Search results for: accounting information quality

Authors: Mehran Memari, Bita Asadi

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Second language (L2) classrooms in academic contexts usually consist of learners with diverse L2 proficiency levels. One solution for managing such heterogeneous classes and addressing individual needs of students is to improve learner autonomy by using technological innovations such as blogging. The focus of this study is on investigating the effects of blogging on improving the quality of Iranian university students' writings. For this aim, twenty-six Iranian university students participated in the study. Students in the experimental group (n=13) were required to blog daily while the students in the control group (n=13) were asked to write a daily schedule using paper and pencil. After a 3-month period of instruction, the five last writings of the students from both groups were rated by two experienced raters. Also, students' attitudes toward the traditional method and blogging were surveyed using a questionnaire and a semi-structured interview. The research results showed evidences in favor of the students who used blogging in their writing program. Also, although students in the experimental group found blogging more demanding than the traditional method, they showed an overall positive attitude toward the use of blogging as a way of improving their writing skills. The findings of the study have implications for the incorporation of computer-assisted learning in L2 academic contexts.

Keywords: blogging, computer-assisted learning, paper and pencil, writing

Procedia PDF Downloads 382

Authors: N. A. Ahmad Zubairi, H. Takaijudin, K. W. Yusof

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Pesticides have been used widely over the world in agriculture to protect from pests and reduce crop losses. However, it affects the environment with toxic chemicals. Exceed of toxic constituents in the ecosystem will result in bad side effects. The hydrological cycle is related to the existence of pesticides and heavy metal which it can penetrate through varieties of sources into the soil or water bodies, especially runoff. Therefore, proper mechanisms of pesticide and heavy metal removal should be studied to improve the quality of ecosystem free or reduce from unwanted substances. This paper reviews the use of treatment train and its mechanisms to minimize pesticides and heavy metal from agricultural runoff. Organochlorine (OCL) is a common pesticide that was found in the agricultural runoff. OCL is one of the toxic chemicals that can disturb the ecosystem such as inhibiting plants' growth and harm human health by having symptoms as asthma, active cancer cell, vomit, diarrhea, etc. Thus, this unwanted contaminant gives disadvantages to the environment and needs treatment system. Hence, treatment train by bioretention system is suitable because removal efficiency achieves until 90% of pesticide removal with selected vegetated plant and additive.

Keywords: pesticides, heavy metal, agricultural runoff, bioretention, mechanism removal, treatment train

Procedia PDF Downloads 141

Authors: Md. Nakib Ul Hasan, Md. Ariful Islam, Md. Sumon Miah, Misbah Ul Hoque, Bulbul Ahmed

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The variability of cotton fiber characteristics has always been influenced by origin, weather conditions, method of culturing, and harvesting. Spinners work tirelessly to ensure consistent yarn quality by using the different origins of fibers to maximizes the profit margin. Spinners often fail to select desired raw materials of various origins to achieve an appropriate mixing plan due to the lack of knowledge on the interrelationship among fiber properties. The purpose of this research is to investigate the correlations among dominating fiber properties such as micronaire, strength, breaking elongation, upper half mean length, length uniformity index, short fiber index, maturity, reflectance, and yellowness. For this purpose, fiber samples from 500 Indian cotton bales and 350 Greek cotton bales were collected and tested using the high volume instrument (HVI). The fiber properties dataset was then compiled and analyzed using python 3.7 to determine the correlations matrix. Results show that Indian cotton fiber have highest correlation between strength-mat = 0.84, followed by SFI-Unf =-0.83, and Neps-Unf = -0.72. Greek cotton fiber, in contrast, have highest correlation between SFI-Unf =-0.98, followed by SFI-Mat = 0.89, +b-Len = 0.84, and Str-Mat = 0.74. Overall, the Greek cotton fiber showed a higher correlational matrix than compared to that of Indian cotton fiber.

Keywords: cotton fiber, fiber properties correlation, Greek cotton, HVI, Indian cotton, spinning

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Authors: Ana Luisa Mouro, Ana Maria Ramalheira

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The Reunification of Germany, in 1990, was not received with great enthusiasm by other European countries. On the contrary, the union of the two German states was accompanied by great concern towards its possible political and economic consequences. The Europeans had not forgotten Germany’s responsibility in the outbreak of the Second World War, and many feared that this new nation would again long for a hegemonic role. During the following years, however, the notion of a threatening Germany faded away, giving place to a description of Germany as an economic giant but a political dwarf. Twenty years after the Reunification, with the outbreak of the financial crisis, Germany conquered a key and powerful position at the heart of Europe and Germanophobia started to gain ground again. The present study has been based on the survey, selection and critical analysis of news reporting, opinion articles, interviews and editorials, published in the weekly Expresso and the daily Público, during two historical moments: the Reunification of Germany in 1990 and the European Crisis, between 2008 and 2015. The findings of this study will show that Germany’s growing influence over the current European economic and political scene woke up old 'demons' that had been 'sleeping' since 1990.

Keywords: media and cultural studies, Euro crisis, German Unification, Germanophobia, Portuguese quality press

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Authors: Tugrul Torun, Ihsan A. Yuksel, Si̇nem On Aktan, Taha K. Vezi̇roglu

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In the quality control processes in some industries, the usage of CMM has increased in recent years. Consequently, the CMMs play important roles in the acceptance or rejection of manufactured parts. For parts, it’s important to be able to make decisions by performing fast measurements. According to related technical drawing and its tolerances, measurement uncertainty should also be considered during assessment. Since uncertainty calculation is difficult and time-consuming, most companies ignore the uncertainty value in their routine inspection method. Although studies on measurement uncertainty have been carried out on CMM’s in recent years, there is still no applicable method for analyzing task-specific measurement uncertainty. There are some standard series for calculating measurement uncertainty (ISO-15530); it is not possible to use it in industrial measurement because it is not a practical method for standard measurement routine. In this study, the inter-laboratory comparison test has been carried out in the ROKETSAN A.Ş. with all dimensional inspection units. The reference part that we used is traceable to the national metrology institute TUBİTAK UME. Each unit has measured reference parts according to related technical drawings, and the task-specific measuring uncertainty has been calculated with related parameters. According to measurement results and uncertainty values, the En values have been calculated.

Keywords: coordinate measurement, CMM, comparison, uncertainty

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Authors: Xianbao Sun, Jinlong Zhao, Shudong He, Jing Li

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Volutharpa ampullacea perryi is a high-protein marine shellfish. However, few data are available on the effects of boiling temperatures and time on quality of the meat. In this study, colour, texture and sensory characteristics of Volutharpa ampullacea perryi meat during the boiling cooking processes (75-100 °C, 5-60 min) were investigated by colors analysis, texture profile analysis (TPA), scanning electron microscope (SEM) and sensory evaluation. The ratio of cooking loss gradually increased with the increase of temperature and time. The colour of meat became lighter and more yellower from 85 °C to 95 °C in a short time (5-20 min), but it became brown after a 30 min treatment. TPA results showed that the Volutharpa ampullacea perryi meat were more firm and less cohesive after a higher temperature (95-100 °C) treatment even in a short period (5-15 min). Based on the SEM analysis, it was easily found that the myofibrils structure was destroyed at a higher temperature (85-100 °C). Sensory data revealed that the meat cooked at 85-90 °C in 10-20 min showed higher scores in overall acceptance, as well as color, hardness and taste. Based on these results, it could be constructed that Volutharpa ampullacea perryi meat should be heated on a suitable condition (such as 85 °C 15 min or 90 °C 10 min) in the boiling cooking to be ensure a better acceptability.

Keywords: Volutharpa ampullacea perryi meat, boiling cooking, colour, sensory, texture

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Authors: Amirmehdi Dokhanchi, Babak Ziyae

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Studying and prioritizing effective factors on productivity of human resources through TOPSIS method is the main aim of the present research study. For this reason, while reviewing concepts existing in productivity, effective factors were studied. Managers, supervisors, staff and personnel of Tabriz Tractor Manufacturing Company are considered subject of this study. Of total individuals, 160 of them were selected through the application of random sampling method as 'subject'. Two questionnaires were used for collecting data in this study. The factors, which had the highest effect on productivity, were recognized through the application of software packages. TOPSIS method was used for prioritizing recognized factors. For this reason, the second questionnaire was put available to statistics sample for studying effect of each of factors towards predetermined indicators. Therefore, decision-making matrix was obtained. The result of prioritizing factors shows that existence of accurate organizational strategy, high level of occupational skill, application of partnership and contribution system, on-the-job-training services, high quality of occupational life, dissemination of appropriate organizational culture, encouraging to creativity and innovation, and environmental factors are prioritized respectively.

Keywords: productivity of human resources, productivity indicators, TOPSIS, prioritizing factors

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Authors: Raana Babadi Fathipour

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Nourishment nanotechnology is an range of rising intrigued and opens up a entirety universe of modern conceivable outcomes for the nourishment industry. The essential categories of nanotechnology applications and functionalities right now within the improvement of nourishment bundling incorporate: the enhancement of plastic materials obstructions, the consolidation of dynamic components that can convey utilitarian properties past those of customary dynamic bundling, and the detecting and signaling of significant data. Nano nourishment bundling materials may amplify nourishment life, move forward nourishment security, alarm buyers that nourishment is sullied or ruined, repair tears in bundling, and indeed release preservatives to expand the life of the nourishment within the bundle. Nanotechnology applications within the nourishment industry can be utilized to identify microbes in bundling, or produce stronger flavors and color quality, and security by expanding the obstruction properties. Nanotechnology holds extraordinary guarantee to supply benefits not fair inside nourishment items but too around nourishment items. In reality, nanotechnology presents modern chances for advancement within the nourishment industry at monstrous speed, but instability and wellbeing concerns are moreover developing. EU/WE/global enactment for the direction of nanotechnology in nourishment are scanty. Besides, current enactment shows up unacceptable to nanotechnology specificity.

Keywords: nano technology, nano foods, food packaging, nano participle

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Authors: Mohamad Javad Shakouri, Hamid Tavakkolipour, Mahdis Jamshidi Tehranian

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The inclination toward using food coatings is increasing daily, due to containing natural elements and not producing environmental pollution. Food coatings are uniform and thin layers of natural substances that cover the food product and act as a barrier against moisture, oxygen, and substances dissolved in food. Using food coatings on fruits and vegetables can delay water dissipation, losing aroma, decolorization, and improve the appearance of the product, and in general, preserve and protect the quality of fresh produce. When fruits and vegetables grow, they are equipped with a natural shield, called cuticle– a layer of wax. Washing the products, after harvest, the cuticle – this protective coating – is removed. In order to replace the cuticle, we can use an edible protective coating. This coating delays dehydration and deterioration and hence increases the life of the product while keeping its moisture. In this study, it was concluded that using food coatings, such as corn zein, carrageenan, and starch can have a substantial effect on the quantitative and qualitative preservation of food products, such as fruits, vegetables, and mushrooms.

Keywords: food coating, corn zein, button and oyster mushrooms, ascorbic and citric acids

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Authors: Valeria Abreu Minero, Edward Barker, Hannah Dickson, Francois Husson, Sandra Flynn, Jennifer Shaw

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Purpose – The purpose of this paper is to identify offender typologies based on aspects of the offenders’ psychopathology and their associations with crime scene behaviours using data derived from the National Confidential Enquiry into Suicide and Safety in Mental Health concerning homicides in England and Wales committed by offenders in contact with mental health services in the year preceding the offence (n=759). Design/methodology/approach – The authors used multiple correspondence analysis to investigate the interrelationships between the variables and hierarchical agglomerative clustering to identify offender typologies. Variables describing: the offender’s mental health history; the offenders’ mental state at the time of offence; characteristics useful for police investigations; and patterns of crime scene behaviours were included. Findings – Results showed differences in the offender’s histories in relation to their crime scene behaviours. Further, analyses revealed three homicide typologies: externalising, psychosis and depression. Analyses revealed three homicide typologies: externalising, psychotic and depressive. Practical implications – These typologies may assist the police during homicide investigations by: furthering their understanding of the crime or likely suspect; offering insights into crime patterns; provide advice as to what an offender’s offence behaviour might signify about his/her mental health background; findings suggest information concerning offender psychopathology may be useful for offender profiling purposes in cases of homicide offenders with schizophrenia, depression and comorbid diagnosis of personality disorder and alcohol/drug dependence. Originality/value – Empirical studies with an emphasis on offender profiling have almost exclusively focussed on the inference of offender demographic characteristics. This study provides a first step in the exploration of offender psychopathology and its integration to the multivariate analysis of offence information for the purposes of investigative profiling of homicide by identifying the dominant patterns of mental illness within homicidal behaviour.

Keywords: offender profiling, mental illness, psychopathology, multivariate analysis, homicide, crime scene analysis, crime scene behviours, investigative advice

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Authors: Ksenia Volkova, Artur Petrosyan, Ignatii Dubyshkin, Alexei Ossadtchi

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Brain-computer interfaces are a growing research field producing many implementations that find use in different fields and are used for research and practical purposes. Despite the popularity of the implementations using non-invasive neuroimaging methods, radical improvement of the state channel bandwidth and, thus, decoding accuracy is only possible by using invasive techniques. Electrocorticography (ECoG) is a minimally invasive neuroimaging method that provides highly informative brain activity signals, effective analysis of which requires the use of machine learning methods that are able to learn representations of complex patterns. Deep learning is a family of machine learning algorithms that allow learning representations of data with multiple levels of abstraction. This study explores the potential of deep learning approaches for ECoG processing, decoding movement intentions and the perception of proprioceptive information. To obtain synchronous recording of kinematic movement characteristics and corresponding electrical brain activity, a series of experiments were carried out, during which subjects performed finger movements at their own pace. Finger movements were recorded with a three-axis accelerometer, while ECoG was synchronously registered from the electrode strips that were implanted over the contralateral sensorimotor cortex. Then, multichannel ECoG signals were used to track finger movement trajectory characterized by accelerometer signal. This process was carried out both causally and non-causally, using different position of the ECoG data segment with respect to the accelerometer data stream. The recorded data was split into training and testing sets, containing continuous non-overlapping fragments of the multichannel ECoG. A deep convolutional neural network was implemented and trained, using 1-second segments of ECoG data from the training dataset as input. To assess the decoding accuracy, correlation coefficient r between the output of the model and the accelerometer readings was computed. After optimization of hyperparameters and training, the deep learning model allowed reasonably accurate causal decoding of finger movement with correlation coefficient r = 0.8. In contrast, the classical Wiener-filter like approach was able to achieve only 0.56 in the causal decoding mode. In the noncausal case, the traditional approach reached the accuracy of r = 0.69, which may be due to the presence of additional proprioceptive information. This result demonstrates that the deep neural network was able to effectively find a representation of the complex top-down information related to the actual movement rather than proprioception. The sensitivity analysis shows physiologically plausible pictures of the extent to which individual features (channel, wavelet subband) are utilized during the decoding procedure. In conclusion, the results of this study have demonstrated that a combination of a minimally invasive neuroimaging technique such as ECoG and advanced machine learning approaches allows decoding motion with high accuracy. Such setup provides means for control of devices with a large number of degrees of freedom as well as exploratory studies of the complex neural processes underlying movement execution.

Keywords: brain-computer interface, deep learning, ECoG, movement decoding, sensorimotor cortex

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Authors: Min Kyeong Cha, Ju Yeon Mun, Seong Baeg Kim

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Recently, ‘play of learning’ became important and is emphasized as a useful learning tool. Therefore, interest in edutainment contents is growing. Storytelling is considered first as a method that improves the transmission of information and learner's interest when planning edutainment contents. In this study, we designed edutainment contents in the form of an adventure game that applies the storytelling method. This content provides questions and items constituted dynamically and reorganized learning contents through analysis of test results. It allows learners to solve various questions through effective iterative learning. As a result, the learners can reach mastery learning.

Keywords: storytelling, edutainment, mastery learning, computer operating principle

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Authors: Jim Shi, Jasmine Chang, Nesreen El-Rayes

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The world has been experiencing a steadily increasing trend in both the production and consumption of plastic. The global consumer revolution should not have been possible without plastic, thanks to its salient feature of inexpensiveness and durability. But, as a two-edged sword, its durable quality has returned to haunt and even jeopardized us. That exacerbating the plastic crisis has attracted various global initiatives and actions. Simultaneously, firms are eager to adopt new technology as they witness and perceive more potential and merit of Industry 4.0 technologies. For example, Blockchain technology (BCT) is drawing the attention of numerous stakeholders because of its wide range of outstanding features that promise to enhance supply chain operations. However, from a research perspective, most of the literature addresses the plastic crisis from either environmental or social perspectives. In contrast, analysis from the data science perspective and technology is relatively scarce. To this end, this study aims to fill this gap and cover the plastic crisis from a holistic view of environmental, social, technological, and business perspectives. In particular, we propose a mathematical model to examine the inclusion of BCT to enhance and improve the efficiency on the upstream and the downstream sides of the plastic value, where the whole value chain is coordinated systematically, and its interoperability can be optimized. Consequently, the Environmental, Social, and Governance (ESG) goal and Circular Economics (CE) sustainability can be maximized.

Keywords: blockchain technology, plastic, circular economy, sustainability

Procedia PDF Downloads 63

Authors: Jan Van Uden

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The paper reviews classical agency-theory and its contributions to the analysis of complex business negotiations and gives an approach for the modification of the basic agency-model in order to examine the negotiation specific dimensions of agency-problems. By illustrating fundamental potentials for the modification of agency-theory in context of business negotiations the paper highlights recent empirical research that investigates agent-based negotiations and inter-team constellations. A general theoretical analysis of complex negotiation would be based on a two-level approach. First, the modification of the basic agency-model in order to illustrate the organizational context of business negotiations (i.e., multi-agent issues, common-agencies, multi-period models and the concept of bounded rationality). Second, the application of the modified agency-model on complex business negotiations to identify agency-problems and relating areas of risk in the negotiation process. The paper is placed on the first level of analysis – the modification. The method builds on the one hand on insights from behavior decision research (BRD) and on the other hand on findings from agency-theory as normative directives to the modification of the basic model. Through neoclassical assumptions concerning the fundamental aspects of agency-relationships in business negotiations (i.e., asymmetric information, self-interest, risk preferences and conflict of interests), agency-theory helps to draw solutions on stated worst-case-scenarios taken from the daily negotiation routine. As agency-theory is the only universal approach able to identify trade-offs between certain aspects of economic cooperation, insights obtained provide a deeper understanding of the forces that shape business negotiation complexity. The need for a modification of the basic model is illustrated by highlighting selected issues of business negotiations from agency-theory perspective: Negotiation Teams require a multi-agent approach under the condition that often decision-makers as superior-agents are part of the team. The diversity of competences and decision-making authority is a phenomenon that overrides the assumptions of classical agency-theory and varies greatly in context of certain forms of business negotiations. Further, the basic model is bound to dyadic relationships preceded by the delegation of decision-making authority and builds on a contractual created (vertical) hierarchy. As a result, horizontal dynamics within the negotiation team playing an important role for negotiation success are therefore not considered in the investigation of agency-problems. Also, the trade-off between short-term relationships within the negotiation sphere and the long-term relationships of the corporate sphere calls for a multi-period perspective taking into account the sphere-specific governance-mechanisms already established (i.e., reward and monitoring systems). Within the analysis, the implementation of bounded rationality is closely related to findings from BRD to assess the impact of negotiation behavior on underlying principal-agent-relationships. As empirical findings show, the disclosure and reservation of information to the agent affect his negotiation behavior as well as final negotiation outcomes. Last, in context of business negotiations, asymmetric information is often intended by decision-makers acting as superior-agents or principals which calls for a bilateral risk-approach to agency-relations.

Keywords: business negotiations, agency-theory, negotiation analysis, interteam negotiations

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Authors: Ali R. Alshawawreh, Francisco Liébana-Cabanillas, Francisco J. Blanco-Encomienda

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Collaboration between marketing and business intelligence (BI) is crucial in today's ever-evolving business landscape. These two domains play pivotal roles in molding customers' experiential knowledge. Marketing insights offer valuable information regarding customer needs, preferences, and behaviors, thus refining marketing strategies and enhancing overall customer experiences. Conversely, BI facilitates data-driven decision-making, leading to heightened operational efficiency, product quality, and customer satisfaction. The analysis of customer data through BI unveils patterns and trends, informing product development, marketing campaigns, and customer service initiatives aimed at enriching experiences and knowledge. Customer experiential knowledge (CEK) encompasses customers' implicit comprehension of consumption experiences influenced by diverse factors, including social and cultural influences. This study primarily focuses on telecommunications companies in Jordan, scrutinizing how experiential customer knowledge mediates the relationship between marketing intelligence, business intelligence, and innovation in product and service offerings. Drawing on theoretical frameworks such as the resource-based view (RBV) and service-dominant logic (SDL), the research aims to comprehend how organizations utilize their resources, particularly knowledge, to foster innovation. Employing a quantitative research approach, the study collected and analyzed primary data to explore hypotheses. The chosen method was justified for its efficacy in handling large sample sizes. Structural equation modeling (SEM) facilitated by Smart PLS software evaluated the relationships between the constructs, followed by mediation analysis to assess the indirect associations in the model. The study findings offer insights into the intricate dynamics of organizational innovation, uncovering the interconnected relationships between business intelligence, customer experiential knowledge-based innovation (CEK-DI), marketing intelligence (MI), and product and service innovation (PSI), underscoring the pivotal role of advanced intelligence capabilities in developing innovative practices rooted in a profound understanding of customer experiences. Organizations equipped with cutting-edge BI tools are better positioned to devise strategies informed by precise insights into customer needs and behaviors. Furthermore, the positive impact of BI on PSI reaffirms the significance of data-driven decision-making in shaping the innovation landscape. Companies leveraging BI demonstrate adeptness in identifying market opportunities guiding the development of novel products and services. The substantial impact of CEK-DI on PSI highlights the crucial role of customer experiences in driving organizational innovation. Firms actively integrating customer insights into their innovation processes are more likely to create offerings aligned with customer expectations, fostering higher levels of product and service innovation. Additionally, the positive and significant effect of MI on CEK-DI underscores the critical role of market insights in shaping innovative strategies. While the relationship between MI and PSI is positive, a slightly weaker significance level indicates a nuanced association, suggesting that while MI contributes to innovation, other factors may also influence the innovation landscape, warranting further exploration. In conclusion, the study underscores the essential role of intelligence capabilities, particularly artificial intelligence, in driving innovation, emphasizing the necessity for organizations to leverage market and customer intelligence for effective and competitive innovation practices. Collaborative efforts between marketing and business intelligence serve as pivotal drivers of innovation, influencing experiential customer knowledge and shaping organizational strategies and practices, ultimately enhancing overall customer experiences and organizational performance.

Keywords: marketing intelligence, business intelligence, product, customer experiential knowledge-driven innovation

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Authors: Payam Mousavi, Andrew L. Stewart, Huiwen You, Aryeh F. G. Fayerman

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We present a decision-support tool to assist an operator in the detection and tracking of a suspect vehicle traveling to an unknown target destination. Multiple data sources, such as traffic cameras, traffic information, weather, etc., are integrated and processed in real-time to infer a suspect’s intended destination chosen from a list of pre-determined high-value targets. Previously, we presented our work in the detection and tracking of vehicles using traffic and airborne cameras. Here, we focus on the fusion and processing of that information to predict a suspect’s behavior. The network of cameras is represented by a directional graph, where the edges correspond to direct road connections between the nodes and the edge weights are proportional to the average time it takes to travel from one node to another. For our experiments, we construct our graph based on the greater Los Angeles subset of the Caltrans’s “Performance Measurement System” (PeMS) dataset. We propose a Bayesian approach where a posterior probability for each target is continuously updated based on detections of the suspect in the live video feeds. Additionally, we introduce the concept of ‘soft interventions’, inspired by the field of Causal Inference. Soft interventions are herein defined as interventions that do not immediately interfere with the suspect’s movements; rather, a soft intervention may induce the suspect into making a new decision, ultimately making their intent more transparent. For example, a soft intervention could be temporarily closing a road a few blocks from the suspect’s current location, which may require the suspect to change their current course. The objective of these interventions is to gain the maximum amount of information about the suspect’s intent in the shortest possible time. Our system currently operates in a human-on-the-loop mode where at each step, a set of recommendations are presented to the operator to aid in decision-making. In principle, the system could operate autonomously, only prompting the operator for critical decisions, allowing the system to significantly scale up to larger areas and multiple suspects. Once the intended target is identified with sufficient confidence, the vehicle is reported to the authorities to take further action. Other recommendations include a selection of road closures, i.e., soft interventions, or to continue monitoring. We evaluate the performance of the proposed system using simulated scenarios where the suspect, starting at random locations, takes a noisy shortest path to their intended target. In all scenarios, the suspect’s intended target is unknown to our system. The decision thresholds are selected to maximize the chances of determining the suspect’s intended target in the minimum amount of time and with the smallest number of interventions. We conclude by discussing the limitations of our current approach to motivate a machine learning approach, based on reinforcement learning in order to relax some of the current limiting assumptions.

Keywords: autonomous surveillance, Bayesian reasoning, decision support, interventions, patterns of life, predictive analytics, predictive insights

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Authors: Mohsen Danesh Mesgaran, Ali Hodjatpanah Montazeri, Alireza Vakili, Mansoor Tahmasbei

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To compare peppermint essential oil versus a mixture of formic and propionic acids a study was conducted to their effects on volatile fatty acid proportion and VFA score of corn silage. Chopped whole crop corn (control) was treated with peppermint essential oil (240 mg kg-1 DM) or a mixture of formic and propionic acids (2:1) at 0.4% of fresh forage weight, and ensiled for 30 days. Then, silage extract was provided and the concentration of each VFA was determined using gas chromatography. The VFA score was calculated according to the patented formula proposed by Dairy One Scientific Committee. The score is calculated based on the positive impact of lactic and acetic acids versus the negative effect of butyric acid to achieve a single value for evaluating silage quality. The essential oil declined pH and increased the concentration of lactic and acetic acids in the silage extract. All corn silages evaluated in this study had a VFA score between 6 through 8. However, silage with peppermint essential oils had lower volatile fatty acids score than those of the other treatments. Both of applied additives caused a significant improvement in silage aerobic stability.

Keywords: peppermint, essential oil, corn silage, VFA (volatile fatty acids)

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Authors: Dua K. S. Y. Klaas, Monzur A. Imteaz, Ika Sudiayem, Elkan M. E. Klaas, Eldav C. M. Klaas

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Due to its porous nature, karst terrains – geomorphologically developed from dissolved formations, is vulnerable to water shortage and deteriorated water quality. Therefore, a solid comprehension on sub-surface flow of karst landscape is essential to assess the long-term availability of groundwater resources. In this paper, a single-continuum model using a finite difference model, MODLFOW, was constructed to represent an unconfined carbonate aquifer in a tropical karst island of Rote in Indonesia. The model, spatially discretized in 20 x 20 m grid cells, was calibrated and validated using available groundwater level and atmospheric variables. In the calibration and validation steps, Parameter Estimation (PEST) and geostatistical pilot point methods were employed to estimate hydraulic conductivity and specific yield values. The results show that the model is able to represent the sub-surface flow indicated by good model performances both in calibration and validation steps. The final model can be used as a robust representation of the system for future study on climate and land use scenarios.

Keywords: carbonate aquifer, karst, sub-surface flow, groundwater model

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Authors: Nihad Chakri, Btissam El Amrani, Faouzi Berrada, Fouad Amraoui

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In Morocco, water scarcity requires the exploitation of non-conventional resources. Rural areas are under-equipped with sanitation infrastructure, unlike urban areas. Decentralized and low-cost solutions could improve the quality of life of the population and the environment. In this context, the Faculty of Sciences Ain Chock "FSAC" has undertaken an integrated project to treat part of its wastewater using a decentralized compact system. The project will propose alternative solutions that are inexpensive and adapted to the context of peri-urban and rural areas in order to treat the wastewater generated and use it for irrigation, watering, and cleaning. For this purpose, several tests were carried out in the laboratory in order to develop a liquid waste treatment system optimized for local conditions. Based on the results obtained at the laboratory scale of the different proposed scenarios, we designed and implemented a prototype of a mini wastewater treatment plant for the Faculty. In this article, we will outline the steps of dimensioning, construction, and monitoring of the mini-station in our Faculty.

Keywords: wastewater, purification, optimization, vertical filter, MBBR process, sizing, decentralized pilot, reuse, irrigation, sustainable development

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Authors: Leanda Denise Mason, Philip William Bateman, Grant Wardell-Johnson

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Ecological traps attract biota to low-quality habitats. Landscape traps are zones caught in a vortex of spiraling degradation. Here, we demonstrate how short-range endemic traits may make such taxa vulnerable to ecological and landscape traps. Three short-range endemic mygalomorph spider species were used in this study. Mygalomorphs can be long-lived ( > 40 years) and select sites for permanent burrows in their early dispersal phase. Spiderlings from two species demonstrated choice for microhabitats that correspond to where adults typically occur. An invasive veldt grass microhabitat was selected almost exclusively by spiderlings of the third species. Habitat dominated by veldt grass has lower prey diversity and abundance than undisturbed habitats and therefore acts as an ecological trap for this species. Furthermore, as a homogenising force, veldt grass can spread to form a landscape trap in naturally heterogeneous ecosystems. Selection of specialised microhabitats of short-range endemics may explain high extinction rates in old, stable landscapes undergoing (human-induced) rapid change.

Keywords: biotic homogenization, invasive species, mygalomorph, short-range endemic

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Authors: Mehdi Shahbazian, Alireza Aarabi, Mohsen Hadiyan

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Proportional-Integral-Derivative (PID) controllers are the most widely used controllers in industry because of its simplicity and robustness. Different values of PID parameters make different step response, so an increasing amount of literature is devoted to proper tuning of PID controllers. The problem merits further investigation as traditional tuning methods make large control signal that can damages the system but using evolutionary algorithms based tuning methods improve the control signal and closed loop performance. In this paper three tuning methods for PID controllers have been studied namely Ziegler and Nichols, which is traditional tuning method and evolutionary algorithms based tuning methods, that are, Genetic algorithm and particle swarm optimization. To examine the validity of PSO and GA tuning methods a comparative analysis of DC motor plant is studied. Simulation results reveal that evolutionary algorithms based tuning method have improved control signal amplitude and quality factors of the closed loop system such as rise time, integral absolute error (IAE) and maximum overshoot.

Keywords: evolutionary algorithm, genetic algorithm, particle swarm optimization, PID controller

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Authors: Mohammad Reza Babaei, Sanaz Kamrani

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The main problems That arise In adopting most Enterprise resources planning (ERP) strategies come from organizational, complex information systems like the ERP integrate the data of all business areas within the organization. The implementation of ERP is a difficult process as it involves different types of end users. Based on literature, we proposed a conceptual framework and examined it to find the effect of some of the individual, organizational, and technological factors on the usage of ERP and its impact on the end user. The results of the analysis suggest that computer self-efficacy, organizational support, training, and compatibility have a positive influence on ERP usage which in turn has significant influence on panoptic empowerment and individual performance.

Keywords: factor, influencing, enterprise, system

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Authors: Yashasvi Thakur, Vikas K. Sharma

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The fragile Himalayan ecosystems are sensitive to environmental stresses, including direct and indirect impacts of climate stresses. A total of 297 naturalized alien plant species belonging to 65 families in the IHR have already been reported. Of the total 297 naturalized alien plant species in IHR, the maximum species occur in Himachal Pradesh (232; 78.1%), followed by Jammu & Kashmir (192; 64.6%) and Uttarakhand (181; 60.90%). The present study reports the spread of some invasive and existing weed species like Ageratum conyzoides, Bidens pilosa, Chromolaena odorata, Lantana camara, Brossnetia papyrifera, Oxalis corniculata, Galinsoga parviflora, Panicum maximum at an extent that they are not only invading the agricultural fields but are also replacing the native plant species and degrading the existing grassland quality. Moreover, the degradation of grassland has led to the dry fodder shortage for livestock in the lower Shivalik ranges of the state of Himachal Pradesh and has also encouraged the use of herbicides at an extensive scale. This article provides a mapping of the current spread of some of these species at the block level to allow the development of appropriate management strategies and policy planning for addressing issues pertaining to plant invasion, agricultural fields, and grasslands across the IHR states.

Keywords: climate change, invasive alien species, agriculture, grassland, IHR

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Authors: S. S. Dol, M. S. Chan, S. F. Wong, J. S. Lim

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Emulsion formation is unavoidable and can be detrimental to an oil field production. The presence of stable emulsions also reduces the quality of crude oil and causes more problems in the downstream refinery operations, such as corrosion and pipeline pressure drop. Hence, it is important to know the effects of emulsions in the pipeline. Light crude oil was used for the continuous phase in the W/O emulsions where the emulsions pass through a flow loop to test the pressure drop across the pipeline. The results obtained shows that pressure drop increases as water cut is increased until it peaks at the phase inversion of the W/O emulsion between 30% to 40% water cut. Emulsions produced by gradual constrictions show a lower stability as compared to sudden constrictions. Lower stability of emulsions in gradual constriction has the higher influence of pressure drop compared to a sudden sharp decrease in diameter in sudden constriction. Generally, sudden constriction experiences pressure drop of 0.013% to 0.067% higher than gradual constriction of the same ratio. Lower constriction ratio cases cause larger pressure drop ranging from 0.061% to 0.241%. Considering the higher profitability in lower emulsion stability and lower pressure drop at the developed flow region of different constrictions, an optimum design of constriction is found to be gradual constriction with a ratio of 0.5.

Keywords: constriction, pressure drop, turbulence, water-in-oil emulsions

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Authors: N. Khater, S. A. Menina, H. Benbouza

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Juniperus thurefera is an endemic cupressacée constitutes a forest cover in the mountains of Aures (Algeria). It is a heritage and important ecological richness but continues to decline, highly endangered species in danger of extinction, these populations show significant originality due to climatic conditions of the environment, because of its strength and extraordinary vitality, made a powerful but fragile and unique ecosystem in which natural regeneration by seed is almost absent in Algeria. Because of the quality of seeds that are either dormant or affected at the tree and the ground level by a large number of pests and parasites, which will lead to the total disappearance of this species and consequently leading to the biodiversity. View the ecological and socio- economic interest presented by this case, it deserves to be preserved and produced in large quantities in this respect. The present work aims to try to regenerate the Juniperus thurefera via vegetative propagation. We studied the potential of cuttings to form adventitious roots and buds. Cuttings were taken from young subjects from 5 to 20 years treated with indole butyric acid (AIB) and planted out-inside perlite under atomizer whose temperature and light are controlled. Results indicated that the percentage of developing buds on cuttings is better than the rooting ones.

Keywords: Juniperus thurefera, indole butyric acid, cutting, buds, rooting

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Authors: Bonguen Onouck Rolande Carole, Ndongo Barthelemy

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The climate change effects on the Lake Chad, coupled with population growth, have pushed large masses of people of various origins towards the lower part of the lower Logonewatershed in search of the benefits of environmental services, causing pressure on the environment and its resources. Economic services are therefore threatened, and the decrease in resources contributes to the deterioration of the social wellbeing resulting to conflicts among/between local communities, immigrants, displaced people, and foreigners. This paper is an information contribution on ethnical conflicts drivers in the area and the provided local management mechanisms such can help mitigate present or future conflicts in similar areas. It also prints out the necessity to alleviate water access deficit and encourage good practices for the population wellbeing. In order to meet the objective, in 2018, through the interface of the World Bank-Cameroon project-PULCI, data were collected on the field directly by discussing with the population and visiting infrastructures, indirectly by a questionnaire survey. Two administrative divisions were chosen (Logoneet Chari, Mayo-Danay) in which targeted localities were Zina, Mazera, Lahai, Andirni near the Waza Park and Yagoua, Tekele, Pouss, respectively. Due to some sociocultural and religious reasons, some information were acquired through the traditional chiefs. A desk study analysis based on resources access and availability conflicts history, and management mechanism was done. As results, roots drivers of ethnical conflicts are struggles over natural resources access, and the possibility of conflicts increases as the scarcity and vulnerabilities persist, creating more sociocultural gaps and tensions. The mitigation mechanisms though fruitful, are limited. There is poor documentation on the topic, the resources management policies of this basin are unsuitable and ineffective for some. Therefore, the restoration of environmental and ecosystems, the mitigation of climate change effects, and food insecurity are the challenges that must be met to alleviate conflicts in these localities.

Keywords: ethnic, communities, conflicts, mitigation mechanisms, natural resources, logone basin

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Authors: Vedi Goenka

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Inequality refers to unequal treatment or perceptions of individuals based on any particular trait. It arises from differences in socially constructed roles. Women are usually characterized as inferior and weak, who are dependent on their male counterparts. Even though it is claimed that both the genders have been given equal rights, inequality has always been prevalent in the Indian society, from personal to the professional front. There are different types of inequality that persist in the corporate world such as age inequality, gender inequality, tenure inequality and so on. Consequently, wage inequality occurs when employees are equally qualified and perform the same task but, one group of employees is paid more than the other. The hospitality sector is one of the emerging sectors in Gujarat which also experiences a lot of organizational dynamics. The proposed paper focuses on the concept of equal pay which states that pay should be based on the kind and quality of work done and not according to any other aspects. An exploratory attempt to understand the existence of inequality in the Hospitality sector on the basis of income is made in this research. The myth that wage discrimination has always favored men over similarly qualified women is analyzed in this research paper. A structured survey of a sample, representative of the employees of the Hospitality sector is being carried out in this study. An attempt to keep the effects of the environmental factors to a minimum level is made.

Keywords: equal pay, human resources, hospitality sector, inequality, perspective, wage structure

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Authors: Victor Bloch, Eerikki Kaila, Reetta Palva

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Field robots are an important tool for enhancing efficiency and decreasing the climatic impact of food production. There exists a number of commercial field robots; however, since this technology is still new, the robot advantages and limitations, as well as methods for optimal using of robots, are still unclear. In this study, the performance of a commercial field robot for seeding and weeding was assessed. A research 2-ha sugar beet field with 0.5m row width was used for testing, which included robotic sowing of sugar beet and weeding five times during the first two months of the growing. About three and five percent of the field were used as untreated and chemically weeded control areas, respectively. The plant detection was based on the exact plant location without image processing. The robot was equipped with six seeding and weeding tools, including passive between-rows harrow hoes and active hoes cutting inside rows between the plants, and it moved with a maximal speed of 0.9 km/h. The robot's performance was assessed by image processing. The field images were collected by an action camera with a height of 2 m and a resolution 27M pixels installed on the robot and by a drone with a 16M pixel camera flying at 4 m height. To detect plants and weeds, the YOLO model was trained with transfer learning from two available datasets. A preliminary analysis of the entire field showed that in the areas treated by the robot, the weed average density varied across the field from 6.8 to 9.1 weeds/m² (compared with 0.8 in the chemically treated area and 24.3 in the untreated area), the weed average density inside rows was 2.0-2.9 weeds / m (compared with 0 on the chemically treated area), and the emergence rate was 90-95%. The information about the robot's performance has high importance for the application of robotics for field tasks. With the help of the developed method, the performance can be assessed several times during the growth according to the robotic weeding frequency. When it’s used by farmers, they can know the field condition and efficiency of the robotic treatment all over the field. Farmers and researchers could develop optimal strategies for using the robot, such as seeding and weeding timing, robot settings, and plant and field parameters and geometry. The robot producers can have quantitative information from an actual working environment and improve the robots accordingly.

Keywords: agricultural robot, field robot, plant detection, robot performance

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Authors: Fatemeh Yazdani

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This paper explores the student intake policies in high-performing private schools in Iran by studying both sides involved in the school choice processes, parents and the school leaders. It is based on in-depth interviews with 27 parents and private schools’ staff and principals supplemented by ethnographic observation in two private schools in Tehran. From the Bourdieusian point of view, this paper argues that the school leadership engineers the composition of private schools’ students via different gatekeeping strategies, and these strategies represent and reconstruct the school’s institutional habitus. It further explores the ways that parents who look for quality education among non-state education providers deal with the school's institutional habitus based on their familial habitus and possessed economic, social, and cultural capital. The conclusion highlights that investigating school choice as a reciprocal process between family and school leadership can shed more light on the ways that an exclusive environment has been created in some high-performing private schools for certain class strata maintaining a distance that needs to be kept from ‘others.’ In a broader sense, this paper engages into an exploration of social inequality reproduction through private education.

Keywords: institutional habitus, private education, school choice, social inequality, student intake

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Authors: Yasaman Ashrafi, Stephen Kajewski, Annastiina Silvennoinen, Madhav Nepal

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Mega projects either in construction, urban development or energy sectors are one of the key drivers that build the foundation of wealth and modern civilizations in regions and nations. Such projects require economic justification and substantial capital investment, often derived from individual and corporate investors as well as governments. Cost overruns and time delays in these mega projects demands a new approach to more accurately predict project costs and establish realistic financial plans. The significance of this paper is that the cost efficiency of megaprojects will improve and decrease cost overruns. This research will assist Project Managers (PMs) to make timely and appropriate decisions about both cost and outcomes of ongoing projects. This research, therefore, examines the oil and gas industry where most mega projects apply the classic methods of Cost Performance Index (CPI) and Schedule Performance Index (SPI) and rely on project data to forecast cost and time. Because these projects are always overrun in cost and time even at the early phase of the project, the probabilistic methods of Monte Carlo Simulation (MCS) and Bayesian Adaptive Forecasting method were used to predict project cost at completion of projects. The current theoretical and mathematical models which forecast the total expected cost and project completion date, during the execution phase of an ongoing project will be evaluated. Earned Value Management (EVM) method is unable to predict cost at completion of a project accurately due to the lack of enough detailed project information especially in the early phase of the project. During the project execution phase, the Bayesian adaptive forecasting method incorporates predictions into the actual performance data from earned value management and revises pre-project cost estimates, making full use of the available information. The outcome of this research is to improve the accuracy of both cost prediction and final duration. This research will provide a warning method to identify when current project performance deviates from planned performance and crates an unacceptable gap between preliminary planning and actual performance. This warning method will support project managers to take corrective actions on time.

Keywords: cost forecasting, earned value management, project control, project management, risk analysis, simulation

Procedia PDF Downloads 379