Developing Online Collaborative Games for e-Learning Environments

Based on our experience, we believe that games, competition and teamwork offer a pleasant and active way of learning. This is much more efficient when the learner has a smile on his face, when he is astonished and curious about next levels and finds the game sufficiently challenging and fun to try again. Our application proposal has the purpose of implementing an e-Learning platform for improving the teaching and learning process in somewhat abstract domains, such as computer architecture or object oriented programming, with the help of games. These games are time-dependent and are able to support collaboration between groups. To this date there are two learning games implemented: a crosswo…

Improving programming skills of Mechanical Engineering students by teaching in C# multi-objective optimizations methods

Designing an optimized suspension system that meet the main functions of comfort, safety and handling on poor quality roads is a goal for researchers. This paper represents a software development guide for designers of suspension systems with less programming skills that will enable them to implement their own optimization methods that improve traditional methods by using their domain knowledge.

Multi-objective optimisations for a superscalar architecture with selective value prediction

This work extends an earlier manual design space ex ploration of our developed Selective Load Value Pre diction based superscalar architecture to the L2 unified cache. A fter that we perform an automatic design space expl oration using a special developed software tool by varying several architectural parameters. Our goal is to find optim al configurations in terms of CPI (Cycles per Instruction) and energy consumption. By varying 19 architectural parameter s, as we proposed, the design space is over 2.5 millions of billions configurations which obviously means that only heuristic search can be considered. Therefore, we propose dif ferent methods of automatic design space exploratio n based…

Using neural networks to obtain indirect information about the state variables in an alcoholic fermentation process

This work provides a manual design space exploration regarding the structure, type, and inputs of a multilayer neural network (NN) to obtain indirect information about the state variables in the alcoholic fermentation process. The main benefit of our application is to help experts reduce the time needed for making the relevant measurements and to increase the lifecycles of sensors in bioreactors. The novelty of this research is the flexibility of the developed application, the use of a great number of variables, and the comparative presentation of the results obtained with different NNs (feedback vs. feed-forward) and different learning algorithms (Back-Propagation vs. Levenberg&ndash

Optimizing the Integration Area and Performance of VLIW Architectures by Hardware/Software Co-design

The cost and the performance are major concerns that the designers of embedded processors shall take into account, especially for market considerations. In order to reduce the cost, embedded systems rely on simple hardware architectures like VLIW (Very Long Instruction Word) processors and they look for compiler support. This paper aims at developing a design space explorer of VLIW architectures from different perspectives like processing performance and integration area. A multi-objective Genetic Algorithm (GA) was used to find the optimum hardware configuration of an embedded system and the optimization rules applied by compiler on the benchmarks code. The first step consisted in represen…

Smart parking system - another way of sharing economy provided by private institutions

This paper presents our smart parking solution implemented at “Lucian Blaga” University of Sibiu (LBUS) Romania, which consists in a hardware / software embedded system for managing the institution’s parking lots, namely sharing the parking places in excess for people who are in traffic in neighbourhood of LBUS and are looking to park. Our solution is flexible, universal, applicable to all faculties that have car parks from Romania and not only, in university cities where the crowd is bigger, but also to other private institutions that own parking spaces inefficiently exploited. The advantages introduced are primarily economic, then social and even environmental. The first benefit is econom…

A Visual Simulation Framework For Simultaneous Multithreading Architectures

The computing systems, and particularly microarchitectures, are in a continuous expansion reaching an unmanageable complexity by the human mind. In order to understand and control this expansion, researchers need to design and implement larger and more complex systems’ simulators. In the current paradigm the simulators play the key role in going further, by translating all complex processing mechanisms in relevant and easy to understand information. This paper aims to make a suggestive description of the concepts and principles implemented into a Simultaneous Multithreading Architecture. We introduce the SMTAHSim framework, an educational tool that simulates in an interactive manner the imp…

OMiLAB: A Smart Innovation Environment for Digital Engineers

This position paper introduces a Smart Innovation Environment for experimentation related to digital transformation projects, for the consolidation of a proposed "Digital Engineer" skill profile (with a business-oriented facet labelled as "Digital Innovator"). In the Internet of Things era, this profile implies the ability to perform both digital design and engineering activities, to semantically bridge multiple layers of abstraction and specificity - from business analysis down to cyber-physical engineering. In the paper's proposal, this integration is enabled by conceptual modelling methods and interoperable modelling tools, tailored to support the creation of Digital Twins for innovative…

Forecasting Electricity Consumption and Production in Smart Homes through Statistical Methods

Abstract Over the last years, a steady increase in both domestic electricity consumption and in the adoption of personal clean energy production systems has been observed worldwide. By analyzing energy consumption and production on photovoltaic panels mounted in a house, this work focuses on finding patterns in electrical energy consumption and devising a predictive model. Our goal is to find an accurate method to predict electrical energy consumption and production. Being able to anticipate how consumers will use energy in the near future, homeowners, companies and governments may optimize their behavior and the import and export of electricity. We evaluated the ARIMA and TBATS statistical…

E-learning approach of the graph coloring problem applied to register allocation in embedded systems

The main aim of this paper consists in developing an effective e-learning tool, focused on evolutionary algorithms, in order to solve the graph coloring problem. Subsidiary, we apply graph coloring for register allocation in embedded systems. From didactic viewpoint, our tool has benefits in the learning process because it helps students to observe the relationship between the graph coloring problem and CPU registers allocation with the help of four developed modules: the genetic algorithm, the graphical viewer, the interference graph for a C program and a web application which collects the simulation results. All these applications are combined by a graphical interface which allows the use…

Understanding Prediction Limits Through Unbiased Branches

The majority of currently available branch predictors base their prediction accuracy on the previous k branch outcomes. Such predictors sustain high prediction accuracy but they do not consider the impact of unbiased branches which are difficult-to-predict. In this paper, we quantify and evaluate the impact of unbiased branches and show that any gain in prediction accuracy is proportional to the frequency of unbiased branches. By using the SPECcpu2000 integer benchmarks we show that there are a significant proportion of unbiased branches which severely impact on prediction accuracy (averaging between 6% and 24% depending on the prediction context used).

Different Methods of Artificial Intelligence Used for Optimization the Turning Process

In this paper, we realize a comparative study between some heuristics methods applied in turning operation in order to find optimal cutting parameters. We consider five different constraints aimed to achieve minimum total cost of machining. We have chosen the Simulated Annealing (SA) – a local search method, and Weighted-Sum Genetic Algorithm (WSGA) – a non-Pareto approach of a multi-objective optimization algorithm, based on a weighted aggregation of objectives. The aggregation may be with fixed weights or with random (variable) weights. The simulations showed that, even if it produces better results than the SA, WSGA with fixed weights, does not lead to optimum results, highlighting in th…

New insights into the cellular makeup and progenitor potential of palatal connective tissues

The present study investigated the regenerative potential of connective tissues harvested from two palatal areas widely used as donor sites for muco-gingival surgical approaches. Connective tissue grafts (CTGs) were obtained by de-epithelialisation of a free gingival graft (deCTG) and by a split flap approach from a previous donor site (reCTG). Two types of mesenchymal stem cell (MSCs) were isolated and were named de-epithelialised MSCs (deMSCs) and re-entry MSCs (reMSCs). The cells were characterised and cellular functionality was investigated. CTGs were evaluated using immunohistochemical and ultrastructural approaches. No significant differences were observed regarding the frequency of c…

The Impact of Java Applications at Microarchitectural Level from Branch Prediction Perspective

The portability, the object-oriented and distributed programming models, multithreading support and automatic garbage collection are features that make Java very attractive for application developers. The main goal of this paper consists in pointing out the impact of Java applications at microarchitectural level from two perspectives: unbiased branches and indirect jumps/calls, such branches limiting the ceiling of dynamic branch prediction and causing significant performance degradation. Therefore, accurately predicting this kind of branches remains an open problem. The simulation part of the paper mainly refers to determining the context length influence on the percentage of unbiased bran…

Load forecast on intelligent buildings based on temporary occupancy monitoring

The modeling of energy consumption in buildings must consider occupancy as a relevant input, since it plays a very important role in the overall building's energy consumption. Frequently, buildings lack of permanent occupancy monitoring solutions. However, they may include data sources that are correlated with real building occupancy. This study proposes a new methodology for energy consumption modeling, supported by these alternative data sources, such as the number of vehicles in a parking lot. The aim is to mitigate investment in permanent occupancy monitoring solutions. The proposed methodology makes use of short-term real occupancy monitoring for model fitting, to enable the developmen…

Improving the Training Methods for Designers of Flexible Production Cells in Factories of the Future

This work proposes a design method for flexible manufacturing systems (FMS). The method reduces the learning curve by helping employees to solve problems related to the design and optimization of the layout, operation and control of FMS, avoiding the drawbacks of current tools. The approach uses Domain Specific Modeling Languages (DSML) for specification of FMS. The paper presents the definition of the DSML and the implementation of the graphical modeling and simulation tool bringing important contributions to development of the domain through the use of constructions from categories theory for DSML specifications. This mathematical basis allows the definition of constraints to avoid supple…

Exploiting selective instruction reuse and value prediction in a superscalar architecture

In our previously published research we discovered some very difficult to predict branches, called unbiased branches. Since the overall performance of modern processors is seriously affected by misprediction recovery, especially these difficult branches represent a source of important performance penalties. Our statistics show that about 28% of branches are dependent on critical Load instructions. Moreover, 5.61% of branches are unbiased and depend on critical Loads, too. In the same way, about 21% of branches depend on MUL/DIV instructions whereas 3.76% are unbiased and depend on MUL/DIV instructions. These dependences involve high-penalty mispredictions becoming serious performance obstac…

Digital Design Skills for Factories of the Future

Industry 4.0, Smart Manufacturing, Factories of the Future all describe aspects of the heralding era of digitalization of manufacturing aiming to interconnect every step of the manufacturing process and seamlessly integrate the physical and digital world. In Factories of the Future a central computer organizes the intelligent networking of all subsystems, suppliers and customers into one system. All relevant requirements concerning manufacturing and product are confirmed at design time, while execution takes place autonomously as ICT and automation are integrated. The main challenge is represented by educational system, how prepared is to provide students, future employees, the digital comp…

Urban smart mobility in the scientific literature — bibliometric analysis

Abstract This article aims at identification of the main trends in scientific literature characterising urban smart mobility, on the basis of bibliometric analysis of articles published in the ISI Web of Science and Scopus databases. The study period was set from 2000 to 2017. Authors used a basic technique of the bibliometric analysis of the scientific literature characterising urban smart mobility with the support of the VOSviewer software. The analysis included the number of publications, citation analysis, research area analysis and the most frequent keywords. The analysis led to taking notice of current research trends dealing with the urban smart mobility. The core of the paper is a t…

Using FOCAP tool for teaching microarchitecture simulation and optimization

This paper presents our new developed FOCAP tool (Framework for optimizing the Computer Architecture Performance) in order to gain a better understanding and familiarity of the students with new advanced learning methods and tools in the Microarchitecture Simulation and Optimization. At this stage, FOCAP allows a mono-objective automatic design space exploration (DSE) of a superscalar processor by varying several architectural parameters. Such DSE tools are very useful, since it is impossible to simulate all the configurations of a highly parameterized microarchitecture. Therefore, heuristic methods, local search algorithms and advanced machine learning methods are good candidates to find n…

Future house automation

In this paper, we propose the future house automation, a PLC-based embedded system that aims reducing the house energy consumption by optimizing the entire hardware assembly and software algorithms. The project started from the idea of designing a self-controlled house, to increase user's comfort in his daily environment, reducing the cost and optimizing the energy consumption. Our embedded application represents a green solution into a growing number of environmentally aware consumers, very suitable for the market of energy-efficient control systems. We provide a cheap solution for developing by everyone its own automation system control house. Therefore, our project contributes for helpin…

Implementing some Evolutionary Computing Methods for Determining the Optimal Parameters in the Turning Process

In this paper, we comparatively present two heuristics search methods – Simulated Annealing and Weighted Sum Genetic Algorithm, in order to find optimal cutting parameters in turning operation. We consider five different constraints aiming to achieve minimum total cost of machining. We developed a customizable software application in Microsoft Visual Studio with C# source code, flexible and extensible that implements the optimization methods. The experiments are based on real data gathered from S.C. “Compa” S.A Sibiu, a company that manufactures automotive components and targets improving of product quality and reducing cost and production time. The obtained results show that, although the …

Human capital evaluation in knowledge-based organizations based on big data analytics

Abstract Starting from a Human Capital Analysis Model, this work introduces an original methodology for evaluating the performance of employees. The proposed architecture, particularly well suited to the special needs of knowledge-based organizations, is articulated into a framework able to manage cases where data is missing and an adaptive scoring algorithm takes into account seniority, performance, and performance evolution trends, allowing employee evaluation over longer periods. We developed a flexible software tool that gathers data from organizations in an automatic way – through adapted connectors – and generates abundant results on the measurement and distribution of employees’ perf…

The Effects of Multiple‐Exposure Textual Enhancement on Child L2 Learners’ Development in Derivational Morphology: A Multi‐Site Study

Enhancing the Sniper Simulator with Thermal Measurement

This paper presents the enhancement of the Sniper multicore / manycore simulator with thermal measurement possibilities using the HotSpot simulator. We present a plugin that interacts with Sniper to retrieve simulation data (integration areas and power consumptions) and calls HotSpot to compute the corresponding thermal results. The plugin also builds a two dimensional floorplan for the simulated microarchitecture. Furthermore we plan to integrate the simulation methodology presented here into an automatic design space exploration process using the multi-objective optimization tool called FADSE. Keywords—multicore; simulator; power consumption; thermal; HotSpot; Sniper

Performance and energy optimisation in CPUs through fuzzy knowledge representation

Abstract This paper presents an automatic design space exploration using processor design knowledge for the multi-objective optimisation of a superscalar microarchitecture enhanced with selective load value prediction (SLVP). We introduced new important SLVP parameters and determined their influence regarding performance, energy consumption, and thermal dissipation. We significantly enlarged initial processor design knowledge expressed through fuzzy rules and we analysed its role in the process of automatic design space exploration. The proposed fuzzy rules improve the diversity and quality of solutions, and the convergence speed of the design space exploration process. Experiments show tha…

Unbiased Branches: An Open Problem

The majority of currently available dynamic branch predictors base their prediction accuracy on the previous k branch outcomes. Such predictors sustain high prediction accuracy but they do not consider the impact of unbiased branches, which are difficult-to-predict. In this paper, we evaluate the impact of unbiased branches in terms of prediction accuracy on a range of branch difference predictors using prediction by partial matching, multiple Markov prediction and neural-based prediction. Since our focus is on the impact that unbiased branches have on processor performance, timing issues and hardware costs are out of scope of this investigation. Our simulation results, with the SPEC2000 in…

A study on forecasting electricity production and consumption in smart cities and factories

Abstract The electrical power sector must undergo a thorough metamorphosis to achieve the ambitious targets in greenhouse gas reduction set forth in the Paris Agreement of 2015. Reducing uncertainty about demand and, in case of renewable electricity generation, supply is important for the determination of spot electricity prices. In this work we propose and evaluate a context-based technique to anticipate the electricity production and consumption in buildings. We focus on a household with photovoltaics and energy storage system. We analyze the efficiency of Markov chains, stride predictors and also their combination into a hybrid predictor in modelling the evolution of electricity producti…

Implementing an embedded system to identify possible COVID-19 suspects using thermovision cameras

The main goal of this paper is to prove that by combining thermal vision cameras and image processing with many deep learning classification algorithms we developed an effective embedded system with high applicability in this critical period caused by COVID-19 pandemic disease. Using fixed and mobile thermal cameras we envisioned and developed a real time temperature screening capable of sending alarm signals over network or by SMS to local authorities along with multiple detection metrics such as the age, the gender, the facial emotion, the GPS location where the alarm went off, the temperature reading from the human face and also if the subject is wearing or not a medical face mask.

Digitization, Epistemic Proximity, and the Education System: Insights from a Bibliometric Analysis

Advances in IoT, AI, Cyber-Physical Systems, Computational Intelligence, and Big Data Analytics require organizations and workforce to be able and willing to learn how to interact with digital technology. In organizations, coordination and cooperation between actors with expertise in business and technology is fundamental, but integration is hard without understanding the terminology and problems of the interlocutor. Epistemic proximity becomes prominent, underlining the importance of an education focused on flexibility, willingness to cope with the unknown, and interdisciplinarity. The main goal of this work is to provide a perspective on how the education system is evolving to support org…