Search results for: recognition primed decision

Authors: Elena Kokkoni, Prasanna Kannappan, Ashkan Zehfroosh, Effrosyni Mavroudi, Kristina Strother-Garcia, James C. Galloway, Jeffrey Heinz, Rene Vidal, Herbert G. Tanner

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Early immobility affects the motor, cognitive, and social development. Current pediatric rehabilitation lacks the technology that will provide the dosage needed to promote mobility for young children at risk. The addition of socially assistive robots in early interventions may help increase the mobility dosage. The aim of this study is to examine the feasibility of an early intervention paradigm where non-walking infants experience independent mobility while socially interacting with robots. A dynamic environment is developed where both the child and the robot interact and learn from each other. The environment involves: 1) a range of physical activities that are goal-oriented, age-appropriate, and ability-matched for the child to perform, 2) the automatic functions that perceive the child’s actions through novel activity recognition algorithms, and decide appropriate actions for the robot, and 3) a networked visual data acquisition system that enables real-time assessment and provides the means to connect child behavior with robot decision-making in real-time. The environment was tested by bringing a two-year old boy with Down syndrome for eight sessions. The child presented delays throughout his motor development with the current being on the acquisition of walking. During the sessions, the child performed physical activities that required complex motor actions (e.g. climbing an inclined platform and/or staircase). During these activities, a (wheeled or humanoid) robot was either performing the action or was at its end point 'signaling' for interaction. From these sessions, information was gathered to develop algorithms to automate the perception of activities which the robot bases its actions on. A Markov Decision Process (MDP) is used to model the intentions of the child. A 'smoothing' technique is used to help identify the model’s parameters which are a critical step when dealing with small data sets such in this paradigm. The child engaged in all activities and socially interacted with the robot across sessions. With time, the child’s mobility was increased, and the frequency and duration of complex and independent motor actions were also increased (e.g. taking independent steps). Simulation results on the combination of the MDP and smoothing support the use of this model in human-robot interaction. Smoothing facilitates learning MDP parameters from small data sets. This paradigm is feasible and provides an insight on how social interaction may elicit mobility actions suggesting a new early intervention paradigm for very young children with motor disabilities. Acknowledgment: This work has been supported by NIH under grant #5R01HD87133.

Keywords: activity recognition, human-robot interaction, machine learning, pediatric rehabilitation

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Authors: Ming-Yen Chang, Sheng-Hung Ke

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This research focuses on the development of a speed bump identification system for real-time control of adjustable shock absorbers in vehicular suspension systems. The study initially involved the collection of images of various speed bumps, and rubber speed bump profiles found on roadways. These images were utilized for training and recognition purposes through the deep learning object detection algorithm YOLOv5. Subsequently, the trained speed bump identification program was integrated with an in-vehicle camera system for live image capture during driving. These images were instantly transmitted to a computer for processing. Using the principles of monocular vision ranging, the distance between the vehicle and an approaching speed bump was determined. The appropriate control distance was established through both practical vehicle measurements and theoretical calculations. Collaboratively, with the electronically adjustable shock absorbers equipped in the vehicle, a shock absorber control system was devised to dynamically adapt the damping force just prior to encountering a speed bump. This system effectively mitigates passenger discomfort and enhances ride quality.

Keywords: adjustable shock absorbers, image recognition, monocular vision ranging, ride

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Authors: Dimitrios J. Dimitriou

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The decades after the end of the second War provide evidence that infrastructures investments contibute to economic development, on terms of productivity and income growth. In order to force productivity and increase competitiveness the financing of large transport infrastructure projects are on the top of the agenda in strategic planning process. Such a decision may take form some days to some decades and stakeholders as well as decision makers need tools in order to estimate the economic impact on natioanl economy of such an investment. The key question in such decisions is if the effects caused by the new infrastructure could be able to boost economic development on one hand, and create new jobs and activities on the other. This paper deals with the review of estimation of the mega transport infrastructure projects economic effects in economy.

Keywords: economic impact, transport infrastructure, strategic planning, decision making

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Authors: Khalid Bashir, Hammad Zahid

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Most of the investors consider that economic and financial information is the most important at the time of making investment decisions. But it is not true, as in the past two decades, the Behavioral aspects and the behavioral biases have gained an important place in the decision-making process of an investor. This study is basically conducted on this fact. The purpose of this study is to examine the impact of behavioral factors on the decision-making of the individual real estate investor in Pakistan. Some important behavioral factors like overconfidence, anchoring, gambler’s fallacy, home bias, loss aversion, regret aversion, mental accounting, herding and representativeness are used in this study to find their impact on the psychology of individual investors. The targeted population is the real estate investor of Pakistan, and a sample of 650 investors is selected on the basis of convenience sampling technique. The data is collected through the questionnaire with a response rate of 46.15 %. Descriptive statistical techniques and SEM are used to analyze the data by using statistical software. The results revealed the fact that some behavioral factors have a significant impact on the decision-making of investors. Among all the behavioral biases, overconfidence, anchoring, gambler’s fallacy, loss aversion and representativeness have a significant positive impact on the decision-making of the individual investor, while the rest of biases like home bias, regret aversion, mental accounting, herding have less impact on the decision-making process of an individual.

Keywords: behavioral finance, anchoring, gambler’s fallacy, loss aversion

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Authors: Abe Degale D., Cheng Jian

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When creating automated video surveillance systems, violent action recognition is crucial. In recent years, hand-crafted feature detectors have been the primary method for achieving violence detection, such as the recognition of fighting activity. Researchers have also looked into learning-based representational models. On benchmark datasets created especially for the detection of violent sequences in sports and movies, these methods produced good accuracy results. The Hockey dataset's videos with surveillance camera motion present challenges for these algorithms for learning discriminating features. Image recognition and human activity detection challenges have shown success with deep representation-based methods. For the purpose of detecting violent images and identifying aggressive human behaviours, this research suggested a deep representation-based model using the transfer learning idea. The results show that the suggested approach outperforms state-of-the-art accuracy levels by learning the most discriminating features, attaining 99.34% and 99.98% accuracy levels on the Hockey and Movies datasets, respectively.

Keywords: violence detection, faster RCNN, transfer learning and, surveillance video

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Authors: Pongsawee Supanonth

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This study aims to investigate the consumer behavior and marketing mixed factor affect on consumer decision making for independent movies presented in Lido cinema. The research method will use quantitative research, data was collected by questionnaires distributed to the audience in the Lido cinema for 400 sample by accidental sampling technique. Data was analyzed by descriptive statistic including percentage, mean, standard deviation and inferential statistic including independent t-test for hypothesis testing. The results showed that marketing mixed factors affecting consumer decision-making for Independent movies presented in Lido cinema by gender as different as less than the 0.05 significance level, it was found that the kind of movie ,quality of theater ,price of ticket, facility of watching movies, staff services and promotion of Lido cinema respectively had a vital influence on their attention and response which makes the advertisement more attractive is in harmony with the research hypotheses also.

Keywords: consumer behavior, marketing mixed factor, resonance, consumer decision making, Lido cinema

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Authors: Chen T. Chen, Hui L. Cheng

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Due to the different knowledge, experience and expertise of experts, they usually provide the different opinions in the group decision-making process. Therefore, it is an important issue to reach the group consensus of opinions of experts in group multiple-criteria decision-making (GMCDM) process. Because the subjective opinions of experts always are fuzziness and uncertainties, it is difficult to use crisp values to describe the real opinions of experts or decision-makers. It is reasonable for experts to use the linguistic variables to express their opinions. The hesitant fuzzy set are extended from the concept of fuzzy sets. Experts use the hesitant fuzzy sets can be flexible to describe their subjective opinions. In order to aggregate the hesitant fuzzy linguistic variables of all experts effectively, an adjustment method based on distance function will be presented in this paper. Based on the opinions adjustment method, this paper will present an effective approach to adjust the hesitant fuzzy linguistic variables of all experts to reach the group consensus. Then, a new hesitant linguistic GMCDM method will be presented based on the group consensus of hesitant fuzzy linguistic variables. Finally, an example will be implemented to illustrate the computational process to enhance the practical value of the proposed model.

Keywords: group multi-criteria decision-making, linguistic variables, hesitant fuzzy linguistic variables, distance function, group consensus

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Authors: Mohammadamin Abbasnejad

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The analysis of expression and facial Action Units (AUs) detection are very important tasks in fields of computer vision and Human Computer Interaction (HCI) due to the wide range of applications in human life. Many works have been done during the past few years which has their own advantages and disadvantages. In this work, we present a new model based on Gaussian Conditional Random Field. We solve our objective problem using ADMM and we show how well the proposed model works. We train and test our work on two facial expression datasets, CK+, and RU-FACS. Experimental evaluation shows that our proposed approach outperform state of the art expression recognition.

Keywords: Gaussian Conditional Random Field, ADMM, convergence, gradient descent

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Authors: Mohsen Akhlaghi, Tahereh Ebrahimi

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Considering the increasing demand for water and limited resources, there is a possibility of a water crisis in the not-so-distant future. Therefore, to prevent this crisis, other options for drinking water supply should be examined. In this regard, the application of multi-criteria decision-making methods in various aspects of water resource management and planning has always been of great interest to researchers. In this report, six options for supplying drinking water to Tehran City were considered. Then, experts' opinions were collected through matrices and questionnaires, and using the TOPSIS method, which is one of the types of multi-criteria decision-making methods, they were calculated and analyzed. In the TOPSIS method, the options were ranked by calculating their proximity to the ideal (Ci). The closer the numerical value of Ci is to one, the more desirable the option is. Based on this, the option with the optimization pattern of water consumption, with Ci = 0.9787, is the best option among the proposed options for supplying drinking water to Tehran City. The other options, in order of priority, are rainwater harvesting, wastewater reuse, increasing current water supply sources, desalination and its transfer, and transferring water from freshwater sources between basins. In conclusion, the findings of this study highlight the importance of exploring alternative drinking water supply options and utilizing multi-criteria decision-making approaches to address the potential water crisis.

Keywords: multi-criteria decision, sustainable development, topsis, water supply

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Authors: Tallataf Rasheed, Adnan Rashdi, Ahmad Naeem Akhtar

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The accurate spectrum sensing is a fundamental requirement of dynamic spectrum access for deployment of Cognitive Radio Network (CRN). To acheive this requirement a Reliability factors based Fuzzy Logic (RFL) Scheme for Spectrum Sensing has been proposed in this paper. Cognitive Radio User (CRU) predicts the presence or absence of Primary User (PU) using energy detector and calculates the Reliability factors which are SNR of sensing node, threshold of energy detector and decision difference of each node with other nodes in a cooperative spectrum sensing environment. Then the decision of energy detector is combined with Reliability factors of sensing node using Fuzzy Logic. These Reliability Factors used in RFL Scheme describes the reliability of decision made by a CRU to improve the local spectrum sensing. This Fuzzy combining scheme provides the accuracy of decision made by sensornode. The simulation results have shown that the proposed technique provide better PU detection probability than existing Spectrum Sensing Techniques.

Keywords: cognitive radio, spectrum sensing, energy detector, reliability factors, fuzzy logic

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Authors: Christina Adly, Meena Abdelmeseeh, Tamer Basha

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This paper proposes a system for hand movement recognition using multichannel surface EMG(sEMG) signals obtained from 40 subjects using 40 different exercises, which are available on the Ninapro(Non-Invasive Adaptive Prosthetics) database. First, we applied processing methods to the raw sEMG signals to convert them to their amplitudes. Second, we used deep learning methods to solve our problem by passing the preprocessed signals to Fully connected neural networks(FCNN) and recurrent neural networks(RNN) with Long Short Term Memory(LSTM). Using intrasubject evaluation, The accuracy using the FCNN is 72%, with a processing time for training around 76 minutes, and for RNN's accuracy is 79.9%, with 8 minutes and 22 seconds processing time. Third, we applied some postprocessing methods to improve the accuracy, like majority voting(MV) and Movement Error Rate(MER). The accuracy after applying MV is 75% and 86% for FCNN and RNN, respectively. The MER value has an inverse relationship with the prediction delay while varying the window length for measuring the MV. The different part uses the RNN with the intersubject evaluation. The experimental results showed that to get a good accuracy for testing with reasonable processing time, we should use around 20 subjects.

Keywords: hand movement recognition, recurrent neural network, movement error rate, intrasubject evaluation, intersubject evaluation

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Authors: Chen Xi, Liu Xuebing, Lao Xueru, Kuan Sinman, Jiang Yike, Wang Hanwei, Yang Xiaolang, Zhou Junjie, Xie Jinpeng

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To further promote the development of smart cities, the microscopic "nerve endings" of the City Intelligent Model (CIM) are extended to be more sensitive. In this paper, we develop a pedestrian trajectory twin terminal based on the CIM and CNN technology. It also uses 5G networks, architectural and geoinformatics technologies, convolutional neural networks, combined with deep learning networks for human behavior recognition models, to provide empirical data such as 'pedestrian flow data and human behavioral characteristics data', and ultimately form spatial performance evaluation criteria and spatial performance warning systems, to make the empirical data accurate and intelligent for prediction and decision making.

Keywords: urban planning, urban governance, CIM, artificial intelligence, sustainable development

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Authors: Wale Agbaje

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The aim of this research study is to assess the impact of financial statement fraud on profitability of some selected Nigerian manufacturing firms covering (2002-2016). The specific objectives focused on to ascertain the effect of incorrect asset valuation on return on assets (ROA) and to ascertain the relationship between improper expense recognition and return on assets (ROA). To achieve these objectives, descriptive research design was used for the study while secondary data were collected from the financial reports of the selected firms and website of security and exchange commission. The analysis of covariance (ANCOVA) was used and STATA II econometric method was used in the analysis of the data. Altman model and operating expenses ratio was adopted in the analysis of the financial reports to create a dummy variable for the selected firms from 2002-2016 and validation of the parameters were ascertained using various statistical techniques such as t-test, co-efficient of determination (R2), F-statistics and Wald chi-square. Two hypotheses were formulated and tested using the t-statistics at 5% level of significance. The findings of the analysis revealed that there is a significant relationship between financial statement fraud and profitability in Nigerian manufacturing industry. It was revealed that incorrect assets valuation has a significant positive relationship and so also is the improper expense recognition on return on assets (ROA) which serves as a proxy for profitability. The implication of this is that distortion of asset valuation and expense recognition leads to decreasing profit in the long run in the manufacturing industry. The study therefore recommended that pragmatic policy options need to be taken in the manufacturing industry to effectively manage incorrect asset valuation and improper expense recognition in order to enhance manufacturing industry performance in the country and also stemming of financial statement fraud should be adequately inculcated into the internal control system of manufacturing firms for the effective running of the manufacturing industry in Nigeria.

Keywords: Althman's Model, improper expense recognition, incorrect asset valuation, return on assets

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Authors: Chiara Mansanta, Daniela Sani

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This paper studies the concept of intrapreneurship discovery for innovation and technology development related to the manufacturing industries set up in the center of Italy, in Marche Region. The study underlined the key drivers of the innovation process and the main factors that influence innovation. Starting from a literature study on open innovation, this paper examines the role of human capital to support company’s development. The empirical part of the study is based on a survey to 151 manufacturing companies that represent the 34% of that universe at the regional level. The survey underlined the main KPI’s that influence companies in their decision processes; then tools for these decision processes are presented.

Keywords: business model, decision making, intrapreneurship discovery, standard methodology

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Authors: Hee-Choul Kwon, Hyungjin Cho, Heeyong Kwon

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Image rotation is one of main pre-processing step in image processing or image pattern recognition. It is implemented with rotation matrix multiplication. However it requires lots of floating point arithmetic operations and trigonometric function calculations, so it takes long execution time. We propose a new high speed image rotation algorithm without two major time-consuming operations. We compare the proposed algorithm with the conventional rotation one with various size images. Experimental results show that the proposed algorithm is superior to the conventional rotation ones.

Keywords: high speed rotation operation, image processing, image rotation, pattern recognition, transformation matrix

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Authors: S. da Costa, D. Páez, E. Martínez, A. Torres, M. Beramendi, D. Hermosilla, M. Muratori

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This study examined the association between creative performance, organizational climate and leadership, affectivity, shared flow, and group decision making. The sample consisted of 315 cadets of a military academic unit of South America. Satisfaction with the decision-making process during a creative task was associated with the usefulness and effectiveness of the ideas generated by the teams with a weighted average correlation of r = .18. Organizational emotional climate, positive and innovation leadership were associated with this group decision-making process r = .25, with shared flow, r = .29 and with positive affect felt during the performance of the creative task, r = .12. In a sequential mediational analysis positive organizational leadership styles were significantly associated with decision-making process and trough cohesion with utility and efficacy of the solution of a creative task. Satisfactory decision-making was related to shared flow during the creative task at collective or group level, and positive affect with flow at individual level.This study examined the association between creative performance, organizational climate and leadership, affectivity, shared flow, and group decision making. The sample consisted of 315 cadets of a military academic unit of South America. Satisfaction with the decision-making process during a creative task was associated with the usefulness and effectiveness of the ideas generated by the teams with a weighted average correlation of r = .18. Organizational emotional climate, positive and innovation leadership were associated with this group decision-making process r = .25, with shared flow, r = .29 and with positive affect felt during the performance of the creative task, r = .12. In a sequential mediational analysis positive organizational leadership styles were significantly associated with decision-making process and trough cohesion with utility and efficacy of the solution of a creative task. Satisfactory decision-making was related to shared flow during the creative task at collective or group level, and positive affect with flow at individual level.

Keywords: creativity, innovation, military, organization, teams

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Authors: Rasha A. Salameh

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This research attempts to evaluate the treatment provided by the Qatari media to the decision to allow Saudi women to drive, and then activate this decision after a few months, that is, within the time frame between September 26, 2017 until June 30, 2018. This is through asking several questions, including whether the political dispute between Qatar and Saudi Arabia has cast a shadow over this handling, and if these Qatari media handlings are used to criticize the Saudi regime for delaying this step. Here emerges one of the research hypotheses that says that the coverage did not have the required professionalism, due to the fact that the decision and its activation took place in light of the political stalemate between Qatar and the Kingdom of Saudi Arabia, which requires testing the media framing and agenda theories to know to what extent they apply to this case. The research dealt with a sample of five Qatari media read in this sample: Al-Jazeera Net, The New Arab Newspaper, Al-Sharq Newspaper, The Arab Newspaper, and Al-Watan Newspaper. The results showed that most of the authors who covered the decision to allow Saudi women to drive a car did not achieve a balance in their writing, and that almost half of them did not have objectivity, and this indicates the proof of the hypothesis that there is a defect in the professional competence in covering the decision to allow Saudi women to drive cars by means of Qatari media, and the researcher attributes this result to the political position between Qatar and Saudi Arabia, in addition to the fact that the Arab media in most of them are characterized by a low ceiling of freedom, and most of them are identical in their position with the position of the regime’s official view.

Keywords: Saudi women, objectivity, hate speech, stereotype

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Authors: I. Arockiarani

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The focus of the paper is to furnish the entropy measure for a neutrosophic set and neutrosophic soft set which is a measure of uncertainty and it permeates discourse and system. Various characterization of entropy measures are derived. Further we exemplify this concept by applying entropy in various real time decision making problems.

Keywords: entropy measure, Hausdorff distance, neutrosophic set, soft set

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Authors: Ivana Mokrá

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The article deals with modelling of the fire pragmatism in the area of military management and its experimental verification. Potential approaches are based on the synergy of mathematical and theoretical ideas, operational and tactical requirements and the military decision-making process. This issue has taken on importance in recent times, particularly with the increasing trend of digitized battlefield, the development of C4ISR systems and intention to streamline the command and control process at the lowest levels of command. From fundamental and philosophical point of view, these new approaches seek to significantly upgrade and enhance the decision-making process of the tactical commanders.

Keywords: military management, decision-making process, strike modeling, experimental evaluation, pragmatism, tactical strike modeling

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Authors: Achut Manandhar, Kenneth D. Morton, Peter A. Torrione, Leslie M. Collins

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The current trends in affect recognition research are to consider continuous observations from spontaneous natural interactions in people using multiple feature modalities, and to represent affect in terms of continuous dimensions, incorporate spatio-temporal correlation among affect dimensions, and provide fast affect predictions. These research efforts have been propelled by a growing effort to develop affect recognition system that can be implemented to enable seamless real-time human-computer interaction in a wide variety of applications. Motivated by these desired attributes of an affect recognition system, in this work a multi-dimensional affect prediction approach is proposed by integrating multivariate Relevance Vector Machine (MVRVM) with a recently developed Output-associative Relevance Vector Machine (OARVM) approach. The resulting approach can provide fast continuous affect predictions by jointly modeling the multiple affect dimensions and their correlations. Experiments on the RECOLA database show that the proposed approach performs competitively with the OARVM while providing faster predictions during testing.

Keywords: dimensional affect prediction, output-associative RVM, multivariate regression, fast testing

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Authors: Zhengyang Ma, Zhiyao Li, Jiayi Zhang

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This article examines the prospect theory’s arguments about decision-making through two case studies, the First Gulf War and Russia’s annexation of Crimea. The article uses the methods of comparative case analysis and process tracing to investigate the prospect theory’s fundamental arguments. Through evidence derived from existing primary and secondary sources, this paper argues that both former U.S. President Bush and Russian President Putin viewed their situations as a domain of loss and made risky decisions to prevent further deterioration, which attests the arguments of the prospect theory. After the two case studies, this article also discusses how the prospect theory could be used in analyzing the decision-making process that led to the current Russia-Ukraine War.

Keywords: the prospect theory, international relations, the first gulf war, the crimea crisis

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Authors: R. N. Begum, Ambalika Sharma, G. K. Singh

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Identity theft has serious ramifications beyond data and personal information loss. This necessitates the implementation of robust and efficient user identification systems. Therefore, automatic biometric recognition systems are the need of the hour, and ECG-based systems are unquestionably the best choice due to their appealing inherent characteristics. The CNNs are the recent state-of-the-art techniques for ECG-based user identification systems. However, the results obtained are significantly below standards, and the situation worsens as the number of users and types of heartbeats in the dataset grows. As a result, this study proposes a highly accurate and resilient ECG-based person identification system using CNN's dense learning framework. The proposed research explores explicitly the calibre of dense CNNs in the field of ECG-based human recognition. The study tests four different configurations of dense CNN which are trained on a dataset of recordings collected from eight popular ECG databases. With the highest FAR of 0.04 percent and the highest FRR of 5%, the best performing network achieved an identification accuracy of 99.94 percent. The best network is also tested with various train/test split ratios. The findings show that DenseNets are not only extremely reliable but also highly efficient. Thus, they might also be implemented in real-time ECG-based human recognition systems.

Keywords: Biometrics, Dense Networks, Identification Rate, Train/Test split ratio

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Authors: Burak Erkayman, Emin Gundogar, Hayrettin Evirgen, Murat Sarı

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With the increasing competition in recent years, airline companies tend to manage their operations aiming fewer losses in a robust manner. Airline operations are complex operations and have the necessity of being performed just in time and more knock-on relevant elements in the event of a disruption. In this study a knowledge based decision support system is suggested and software is developed. The developed software includes knowledge bases which are based on expert experience and government regulations, model bases and data bases. The results of the suggested approach are presented and improvable aspects of the approach are discussed.

Keywords: knowledge based systems, irregular operations, decision support systems, flight disruptions management

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Authors: Ufuk Cebeci, Onur Doğan

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New product becomes critical in competitive environment shortening a product's lifecycle due to the rapidly changing technology and increasing consumer requirements. Quality Function Deployment is one of the first steps of NPD process. The study presents an intelligent QFD application in metal plating industry. For application, an intelligent decision support system was developed. By intelligent system, house of quality was drawn and some calculations were shown. According to the results, some recommendations are given to end user. One of the purposes of this system is to give some advices to firms which do not know technical details of QFD and guide them about first steps of the new product development process.

Keywords: intelligent decision support systems, metal plating, quality function deployment, QFD software, new product development

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Authors: Tania Viju, Bimal P., Naseer M. A.

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This study aims to develop a conceptual framework for the decision support system (DSS), that helps the decision-makers to dynamically choose appropriate safety measures for each identified accident blackspot. An accident blackspot is a segment of road where the frequency of accident occurrence is disproportionately greater than other sections on roadways. According to a report by the World Bank, India accounts for the highest, that is, eleven percent of the global death in road accidents with just one percent of the world’s vehicles. Hence in 2015, the Ministry of Road Transport and Highways of India gave prime importance to the rectification of accident blackspots. To enhance road traffic safety and reduce the traffic accident rate, effectively identifying and rectifying accident blackspots is of great importance. This study helps to understand and evaluate the existing methods in accident blackspot identification and prediction that are used around the world and their application in Indian roadways. The decision support system, with the help of IoT, ICT and smart systems, acts as a management and planning tool for the government for employing efficient and cost-effective rectification strategies. In order to develop a decision criterion, several factors in terms of quantitative as well as qualitative data that influence the safety conditions of the road are analyzed. Factors include past accident severity data, occurrence time, light, weather and road conditions, visibility, driver conditions, junction type, land use, road markings and signs, road geometry, etc. The framework conceptualizes decision-making by classifying blackspot stretches based on factors like accident occurrence time, different climatic and road conditions and suggesting mitigation measures based on these identified factors. The decision support system will help the public administration dynamically manage and plan the necessary safety interventions required to enhance the safety of the road network.

Keywords: decision support system, dynamic management, road accident blackspots, road safety

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Authors: H. Gonzalez-Rivera, J. L. Palmeros-Torres

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This paper describes the application of traditional computer vision techniques as a procedure for automatic measurement of the secondary dendrite arm spacing (SDAS) from microscopic images. The algorithm is capable of finding the lineal or curve-shaped secondary column of the main microstructure, measuring its length size in a micro-meter and counting the number of spaces between dendrites. The automatic characterization was compared with a set of 1728 manually characterized images, leading to an accuracy of −0.27 µm for the length size determination and a precision of ± 2.78 counts for dendrite spacing counting, also reducing the characterization time from 7 hours to 2 minutes.

Keywords: dendrite arm spacing, microstructure inspection, pattern recognition, polynomial regression

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Authors: Laura Victoria Vigoya Morales, David Rolando Suarez Mora

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The problem of detecting enterococcus faecalis is receiving considerable attention with the new cases of beachgoers infected with the bacteria, which can be found in fecal matter. The process detection of this kind of bacteria would be taking a long time, which waste time and money as a result of closing recreation place, like beach or pools. Hence, new methods for automating the process of detecting and recognition of this bacteria has become in a challenge. This article describes a novel approach to detect the enterococcus faecalis bacteria in water by using an octave algorithm, which embody a network neural. This document shows result of performance, quality and integrity of the algorithm.

Keywords: Enterococcus faecalis, image treatment, octave and network neuronal

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Authors: Marina Tsetseli, Eleni Zetou, Maria Michalopoulou, Nikos Vernadakis

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Game performance, besides the accuracy and the quality skills execution, depends heavily on where the athletes will focus their attention while performing a skill. The purpose of the present study was to examine and compare the effect of internal and external focus of attention instructions on the decision making in tennis at players 8-9 years old (M=8.4, SD=0.49). The participants (N=40) were divided into two groups and followed an intervention training program that lasted 4 weeks; first group (N=20) under internal focus of attention instructions and the second group (N=20) under external focus of attention instructions. Three measurements took place (pre-test, post-test, and retention test) in which the participants were video recorded while playing matches in real scoring conditions. GPAI (Game Performance Assessment Instrument) was used to evaluate decision making in three game situations; service, return of the service, baseline game. ANOVA repeated measures (2 groups x 3 measurements) revealed a significant interaction between groups and measurements. Specifically, the data analysis showed superiority of the group that was instructed to focus externally. The high scores of the external attention group were maintained at the same level at the third measurement as well, which indicates that the impact was concerning not only performance but also learning. Thus, cues that lead to an external focus of attention enhance the decision-making skill and therefore the game performance of the young tennis players.

Keywords: decision making, evaluation, focus of attention, game performance, tennis

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Authors: Aparna Gulhane

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Biometrics is the science and technology of measuring and analyzing biological data form the basis of research in biological measuring techniques for the purpose of people identification and recognition. In information technology, biometrics refers to technologies that measure and analyze human body characteristics, such as DNA, fingerprints, eye retinas and irises, voice patterns, facial patterns and hand measurements. Biometric systems are used to authenticate the person's identity. The idea is to use the special characteristics of a person to identify him. These papers present a biometric authentication techniques and actual deployment of potential by overall invocation of biometrics recognition, with an independent testing of various biometric authentication products and technology.

Keywords: types of biometrics, importance of biometric, review for biometrics and getting a new implementation, biometric authentication technique

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Authors: Nugzar Todua

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The paper studies the role of food labeling in order to promote healthy eating issue in Georgia. The main focus of the research is directed to consumer attitudes regarding food labeling. The methodology of the paper is based on the focus group work, as well as online and face to face surveys. The data analysis has been provided through ANOVA. The study proves that the impact of variables such as the interest, awareness, reliability, assurance and satisfaction of consumers' on buying decision, is statistically important. The study reveals that consumers’ perception regarding to food labeling is positive, but their level of knowledge and ability is rather low. It is urgent to strengthen marketing promotions strategies in the process of implementations of food security policy in Georgia.

Keywords: food labeling, buying decision, Georgian consumers, marketing research

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