Search results for: data exchange

Authors: Dustin Schöder

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The potential benefits of the utilization of highly automated and autonomous trucks in logistics operations are the subject of interest to the entire logistics industry. The benefits of the use of these new technologies were scientifically investigated and implemented in roadmaps. So far, reliable data and experiences from real life use cases are still limited. A German research consortium of both academics and industry developed a highly automated (SAE level 4) vehicle for yard operations at railports and container depots. After development and testing, a several month field test at the DUSS Terminal in Ulm-Dornstadt (Germany) and the nearby DB Intermodal Services Container Depot in Ulm-Dornstadt was conducted. The truck was piloted in a shuttle service between both sites. In a holistic automation approach, the vehicle was integrated into a digital communication platform so that the truck could move autonomously without a driver and his manual interactions with a wide variety of stakeholders. The main goal is to investigate the effects of highly automated trucks in the key processes of container loading, unloading and container relocation on holistic railport yard operation. The field test data were used to investigate changes in process efficiency of key processes of railport and container yard operations. Moreover, effects on the capacity utilization and potentials for smothering peak workloads were analyzed. The results state that process efficiency in the piloted use case was significantly higher. The reason for that could be found in the digitalized data exchange and automated dispatch. However, the field test has shown that the effect is greatly varying depending on the ratio of highly automated and manual trucks in the yard as well as on the congestion level in the loading area. Furthermore, the data confirmed that under the right conditions, the capacity utilization of highly automated trucks could be increased. In regard to the potential for smothering peak workloads, no significant findings could be made based on the limited requirements and regulations of railway operation in Germany. In addition, an empirical survey among railport managers, operational supervisors, innovation managers and strategists (n=15) within the logistics industry in Germany was conducted. The goal was to identify key characteristics of future railports and terminals as well as requirements that railports will have to meet in the future. Furthermore, the railport processes where automation and autonomization make the greatest impact, as well as hurdles and challenges in the introduction of new technologies, have been surveyed. Hence, further potential use cases of highly automated and autonomous applications could be identified, and expectations have been mapped. As a result, a highly detailed and practice-based roadmap towards a ‘terminal 4.0’ was developed.

Keywords: highly automated driving, autonomous driving, SAE level 4, railport operations, container depot, intermodal logistics, potentials of autonomization

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Authors: Flavien Marteau, Pedro Affonso Nóbrega, Pascal Biwole, Nicolas Autrusson, Iona De Bievre, Christian Beauger

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Effective water management is essential for the optimal performance of fuel cells. For this reason, many vehicle systems use a membrane humidifier, a passive device that humidifies the air before the cathode inlet. Although they offer good performance, humidifiers are voluminous, costly, and fragile, hence the desire to find an alternative. Direct water injection could be an option, although this method lacks maturity. It consists of injecting liquid water as a spray in the dry heated air coming out from the compressor. This work focuses on the evaluation of direct water injection and its performance compared to the membrane humidifier selected as a reference. Two architectures were experimentally tested to humidify an industrial 2 kW short stack made up of 20 cells of 150 cm² each. For the reference architecture, the inlet air is humidified with a commercial membrane humidifier. For the direct water injection architecture, a pneumatic nozzle was selected to generate a fine spray in the air flow with a Sauter mean diameter of about 20 μm. Initial performance was compared over the entire range of current based on polarisation curves. Then, the influence of various parameters impacting water management was studied, such as the temperature, the gas stoichiometry, and the water injection flow rate. The experimental results obtained confirm the possibility of humidifying the fuel cell using direct water injection. This study, however shows the limits of this humidification method, the mean cell voltage being significantly lower in some operating conditions with direct water injection than with the membrane humidifier. The voltage drop reaches 30 mV per cell (4 %) at 1 A/cm² (1,8 bara, 80 °C) and increases in more demanding humidification conditions. It is noteworthy that the heat of compression available is not enough to evaporate all the injected liquid water in the case of DWI, resulting in a mix of liquid and vapour water entering the fuel cell, whereas only vapour is present with the humidifier. Variation of the injection flow rate shows that part of the injected water is useless for humidification and seems to cross channels without reaching the membrane. The stack was successfully humidified thanks to direct water injection. Nevertheless, our work shows that its implementation requires substantial adaptations and may reduce the fuel cell stack performance when compared to conventional membrane humidifiers, but opportunities for optimisation have been identified.

Keywords: cathode humidification, direct water injection, membrane humidifier, proton exchange membrane fuel cell

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Authors: F. Amin, S. Feizi

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Big data has the potential to improve the quality of services; enable infrastructure that businesses depend on to adapt continually and efficiently; improve the performance of employees; help organizations better understand customers; and reduce liability risks. Analytics and marketing models of fixed and mobile operators are falling short in combating churn and declining revenue per user. Big Data presents new method to reverse the way and improve profitability. The benefits of Big Data and next-generation network, however, are more exorbitant than improved customer relationship management. Next generation of networks are in a prime position to monetize rich supplies of customer information—while being mindful of legal and privacy issues. As data assets are transformed into new revenue streams will become integral to high performance.

Keywords: big data, next generation networks, network transformation, strategy

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Authors: John Kabuba

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The study investigated the implementation of the Neural Network (NN) techniques for prediction of the loading of Cu ions onto clinoptilolite. The experimental design using analysis of variance (ANOVA) was chosen for testing the adequacy of the Neural Network and for optimizing of the effective input parameters (pH, temperature and initial concentration). Feed forward, multi-layer perceptron (MLP) NN successfully tracked the non-linear behavior of the adsorption process versus the input parameters with mean squared error (MSE), correlation coefficient (R) and minimum squared error (MSRE) of 0.102, 0.998 and 0.004 respectively. The results showed that NN modeling techniques could effectively predict and simulate the highly complex system and non-linear process such as ion-exchange.

Keywords: clinoptilolite, loading, modeling, neural network

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Authors: Apkar Salatian

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To relieve the burden of reasoning on a point to point basis, in many domains there is a need to reduce large and noisy data sets into trends for qualitative reasoning. In this paper we propose and describe a new architectural design pattern called REDUCER for reducing large and noisy data sets that can be tailored for particular situations. REDUCER consists of 2 consecutive processes: Filter which takes the original data and removes outliers, inconsistencies or noise; and Compression which takes the filtered data and derives trends in the data. In this seminal article, we also show how REDUCER has successfully been applied to 3 different case studies.

Keywords: design pattern, filtering, compression, architectural design

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Authors: Ruth Diego, Luis M. Romeo, Antonio Morán

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In the present work, a study of the coupling of a Bioelectrochemical System together with an oxy-combustion boiler is carried out; specifically, it proposes to connect the combustion gas outlet of a boiler with a microbial electrolysis cell (MEC) where the CO2 from the gases are transformed into methane in the cathode chamber, and the oxygen produced in the anode chamber is recirculated to the oxy-combustion boiler. The MEC mainly consists of two electrodes (anode and cathode) immersed in an aqueous electrolyte; these electrodes are separated by a proton exchange membrane (PEM). In this case, the anode is abiotic (where oxygen is produced), and it is at the cathode that an electroactive biofilm is formed with microorganisms that catalyze the CO2 reduction reactions. Real data from an oxy-combustion process in a boiler of around 20 thermal MW have been used for this study and are combined with data obtained on a smaller scale (laboratory-pilot scale) to determine the yields that could be obtained considering the system as environmentally sustainable energy storage. In this way, an attempt is made to integrate a relatively conventional energy production system (oxy-combustion) with a biological system (microbial electrolysis cell), which is a challenge to be addressed in this type of new hybrid scheme. In this way, a novel concept is presented with the basic dimensioning of the necessary equipment and the efficiency of the global process. In this work, it has been calculated that the efficiency of this power-to-gas system based on MEC cells when coupled to industrial processes is of the same order of magnitude as the most promising equivalent routes. The proposed process has two main limitations, the overpotentials in the electrodes that penalize the overall efficiency and the need for storage tanks for the process gases. The results of the calculations carried out in this work show that certain real potentials achieve an acceptable performance. Regarding the tanks, with adequate dimensioning, it is possible to achieve complete autonomy. The proposed system called OxyMES provides energy storage without energetically penalizing the process when compared to an oxy-combustion plant with conventional CO2 capture. According to the results obtained, this system can be applied as a measure to decarbonize an industry, changing the original fuel of the oxy-combustion boiler to the biogas generated in the MEC cell. It could also be used to neutralize CO2 emissions from industry by converting it to methane and then injecting it into the natural gas grid.

Keywords: microbial electrolysis cells, oxy-combustion, co2, power-to-gas

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Authors: John Zanetich

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This paper uses a pragmatic research approach to investigate the relationships between Active Development of Tacit Knowledge (ADTK), social media (Facebook) and classroom learning communities. This paper investigates the use of learning communities and social media as the context and means for changing tacit knowledge to explicit and presents a dynamic model of the development of a classroom learning community. The goal of this study is to identify the point that explicit knowledge is converted to tacit knowledge and to test a way to quantify the exchange using social media and learning communities.

Keywords: tacit knowledge, knowledge management, college programs, experiential learning, learning communities

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Authors: Mario M. Figueroa de la Cruz, Claudia I. Solorzano, Raul Acosta, Ignacio Funes

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This technological development project seeks to create a tool that allows companies, in need of implementing a Data Center, intelligently determining factors for allocating resources support cooling and power supply (UPS) in its conception. The results should show clearly the speed, robustness and reliability of a system designed for deployment in environments where they must manage and protect large volumes of data.

Keywords: telecommunications, data center, fuzzy logic, expert systems

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Authors: S. Rodosik, J. P. Poirot-Crouvezier, Y. Bultel

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With the expansion of the hydrogen economy, Proton Exchange Membrane Fuel Cell (PEMFC) systems are often presented as promising energy converters suitable for transport applications. However, reaching a durability of 5000 h recommended by the U.S. Department of Energy and decreasing system cost are still major hurdles to their development. In order to increase the system efficiency and simplify the system without affecting the fuel cell lifetime, an architecture called alternative fuel feeding has been developed. It consists in a fuel cell stack divided into two parts, alternatively fed, implemented on a 5-kW system for real scale testing. The operation strategy can be considered close to Dead End Anode (DEA) with specific modifications to avoid water and nitrogen accumulation in the cells. The two half-stacks are connected in series to enable each stack to be alternatively fed. Water and nitrogen accumulated can be shifted from one half-stack to the other one according to the alternative feeding frequency. Thanks to the homogenization of water vapor along the stack, water management was improved. The operating conditions obtained at system scale are close to recirculation without the need of a pump or an ejector. In a first part, a performance comparison with the DEA strategy has been performed. At high temperature and low pressure (80°C, 1.2 bar), performance of alternative fuel feeding was higher, and the system efficiency increased. In a second part, in order to highlight the benefits of the architecture on the fuel cell lifetime, two durability tests, lasting up to 1000h, have been conducted. A test on the 5-kW system has been compared to a reference test performed on a test bench with a shorter stack, conducted with well-controlled operating parameters and flow-through hydrogen strategy. The durability test is based upon the Fuel Cell Dynamic Load Cycle (FC-DLC) protocol but adapted to the system limitations: without OCV steps and a maximum current density of 0.4 A/cm². In situ local measurements with a segmented S++® plate performed all along the tests, showed a more homogeneous distribution of the current density with alternative fuel feeding than in flow-through strategy. Tests performed in this work enabled the understanding of this architecture advantages and drawbacks. Alternative fuel feeding architecture appeared to be a promising solution to ensure the humidification function at the anode side with a simplified fuel cell system.

Keywords: automotive conditions, durability, fuel cell system, proton exchange membrane fuel cell, stack architecture

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Authors: Abubakar Aminu

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Sand dunes, as a major product of desertification, is well known to affect soil resources, water resources and vegetation, especially in arid and semi-arid region; this scenario disrupt the livelihood security of people in the affected areas. The research assessed the episode of sand dune accumulation on water resources, soil and vegetation in Gada local government of Sokoto State, Nigeria. In this paper, both qualitative and quantitative methods were used to generate data which was analyzed and discussed. The finding of the paper shows that livelihood was affected by accumulations of sand dunes as water resources and soils were affected negatively thereby reducing crop yields and making livestock domestication a very difficult and expensive task; the finding also shows that 60% of the respondents agreed to planting of trees as the major solution to combat sand dunes accumulation. However, the soil parameters tested indicated low Organic carbon, low Nitrogen, low Potassium, Calcium and Phosphorus but higher values were recorded in Sodium and Cation exchange capacity which served as evidence of the high or strong aridity nature of the soil in the area. In line with the above, the researcher recommended a massive tree planting campaign to curtail desertification as well as using organic manures for higher agricultural yield and as such, improvement in livelihood security.

Keywords: soils, vegetatio, water, desertification

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Authors: Anastasios Papathanasiou, George Liontos, Athanasios Katsouras, Vasiliki Liagkou, Euripides Glavas

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Email remains a crucial communication tool due to its efficiency, accessibility and cost-effectiveness, enabling rapid information exchange across global networks. However, the global adoption of email has also made it a prime target for cyber threats, including phishing, malware and Business Email Compromise (BEC) attacks, which exploit its integral role in personal and professional realms in order to perform fraud and data breaches. To combat these threats, this research advocates for a multi-layered defense strategy incorporating advanced technological tools such as anti-spam and anti-malware software, machine learning algorithms and authentication protocols. Moreover, we developed an artificial intelligence model specifically designed to analyze email headers and assess their security status. This AI-driven model examines various components of email headers, such as "From" addresses, ‘Received’ paths and the integrity of SPF, DKIM and DMARC records. Upon analysis, it generates comprehensive reports that indicate whether an email is likely to be malicious or benign. This capability empowers users to identify potentially dangerous emails promptly, enhancing their ability to avoid phishing attacks, malware infections and other cyber threats.

Keywords: email security, artificial intelligence, header analysis, threat detection, phishing, DMARC, DKIM, SPF, ai model

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Authors: Amy Gooden, Meshandren Naidoo

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Genetic research is not confined to a particular jurisdiction. Using direct-to-consumer genetic testing (DTC-GT) as an example, this research assesses the status of data sharing into and out of South Africa (SA). While SA laws cover the sending of genetic data out of SA, prohibiting such transfer unless a legal ground exists, the position where genetic data comes into the country depends on the laws of the country from where it is sent – making the legal position less clear.

Keywords: cross-border, data, genetic testing, law, regulation, research, sharing, South Africa

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Authors: Sarina Zainab Shirazi

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Abstract— With the advent of globalization, different countries have liberalized their trade policies to enhance economic integration and developmental processes but the advantages accrued vary greatly from region to region. This study specifically examines European Union (EU) and Association for South East Asian Nations (ASEAN), two regions that show contrasting integration patterns. EU shows most successful integrations versus the slower paced integration in the ASEAN region. A comprehensive panel data empirical investigation of EU and ASEAN in the context of economy size, geographical distances, language, ethnicity, common border and regional trade agreements (RTA) is conducted for a period of 1985 – 2015. The empirical investigation through the augmented gravity equation shows that the real effectiveness for enhanced intra-regional trade is significant when specific examination of export and import components is conducted in the presence of non-tariff barriers. These barriers surface in the form of terms of trade openness, inflation, exchange rate, common borders, common language, ethnic similarity, and presence of a formal regional trade agreement (RTA). Thus, these factors can be utilized by the EU and ASEAN regions in order to formulate effective policy tools to enhance trade within their respective spheres of influence.

Keywords: Association for South East Asian Nations, European Union, Gravity Model, Regional Trade

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Authors: Andrés I. Ávila, Patricia Aros, César San Martín, Elizabeth Kehr, Yovana Leal

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We consider a linear programming model to help farmers to decide if it is convinient to choose among three kinds of export fruits for their future investment. We consider area, investment, water, productivitiy minimal unit, and harvest restrictions and a monthly based model to compute the average income in five years. Also, conditions on the field as area, water availability and initia investment are required. Using the Chilean costs and dollar-peso exchange rate, we can simulate several scenarios to understand the possible risks associated to this market.

Keywords: mixed integer problem, fruit production, support decision model, fruit tree farms

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Authors: Rodrigo Arnaldo Scarpel

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Trend following is a widely accepted investment strategy that adopts a rule-based trading mechanism that rather than striving to predict market direction or on information gathering to decide when to buy and when to sell a stock. Thus, in trend following one must respond to market’s movements that has recently happen and what is currently happening, rather than on what will happen. Optimally, in trend following strategy, is to catch a bull market at its early stage, ride the trend, and liquidate the position at the first evidence of the subsequent bear market. For applying the trend following strategy one needs to find the trend and identify trade signals. In order to avoid false signals, i.e., identify fluctuations of short, mid and long terms and to separate noise from real changes in the trend, most academic works rely on moving averages and other technical analysis indicators, such as the moving average convergence divergence (MACD) and the relative strength index (RSI) to uncover intelligible stock trading rules following trend following strategy philosophy. Recently, some works has applied machine learning techniques for trade rules discovery. In those works, the process of rule construction is based on evolutionary learning which aims to adapt the rules to the current environment and searches for the global optimum rules in the search space. In this work, instead of focusing on the usage of machine learning techniques for creating trading rules, a time series trend classification employing a semi-supervised approach was used to early identify both the beginning and the end of upward and downward trends. Such classification model can be employed to identify trade signals and the decision-making procedure is that if an up-trend (down-trend) is identified, a buy (sell) signal is generated. Semi-supervised learning is used for model training when only part of the data is labeled and Semi-supervised classification aims to train a classifier from both the labeled and unlabeled data, such that it is better than the supervised classifier trained only on the labeled data. For illustrating the proposed approach, it was employed daily trade information, including the open, high, low and closing values and volume from January 1, 2000 to December 31, 2022, of the São Paulo Exchange Composite index (IBOVESPA). Through this time period it was visually identified consistent changes in price, upwards or downwards, for assigning labels and leaving the rest of the days (when there is not a consistent change in price) unlabeled. For training the classification model, a pseudo-label semi-supervised learning strategy was used employing different technical analysis indicators. In this learning strategy, the core is to use unlabeled data to generate a pseudo-label for supervised training. For evaluating the achieved results, it was considered the annualized return and excess return, the Sortino and the Sharpe indicators. Through the evaluated time period, the obtained results were very consistent and can be considered promising for generating the intended trading signals.

Keywords: evolutionary learning, semi-supervised classification, time series data, trading signals generation

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Authors: Jameela Ali, Hamid A. Jalab, Loay E. George, Abdul Rahim Ahmad, Azizah Suliman, Karim Al-Jashamy

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Red blood cells (RBC) are the most common types of blood cells and are the most intensively studied in cell biology. The lack of RBCs is a condition in which the amount of hemoglobin level is lower than normal and is referred to as “anemia”. Abnormalities in RBCs will affect the exchange of oxygen. This paper presents a comparative study for various techniques for classifying the RBCs as normal, or abnormal (anemic) using WEKA. WEKA is an open source consists of different machine learning algorithms for data mining applications. The algorithm tested are Radial Basis Function neural network, Support vector machine, and K-Nearest Neighbors algorithm. Two sets of combined features were utilized for classification of blood cells images. The first set, exclusively consist of geometrical features, was used to identify whether the tested blood cell has a spherical shape or non-spherical cells. While the second set, consist mainly of textural features was used to recognize the types of the spherical cells. We have provided an evaluation based on applying these classification methods to our RBCs image dataset which were obtained from Serdang Hospital-alaysia, and measuring the accuracy of test results. The best achieved classification rates are 97%, 98%, and 79% for Support vector machines, Radial Basis Function neural network, and K-Nearest Neighbors algorithm respectively.

Keywords: K-nearest neighbors algorithm, radial basis function neural network, red blood cells, support vector machine

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Authors: Zhenxiang Zhou

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The triose phosphate utilisation (TPU) limitation to leaf photosynthesis is a biochemical process concerning the sub-foliar carbon sink-source (im)balance, in which photorespiration-associated amino acids exports provide an additional outlet for carbon and increases leaf photosynthetic rate. However, whether this process is regulated by whole-plant sink-source relations and nitrogen budgets remains unclear. We address this question by model analyses of gas-exchange data measured on leaves at three growth stages of rice plants grown at two-nitrogen levels, where three means (leaf-colour modification, adaxial vs abaxial measurements, and panicle pruning) were explored to alter source-sink ratios. Higher specific leaf nitrogen (SLN) resulted in higher rates of TPU and also led to the TPU limitation occurring at a lower intercellular CO2 concentration. Photorespiratory nitrogen assimilation was greater in higher-nitrogen leaves but became smaller in cases associated with yellower-leaf modification, abaxial measurement, or panicle pruning. The feedback inhibition of panicle pruning on rates of TPU was not always observed because panicle pruning blocked nitrogen remobilisation from leaves to grains, and the increased SLN masked the feedback inhibition. The (sub)foliar TPU limitation can be modulated by whole-plant source-sink ratios and nitrogen budgets during rice grain filling, suggesting a close link between sub-foliar and whole-plant sink limitations.

Keywords: triose phosphate utilization, sink limitation, panicle pruning, oryza sativa

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Authors: Baris Can Yalcin

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Motion sensors have been commonly used as a valuable component in mechatronic systems, however, many mechatronic designs and applications that need motion sensors cost enormous amount of money, especially high-tech systems. Design of a software for communication protocol between data acquisition card and motion sensor is another issue that has to be solved. This study presents how to design a low cost motion data acquisition setup consisting of MPU 6050 motion sensor (gyro and accelerometer in 3 axes) and Arduino Mega2560 microcontroller. Design parameters are calibration of the sensor, identification and communication between sensor and data acquisition card, interpretation of data collected by the sensor.

Keywords: design, mechatronics, motion sensor, data acquisition

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Authors: Lyton Chithambo

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This paper reports the results of an investigation into the extent to which various stakeholder pressures influence voluntary disclosure of greenhouse-gas (GHG) emissions in the United Kingdom (UK). The study, which is grounded on institutional theory, also borrows from the insights of upper echelons theory and examines whether specific managerial (chief executive officer) characteristics explain and moderates various stakeholder pressures in explaining GHG voluntary disclosure. Data were obtained from the 2011 annual and sustainability reports of a sample of 216 UK companies on the FTSE350 index listed on the London Stock Exchange. Generally the results suggest that there is no substantial shareholder and employee pressure on a firm to disclose GHG information but there is significant positive pressure from the market status of a firm with those firms with more market share disclosing more GHG information. Consistent with the predictions of institutional theory, we found evidence that coercive pressure i.e. regulatory pressure and mimetic pressures emanating in some industries notably industrials and consumer services have a significant positive influence on firms’ GHG disclosure decisions. Besides, creditor pressure also had a significant negative relationship with GHG disclosure. While CEO age had a direct negative effect on GHG voluntary disclosure, its moderation effect on stakeholder pressure influence on GHG disclosure was only significant on regulatory pressure. The results have important implications for both policy makers and company boards strategizing to reign in their GHG emissions.

Keywords: greenhouse gases, voluntary disclosure, upper echelons theory, institution theory

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Authors: Ashish Dhamaniya, Satish Chandra

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Speed and traffic volume data are collected on different sections of four lane and six lane roads in three metropolitan cities in India. Speed data are analyzed to fit the statistical distribution to individual vehicle speed data and all vehicles speed data. It is noted that speed data of individual vehicle generally follows a normal distribution but speed data of all vehicle combined at a section of urban road may or may not follow the normal distribution depending upon the composition of traffic stream. A new term Speed Spread Ratio (SSR) is introduced in this paper which is the ratio of difference in 85^th and 50^th percentile speed to the difference in 50^th and 15^th percentile speed. If SSR is unity then speed data are truly normally distributed. It is noted that on six lane urban roads, speed data follow a normal distribution only when SSR is in the range of 0.86 – 1.11. The range of SSR is validated on four lane roads also.

Keywords: normal distribution, percentile speed, speed spread ratio, traffic volume

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Authors: Ming Wei

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Over the past two decades, Location Based Service (LBS) data have been increasingly applied to urban and transportation studies due to their comprehensiveness and consistency. However, compared to other LBS data including mobile phone data, GPS and social networking platforms, smart card data collected from public transport users have arguably yet to be fully exploited in urban systems analysis. By using five weekdays of passenger travel transaction data taken from go card – Southeast Queensland’s transit smart card – this paper analyses the spatiotemporal distribution of passenger movement with regard to the land use patterns in Brisbane. Work and residential places for public transport commuters were identified after extracting journeys-to-work patterns. Our results show that the locations of the workplaces identified from the go card data and residential suburbs are largely consistent with those that were marked in the land use map. However, the intensity for some residential locations in terms of population or commuter densities do not match well between the map and those derived from the go card data. This indicates that the misalignment between residential areas and workplaces to a certain extent, shedding light on how enhancements to service management and infrastructure expansion might be undertaken.

Keywords: big data, smart card data, travel pattern, land use

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Authors: Nursuhaila Ibrahim, Noor Hanim Rahmat, Nurul Ain Hasni, Nursyuhada Zakaria

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Past studies have shown that class discussions in the ESL classrooms not only helped students exchange ideas with their peers. Students also learn turn taking skills throughout the discussion. Through interacting with their peers, learners learn to use turn-taking strategies. They learn to wait for their turn, to listen to the ideas of others, to disagree, or to agree, and to add on more points in the conversation. This quantitative research explores students’ perception on class discussions and how the discussions influence their choice of turn-taking strategies. Findings of this research will have interesting implications towards the use of class discussions in the ESL classrooms.

Keywords: ESL, class discussions, turn-taking skills, peers

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Authors: Moridi Fatemeh, Dasineh Mehdi, Jafari Narges

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The aim of this study was to investigate the relationship between dividends and investment in a condition of cash flow uncertainty. Previous studies have also found some evidence that there is N-shaped relationship between dividends and investment given different levels of cash uncertainly. Thus, this study examines this relationship over the period 2009-2014 in Tehran Stock Exchange (TSE). Based on our sample and new variables, we found reverse N-shaped relationship in different levels of cash flow uncertainly. This shape was descending in cash flow certainly and uncertainly but it is ascending in medial position.

Keywords: dividends, investment, nonlinear relationship, uncertainty of cash flow

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Authors: Jose Marie E. Ocdenaria, Riceli C. Mendoza

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Culturally, languages meet, merge, share, exchange, appropriate, donate, and divide in and to and from each other. Further, this type of recurrence manifests in East Asian cultures, where language influence diffuses across geographical proximities. Historically, China has notable impacts on Japan’s culture. For instance, Japanese borrowed words from China and their way of reading and writing. This qualitative and descriptive employing contrastive analysis study addressed the true and false cognates of Japanese-Philippine languages and Chinese-Philippine languages. It involved a rich collection of data from various sources like textual pieces of evidence or corpora to gain a deeper understanding of true and false cognates between L1 and L2. Cognates of Japanese-Philippine languages and Chinese-Philippine languages were analyzed contrastively according to orthography, phonology, and semantics. The words presented were the roots; however, derivatives, reduplications, and variants of stress were included when they shed emphases on the comparison. The basis of grouping the cognates was its phonetic-semantic resemblance. Based on the analysis, it revealed that there are words which may have several types of lexical relationship. Further, the study revealed that the Japanese language has more false cognates in the Philippine languages, particularly in Tagalog and Cebuano. On the other hand, there are more true cognates of Chinese in Tagalog. It is the hope of this study to provide a significant contribution to a diverse audience. These include the teachers and learners of foreign languages such as Japanese and Chinese, future researchers and investigators, applied linguists, curricular theorists, community, and publishers.

Keywords: Contrastive Analysis, Japanese, Chinese and Philippine languages, Qualitative and descriptive study, True and False Cognates

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Authors: Seung Hwan Park, Cheng-Sool Park, Jun Seok Kim, Youngji Yoo, Daewoong An, Jun-Geol Baek

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Depending on the big data analysis becomes important, yield prediction using data from the semiconductor process is essential. In general, yield prediction and analysis of the causes of the failure are closely related. The purpose of this study is to analyze pattern affects the final test results using a die map based clustering. Many researches have been conducted using die data from the semiconductor test process. However, analysis has limitation as the test data is less directly related to the final test results. Therefore, this study proposes a framework for analysis through clustering using more detailed data than existing die data. This study consists of three phases. In the first phase, die map is created through fail bit data in each sub-area of die. In the second phase, clustering using map data is performed. And the third stage is to find patterns that affect final test result. Finally, the proposed three steps are applied to actual industrial data and experimental results showed the potential field application.

Keywords: die-map clustering, feature extraction, pattern recognition, semiconductor manufacturing process

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Authors: Afiq Juazer Rizal, Siti Zaleha Misnan, M. Zairi M. Yusof

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Seismic data is the fundamental tool utilized by exploration companies to determine potential hydrocarbon. However, the importance of seismic trace data will be undermined unless the geo-spatial component of the data is understood. Deriving a proposed well to be drilled from data that has positional ambiguity will jeopardize business decision and millions of dollars’ investment that every oil and gas company would like to avoid. Spatial integrity QC workflow has been introduced in PETRONAS to ensure positional errors within the seismic data are recognized throughout the exploration’s lifecycle from acquisition, processing, and seismic interpretation. This includes, amongst other tests, quantifying that the data is referenced to the appropriate coordinate reference system, survey configuration validation, and geometry loading verification. The direct outcome of the workflow implementation helps improve reliability and integrity of sub-surface geological model produced by geoscientist and provide important input to potential hazard assessment where positional accuracy is crucial. This workflow’s development initiative is part of a bigger geospatial integrity management effort, whereby nearly eighty percent of the oil and gas data are location-dependent.

Keywords: oil and gas exploration, PETRONAS, seismic data, spatial integrity QC workflow

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Authors: Piotr Prewysz-Kwinto, Grazyna Voss

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Accounting policies are a set of solutions compliant with legal regulations that an entity selects and adopts, and which guarantee a proper quality of financial statements. Those solutions may differ depending on whether the entity adopts national or international accounting standards. The aim of this article is to present accounting principles (policies) in Polish and international legal regulations and their adoption in selected Polish companies listed on the Warsaw Stock Exchange. The research method adopted in this work is the analysis and evaluation of legal conditions in Polish companies.

Keywords: accounting policies, international financial reporting standards, financial statement, method of measuring

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Authors: Maryam Aloshan, Imam Mohammad Ibn Saud, Ahmad Khudair

Abstract:

This study assesses the data governance maturity of nonprofit organizations in Riyadh, Saudi Arabia, using the National Data Maturity Index (NDI) framework developed by the Saudi Data and Artificial Intelligence Authority (SDAIA). Employing a survey designed around the NDI model, data maturity levels were evaluated across 14 dimensions using a 5-point Likert scale. The results reveal a spectrum of maturity levels among the organizations surveyed: while some medium-sized associations reached the ‘Defined’ stage, others, including large associations, fell within the ‘Absence of Capabilities’ or ‘Building’ phases, with no organizations achieving the advanced ‘Established’ or ‘Pioneering’ levels. This variation suggests an emerging recognition of data governance but underscores the need for targeted interventions to bridge the maturity gap. The findings point to a significant opportunity to elevate data governance capabilities in Saudi nonprofits through customized capacity-building initiatives, including training, mentorship, and best practice sharing. This study contributes valuable insights into the digital transformation journey of the Saudi nonprofit sector, aligning with national goals for data-driven governance and organizational efficiency.

Keywords: nonprofit organizations-national data maturity index (NDI), Saudi Arabia- SDAIA, data governance, data maturity

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Authors: Zhenqiu Liu

Abstract:

Visualizing the heterogeneity within cell-populations for single-cell RNA-seq data is crucial for studying the functional diversity of a cell. However, because of the high level of noises, outlier, and dropouts, it is very challenging to measure the cell-to-cell similarity (distance), visualize and cluster the data in a low-dimension. Minimum volume embedding (MVE) projects the data into a lower-dimensional space and is a promising tool for data visualization. However, it is computationally inefficient to solve a semi-definite programming (SDP) when the sample size is large. Therefore, it is not applicable to single-cell RNA-seq data with thousands of samples. In this paper, we develop an efficient algorithm with an accelerated proximal gradient method and visualize the single-cell RNA-seq data efficiently. We demonstrate that the proposed approach separates known subpopulations more accurately in single-cell data sets than other existing dimension reduction methods.

Keywords: single-cell RNA-seq, minimum volume embedding, visualization, accelerated proximal gradient method

Procedia PDF Downloads 228

Authors: Sara Ibn El Ahrache, Tajje-eddine Rachidi, Hassan Badir, Abderrahmane Sbihi

Abstract:

Recently, there has been increasing confidence for a favorable usage of big data drawn out from the huge amount of information deposited in a cloud computing system. Data kept on such systems can be retrieved through the network at the user’s convenience. However, the data that users send include private information, and therefore, information leakage from these data is now a major social problem. The usage of secret sharing schemes for cloud computing have lately been approved to be relevant in which users deal out their data to several servers. Notably, in a (k,n) threshold scheme, data security is assured if and only if all through the whole life of the secret the opponent cannot compromise more than k of the n servers. In fact, a number of secret sharing algorithms have been suggested to deal with these security issues. In this paper, we present a Mapreduce implementation of Shamir’s secret sharing scheme to increase its performance and to achieve optimal security for cloud data. Different tests were run and through it has been demonstrated the contributions of the proposed approach. These contributions are quite considerable in terms of both security and performance.

Keywords: cloud computing, data security, Mapreduce, Shamir's secret sharing

Procedia PDF Downloads 307