Search results for: probing task
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2142

Search results for: probing task

1332 Power Control in Solar Battery Charging Station Using Fuzzy Decision Support System

Authors: Krishnan Manickavasagam, Manikandan Shanmugam

Abstract:

Clean and abundant renewable energy sources (RES) such as solar energy is seen as the best solution to replace conventional energy source. Unpredictable power generation is a major issue in the penetration of solar energy, as power generated is governed by the irradiance received. Controlling the power generated from solar PV (SPV) panels to battery and load is a challenging task. In this paper, power flow control from SPV to load and energy storage device (ESD) is controlled by a fuzzy decision support system (FDSS) on the availability of solar irradiation. The results show that FDSS implemented with the energy management system (EMS) is capable of managing power within the area, and if excess power is available, then shared with the neighboring area.

Keywords: renewable energy sources, fuzzy decision support system, solar photovoltaic, energy storage device, energy management system

Procedia PDF Downloads 88
1331 A Review on Robot Trajectory Optimization and Process Validation through off-Line Programming in Virtual Environment Using Robcad

Authors: Ashwini Umale

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Trajectory planning and optimization is a fundamental problem in articulated robotics. It is often viewed as a two phase problem of initial feasible path planning around obstacles and subsequent optimization of a trajectory satisfying dynamical constraints. An optimized trajectory of multi-axis robot is important and directly influences the Performance of the executing task. Optimal is defined to be the minimum time to transition from the current speed to the set speed. In optimization of trajectory through virtual environment explores the most suitable way to represent robot motion from virtual environment to real environment. This paper aims to review the research of trajectory optimization in virtual environment using simulation software Robcad. Improvements are to be expected in trajectory optimization to generate smooth and collision free trajectories with minimization of overall robot cycle time.

Keywords: trajectory optimization, forward kinematics and reverse kinematics, dynamic constraints, robcad simulation software

Procedia PDF Downloads 487
1330 Identification of Failures Occurring on a System on Chip Exposed to a Neutron Beam for Safety Applications

Authors: S. Thomet, S. De-Paoli, F. Ghaffari, J. M. Daveau, P. Roche, O. Romain

Abstract:

In this paper, we present a hardware module dedicated to understanding the fail reason of a System on Chip (SoC) exposed to a particle beam. Impact of Single-Event Effects (SEE) on processor-based SoCs is a concern that has increased in the past decade, particularly for terrestrial applications with automotive safety increasing requirements, as well as consumer and industrial domains. The SEE created by the impact of a particle on an SoC may have consequences that can end to instability or crashes. Specific hardening techniques for hardware and software have been developed to make such systems more reliable. SoC is then qualified using cosmic ray Accelerated Soft-Error Rate (ASER) to ensure the Soft-Error Rate (SER) remains in mission profiles. Understanding where errors are occurring is another challenge because of the complexity of operations performed in an SoC. Common techniques to monitor an SoC running under a beam are based on non-intrusive debug, consisting of recording the program counter and doing some consistency checking on the fly. To detect and understand SEE, we have developed a module embedded within the SoC that provide support for recording probes, hardware watchpoints, and a memory mapped register bank dedicated to software usage. To identify CPU failure modes and the most important resources to probe, we have carried out a fault injection campaign on the RTL model of the SoC. Probes are placed on generic CPU registers and bus accesses. They highlight the propagation of errors and allow identifying the failure modes. Typical resulting errors are bit-flips in resources creating bad addresses, illegal instructions, longer than expected loops, or incorrect bus accesses. Although our module is processor agnostic, it has been interfaced to a RISC-V by probing some of the processor registers. Probes are then recorded in a ring buffer. Associated hardware watchpoints are allowing to do some control, such as start or stop event recording or halt the processor. Finally, the module is also providing a bank of registers where the firmware running on the SoC can log information. Typical usage is for operating system context switch recording. The module is connected to a dedicated debug bus and is interfaced to a remote controller via a debugger link. Thus, a remote controller can interact with the monitoring module without any intrusiveness on the SoC. Moreover, in case of CPU unresponsiveness, or system-bus stall, the recorded information can still be recovered, providing the fail reason. A preliminary version of the module has been integrated into a test chip currently being manufactured at ST in 28-nm FDSOI technology. The module has been triplicated to provide reliable information on the SoC behavior. As the primary application domain is automotive and safety, the efficiency of the module will be evaluated by exposing the test chip under a fast-neutron beam by the end of the year. In the meantime, it will be tested with alpha particles and electromagnetic fault injection (EMFI). We will report in the paper on fault-injection results as well as irradiation results.

Keywords: fault injection, SoC fail reason, SoC soft error rate, terrestrial application

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1329 Scheduling Algorithm Based on Load-Aware Queue Partitioning in Heterogeneous Multi-Core Systems

Authors: Hong Kai, Zhong Jun Jie, Chen Lin Qi, Wang Chen Guang

Abstract:

There are inefficient global scheduling parallelism and local scheduling parallelism prone to processor starvation in current scheduling algorithms. Regarding this issue, this paper proposed a load-aware queue partitioning scheduling strategy by first allocating the queues according to the number of processor cores, calculating the load factor to specify the load queue capacity, and it assigned the awaiting nodes to the appropriate perceptual queues through the precursor nodes and the communication computation overhead. At the same time, real-time computation of the load factor could effectively prevent the processor from being starved for a long time. Experimental comparison with two classical algorithms shows that there is a certain improvement in both performance metrics of scheduling length and task speedup ratio.

Keywords: load-aware, scheduling algorithm, perceptual queue, heterogeneous multi-core

Procedia PDF Downloads 124
1328 Modern Machine Learning Conniptions for Automatic Speech Recognition

Authors: S. Jagadeesh Kumar

Abstract:

This expose presents a luculent of recent machine learning practices as employed in the modern and as pertinent to prospective automatic speech recognition schemes. The aspiration is to promote additional traverse ablution among the machine learning and automatic speech recognition factions that have transpired in the precedent. The manuscript is structured according to the chief machine learning archetypes that are furthermore trendy by now or have latency for building momentous hand-outs to automatic speech recognition expertise. The standards offered and convoluted in this article embraces adaptive and multi-task learning, active learning, Bayesian learning, discriminative learning, generative learning, supervised and unsupervised learning. These learning archetypes are aggravated and conferred in the perspective of automatic speech recognition tools and functions. This manuscript bequeaths and surveys topical advances of deep learning and learning with sparse depictions; further limelight is on their incessant significance in the evolution of automatic speech recognition.

Keywords: automatic speech recognition, deep learning methods, machine learning archetypes, Bayesian learning, supervised and unsupervised learning

Procedia PDF Downloads 425
1327 The Quality of Human Capital as a Factor of Social and Economic Development of the Region

Authors: O. Gubnitsyna, O. Zakoretskaya, O. Russova

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It is generally recognized that the main task of modern society is human development. The quality of human capital has been identified as a key driver of economic development in the region. In this article, considered the quality of human capital as one of the main types of social and economic potential for the region’s development. The phenomenon of human capital represents both material and intellectual components of human activity. It is show that the necessary population characterized by certain quantitative and qualitative indicators (qualification and professional structure, education or social general condition and others) and is an necessary resource for the development of the regional economy. The connection of the regional goals with the quality of human capital is discussed in the article and a number of recommendations on its improvement were given. Solving the tasks stated in the article, the authors used analytical and statistical methods of research, scientific publications of domestic and foreign scientists on this issue. The results can be used in this implementation of the concept of regional development.

Keywords: human capital, the quality of human capital, economic development, social general condition

Procedia PDF Downloads 269
1326 Naïve Bayes: A Classical Approach for the Epileptic Seizures Recognition

Authors: Bhaveek Maini, Sanjay Dhanka, Surita Maini

Abstract:

Electroencephalography (EEG) is used to classify several epileptic seizures worldwide. It is a very crucial task for the neurologist to identify the epileptic seizure with manual EEG analysis, as it takes lots of effort and time. Human error is always at high risk in EEG, as acquiring signals needs manual intervention. Disease diagnosis using machine learning (ML) has continuously been explored since its inception. Moreover, where a large number of datasets have to be analyzed, ML is acting as a boon for doctors. In this research paper, authors proposed two different ML models, i.e., logistic regression (LR) and Naïve Bayes (NB), to predict epileptic seizures based on general parameters. These two techniques are applied to the epileptic seizures recognition dataset, available on the UCI ML repository. The algorithms are implemented on an 80:20 train test ratio (80% for training and 20% for testing), and the performance of the model was validated by 10-fold cross-validation. The proposed study has claimed accuracy of 81.87% and 95.49% for LR and NB, respectively.

Keywords: epileptic seizure recognition, logistic regression, Naïve Bayes, machine learning

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1325 Graphical User Interface Testing by Using Deep Learning

Authors: Akshat Mathur, Sunil Kumar Khatri

Abstract:

This paper presents brief about how the use of Artificial intelligence in respect to GUI testing can reduce workload by using DL-fueled method. This paper also discusses about how graphical user interface and event driven software testing can derive benefits from the use of AI techniques. The use of AI techniques not only reduces the task and work load but also helps in getting better output than manual testing. Although results are same, but the use of Artifical intelligence techniques for GUI testing has proven to provide ideal results. DL-fueled framework helped us to find imperfections of the entire webpage and provides test failure result in a score format between 0 and 1which signifies that are test meets it quality criteria or not. This paper proposes DL-fueled method which helps us to find the genuine GUI bugs and defects and also helped us to scale the existing labour-intensive and skill-intensive methodologies.

Keywords: graphical user interface, GUI, artificial intelligence, deep learning, ML technology

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1324 Transcending or Going beyond the Concept of Race

Authors: Ovett Nwosimiri

Abstract:

Historically the concept of race has played a significant part in the existence of African philosophy. Race, as part of the historical events, has been used as a reason for colonization. In recent years, there has been a numerous work on the concept of race. Some philosophers have devoted their time to the discourse of race and to understand the ascription of the race. These philosophers have dedicated their time and energy to the concept of race. Philosophers, like Joshua Glasgow, W. E. B. Du Bois, Lucius Outlaw, Kwame Anthony Appiah, Naomi Zack, Emmanuel C. Eze and many others took up the task to explain the concept of race, and also to explain in their view whether the concept of race should be conserved or eliminated. According to the eliminativists, the concept of race should be eliminated. According to the conservationists, the concept of race should be conserved. The aim of this paper is to look at the possibility of transcending the concept of race. In order to do this, the paper will briefly explain Joshua Glasgow’ idea theory of ‘racial reconstructionism’, and it will propose a theory of ‘racial transcendentalism’ as a way of transcending the concept of race. The paper will argue that we should see the concept of race as a concept that has a future beyond the mere meaning and ideas that call for its elimination or conservation.

Keywords: conservationists, eliminativists, race, transcending

Procedia PDF Downloads 330
1323 Agriculture Yield Prediction Using Predictive Analytic Techniques

Authors: Nagini Sabbineni, Rajini T. V. Kanth, B. V. Kiranmayee

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India’s economy primarily depends on agriculture yield growth and their allied agro industry products. The agriculture yield prediction is the toughest task for agricultural departments across the globe. The agriculture yield depends on various factors. Particularly countries like India, majority of agriculture growth depends on rain water, which is highly unpredictable. Agriculture growth depends on different parameters, namely Water, Nitrogen, Weather, Soil characteristics, Crop rotation, Soil moisture, Surface temperature and Rain water etc. In our paper, lot of Explorative Data Analysis is done and various predictive models were designed. Further various regression models like Linear, Multiple Linear, Non-linear models are tested for the effective prediction or the forecast of the agriculture yield for various crops in Andhra Pradesh and Telangana states.

Keywords: agriculture yield growth, agriculture yield prediction, explorative data analysis, predictive models, regression models

Procedia PDF Downloads 289
1322 Creativity and Stereotype Threat: Analysis of the Impact of Creativity on Eliminating the Stereotype Threat in the Educational Setting

Authors: Aleksandra Gajda

Abstract:

Among students between 12 and 13, the probability of activating the stereotype threat increases noticeably. Girls consider themselves weaker in science, while boys consider themselves weaker in the field of language skills. This phenomenon is disturbing because it may result in wrong choices of the further path of education, not consistent with the actual competences of the students. Meanwhile, negative effects of the stereotype threat, observable in the loss of focus on the task and transferring it to dealing with fear of failure, can be reduced by various factors. The study examined the impact of creativity on eliminating the stereotype threat. The experiment in the form of a 2 (gender: male vs. female) x 3 (traditional gender roles: neutral version vs. nontraditional gender roles) x 2 (creativity: low vs. high) factorial design was conducted. The results showed that a high level of creative abilities may reduce the negative effects of stereotype threat in educational setting.

Keywords: creativity, education, language skills, mathematical skills, stereotype threat

Procedia PDF Downloads 99
1321 A Dream to Bicycle: A Curriculum Practice of Thematic Teaching Constructed by Scaffolding Theory

Authors: Gu Chun-Mei, Kung Mei-Juan

Abstract:

The aim of this research is to examine (1) how a kindergarten teacher followed the scaffolding theory to inspire children’s interest in bicycling and (2) how these children had learned the skill of bicycling. Results revealed that: first of all, the teacher (1) used questions during the teaching process to stimulate the levels of children’s abilities; (2) provided follow-up thematic clues and hints which are based on children’s abilities (e.g., would not provide instructions and demonstrations except children continued failing to solve the current problems); (3) assisted only when children needed it. Furthermore, when children continued failing the task and being frustrated, instead of providing more concrete guidance, the teacher would utilize the following strategies: (1) postulating children’s thoughts; (2) encouraging children to feel the difficulties; (3) giving children opportunities to reflect on how to solve the problems. In sum, by raising questions, allowing children to implement by themselves for the first attempt, then inducing children to correct their actions, the teacher built a scaffold with thematic teaching to develop children’s potential on bicycling.

Keywords: thematic teaching, scaffold, zone of proximal development, children

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1320 Research and Development of Intelligent Cooling Channels Design System

Authors: Q. Niu, X. H. Zhou, W. Liu

Abstract:

The cooling channels of injection mould play a crucial role in determining the productivity of moulding process and the product quality. It’s not a simple task to design high quality cooling channels. In this paper, an intelligent cooling channels design system including automatic layout of cooling channels, interference checking and assembly of accessories is studied. Automatic layout of cooling channels using genetic algorithm is analyzed. Through integrating experience criteria of designing cooling channels, considering the factors such as the mould temperature and interference checking, the automatic layout of cooling channels is implemented. The method of checking interference based on distance constraint algorithm and the function of automatic and continuous assembly of accessories are developed and integrated into the system. Case studies demonstrate the feasibility and practicality of the intelligent design system.

Keywords: injection mould, cooling channel, intelligent design, automatic layout, interference checking

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1319 Delegation or Assignment: Registered Nurses’ Ambiguity in Interpreting Their Scope of Practice in Long Term Care Settings

Authors: D. Mulligan, D. Casey

Abstract:

Introductory Statement: Delegation is when a registered nurse (RN) transfers a task or activity that is normally within their scope of practice to another person (delegatee). RN delegation is common practice with unregistered staff, e.g., student nurses and health care assistants (HCAs). As the role of the HCA is increasingly embedded as a direct care and support role, especially in long-term residential care for older adults, there is RN uncertainty as to their role as a delegator. The assignment is when a task is transferred to a person that is within the role specification of the delegatee. RNs in long-term care (LTC) for older people are increasingly working in teams where there are less RNs and more HCAs providing direct care to the residents. The RN is responsible and accountable for their decision to delegate and assign tasks to HCAs. In an interpretive, multiple case studies to explore how delegation of tasks by RNs to HCAs occurred in long-term care settings in Ireland the importance of the RN understanding their scope of practice emerged. Methodology: Focus group interviews and individual interviews were undertaken as part of a multiple case study. Both cases, anonymized as Case A and Case B, were within the public health service in Ireland. The case study sites were long-term care settings for older adults located in different social care divisions, and in different geographical areas. Four focus group interviews with staff nurses and three individual interviews with CNMs were undertaken. The interactive data analysis approach was the analytical framework used, with within-case and cross-case analysis. The theoretical lens of organizational role theory, applying the role episode model (REM), was used to understand, interpret, and explain the findings. Study Findings: RNs and CNMs understood the role of the nurse regulator and the scope of practice. RNs understood that the RN was accountable for the care and support provided to residents. However, RNs and CNM2s could not describe delegation in the context of their scope of practice. In both cases, the RNs did not have a standardized process for assessing HCA competence to undertake nursing tasks or interventions. RNs did not routinely supervise HCAs. Tasks were assigned and not delegated. There were differences between the cases in relation to understanding which nursing tasks required delegation. HCAs in Case A undertook clinical vital sign assessments and documentation. HCAs in Case B did not routinely undertake these activities. Delegation and assignment were influenced by the organizational factors, e.g., model of care, absence of delegation policies, inadequate RN education on delegation, and a lack of RN and HCA role clarity. Concluding Statement: Nurse staffing levels and skill mix in long-term care settings continue to change with more HCAs providing more direct care and support. With decreasing RN staffing levels RNs will be required to delegate and assign more direct care to HCAs. There is a requirement to distinguish between RN assignment and delegation at policy, regulation, and organizational levels.

Keywords: assignment, delegation, registered nurse, scope of practice

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1318 Core Number Optimization Based Scheduler to Order/Mapp Simulink Application

Authors: Asma Rebaya, Imen Amari, Kaouther Gasmi, Salem Hasnaoui

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Over these last years, the number of cores witnessed a spectacular increase in digital signal and general use processors. Concurrently, significant researches are done to get benefit from the high degree of parallelism. Indeed, these researches are focused to provide an efficient scheduling from hardware/software systems to multicores architecture. The scheduling process consists on statically choose one core to execute one task and to specify an execution order for the application tasks. In this paper, we describe an efficient scheduler that calculates the optimal number of cores required to schedule an application, gives a heuristic scheduling solution and evaluates its cost. Our proposal results are evaluated and compared with Preesm scheduler results and we prove that ours allows better scheduling in terms of latency, computation time and number of cores.

Keywords: computation time, hardware/software system, latency, optimization, multi-cores platform, scheduling

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1317 Model-Independent Price Bounds for the Swiss Re Mortality Bond 2003

Authors: Raj Kumari Bahl, Sotirios Sabanis

Abstract:

In this paper, we are concerned with the valuation of the first Catastrophic Mortality Bond that was launched in the market namely the Swiss Re Mortality Bond 2003. This bond encapsulates the behavior of a well-defined mortality index to generate payoffs for the bondholders. Pricing this bond is a challenging task. We adapt the payoff of the terminal principal of the bond in terms of the payoff of an Asian put option and present an approach to derive model-independent bounds exploiting comonotonic theory. We invoke Jensen’s inequality for the computation of lower bounds and employ Lagrange optimization technique to achieve the upper bound. The success of these bounds is based on the availability of compatible European mortality options in the market. We carry out Monte Carlo simulations to estimate the bond price and illustrate the strength of these bounds across a variety of models. The fact that our bounds are model-independent is a crucial breakthrough in the pricing of catastrophic mortality bonds.

Keywords: mortality bond, Swiss Re Bond, mortality index, comonotonicity

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1316 The Role of Emotion in Attention Allocation

Authors: Michaela Porubanova

Abstract:

In this exploratory study to examine the effects of emotional significance on change detection using the flicker paradigm, three different categories of scenes were randomly presented (neutral, positive and negative) in three different blocks. We hypothesized that because of the different effects on attention, performance in change detection tasks differs for scenes with different effective values. We found the greatest accuracy of change detection was for changes occurring in positive and negative scenes (compared with neutral scenes). Secondly and most importantly, changes in negative scenes (and also positive scenes, though not with statistical significance) were detected faster than changes in neutral scenes. Interestingly, women were less accurate than men in detecting changes in emotionally significant scenes (both negative and positive), i.e., women detected fewer changes in emotional scenes in the time limit of 40s. But on the other hand, women were quicker to detect changes in positive and negative images than men. The study makes important contributions to the area of the role of emotions on information processing. The role of emotion in attention will be discussed.

Keywords: attention, emotion, flicker task, IAPS

Procedia PDF Downloads 334
1315 Purpose-Driven Collaborative Strategic Learning

Authors: Mingyan Hong, Shuozhao Hou

Abstract:

Collaborative Strategic Learning (CSL) teaches students to use learning strategies while working cooperatively. Student strategies include the following steps: defining the learning task and purpose; conducting ongoing negotiation of the learning materials by deciding "click" (I get it and I can teach it – green card, I get it –yellow card) or "clunk" (I don't get it – red card) at the end of each learning unit; "getting the gist" of the most important parts of the learning materials; and "wrapping up" key ideas. Find out how to help students of mixed achievement levels apply learning strategies while learning content area in materials in small groups. The design of CSL is based on social-constructivism and Vygotsky’s best-known concept of the Zone of Proximal Development (ZPD). The definition of ZPD is the distance between the actual acquisition level as decided by individual problem solution case and the level of potential acquisition level, similar to Krashen (1980)’s i+1, as decided through the problem-solution case under the facilitator’s guidance, or in group work with other more capable members (Vygotsky, 1978). Vygotsky claimed that learners’ ideal learning environment is in the ZPD. An ideal teacher or more-knowledgable-other (MKO) should be able to recognize a learner’s ZPD and facilitates them to develop beyond it. Then the MKO is able to leave the support step by step until the learner can perform the task without aid. Steven Krashen (1980) proposed Input hypothesis including i+1 hypothesis. The input hypothesis models are the application of ZPD in second language acquisition and have been widely recognized until today. Krashen (2019)’s optimal language learning environment (2019) further developed the application of ZPD and added the component of strategic group learning. The strategic group learning is composed of desirable learning materials learners are motivated to learn and desirable group members who are more capable and are therefore able to offer meaningful input to the learners. Purpose-driven Collaborative Strategic Learning Model is a strategic integration of ZPD, i+1 hypothesis model, and Optimal Language Learning Environment Model. It is purpose driven to ensure group members are motivated. It is collaborative so that an optimal learning environment where meaningful input from meaningful conversation can be generated. It is strategic because facilitators in the model strategically assign each member a meaningful and collaborative role, e.g., team leader, technician, problem solver, appraiser, offer group learning instrument so that the learning process is structured, and integrate group learning and team building making sure holistic development of each participant. Using data collected from college year one and year two students’ English courses, this presentation will demonstrate how purpose-driven collaborative strategic learning model is implemented in the second/foreign language classroom, using the qualitative data from questionnaire and interview. Particular, this presentation will show how second/foreign language learners grow from functioning with facilitator or more capable peer’s aid to performing without aid. The implication of this research is that purpose-driven collaborative strategic learning model can be used not only in language learning, but also in any subject area.

Keywords: collaborative, strategic, optimal input, second language acquisition

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1314 A Method of Drilling a Ground Using a Robotic Arm

Authors: Lotfi Beji, Laredj Benchikh

Abstract:

Underground tunnel face bolting and pipe umbrella reinforcement are one of the most challenging tasks in construction whether industrial or not, and infrastructures such as roads or pipelines. It is one of the first sectors of economic activity in the world. Through a variety of soil and rock, a cyclic Conventional Tunneling Method (CTM) remains the best one for projects with highly variable ground conditions or shapes. CTM is the only alternative for the renovation of existing tunnels and creating emergency exit. During the drilling process, a wide variety of non-desired vibrations may arise, and a method using a robot arm is proposed. The main kinds of drilling through vibration here is the bit-bouncing phenomenon (resonant axial vibration). Hence, assisting the task by a robot arm may play an important role on drilling performances and security. We propose to control the axial-vibration phenomenon along the drillstring at a practical resonant frequency, and embed a Resonant Sonic Drilling Head (RSDH) as a robot end effector for drilling. Many questionable industry drilling criteria and stability are discussed in this paper.

Keywords: drilling, resonant vibration, robot arm, control

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1313 Lean Implementation: Manufacturing vs. Construction a Roadmap for Success

Authors: Patrick Ahern, David Collery

Abstract:

The implementation of lean thinking in the manufacturing industry revolutionized the traditional approach to large-scale production through the process of identifying the waste in each task and putting in place mitigation measures to eliminate the waste in all its forms. The Irish construction industry, however, has been much slower to adopt the principles of lean, opting instead to stick with the traditional approach to construction project delivery which is inherently wasteful. Lean thinking holds the potential to revolutionize the construction industry in a similar manner to the adoption of lean manufacturing. Lean principles present opportunities for reduced project duration, reduced project cost, improved quality, and elimination of re-works and non-value-added activities. The following research has been designed to accumulate research data through available literature, electronic surveys, and interviews. The results show an industry reluctant to accept change and an undefined path to successful lean construction implementation.

Keywords: barriers, lean construction, lean implementation, lean manufacturing, lean philosophy

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1312 Feature Selection for Production Schedule Optimization in Transition Mines

Authors: Angelina Anani, Ignacio Ortiz Flores, Haitao Li

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The use of underground mining methods have increased significantly over the past decades. This increase has also been spared on by several mines transitioning from surface to underground mining. However, determining the transition depth can be a challenging task, especially when coupled with production schedule optimization. Several researchers have simplified the problem by excluding operational features relevant to production schedule optimization. Our research objective is to investigate the extent to which operational features of transition mines accounted for affect the optimal production schedule. We also provide a framework for factors to consider in production schedule optimization for transition mines. An integrated mixed-integer linear programming (MILP) model is developed that maximizes the NPV as a function of production schedule and transition depth. A case study is performed to validate the model, with a comparative sensitivity analysis to obtain operational insights.

Keywords: underground mining, transition mines, mixed-integer linear programming, production schedule

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1311 The Effect of Work Site Dangers on the Management of Construction Projects in Syria

Authors: Mohammed Aljoma, Eblal Zakzok

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Safety is a science that seeks to protect and avoid humans from risks in any field and prevent losses in properties and lives as much as possible. On the other hand, occupational safety goals aim to protect workers from risks which can occur during work execution. The main purpose of occupational safety is to ultimately protect people, properties and the environment by reducing accidents and injuries that may cause losses and damages. To achieve this goal, we must remove the direct and indirect reasons which cause accidents and injuries; some of the reasons of accidents are the unsafe cases and inept behavior or both of them. This research focuses on the manner of providing instant protection from the very first beginning to people, properties and the environment by: -Inserting safety demands in the planning and designing works by identifying risk levels in every task of the project, -Using a new risk managing system or modifying or changing a previously-used one.

Keywords: planning, scheduling, risk management, project duration, site safety

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1310 Sentiment Analysis on the East Timor Accession Process to the ASEAN

Authors: Marcelino Caetano Noronha, Vosco Pereira, Jose Soares Pinto, Ferdinando Da C. Saores

Abstract:

One particularly popular social media platform is Youtube. It’s a video-sharing platform where users can submit videos, and other users can like, dislike or comment on the videos. In this study, we conduct a binary classification task on YouTube’s video comments and review from the users regarding the accession process of Timor Leste to become the eleventh member of the Association of South East Asian Nations (ASEAN). We scrape the data directly from the public YouTube video and apply several pre-processing and weighting techniques. Before conducting the classification, we categorized the data into two classes, namely positive and negative. In the classification part, we apply Support Vector Machine (SVM) algorithm. By comparing with Naïve Bayes Algorithm, the experiment showed SVM achieved 84.1% of Accuracy, 94.5% of Precision, and Recall 73.8% simultaneously.

Keywords: classification, YouTube, sentiment analysis, support sector machine

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1309 Esports: A Biomechanics and Performance Perspective

Authors: Alex S. Talan

Abstract:

The introduction of scientific terms for esports can directly affect the quality of the training process. This is a critically important scientific task since esports is a rapidly developing global sport that has only recently begun to receive scientific and methodological consideration. In this report, we evaluate esports from a biomechanical perspective. First, we examine the relationship between physical performance and esports gaming techniques, with consideration toward engineering more effective physical and in-game training methodologies for amateur and professional esports competitors. In addition, we advocate that applying biomechanical research methodologies has the added potential to improve physical performance and endurance in esports athletes. With the budding attention on the esports enterprise globally, scientific research into esports would benefit from standardizing terminologies and methodological approaches that are specifically tailored to assess esports training efficacy to enhance individual and team performance within the esports community.

Keywords: cybersport, esports, biomechanics, sports technique, training standards, dental occlusion, sports engineering, sitting pose

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1308 Estimation of the External Force for a Co-Manipulation Task Using the Drive Chain Robot

Authors: Sylvain Devie, Pierre-Philippe Robet, Yannick Aoustin, Maxime Gautier

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The aim of this paper is to show that the observation of the external effort and the sensor-less control of a system is limited by the mechanical system. First, the model of a one-joint robot with a prismatic joint is presented. Based on this model, two different procedures were performed in order to identify the mechanical parameters of the system and observe the external effort applied on it. Experiments have proven that the accuracy of the force observer, based on the DC motor current, is limited by the mechanics of the robot. The sensor-less control will be limited by the accuracy in estimation of the mechanical parameters and by the maximum static friction force, that is the minimum force which can be observed in this case. The consequence of this limitation is that industrial robots without specific design are not well adapted to perform sensor-less precision tasks. Finally, an efficient control law is presented for high effort applications.

Keywords: control, identification, robot, co-manipulation, sensor-less

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1307 Resume Ranking Using Custom Word2vec and Rule-Based Natural Language Processing Techniques

Authors: Subodh Chandra Shakya, Rajendra Sapkota, Aakash Tamang, Shushant Pudasaini, Sujan Adhikari, Sajjan Adhikari

Abstract:

Lots of efforts have been made in order to measure the semantic similarity between the text corpora in the documents. Techniques have been evolved to measure the similarity of two documents. One such state-of-art technique in the field of Natural Language Processing (NLP) is word to vector models, which converts the words into their word-embedding and measures the similarity between the vectors. We found this to be quite useful for the task of resume ranking. So, this research paper is the implementation of the word2vec model along with other Natural Language Processing techniques in order to rank the resumes for the particular job description so as to automate the process of hiring. The research paper proposes the system and the findings that were made during the process of building the system.

Keywords: chunking, document similarity, information extraction, natural language processing, word2vec, word embedding

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1306 Topic-to-Essay Generation with Event Element Constraints

Authors: Yufen Qin

Abstract:

Topic-to-Essay generation is a challenging task in Natural language processing, which aims to generate novel, diverse, and topic-related text based on user input. Previous research has overlooked the generation of articles under the constraints of event elements, resulting in issues such as incomplete event elements and logical inconsistencies in the generated results. To fill this gap, this paper proposes an event-constrained approach for a topic-to-essay generation that enforces the completeness of event elements during the generation process. Additionally, a language model is employed to verify the logical consistency of the generated results. Experimental results demonstrate that the proposed model achieves a better BLEU-2 score and performs better than the baseline in terms of subjective evaluation on a real dataset, indicating its capability to generate higher-quality topic-related text.

Keywords: event element, language model, natural language processing, topic-to-essay generation.

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1305 Investigate and Solving Analytically at Vibrational structures (In Arched Beam to Bridges) by New Method “AGM”

Authors: M. R. Akbari, P. Soleimani, R. Khalili, Sara Akbari

Abstract:

Analyzing and modeling the vibrational behavior of arched bridges during the earthquake in order to decrease the exerted damages to the structure is a very hard task to do. This item has been done analytically in the present paper for the first time. Due to the importance of building arched bridges as a great structure in the human being civilization and its specifications such as transferring vertical loads to its arcs and the lack of bending moments and shearing forces, this case study is devoted to this special issue. Here, the nonlinear vibration of arched bridges has been modeled and simulated by an arched beam with harmonic vertical loads and its behavior has been investigated by analyzing a nonlinear partial differential equation governing the system. It is notable that the procedure has been done analytically by AGM (Akbari, Ganji Method). Furthermore, comparisons have been made between the obtained results by numerical Method (rkf-45) and AGM in order to assess the scientific validity.

Keywords: new method (AGM), arched beam bridges, angular frequency, harmonic loads

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1304 Combined Machine That Fertilizes Evenly under Plowing on Slopes and Planning an Experiment

Authors: Qurbanov Huseyn Nuraddin

Abstract:

The results of scientific research on a machine that pours an equal amount of mineral fertilizer under the soil to increase the productivity of grain in mountain farming and obtain quality grain are substantiated. The average yield of the crop depends on the nature of the distribution of fertilizers in the soil. Therefore, the study of effective energy-saving methods for the application of mineral fertilizers is the actual task of modern agriculture. Depending on the type and variety of plants in mountain farming, there is an optimal norm of mineral fertilizers. Applying an equal amount of fertilizer to the soil is one of the conditions that increase the efficiency of the field. One of the main agro-technical indicators of the work of mineral fertilizing machines is to ensure equal distribution of mineral fertilizers in the field. Taking into account the above-mentioned issues, a combined plough has been improved in our laboratory.

Keywords: combined plough, mineral fertilizers, sprinkle fluently, fertilizer rate, cereals

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1303 Motivation and Multiglossia: Exploring the Diversity of Interests, Attitudes, and Engagement of Arabic Learners

Authors: Anna-Maria Ramezanzadeh

Abstract:

Demand for Arabic language is growing worldwide, driven by increased interest in the multifarious purposes the language serves, both for the population of heritage learners and those studying Arabic as a foreign language. The diglossic, or indeed multiglossic nature of the language as used in Arabic speaking communities however, is seldom represented in the content of classroom courses. This disjoint between the nature of provision and students’ expectations can severely impact their engagement with course material, and their motivation to either commence or continue learning the language. The nature of motivation and its relationship to multiglossia is sparsely explored in current literature on Arabic. The theoretical framework here proposed aims to address this gap by presenting a model and instruments for the measurement of Arabic learners’ motivation in relation to the multiple strands of the language. It adopts and develops the Second Language Motivation Self-System model (L2MSS), originally proposed by Zoltan Dörnyei, which measures motivation as the desire to reduce the discrepancy between leaners’ current and future self-concepts in terms of the second language (L2). The tripartite structure incorporates measures of the Current L2 Self, Future L2 Self (consisting of an Ideal L2 Self, and an Ought-To Self), and the L2 Learning Experience. The strength of the self-concepts is measured across three different domains of Arabic: Classical, Modern Standard and Colloquial. The focus on learners’ self-concepts allows for an exploration of the effect of multiple factors on motivation towards Arabic, including religion. The relationship between Islam and Arabic is often given as a prominent reason behind some students’ desire to learn the language. Exactly how and why this factor features in learners’ L2 self-concepts has not yet been explored. Specifically designed surveys and interview protocols are proposed to facilitate the exploration of these constructs. The L2 Learning Experience component of the model is operationalized as learners’ task-based engagement. Engagement is conceptualised as multi-dimensional and malleable. In this model, situation-specific measures of cognitive, behavioural, and affective components of engagement are collected via specially designed repeated post-task self-report surveys on Personal Digital Assistant over multiple Arabic lessons. Tasks are categorised according to language learning skill. Given the domain-specific uses of the different varieties of Arabic, the relationship between learners’ engagement with different types of tasks and their overall motivational profiles will be examined to determine the extent of the interaction between the two constructs. A framework for this data analysis is proposed and hypotheses discussed. The unique combination of situation-specific measures of engagement and a person-oriented approach to measuring motivation allows for a macro- and micro-analysis of the interaction between learners and the Arabic learning process. By combining cross-sectional and longitudinal elements with a mixed-methods design, the model proposed offers the potential for capturing a comprehensive and detailed picture of the motivation and engagement of Arabic learners. The application of this framework offers a number of numerous potential pedagogical and research implications which will also be discussed.

Keywords: Arabic, diglossia, engagement, motivation, multiglossia, sociolinguistics

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