. Today the concept of a brand is not just about the product but can concern territories. The competition between territories, due to tourism, research, jobs, etc., leads territories to develop territorial brands to bring out their identity and specificity. Some territorial brands are based on natural resources or products characteristic of a territory. In the French wood sector, we can observe the emergence of many territorial brands. Supported by the inter-professional organization, these brands have the main objective of showcasing wood as a source of solutions at the local level in terms of construction and energy. The implementation of these collective projects raises the question of the way in which relations between companies are structured and animated. The central question of our work is to understand how the territorial brand promotes the structuring of a sector and the construction of collective relations between actors. In other words, we are interested in the conditions for the emergence of the territorial brand and the way in which it will be a means of mobilizing the actors around a common project. The objectives of the research are (1) to understand in which context a territorial brand emerges, (2) to analyze the way in which the territorial brand structures the collective relations between actors, (3) to give entry keys to the actors to successfully develop this type of project. Thus, our research is based on a qualitative methodology with semi-structured interviews conducted with the main territorial brands in France. The research will answer various academic and empirical questions. From an academic point of view, it brings elements of understanding to the construction of a collective project and to the way in which governance operates. From an empirical point of view, the interest of our work is to bring out the key success factors in the development of a territorial brand and how the brand can become an element of valuation for a territory.

Keywords: brand, marketing, strategy, territory, third party stakeholder, wood

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Authors: Wheyming Tina Song, Chi-Hao Hong

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In this study, we investigate the effect of a new boarding policy - short stay, on the overcrowding efficiency in emergency department (ED). The decision variables are no. of short stay beds for least acuity ED patients. The performance measurements used are national emergency department overcrowding score (NEDOCS) and ED retention rate (the percentage that patients stay in ED over than 48 hours in one month). Discrete event simulation (DES) is used as an analysis tool to evaluate the strategy. Also, common random number (CRN) technique is applied to enhance the simulation precision. The DES model was based on a census of 6 months' patients who were treated in the ED of the National Taiwan University Hospital Yunlin Branch. Our results show that the new short-stay boarding significantly impacts both the NEDOCS and ED retention rate when the no. of short stay beds is more than three.

Keywords: emergency department (ED), common random number (CRN), national emergency department overcrowding score (NEDOCS), discrete event simulation (DES)

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Authors: Khalid Ahmed Eldwaib

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In this study, Al-Mg alloy 5052 was used as the testing material. Corrosion fatigue life was studied for the alloy in 3.5% NaCl (pH=1, 3, 5, 7, 9, and 11), and 3.5% NaCl (pH=1) with inhibitors. The compound inhibitors were composed mainly of phosphate (PO4³-), adding a certain proportion of other nontoxic inhibitors so as to select alternatives to environmentally hazardous chromate (Cr2O7²-). The inhibitors were sodium dichromate Na2Cr2O7, sodium phosphate Na3PO4, sodium molybdate Na2MoO4, and sodium citrate Na3C6H5O7. The total amount of inhibiting pigments was at different concentrations (250,500,750, and 1000 ppm) in the solutions. Corrosion fatigue behavior was studied by using plane-bending corrosion fatigue machine with stress ratio R=0.5 and under the constant frequency of 13.3 Hz. Results show that in 3.5% NaCl the highest fatigue life (number of cycles to failure Nf) is obtained at pH=5 where the oxide film on aluminum has very low solubility, and the lowest number of cycles is obtained at pH=1, where the media is too aggressive (extremely acidic). When the concentration of inhibitor increases the cycles to failure increase. The surface morphology and fracture section of the specimens had been characterized through scanning electron microscope (SEM).

Keywords: Al-Mg alloy 5052, corrosion, fatigue, inhibitors

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Authors: Anne-Lena Kampen, Øivind Kure

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Machine learning (ML) can be implemented in Wireless Sensor Networks (WSNs) as a central solution or distributed solution where the ML is embedded in the nodes. Embedding improves privacy and may reduce prediction delay. In addition, the number of transmissions is reduced. However, quality factors such as prediction accuracy, fault detection efficiency and coordinated control of the overall system suffer. Here, we discuss and highlight the trade-offs that should be considered when choosing between embedding and centralized ML, especially for multihop networks. In addition, we present estimations that demonstrate the energy trade-offs between embedded and centralized ML. Although the total network energy consumption is lower with central prediction, it makes the network more prone for partitioning due to the high forwarding load on the one-hop nodes. Moreover, the continuous improvements in the number of operations per joule for embedded devices will move the energy balance toward embedded prediction.

Keywords: central machine learning, embedded machine learning, energy consumption, local machine learning, wireless sensor networks, WSN

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Authors: Getachew Tilahun, Oluwole Makinde, David Malonza

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We propose and analyze a non-linear mathematical model for the transmission dynamics of pneumonia disease in a population of varying size. The deterministic compartmental model is studied using stability theory of differential equations. The effective reproduction number is obtained and also the local and global asymptotically stability conditions for the disease free and as well as for the endemic equilibria are established. The model exhibit a backward bifurcation and the sensitivity indices of the basic reproduction number to the key parameters are determined. Using Pontryagin’s maximum principle, the optimal control problem is formulated with three control strategies; namely disease prevention through education, treatment and screening. The cost effectiveness analysis of the adopted control strategies revealed that the combination of prevention and treatment is the most cost effective intervention strategies to combat the pneumonia pandemic. Numerical simulation is performed and pertinent results are displayed graphically.

Keywords: cost effectiveness analysis, optimal control, pneumonia dynamics, stability analysis, numerical simulation

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Authors: Hanbey Hazar, Hakan Gul

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In this study; piston, exhaust, and suction valves of a diesel engine were coated in 300 mm thickness with Tungsten Carbide (WC) by using the HVOF coating method. Mathematical modeling of a coated and uncoated (standardized) engine was performed by using ANN (Artificial Neural Networks). The purpose was to decrease the number of repetitions of tests and reduce the test cost through mathematical modeling of engines by using ANN. The results obtained from the tests were entered in ANN and therefore engines' values at all speeds were estimated. Results obtained from the tests were compared with those obtained from ANN and they were observed to be compatible. It was also observed that, with thermal barrier coating, hydrocarbon (HC), carbon monoxide (CO), and smoke density values of the diesel engine decreased; but nitrogen oxides (NOx) increased. Furthermore, it was determined that results obtained through mathematical modeling by means of ANN reduced the number of test repetitions. Therefore, it was understood that time, fuel and labor could be saved in this way.

Keywords: Artificial Neural Network, Diesel Engine, Mathematical Modelling, Thermal Barrier Coating

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Authors: Turki M. Habeebullah, Atef M. F. Mohammed, Essam A. Morsy

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In recent decades, particulate matter (PM10) have received much attention due to its potential adverse health impact and the subsequent need to better control or regulate these pollutants. The aim of this paper is focused on study risk assessment of PM10 in four different districts (Shebikah, Masfalah, Aziziyah, Awali) in Makkah, Saudi Arabia during the period from 1 Ramadan 1434 AH - 27 Safar 1435 AH. samples was collected by using Low Volume Sampler (LVS Low Volume Sampler) device and filtration method for estimating the total concentration of PM10. The study indicated that the mean PM10 concentrations were 254.6 (186.1 - 343.2) µg/m3 in Shebikah, 184.9 (145.6 - 271.4) µg/m3 in Masfalah, 162.4 (92.4 - 253.8) µg/m3 in Aziziyah, and 56.0 (44.5 - 119.8) µg/m3 in Awali. These values did not exceed the permissible limits in PME (340 µg/m3 as daily average). Furthermore, health assessment is carried out using AirQ2.2.3 model to estimate the number of hospital admissions due to respiratory diseases. The cumulative number of cases per 100,000 were 1534 (18-3050 case), which lower than that recorded in the United States, Malaysia. The concentration response coefficient was 0.49 (95% CI 0.05 - 0.70) per 10 μg/m3 increase of PM10.

Keywords: air pollution, respiratory diseases, airQ2.2.3, Makkah

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Authors: E. Ghayoula, M. Haj Taieb, A. Bouallegue, J. Y. Chouinard, R. Ghayoula

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This paper evaluates the bit error rate (BER) performance of MIMO systems for wireless communication. MIMO uses multiple transmitting antennas, multiple receiving antennas and the space-time block codes to provide diversity. MIMO transmits signal encoded by space-time block (STBC) encoder through different transmitting antennas. These signals arrive at the receiver at slightly different times. Spatially separated multiple receiving antennas are employed to provide diversity reception to combat the effect of fading in the channel. This paper presents a detailed study of diversity coding for MIMO systems. STBC techniques are implemented and simulation results in terms of the BER performance with varying number of MIMO transmitting and receiving antennas are presented. Our results show how increasing the number of both transmit and receive antenna improves system performance and reduces the bit error rate.

Keywords: MIMO systems, diversity, BER, MRRC, SIMO, MISO, STBC, alamouti, SNR

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Authors: Susan Lanz, Gary T. Burke, Omid Omidvar

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The intention to transfer ownership control across family generations is acknowledged to be central to developing a theoretical understanding of how family businesses differ and are distinct as a business group. However, in practice, most business-owning families face challenges to transfer their business ownership from one family generation to the next. To date, researchers have paid little attention to how and when ownership is passed across family generations and what the dynamics of such transitions are. This is primarily due to the prevailing assumption that ownership transfer is an unimportant and legalistic issue that occurs within a wider family management succession process. Yet, the limited evidence available suggests that family ownership transfer occurs inside and outside of the management succession process and is a difficult process for business-owning families to navigate. As a result, many otherwise viable family businesses are closing, leading to unnecessary loss of jobs and knowledge. This qualitative paper examines how family members understand and navigate the ownership transfer process. This study uses an inductive qualitative research design, conducted through in-depth interviews within eight business-owning families. It draws on family development theory and shows how a wide range of family-related events and dynamics outside of family business involvement underlie and shape the ownership transfer process. The findings extend the theory on how these events trigger ownership transfer and how they shape the ownership meanings held within business-owning families. This study found that ownership transfer meanings extend beyond that of transferring the legal control and financial appropriation rights of shareholders. The study concludes there are three different stages in the process of ownership transfer -symbolic, re-balancing, and protectionist. Each stage creates distinct family social constructions of the rights of family members to hold business ownership, and each stage occurs within a specific family development phase.

Keywords: business-owning family, family development theory, ownership transfer, process

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Authors: Damir Počakal

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Continental part Croatia is exposed, mainly in the summer months, to the frequent occurrence of severe thunderstorms and hail. In the 1960s, aiming to protect and reduce the damage, an operational hail suppression system was introduced in that area. The current protected area is 26800 km2 and has about 580 hail suppression stations (rockets and ground generators) which are managed with 8 radar centres (S-band radars). In order to obtain objective and precise hailstone measurement for different research studies, hailpads were installed on all this stations in 2001. Additionally the dense hailpad network with the dimensions of 20 km x 30 km (1 hailpad per 4 km2), was established in the area with the highest average number of days with hail in Croatia in 2002. This paper presents analysis of relation between radar measured parameters of Cb cells in the time of hail fall with physical parameters of hail (max. diameter, number of hail stones and kinetic energy) measured on hailpads in period 2002 -2014. In addition are compared radar parameters of Cb cells with and without hail on the ground located at the same time over the polygon area.

Keywords: Cb cell, hail, radar, hailpad

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Authors: Yunusa Aliyu Hadejia

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Cholera is a gastrointestinal disease caused by a bacterium called Vibrio Cholerae which spread as a result of eating food or drinking water contaminated with feaces from an infected person. In this work we proposed and analyzed the impact of isolating infected people and give them therapeutic treatment, the specific objectives of the research was to formulate a mathematical model of cholera transmission incorporating treatment class, to make analysis on stability of equilibrium points of the model, positivity and boundedness was shown to ensure that the model has a biological meaning, the basic reproduction number was derived by next generation matrix approach. The result of stability analysis show that the Disease free equilibrium was both locally and globally asymptotically stable when R_0< 1 while endemic equilibrium has locally asymptotically stable when R_0> 1. Sensitivity analysis was perform to determine the contribution of each parameter to the basic reproduction number. Numerical simulation was carried out to show the impact of the model parameters using MAT Lab Software.

Keywords: mathematical model, treatment, stability, sensitivity

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Authors: Olesya Bolkhovskaya, Alexander Maltsev

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Antenna arrays are widely used in modern radio systems in sonar and communications. The solving of the detection problems of a useful signal on the background of noise is based on the GLRT method. There is a large number of problem which depends on the known a priori information. In this work, in contrast to the majority of already solved problems, it is used only difference spatial properties of the signal and noise for detection. We are analyzing the influence of the degree of non-coherence of signal and noise unhomogeneity on the performance characteristics of different GLRT statistics. The description of the signal and noise is carried out by means of the spatial covariance matrices C in the cases of different number of known information. The partially coherent signal is simulated as a plane wave with a random angle of incidence of the wave concerning a normal. Background noise is simulated as random process with uniform distribution function in each element. The results of investigation of degradation of performance characteristics for different cases are represented in this work.

Keywords: GLRT, Neumann-Pearson’s criterion, Test-statistics, degradation, spatial processing, multielement antenna array

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Authors: Vesile Evrim, Aliyu Awwal

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By the evolvement in technology, the way of expressing opinions switched the direction to the digital world. The domain of politics as one of the hottest topics of opinion mining research merged together with the behavior analysis for affiliation determination in text which constitutes the subject of this paper. This study aims to classify the text in news/blogs either as Republican or Democrat with the minimum number of features. As an initial set, 68 features which 64 are constituted by Linguistic Inquiry and Word Count (LIWC) features are tested against 14 benchmark classification algorithms. In the later experiments, the dimensions of the feature vector reduced based on the 7 feature selection algorithms. The results show that Decision Tree, Rule Induction and M5 Rule classifiers when used with SVM and IGR feature selection algorithms performed the best up to 82.5% accuracy on a given dataset. Further tests on a single feature and the linguistic based feature sets showed the similar results. The feature “function” as an aggregate feature of the linguistic category, is obtained as the most differentiating feature among the 68 features with 81% accuracy by itself in classifying articles either as Republican or Democrat.

Keywords: feature selection, LIWC, machine learning, politics

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Authors: Natalia Feruleva

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The goal of this paper is to develop the fraud risk assessment model basing on both relational and financial data and test the impact of the relationships between Russian non-public companies on the likelihood of financial fraud commitment. Relationships mean various linkages between companies such as parent-subsidiary relationship and person-related relationships. These linkages may provide additional opportunities for committing fraud. Person-related relationships appear when firms share a director, or the director owns another firm. The number of companies belongs to CEO and managed by CEO, the number of subsidiaries was calculated to measure the relationships. Moreover, the dummy variable describing the existence of parent company was also included in model. Control variables such as financial leverage and return on assets were also implemented because they describe the motivating factors of fraud. To check the hypotheses about the influence of the chosen parameters on the likelihood of financial fraud, information about person-related relationships between companies, existence of parent company and subsidiaries, profitability and the level of debt was collected. The resulting sample consists of 160 Russian non-public firms. The sample includes 80 fraudsters and 80 non-fraudsters operating in 2006-2017. The dependent variable is dichotomous, and it takes the value 1 if the firm is engaged in financial crime, otherwise 0. Employing probit model, it was revealed that the number of companies which belong to CEO of the firm or managed by CEO has significant impact on the likelihood of financial fraud. The results obtained indicate that the more companies are affiliated with the CEO, the higher the likelihood that the company will be involved in financial crime. The forecast accuracy of the model is about is 80%. Thus, the model basing on both relational and financial data gives high level of forecast accuracy.

Keywords: financial fraud, fraud prediction, non-public companies, regression analysis, relational data

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Authors: Tsukasa Ogawa, Mitsuhiro Okayasu

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To examine the generation properties of electric power for piezoelectric (PbZrTiO3) ceramic plates, the electric-power generation characteristics were examined experimentally and numerically during cyclic bending under various loading fixtures with different contact condition, i.e., point and area contact. In the low applied loading condition between 10 and 50 N, increasing the load-contact area on the piezoelectric ceramic led to a nonlinear decrease in the generated voltage. Decreasing contact area, including the point contact, basically enhanced the generated voltage, although the voltage saturated during loading when the contact area is less than ϕ5 mm, which was attributed to the high strain status, resulting in the material failure, i.e., high stress concentration. In this case, severe plastic deformation and the domain switching were dominated failure modes in the ceramic. From this approach, it is clear that the applied load became more larger (50 ~100 N), larger contact area (ϕ10 ~ ϕ20 mm) became advantageous for power generation. Based upon this cyclic loading was carried out to investigate the fatigue characteristics of the piezoelectric ceramic late. For all contact conditions, electric voltage dropped in the beginning of the cyclic loading, although the higher electric generation was stable in the further cyclic loading for the contact area of ϕ10 ~ ϕ20 mm. In constant, further decrement of electric generation occurred for the point contact condition, and the low electric voltage was generated for the larger contact condition.

Keywords: electric power generation, piezoelectric ceramic, lead zirconate titanate ceramic, loading conditions

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Authors: Suvorov Vasyl, Filipchuk Viktor

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Background: If non-surgical treatment of developmental dysplasia of the hip (DDH) fails or if DDH is late-detected, surgery is necessary. Salter pelvic osteotomy (SPO) is an effective surgical option for such cases. The objectives of this study were to assess the results after SPO, evaluate risk factors, and reveal those radiological parameters that may correlate with the results. Mid- and long-term postoperative results after SPO in 17 patients (22 hip joints) were analyzed. Risk factors included those that do not depend on the surgeon (patient's age, value of the acetabular index (AI) preoperatively, DDH Tonnis grade) and those that depend on the surgeon (amount of AI correction). To radiological parameters which may correlate with the amount of AI correction, we referred distance "d" and the lateral rotation angle. Results: SPO allows performing AI correction in ranges 24.1 ± 6.5°. Excellent and good clinical results were obtained in 95.5% of patients; excellent and good radiological results in 86.4% of patients. Risk factors that do not depend on the surgeon were older patient’s age and higher preoperative AI values (p < 0.05). The risk factor that depends on the surgeon was the amount of AI correction (p < 0.05). The distance "d" was recognized as a radiological parameter that may indicate sufficient AI correction (p < 0.05). Conclusion: In older patients with a higher preoperative AI value, the results will be predictably worse. The surgeon may influence the result with a greater amount of AI correction (which may also be indicated radiologically by the distance "d" values).

Keywords: developmental dysplasia of the hip, results, risk factor, pelvic osteotomy, salter osteotomy

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Authors: Karun K. Karki

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Globalization has intensified the transnational movement of people, mainly from the Global South to the Global North. In this context of transnationalism, migration is framed within the national interests required for economic prosperity. More specifically, the competition for the ‘best and the brightest of highly educated immigrants from around the world can be perceived as evidence that countries in the North are competing in the knowledge-based global economy. Canada is not an exception. Since the early 1970s, Canada has successfully admitted, on average, 200,000 to 280,000 immigrants annually for permanent residency, primarily for economic development, family reunification and humanitarian affairs. Among these three components, economic class immigrants are the highest priority in its immigration policy. Although Canada admits highly qualified immigrant professionals with the expectation of easily integrating them, many highly skilled immigrants are marginalized in the labour market due to a myriad of layered structural and institutional barriers that prevent them from working in the professions for which they were trained in their country of origin. More than 67% of highly skilled immigrants are more likely to be in jobs for which they are formally overqualified. The deteriorating employment situation of highly educated immigrants, particularly the immigrants of racialized groups, needs analytical scrutiny of the immigration policy of Canada. In this paper, author examine how the historical legacy of colonialism still continues in Canada’s immigration policymaking and how this legacy has impacted developing countries in the global South. Author argue that the Canadian immigration policy is based on the notion of exploiting/dominating smaller countries and immigrants from these countries. Such colonial policies have systematically ‘Othered’ immigrants based on their race, ethnicity, gender, culture, and linguistic characteristics. Recommendations are made to revisit contemporary immigration and settlement policies to effectively integrate immigrants into Canadian society.

Keywords: colonialism, Canadian immigration policy, racialized immigrants, skilled immigrants

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Authors: Rhea Kapoor

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Fractal dimension provides a way to characterize non-geometric shapes like those found in nature. The purpose of this research is to estimate Minkowski fractal dimension of human lung images for early detection of lung cancer. Lung cancer is the leading cause of death among all types of cancer and an early histopathological analysis will help reduce deaths primarily due to late diagnosis. A Python application program, PathoPy2.0, was developed for analyzing medical images in pixelated format and estimating Minkowski fractal dimension using a new box-counting algorithm that allows windowing of images for more accurate calculation in the suspected areas of cancerous growth. Benchmark geometric fractals were used to validate the accuracy of the program and changes in fractal dimension of lung images to indicate the presence of issues in the lung. The accuracy of the program for the benchmark examples was between 93-99% of known values of the fractal dimensions. Fractal dimension values were then calculated for lung images, from National Cancer Institute, taken over time to correctly detect the presence of cancerous growth. For example, as the fractal dimension for a given lung increased from 1.19 to 1.27 due to cancerous growth, it represents a significant change in fractal dimension which lies between 1 and 2 for 2-D images. Based on the results obtained on many lung test cases, it was concluded that fractal dimension of human lungs can be used to diagnose lung cancer early. The ideas behind PathoPy2.0 can also be applied to study patterns in the electrical activity of the human brain and DNA matching.

Keywords: fractals, histopathological analysis, image processing, lung cancer, Minkowski dimension

Procedia PDF Downloads 156

Authors: Susan Diamond

Abstract:

Machine Learning workloads have traditionally been run in high-performance computing (HPC) environments, where users log in to dedicated machines and utilize the attached GPUs to run training jobs on huge datasets. Training of large neural network models is very resource intensive, and even after exploiting parallelism and accelerators such as GPUs, a single training job can still take days. Consequently, the cost of hardware is a barrier to entry. Even when upfront cost is not a concern, the lead time to set up such an HPC environment takes months from acquiring hardware to set up the hardware with the right set of firmware, software installed and configured. Furthermore, scalability is hard to achieve in a rigid traditional lab environment. Therefore, it is slow to react to the dynamic change in the artificial intelligent industry. Watson Deep Learning as a service, a cloud-based deep learning platform that mitigates the long lead time and high upfront investment in hardware. It enables robust and scalable sharing of resources among the teams in an organization. It is designed for on-demand cloud environments. Providing a similar user experience in a multi-tenant cloud environment comes with its own unique challenges regarding fault tolerance, performance, and security. Watson Deep Learning as a service tackles these challenges and present a deep learning stack for the cloud environments in a secure, scalable and fault-tolerant manner. It supports a wide range of deep-learning frameworks such as Tensorflow, PyTorch, Caffe, Torch, Theano, and MXNet etc. These frameworks reduce the effort and skillset required to design, train, and use deep learning models. Deep Learning as a service is used at IBM by AI researchers in areas including machine translation, computer vision, and healthcare. 

Keywords: deep learning, machine learning, cognitive computing, model training

Procedia PDF Downloads 196