In Search of High Growth: Mapping out Academic Spin-Off´s Performance in Catalonia

This exploratory study gives an overview of the evolution of the main financial and performance indicators of the Academic Spin-Off’s and High Growth Academic Spin-Off’s in year 3 and year 6 after its creation in the region of Catalonia in Spain. The study compares and evaluates results of these different measures of performance and the degree of success of these companies for each University. We found that the average Catalonian Academic Spin-Off is small and have not achieved the sustainability stage at year 6. On the contrary, a small group of High Growth Academic Spin-Off’s exhibits robust performance with high profits in year 6. Our results support the need to increase selectivity and support for these companies especially near year 3, because are the ones that will bring wealth and employment. University role as an investor has rigid norms and habits that impede an efficient economic return from their ASO investment. Universities with high performance on sales and employment in year 3 not always could sustain this growth in year 6 because their ASO’s are not profitable. On the contrary, profitable ASO exhibit superior performance in all measurement indicators in year 6. We advocate the need of a balanced growth (with profits) as a way to obtain subsequent continuous growth.

Inverse Heat Conduction Analysis of Cooling on Run Out Tables

In this paper, we introduced a gradient-based inverse solver to obtain the missing boundary conditions based on the readings of internal thermocouples. The results show that the method is very sensitive to measurement errors, and becomes unstable when small time steps are used. The artificial neural networks are shown to be capable of capturing the whole thermal history on the run-out table, but are not very effective in restoring the detailed behavior of the boundary conditions. Also, they behave poorly in nonlinear cases and where the boundary condition profile is different. GA and PSO are more effective in finding a detailed representation of the time-varying boundary conditions, as well as in nonlinear cases. However, their convergence takes longer. A variation of the basic PSO, called CRPSO, showed the best performance among the three versions. Also, PSO proved to be effective in handling noisy data, especially when its performance parameters were tuned. An increase in the self-confidence parameter was also found to be effective, as it increased the global search capabilities of the algorithm. RPSO was the most effective variation in dealing with noise, closely followed by CRPSO. The latter variation is recommended for inverse heat conduction problems, as it combines the efficiency and effectiveness required by these problems.

Semantic Enhanced Social Media Sentiments for Stock Market Prediction

Traditional document representation for classification follows Bag of Words (BoW) approach to represent the term weights. The conventional method uses the Vector Space Model (VSM) to exploit the statistical information of terms in the documents and they fail to address the semantic information as well as order of the terms present in the documents. Although, the phrase based approach follows the order of the terms present in the documents rather than semantics behind the word. Therefore, a semantic concept based approach is used in this paper for enhancing the semantics by incorporating the ontology information. In this paper a novel method is proposed to forecast the intraday stock market price directional movement based on the sentiments from Twitter and money control news articles. The stock market forecasting is a very difficult and highly complicated task because it is affected by many factors such as economic conditions, political events and investor’s sentiment etc. The stock market series are generally dynamic, nonparametric, noisy and chaotic by nature. The sentiment analysis along with wisdom of crowds can automatically compute the collective intelligence of future performance in many areas like stock market, box office sales and election outcomes. The proposed method utilizes collective sentiments for stock market to predict the stock price directional movements. The collective sentiments in the above social media have powerful prediction on the stock price directional movements as up/down by using Granger Causality test.

Transnational Higher Education: Developing a Transnational Student Success 'Signature' for Pre-Clinical Medical Students – An Action Research Project

This paper describes an Action Research project which was undertaken to inform professional practice in order to develop a newly created Centre for Student Success in the specific context of transnational medical and nursing education in the Middle East. The objectives were to enhance the academic performance, persistence, integration and personal and professional development of a multinational study body, in particular in relation to pre-clinical medical students, and to establish a comfortable, friendly and student-driven environment within an Irish medical university recently established in Bahrain. The outcomes of the project resulted in the development of a specific student success ‘signature’ for this particular transnational higher education context.

Simulation of Solar Assisted Absorption Cooling and Electricity Generation along with Thermal Storage

Parabolic solar trough systems have seen limited deployments in cold northern climates as they are more suitable for electricity production in southern latitudes. A numerical dynamic model is developed to simulate troughs installed in cold climates and validated using a parabolic solar trough facility in Winnipeg. The model is developed in Simulink and will be utilized to simulate a trigeneration system for heating, cooling and electricity generation in remote northern communities. The main objective of this simulation is to obtain operational data of solar troughs in cold climates and use the model to determine ways to improve the economics and address cold weather issues. In this paper the validated Simulink model is applied to simulate a solar assisted absorption cooling system along with electricity generation using Organic Rankine Cycle (ORC) and thermal storage. A control strategy is employed to distribute the heated oil from solar collectors among the above three systems considering the temperature requirements. This modelling provides dynamic performance results using measured meteorological data recorded every minute at the solar facility location. The purpose of this modeling approach is to accurately predict system performance at each time step considering the solar radiation fluctuations due to passing clouds. Optimization of the controller in cold temperatures is another goal of the simulation to for example minimize heat losses in winter when energy demand is high and solar resources are low. The solar absorption cooling is modeled to use the generated heat from the solar trough system and provide cooling in summer for a greenhouse which is located next to the solar field. The results of the simulation are presented for a summer day in Winnipeg which includes comparison of performance parameters of the absorption cooling and ORC systems at different heat transfer fluid (HTF) temperatures.

Thermodynamic Analysis of a Vapor Absorption System Using Modified Gouy-Stodola Equation

In this paper, the exergy analysis of vapor absorption refrigeration system using LiBr-H2O as working fluid is carried out with the modified Gouy-Stodola approach rather than the classical Gouy-Stodola equation and effect of varying input parameters is also studied on the performance of the system. As the modified approach uses the concept of effective temperature, the mathematical expressions for effective temperature have been formulated and calculated for each component of the system. Various constraints and equations are used to develop program in EES to solve these equations. The main aim of this analysis is to determine the performance of the system and the components having major irreversible loss. Results show that exergy destruction rate is considerable in absorber and generator followed by evaporator and condenser. There is an increase in exergy destruction in generator, absorber and condenser and decrease in the evaporator by the modified approach as compared to the conventional approach. The value of exergy determined by the modified Gouy-Stodola equation deviates maximum i.e. 26% in the generator as compared to the exergy calculated by the classical Gouy-Stodola method.

A Superior Delay Estimation Model for VLSI Interconnect in Current Mode Signaling

Today’s VLSI networks demands for high speed. And in this work the compact form mathematical model for current mode signalling in VLSI interconnects is presented.RLC interconnect line is modelled using characteristic impedance of transmission line and inductive effect. The on-chip inductance effect is dominant at lower technology node is emulated into an equivalent resistance. First order transfer function is designed using finite difference equation, Laplace transform and by applying the boundary conditions at the source and load termination. It has been observed that the dominant pole determines system response and delay in the proposed model. The novel proposed current mode model shows superior performance as compared to voltage mode signalling. Analysis shows that current mode signalling in VLSI interconnects provides 2.8 times better delay performance than voltage mode. Secondly the damping factor of a lumped RLC circuit is shown to be a useful figure of merit.

Optimal Design of a PV/Diesel Hybrid System for Decentralized Areas through Economic Criteria

An innovative concept called “Flexy-Energy” is developing at 2iE. This concept aims to produce electricity at lower cost by smartly mix different available energy sources in accordance to the load profile of the region. With a higher solar irradiation and due to the fact that Diesel generator are massively used in sub-Saharan rural areas, PV/Diesel hybrid systems could be a good application of this concept and a good solution to electrify this region, provided they are reliable, cost effective and economically attractive to investors. Presentation of the developed approach is the aims of this paper. The PV/Diesel hybrid system designed consists to produce electricity and/or heat from a coupling between Diesel Diesel generators and PV panels without batteries storage, while ensuring the substitution of gasoil by bio-fuels available in the area where the system will be installed. The optimal design of this system is based on his technical performances; the Life Cycle Cost (LCC) and Levelized Cost of Energy are developed and use as economic criteria. The Net Present Value (NPV), the internal rate of return (IRR) and the discounted payback (DPB) are also evaluated according to dual electricity pricing (in sunny and unsunny hours). The PV/Diesel hybrid system obtained is compared to the standalone Diesel Diesel generators. The approach carried out in this paper has been applied to Siby village in Mali (Latitude 12 ° 23'N 8 ° 20'W) with 295 kWh as daily demand.This approach provides optimal physical characteristics (size of the components, number of component) and dynamical characteristics in real time (number of Diesel generator on, their load rate, fuel specific consumptions, and PV penetration rate) of the system. The system obtained is slightly cost effective; but could be improved with optimized tariffing strategies.

Using High Performance Computing for Online Flood Monitoring and Prediction

The main goal of this article is to describe the online flood monitoring and prediction system Floreon+ primarily developed for the Moravian-Silesian region in the Czech Republic and the basic process it uses for running automatic rainfall-runoff and hydrodynamic simulations along with their calibration and uncertainty modeling. It takes a long time to execute such process sequentially, which is not acceptable in the online scenario, so the use of a high performance computing environment is proposed for all parts of the process to shorten their duration. Finally, a case study on the Ostravice River catchment is presented that shows actual durations and their gain from the parallel implementation.

Investigation on Novel Based Naturally-Inspired Swarm Intelligence Algorithms for Optimization Problems in Mobile Ad Hoc Networks

Nature is the immense gifted source for solving complex problems. It always helps to find the optimal solution to solve the problem. Mobile Ad Hoc NETwork (MANET) is a wide research area of networks which has set of independent nodes. The characteristics involved in MANET’s are Dynamic, does not depend on any fixed infrastructure or centralized networks, High mobility. The Bio-Inspired algorithms are mimics the nature for solving optimization problems opening a new era in MANET. The typical Swarm Intelligence (SI) algorithms are Ant Colony Optimization (ACO), Artificial Bee Colony (ABC), Particle Swarm Optimization (PSO), Modified Termite Algorithm, Bat Algorithm (BA), Wolf Search Algorithm (WSA) and so on. This work mainly concentrated on nature of MANET and behavior of nodes. Also it analyses various performance metrics such as throughput, QoS and End-to-End delay etc.

Metal(loids) Speciation Using HPLC-ICP-MS Technique in Klodnica River, Upper Silesia, Poland

The work allowed gaining knowledge about redox and speciation changes of As, Cr and Sb ionic forms in Klodnica River water. This kind of studies never has been conducted in this region of Poland. In study optimized and validated previously HPLC-ICP-MS methods for determination of As, Sb and Cr was used. Separation step was done using high-performance liquid chromatograph equipped with ion-exchange column followed by ICP-MS spectrometer detector. Preliminary studies included determination of the total concentration of As, Sb and Cr, pH, Eh, temperature and conductivity of the water samples. The study was conducted monthly from March to August 2014, at six points on the Klodnica River. The results indicate that exceeded at acceptable concentration of total Cr and Sb was observed in Klodnica River and we should qualify Klodnica River waters below the second purity class. In Klodnica River waters dominates oxidized antimony and arsenic forms, as well as the two forms of chromium Cr(VI) and Cr(III). Studies have also shown the methyl derivative of arsenic's presence.

Adsorption of Acetone Vapors by SBA-16 and MCM-48 Synthesized from Rice Husk Ash

Silica was extracted from agriculture waste rice husk ash (RHA) and was used as the silica source for synthesis of RMCM-48 and RSBA-16. An alkali fusion process was utilized to separate silicate supernatant and the sediment effectively. The CTAB/Si and F127/Si molar ratio was employed to control the structure properties of the obtained RMCM-48 and RSBA-16 materials. The N2 adsorption-desorption results showed the micro-mesoporous RSBA-16 possessed high specific surface areas (662-1001 m2/g). All the obtained RSBA-16 materials were applied as the adsorbents for acetone adsorption. And the breakthrough tests clearly revealed that the RSBA-16(0.004) materials could achieve the highest acetone adsorption capacity of 181 mg/g under 1000 ppmv acetone vapor concentration at 25oC, which was also superior to ZSM-5 (71mg/g) and MCM-41 (157mg/g) under same test conditions. This can help to reduce the solid waste and the high adsorption performance of the obtained materials could consider as potential adsorbents for acetone adsorption.

STATISTICA Software: A State of the Art Review

Data mining idea is mounting rapidly in admiration and also in their popularity. The foremost aspire of data mining method is to extract data from a huge data set into several forms that could be comprehended for additional use. The data mining is a technology that contains with rich potential resources which could be supportive for industries and businesses that pay attention to collect the necessary information of the data to discover their customer’s performances. For extracting data there are several methods are available such as Classification, Clustering, Association, Discovering, and Visualization… etc., which has its individual and diverse algorithms towards the effort to fit an appropriate model to the data. STATISTICA mostly deals with excessive groups of data that imposes vast rigorous computational constraints. These results trials challenge cause the emergence of powerful STATISTICA Data Mining technologies. In this survey an overview of the STATISTICA software is illustrated along with their significant features.

Intelligent Path Tracking Hybrid Fuzzy Controller for a Unicycle-Type Differential Drive Robot

In this paper, we discuss the performance of applying hybrid spiral dynamic bacterial chemotaxis (HSDBC) optimisation algorithm on an intelligent controller for a differential drive robot. A unicycle class of differential drive robot is utilised to serve as a basis application to evaluate the performance of the HSDBC algorithm. A hybrid fuzzy logic controller is developed and implemented for the unicycle robot to follow a predefined trajectory. Trajectories of various frictional profiles and levels were simulated to evaluate the performance of the robot at different operating conditions. Controller gains and scaling factors were optimised using HSDBC and the performance is evaluated in comparison to previously adopted optimisation algorithms. The HSDBC has proven its feasibility in achieving a faster convergence toward the optimal gains and resulted in a superior performance.

Human Capital and the Innovation System – Case Study of the Mpumalanga Province, South Africa

Innovation plays an important role in economic growth and development. Evolutionary economics has entrepreneurs at the centre of the innovation system, but includes all other participants as contributors to the performance of the innovation system. Education and training institutions, one of the participants in the innovation system, contributes in different ways to human capital. The gap in literature on the competence building as part of human capital in the analysis of innovation systems is addressed in this paper. The Mpumalanga Province of South Africa is used as a case study. It was found that the absence of a university, the level of education, the quality and performance in the education sector and the condition of the education infrastructure have not been conducive to learning.

Students’ Willingness to Accept Virtual Lecturing Systems: An Empirical Study by Extending the UTAUT Model

The explosion of the World Wide Web and the electronic trend of university teaching have transformed the learning style to become more learner-centered, which has popularized the digital delivery of mediated lectures as an alternative or an adjunct to traditional lectures. Despite its potential and popularity, virtual lectures have not been adopted yet in Jordanian universities. This research aimed to fill this gap by studying the factors that influence students’ willingness to accept virtual lectures in one Jordanian University. A quantitative approach was followed, by obtaining 216 survey responses and statistically applying the UTAUT model with some modifications. Results revealed that performance expectancy, effort expectancy, social influences, and self-efficacy could significantly influence students’ attitudes towards virtual lectures. Additionally, Facilitating conditions and attitudes towards virtual lectures were found with significant influence on students’ intention to take virtual lectures. Research implications and future work were specified afterwards.

Kinetic Rate Comparison of Methane Catalytic Combustion of Palladium Catalysts Impregnated onto γ-Alumina and Bio-Char

Catalytic combustion of methane is imperative due to stability of methane at low temperature. Methane (CH4), therefore, remains unconverted in vehicle exhausts thereby causing greenhouse gas GHG emission problem. In this study, heterogeneous catalysts of palladium with bio-char (2 wt% Pd/Bc) and Al2O3 (2wt% Pd/ Al2O3) supports were prepared by incipient wetness impregnation and then subsequently tested for catalytic combustion of CH4. Support-porous heterogeneous catalytic combustion (HCC) material were selected based on factors such as surface area, porosity, thermal stability, thermal conductivity, reactivity with reactants or products, chemical stability, catalytic activity, and catalyst life. Sustainable and renewable support-material of bio-mass char derived from palm shell waste material was compared with those from the conventional support-porous materials. Kinetic rate of reaction was determined for combustion of methane on Palladium (Pd) based catalyst with Al2O3 support and bio-char (Bc). Material characterization was done using TGA, SEM, and BET surface area. The performance test was accomplished using tubular quartz reactor with gas mixture ratio of 3% methane and 97% air. The methane porous-HCC conversion was carried out using online gas analyzer connected to the reactor that performed porous-HCC. BET surface area for prepared 2 wt% Pd/Bc is smaller than prepared 2wt% Pd/ Al2O3 due to its low porosity between particles. The order of catalyst activity based on kinetic rate on reaction of catalysts in low temperature was 2wt% Pd/Bc>calcined 2wt% Pd/ Al2O3> 2wt% Pd/ Al2O3>calcined 2wt% Pd/Bc. Hence agro waste material can successfully be utilized as an inexpensive catalyst support material for enhanced CH4 catalytic combustion.

Innovative Activity and Firm Performance: The Case of Eurozone Periphery

In this work, we attempt to analyze the contribution of innovative activities to firm performance and growth. We examine economic data from some of the economies that were heavily affected by current economic crisis: the countries of southern Europe (Portugal, Italy, Greece and Spain) and Ireland. Following literature, an appropriate econometric model is developed and several indicators are tested in order to disclose possible relation with innovative activity. Findings confirm the crucial effect of innovative process in economic activity, in firm and country level.

Advanced Pulse Width Modulation Techniques for Z Source Multi Level Inverter

This paper proposes five level diode clamped Z source Inverter. The existing PWM techniques used for ZSI are restricted for two level. The two level Z Source Inverter have high harmonic distortions which effects the performance of the grid connected PV system. To improve the performance of the system the number of voltage levels in the output waveform need to be increased. This paper presents comparative analysis of a five level diode clamped Z source Inverter with different carrier based Modified Pulse Width Modulation techniques. The parameters considered for comparison are output voltage, voltage gain, voltage stress across switch and total harmonic distortion when powered by same DC supply. Analytical results are verified using MATLAB.

Object-Oriented Programming for Modeling and Simulation of Systems in Physiology

Object-oriented modeling is spreading in current simulation of physiological systems through the use of the individual components of the model and its interconnections to define the underlying dynamic equations. In this paper we describe the use of both the SIMSCAPE and MODELICA simulation environments in the object-oriented modeling of the closed loop cardiovascular system. The performance of the controlled system was analyzed by simulation in light of the existing hypothesis and validation tests previously performed with physiological data. The described approach represents a valuable tool in the teaching of physiology for graduate medical students.