Search results for: work satisfaction and performance

Authors: Abdelsalam Omar

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This paper presents simulation-based case study that indicate the need for accurate dynamic modeling of distance protection relay. In many cases, a static analysis based on current and voltage phasors may be sufficient to assess the performance of distance protection. There are several circumstances under which such a simplified study does not provide the depth of analysis necessary to obtain accurate results, however. This letter present study of the influences of magnetizing inrush and power swing on the performance of distance protection relay. One type of numerical distance protection relay has been investigated: 7SA511. The study has been performed in order to demonstrate the relay response when dynamic model of distance relay is utilized.

Keywords: distance protection, magnitizing inrush, power swing, dynamic model of protection relays, simulatio

Procedia PDF Downloads 468

Authors: Julia Ive, Lucia Specia

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Understanding and detecting toxicity is an important problem to support safer human interactions online. Our work focuses on the important problem of contextual toxicity detection, where automated classifiers are tasked with determining whether a short textual segment (usually a sentence) is toxic within its conversational context. We use “toxicity” as an umbrella term to denote a number of variants commonly named in the literature, including hate, abuse, offence, among others. Detecting toxicity in context is a non-trivial problem and has been addressed by very few previous studies. These previous studies have analysed the influence of conversational context in human perception of toxicity in controlled experiments and concluded that humans rarely change their judgements in the presence of context. They have also evaluated contextual detection models based on state-of-the-art Deep Learning and Natural Language Processing (NLP) techniques. Counterintuitively, they reached the general conclusion that computational models tend to suffer performance degradation in the presence of context. We challenge these empirical observations by devising better contextual predictive models that also rely on NLP data augmentation techniques to create larger and better data. In our study, we start by further analysing the human perception of toxicity in conversational data (i.e., tweets), in the absence versus presence of context, in this case, previous tweets in the same conversational thread. We observed that the conclusions of previous work on human perception are mainly due to data issues: The contextual data available does not provide sufficient evidence that context is indeed important (even for humans). The data problem is common in current toxicity datasets: cases labelled as toxic are either obviously toxic (i.e., overt toxicity with swear, racist, etc. words), and thus context does is not needed for a decision, or are ambiguous, vague or unclear even in the presence of context; in addition, the data contains labeling inconsistencies. To address this problem, we propose to automatically generate contextual samples where toxicity is not obvious (i.e., covert cases) without context or where different contexts can lead to different toxicity judgements for the same tweet. We generate toxic and non-toxic utterances conditioned on the context or on target tweets using a range of techniques for controlled text generation(e.g., Generative Adversarial Networks and steering techniques). On the contextual detection models, we posit that their poor performance is due to limitations on both of the data they are trained on (same problems stated above) and the architectures they use, which are not able to leverage context in effective ways. To improve on that, we propose text classification architectures that take the hierarchy of conversational utterances into account. In experiments benchmarking ours against previous models on existing and automatically generated data, we show that both data and architectural choices are very important. Our model achieves substantial performance improvements as compared to the baselines that are non-contextual or contextual but agnostic of the conversation structure.

Keywords: contextual toxicity detection, data augmentation, hierarchical text classification models, natural language processing

Procedia PDF Downloads 154

Authors: M. L. Anitha, K. A. Radhakrishna Rao

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With the advent of modern computing technology, there is an increased demand for developing recognition systems that have the capability of verifying the identity of individuals. Recognition systems are required by several civilian and commercial applications for providing access to secured resources. Traditional recognition systems which are based on physical identities are not sufficiently reliable to satisfy the security requirements due to the use of several advances of forgery and identity impersonation methods. Recognizing individuals based on his/her unique physiological characteristics known as biometric traits is a reliable technique, since these traits are not transferable and they cannot be stolen or lost. Since the performance of biometric based recognition system depends on the particular trait that is utilized, the present work proposes a fusion approach which combines Inner knuckle print (IKP) trait of the middle, ring and index fingers with the geometrical features of hand. The hand image captured from a digital camera is preprocessed to find finger IKP as region of interest (ROI) and hand geometry features. Geometrical features are represented as the distances between different key points and IKP features are extracted by applying local binary pattern descriptor on the IKP ROI. The decision level AND fusion was adopted, which has shown improvement in performance of the combined scheme. The proposed approach is tested on the database collected at our institute. Proposed approach is of significance since both hand geometry and IKP features can be extracted from the palm region of the hand. The fusion of these features yields a false acceptance rate of 0.75%, false rejection rate of 0.86% for verification tests conducted, which is less when compared to the results obtained using individual traits. The results obtained confirm the usefulness of proposed approach and suitability of the selected features for developing biometric based recognition system based on features from palmar region of hand.

Keywords: biometrics, hand geometry features, inner knuckle print, recognition

Procedia PDF Downloads 210

Authors: Yi-Yu Huang, Chien-Kuo Wang, Sreerag Chota Veettil, Hang Zhang, Hu Yike

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Regarding the pressing issue of reducing energy consumption and carbon footprint of buildings, past research has focused more on analyzing the thermal performance of the extensive terrestrial green roofs with sedum plants in summer. However, the disadvantages of this type of green roof are relatively limited thermal performance, low extreme weather adaptability, relatively higher demands in maintenance, and lower added value in healing landscape. In view of this, this research aims to develop the extensive wetland green roofs with higher thermal performance, high extreme weather adaptability, low demands in maintenance, and high added value in healing landscape, and to measure its thermal performance for buildings in winter. The following factors are considered including the type and mixing formula of growth medium (light weight soil, akadama, creek gravel, pure water) and the type of aquatic plants. The research adopts a four-stage field experiment conducting on the rooftop of a building in a humid subtropical climate. The results found that emergent (Roundleaf rotala), submerged (Ribbon weed), floating-leaved (Water lily) wetland green roofs had similar thermal performance, and superior over wetland green roof without plant, traditional terrestrial green roof (without plant), and pure water green roof (without plant, nighttime only) in terms of overall passive cooling (8.00C) and thermal insulation (4.50C) effects as well as a reduction in heat amplitude (77-85%) in winter in a humid subtropical climate. The thermal performance of the free-floating (Water hyacinth) wetland green roof is inferior to that of the other three types of wetland green roofs, whether in daytime or nighttime.

Keywords: thermal performance, extensive wetland green roof, Aquatic plant, Winter , Humid subtropical climate

Procedia PDF Downloads 163

Authors: Zhenzhen Xu, Chunfu Shao, Shengyou Wang, Chunjiao Dong

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To improve the satisfaction of residents' travel, this paper analyzes the characteristics and influencing factors of urban residents' travel behavior. First, a Multinominal Logit Model (MNL) model is built to analyze the characteristics of residents' travel behavior, reveal the influence of individual attributes, family attributes and travel characteristics on the choice of travel mode, and identify the significant factors. Then put forward suggestions for policy improvement. Finally, Support Vector Machine (SVM) and Multi-Layer Perceptron (MLP) models are introduced to evaluate the policy effect. This paper selects Futian Street in Futian District, Shenzhen City for investigation and research. The results show that gender, age, education, income, number of cars owned, travel purpose, departure time, journey time, travel distance and times all have a significant influence on residents' choice of travel mode. Based on the above results, two policy improvement suggestions are put forward from reducing public transportation and non-motor vehicle travel time, and the policy effect is evaluated. Before the evaluation, the prediction effect of MNL, SVM and MLP models was evaluated. After parameter optimization, it was found that the prediction accuracy of the three models was 72.80%, 71.42%, and 76.42%, respectively. The MLP model with the highest prediction accuracy was selected to evaluate the effect of policy improvement. The results showed that after the implementation of the policy, the proportion of public transportation in plan 1 and plan 2 increased by 14.04% and 9.86%, respectively, while the proportion of private cars decreased by 3.47% and 2.54%, respectively. The proportion of car trips decreased obviously, while the proportion of public transport trips increased. It can be considered that the measures have a positive effect on promoting green trips and improving the satisfaction of urban residents, and can provide a reference for relevant departments to formulate transportation policies.

Keywords: neural network, travel characteristics analysis, transportation choice, travel sharing rate, traffic resource allocation

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Authors: Michelle W. T. Cheng, Yau Y.

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Hong Kong continues to be ranked as the least affordable housing market in the world, making co-living a feasible alternative in this high-density city. Although the number of co-living residences has increased in Hong Kong, co-living as a housing typology is still a new concept for many. Little research has been conducted on this new housing typology, let alone the co-living experience. To address this gap, this study targeted student residents in university residential halls as it is a more controlled environment (e.g., with established rules and guidelines regarding the use of communal facilitates and housing management) for studying co-living experiences in Hong Kong. To date, no research study has systematically identified anti-social behavior (ASB) in co-living spaces. Since ASB can be influenced by factors such as social norms and individual interpretation, it has an elastic definition that results in different levels of acceptance. Unlike other types of housing, co-living spaces can be potentially more influenced by the neighborhood as residents share more time and space. As a pilot study, this research targeted one university residential hall to examine student co-living experiences. To clarify, the research question is focused on identifying the social factors that impact the residential satisfaction of those who co-living in residential halls. Quantitative data (n=100) were collected via a structured questionnaire to measure the residential environment, including ASB, social neighboring, community attachment, and perceived hall management efficacy. The survey was distributed at the end of the academic year to ensure that respondents had at least one year of first-hand experience living in a co-living space. To gather qualitative data, follow-up focus group interviews were conducted with 16 participants who completed the survey. The semi-structured interviews aimed to elicit the participants' perspectives on their co-living experience. Through analyzing their co-living experiences, the researcher identified factors that affected their residential satisfaction and provided recommendations to enhance their co-living experience.

Keywords: co-living, university residential hall, anti-social behabiour, neighbour relationship, community attachement

Procedia PDF Downloads 66

Authors: Itumeleng Judith Maome, Robert Walter Dumisani Zondo

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The concept of Corporate Social Responsibility (CSR) has gained popularity as a management philosophy in companies. They integrate social and environmental concerns into their operations and interactions with stakeholders. While CSR has mostly been associated with large organisations, it contributes to societal goals by engaging in activities or supporting volunteering or ethically oriented practices. However, small and medium enterprises (SMEs) have been recognised for their contributions to the social and economic development of any country. Consequently, this study examines the effect of CSR practices on human resource performance in the selected manufacturing SME in South Africa. This study was quantitative in design and examined the production and related experiences of the manufacturing SME organisation that had adopted a CSR strategy for human resource improvement. The study was achieved by collecting pre- and post-quarterly data, overtime, for employee turnover and labour absenteeism for analysis using the regression model. The results indicate that both employee turnover and labour absenteeism have no relationship with human resource performance post-CSR implementation. However, CSR has a relationship with human resource performance. Any increase in CSR activities results in an increase in human resource performance.

Keywords: corporate social responsibility, employee turnover, human resource, labour absenteeism, manufacturing SME

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Authors: Hamida Qumber Ali, Waseem Muhammad Arain, Shama Siddiqui, Sayeed Ghani

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We present an implementing of RMAC in TinyOS 1.x. RMAC is a cross layer and Duty-cycle MAC protocols that was proposed to provide energy efficient transmission services for wireless sensor networks. The protocol has a unique and efficient packet transmission scheduling mechanism that enables it to overcome delivery latency and overcome traffic congestion. Design details and implementation challenges are divulged. Experiments are conducted to show the correctness of our implementation with numerous assumptions. Simulations are performed to compare the performance of RMAC and SMAC. Our results show that RMAC outperforms SMAC in energy efficiency and delay.

Keywords: MAC protocol, performance, RMAC, wireless sensor networks

Procedia PDF Downloads 301

Authors: Joselito Medina-Marin, Maria G. Serna-Diaz, Alejandro Tellez-Jurado, Juan C. Seck-Tuoh-Mora, Eva S. Hernandez-Gress, Norberto Hernandez-Romero, Iaina P. Medina-Serna

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Trichoderma harzianum is a fungus that has been utilized as a low-cost fungicide for biological control of pests, and it is important to determine the optimal conditions to produce the highest amount of conidiospores of Trichoderma harzianum. In this work, the conidiospore production of Trichoderma harzianum is modeled and optimized by using Artificial Neural Networks (AANs). In order to gather data of this process, 30 experiments were carried out taking into account the number of hours of culture (10 distributed values from 48 to 136 hours) and the culture humidity (70, 75 and 80 percent), obtained as a response the number of conidiospores per gram of dry mass. The experimental results were used to develop an iterative algorithm to create 1,110 ANNs, with different configurations, starting from one to three hidden layers, and every hidden layer with a number of neurons from 1 to 10. Each ANN was trained with the Levenberg-Marquardt backpropagation algorithm, which is used to learn the relationship between input and output values. The ANN with the best performance was chosen in order to simulate the process and be able to maximize the conidiospores production. The obtained ANN with the highest performance has 2 inputs and 1 output, three hidden layers with 3, 10 and 10 neurons in each layer, respectively. The ANN performance shows an R2 value of 0.9900, and the Root Mean Squared Error is 1.2020. This ANN predicted that 644175467 conidiospores per gram of dry mass are the maximum amount obtained in 117 hours of culture and 77% of culture humidity. In summary, the ANN approach is suitable to represent the conidiospores production of Trichoderma harzianum because the R2 value denotes a good fitting of experimental results, and the obtained ANN model was used to find the parameters to produce the biggest amount of conidiospores per gram of dry mass.

Keywords: Trichoderma harzianum, modeling, optimization, artificial neural network

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Authors: Sameh Frikha, Mohamed Salah Abid

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We investigate the performance of an integrated cascade (IC) refrigeration system which uses environment friendly zeotropic mixtures. Computational calculation has been carried out by varying pressure level at the evaporator and the condenser of the system. Effects of mass flow rate of the refrigerant on the coefficient of performance (COP) are presented. We show that the integrated cascade system produces ultra-low temperatures in the evaporator by using environment friendly zeotropic mixture.

Keywords: coefficient of performance, environment friendly zeotropic mixture, integrated cascade, ultra low temperature, vapor compression refrigeration cycles

Procedia PDF Downloads 245

Authors: Liu Li, Kim Seng Lee, Li Lu

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The high-energy-density Li-rich layered materials are promising cathode materials for the next-generation high-performance lithium-ion batteries. The relatively low rate capability is one of the major problems that limit their practical application. In this work, Li-rich layered Li1.2Mn0.54Ni0.13Co0.13O2 cathode material synthesized by coprecipitation method is further modified by F doping or surface treatment to enhance its cycling stability as well as rate capability.

Keywords: Li-ion battery, Li-rich layered cathode material, phase transformation, cycling stability, rate capacility

Procedia PDF Downloads 344

Authors: Mohamed Hassan, Rahul Gajbhiye

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The high mobility and gravity override of CO₂ gas can be minimized by generating the CO₂ foam with the aid of surfactant. However, CO₂ is unable to generate the foam/stable foam above its supercritical point (1100 psi, 31°C). These difficulties with CO₂ foam is overcome by adding N₂ in small fraction to enhance the foam generation of CO₂ at supercritical conditions. This study shows how the addition of small quantity of N₂ helps in generating the CO₂ foam and performance of the CO₂/N₂ mixture foam in enhanced oil recovery. To investigate the performance of CO₂/N₂ foam, core-flooding experiments were conducted at elevated pressure and temperature condition (higher than supercritical CO₂ - 50°C and 1500 psi) in sandstone cores. Fluorosurfactant (FS-51) was used as a foaming agent, and n-decane was used as model oil in all the experiments. The selection of foam quality and N₂ fraction was optimized based on foam generation and stability tests. Every gas or foam flooding was preceded by seawater injection to simulate the behavior in the reservoir. The results from the core-flood experiments showed that the CO₂ and CO₂/N₂ foam flooding recovered an additional 34-40% of Original Initial Oil in Place (OIIP) indicating that foam flooding succeeded in producing more oil than pure CO₂ gas injection processes. Additionally, the performance CO₂/N₂ foam injection was better than CO₂ foam injection.

Keywords: CO₂/N₂ foam, enhanced oil recovery (EOR), supercritical CO₂, sweep efficiency

Procedia PDF Downloads 266

Authors: Fan Wei, Tang Yipeng

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The outbreak of COVID-19 in early 2020 has been raging around the world, which has severely affected people's work and life. In today's post-pandemic era, although the pandemic has been effectively controlled, people still need to maintain social distancing at all times to prevent the further spread of the virus. Based on this, social distancing in the context of the pandemic has aroused widespread attention from scholars. At present, most studies exploring the influencing factors of social distancing are studying the negative impact of social distancing on the physical and mental state of special groups from the inter-individual level, and their more focus on the forced complete social distancing during the severe period of the pandemic. Few studies have focused on the impact of social distancing on working groups in the post-pandemic era from the within-individual level. In order to explore this problem, this paper constructs a cross-level moderating model based on resource conservation theory from the perspective of psychological resources. A total of 81 subjects were recruited to fill in the three-stage questionnaires each day for 10 working days, and 661valid questionnaires were finally obtained. Through the empirical tests, the following conclusions were finally obtained: (1) At the within-individual level, daily social distancing is positively correlated with the second day’s recovery, and the individual’s low sociability regulates the relationship between social distancing and recovery. The indirect effect of daily social distancing through recovery has positive relationship employees’ work engagement and work-goal progress only when the individual has low sociability. For individuals with high sociability, none of these paths are significant. (2) At the within-individual level, there is a significant relationship between individual's recovery and work engagement and work-goal progress, indicating that the recovery of resources can produce positive work outcomes. According to the results, this study believes that in the post-pandemic era, social distancing can not only effectively prevent and control the pandemic but also have positive impacts. Employees can use the time and energy originally saved for social activities through social distancing to invest in things that can provide resources and help them recover.

Keywords: social distancing, recovery, work engagement, work goal progress, sociability

Procedia PDF Downloads 117

Authors: J. G. Batista, T. S. Santiago, E. A. Ribeiro, G. A. P. Thé

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This work deals with parameter identification of permanent magnet motors, a class of ac motor which is particularly important in industrial automation due to characteristics like applications high performance, are very attractive for applications with limited space and reducing the need to eliminate because they have reduced size and volume and can operate in a wide speed range, without independent ventilation. By using experimental data and genetic algorithm we have been able to extract values for both the motor inductance and the electromechanical coupling constant, which are then compared to measure and/or expected values.

Keywords: modeling, AC servomotor, permanent magnet synchronous motor-PMSM, genetic algorithm, vector control, robotic manipulator, control

Procedia PDF Downloads 505

Authors: N. Arunraj, C. P. V. Paul, D. M. D. Jayawardena, W. N. D. Fernando

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Traffic congestion with increased numbers of vehicles is already a serious issue for many countries. The absence of sufficient parking spaces adds to the issue. Motorists are forced to wait in long queues to park their vehicles. This adds to the inconvenience faced by a motorist, kept waiting for a slot allocation, manually done along with the parking payment calculation. In Sri Lanka, nowadays, parking systems use barcode technology to identify the vehicles at both the entrance and the exit points. Customer management is handled by the use of man power. A parking space is, generally permanently sub divided according to the vehicle type. Here, again, is an issue. Parking spaces are not utilized to the maximum. The current arrangement leaves room for unutilized parking spaces. Accordingly, there is a need to manage the parking space dynamically. As a vehicle enters the parking area, available space has to be assigned for the vehicle according to the vehicle type. The system, Automated Parking System (APS), provides an automated solution using RFID Technology to identify the vehicles. Simultaneously, an algorithm manages the space allocation dynamically. With this system, there is no permanent parking slot allocation for a vehicle type. A desktop application manages the customer. A Web application is used to manage the external users with their reservations. The system also has an android application to view the nearest parking area from the current location. APS is built using java and php. It uses LED panels to guide the user inside the parking area to find the allocated parking slot accurately. The system ensures efficient performance, saving precious time for a customer. Compared with the current parking systems, APS interacts with users and increases customer satisfaction as well.

Keywords: RFID, android, web based system, barcode, algorithm, LED panels

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Authors: Samira Ghizellaoui, Manel Boumagoura

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The municipality of Constantine in eastern Algeria draws water from the Hamma groundwater source. The high fouling capacity is due to the high content of bicarbonate (442 mg/L) and calcium (136 mg/L). This work focuses on the use of three new green inhibitors for reducing calcium carbonate scale formation: gallic acid, quercetin and alginate, and on the comparison between them. These inhibitors have proven to be green antiscalants because they have no impact on the environment. Electrochemical methods (chronoamperometry and impedancemetry) were used to evaluate their performance. According to the study, these inhibitors are excellent green chemical inhibitors of scaling, and the best inhibitor is quercetin because it gave a good result with a lower concentration (2mg/L) compared to others inhibitors.

Keywords: scaling, green inhibitor, chronoamperometry, impedancemetry

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Authors: Yvonne A. Unrau

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Social work education is a competency-based curriculum that relies mostly on cognitive frameworks and problem-solving models. Absent from the curriculum is knowledge and skills that draw from an embodiment perspective, especially somatic practice methods. Embodiment broadly encompasses the understanding that biological, political, historical, and social factors impact human development via changes to the nervous system. In the past 20 years, research has well-established that unresolved traumatic events, especially during childhood, negatively impacts long-term health and well-being. Furthermore, traumatic stress compromises cognitive processing and activates reflexive action such as ‘fight’ or ‘flight,’ which are the focus of somatic methods. The main objective of this paper is to show how embodiment perspectives and somatic methods can enhance social work practice overall. Using an exploratory approach, the author shares a decade-long journey that involved creating an education-support program for college students who exited the state foster care system. Personal experience, program outcomes and case study narratives revealed that ‘classical’ social work methods were insufficient to fully address the complex needs of college students who were living with complex traumatic stressors. The paper chronicles select case study scenarios and key program development milestones over a 10-year period to show the benefit of incorporating embodiment perspectives in social work practice. The lessons reveal that there is an immediate need for social work curriculum to include embodiment perspectives so that social workers may be equipped to respond competently to their many clients who live with unresolved trauma.

Keywords: social work practice, social work curriculum, embodiment, traumatic stress

Procedia PDF Downloads 111

Authors: Minase Yitbarek Mengistu, Abrham Melkamu, Dawit Yisfaw, Bisrat Belihu, Abdulhakim Lalega

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This research was aimed at reducing and recycling waste paper and sawdust from our environment, thereby reducing environmental pollution resulting from the management/disposal of these waste materials. In this research, some mechanical properties of composite ceiling board materials made from waste paper, sawdust, and pineapple leaf fibers were investigated to determine their suitability for use in low-cost construction work. The ceiling board was obtained from the waste of paper, sawdust chips, and pineapple leaf fibers by manual mechanical bonding techniques using dissolved polystyrene films as a binding agent. The results obtained showed that the water absorption values of between 6 % and 8.1 %; as well as density values of 500 kg/mm3 and 611.1 kg/mm3.From our result, the better one is a ratio of pineapple leaf fiber 25%, sawdust 40%, binder 25%, and waste paper 10%. The composite ceiling boards were successfully nailed with firm grips. These values obtained were compared with those of the conventional ceiling boards and it was observed that these composite materials can be used for internal low-cost construction work and Insulation (acoustic and thermal) performance. It is highly recommended that small and medium enterprises be encouraged to venture into waste recycling and the production of these composite ceiling materials to create jobs for skilled and unskilled labor that are locally available.

Keywords: composite material, environment, textile, ceiling board

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Authors: Jiao Sun, Li Pan, Shijun Liu

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Recommender systems have been widely used in contemporary industry, and plenty of work has been done in this field to help users to identify items of interest. Collaborative Filtering (CF, for short) algorithm is an important technology in recommender systems. However, less work has been done in automobile recommendation system with the sharp increase of the amount of automobiles. What’s more, the computational speed is a major weakness for collaborative filtering technology. Therefore, using MapReduce framework to optimize the CF algorithm is a vital solution to this performance problem. In this paper, we present a recommendation of the users’ comment on industrial automobiles with various properties based on real world industrial datasets of user-automobile comment data collection, and provide recommendation for automobile providers and help them predict users’ comment on automobiles with new-coming property. Firstly, we solve the sparseness of matrix using previous construction of score matrix. Secondly, we solve the data normalization problem by removing dimensional effects from the raw data of automobiles, where different dimensions of automobile properties bring great error to the calculation of CF. Finally, we use the MapReduce framework to optimize the CF algorithm, and the computational speed has been improved times. UV decomposition used in this paper is an often used matrix factorization technology in CF algorithm, without calculating the interpolation weight of neighbors, which will be more convenient in industry.

Keywords: collaborative filtering, recommendation, data normalization, mapreduce

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Authors: Hasti Abbasi

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Creative writers have long followed the tradition of romantic exile, looking inward in an attempt to construct new viewpoints through the power of imagination. The writer, who attempts to resist uncertainty and locate her place in the new country through writing, resists creativity itself. For a writer, certain satisfaction can be achieved through producing a creative art away from the anxiety of the sense of dislocation. Dislocation, whether enforced or self-inflicted, could in many ways be a disaster but it could also cultivate a greater creative capacity and be a source of creative expression. This paper will investigate the idea of the creative writer as exiled self through reflections on the relationship between dislocation and writing.

Keywords: dislocation, creative writing, remaking identity, exile literature

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Authors: Pakinee Aimmanee, Phoom Chokratsamesiri

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Search engine has become an essential tool nowadays for people to search for their needed information on the internet. In this work, we evaluate the performance of the search engine from three factors: the keyword frequency, the number of inbound links, and the difficulty of the keyword. The evaluations are based on the ranking position and the number of days that Google has seen or detect the webpage. We find that the keyword frequency and the difficulty of the keyword do not affect the Google ranking where the number of inbound links gives remarkable improvement of the ranking position. The optimal number of inbound links found in the experiment is 10.

Keywords: SEO, information retrieval, web search, knowledge technologies

Procedia PDF Downloads 269

Authors: E. Ghayoula, M. Haj Taieb, A. Bouallegue, J. Y. Chouinard, R. Ghayoula

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This paper evaluates the bit error rate (BER) performance of MIMO systems for wireless communication. MIMO uses multiple transmitting antennas, multiple receiving antennas and the space-time block codes to provide diversity. MIMO transmits signal encoded by space-time block (STBC) encoder through different transmitting antennas. These signals arrive at the receiver at slightly different times. Spatially separated multiple receiving antennas are employed to provide diversity reception to combat the effect of fading in the channel. This paper presents a detailed study of diversity coding for MIMO systems. STBC techniques are implemented and simulation results in terms of the BER performance with varying number of MIMO transmitting and receiving antennas are presented. Our results show how increasing the number of both transmit and receive antenna improves system performance and reduces the bit error rate.

Keywords: MIMO systems, diversity, BER, MRRC, SIMO, MISO, STBC, alamouti, SNR

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Authors: Shital Suresh Borse, Vijayalaxmi Kadroli

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E-commerce industries nowadays implement the latest AI, ML Techniques to improve their own performance and prediction accuracy. This helps to gain a huge profit from the online market. Ant Colony Optimization, Genetic algorithm, Particle Swarm Optimization, Neural Network & GWO help many e-commerce industries for up-gradation of their predictive performance. These algorithms are providing optimum results in various applications, such as stock price prediction, prediction of drug-target interaction & user ratings of similar products in e-commerce sites, etc. In this study, customer reviews will play an important role in prediction analysis. People showing much interest in buying a lot of services& products suggested by other customers. This ultimately increases net profit. In this work, a convolution neural network (CNN) is proposed which further is useful to optimize the prediction accuracy of an e-commerce website. This method shows that CNN is used to optimize hyperparameters of GWO algorithm using an appropriate coding scheme. Accurate model results are verified by comparing them to PSO results whose hyperparameters have been optimized by CNN in Amazon's customer review dataset. Here, experimental outcome proves that this proposed system using the GWO algorithm achieves superior execution in terms of accuracy, precision, recovery, etc. in prediction analysis compared to the existing systems.

Keywords: prediction analysis, e-commerce, machine learning, grey wolf optimization, particle swarm optimization, CNN

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Authors: Afif Saleh Abugharsa

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The IEEE 802.15.4 standard is designed for low-rate wireless personal area networks (LR-WPAN) with focus on enabling wireless sensor networks. It aims to give a low data rate, low power consumption, and low cost wireless networking on the device-level communication. The objective of this study is to investigate the performance of IEEE 802.15.4 based networks using simulation tool. In this project the network simulator 2 NS2 was used to several performance measures of wireless sensor networks. Three scenarios were considered, multi hop network with a single coordinator, star topology, and an ad hoc on demand distance vector AODV. Results such as packet delivery ratio, hop delay, and number of collisions are obtained from these scenarios.

Keywords: ZigBee, wireless sensor networks, IEEE 802.15.4, low power, low data rate

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Authors: Chanthima Phromket, Jakret Mettathamrong, Parnisara Prajudtasri

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The purpose of this paper is to investigate the relationship between effects of service quality management capability and business alliance effectiveness on the performance of tourist agency business in Thailand: The moderating role of organizational climate. A survey was used as a research instrument and was given to the owner/managers of tourist agency business in Thailand. The model is tested using the data collected from 400 tourist agency business in Thailand. The results indicate that service quality management capability have the positive influence on business alliance effectiveness and performance. Trust, commitment, and cooperation are the antecedents that have a positive effect on the performance, and the results show non-significant when it is moderated by Organizational climate. Thus, contributions and suggestions are also provided for further research.

Keywords: service quality management capability, business alliance effectiveness, organizational climate, tourist agency

Procedia PDF Downloads 375

Authors: Zhou Yang, Heli Sun, Jianbin Huang, Jizhong Zhao, Shaojie Qiao

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Traffic prediction is essential in a multitude of ways in modern urban life. The researchers of earlier work in this domain carry out the investigation chiefly with two major focuses: (1) the accurate forecast of future values in multiple time series and (2) knowledge extraction from spatial-temporal correlations. However, two key considerations for traffic prediction are often missed: the completeness of raw data and the full context of the prediction timestamp. Concentrating on the two drawbacks of earlier work, we devise an approach that can address these issues in a two-phase framework. First, we utilize the raw trajectories to a greater extent through building a VLA table and data compression. We obtain the intra-trajectory features with graph-based encoding and the intertrajectory ones with a grid-based model and the technique of back projection that restore their surrounding high-resolution spatial-temporal environment. To the best of our knowledge, we are the first to study direct feature extraction from raw trajectories for traffic prediction and attempt the use of raw data with the least degree of reduction. In the prediction phase, we provide a broader context for the prediction timestamp by taking into account the information that are around it in the training dataset. Extensive experiments on several well-known datasets have verified the effectiveness of our solution that combines the strength of raw trajectory data and prediction context. In terms of performance, our approach surpasses several state-of-the-art methods for traffic prediction.

Keywords: traffic prediction, raw data utilization, context building, data reduction

Procedia PDF Downloads 111

Authors: Alexandria Carey, Angela Starkweather, Ann Horgas, Hwayoung Cho, Jason Beneciuk

Abstract:

Background/Significance: Over 3.4 million acute axial low back pain (aLBP) cases are treated annually in the United States (US) emergency departments (ED). ED patients with aLBP receive varying verbal and written discharge routine care (RC), leading to ineffective patient self-management. Ineffective self-management increase chronic low back pain (cLPB) transition risks, a chief cause of worldwide disability, with associated costs >$60 million annually. This research addresses this significant problem by evaluating an ED digital pain self-management intervention (EDPSI) focused on improving self-management through improved knowledge retainment, skills, and self-efficacy (confidence) (KSC) thus reducing aLBP to cLBP transition in ED patients discharged with aLBP. The research has significant potential to increase self-efficacy, one of the most potent mechanisms of behavior change and improve health outcomes. Focusing on accessibility and usability, the intervention may reduce discharge disparities in aLBP self-management, especially with low health literacy. Study Questions: This research will answer the following questions: 1) Will an EDPSI focused on improving KSC progress patient self-management behaviors and health status?; 2) Is the EDPSI sustainable to improve pain severity, interference, and pain recurrence?; 3) Will an EDPSI reduce aLBP to cLBP transition in patients discharged with aLBP? Aims: The pilot randomized-controlled trial (RCT) study’s objectives assess the effects of a 12-week digital self-management discharge tool in patients with aLBP. We aim to 1) Primarily assess the feasibility [recruitment, enrollment, and retention], and [intervention] acceptability, and sustainability of EDPSI on participant’s pain self-management; 2) Determine the effectiveness and sustainability of EDPSI on pain severity/interference among participants. 3) Explore patient preferences, health literacy, and changes among participants experiencing the transition to cLBP. We anticipate that EDPSI intervention will increase likelihood of achieving self-management milestones and significantly improve pain-related symptoms in aLBP. Methods: The study uses a two-group pilot RCT to enroll 30 individuals who have been seen in the ED with aLBP. Participants are randomized into RC (n=15) or RC + EDPSI (n=15) and receive follow-up surveys for 12-weeks post-intervention. EDPSI innovative content focuses on 1) highlighting discharge education; 2) provides self-management treatment options; 3) actor demonstration of ergonomics, range of motion movements, safety, and sleep; 4) complementary alternative medicine (CAM) options including acupuncture, yoga, and Pilates; 5) combination therapies including thermal application, spinal manipulation, and PT treatments. The intervention group receives Booster sessions via Zoom to assess and reinforce their knowledge retention of techniques and provide return demonstration reinforcing ergonomics, in weeks two and eight. Outcome Measures: All participants are followed for 12-weeks, assessing pain severity/ interference using the Brief Pain Inventory short-form (BPI-sf) survey, self-management (measuring KSC) using the short 13-item Patient Activation Measure (PAM), and self-efficacy using the Pain Self-Efficacy Questionnaire (PSEQ) weeks 1, 6, and 12. Feasibility is measured by recruitment, enrollment, and retention percentages. Acceptability and education satisfaction are measured using the Education-Preference and Satisfaction Questionnaire (EPSQ) post-intervention. Self-management sustainment is measured including PSEQ, PAM, and patient satisfaction and healthcare utilization (PSHU) requesting patient overall satisfaction, additional healthcare utilization, and pain management related to continued back pain or complications post-injury.

Keywords: digital, pain self-management, education, tool

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Authors: Jeni A. Popescu, Sorin G. Tomescu, Valeriu A. Vilag

Abstract:

The paper focuses on the potential methods of increasing the performance of a microturbine by combining additional elements available for utilization in a cogeneration plant. The activity is carried out within the framework of a project aiming to develop, manufacture and test a microturbine functional model with high potential in energetic industry utilization. The main goal of the analysis is to determine the parameters of the fluid flow passing through each section of the turbine, based on limited data available in literature for the focus output power range or provided by experimental studies, starting from a reference cycle, and considering different cycle options, including simple, intercooled and recuperated options, in order to optimize a small cogeneration plant operation. The studied configurations operate under the same initial thermodynamic conditions and are based on a series of assumptions, in terms of individual performance of the components, pressure/velocity losses, compression ratios, and efficiencies. The thermodynamic analysis evaluates the expected performance of the microturbine cycle, while providing a series of input data and limitations to be included in the development of the experimental plan. To simplify the calculations and to allow a clear estimation of the effect of heat transfer between fluids, the working fluid for all the thermodynamic evolutions is, initially, air, the combustion being modelled by simple heat addition to the system. The theoretical results, along with preliminary experimental results are presented, aiming for a correlation in terms of microturbine performance.

Keywords: cogeneration, microturbine, performance, thermodynamic analysis

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Authors: Salma Mefteh-Wali, Marie-Josephe Rigobert

Abstract:

We investigate the impact of foreign currency debt on firm performance for a sample of non-financial French firms studied over the period 2002 to 2012. As foreign currency debt is both a financing and hedging instrument against foreign exchange risk, we mobilize optimal hedging theory and capital structure theory. When we study the impact on firm value, our main results show that before and after the financial crisis of 2008, foreign debt had the same behavior as domestic debt. We find that during the crisis period, foreign debt positively affects firm value. Investors perceive foreign debt as a natural hedging instrument that is likely to reduce the costs of underinvestment, alleviate cash flow volatility, limit the costs of financial distress, and generate tax shield benefits. Also, our results show that foreign leverage negatively affects the firm performance proxied by ROA and ROE, during and after the financial crisis. However, this impact is positive in the pre-crisis period.

Keywords: foreign currency derivatives, foreign currency debt, foreign currency hedging, firm performance

Procedia PDF Downloads 290

Authors: Palash Bandyopadhyay

Abstract:

Background and significance of the study: Crude oil and natural gas is of crucial importance due to its increasing demand in India. The demand has been increased because of change of lifestyle overtime. Since India has poor utilization of oil production capacity, constantly the import of it has been increased progressively day by day. This ultimately hit the foreign exchange reserves of India, however it negatively affect the Indian economy as well. The financial performance of crude oil and natural gas companies in India has been trimmed down year after year because of underutilization of production capacity, enhancement of demand, change in life style, and change in import bill and outflows of foreign currencies. In this background, the current study seeks to measure the financial performance of crude oil and natural gas companies of India in the post liberalization period. Keeping in view of this, this study assesses the financial performance in terms of liquidity management, solvency, efficiency, financial stability, and profitability of the companies under study. Methodology: This research work is encircled on yearly ratio data collected from Centre for Monitoring Indian Economy (CMIE) Prowess database for the periods between 1993-94 and 2012-13 with 20 observations using liquidity, solvency and efficiency indicators, profitability indicators and financial stability indicators of all the major crude oil and natural gas companies in India. In the course of analysis, descriptive statistics, correlation statistics, and linear regression test have been utilized. Major findings: Descriptive statistics indicate that liquidity position is satisfactory in case of three crude oil and natural gas companies (Oil and Natural Gas Companies Videsh Limited, Oil India Limited and Selan exploration and transportation Limited) out of selected companies under study but solvency position is satisfactory only for one company (Oil and Natural Gas Companies Videsh Limited). However, efficiency analysis points out that Oil and Natural Gas Companies Videsh Limited performs effectively the management of inventory, receivables, and payables, but the overall liquidity management is not well. Profitability position is very much satisfactory in case of all the companies except Tata Petrodyne Limited, but profitability management is not satisfactory for all the companies under study. Financial stability analysis shows that all the companies are more dependent on debt capital, which bears a financial risk. Correlation and regression test results illustrates that profitability is positively and negatively associated with liquidity, solvency, efficiency, and financial stability indicators. Concluding statement: Management of liquidity and profitability of crude oil and natural gas companies in India should have been improved through controlling unnecessary imports in spite of the heavy demand of crude oil and natural gas in India and proper utilization of domestic oil reserves. At the same time, Indian government has to concern about rupee depreciation and interest rates.

Keywords: financial performance, crude oil and natural gas companies, India, linear regression

Procedia PDF Downloads 308