Search results for: computational neural networks

Authors: Trevor Sabiston, Mohsen Mohammadi, Mohammed Cherkaoui, Kaan Inal

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A new micromechanics framework is developed for long fibre reinforced composites using a single fibre surrounded by a functionally graded interphase and matrix as a representative unit cell. The unit cell is formulated to represent any number of aligned fibres by a single fibre. Using this model the elastic response of long fibre composites is predicted in all directions. The model is calibrated to experimental results and shows very good agreement in the elastic regime. The differences between the proposed model and existing models are discussed.

Keywords: computational mechanics, functionally graded interphase, long fibre composites, micromechanics

Procedia PDF Downloads 316

Authors: Juraj Camaj, Martin Kendra, Jaroslav Masek

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The paper is focused to the evaluation railway tracks in the Slovakia by using Multi-Criteria method. Evaluation of railway tracks has important impacts for the assessment of investment in technical equipment. Evaluation of railway tracks also has an important impact for the allocation of marshalling yards. Marshalling yards are in transport model as centers for the operation assigned catchment area. This model is one of the effective ways to meet the development strategy of the European Community's railways. By applying this model in practice, a transport company can guarantee a higher quality of service and then expect an increase in performance. The model is also applicable to other rail networks. This model supplements a theoretical problem of train formation problem of new ways of looking at evaluation of factors affecting the organization of wagon flows.

Keywords: railway track, multi-criteria methods, evaluation, transportation model

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Authors: Alina Petronela Negrea, Valentin Cojanu

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The article examines the synergy between innovation and entrepreneurship by means of a qualitative research on actors in the automotive industry in the Romanian southern region, Muntenia. The region is of particular interest because most of the industry suppliers are located there, as well as because it gathers the full range of key actors involved in the innovation process. The research design aims (1) to reflect entrepreneurs’ approach to and perception on innovation; (2) to underline forces driving or stifling innovation in the automotive industry; and (3) to evaluate the awareness of the existing knowledge database and the communication channels through which it is transferred within and between innovation networks. Empirical evidence results from triangula¬tion of three data collection methods: statistical data and other publicly available materials; semi - structured inter¬views, and experiential visits. The conclusions emphasize the convergent opinion of the entrepreneurs about the vital role of innovation in their investment plans.

Keywords: automotive industry, entrepreneurship, innovation, Romania

Procedia PDF Downloads 548

Authors: Boudjedra Abderrahim, Toumi Salah, Boutalbi Mostefa, Frihi Mohammed

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Nowadays, using the advancement of technology in semiconductor device fabrication, many transistors can be integrated to a single chip (VLSI). Although the growth chip density potentially eases systems-on-chip (SoCs) integrating thousands of processing element (PE) such as memory, processor, interfaces cores, system complexity, high-performance interconnect and scalable on-chip communication architecture become most challenges for many digital and embedded system designers. Networks-on-chip (NoCs) becomes a new paradigm that makes possible integrating heterogeneous devices and allows many communication constraints and performances. In this paper, we are interested for good performance and low area for implementation and a behavioral modeling of network on chip mesh topology design using VHDL hardware description language with performance evaluation and FPGA implementation results.

Keywords: design, implementation, communication system, network on chip, VHDL

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Authors: Vinay Kumar Vanjakula, Frank Adam, Nils Goseberg, Christian Windt

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When a structure is installed on a seabed, the presence of the structure will influence the flow field around it. The changes in the flow field include, formation of vortices, turbulence generation, waves or currents flow breaking and pressure differentials around the seabed sediment. These changes allow the local seabed sediment to be carried off and results in Scour (erosion). These are a threat to the structure's stability. In recent decades, rapid developments of research work and the knowledge of scour On fixed structures (bridges and Monopiles) in rivers and oceans has been carried out, and very limited research work on scour and liquefaction for gravity anchors, particularly for floating Tension Leg Platform (TLP) substructures. Due to its importance and need for enhancement of knowledge in scour and liquefaction around marine structures, the MarTERA funded a three-year (2020-2023) research program called NuLIMAS (Numerical Modeling of Liquefaction Around Marine Structures). It’s a group consists of European institutions (Universities, laboratories, and consulting companies). The objective of this study is to build a numerical model that replicates the reality, which indeed helps to simulate (predict) underwater flow conditions and to study different marine scour and Liquefication situations. It helps to design a heavyweight anchor for the TLP substructure and to minimize the time and expenditure on experiments. And also, the achieved results and the numerical model will be a basis for the development of other design and concepts For marine structures. The Computational Fluid Dynamics (CFD) numerical model will build in OpenFOAM. A conceptual design of heavyweight anchor for TLP substructure is designed through taking considerations of available state-of-the-art knowledge on scour and Liquefication concepts and references to Previous existing designs. These conceptual designs are validated with the available similar experimental benchmark data and also with the CFD numerical benchmark standards (CFD quality assurance study). CFD optimization model/tool is designed as to minimize the effect of fluid flow, scour, and Liquefication. A parameterized model is also developed to automate the calculation process to reduce user interactions. The parameters such as anchor Lowering Process, flow optimized outer contours, seabed interaction study, and FSSI (Fluid-Structure-Seabed Interactions) are investigated and used to carve the model as to build an optimized anchor.

Keywords: gravity anchor, liquefaction, scour, computational fluid dynamics

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Authors: Dalu Zhang, Xiang Jin, Dejiang Zhou, Jianpeng Wang, Haiying Jiang

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Traditional TCP/IP network is showing lots of shortages and research for future networks is becoming a hotspot. FIA (Future Internet Architecture) and FIA-NP (Next Phase) are supported by US NSF for future Internet designing. Moreover, virtual machine migration is a significant technique in cloud computing. As a network application, it should also be supported in XIA (expressive Internet Architecture), which is in both FIA and FIA-NP projects. This paper is an experimental study aims at verifying the feasibility of VM migration over XIA. We present three ways to maintain VM connectivity and communication states concerning DAG design and routing table modification. VM migration experiments are conducted intra-AD and inter-AD with KVM instances. The procedure is achieved by a migration control protocol which is suitable for the characters of XIA. Evaluation results show that our solutions can well supports full live VM migration over XIA network respectively, keeping services seamless.

Keywords: DAG, downtime, virtual machine migration, XIA

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Authors: A. Perdomo, J. R. Bacca, Q. E. Jabid

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In recent years, technological and investigative progress has been achieved in the area of monitoring of equipment and installation as a result of a deeper understanding of physical phenomenon associated with the non-destructive tests (NDT). The modal analysis proposes an efficient solution to determine the dispersion curves of an arbitrary waveguide cross-sectional. Dispersion curves are essential in the discontinuity localization based on guided waves. In this work, an isotropic hollow cylinder is dynamically analyzed in ANSYS to obtain resonant frequencies and mode shapes all of them associated with the dispersion curves. The numerical results provide the relation between frequency and wavelength which is the foundation of the dispersion curves. Results of the simulation process are validated with the software GUIGW.

Keywords: ansys APDL, dispersion curves, guide waves, modal analysis

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Authors: Li Li, Kai-Hsuan Chu

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It is well known that the real estate price depends on a lot of factors. Each house current value is dependent on the location, room number, transportation, living convenience, year and surrounding environments. Although, there are different experienced models for housing agent to estimate the price, it is a case by case study without overall dynamic variation investigation. However, many economic parameters may more or less influence the real estate price variation. Here, the influences of most macroeconomic parameters on real estate price are investigated individually based on least-square scheme and grey correlation strategy. Then those parameters are classified into leading indices, simultaneous indices and laggard indices. In addition, the leading time period is evaluated based on least square method. The important leading and simultaneous indices can be used to establish an artificial intelligent neural network model for real estate price variation prediction. The real estate price variation of Taipei, Taiwan during 2005 ~ 2017 are chosen for this research data analysis and validation. The results show that the proposed method has reasonable prediction function for real estate business reference.

Keywords: real estate price, least-square, grey correlation, macroeconomics

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Authors: Neziha Jaouedi, Noureddine Boujnah, Mohamed Salim Bouhlel

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In the framework of human machine interaction systems enhancement, we focus throw this paper on human behavior analysis and action recognition. Human behavior is characterized by actions and reactions duality (movements, psychological modification, verbal and emotional expression). It’s worth noting that many information is hidden behind gesture, sudden motion points trajectories and speeds, many research works reconstructed an information retrieval issues. In our work we will focus on motion extraction, tracking and action recognition using wavelet network approaches. Our contribution uses an analysis of human subtraction by Gaussian Mixture Model (GMM) and body movement through trajectory models of motion constructed from kalman filter. These models allow to remove the noise using the extraction of the main motion features and constitute a stable base to identify the evolutions of human activity. Each modality is used to recognize a human action using wavelets of derived beta distributions approach. The proposed approach has been validated successfully on a subset of KTH and UCF sports database.

Keywords: feautures extraction, human action classifier, wavelet neural network, beta wavelet

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Authors: Anastasiya Paltarzhitskaya

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Subjective time plays an important role in consciousness processes and self-awareness at the moment. The concept of intrinsic neural timescales (INT) explains the difference in perceiving various time intervals. The capacity to experience the present builds on the fundamental properties of temporal cognition. The challenge that both philosophy and neuroscience try to answer is how the brain differentiates the present from the past and future. In our work, we analyze papers which describe mechanisms involved in the perception of ‘present’ and ‘non-present’, i.e., future and past moments. Taking into account that we perceive time intervals even during rest or relaxation, we suppose that the default-mode network activity can code time features, including the present moment. We can compare some results of time perceptual studies, where brain activity was shown in states with different flows of time, including resting states and during “mental time travel”. According to the concept of mental traveling, we employ a range of scenarios which demand episodic memory. However, some papers show that the hippocampal region does not activate during time traveling. It is a controversial result that is further complicated by the phenomenological aspect that includes a holistic set of information about the individual’s past and future.

Keywords: temporal consciousness, time perception, memory, present

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Authors: Fernanda Pinheiro Martins, Pedro Teixeira Lacava

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The objective of this research is to analyze the effects of different spark plug conditions in engine-like conditions by applying computational fluid dynamics analysis. The 3D models applied consist of 3-Zones Extended Coherent Flame (ECFM-3Z) and Imposed Stretch Spark Ignition Model (ISSIM), respectively, for the combustion and the spark plug modelling. For this study, it was applied direct injection fuel system in a single cylinder engine operating with E0. The application of realistic operating conditions (load and speed) to the different cases studied will provide a deeper understanding of the effects of the spark plug gap, a result of parts outwearing in most of the cases, to the development of the combustion in engine-like conditions.

Keywords: engine, CFD, direct injection, combustion, spark plug

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Authors: Eman Hegazy, Stefan Anderberg, Joakim Krook

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Urban water infrastructure is crucial for efficient and reliable water supply in growing cities. With the growth of cities, the need for maintenance and renewal of these systems increases but often goes unfulfilled due to a variety of reasons, such as limited funding, political priorities, or lack of public awareness. Neglecting the renewal needs of these systems can lead to frequent malfunctions and reduced quality and reliability of water supply, as well as increased costs and health and environmental hazards. It is important for cities to prioritize investment in water infrastructure and develop long-term plans to address renewal needs. Drawing general conclusions about the rate of renewal of urban water infrastructure systems at an international or national level can be challenging due to the influence of local management decisions. In many countries, the responsibility for water infrastructure management lies with the municipal authorities, who are responsible for making decisions about the allocation of resources for repair, maintenance, and renewal. These decisions can vary widely based on factors such as local finances, political priorities, and public perception of the importance of water infrastructure. As a result, it is difficult to make generalizations about the rate of renewal across different countries or regions. In Sweden, the situation is not different, and the information from Svenskt Vatten indicates that the rate of renewal varies across municipalities and can be insufficient, leading to a buildup of maintenance and renewal needs. This study aims to examine the adequacy of the rate of renewal of urban water infrastructure in Linköping case city in Sweden. Using a case study framework, the study will assess the current status of the urban water system and the need for renewal. The study will also consider the role of factors such as proper identification processes, limited funding, competing for political priorities, and local management decisions in contributing to insufficient renewal. The study investigates the following questions: (1) What is the current status of water and sewerage networks in terms of length, age distribution, and material composition, estimated total water leakage in the network per year, damages, leaks, and outages occur per year, both overall and by district? (2) What are the main causes of these damages, leaks, and interruptions, and how are they related to lack of maintenance and renewal? (3) What is the current status of renewal work for the water and sewerage networks, including the renewal rate and changes over time, recent renewal material composition, and the budget allocation for renewal and emergency repairs? (4) What factors influence the need for renewal and what conditions should be considered in the assessment? The findings of the study provide insights into the challenges facing urban water infrastructure and identify strategies for improving the rate of renewal to ensure a reliable and sustainable water supply.

Keywords: case study, infrastructure, management, renewal need, Sweden

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Authors: Bruno Vicente, Sandra Rafael, Vera Rodrigues, Sandra Sorte, Sara Silva, Ana Isabel Miranda, Carlos Borrego

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Wind comfort for pedestrians is an important condition in urban areas. In Portugal, a country with 900 km of coastline, the wind direction are predominantly from Nor-Northwest with an average speed of 2.3 m·s -1 (at 2 m height). As a result, a set of city authorities have been requesting studies of pedestrian wind comfort for new urban areas/buildings, as well as to mitigate wind discomfort issues related to existing structures. This work covers the efficiency evaluation of a set of measures to reduce the wind speed in an outdoor auditorium (open space) located in a coastal Portuguese urban area. These measures include the construction of barriers, placed at upstream and downstream of the auditorium, and the planting of trees, placed upstream of the auditorium. The auditorium is constructed in the form of a porch, aligned with North direction, driving the wind flow within the auditorium, promoting channelling effects and increasing its speed, causing discomfort in the users of this structure. To perform the wind comfort assessment, two approaches were used: i) a set of experiments using the wind tunnel (physical approach), with a representative mock-up of the study area; ii) application of the CFD (Computational Fluid Dynamics) model VADIS (numerical approach). Both approaches were used to simulate the baseline scenario and the scenarios considering a set of measures. The physical approach was conducted through a quantitative method, using hot-wire anemometer, and through a qualitative analysis (visualizations), using the laser technology and a fog machine. Both numerical and physical approaches were performed for three different velocities (2, 4 and 6 m·s-1 ) and two different directions (NorNorthwest and South), corresponding to the prevailing wind speed and direction of the study area. The numerical results show an effective reduction (with a maximum value of 80%) of the wind speed inside the auditorium, through the application of the proposed measures. A wind speed reduction in a range of 20% to 40% was obtained around the audience area, for a wind direction from Nor-Northwest. For southern winds, in the audience zone, the wind speed was reduced from 60% to 80%. Despite of that, for southern winds, the design of the barriers generated additional hot spots (high wind speed), namely, in the entrance to the auditorium. Thus, a changing in the location of the entrance would minimize these effects. The results obtained in the wind tunnel compared well with the numerical data, also revealing the high efficiency of the purposed measures (for both wind directions).

Keywords: urban microclimate, pedestrian comfort, numerical modelling, wind tunnel experiments

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

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We seek to develop a UAV for agricultural spraying at a maximum altitude of 5000 meters above sea level, with a payload of 100 liters of fumigant. For the developing the aerodynamic design of the aircraft is using computational tools such as the "Vortex Lattice Athena" software, "MATLAB", "ANSYS FLUENT", "XFoil" package among others. Also methods are being used structured programming, exhaustive analysis of optimization methods and search. The results have a very low margin of error, and the multi-objective problems can be helpful for future developments. Also we developed method for Stability Analysis (Lateral-Directional and Longitudinal).

Keywords: aerodynamics design, optimization, algorithm genetic, multi-objective problem, longitudinal stability, lateral-directional stability

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Authors: Damanjit Kaur, Avani Bhatia

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Color constancy is significant for human vision since color is a pictorial cue that helps in solving different visions tasks such as tracking, object recognition, or categorization. Therefore, several computational methods have tried to simulate human color constancy abilities to stabilize machine color representations. Two different kinds of methods have been used, i.e., normalization and constancy. While color normalization creates a new representation of the image by canceling illuminant effects, color constancy directly estimates the color of the illuminant in order to map the image colors to a canonical version. Color constancy is the capability to determine colors of objects independent of the color of the light source. This research work studies the most of the well-known color constancy algorithms like white point and gray world.

Keywords: color constancy, gray world, white patch, modified white patch

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Authors: Soulayma Smirani, Mourad Aidi, Taoufik Aguili

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Energy harvesting has arisen as a prominent research area for low power delivery to RF devices. Rectennas have become a key element in this technology. In this paper, electromagnetic modeling of a rectenna system is presented. In our approach, a hybrid technique was demonstrated to associate both the method of auxiliary sources (MAS) and MoM-GEC (the method of moments combined with the generalized equivalent circuit technique). Auxiliary sources were used in order to substitute specific electronic devices. Therefore, a simple and controllable model is obtained. Also, it can easily be interconnected to form different topologies of rectenna arrays for more energy harvesting. At last, simulation results show the feasibility and simplicity of the proposed rectenna model with high precision and computation efficiency.

Keywords: computational electromagnetics, MoM-GEC method, rectennas, RF energy harvesting

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Authors: P. Hajek, J. Stejskal

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The aim of this paper is to analyze the ability to identify and acquire knowledge from external sources at the regional level in the Czech Republic. The results show that the most important sources of knowledge for innovative activities are sources within the businesses themselves, followed by customers and suppliers. Furthermore, the analysis of relationships between the objective of the innovative activity and the ability to identify and acquire knowledge implies that knowledge obtained from a) customers aims at replacing outdated products and increasing product quality; b) suppliers aims at increasing capacity and flexibility of production; and c) competing businesses aims at growing market share and increasing the flexibility of production and services. Regions should therefore direct their support especially into development and strengthening of networks within the value chain.

Keywords: knowledge, acquisition, innovative business, Czech republic, region

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Authors: Qazi Umer Jamil, Abubakr Siddique, Mubeen Ur Rehman, Nida Aziz, Mohsin I. Tiwana

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This paper discusses a brain controlled robotic gait trainer for neurorehabilitation of Spinal Cord Injury (SCI) patients. Patients suffering from Spinal Cord Injuries (SCI) become unable to execute motion control of their lower proximities due to degeneration of spinal cord neurons. The presented approach can help SCI patients in neuro-rehabilitation training by directly translating patient motor imagery into walkers motion commands and thus bypassing spinal cord neurons completely. A non-invasive EEG based brain-computer interface is used for capturing patient neural activity. For signal processing and classification, an open source software (OpenVibe) is used. Classifiers categorize the patient motor imagery (MI) into a specific set of commands that are further translated into walker motion commands. The robotic walker also employs fall detection for ensuring safety of patient during gait training and can act as a support for SCI patients. The gait trainer is tested with subjects, and satisfactory results were achieved.

Keywords: brain computer interface (BCI), gait trainer, spinal cord injury (SCI), neurorehabilitation

Procedia PDF Downloads 159

Authors: Yu-Hsiu Lin, Wen-Chun Lin, Yen-Chang Cheng, Chia-Ju Yeh, Yu-Chuan Chen, Tai-You Li

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Demand-Side Management (DSM) has the potential to reduce electricity costs and carbon emission, which are associated with electricity used in the modern society. A home Energy Management System (EMS) commonly used by residential consumers in a down-stream sector of a smart grid to monitor, control, and optimize energy efficiency to domestic appliances is a system of computer-aided functionalities as an energy audit for residential DSM. Implementing fault detection and classification to domestic appliances monitored, controlled, and optimized is one of the most important steps to realize preventive maintenance, such as residential air conditioning and heating preventative maintenance in residential/industrial DSM. In this study, a cloud intelligence-based green EMS that comes up with an Internet of Things (IoT) technology stack for residential DSM is developed. In the EMS, Arduino MEGA Ethernet communication-based smart sockets that module a Real Time Clock chip to keep track of current time as timestamps via Network Time Protocol are designed and implemented for readings of load phenomena reflecting on voltage and current signals sensed. Also, a Network-Attached Storage providing data access to a heterogeneous group of IoT clients via Hypertext Transfer Protocol (HTTP) methods is configured to data stores of parsed sensor readings. Lastly, a desktop computer with a WAMP software bundle (the Microsoft® Windows operating system, Apache HTTP Server, MySQL relational database management system, and PHP programming language) serves as a data science analytics engine for dynamic Web APP/REpresentational State Transfer-ful web service of the residential DSM having globally-Advanced Internet of Artificial Intelligence (AI)/Computational Intelligence. Where, an abstract computing machine, Java Virtual Machine, enables the desktop computer to run Java programs, and a mash-up of Java, R language, and Python is well-suited and -configured for AI in this study. Having the ability of sending real-time push notifications to IoT clients, the desktop computer implements Google-maintained Firebase Cloud Messaging to engage IoT clients across Android/iOS devices and provide mobile notification service to residential/industrial DSM. In this study, in order to realize edge intelligence that edge devices avoiding network latency and much-needed connectivity of Internet connections for Internet of Services can support secure access to data stores and provide immediate analytical and real-time actionable insights at the edge of the network, we upgrade the designed and implemented smart sockets to be embedded AI Arduino ones (called embedded AIduino). With the realization of edge analytics by the proposed embedded AIduino for data analytics, an Arduino Ethernet shield WizNet W5100 having a micro SD card connector is conducted and used. The SD library is included for reading parsed data from and writing parsed data to an SD card. And, an Artificial Neural Network library, ArduinoANN, for Arduino MEGA is imported and used for locally-embedded AI implementation. The embedded AIduino in this study can be developed for further applications in manufacturing industry energy management and sustainable energy management, wherein in sustainable energy management rotating machinery diagnostics works to identify energy loss from gross misalignment and unbalance of rotating machines in power plants as an example.

Keywords: demand-side management, edge intelligence, energy management system, fault detection and classification

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Authors: Asmaa El Harat, Toumi Hicham, Youssef Baddi

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This survey delves into the complex realm of Internet of Things (IoT) security, highlighting the urgent need for effective cybersecurity measures as IoT devices become increasingly common. It explores a wide array of cyber threats targeting IoT devices and focuses on mitigating these attacks through the combined use of deep learning and machine learning algorithms, as well as edge and cloud computing paradigms. The survey starts with an overview of the IoT landscape and the various types of attacks that IoT devices face. It then reviews key machine learning and deep learning algorithms employed in IoT cybersecurity, providing a detailed comparison to assist in selecting the most suitable algorithms. Finally, the survey provides valuable insights for cybersecurity professionals and researchers aiming to enhance security in the intricate world of IoT.

Keywords: internet of things (IoT), cybersecurity, machine learning, deep learning

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Authors: Laura Micheli, Majd Hijazi, Mahmoud Faytarouni

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The damage reported by oil and gas industrial facilities revealed the utmost vulnerability of steel liquid storage tanks to seismic events. The failure of steel storage tanks may yield devastating and long-lasting consequences on built and natural environments, including the release of hazardous substances, uncontrolled fires, and soil contamination with hazardous materials. It is, therefore, fundamental to reliably predict the damage that steel liquid storage tanks will likely experience under future seismic hazard events. The seismic performance of steel liquid storage tanks is usually assessed using vulnerability curves obtained from the numerical simulation of a tank under different hazard scenarios. However, the computational demand of high-fidelity numerical simulation models, such as finite element models, makes the vulnerability assessment of liquid storage tanks time-consuming and often impractical. As a solution, this paper presents a surrogate model-based strategy for predicting seismic-induced damage in steel liquid storage tanks. In the proposed strategy, the surrogate model is leveraged to reduce the computational demand of time-consuming numerical simulations. To create the data set for training the surrogate model, field damage data from past earthquakes reconnaissance surveys and reports are collected. Features representative of steel liquid storage tank characteristics (e.g., diameter, height, liquid level, yielding stress) and seismic excitation parameters (e.g., peak ground acceleration, magnitude) are extracted from the field damage data. The collected data are then utilized to train a surrogate model that maps the relationship between tank characteristics, seismic hazard parameters, and seismic-induced damage via a data-driven surrogate model. Different types of surrogate algorithms, including naïve Bayes, k-nearest neighbors, decision tree, and random forest, are investigated, and results in terms of accuracy are reported. The model that yields the most accurate predictions is employed to predict future damage as a function of tank characteristics and seismic hazard intensity level. Results show that the proposed approach can be used to estimate the extent of damage in steel liquid storage tanks, where the use of data-driven surrogates represents a viable alternative to computationally expensive numerical simulation models.

Keywords: damage prediction , data-driven model, seismic performance, steel liquid storage tanks, surrogate model

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Authors: Juha Kettunen

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This study analyzes the quality and the size of the strategic network of higher education institutions. The study analyses the concept of fitness for purpose in quality assurance. It also analyses the transaction costs of networking that have consequences on the number of members in the network. Empirical evidence is presented of the Consortium on Applied Research and Professional Education, which is a European strategic network of six higher education institutions. The results of the study support the argument that the number of members in the strategic network should be relatively small to provide high quality results. The practical importance is that networking has been able to promote international research and development projects. The results of this study are important for those who want to design and improve international networks in higher education.

Keywords: balanced scorecard, higher education, social networking, strategic planning

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Authors: Sahar Mobeen, Anam Rafique, Irum Baig

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Acoustic echo cancellation in multichannel is a system identification application. In real time environment, signal changes very rapidly which required adaptive algorithms such as Least Mean Square (LMS), Leaky Least Mean Square (LLMS), Normalized Least Mean square (NLMS) and average (AFA) having high convergence rate and stable. LMS and NLMS are widely used adaptive algorithm due to less computational complexity and AFA used of its high convergence rate. This research is based on comparison of acoustic echo (generated in a room) cancellation thorough LMS, LLMS, NLMS, AFA and newly proposed average normalized leaky least mean square (ANLLMS) adaptive filters.

Keywords: LMS, LLMS, NLMS, AFA, ANLLMS

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Authors: Jayant Kumar, Aarcha Jayachandran Sasikala, Barry Adrian Shepherd

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Public Distribution System is a flagship welfare programme of the Government of India with both historical and political significance. Targeted at lower sections of society,it is one of the largest supply chain networks in the world. There has been several studies by academics and planning commission about the effectiveness of the system. Our study focuses on applying predictive analytics to aid the central body to keep track of the problem of breach of service level agreement between the two echelons of food supply chain. Each shop breach is leading to a potential additional inventory carrying cost. Thus, through this study, we aim to show that aided with such analytics, the network can be made more cost effective. The methods we illustrate in this study are applicable to other commercial supply chains as well.

Keywords: PDS, analytics, cost effectiveness, Karnataka, inventory cost, service level JEL classification: C53

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Authors: Zhong Ma, Zhuping Wang, Congxin Liu, Xiangzeng Liu

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Satellite imagery classification is a challenging problem with many practical applications. In this paper, we designed a deep convolution neural network (DCNN) to classify the satellite imagery. The contributions of this paper are twofold — First, to cope with the large-scale variance in the satellite image, we introduced the inception module, which has multiple filters with different size at the same level, as the building block to build our DCNN model. Second, we proposed a genetic algorithm based method to efficiently search the best hyper-parameters of the DCNN in a large search space. The proposed method is evaluated on the benchmark database. The results of the proposed hyper-parameters search method show it will guide the search towards better regions of the parameter space. Based on the found hyper-parameters, we built our DCNN models, and evaluated its performance on satellite imagery classification, the results show the classification accuracy of proposed models outperform the state of the art method.

Keywords: satellite imagery classification, deep convolution network, genetic algorithm, hyper-parameter optimization

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Authors: Paul Stonaha, Mariia Romashchenko, Xaio Xu

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Magnetic shape memory alloys (MSMAs) are promising technological materials for a range of fields, from biomaterials to energy harvesting. We have performed inelastic neutron scattering on two powder samples of cobalt-based high-entropy MSMAs across a range of temperatures in an effort to compare calculations of thermodynamic properties (entropy, specific heat, etc.) to the measured ones. The measurements were correct for multiphonon scattering and multiple scattering contributions. We present herein the neutron-weighted vibrational density of states. Future work will utilize DFT calculations of the disordered lattice to correct for the neutron weighting and retrieve the true thermodynamical properties.

Keywords: neutron scattering, vibrational dynamics, computational physics, material science

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Authors: Hasanein Hasan, Mohammed Al-Taie, Basil Shanshool, Khalaf Abd-Ali

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This approach aims to deal with establishing and operating Iraqi Fibre-To-The-Home (FTTH) projects. The problems they suffer from are organized sabotage, vandalism, accidental damage and poor planning. It provides practical solutions that deal with the aforementioned problems. These solutions consist of both technical and financial clarifications that ensure the achievement of the FTTH network’s stability for the purpose of equipping citizens, private sector companies, and governmental institutions with services, data transmission, the Internet, and other services. They aim to solve problems and obstacles accompanying the operation and maintenance of FTTH projects implemented by the Informatics and Telecommunications Public Company (ITPC)/ Iraqi Ministry of Communications (MoC). This approach takes the FTTH network of AlMaalif-AlMuaslat districts/ Baghdad-Iraq as a case study.

Keywords: CCTV, FTTH, ITPC, MoC, NVR, PTZ

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Authors: Sina Saadati, Mohammadreza Razzazi

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In this article, we have tried to present an agent-based model of human muscle. A suitable model of muscle is necessary for the analysis of mankind's movements. It can be used by clinical researchers who study the influence of motion sicknesses, like Parkinson's disease. It is also useful in the development of a prosthesis that receives the electromyography signals and generates force as a reaction. Since we have focused on computational efficiency in this research, the model can compute the calculations very fast. As far as it concerns prostheses, the model can be known as a charge-efficient method. In this paper, we are about to illustrate an agent-based model. Then, we will use it to simulate the human gait cycle. This method can also be done reversely in the analysis of gait in motion sicknesses.

Keywords: agent-based modeling and simulation, human muscle, gait cycle, motion sickness

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Authors: Mairaj Salim, Asma Zaheer

Abstract:

Oman has accomplished as much or more than its fellow Gulf monarchies, despite starting from scratch considerably later, having less oil income to utilize, dealing with a larger and more rugged geography, and resolving a bitter civil war along the way. Of course, Oman's progress in the past 30-plus years has not been without problems and missteps, but the balance is squarely on the positive side of the ledger. Oil has been the driving force of the Omani economy since Oman began commercial production in 1967. The oil industry supports the country’s high standard of living and is primarily responsible for its modern and expansive infrastructure, including electrical utilities, telephone services, roads, public education and medical services. In addition to extensive oil reserves, Oman also has substantial natural gas reserves, which are expected to play a leading role in the Omani economy in the Twenty-first Century. To reduce the country’s dependence on oil revenues, the government is restructuring the economy by directing investment to non-oil activities. Since the 21st century IT has changed the performing tasks. To manage the affairs for the benefits of organizations and economy, the Omani government has adopted E-Business technologies for the development. E-Business is important because it allows • Transformation of old economy relationships (vertical/linear relationships) to new economy relationships characterized by end-to-end relationship management solutions (integrated or extended relationships) • Facilitation and organization of networks, small firms depend on ‘partner’ firms for supplies and product distribution to meet customer demands • SMEs to outsource back-end process or cost centers enabling the SME to focus on their core competence • ICT to connect, manage and integrate processes internally and externally • SMEs to join networks and enter new markets, through shortened supply chains to increase market share, customers and suppliers • SMEs to take up the benefits of e-business to reduce costs, increase customer satisfaction, improve client referral and attract quality partners • New business models of collaboration for SMEs to increase their skill base • SMEs to enter virtual trading arena and increase their market reach A national strategy for the advancement of information and communication technology (ICT) has been worked out, mainly to introduce e-government, e-commerce, and a digital society. An information technology complex KOM (Knowledge Oasis Muscat) had been established, consisting of section for information technology, incubator services, a shopping center of technology software and hardware, ICT colleges, E-Government services and other relevant services. So, all these efforts play a vital role in the development of Oman economy.

Keywords: ICT, ITA, CRM, SCM, ERP, KOM, SMEs, e-commerce and e-business

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Authors: Amir Mohagheghzadeh, Solaleh Salimi, Ramin Tafazzoli

Abstract:

Ecosystem and networks plays significant roles in product innovation. External innovation within developing firms can bring a wide range of advantages for a firm in a competitive market. Using external innovation can be mentioned as one of the most significant concepts regarding the firm’s transition phase into openness. Derivative concepts such as open or shared platform and app stores are the main result of this thinking within the firms. However, adopting this concept and leverage the defined advantages of external innovation should be aligned with other strategies and policies of a firm. Consequently, one of the key aspects that have been raised while using external innovation is how to govern external innovation within a developing firm. This paper describes the frameworks that two pioneer companies in mobile operating system development have used in order to control and govern external innovation through platform.

Keywords: external innovation, open innovation, governance, governance mechanisms, innovation, Apple, iOS, Google, Android

Procedia PDF Downloads 513