Search results for: Stock Prediction

Authors: Kepeng Li

Abstract:

This paper examines the phenomenon of recidivism in the Chinese stock market, emphasizing the significance of mitigating repeat offences within the corporate domain. Using a contingency model and data from Chinese publicly listed companies (1999-2018), the study investigates the impact of underperformance, governance factors, and managerial traits on unethical conduct. The research suggests that persistently unmet economic objectives can foster problem-focused exploration, potentially leading to misconduct. Furthermore, the study considers the unique cultural context of China, where “guanxi” and corruption may influence corporate behavior. It concludes that governance mechanisms play a pivotal role in regulating corporate behavior, underscoring the necessity for enhanced oversight and enforcement of corporate governance standards.

Keywords: Recidivism, corporate misbehavior, BTOF, aspiration level, corporate governance, individual characteristics.

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Authors: G. Guramishvili, M. Moistsrapishvili, L. Andghuladze

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In the article are considered the problems arising at increasing of transferring from rolling stock axles on rail loading from 210 KN up to 270 KN and is offered for rail strength analysis definition of rail force loading complex integral characteristic with taking into account all affecting force factors that is characterizing specific operation condition of rail structure and defines the working capability of structure.

As result of analysis due mentioned method is obtained that in the conditions of 270 KN loading the rail meets the working assessment criteria of rail and rail structures: Strength, rail track stability, rail links stability and its transverse stability, traffic safety condition that is rather important for post-Soviet countries railways.

Keywords: Axial loading, rail force loading, rail structure, rail strength analysis, rail track stability.

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Authors: Nikolaos Sariannidis, Grigoris Giannarakis, Nikolaos Litinas, Nikos Kartalis

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This study investigates the relationship between 10 year bond value, Yen/U.S dollar exchange rate, non-farm payrolls (all employs) and crude oil to U.S. Dow Jones Sustainability Index. A GARCH model is used to test these relationships for the period January 1st 1999 to January 31st 2008 using monthly data. Results show that an increase of the 10 year bond and non farm payrolls (all employs) lead to an increase of the D.J.S.I returns. On the contrary the volatility of the Yen/U.S dollar exchange rates as well as the increase of crude oil returns has negative effects on the U.S D.J.S.I returns. This study aims at assisting investors to understand the influences certain macroeconomic indicators have on the companies- stock returns as reported by the D.J.S.I.

Keywords: Bond value, Corporate Social Responsibility, Crudeoil, D.J.S.I United States, Exchange rate, GARCH, Non-farmpayrolls.

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Authors: Jay M. Joshi, Upena D. Dalal

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Multimedia information availability has increased dramatically with the advent of video broadcasting on handheld devices. But with this availability comes problems of maintaining the security of information that is displayed in public. ISMA Encryption and Authentication (ISMACryp) is one of the chosen technologies for service protection in DVB-H (Digital Video Broadcasting- Handheld), the TV system for portable handheld devices. The ISMACryp is encoded with H.264/AVC (advanced video coding), while leaving all structural data as it is. Two modes of ISMACryp are available; the CTR mode (Counter type) and CBC mode (Cipher Block Chaining) mode. Both modes of ISMACryp are based on 128- bit AES algorithm. AES algorithms are more complex and require larger time for execution which is not suitable for real time application like live TV. The proposed system aims to gain a deep understanding of video data security on multimedia technologies and to provide security for real time video applications using selective encryption for H.264/AVC. Five level of security proposed in this paper based on the content of NAL unit in Baseline Constrain profile of H.264/AVC. The selective encryption in different levels provides encryption of intra-prediction mode, residue data, inter-prediction mode or motion vectors only. Experimental results shown in this paper described that fifth level which is ISMACryp provide higher level of security with more encryption time and the one level provide lower level of security by encrypting only motion vectors with lower execution time without compromise on compression and quality of visual content. This encryption scheme with compression process with low cost, and keeps the file format unchanged with some direct operations supported. Simulation was being carried out in Matlab.

Keywords: AES-128, CAVLC, H.264, ISMACryp

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Authors: Abbas Hani, Seyed Ali Hoseini Abari

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Soil chemical and physical properties have important roles in compartment of the environment and agricultural sustainability and human health. The objectives of this research is determination of spatial distribution patterns of Cd, Zn, K, pH, TNV, organic material and electrical conductivity (EC) in agricultural soils of Natanz region in Esfehan province. In this study geostatistic and non-geostatistic methods were used for prediction of spatial distribution of these parameters. 64 composite soils samples were taken at 0-20 cm depth. The study area is located in south of NATANZ agricultural lands with area of 21660 hectares. Spatial distribution of Cd, Zn, K, pH, TNV, organic material and electrical conductivity (EC) was determined using geostatistic and geographic information system. Results showed that Cd, pH, TNV and K data has normal distribution and Zn, OC and EC data had not normal distribution. Kriging, Inverse Distance Weighting (IDW), Local Polynomial Interpolation (LPI) and Redial Basis functions (RBF) methods were used to interpolation. Trend analysis showed that organic carbon in north-south and east to west did not have trend while K and TNV had second degree trend. We used some error measurements include, mean absolute error(MAE), mean squared error (MSE) and mean biased error(MBE). Ordinary kriging(exponential model), LPI(Local polynomial interpolation), RBF(radial basis functions) and IDW methods have been chosen as the best methods to interpolating of the soil parameters. Prediction maps by disjunctive kriging was shown that in whole study area was intensive shortage of organic matter and more than 63.4 percent of study area had shortage of K amount.

Keywords: Electrical conductivity, Geostatistics, Geographical Information System, TNV

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Authors: Bryce Benson, Sooin Lee, Ashwin Belle

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Unrecognized or delayed identification of patient deterioration is a key cause of in-hospitals adverse events. Clinicians rely on vital signs monitoring to recognize patient deterioration. However, due to ever increasing nursing workloads and the manual effort required, vital signs tend to be measured and recorded intermittently, and inconsistently causing large gaps during patient monitoring. Additionally, during deterioration, the body’s autonomic nervous system activates compensatory mechanisms causing the vital signs to be lagging indicators of underlying hemodynamic decline. This study analyzes the predictive efficacy of the Analytic for Hemodynamic Instability (AHI) system, an automated tool that was designed to help clinicians in early identification of deteriorating patients. The lead time analysis in this retrospective observational study assesses how far in advance AHI predicted deterioration prior to the start of an episode of hemodynamic instability (HI) becoming evident through vital signs? Results indicate that of the 362 episodes of HI in this study, 308 episodes (85%) were correctly predicted by the AHI system with a median lead time of 57 minutes and an average of 4 hours (240.5 minutes). Of the 54 episodes not predicted, AHI detected 45 of them while the episode of HI was ongoing. Of the 9 undetected, 5 were not detected by AHI due to either missing or noisy input ECG data during the episode of HI. In total, AHI was able to either predict or detect 98.9% of all episodes of HI in this study. These results suggest that AHI could provide an additional ‘pair of eyes’ on patients, continuously filling the monitoring gaps and consequently giving the patient care team the ability to be far more proactive in patient monitoring and adverse event management.

Keywords: Clinical deterioration prediction, decision support system, early warning system, hemodynamic status, physiologic monitoring.

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Authors: Ernest Nweke, Enkhtuya Bavuudorj

Abstract:

The harsh realities of the scandalous failure of several notable corporations in the past two decades have inextricably resulted in a surge in corporate governance studies. Nevertheless, little or no attention has been paid to corporate governance studies in Mongolian firms and much less to the comprehension of the correlation among ownership structure, corporate governance mechanisms and trend of innovative activities. Innovation is the bed rock of enterprise success. However, the funding and support for innovative activities in many firms are to a great extent determined by the incentives provided by the firm’s internal and external governance mechanisms. Mongolia is an East Asian country currently undergoing a fast-paced transition from socialist to democratic system and it is a widely held view that private ownership as against public ownership fosters innovation. Hence, following the privatization policy of Mongolian Government which has led to the transfer of the ownership of hitherto state controlled and state directed firms to private individuals and organizations, expectations are high that sufficient motivation would be provided for firm managers to engage in innovative activities. This research focuses on the relationship between ownership structure, corporate governance on one hand and the level of innovation on the hand. The paper is empirical in nature and derives data from both reliable secondary and primary sources. Secondary data for the study was in respect of ownership structure of Mongolian listed firms and innovation trend in Mongolia generally. These were analyzed using tables, charts, bars and percentages. Personal interviews and surveys were held to collect primary data. Primary data was in respect of corporate governance practices in Mongolian firms and were collected using structured questionnaire. Out of a population of three hundred and twenty (320) companies listed on the Mongolian Stock Exchange (MSE), a sample size of thirty (30) randomly selected companies was utilized for the study. Five (5) management level employees were surveyed in each selected firm giving a total of one hundred and fifty (150) respondents. Data collected were analyzed and research hypotheses tested using Chi-Square test statistic. Research results showed that corporate governance mechanisms were better and have significantly improved overtime in privately held as opposed to publicly owned firms. Consequently, the levels of innovation in privately held firms were considerably higher. It was concluded that a significant and positive relationship exists between private ownership and good corporate governance on one hand and the level of funding provided for innovative activities in Mongolian firms on the other hand.

Keywords: Corporate governance, innovation, ownership structure, stock exchange.

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Authors: Nebu Tom John, N. Dhinakaran

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Multiparty voice over IP (MVoIP) systems allows a group of people to freely communicate each other via the internet, which have many applications such as online gaming, teleconferencing, online stock trading etc. Peertalk is a peer to peer multiparty voice over IP system (MVoIP) which is more feasible than existing approaches such as p2p overlay multicast and coupled distributed processing. Since the stream mixing and distribution are done by the peers, it is vulnerable to major security threats like nodes misbehavior, eavesdropping, Sybil attacks, Denial of Service (DoS), call tampering, Man in the Middle attacks etc. To thwart the security threats, a security framework called PEERTS (PEEred Reputed Trustworthy System for peertalk) is implemented so that efficient and secure communication can be carried out between peers.

Keywords: Key management system, peer-to-peer voice streaming, reputed trust management system, voice-over-IP.

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Authors: Bita Mashayekhi, Zeynab Lotfi Aghel

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The determinants of Earnings Response Coefficient (ERC), including firm size, earnings growth, and earnings persistence are studied in this research. These determinants are supposed to be moderator variables that affect ERC and Return Response Coefficient. The research sample contains 82 Iranian listed companies in Tehran Stock Exchange (TSE) from 2001 to 2012. Gathered data have been processed by EVIEWS Software. Results show a significant positive relation between firm size and ERC, and also between earnings growth and ERC; however, there is no significant relation between earnings persistence and ERC. Also, the results show that ERC will be increased by firm size and earnings growth, but there is no relation between earnings persistence and ERC.

Keywords: Earnings response coefficient, return response coefficient, firm size, earnings growth, earnings persistence.

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Authors: Maria Damian, Carmen G. Bonaci, Jiří Strouhal, Razvan V. Mustata, Dumitru Matis, Jiřina Bokšová

Abstract:

In the current context of globalization, a large number of companies sought to develop as a group in order to reach to other markets or meet the necessary criteria for listing on a stock exchange. The issue of consolidated financial statements prepared by a parent, an investor or a venture and the financial reporting standards guiding them therefore becomes even more important. The aim of our paper is to expose this issue in a consistent manner, first by summarizing the international accounting and financial reporting standards applicable before the 1st of January 2013 and considering the role of the crisis in shaping the standard setting process, and secondly by analyzing the newly issued/modified standards and main changes being brought

Keywords: Consolidated financial statements, control, IFRS 10, financial crisis.

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Authors: M. Pervan, I. Pervan, M. Todoric

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Using data of listed Croatian firms from the Zagreb Stock Exchange we analyze the relationship between firm ownership (ownership concentration and type) and performance (ROA). Empirical research was conducted for the period 2003-2010, yielding with the total of 1,430 observations. Empirical findings based on dynamic panel analysis indicate that ownership concentration variable - CR4 is negatively related with performance, i.e. listed firms with dispersed ownership perform better than firms with concentrated ownership. Also, the research indicated that foreign controlled listed firms perform better than domestically controlled firms. Majority state owned firms perform worse than privately held firms but dummy variable for privately controlled firms was not statistically significant in the estimated panel model.

Keywords: Croatia, firm, ownership, performance

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Authors: H. Benjamin Fredrick David, R. Balasubramanian, A. Anbarasa Pandian

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Image retrieval is the most interesting technique which is being used today in our digital world. CBIR, commonly expanded as Content Based Image Retrieval is an image processing technique which identifies the relevant images and retrieves them based on the patterns that are extracted from the digital images. In this paper, two research works have been presented using CBIR. The first work provides an automated and interactive approach to the analysis of CBIR techniques. CBIR works on the principle of supervised machine learning which involves feature selection followed by training and testing phase applied on a classifier in order to perform prediction. By using feature extraction, the image transforms such as Contourlet, Ridgelet and Shearlet could be utilized to retrieve the texture features from the images. The features extracted are used to train and build a classifier using the classification algorithms such as Naïve Bayes, K-Nearest Neighbour and Multi-class Support Vector Machine. Further the testing phase involves prediction which predicts the new input image using the trained classifier and label them from one of the four classes namely 1- Normal brain, 2- Benign tumour, 3- Malignant tumour and 4- Severe tumour. The second research work includes developing a tool which is used for tumour stage identification using the best feature extraction and classifier identified from the first work. Finally, the tool will be used to predict tumour stage and provide suggestions based on the stage of tumour identified by the system. This paper presents these two approaches which is a contribution to the medical field for giving better retrieval performance and for tumour stages identification.

Keywords: Brain tumour detection, content based image retrieval, classification of tumours, image retrieval.

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Authors: Vipul M. Patel, Hemantkumar B. Mehta

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Technological innovations in electronic world demand novel, compact, simple in design, less costly and effective heat transfer devices. Closed Loop Pulsating Heat Pipe (CLPHP) is a passive phase change heat transfer device and has potential to transfer heat quickly and efficiently from source to sink. Thermal performance of a CLPHP is governed by various parameters such as number of U-turns, orientations, input heat, working fluids and filling ratio. The present paper is an attempt to predict the thermal performance of a CLPHP using Artificial Neural Network (ANN). Filling ratio and heat input are considered as input parameters while thermal resistance is set as target parameter. Types of neural networks considered in the present paper are radial basis, generalized regression, linear layer, cascade forward back propagation, feed forward back propagation; feed forward distributed time delay, layer recurrent and Elman back propagation. Linear, logistic sigmoid, tangent sigmoid and Radial Basis Gaussian Function are used as transfer functions. Prediction accuracy is measured based on the experimental data reported by the researchers in open literature as a function of Mean Absolute Relative Deviation (MARD). The prediction of a generalized regression ANN model with spread constant of 4.8 is found in agreement with the experimental data for MARD in the range of ±1.81%.

Keywords: ANN models, CLPHP, filling ratio, generalized regression, spread constant.

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Authors: Sotirios Raptis

Abstract:

Health and Social care (HSc) services planning and scheduling are facing unprecedented challenges, due to the pandemic pressure and also suffer from unplanned spending that is negatively impacted by the global financial crisis. Data-driven approaches can help to improve policies, plan and design services provision schedules using algorithms that assist healthcare managers to face unexpected demands using fewer resources. The paper discusses services packing using statistical significance tests and machine learning (ML) to evaluate demands similarity and coupling. This is achieved by predicting the range of the demand (class) using ML methods such as Classification and Regression Trees (CART), Random Forests (RF), and Logistic Regression (LGR). The significance tests Chi-Squared and Student’s test are used on data over a 39 years span for which data exist for services delivered in Scotland. The demands are associated using probabilities and are parts of statistical hypotheses. These hypotheses, as their NULL part, assume that the target demand is statistically dependent on other services’ demands. This linking is checked using the data. In addition, ML methods are used to linearly predict the above target demands from the statistically found associations and extend the linear dependence of the target’s demand to independent demands forming, thus, groups of services. Statistical tests confirmed ML coupling and made the prediction statistically meaningful and proved that a target service can be matched reliably to other services while ML showed that such marked relationships can also be linear ones. Zero padding was used for missing years records and illustrated better such relationships both for limited years and for the entire span offering long-term data visualizations while limited years periods explained how well patients numbers can be related in short periods of time or that they can change over time as opposed to behaviours across more years. The prediction performance of the associations were measured using metrics such as Receiver Operating Characteristic (ROC), Area Under Curve (AUC) and Accuracy (ACC) as well as the statistical tests Chi-Squared and Student. Co-plots and comparison tables for the RF, CART, and LGR methods as well as the p-value from tests and Information Exchange (IE/MIE) measures are provided showing the relative performance of ML methods and of the statistical tests as well as the behaviour using different learning ratios. The impact of k-neighbours classification (k-NN), Cross-Correlation (CC) and C-Means (CM) first groupings was also studied over limited years and for the entire span. It was found that CART was generally behind RF and LGR but in some interesting cases, LGR reached an AUC = 0 falling below CART, while the ACC was as high as 0.912 showing that ML methods can be confused by zero-padding or by data’s irregularities or by the outliers. On average, 3 linear predictors were sufficient, LGR was found competing well RF and CART followed with the same performance at higher learning ratios. Services were packed only when a significance level (p-value) of their association coefficient was more than 0.05. Social factors relationships were observed between home care services and treatment of old people, low birth weights, alcoholism, drug abuse, and emergency admissions. The work found  that different HSc services can be well packed as plans of limited duration, across various services sectors, learning configurations, as confirmed by using statistical hypotheses.

Keywords: Class, cohorts, data frames, grouping, prediction, probabilities, services.

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Authors: S. Madhavi, S. Abirami, C. Bharathi, B. Ekambaram, T. Krishna Sankar, A. Nattudurai, N. Vijayarangan

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The high utilization rate of Automated Teller Machine (ATM) has inevitably caused the phenomena of waiting for a long time in the queue. This in turn has increased the out of stock situations. The ATM utilization helps to determine the usage level and states the necessity of the ATM based on the utilization of the ATM system. The time in which the ATM used more frequently (peak time) and based on the predicted solution the necessary actions are taken by the bank management. The analysis can be done by using the concept of Data Mining and the major part are analyzed based on the predictive data mining. The results are predicted from the historical data (past data) and track the relevant solution which is required. Weka tool is used for the analysis of data based on predictive data mining.

Keywords: ATM, Bank Management, Data Mining, Historical data, Predictive Data Mining, Weka tool.

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Authors: Soumiya Bhattacharjee, P. K. Champati Ray, Shovan L. Chattoraj, Mrinmoy Dhara

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The entire Himalayan range is globally renowned for rainfall-induced landslides. The prime focus of the study is to determine rainfall based threshold for initiation of landslides that can be used as an important component of an early warning system for alerting stake holders. This research deals with temporal dimension of slope failures due to extreme rainfall events along the National Highway-58 from Karanprayag to Badrinath in the Garhwal Himalaya, India. Post processed 3-hourly rainfall intensity data and its corresponding duration from daily rainfall data available from Tropical Rainfall Measuring Mission (TRMM) were used as the prime source of rainfall data. Landslide event records from Border Road Organization (BRO) and some ancillary landslide inventory data for 2013 and 2014 have been used to determine Intensity Duration (ID) based rainfall threshold. The derived governing threshold equation, I= 4.738D^-0.025, has been considered for prediction of landslides of the study region. This equation was validated with an accuracy of 70% landslides during August and September 2014. The derived equation was considered for further prediction of landslides of the study region. From the obtained results and validation, it can be inferred that this equation can be used for initiation of landslides in the study area to work as a part of an early warning system. Results can significantly improve with ground based rainfall estimates and better database on landslide records. Thus, the study has demonstrated a very low cost method to get first-hand information on possibility of impending landslide in any region, thereby providing alert and better preparedness for landslide disaster mitigation.

Keywords: Landslide, intensity-duration, rainfall threshold, Tropical Rainfall Measuring Mission, slope, inventory, early warning system.

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Authors: S. Farzi

Abstract:

Recently, a lot of attention has been devoted to advanced techniques of system modeling. PNN(polynomial neural network) is a GMDH-type algorithm (Group Method of Data Handling) which is one of the useful method for modeling nonlinear systems but PNN performance depends strongly on the number of input variables and the order of polynomial which are determined by trial and error. In this paper, we introduce GPNN (genetic polynomial neural network) to improve the performance of PNN. GPNN determines the number of input variables and the order of all neurons with GA (genetic algorithm). We use GA to search between all possible values for the number of input variables and the order of polynomial. GPNN performance is obtained by two nonlinear systems. the quadratic equation and the time series Dow Jones stock index are two case studies for obtaining the GPNN performance.

Keywords: GMDH, GPNN, GA, PNN.

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Authors: Chongyang Ye, Rong Liu

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Elastic compression stockings (ECSs) have been widely applied in prophylaxis and treatment of chronic venous insufficiency of lower extremities. The medical function of ECS is to improve venous return and increase muscular pumping action to facilitate blood circulation, which is largely determined by the complex interaction between the ECS and lower limb tissues. Understanding the mechanical transmission of ECS along the skin surface, deeper tissues, and vascular system is essential to assess the effectiveness of the ECSs. In this study, a three-dimensional (3D) finite element (FE) model of the leg-ECS system integrated with a 3D fluid-solid interaction (FSI) model of the leg-vein system was constructed to analyze the biomechanical properties of veins and soft tissues under different ECS compression. The Magnetic Resonance Imaging (MRI) of the human leg was divided into three regions, including soft tissues, bones (tibia and fibula) and veins (peroneal vein, great saphenous vein, and small saphenous vein). The ECSs with pressure ranges from 15 to 26 mmHg (Classes I and II) were adopted in the developed FE-FSI model. The soft tissue was assumed as a Neo-Hookean hyperelastic model with the fixed bones, and the ECSs were regarded as an orthotropic elastic shell. The interfacial pressure and stress transmission were simulated by the FE model, and venous hemodynamics properties were simulated by the FSI model. The experimental validation indicated that the simulated interfacial pressure distributions were in accordance with the pressure measurement results. The developed model can be used to predict interfacial pressure, stress transmission, and venous hemodynamics exerted by ECSs and optimize the structure and materials properties of ECSs design, thus improving the efficiency of compression therapy.

Keywords: Elastic compression stockings, fluid-solid interaction, tissue and vein properties, prediction.

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Authors: Mansoor Momeni, Mahmoud Dehghan Nayeri, Ali Faal Ghayoumi, Hoda Ghorbani

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This research is aimed to describe the application of robust regression and its advantages over the least square regression method in analyzing financial data. To do this, relationship between earning per share, book value of equity per share and share price as price model and earning per share, annual change of earning per share and return of stock as return model is discussed using both robust and least square regressions, and finally the outcomes are compared. Comparing the results from the robust regression and the least square regression shows that the former can provide the possibility of a better and more realistic analysis owing to eliminating or reducing the contribution of outliers and influential data. Therefore, robust regression is recommended for getting more precise results in financial data analysis.

Keywords: Financial data analysis, Influential data, Outliers, Robust regression.

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Authors: Sahar Modirzadehbami, Gholamreza Mansourfar

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Different types of Islamic debts have been increasingly utilized as preferred means of debt funding by Malaysian private firms in recent years. This study examines the impact of Islamic debts announcement on private firms- stock returns. Our sample includes forty five listed companies on Bursa Malaysia involved in issuing of Islamic debts during 2005 to 2008. The abnormal returns and cumulative average abnormal returns are calculated and tested using standard event study methodology. The results show that a significant, negative abnormal return occurs one day before announcement date. This negative abnormal return is representing market participant-s adverse attitude toward Islamic private debt announcement during the research period.

Keywords: Announcement effect, Event study, Islamic debts, Malaysia, Sukuk

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Authors: Jianfeng Li, Feng Jin, Xiaoyu Yang

Abstract:

This paper applies fuzzy clustering algorithm in classifying real estate companies in China according to some general financial indexes, such as income per share, share accumulation fund, net profit margins, weighted net assets yield and shareholders' equity. By constructing and normalizing initial partition matrix, getting fuzzy similar matrix with Minkowski metric and gaining the transitive closure, the dynamic fuzzy clustering analysis for real estate companies is shown clearly that different clustered result change gradually with the threshold reducing, and then, it-s shown there is the similar relationship with the prices of those companies in stock market. In this way, it-s great valuable in contrasting the real estate companies- financial condition in order to grasp some good chances of investment, and so on.

Keywords: Fuzzy clustering algorithm, data mining, real estate company, financial analysis.

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Authors: César Camisón-Zornoza, Beatriz Forés-Julián, Alba Puig-Denia

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The literature has argued that firms based in industrial districts enjoy advantages for creating internal knowledge and absorbing external knowledge as a consequence of to the knowledge flows and spillovers that exist in the district. However, empirical evidence to show how belonging to an industrial district affects the business processes of creation and absorption of knowledge is scarce and, moreover, empirical research has not taken into account the influence of variations in the flows of knowledge circulating in each cluster. This study aims to extend empirical evidence on the effect that the stock of shared competencies in industrial districts has on the business processes of creation and absorption of knowledge, through data from an initial study on 952 firms and 35 industrial districts in Spain.

Keywords: Absorptive capacity, industrial district, knowledge creation, organisational learning

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Authors: Zoran D. Banjac, Branko D. Kovacevic

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The problem of FIR system parameter estimation has been considered in the paper. A new robust recursive algorithm for simultaneously estimation of parameters and scale factor of prediction residuals in non-stationary environment corrupted by impulsive noise has been proposed. The performance of derived algorithm has been tested by simulations.

Keywords: Adaptive filtering, Non-Gaussian filtering, Robustestimation, Scale factor estimation.

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Authors: E. Murányi, P. Pepó

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The small plot experiment was set in 2013 at the RISFLátókép Experimental Farm of the Centre for Agricultural and Applied Economic Sciences of the University of Debrecen, on lime-coated chernozem soil in four replications. The final heights of the maize hybrids were studied at three plant densities (50, 70, and 90 thousand ha^-1) and two row spacing (45 and 76cm). During the experiment, we have investigated the development of the final plant heights of five maize hybrids of different vegetation time and genotype: Sarolta, DKC 4025, P 9175, Reseda/P 37M81, and SY Affinity. In the development of the plant heights, the tiller number and the hybrid were the decisive factors. The increasing stock density resulted in significant difference in the plant height values, while the row spacing did not. With the increase of plant density and the length of vegetation time, the heights of the individual plants increased.

Keywords: Maize, plant density, row spacing, plant height, genotype.

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Authors: Jovana Dj. Jovanovic, Svetlana M. Stevovic

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The highest priority of so called, projected passive houses is to meet the appropriate energy demand. Every single material and layer which is injected into a dwelling has a certain energy quantity stored. The passive houses include optimized insulation levels with minimal thermal bridges, minimum of air leakage through the building, utilization of passive solar and internal gains, and good circulation of air which leans on mechanical ventilation system. The focus of this paper is on passive house features, benefits and targets, their feasibility and energy demands which are set up during each project. Numerous passive house-standards outline the very significant role of zero-energy dwellings towards the modern label of sustainable development. It is clear that the performance of both built and existing housing stock must be addressed if the population across the world sets out the energy objectives. This scientific article examines passive house features since the many passive house cases are launched.

Keywords: Benefits, energy demands, passive houses, sustainable development.

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Authors: Oghenerukome Akponovo, Lynda I. Onyebuchukwu

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Construction waste, along with that of many other industries, contributes significantly to the world's annual solid waste totals. Most of these materials, such as ash from rice hulls, slags, cement kiln dust, tire ash, plastic waste (PW), and silica fumes, end up in landfills or waterways. Some of them might even end up polluting the air from high in the atmosphere. It is sustainable, cheap, and environmentally friendly to recycle these items into new building supplies. When constructing a "green" structure, the materials employed have the potential to either exacerbate environmental imbalance or maintain a stable ecosystem. The purpose of this research is to take stock of what is already known about recycling's potential in the construction industry and to identify its deficiencies. Therefore, this study systematically reviews the wide range of recycled materials that go into building construction. In the construction industry, the utilization of recycled materials plays a significant role in environmental conservation, and a thorough investigation into these materials could potentially yield substantial economic benefits if appropriately harnessed.

Keywords: Paper waste, rice grain husks, recycled materials, waste management.

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Authors: Haksoon Kim

Abstract:

The paper investigates the relationship between the foreign direct investment (FDI) and the corporate governance or transparency by investigating the country-level FDI flows, FDI inward performance, corporate governance and transparency variables. From the regression analysis with Newey-West estimator of 28 country panel data from 1990- 2002, we find strong positive relationships between corporate governance or transparency level of hosting countries and FDI inward performance within hosting countries. A strong positive relationship is found between anti-director rights level or number of analysts of hosting countries and FDI inward performance within hosting countries. Also, we find a positive relationship between the number of analysts of hosting countries and FDI inflows. The empirical results are consistent with stock market liberalizations and corporate governance explanations of reasons for FDI.

Keywords: corporate governance, corporate transparency, FDIflows, FDI inward performance

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Authors: D. Cardone

Abstract:

Past earthquakes have shown that seismic events may incur large economic losses in buildings. FEMA P-58 provides engineers a practical tool for the performance seismic assessment of buildings. In this study, FEMA P-58 is applied to two typical Italian pre-1970 reinforced concrete frame buildings, characterized by plain rebars as steel reinforcement and masonry infills and partitions. Given that suitable tools for these buildings are missing in FEMA P- 58, specific fragility curves and loss functions are first developed. Next, building performance is evaluated following a time-based assessment approach. Finally, expected annual losses for the selected buildings are derived and compared with past applications to old RC frame buildings representative of the US building stock. 

Keywords: FEMA P-58, RC frame buildings, plain rebars, masonry infills, fragility functions, loss functions, expected annual loss.

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Authors: Reeta Devi, Hitender Kumar Tyagi, Dinesh Kumar

Abstract:

In present scenario, cardiovascular problems are growing challenge for researchers and physiologists. As heart disease have no geographic, gender or socioeconomic specific reasons; detecting cardiac irregularities at early stage followed by quick and correct treatment is very important. Electrocardiogram is the finest tool for continuous monitoring of heart activity. Heart rate variability (HRV) is used to measure naturally occurring oscillations between consecutive cardiac cycles. Analysis of this variability is carried out using time domain, frequency domain and non-linear parameters. This paper presents HRV analysis of the online dataset for normal sinus rhythm (taken as healthy subject) and sudden cardiac death (SCD subject) using all three methods computing values for parameters like standard deviation of node to node intervals (SDNN), square root of mean of the sequences of difference between adjacent RR intervals (RMSSD), mean of R to R intervals (mean RR) in time domain, very low-frequency (VLF), low-frequency (LF), high frequency (HF) and ratio of low to high frequency (LF/HF ratio) in frequency domain and Poincare plot for non linear analysis. To differentiate HRV of healthy subject from subject died with SCD, k –nearest neighbor (k-NN) classifier has been used because of its high accuracy. Results show highly reduced values for all stated parameters for SCD subjects as compared to healthy ones. As the dataset used for SCD patients is recording of their ECG signal one hour prior to their death, it is therefore, verified with an accuracy of 95% that proposed algorithm can identify mortality risk of a patient one hour before its death. The identification of a patient’s mortality risk at such an early stage may prevent him/her meeting sudden death if in-time and right treatment is given by the doctor.

Keywords: Early stage prediction, heart rate variability, linear and non linear analysis, sudden cardiac death.

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Authors: Yu Zhou, Zhaoyang Dong, Xiaomei Zhao

Abstract:

This paper mainly investigates the environmental and economic impacts of worldwide use of electric vehicles. It can be concluded that governments have good reason to promote the use of electric vehicles. First, the global vehicles population is evaluated with the help of grey forecasting model and the amount of oil saving is estimated through approximate calculation. After that, based on the game theory, the amount and types of electricity generation needed by electronic vehicles are established. Finally, some conclusions on the government-s attitudes are drawn.

Keywords: electronic vehicles, grey prediction, game theory

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