Search results for: writing task

Authors: Damien Mouratille, Antonio R. Hidalgo-Muñoz, Nadine Matton, Yves Rouillard, Mickael Causse, Radouane El Yagoubi

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Background: The monitoring of the physiological activity related to mental workload (MW) on pilots will be useful to improve aviation safety by anticipating human performance degradation. The electrocardiogram (ECG) can reveal MW fluctuations due to either cognitive workload or/and emotional state since this measure exhibits autonomic nervous system modulations. Arguably, heart rate (HR) is one of its most intuitive and reliable parameters. It would be particularly interesting to analyze the interaction between cognitive requirements and emotion in ecologic sets such as a flight simulator. This study aims to explore by means of HR the relation between cognitive demands and emotional activation. Presumably, the effects of cognition and emotion overloads are not necessarily cumulative. Methodology: Eight healthy volunteers in possession of the Private Pilot License were recruited (male; 20.8±3.2 years). ECG signal was recorded along the whole experiment by placing two electrodes on the clavicle and left pectoral of the participants. The HR was computed within 4 minutes segments. NASA-TLX and Big Five inventories were used to assess subjective workload and to consider the influence of individual personality differences. The experiment consisted in completing two dual-tasks of approximately 30 minutes of duration into a flight simulator AL50. Each dual-task required the simultaneous accomplishment of both a pre-established flight plan and an additional task based on target stimulus discrimination inserted between Air Traffic Control instructions. This secondary task allowed us to vary the cognitive workload from low (LC) to high (HC) levels, by combining auditory and visual numerical stimuli to respond to meeting specific criteria. Regarding emotional condition, the two dual-tasks were designed to assure analogous difficulty in terms of solicited cognitive demands. The former was realized by the pilot alone, i.e. Low Arousal (LA) condition. In contrast, the latter generates a high arousal (HA), since the pilot was supervised by two evaluators, filmed and involved into a mock competition with the rest of the participants. Results: Performance for the secondary task showed significant faster reaction times (RT) for HA compared to LA condition (p=.003). Moreover, faster RT was found for LC compared to HC (p < .001) condition. No interaction was found. Concerning HR measure, despite the lack of main effects an interaction between emotion and cognition is evidenced (p=.028). Post hoc analysis showed smaller HR for HA compared to LA condition only for LC (p=.049). Conclusion. The control of an aircraft is a very complex task including strong cognitive demands and depends on the emotional state of pilots. According to the behavioral data, the experimental set has permitted to generate satisfactorily different emotional and cognitive levels. As suggested by the interaction found in HR measure, these two factors do not seem to have a cumulative impact on the sympathetic nervous system. Apparently, low cognitive workload makes pilots more sensitive to emotional variations. These results hint the independency between data processing and emotional regulation. Further physiological data are necessary to confirm and disentangle this relation. This procedure may be useful for monitoring objectively pilot’s mental workload.

Keywords: cognitive demands, emotion, flight simulator, heart rate, mental workload

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Authors: Selina Studer, Maria Kleinstäuber, Cornelia Weise

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Background: Finding words to report what you have been through may be challenging, especially when dealing with stressful or highly emotional experiences. Photovoice (PV) represents a possible way of facilitating experience reporting. In this approach, people take photos about a particular topic (in our study: worries about the future) and talk about the topic based on the photos. So far, the benefits of Photovoice have been quantitatively insufficiently tested. There is a lack of randomized controlled trials investigating PV in comparison to other methods. This study aimed to fill this research gap. Methods: 65 participants took part in the study and were randomly assigned to the PV group, the writing group (WG), or the control group (CG). The PV group received the task to take photos of worries regarding the future for one week and send max. 5 of them to the interviewer before the interview. The WG had to write down the worries about the future and send max. 5 of them to the interviewer before the interview. The control group did not receive a specific assignment. The semi-structured interview consisted of six open-ended questions and was applied to all future worries. The questions included the content of the future worries, the meaning, and how the worry expressed itself emotionally and physically. The interview was recorded and later transcribed. After the interview, online questionnaires were filled out. They covered a range of variables such as access to emotional content, ability to describe feelings, the extent of self-disclosure, and relationship quality. Results: Contrary to our hypotheses, one-way ANOVA revealed no differences between the three conditions concerning all variables (access to emotional content, ability to describe feelings, the extent of self-disclosure, and so on), all p's > 0.14, BF₀₁ = 1.78-7.66. In a subsequent step, the words in the transcribed interviews were analyzed. The LIWC program counted how many emotional words occurred in the text and assigned them to predefined categories. Planned contrasts revealed that the PV reported more negative emotional words compared to the two groups t(62) = 2.62, p = .011, and also compared to the WG only, t(62) = 2.36, p = .022, BF₀₁ = 0.62. Conclusions and implications: The applied self-report instruments did not reveal any differences between the groups. However, the PV group used more negative emotional words than the other two groups. The discrepancy between self-report and observation variables regarding emotionality is noticeable. It is suggested that the highly educated and above-average female sample may not have needed PV to access emotional content. It is possible that the approach would yield clearer results in a clinical sample. This and other approaches are currently being investigated in a follow-up study.

Keywords: photovoice, controlled randomized study, online intervention, emotional awareness, self-disclosure, data triangulation, interviews

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Authors: Mariane G. Tadros, Shahira M. Ezzat, Maha M. Salama, Mohamed A. Farag

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In this study, the in vitro anticholinesterase activity of the volatile oils of both O. basilicum and O. africanum was investigated and both samples showed significant activity. As a result, the major constituents of the two oils were isolated using several column chromatography. Linalool, 1,8-cineol and eugenol were isolated from the volatile oil of O. basilicum and camphor was isolated from the volatile oil of O. africanum. The anticholinesterase activity of the isolated compounds were also evaluated where 1,8-cineol showed the highest inhibitory activity followed by camphor. To confirm these activities, learning and memory enhancing effects were tested in mice. Memory impairment was induced by scopolamine, a cholinergic muscarinic receptor antagonist. Anti-amnesic effects of both volatile oils and their terpenoids were investigated by the passive avoidance task in mice. We also examined their effects on brain acetylcholinesterase activity. Results showed that scopolamine-induced cognitive dysfunction was significantly attenuated by administration of the volatile oils and their terpenoids, eugenol and camphor, in the passive avoidance task and inhibited brain acetylcholinesterase activity. These results suggest that O. basilicum and O. africanum volatile oils can be good candidates for further studies on Alzheimer’s disease via their acetylcholinesterase inhibitory actions.

Keywords: Ocimum baselicum, Ocimum africanum, GC/MS analysis, anticholinesterase

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Authors: Arunai Nambi Raj N., Kaviarasu Karunakaran, Krishnamurthy K.

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The purpose of this study was to create American Association of Physicist in Medicine (AAPM) Task Group 119 (TG 119) benchmark plans for flattening filter free beam (FFF) deliveries of intensity modulated radiation therapy (IMRT) and volumetric arc therapy (VMAT) in the Eclipse treatment planning system. The planning data were compared with the flattening filter (FF) IMRT & VMAT plan data to verify the dosimetric commissioning accuracy of FFF deliveries. AAPM TG 119 proposed a set of test cases called multi-target, mock prostate, mock head and neck, and C-shape to ascertain the overall accuracy of IMRT planning, measurement, and analysis. We used these test cases to investigate the performance of the Eclipse Treatment planning system for the flattening filter free beam deliveries. For these test cases, we generated two sets of treatment plans, the first plan using 7–9 IMRT fields and a second plan utilizing two arc VMAT technique for both the beam deliveries (6 MV FF, 6MV FFF, 10 MV FF and 10 MV FFF). The planning objectives and dose were set as described in TG 119. The dose prescriptions for multi-target, mock prostate, mock head and neck, and C-shape were taken as 50, 75.6, 50 and 50 Gy, respectively. The point dose (mean dose to the contoured chamber volume) at the specified positions/locations was measured using compact (CC‑13) ion chamber. The composite planar dose and per-field gamma analysis were measured with IMatriXX Evaluation 2D array with OmniPro IMRT Software (version 1.7b). FFF beam deliveries of IMRT and VMAT plans were comparable to flattening filter beam deliveries. Our planning and quality assurance results matched with TG 119 data. AAPM TG 119 test cases are useful to generate FFF benchmark plans. From the obtained data in this study, we conclude that the commissioning of FFF IMRT and FFF VMAT delivery were found within the limits of TG-119 and the performance of the Eclipse treatment planning system for FFF plans were found satisfactorily.

Keywords: flattening filter free beams, intensity modulated radiation therapy, task group 119, volumetric modulated arc therapy

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Authors: Nuraddeen Usman, Khiruddin Abdullah, Mohd Nawawi, Amin Khalil Ismail

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A magnetic survey is carried out in order to locate the remains of construction items, specifically concrete pillars. The conventional Euler deconvolution technique can perform the task but it requires the use of fixed structural index (SI) and the construction items are made of materials with different shapes which require different SI (unknown). A Euler deconvolution technique that estimate background, horizontal coordinate (xo and yo), depth and structural index (SI) simultaneously is prepared and used for this task. The synthetic model study carried indicated the new methodology can give a good estimate of location and does not depend on magnetic latitude. For field data, both the total magnetic field and gradiometer reading had been collected simultaneously. The computed vertical derivatives and gradiometer readings are compared and they have shown good correlation signifying the effectiveness of the method. The filtering is carried out using automated procedure, analytic signal and other traditional techniques. The clustered depth solutions coincided with the high amplitude/values of analytic signal and these are the possible target positions of the concrete pillars being sought. The targets under investigation are interpreted to be located at the depth between 2.8 to 9.4 meters. More follow up survey is recommended as this mark the preliminary stage of the work.

Keywords: concrete pillar, magnetic survey, geotechnical investigation, Euler Deconvolution

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Authors: Yi-Hsuan Gloria Lo

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The educational objective of vocational high schools (VHSs) is to equip VHS students with practical skills and knowledge that can be applied in the job-related market. However, with the increasing number of technological universities over the past two decades, the majority of VHS students have chosen to receive higher education rather than enter the job market. VHS English education has been confronting a dilemma: Should an English for specific purposes (ESP) approach, which aligns with the educational goal of VHS education, be taken or should an English for general purposes (EGP) approach, which prepares VHS students for advanced studies in universities, be followed? While ESP theorists proposed that that ESP can be taught to secondary learners, little was known about VHS students’ perspective on this ESP-versus-EGP dilemma. Scant research has investigated different facets of students’ needs (necessities, wants, and lacks) for both ESP and EGP in terms of the four language skills and the factors that contribute to any differences. To address the gap in the literature, 100 VHS students responded to statements related to their necessities, wants, and lacks in learning ESP and EGP on a 6-point Likert scale. Six VHS students were interviewed to tap into the reasons for different facets of the needs for learning EGP and ESP. The statistical analysis indicates that at this stage of learning English, VHS subjects believed that EGP was more necessary than ESP; EGP was more desirable than ESP. However, they reported that they were more lacking in ESP than in EGP learning. Regarding EGP, the results show that the VHS subjects rated speaking as their most necessary skill, speaking as the most desirable skill, and writing as the most lacking skill. A significant difference was found between perceived learning necessities and lacks and between perceived wants and lacks. No statistical difference was found between necessities and wants. In the aspect of ESP, the results indicate that the VHS subjects marked reading as their most necessary skill, speaking as the most desirable skill, and writing as the most lacking skill. A significant difference exists between their perceived necessities and lacks and between their wants and lacks. However, there is no statistically significant difference between their perceived lacks and wants. Despite the lack of a significant difference between learning necessities and wants, the qualitative interview data reveal that the reasons for their perceived necessities and wants were different. The findings of the study confirm previous research that demonstrates that ‘needs’ is a multiple and conflicting construct. What VHS students felt most lacking was not necessarily what they believed they should learn or would like to learn. Although no statistical difference was found, different reasons were attributed to their perceived necessities and wants. Both theoretical and practical implications have been drawn and discussed for ESP research in general and teaching ESP in VHSs in particular.

Keywords: vocational high schools (VHSs), English for General Purposes (EGP), English for Specific Purposes (ESP), needs analysis

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Authors: Alvaro Javier Ortega

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A large number of companies face the challenge of matching highly-skilled professionals to high-end positions by human resource deployment professionals. However, when the professional list and tasks to be matched are larger than a few dozens, this process result is far from optimal and takes a long time to be made. Therefore, an automated assignment algorithm for this workforce management problem is needed. The majority of companies are divided into several sectors or departments, where trained employees with different experience levels deal with a large number of tasks daily. Also, the execution order of all tasks is of mater consequence, due to some of these tasks just can be run it if the result of another task is provided. Thus, a wrong execution order leads to large waiting times between consecutive tasks. The desired goal is, therefore, creating accurate matches and a near-optimal execution order that maximizes the number of tasks performed and minimizes the idle time of the expensive skilled employees. The problem described before can be model as a mixed-integer non-linear programming (MINLP) as it will be shown in detail through this paper. A large number of MINLP algorithms have been proposed in the literature. Here, genetic algorithm solutions are considered and a comparison between two different mutation approaches is presented. The simulated results considering different complexity levels of assignment decisions show the appropriateness of the proposed model.

Keywords: employees, genetic algorithm, industry management, workforce

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Authors: Seokbeen Lim, Gilwon Yoon

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The readiness potential in brain waves is a brain activity related with an intention whose potential arises even before its conscious intention. This study was carried out in order to understand the generation and mechanism of the readiness potential more. The experiment with two subjects was conducted in two ways following the Oddball task protocol. Firstly, auditory stimuli were randomly presented to the subjects. The subject was allowed to press the keyboard with the right index finger only when the subject heard the target stimulus but not the standard stimulus. Secondly, unlike the first one, the auditory stimuli were randomly presented, and the subjects pressed the keyboard in the same manner, but at the same time with grasping action of the left hand. The readiness potential showed up for both of these experiments. In the first Oddball experiment, the readiness potential was detected only when the target stimulus was presented. However, in the second Oddball experiment with the left hand action of grasping something, the readiness potential was detected at the presentation of for both standard and target stimuli. However, detected readiness potentials with the target stimuli were larger than those of the standard stimuli. We found an interesting phenomenon that the readiness potential was able to be detected even the standard stimulus. This indicates that motor-related readiness potentials can be generated only by the intention to move. These results present a new perspective in psychology and brain engineering since subconscious brain action may be prior to conscious recognition of the intention.

Keywords: readiness potential, auditory stimuli, event-related potential, electroencephalography, oddball task

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Authors: X. Laurent, M. A. Estevez, P. Mari-Beffa

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A focus of recent research is to understand the role of our own response goals in the selection of information that will be encoded in episodic memory. For example, if we respond to a target in the presence of distractors, an important aspect under study is whether the distractor and the target share a common response (compatible) or not (incompatible). Some studies have found that compatible objects tend to be groups together and stored in episodic memory, whereas others found that targets in the presence of incompatible distractors are remembered better. Our current research seems to support both views. We used a Tulving-based definition of episodic memory to differentiate memory from episodic and non-episodic traces. In this task, participants first had to classify a blue object as human or animal (target) which appeared in the presence of a green one (distractor) that could belong to the same category of the target (compatible), to the opposite (incompatible) or to an irrelevant one (neutral). Later they had to report the identity (What), location (Where) and time (When) of both target objects (which had been previously responded to) and distractors (which had been ignored). Episodic memory was inferred when the three scene properties (identity, location and time) were correct. The measure of non-episodic memory consisted of those trials in which the identity was correctly remembered, but not the location or time. Our results showed that episodic memory for compatible stimuli is significantly superior to incompatible ones. In sharp contrast, non-episodic measures found superior memory for targets in the presence of incompatible distractors. Our results demonstrate that response compatibility affects the encoding of episodic and non-episodic memory traces in different ways.

Keywords: episodic memory, action systems, compatible response, what-where-when task

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Authors: Yu-Chi Liao, Nai-Wen Guo, Chun‑Hung Lee, Yung-Chin Lu, Cheng-Hung Ko

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Objective: The incidence of behavioral addictions, especially substance use disorders (SUDs), is gradually be taken seriously with various physical health problems. Mindfulness-based relapse prevention (MBRP) is a treatment option for promoting long-term health behavior change in recent years. MBRP is a structured protocol that integrates formal meditation practices with the cognitive-behavioral approach of relapse prevention treatment by teaching participants not to engage in reappraisal or savoring techniques. However, considering SUDs as a complex brain disease, questionnaires and symptom evaluation are not sufficient to evaluate the effect of MBRP. Neurophysiological biomarkers such as quantitative electroencephalogram (QEEG) may improve accurately represent the curative effects. This study attempted to find out the neurophysiological indicator of MBRP in various severity SUD involuntary clients. Participants and Methods: Thirteen participants (all males) completed 8-week mindfulness-based treatment provided by trained, licensed clinical psychologists. The behavioral data were from the Severity of Dependence Scale (SDS) and Negative Mood Regulation Scale (NMR) before and afterMBRP treatment. The QEEG data were simultaneously recorded with executive attention tasks, called comprehensive nonverbal attention test(CNAT). The two-way repeated-measures (treatment * severity) ANOVA and independent t-test were used for statistical analysis. Results: Thirteen participants regrouped into high substance dependence (HS) and low substance dependence (LS) by SDS cut-off. The HS group showed more SDS total score and lower gamma wave in the Go/No Go task of CNAT at pretest. Both groups showed the main effect that they had a lower frontal theta/beta ratio (TBR) during the simple reaction time task of CNAT. The main effect showed that the delay errors of CNAT were lower after MBRP. There was no other difference in CNAT between groups. However, after MBRP, compared to LS, the HS group have resonant progress in improving SDS and NMR scores. The neurophysiological index, the frontal TBR of the HS during the Go/No Go task of CNATdecreased than that of the LS group. Otherwise, the LS group’s gamma wave was a significant reduction on the Go/No Go task of CNAT. Conclusion: The QEEG data supports the MBRP can restore the prefrontal function of involuntary addicts and lower their errors in executive attention tasks. However, the improvement of MBRPfor the addict with high addiction severity is significantly more than that with low severity, including QEEG’s indicators and negative emotion regulation. Future directions include investigating the reasons for differences in efficacy among different severity of the addiction.

Keywords: mindfulness, involuntary clients, QEEG, emotion regulation

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Authors: Faishal Muhammad, Erlinda Muslim, Nadia Faradilla, Sayidul Fikri

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To deal with the increase of mass transportation needs problem, PT. Kereta Commuter Jabodetabek (KCJ) implements Commuter Vending Machine (C-VIM) as the solution. For that background, C-VIM is implemented as a substitute to the conventional ticket windows with the purposes to make transaction process more efficient and to introduce self-service technology to the commuter line user. However, this implementation causing problems and long queues when the user is not accustomed to using the machine. The objective of this research is to evaluate user experience after using the commuter vending machine. The goal is to analyze the existing user experience problem and to achieve a better user experience design. The evaluation method is done by giving task scenario according to the features offered by the machine. The features are daily insured ticket sales, ticket refund, and multi-trip card top up. There 20 peoples that separated into two groups of respondents involved in this research, which consist of 5 males and 5 females each group. The experienced and inexperienced user to prove that there is a significant difference between both groups in the measurement. The user experience is measured by both quantitative and qualitative measurement. The quantitative measurement includes the user performance metrics such as task success, time on task, error, efficiency, and learnability. The qualitative measurement includes system usability scale questionnaire (SUS), questionnaire for user interface satisfaction (QUIS), and retrospective think aloud (RTA). Usability performance metrics shows that 4 out of 5 indicators are significantly different in both group. This shows that the inexperienced group is having a problem when using the C-VIM. Conventional ticket windows also show a better usability performance metrics compared to the C-VIM. From the data processing, the experienced group give the SUS score of 62 with the acceptability scale of 'marginal low', grade scale of “D”, and the adjective ratings of 'good' while the inexperienced group gives the SUS score of 51 with the acceptability scale of 'marginal low', grade scale of 'F', and the adjective ratings of 'ok'. This shows that both groups give a low score on the system usability scale. The QUIS score of the experienced group is 69,18 and the inexperienced group is 64,20. This shows the average QUIS score below 70 which indicate a problem with the user interface. RTA was done to obtain user experience issue when using C-VIM through interview protocols. The issue obtained then sorted using pareto concept and diagram. The solution of this research is interface redesign using activity relationship chart. This method resulted in a better interface with an average SUS score of 72,25, with the acceptable scale of 'acceptable', grade scale of 'B', and the adjective ratings of 'excellent'. From the time on task indicator of performance metrics also shows a significant better time by using the new interface design. Result in this study shows that C-VIM not yet have a good performance and user experience.

Keywords: activity relationship chart, commuter line vending machine, system usability scale, usability performance metrics, user experience evaluation

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Authors: Derya Duran, Christine Jacknick

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This study explores post-task reflections in an English as a Medium of Instruction (EMI) setting, and it specifically focuses on how a teacher performs pedagogical practices such as reformulating, extending and evaluating following students’ spontaneous experience tellings in EMI classrooms. The data consist of 30 hours of video recordings from two EMI content classes, which were recorded for an academic term at a university in Turkey. The course, Guidance, is offered to fourth year undergraduate students as a compulsory course in the Department of Educational Sciences. The participants (n=78) study at the Faculty of Education, majoring in different educational departments (i.e., Computer Education and Instructional Technology, Elementary Education, Foreign Language Education). Using conversation analysis, we demonstrate that the teacher employs a variety of interactional resources to elicit (i.e., asking specific questions) and also provides (i.e., giving scientific information) as much content as possible, which also sheds light on the institutional fingerprints of the current research context. The study contributes to the existing research by unpacking articulation of personal experiences and cultivation of collaborativeness in classroom interaction. Moreover, describing the dialogic nature of these specific occasions, the study demonstrates how teacher and students address learning tasks together (collectivity), how they orient to each other turns interactionally (reciprocity), and how they keep the pedagogical focus in mind (purposefulness).

Keywords: conversation analysis, English as a medium of instruction, higher education, post-task reflections

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Authors: C. Manjula, Lilly Florence

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Software technology is developing rapidly which leads to the growth of various industries. Now-a-days, software-based applications have been adopted widely for business purposes. For any software industry, development of reliable software is becoming a challenging task because a faulty software module may be harmful for the growth of industry and business. Hence there is a need to develop techniques which can be used for early prediction of software defects. Due to complexities in manual prediction, automated software defect prediction techniques have been introduced. These techniques are based on the pattern learning from the previous software versions and finding the defects in the current version. These techniques have attracted researchers due to their significant impact on industrial growth by identifying the bugs in software. Based on this, several researches have been carried out but achieving desirable defect prediction performance is still a challenging task. To address this issue, here we present a machine learning based hybrid technique for software defect prediction. First of all, Genetic Algorithm (GA) is presented where an improved fitness function is used for better optimization of features in data sets. Later, these features are processed through Decision Tree (DT) classification model. Finally, an experimental study is presented where results from the proposed GA-DT based hybrid approach is compared with those from the DT classification technique. The results show that the proposed hybrid approach achieves better classification accuracy.

Keywords: decision tree, genetic algorithm, machine learning, software defect prediction

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Authors: Ben Mansour Mouin, Elloumi Abdelkarim

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We will discuss the problem of routing a fleet of different vehicles from a central depot to different types of infrastructure-defaults with dynamic maintenance requests, modified time windows, and control of default maintained. For this reason, we propose a modified metaheuristicto to solve our mathematical model. SVRDP-CMTW is a variant VRP of an optimal vehicle plan that facilitates the maintenance task of different types of infrastructure-defaults. This task will be monitored after the maintenance, based on its priorities, the degree of danger associated with each default, and the neighborhood at the black-spots. We will present, in this paper, a multidimensional genetic algorithm “MGA” by detailing its characteristics, proposed mechanisms, and roles in our work. The coding of this algorithm represents the necessary parameters that characterize each infrastructure-default with the objective of minimizing a combination of cost, distance and maintenance times while satisfying the priority levels of the most urgent defaults. The developed algorithm will allow the dynamic integration of newly detected defaults at the execution time. This result will be displayed in our programmed interactive system at the routing time. This multidimensional genetic algorithm replaces N genetic algorithm to solve P different type problems of infrastructure defaults (instead of N algorithm for P problem we can solve in one multidimensional algorithm simultaneously who can solve all these problemsatonce).

Keywords: mathematical model, VRP, multidimensional genetic algorithm, metaheuristics

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Authors: Jingting Luo, Yong Wang, Ying Wang

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Pedestrian detection in image or video data is a very important and challenging task in security surveillance. The difficulty of this task is to locate and detect pedestrians of different scales in complex scenes accurately. To solve these problems, a deep neural network (RT-YOLOv3) is proposed to realize real-time pedestrian detection at different scales in security monitoring. RT-YOLOv3 improves the traditional YOLOv3 algorithm. Firstly, the deep residual network is added to extract vehicle features. Then six convolutional neural networks with different scales are designed and fused with the corresponding scale feature maps in the residual network to form the final feature pyramid to perform pedestrian detection tasks. This method can better characterize pedestrians. In order to further improve the accuracy and generalization ability of the model, a hybrid pedestrian data set training method is used to extract pedestrian data from the VOC data set and train with the INRIA pedestrian data set. Experiments show that the proposed RT-YOLOv3 method achieves 93.57% accuracy of mAP (mean average precision) and 46.52f/s (number of frames per second). In terms of accuracy, RT-YOLOv3 performs better than Fast R-CNN, Faster R-CNN, YOLO, SSD, YOLOv2, and YOLOv3. This method reduces the missed detection rate and false detection rate, improves the positioning accuracy, and meets the requirements of real-time detection of pedestrian objects.

Keywords: pedestrian detection, feature detection, convolutional neural network, real-time detection, YOLOv3

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Authors: Ibrahim Hassan

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Motion typography is one of the most important types of visual communication based on display. Through the digital display media, we can control the text properties (size, direction, thickness, color, etc.). The use of motion typography in visual communication made it have several images. We need to adjust the terminology and clarify the different differences between them, so relying on the word motion typography -considered a general term- is not enough to separate the different communicative functions of the moving text. In this paper, we discuss the different effects of motion typography on Arabic writing and how we can achieve harmony between the movement and the letterform, and we will, during our experiments, present a new type of text movement.

Keywords: Arabic typography, motion typography, kinetic typography, fluid typography, temporal typography

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Authors: Indu Chandran, Shubham Sharma, Rohan Mehta, Vipin Kizheppatt

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Unmanned aerial vehicles are increasingly being explored as the most promising solution to disaster monitoring, assessment, and recovery. Current relief operations heavily rely on intelligent robot swarms to capture the damage caused, provide timely rescue, and create road maps for the victims. To perform these time-critical missions, efficient path planning that ensures quick coverage of the area is vital. This study aims to develop a technically balanced approach to provide maximum coverage of the affected area in a minimum time using the optimal number of UAVs. A coverage trajectory is designed through area decomposition and task assignment. To perform efficient and autonomous coverage mission, solution to a TSP-based optimization problem using meta-heuristic approaches is designed to allocate waypoints to the UAVs of different flight capacities. The study exploits multi-agent simulations like PX4-SITL and QGroundcontrol through the ROS framework and visualizes the dynamics of UAV deployment to different search paths in a 3D Gazebo environment. Through detailed theoretical analysis and simulation tests, we illustrate the optimality and efficiency of the proposed methodologies.

Keywords: area coverage, coverage path planning, heuristic algorithm, mission monitoring, optimization, task assignment, unmanned aerial vehicles

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Authors: Nadine Sammy, Mark Wilson, Samuel Vine

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The Theory of Challenge and Threat States in Athletes (TCTSA) states that self-efficacy is an antecedent of challenge and threat. These states result from conscious and unconscious evaluations of situational demands and personal resources and are represented by both cognitive and physiological markers. Challenge is considered a more adaptive stress response as it is associated with a more efficient cardiovascular profile, as well as better performance and attention effects compared with threat. Self-efficacy is proposed to influence challenge/threat because an individual’s belief that they have the skills necessary to execute the courses of action required to succeed contributes to a perception that they can cope with the demands of the situation. This study experimentally examined the effects of self-efficacy on cardiovascular responses (challenge and threat), demand and resource evaluations, performance and attention under pressurised conditions. Forty-five university students were randomly assigned to either a control (n=15), low self-efficacy (n=15) or high self-efficacy (n=15) group and completed baseline and pressurised golf putting tasks. Self-efficacy was manipulated using false feedback adapted from previous studies. Measures of self-efficacy, cardiovascular reactivity, demand and resource evaluations, task performance and attention were recorded. The high self-efficacy group displayed more favourable cardiovascular reactivity, indicative of a challenge state, compared with the low self-efficacy group. The former group also reported high resource evaluations, but no task performance or attention effects were detected. These findings demonstrate that levels of self-efficacy influence cardiovascular reactivity and perceptions of resources under pressurised conditions.

Keywords: cardiovascular, challenge, performance, threat

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Authors: Nirit Gavish, Rotem Halutz, Liad Neta

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Nowadays, chatbots are gaining more and more attention due to the advent of large language models. One of the important considerations in chatbot design is how to create an interface to achieve high user satisfaction, trust, and acceptance. Since WhatsApp conversations sometimes substitute for face-to-face communication, we studied whether WhatsAppization of the chatbot -making the conversation resemble a WhatsApp conversation more- will improve user satisfaction, trust, and acceptance, or whether the opposite will occur due to the Uncanny Valley (UV) effect. The task was a drive-sharing task, in which participants communicated with a textual chatbot via WhatsApp and could decide whether to participate in a ride to college with a driver suggested by the chatbot. WhatsAppization of the chatbot was done in two ways: By a dialog-style conversation (Dialog versus No Dialog), and by adding WhatsApp indicators – “Last Seen”, “Connected”, “Read Receipts”, and “Typing…” (Indicators versus No Indicators). Our 120 participants were randomly assigned to one of the four 2 by 2 design groups, with 30 participants in each. They interacted with the WhatsApp chatbot and then filled out a questionnaire. The results demonstrated that, as expected from the manipulation, the interaction with the chatbot was longer for the dialog condition compared to the no dialog. This extra interaction, however, did not lead to higher acceptance -quite the opposite, since participants in the dialog condition were less willing to implement the decision made at the end of the conversation with the chatbot and continue the interaction with the driver they chose. The results are even more striking when considering the Indicators condition. Both for the satisfaction measures and the trust measures, participants’ ratings were lower in the Indicators condition compared to the No Indicators. Participants in the Indicators condition felt that the ride search process was harder to operate, and slower (even though the actual interaction time was similar). They were less convinced that the chatbot suggested real trips and they trusted the person offering the ride and referred to them by the chatbot less. These effects were more evident for participants who preferred to share their rides using WhatsApp compared to participants who preferred chatbots for that purpose. Considering our findings, we can say that the WhatsAppization of the chatbot was detrimental. This is true for the both chatbot WhatsAppization methods – by making the conversation more a dialog and adding WhatsApp indicators. For the chosen drive-sharing task, the results were, in addition to lower satisfaction, less trust in the chatbot’s suggestion and even in the driver suggested by the chatbot, and lower willingness to actually undertake the suggested ride. In addition, it seems that the most problematic WhatsAppization method was using WhatsApp’s indicators during the interaction with the chatbot. The current study suggests that a conversation with an artificial agent should also not imitate a WhatsApp conversation very closely. With the proliferation of WhatsApp use, the emotional and social aspect of face-to face commination are moving to WhatsApp communication. Based on the current study’s findings, it is possible that the UV effect also occurs in WhatsAppization, and not only in humanization, of the chatbot, with a similar feeling of eeriness, and is more pronounced for people who prefer to use WhatsApp over chatbots. The current research can serve as a starting point to study the very interesting and important topic of chatbots WhatsAppization. More methods of WhatsAppization and other tasks could be the focus of further studies.

Keywords: chatbot, WhatsApp, humanization, Uncanny Valley, drive sharing

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Authors: Sigal Portnoy, Jason Friedman, Eitan Raveh

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Introduction: Sensory substitution is possible due to the capacity of our brain to adapt to information transmitted by a synthetic receptor via an alternative sensory system. Practical sensory substitution systems are being developed in order to increase the functionality of individuals with sensory loss, e.g. amputees. For upper limb prosthetic-users the loss of tactile feedback compels them to allocate visual attention to their prosthesis. The effect of adding vibrotactile feedback (VTF) to the applied force has been studied, however its effect on the allocation if visual attention during dual-tasking and the response during misleading visual feedback have not been studied. We hypothesized that VTF will improve the performance and reduce visual attention during dual-task assignments in healthy individuals using a robotic hand and improve the performance in a standardized functional test, despite the presence of misleading visual feedback. Methods: For the dual-task paradigm, twenty healthy subjects were instructed to toggle two keyboard arrow keys with the left hand to retain a moving virtual car on a road on a screen. During the game, instructions for various activities, e.g. mix the sugar in the glass with a spoon, appeared on the screen. The subject performed these tasks with a robotic hand, attached to the right hand. The robotic hand was controlled by the activity of the flexors and extensors of the right wrist, recorded using surface EMG electrodes. Pressure sensors were attached at the tips of the robotic hand and induced VTF using vibrotactile actuators attached to the right arm of the subject. An eye-tracking system tracked to visual attention of the subject during the trials. The trials were repeated twice, with and without the VTF. Additionally, the subjects performed the modified box and blocks, hidden from eyesight, in a motion laboratory. A virtual presentation of a misleading visual feedback was be presented on a screen so that twice during the trial, the virtual block fell while the physical block was still held by the subject. Results: This is an ongoing study, which current results are detailed below. We are continuing these trials with transradial myoelectric prosthesis-users. In the healthy group, the VTF did not reduce the visual attention or improve performance during dual-tasking for the tasks that were typed transfer-to-target, e.g. place the eraser on the shelf. An improvement was observed for other tasks. For example, the average±standard deviation of time to complete the sugar-mixing task was 13.7±17.2s and 19.3±9.1s with and without the VTF, respectively. Also, the number of gaze shifts from the screen to the hand during this task were 15.5±23.7 and 20.0±11.6, with and without the VTF, respectively. The response of the subjects to the misleading visual feedback did not differ between the two conditions, i.e. with and without VTF. Conclusions: Our interim results suggest that the performance of certain activities of daily living may be improved by VTF. The substitution of visual sensory input by tactile feedback might require a long training period so that brain plasticity can occur and allow adaptation to the new condition.

Keywords: prosthetics, rehabilitation, sensory substitution, upper limb amputation

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Authors: Mais Nijim, Rama Devi Chennuboyina, Waseem Al Aqqad

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Advances in spatial and spectral resolution of satellite images have led to tremendous growth in large image databases. The data we acquire through satellites, radars and sensors consists of important geographical information that can be used for remote sensing applications such as region planning, disaster management. Spatial data classification and object recognition are important tasks for many applications. However, classifying objects and identifying them manually from images is a difficult task. Object recognition is often considered as a classification problem, this task can be performed using machine-learning techniques. Despite of many machine-learning algorithms, the classification is done using supervised classifiers such as Support Vector Machines (SVM) as the area of interest is known. We proposed a classification method, which considers neighboring pixels in a region for feature extraction and it evaluates classifications precisely according to neighboring classes for semantic interpretation of region of interest (ROI). A dataset has been created for training and testing purpose; we generated the attributes by considering pixel intensity values and mean values of reflectance. We demonstrated the benefits of using knowledge discovery and data-mining techniques, which can be on image data for accurate information extraction and classification from high spatial resolution remote sensing imagery.

Keywords: remote sensing, object recognition, classification, data mining, waterbody identification, feature extraction

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Authors: M. K. Benhaoua, A. K. Singh, A. E. Benyamina, P. Boulet

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Mapping parallelized tasks of applications onto these MPSoCs can be done either at design time (static) or at run-time (dynamic). Static mapping strategies find the best placement of tasks at design-time, and hence, these are not suitable for dynamic workload and seem incapable of runtime resource management. The number of tasks or applications executing in MPSoC platform can exceed the available resources, requiring efficient run-time mapping strategies to meet these constraints. This paper describes a new Spiral Dynamic Task Mapping heuristic for mapping applications onto NoC-based Heterogeneous MPSoC. This heuristic is based on packing strategy and routing Algorithm proposed also in this paper. Heuristic try to map the tasks of an application in a clustering region to reduce the communication overhead between the communicating tasks. The heuristic proposed in this paper attempts to map the tasks of an application that are most related to each other in a spiral manner and to find the best possible path load that minimizes the communication overhead. In this context, we have realized a simulation environment for experimental evaluations to map applications with varying number of tasks onto an 8x8 NoC-based Heterogeneous MPSoCs platform, we demonstrate that the new mapping heuristics with the new modified dijkstra routing algorithm proposed are capable of reducing the total execution time and energy consumption of applications when compared to state-of-the-art run-time mapping heuristics reported in the literature.

Keywords: multiprocessor system on chip, MPSoC, network on chip, NoC, heterogeneous architectures, run-time mapping heuristics, routing algorithm

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Authors: Sonia Pajaron, Flaviano Sentina, Ranulfo Etulle

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Learning a second language calls for a total commitment from the learner whose response is necessary to successfully send and receive linguistic messages. It is relevant to virtually every aspect of human behaviour which is even more challenging when the components on -affective domains- are involved in second language learning. This study investigated the association between the identified affective attributes and second language performance of the one hundred seventeen (117) randomly selected third year maritime students. A descriptive-correlational method was utilized to generate data on their affective attributes while composition writing (2 series) and IELTS-based interview was done for speaking test. Additionally, to establish the respondents’ English language profile, data on their high school grades (GPA), entrance exam results in English subject (written) as well as in the interview was extracted as baseline information. Data were subjected to various statistical treatment (average means, percentages and pearson-r moment coefficient correlation) and found out that, Nautical Science and Marine Engineering students were found to have average high school grade, entrance test results, both written and in the interview turned out to be very satisfactory at 50% passing percentage. Varied results were manifested in their affective attributes towards learning the second language. On attitude, nautical science students had true positive attitude while marine engineering had only a moderate positive one. Secondly, the former were positively motivated to learn English while the latter were just moderately motivated. As regards anxiety, both groups embodied a moderate level of anxiety in the English language. Finally, data showed that nautical science students exuded real confidence while the marine engineering group had only moderate confidence with the second language. Respondents’ English academic achievement (GWA) was significantly correlated with confidence and speaking with anxiety towards the second language among the students from the nautical science group with moderate positive and low negative degree of correlation, respectively. On the other hand, the marine engineering students’ speaking test result was significantly correlated with anxiety and self-confidence with a moderate negative and low positive degree of correlation, respectively while writing was significantly correlated with motivation bearing a low positive degree of correlation.

Keywords: affective attributes, second language, second language performance, anxiety, attitude, self-confidence and motivation

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Authors: Prathiksha Kamath, Pratibha Jamkhandi, Prateek Ghanti, Priyanshu Gupta, M. Lakshmi Neelima

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Combining Image Captioning and Visual Question Answering (VQA) tasks have emerged as a new and exciting research area. The image captioning task involves generating a textual description that summarizes the content of the image. VQA aims to answer a natural language question about the image. Both these tasks include computer vision and natural language processing (NLP) and require a deep understanding of the content of the image and semantic relationship within the image and the ability to generate a response in natural language. There has been remarkable growth in both these tasks with rapid advancement in deep learning. In this paper, we present a comprehensive review of recent progress in combining image captioning and visual question-answering (VQA) tasks. We first discuss both image captioning and VQA tasks individually and then the various ways in which both these tasks can be integrated. We also analyze the challenges associated with these tasks and ways to overcome them. We finally discuss the various datasets and evaluation metrics used in these tasks. This paper concludes with the need for generating captions based on the context and captions that are able to answer the most likely asked questions about the image so as to aid the VQA task. Overall, this review highlights the significant progress made in combining image captioning and VQA, as well as the ongoing challenges and opportunities for further research in this exciting and rapidly evolving field, which has the potential to improve the performance of real-world applications such as autonomous vehicles, robotics, and image search.

Keywords: image captioning, visual question answering, deep learning, natural language processing

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Authors: Akbarov Elbek Elmurodovich

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Introduction: We are analyzing the topic of hemolytic anemia observed in patients after COVID-19 infection. The purpose of this research is to investigate the development of hemolytic anemia, identify its causes, and study treatment methods. Objective and Task: The goal of our research is to analyze the changes in blood occurring after COVID-19 infection and study the development of hemolytic anemia. Our main task is to analyze the results and assess subsequent changes in patients. Materials and Methods: The study was conducted among patients treated with a diagnosis of COVID-19 in the Department of Infectious Diseases at the TTA 1-Multiprofile Clinic from March to August 2023. Out of the 32 patients included, 16 were female, and 16 were male. Monitoring Blood Coagulation in Patients: The hemoglobin level of patients upon admission was initially measured using the URITEST-150 analyzer. The average for women was 110 g/l, and for men was 120 g/l. Over the course of 3 months, a decrease was observed: an average of 72 g/l in women (a decrease of up to 35%) and 84 g/l in men (a decrease of up to 30%). In the next 2 months, the positive dynamics of hemoglobin levels were observed, with an average increase to 93 g/l in women (>28%) and 112 g/l in men (>25%). Research Results: Hemolytic anemia developed in men within 5 months, reaching up to 112 g/l. In women, this process required a longer period, with the last month of observation (6 months) showing that women reached levels of up to 112 g/l, similar to men. Conclusion: Hemolytic anemia observed in patients after COVID-19 infection was monitored for 6 months (5 months in men, 6 months in women), reaching up to 112 g/l. The first 3 months after contracting COVID showed the period of development of anemia, and the subsequent 3 months indicated a stabilization period in patients.

Keywords: COVID, anemia, hemoglobin, tma, virus, viral infrection

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Authors: Alireza Behfar, Mohammad Mahdavi

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Nowadays, in the light of progress in the world of science, technology and communications, mastery of learning international languages is a sure and needful matter. In learning any language as a second language, progress and achieving a desirable level in speaking is indeed important for approximately all learners. In this research, we find out how preparation can influence L2 learners' oral fluency with respect to individual differences in working memory capacity. The participants consisted of sixty-one advanced L2 learners including MA students of TEFL at Isfahan University as well as instructors teaching English at Sadr Institute in Isfahan. The data collection consisted of two phases: A working memory test (reading span test) and a picture description task, with a one-month interval between the two tasks. Speaking was elicited through speech generation task in which the individuals were asked to discuss four topics emerging in two pairs. The two pairs included one simple and one complex topic and was accompanied by planning time and without any planning time respectively. Each topic was accompanied by several relevant pictures. L2 fluency was assessed based on preparation. The data were then analyzed in terms of the number of syllables, the number of silent pauses, and the mean length of pauses produced per minute. The study offers implications for strategies to improve learners’ both fluency and working memory.

Keywords: two factors, fluency, working memory capacity, preparation, L2 speech production reading span test picture description

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Authors: Sean W. T. Bayly, Daniel Glover, Don Horrell, Simon Horrocks, Barnes Callum, Stuart Gibson, Mac Misuira

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We assess suitability of recent, ∼7B parameter, instruction-tuned Language Models Mistral-v0.3, Llama-3, and Phi-3, for Generative Named Entity Recognition (GNER). Our proposed Multi-Level Information Retrieval method achieves notable improvements over finetuned entity-level and sentence-level methods. We consider recent developments at the cross roads of prompt engineering and Retrieval Augmented Generation (RAG), such as EmotionPrompt. We conclude that language models directed toward this task are highly capable when distinguishing between positive classes (precision). However, smaller models seem to struggle to find all entities (recall). Poorly defined classes such as ”Miscellaneous” exhibit substantial declines in performance, likely due to the ambiguity it introduces to the prompt. This is partially resolved through a self verification method using engineered prompts containing knowledge of the stricter class definitions, particularly in areas where their boundaries are in danger of overlapping, such as the conflation between the location ”Britain” and the nationality ”British”. Finally, we explore correlations between model performance on the GNER task with performance on relevant academic benchmarks.

Keywords: generative named entity recognition, information retrieval, lightweight artificial intelligence, prompt engineering, personal information identification, retrieval augmented generation, self verification

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Authors: Felipe A. Guth, Shane Ward, Kevin McDonnell

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The assessment of disease levels in crop fields is an important and time-consuming task that generally relies on expert knowledge of trained individuals. Image classification in agriculture problems historically has been based on classical machine learning strategies that make use of hand-engineered features in the top of a classification algorithm. This approach tends to not produce results with high accuracy and generalization to the classes classified by the system when the nature of the elements has a significant variability. The advent of deep convolutional neural networks has revolutionized the field of machine learning, especially in computer vision tasks. These networks have great resourcefulness of learning and have been applied successfully to image classification and object detection tasks in the last years. The objective of this work was to propose a new method based on deep learning convolutional neural networks towards the task of disease level monitoring. Common RGB images of winter wheat were obtained during a growing season. Five categories of disease levels presence were produced, in collaboration with agronomists, for the algorithm classification. Disease level tasks performed by experts provided ground truth data for the disease score of the same winter wheat plots were RGB images were acquired. The system had an overall accuracy of 84% on the discrimination of the disease level classes.

Keywords: crop disease assessment, deep learning, precision agriculture, residual neural networks

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Authors: Yanan Wang

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It is proposed that when people give a gift they engage in 'love accounting', so that they will spend less on it if they include a written expression of love with it. This hypothesis was tested with college students (N = 308). It was found that participants who wrote a love message to accompany a Mother's Day gift budgeted less for the gift itself than control participants (Experiment 1), and this effect was replicated for a Christmas gift (Experiment 2). The amount of effort expended by the giver on preparing the love message did not account for the effect (Experiment 3). It is concluded that a gift and its accompanying love message are mentally computed as belonging to the same love account, implying that consumers’ excessive splurging on gifts might be controlled by writing a love message before gift shopping.

Keywords: expression of love, gift-giving, gift-budgeting, mental accounting

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Authors: Robert Herold

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This project aims to begin building out a new approach within the philosophy of science that is based around a combination of insights from Albert Camus and Paul Feyerabend. This approach is one that will be labeled an absurdist approach as it uses, for its foundation, the philosophy of the absurd as discussed by Camus. While Camus didn’t directly discuss the philosophy of science, nor did he offer his own views on the subject in any substantial way, that doesn’t mean that his work doesn’t have applications within the philosophy of science. In fact, as is argued throughout the piece, much of the work done by Paul Feyerabend stems from a similar metaphysical and epistemological foundation as Camus. This foundation is the notion of the absurd and the inability of us as humans to reach some sort of objective truth. In modern times both Camus and Feyerabend have been largely pushed to the wayside, though Feyerabend has undoubtedly received the most unfair treatment of the two, and this is something that serves to act more as a hindrance than anything else. Much of the claims and arguments made by both Camus and Feyerabend have not been truly refuted and have simply been pushed aside by pointing to supposed contradictions or inconsistencies. However, while it would be a monumental task to attempt to discuss all of this past work, perhaps it might be better to move beyond both Camus and Feyerabend and chart a new path. This is the overall goal of this paper. This research will demonstrate that not only are the philosophies of Camus and Feyerabend surprisingly similar and able to mesh well together, they also are able to form into something that is truly more than the sum of its parts. While the task of actually building out an approach is a monumental undertaking, the plan is to use this project as a jumping-off point. As such, this paper will start by examining some of the main claims made by both Camus and Feyerabend. Once this is done, then begin weaving them together and demonstrating where the links between the philosophies of both are. Then this study will end by building out the very begging foundations of the absurdist approach to the philosophy of science.

Keywords: philosophy, philosophy of science, albert camus, paul feyerabend

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