Search results for: approximate computing

Authors: Fariborz Ahmadi, Reza Tati

Abstract:

Genetic algorithm is a soft computing method that works on set of solutions. These solutions are called chromosome and the best one is the absolute solution of the problem. The main problem of this algorithm is that after passing through some generations, it may be produced some chromosomes that had been produced in some generations ago that causes reducing the convergence speed. From another respective, most of the genetic algorithms are implemented in software and less works have been done on hardware implementation. Our work implements genetic algorithm in hardware that doesn’t produce chromosome that have been produced in previous generations. In this work, most of genetic operators are implemented without producing iterative chromosomes and genetic diversity is preserved. Genetic diversity causes that not only do not this algorithm converge to local optimum but also reaching to global optimum. Without any doubts, proposed approach is so faster than software implementations. Evaluation results also show the proposed approach is faster than hardware ones.

Keywords: hardware, genetic algorithm, computer science, engineering

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Authors: Jiangping Wang

Abstract:

This presentation describes the design and implementation of PaaS (platform as a service) cloud-based labs that are used in database-related courses to teach students practical skills. Traditionally, all labs are implemented in a desktop-based environment where students have to install heavy client software to access database servers. In order to release students from that burden, we have successfully deployed the cloud-based solution to support database-related courses, from which students and teachers can practice and learn database topics in various database courses via cloud access. With its development environment, execution runtime, web server, database server, and collaboration capability, it offers a shared pool of configurable computing resources and comprehensive environment that supports students’ needs without the complexity of maintaining the infrastructure.

Keywords: PaaS, database environment, e-learning, web server

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Authors: Ng Liang Shen, Ngahzaifa Abdul Ghani

Abstract:

This research aimed at developing an early warning system for pre-diabetic and diabetics by analyzing simple and easily determinable signs and symptoms of diabetes among the people living in Malaysia using Particle Swarm Optimized Artificial. With the skyrocketing prevalence of Type 2 diabetes in Malaysia, the system can be used to encourage affected people to seek further medical attention to prevent the onset of diabetes or start managing it early enough to avoid the associated complications. The study sought to find out the best predictive variables of Type 2 Diabetes Mellitus, developed a system to diagnose diabetes from the variables using Artificial Neural Networks and tested the system on accuracy to find out the patent generated from diabetes diagnosis result in machine learning algorithms even at primary or advanced stages.

Keywords: diabetes diagnosis, Artificial Neural Networks, artificial intelligence, soft computing, medical diagnosis

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Authors: G. Judakova, M. Bause

Abstract:

The ability to model and simulate numerically natural gas flow in pipelines has become of high importance for the design of pipeline systems. The understanding of the formation of hydrate particles and their dynamical behavior is of particular interest, since these processes govern the operation properties of the systems and are responsible for system failures by clogging of the pipelines under certain conditions. Mathematically, natural gas flow can be described by multiphase flow models. Using the two-fluid modeling approach, the gas phase is modeled by the compressible Euler equations and the particle phase is modeled by the pressureless Euler equations. The numerical simulation of compressible multiphase flows is an important research topic. It is well known that for nonlinear fluxes, even for smooth initial data, discontinuities in the solution are likely to occur in finite time. They are called shock waves or contact discontinuities. For hyperbolic and singularly perturbed parabolic equations the standard application of the Galerkin finite element method (FEM) leads to spurious oscillations (e.g. Gibb's phenomenon). In our approach, we use stabilized FEM, the streamline upwind Petrov-Galerkin (SUPG) method, where artificial diffusion acting only in the direction of the streamlines and using a special treatment of the boundary conditions in inviscid convective terms, is added. Numerical experiments show that the numerical solution obtained and stabilized by SUPG captures discontinuities or steep gradients of the exact solution in layers. However, within this layer the approximate solution may still exhibit overshoots or undershoots. To suitably reduce these artifacts we add a discontinuity capturing or shock capturing term. The performance properties of our numerical scheme are illustrated for two-phase flow problem.

Keywords: two-phase flow, gas-particle mixture, inviscid two-fluid model, euler equation, finite element method, streamline upwind petrov-galerkin, shock capturing

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Authors: Juan A. Ferriz-Papi, Allan L. Nantel, Talib E. Butt

Abstract:

Buildings are thought to consume about 50% of the total energy in the UK. The use stage in a building life cycle has the largest energy consumption, although different assessments are showing that the construction can equal several years of maintenance and operations. The selection of materials with lower embodied energy is very important to reduce this consumption. For this reason, timber is one adequate material due to its low embodied energy and the capacity to be used as carbon storage. The use of timber in the construction industry is very significant. Sawn wood, for example, is one of the top 5 construction materials consumed in the UK according to National Statistics. Embodied energy for building products considers the energy consumed in extraction and production stages. However, it is not the same consideration if this product is produced locally as when considering the resource produced further afield. Transport is a very relevant matter that profoundly influences in the results of embodied energy. The case of timber use in the UK is important because the balance between imports and exports is far negative, industry consuming more imported timber than produced. Nearly 80% of sawn softwood used in construction is imported. The imports-exports deficit for sawn wood accounted for more than 180 million pounds during the first four-month period of 2016. More than 85% of these imports come from Europe (83% from the EU). The aim of this study is to analyze climate change impact due to transport for timber products consumed in the UK. An approximate estimation of energy consumed and carbon emissions are calculated considering the timber product’s import origin. The results are compared to the total consumption of each product, estimating the impact of transport on the final embodied energy and carbon emissions. The analysis of these results can help deduce that one big challenge for climate change is the reduction of external dependency, with the associated improvement of internal production of timber products. A study of different types of timber products produced in the UK and abroad is developed to understand the possibilities for this country to improve sustainability and self-management. Reuse and recycle possibilities are also considered.

Keywords: embodied energy, climate change, CO2 emissions, timber, transport

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Authors: Dana Kristalova

Abstract:

This article deals with geographical conditions in terrain and their effect on the movement of vehicles, their effect on speed and safety of movement of people and vehicles. Finding of the optimal routes outside the communication is studied in the army environment, but it occur in civilian as well, primarily in crisis situation, or by the provision of assistance when natural disasters such as floods, fires, storms, etc. have happened. These movements require the optimization of routes when effects of geographical factors should be included. The most important factor is surface of the terrain. It is based on several geographical factors as are slopes, soil conditions, micro-relief, a type of surface and meteorological conditions. Their mutual impact has been given by coefficient of deceleration. This coefficient can be used for commander´s decision. New approaches and methods of terrain testing, mathematical computing, mathematical statistics or cartometric investigation are necessary parts of this evaluation.

Keywords: surface of a terrain, movement of vehicles, geographical factor, optimization of routes

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Authors: Fuyuan Ma, Yuhan Wang, Junhe Zhang, Ying Wang

Abstract:

Identifying the sources of information dissemination is a pivotal task in the study of collective behaviors in networks, enabling us to discern and intercept the critical pathways through which information propagates from its origins. This allows for the control of the information’s dissemination impact in its early stages. Numerous methods for source detection rely on pre-existing, underlying propagation models as prior knowledge. Current models that eschew prior knowledge attempt to harness label propagation algorithms to model the statistical characteristics of propagation states or employ Graph Neural Networks (GNNs) for deep reverse modeling of the diffusion process. These approaches are either deficient in modeling the propagation patterns of information or are constrained by the over-smoothing problem inherent in GNNs, which limits the stacking of sufficient model depth to excavate global propagation patterns. Consequently, we introduce the ODESI model. Initially, the model employs a label propagation algorithm to delineate the distribution density of infected states within a graph structure and extends the representation of infected states from integers to state vectors, which serve as the initial states of nodes. Subsequently, the model constructs a deep architecture based on GNNs-coupled Ordinary Differential Equations (ODEs) to model the global propagation patterns of continuous propagation processes. Addressing the challenges associated with solving ODEs on graphs, we approximate the analytical solutions to reduce computational costs. Finally, we conduct simulation experiments on two real-world social network datasets, and the results affirm the efficacy of our proposed ODESI model in source identification tasks.

Keywords: source identification, ordinary differential equations, label propagation, complex networks

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Authors: Ahmed I. Alutabi, Naghmeh Dezhabad, Sudhakar Ganti

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Data centers have been growing in size and dema nd continuously in the last two decades. Planning for the deployment of resources has been shallow and always resorted to over-provisioning. Data center operators try to maximize the availability of their services by allocating multiple of the needed resources. One resource that has been wasted, with little thought, has been energy. In recent years, programmable resource allocation has paved the way to allow for more efficient and robust data centers. In this work, we examine the predictability of resource usage in a data center environment. We use a number of models that cover a wide spectrum of machine learning categories. Then we establish a framework to guarantee the client service level agreement (SLA). Our results show that using prediction can cut energy loss by up to 55%.

Keywords: machine learning, artificial intelligence, prediction, data center, resource allocation, green computing

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Authors: Jamal Alqinai

Abstract:

A pragmatic approach to translation studies the rules and principles governing the use of language over and above the rules of syntax or morphology, and what makes some uses of language more appropriate than others in [communicative] situations. It attempts to explain translation as a procedure and product from the point of view of how, why and what is done by the source text author (ST) and what is to be done in the target text (TT) rendition. The latter will be subject to evaluation not as generated by the linguistics system but as conveyed and manipulated by participants in a communicative situation according to the referential and pragmatic standards employed. The failure of a purely lexical or structural translation stems from ignoring the relation between words as signs and the effect they have on their users. A more refined approach would also consider those processes that are sometimes labeled extra-linguistic or intuitive and which translators strive to reproduce unscathed in the translation process. We need to grasp the kind of actions an ST author performs on his readers by combining linguistic and non-linguistic elements against a backdrop of beliefs and cultural values. In other words, aside from considering the cohesive ties at the textual level, one needs to understand how the whole ST discourse hangs together logically in order to reproduce a coherent TT. The latter can only be achieved by an analysis of the pragmatic elements of presuppositions, implicatures and acts performed in the ST. Establishing cohesive ties within a text may require seeking reference outside the immediate text. The illocutionary functions manifested in one language/culture are relatively autonomous cultural/linguistic categories, but are imaginable by members of other cultures and, to some extent , are translatable though not, of course, without translation loss. Globalization and the spread of literacy worldwide may have created a universal empathy to comprehend the performative aspect of utterances when explained by approximate glosses or by paraphrase. Yet, it is often the multilayered and the culture-specific nature of illocutionary functions that de-universalize their possible interpretations. This paper addresses the pragmatic interpretation of culturally specific texts with examples adduced from a number of distinct settings to illustrate the influence of the pragmatic factors at stake.

Keywords: pragmatic, presupposition, implicature, cohesion

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Authors: Long Kim Vu

Abstract:

The central processing unit in Electro-Optical devices is a Field-programmable gate array (FPGA) chip package allowing flexible, reconfigurable computing but energy consumption. Because chip package is placed in isolated devices based on IP67 waterproof standard, there is no air circulation and the heat dissipation is a challenge. In this paper, the author successfully modeled a chip package which various interposer materials such as silicon, glass and organics. Computational fluid dynamics (CFD) was utilized to analyze the thermal performance of chip package in the case of considering comprehensive heat transfer modes: conduction, convection and radiation, which proposes equivalent heat dissipation. The logic chip temperature varying with time is compared between the simulation and experiment results showing the excellent correlation, proving the reasonable chip modeling and simulation method.

Keywords: CFD, FPGA, heat transfer, thermal analysis

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Authors: Madhalasa Iyer

Abstract:

The increase in sustainable practices have encouraged the research and production of alternative fuels. New techniques of bio flocculation with the addition of yeast and bacteria strains have increased the efficiency of biofuel production. Fatty acid methyl ester (FAME) analysis in previous research has indicated that yeast can serve as a plausible enhancer for microalgal lipid production. The research hopes to identify the yeast and microalgae treatment group that produces the largest algae biomass. The mass of the dried algae is used as a proxy for TAG production correlating to the cultivation of biofuels. The study uses a model bioreactor created and built using PVC pipes, 8-port sprinkler system manifold, CO2 aquarium tank, and disposable water bottles to grow the microalgae. Nannochloropsis sp., and Isochrysis galbanawere inoculated separately in experimental group 1 and 2 with no treatments and in experimental groups 3 and 4 with each algaeco-cultured with Saccharomyces cerevisiae in the medium of standard garden stone fertilizer. S. cerevisiae was grown in a petri dish with nutrient agar medium before inoculation. A Secchi stick was used before extraction to collect data for the optical density of the microalgae. The biomass estimator was then used to measure the approximate production of biomass. The microalgae were grown and extracted with a french press to analyze secondary measurements using the dried biomass. The experimental units of Isochrysis galbana treated with the baker’s yeast strains showed an increase in the overall mass of the dried algae. S. cerevisiae proved to be an accurate and helpful addition to the solution to provide for the growth of algae. The increase in productivity of this fuel source legitimizes the possible replacement of non-renewable sources with more promising renewable alternatives. This research furthers the notion that yeast and mutants can be engineered to be employed in efficient biofuel creation.

Keywords: biofuel, co-culture, S. cerevisiae, microalgae, yeast

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Authors: Josef Steinberger, Vanni Zavarella, Hristo Tanev

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Natural disasters cause tens of thousands of victims and massive material damages. We refer to all those events caused by natural disasters, such as damage on people, infrastructure, vehicles, services and resource supply, as micro events. This paper addresses the problem of micro - event detection in online media sources. We present a natural language grammar learning algorithm and apply it to online news. The algorithm in question is based on distributional clustering and detection of word collocations. We also explore the extraction of micro-events from social media and describe a Twitter mining robot, who uses combinations of keywords to detect tweets which talk about effects of disasters.

Keywords: online news, natural language processing, machine learning, event extraction, crisis computing, disaster effects, Twitter

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Authors: Mohammad W. Dewan, Jahangir Alam, Khurshida Sharmin

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Synthetic fibers (carbon, glass, aramid, etc.) are generally utilized to make composite materials for better mechanical and thermal properties. However, they are expensive and non-biodegradable. In the perspective of Bangladesh, jute fibers are available, inexpensive, and comprising good mechanical properties. The improved properties (i.e., low cost, low density, eco-friendly) of natural fibers have made them a promising reinforcement in hybrid composites without sacrificing mechanical properties. In this study, jute and e-glass fiber reinforced hybrid composite materials are fabricated utilizing hand lay-up followed by a compression molding technique. Room temperature cured two-part epoxy resin is used as a matrix. Approximate 6-7 mm thick composite panels are fabricated utilizing 17 layers of woven glass and jute fibers with different fiber layering sequences- only jute, only glass, glass, and jute alternatively (g/j/g/j---) and 4 glass - 9 jute – 4 glass (4g-9j-4g). The fabricated composite panels are analyzed through fiber volume calculation, tensile test, bending test, and water absorption test. The hybridization of jute and glass fiber results in better tensile, bending, and water absorption properties than only jute fiber-reinforced composites, but inferior properties as compared to only glass fiber reinforced composites. Among different fiber layering sequences, 4g-9j-4g fibers layering sequence resulted in better tensile, bending, and water absorption properties. The effect of chemical treatment on the woven jute fiber and chopped glass microfiber infusion are also investigated in this study. Chemically treated jute fiber and 2 wt. % chopped glass microfiber infused hybrid composite shows about 12% improvements in flexural strength as compared to untreated and no micro-fiber infused hybrid composite panel. However, fiber chemical treatment and micro-filler do not have a significant effect on tensile strength.

Keywords: compression molding, chemical treatment, hybrid composites, mechanical properties

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Authors: Lucia Billeci, Gennaro Tartarisco, Maurizio Varanini

Abstract:

Fetal cardiac monitoring by fetal electrocardiogram (fECG) can provide significant clinical information about the healthy condition of the fetus. Despite this potentiality till now the use of fECG in clinical practice has been quite limited due to the difficulties in its measuring. The recovery of fECG from the signals acquired non-invasively by using electrodes placed on the maternal abdomen is a challenging task because abdominal signals are a mixture of several components and the fetal one is very weak. This paper presents an approach for fECG extraction from abdominal maternal recordings, which exploits the characteristics of pseudo-periodicity of fetal ECG. It consists of devising a quality index (fQI) for fECG and of finding the linear combinations of preprocessed abdominal signals, which maximize these fQI (quality index optimization - QIO). It aims at improving the performances of the most commonly adopted methods for fECG extraction, usually based on maternal ECG (mECG) estimating and canceling. The procedure for the fECG extraction and fetal QRS (fQRS) detection is completely unsupervised and based on the following steps: signal pre-processing; maternal ECG (mECG) extraction and maternal QRS detection; mECG component approximation and canceling by weighted principal component analysis; fECG extraction by fQI maximization and fetal QRS detection. The proposed method was compared with our previously developed procedure, which obtained the highest at the Physionet/Computing in Cardiology Challenge 2013. That procedure was based on removing the mECG from abdominal signals estimated by a principal component analysis (PCA) and applying the Independent component Analysis (ICA) on the residual signals. Both methods were developed and tuned using 69, 1 min long, abdominal measurements with fetal QRS annotation of the dataset A provided by PhysioNet/Computing in Cardiology Challenge 2013. The QIO-based and the ICA-based methods were compared in analyzing two databases of abdominal maternal ECG available on the Physionet site. The first is the Abdominal and Direct Fetal Electrocardiogram Database (ADdb) which contains the fetal QRS annotations thus allowing a quantitative performance comparison, the second is the Non-Invasive Fetal Electrocardiogram Database (NIdb), which does not contain the fetal QRS annotations so that the comparison between the two methods can be only qualitative. In particular, the comparison on NIdb was performed defining an index of quality for the fetal RR series. On the annotated database ADdb the QIO method, provided the performance indexes Sens=0.9988, PPA=0.9991, F1=0.9989 overcoming the ICA-based one, which provided Sens=0.9966, PPA=0.9972, F1=0.9969. The comparison on NIdb was performed defining an index of quality for the fetal RR series. The index of quality resulted higher for the QIO-based method compared to the ICA-based one in 35 records out 55 cases of the NIdb. The QIO-based method gave very high performances with both the databases. The results of this study foresees the application of the algorithm in a fully unsupervised way for the implementation in wearable devices for self-monitoring of fetal health.

Keywords: fetal electrocardiography, fetal QRS detection, independent component analysis (ICA), optimization, wearable

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Authors: H. Samadiyeh, R. Khajavi

Abstract:

A new FD-based procedure, modal finite difference method (MFDM), is proposed for seismic wave propagation modeling, in which simulation is dealt with in the modal space. The method employs eigenvalues of a characteristic matrix formed by appropriate time-space FD stencils. Since MFD runs for different modes are totally independent of each other, MFDM can easily be parallelized while considerable simplicity in parallel-algorithm is also achieved. There is no requirement to any domain-decomposition procedure and inter-core data exchange. More important is the possibility to skip processing of less-significant modes, which enables one to adjust the procedure up to the level of accuracy needed. Thus, in addition to considerable ease of parallel programming, computation and storage costs are significantly reduced. The method is qualified for its efficiency by some numerical examples.

Keywords: Finite Difference Method, Graphics Processing Unit (GPU), Message Passing Interface (MPI), Modal, Wave propagation

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Authors: Wajahat Munir, Muhammad Haseeb, Adeel Anjum, Basit Raza, Ahmad Kamran Malik

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Databases are the key components of the software systems. Due to the exponential growth of data, it is the concern that the data should be accurate and available. The data in databases is vulnerable to internal and external threats, especially when it contains sensitive data like medical or military applications. Whenever the data is changed by malicious intent, data analysis result may lead to disastrous decisions. Autonomic self-healing is molded toward computer system after inspiring from the autonomic system of human body. In order to guarantee the accuracy and availability of data, we propose a technique which on a priority basis, tries to avoid any malicious transaction from execution and in case a malicious transaction affects the system, it heals the system in an isolated mode in such a way that the availability of system would not be compromised. Using this autonomic system, the management cost and time of DBAs can be minimized. In the end, we test our model and present the findings.

Keywords: autonomic computing, self-healing, threat avoidance, security

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Authors: Fahad Suleiman

Abstract:

Queuing, in medical system is the process of moving patients in a specific sequence to a specific service according to the patients’ nature of illness. The term scheduling stands for the process of computing a schedule. This may be done by a queuing based scheduler. This paper focuses on the medical consultancy system, the different queuing algorithms that are used in healthcare system to serve the patients, and the average waiting time. The aim of this paper is to build automatic queuing system for organizing the medical queuing system that can analyses the queue status and take decision which patient to serve. The new queuing architecture model can switch between different scheduling algorithms according to the testing results and the factor of the average waiting time. The main innovation of this work concerns the modeling of the average waiting time is taken into processing, in addition with the process of switching to the scheduling algorithm that gives the best average waiting time.

Keywords: queuing systems, queuing system models, scheduling algorithms, patients

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Authors: Mattias Bergstrom

Abstract:

Significance of the Study: This research will provide new insights into the risks with digital embedded infrastructure. Through this research, we will analyze each risk and its potential negation strategies, especially for AI and autonomous automation. Moreover, the analysis that is presented in this paper will convey valuable information for future research that can create more stable, secure, and efficient autonomous systems. To learn and understand the risks, a large IoT system was envisioned, and risks with hardware, tampering, and cyberattacks were collected, researched, and evaluated to create a comprehensive understanding of the potential risks. Potential solutions have then been evaluated on an open source IoT hardware setup. This list shows the identified passive and active risks evaluated in the research. Passive Risks: (1) Hardware failures- Critical Systems relying on high rate data and data quality are growing; SCADA systems for infrastructure are good examples of such systems. (2) Hardware delivers erroneous data- Sensors break, and when they do so, they don’t always go silent; they can keep going, just that the data they deliver is garbage, and if that data is not filtered out, it becomes disruptive noise in the system. (3) Bad Hardware injection- Erroneous generated sensor data can be pumped into a system by malicious actors with the intent to create disruptive noise in critical systems. (4) Data gravity- The weight of the data collected will affect Data-Mobility. (5) Cost inhibitors- Running services that need huge centralized computing is cost inhibiting. Large complex AI can be extremely expensive to run. Active Risks: Denial of Service- It is one of the most simple attacks, where an attacker just overloads the system with bogus requests so that valid requests disappear in the noise. Malware- Malware can be anything from simple viruses to complex botnets created with specific goals, where the creator is stealing computer power and bandwidth from you to attack someone else. Ransomware- It is a kind of malware, but it is so different in its implementation that it is worth its own mention. The goal with these pieces of software is to encrypt your system so that it can only be unlocked with a key that is held for ransom. DNS spoofing- By spoofing DNS calls, valid requests and data dumps can be sent to bad destinations, where the data can be extracted for extortion or to corrupt and re-inject into a running system creating a data echo noise loop. After testing multiple potential solutions. We found that the most prominent solution to these risks was to use a Peer 2 Peer consensus algorithm over a blockchain to validate the data and behavior of the devices (sensors, storage, and computing) in the system. By the devices autonomously policing themselves for deviant behavior, all risks listed above can be negated. In conclusion, an Internet middleware that provides these features would be an easy and secure solution to any future autonomous IoT deployments. As it provides separation from the open Internet, at the same time, it is accessible over the blockchain keys.

Keywords: IoT, security, infrastructure, SCADA, blockchain, AI

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Authors: Gulshad Azatova, Aleksandr Kapitonov, Natig Aminov

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Multiagent systems have gained significant attention in various fields, such as robotics, autonomous vehicles, and distributed computing, where multiple agents cooperate and communicate to achieve complex tasks. Efficient communication among agents is a crucial aspect of these systems, as it directly impacts their overall performance and scalability. This scholarly work provides an exploration of essential communication elements and conducts a comparative assessment of diverse protocols utilized in multiagent systems. The emphasis lies in scrutinizing the strengths, weaknesses, and applicability of these protocols across various scenarios. The research also sheds light on emerging trends within communication protocols for multiagent systems, including the incorporation of machine learning methods and the adoption of blockchain-based solutions to ensure secure communication. These trends provide valuable insights into the evolving landscape of multiagent systems and their communication protocols.

Keywords: communication, multi-agent systems, protocols, consensus

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Authors: Te-Jen Chang, Ping-Sheng Huang, Shan-Ten Cheng, Chih-Lin Lin, I-Hui Pan, Tsung- Hsien Lin

Abstract:

RSA system is a great contribution for the encryption and the decryption. It is based on the modular exponentiation. We call this system as “a large of numbers for calculation”. The operation of a large of numbers is a very heavy burden for CPU. For increasing the computational speed, in addition to improve these algorithms, such as the binary method, the sliding window method, the addition chain method, and so on, the cluster computer can be used to advance computational speed. The cluster system is composed of the computers which are installed the MPICH2 in laboratory. The parallel procedures of the modular exponentiation can be processed by combining the sliding window method with the addition chain method. It will significantly reduce the computational time of the modular exponentiation whose digits are more than 512 bits and even more than 1024 bits.

Keywords: cluster system, modular exponentiation, sliding window, addition chain

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Authors: Tai Nguyen, Minh Bui, Huong Ninh, Tu Nguyen, Hai Tran

Abstract:

GraphCut algorithm has been widely utilized to solve various types of computer vision problems. Its expensive computational cost encouraged many researchers to improve the speed of the algorithm. Recent works proposed schemes that work on parallel computing platforms such as CUDA. However, the problem of low convergence speed prevents the usage of GraphCut for real time applications. In this paper, we propose global suppression heuristic to boost the conver-gence process of the algorithm. A parallel implementation of GraphCut algorithm on CUDA designed for the image stitching problem is introduced. Our method achieves up to 3× time boost on the graph of size 80 × 480 compared to the best sequential GraphCut algorithm while achieving satisfactory stitched images, suitable for panorama applications. Our source code will be soon available for further research.

Keywords: CUDA, graph cut, image stitching, texture synthesis, maxflow/mincut algorithm

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Authors: Dayo Samuel Banjo, Connice Trimmingham, Niloofar Yousefi, Nitin Agarwal

Abstract:

Technological advancement and its omnipresent connection have pushed humans past the boundaries and limitations of a computer screen, physical state, or geographical location. It has provided a depth of avenues that facilitate human-computer interaction that was once inconceivable such as audio and body language detection. Given the complex modularities of emotions, it becomes vital to study human-computer interaction, as it is the commencement of a thorough understanding of the emotional state of users and, in the context of social networks, the producers of multimodal information. This study first acknowledges the accuracy of classification found within multimodal emotion detection systems compared to unimodal solutions. Second, it explores the characterization of multimedia content produced based on their emotions and the coherence of emotion in different modalities by utilizing deep learning models to classify emotion across different modalities.

Keywords: affective computing, deep learning, emotion recognition, multimodal

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Authors: A. H. Elkholy, A. H. Falah

Abstract:

A new approach has been developed to estimate the load share and stress distribution of worm gear sets. The approach is based upon considering the instantaneous tooth meshing stiffness where the worm gear drive was modelled as a series of spur gear slices, and each slice was analyzed separately using the well established formulae of spur gears. By combining the results obtained for all slices, the entire envolute worm gear set loading and stressing was obtained. The geometric modelling method presented, allows tooth elastic deformation and tooth root stresses of worm gear drives under different load conditions to be investigated. On the basis of the method introduced in this study, the instantaneous meshing stiffness and load share were obtained. In comparison with existing methods, this approach has both good analysis accuracy and less computing time.

Keywords: gear, load/stress distribution, worm, wheel, tooth stiffness, contact line

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Authors: S. J. Ha, S. J. Baik, T. O. Kim, S. W. Han

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For computing the seismic responses of structures, current seismic design provisions permit response history analyses (RHA) that can be used without limitations in height, seismic design category, and building irregularity. In order to obtain accurate seismic responses using RHA, it is important to use adequate input ground motions. Current seismic design provisions provide criteria for selecting ground motions. In this study, the accurate and computationally efficient algorithm is proposed for accurately selecting ground motions that satisfy the requirements specified in current seismic design provisions. The accuracy of the proposed algorithm is verified using single-degree-of-freedom systems with various natural periods and yield strengths. This study shows that the mean seismic responses obtained from RHA with seven and ten ground motions selected using the proposed algorithm produce errors within 20% and 13%, respectively.

Keywords: algorithm, ground motion, response history analysis, selection

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Authors: Sebastião Pais, João Casal, Ricardo Ponciano, Sérgio Lorenço

Abstract:

The adaptation paradigm is a basic defining feature for pervasive computing systems. Adaptation systems must work efficiently in a smart environment while providing suitable information relevant to the user system interaction. The key objective is to deduce the information needed information changes. Therefore relying on fixed operational models would be inappropriate. This paper presents a study on developing an Intelligent Personal Assistant to assist the user in interacting with their Smart Environment. We propose an Unsupervised and Language-Independent Adaptation through Intelligent Speech Interface and a set of methods of Acquiring Knowledge, namely Semantic Similarity and Unsupervised Learning.

Keywords: intelligent personal assistants, intelligent speech interface, unsupervised learning, language-independent, knowledge acquisition, association measures, symmetric word similarities, attributional word similarities

Procedia PDF Downloads 560

Authors: Sebastião Pais, João Casal, Ricardo Ponciano, Sérgio Lourenço

Abstract:

The adaptation paradigm is a basic defining feature for pervasive computing systems. Adaptation systems must work efficiently in smart environment while providing suitable information relevant to the user system interaction. The key objective is to deduce the information needed information changes. Therefore, relying on fixed operational models would be inappropriate. This paper presents a study on developing a Intelligent Personal Assistant to assist the user in interacting with their Smart Environment. We propose a Unsupervised and Language-Independent Adaptation through Intelligent Speech Interface and a set of methods of Acquiring Knowledge, namely Semantic Similarity and Unsupervised Learning.

Keywords: intelligent personal assistants, intelligent speech interface, unsupervised learning, language-independent, knowledge acquisition, association measures, symmetric word similarities, attributional word similarities

Procedia PDF Downloads 643

Authors: Krisstalova Dana, Mazal Jan

Abstract:

This article deals with geographical conditions in terrain and their effect on the movement of vehicles, their effect on speed and safety of movement of people and vehicles. Finding of the optimal routes outside the communication is studied in the army environment, but it occur in civilian as well, primarily in crisis situation, or by the provision of assistance when natural disasters such as floods, fires, storms etc., have happened. These movements require the optimization of routes when effects of geographical factors should be included. The most important factor is the surface of a terrain. It is based on several geographical factors as are slopes, soil conditions, micro-relief, a type of surface and meteorological conditions. Their mutual impact has been given by coefficient of deceleration. This coefficient can be used for the commander`s decision. New approaches and methods of terrain testing, mathematical computing, mathematical statistics or cartometric investigation are necessary parts of this evaluation.

Keywords: movement in a terrain, geographical factors, surface of a field, mathematical evaluation, optimization and searching paths

Procedia PDF Downloads 425

Authors: Zahra Soleimani Rad, Fariborz Masoudi, Shirin Tondkar

Abstract:

Turquoise is one of the most well-known gemstones in Iran. The mineralogy, crystallography, and gemology of Shahr-e-Babak turquoise in Kerman were investigated and the results are presented in this research. The Miduk porphyry copper deposit is positioned in the Shahr-Babak area in Kerman province, Iran. This deposit is located 85 km NW of the Sar-Cheshmeh porphyry copper deposit. Preliminary mineral exploration was carried out from 1967 to 1970. So far, more than fifty diamond drill holes, each reaching a maximum depth of 1013 meters, have provided evidence supporting the presence of significant and promising porphyry copper mineralization at the Miduk deposit. The mineral deposit harbors a quantity of 170 million metric tons of ore, characterized by a mean composition of 0.86% copper (Cu), 0.007% molybdenum (Mo), 82 parts-per-billion gold (Au), and 1.8 parts-per-million silver (Ag). The Supergene enrichment layer, which constitutes the predominant source of copper ore, exhibits an approximate thickness of 50 meters. Petrography shows that the texture is homogeneous. In terms of a gemstone, greasy luster and blue color are seen, and samples are similar to what is commonly known as turquoise. The geometric minerals were detected in XRD analysis by analyzing the data using the x-pert software. From the mineralogical point of view; the turquoise gemstones of Miduk of Kerman consist of turquoise, quartz, mica, and hübnerite. In this article, to our best knowledge, we are stating the hübnerite mineral identified and seen in the Persian turquoise. Based on the obtained spectra, the main mineral of the Miduk samples from the six members of the turquoise family is the turquoise type with identical peaks that can be used as a reference for identification of the Miduk turquoise. This mineral is structurally composed of phosphate units, units of Al, Cu, water, and hydroxyl units, and does not include a Fe unit. In terms of gemology, the quality of a gemstone depends on the quantity of the turquoise phase and the amount of Cu in it according to SEM and XRD analysis.

Keywords: turquoise, hübnerite, XRD analysis, Miduk, Kerman, Iran

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Authors: Jian-Heng Wu, Bor-Shen Lin

Abstract:

The temperature-salinity relationship is one of the most important characteristics used for identifying water masses in marine research. Temperature-salinity characteristics, however, may change dynamically with respect to the geographic location and is quite sensitive to the depth at the same location. When depth is taken into consideration, however, it is not easy to compare the characteristics of different water masses efficiently for a wide range of areas of the ocean. In this paper, the Gaussian mixture model was proposed to analyze the temperature-salinity-depth characteristics of water masses, based on which comparison between water masses may be conducted. Gaussian mixture model could model the distribution of a random vector and is formulated as the weighting sum for a set of multivariate normal distributions. The temperature-salinity-depth data for different locations are first used to train a set of Gaussian mixture models individually. The distance between two Gaussian mixture models can then be defined as the weighting sum of pairwise Bhattacharyya distances among the Gaussian distributions. Consequently, the distance between two water masses may be measured fast, which allows the automatic and efficient comparison of the water masses for a wide range area. The proposed approach not only can approximate the distribution of temperature, salinity, and depth directly without the prior knowledge for assuming the regression family, but may restrict the complexity by controlling the number of mixtures when the amounts of samples are unevenly distributed. In addition, it is critical for knowledge discovery in marine research to represent, manage and share the temperature-salinity-depth characteristics flexibly and responsively. The proposed approach has been applied to a real-time visualization system of ocean data, which may facilitate the comparison of water masses by aggregating the data without degrading the discriminating capabilities. This system provides an interface for querying geographic locations with similar temperature-salinity-depth characteristics interactively and for tracking specific patterns of water masses, such as the Kuroshio near Taiwan or those in the South China Sea.

Keywords: water mass, Gaussian mixture model, data visualization, system framework

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Authors: Gjergji Buzo

Abstract:

This paper presents the communist policy about tangible and intangible religious heritage in Pogradec District, Albania. The district of Pogradec lies in the southeast of Albania and consists of the municipality, located on the shore of Ohrid Lake, and 7 Administrative Units, with a population of about 61,530 inhabitants. From the statistical data provided by the Institute of Statistics, the city of Pogradec has 55.9% Muslims, 19.9% Orthodox, 1.4% Catholic and 1.1% Bektashi. While the religious affiliation in the Administrative Unit is as follows: Muslim 72.1%, Orthodox 3.32%, Catholic 1.18%, Bektashi 0.2%. The percentages are approximate values, taking into consideration that 13.8% of the total population preferred not to answer the question on religion and that for 2.4% of the persons who answered, the information provided was not relevant or stated. The percentage of the persons who declared themselves as believers without belonging to any religion was 5.5 and the persons who declared themselves as a non-believer and not belonging to any religion was 2.5. Number of persons who declared themselves as evangelists was 0.1% and the number of them declared as "other Christians" was 0.1%. About 80% of the population believe in God, and most of them practice one of the monotheist religions. We have divided religious practices into three major periods. The first is until 1967, when different religions were practiced in Pogradec in harmony with each other; the second is the period 1967-1990, during which the practice of religion was prohibited, and the period after 1990, when religious freedom was restored. This article is focused on the communist period 1967-1990 when Albania (and Pogradec as part of it) became the only atheist country in the world. The object of the study is the impact of these policies on spiritual and material religious identity. The communist regime destroyed or transformed the religious objects, whether Islamic or Christian and prohibited practicing religious rituals in Albania. They followed an education policy with an atheistic spirituality among young people, characterizing religion as opium for the people. All these left traces on the people and brought a deformation of the religious identity. In order to better understand the reality of that time and how this policy was experienced by the people, we conducted a survey in Pogradect District with the participation of 1000 people.

Keywords: communism policy, heritage, identity, religion, statistics, survey

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