Search results for: random coefficients model

Authors: Ammar Y. Alqahtani

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In order to minimize the negative impact on the environment, it is essential to manage the waste that generated from the premature disposal of end-of-life (EOL) products properly. Consequently, government and international organizations introduced new policies and regulations to minimize the amount of waste being sent to landfills. Moreover, the consumers’ awareness regards environment has forced original equipment manufacturers to consider being more environmentally conscious. Therefore, manufacturers have thought of different ways to deal with waste generated from EOL products viz., remanufacturing, reusing, recycling, or disposing of EOL products. The rate of depletion of virgin natural resources and their dependency on the natural resources can be reduced by manufacturers when EOL products are treated as remanufactured, reused, or recycled, as well as this will cut on the amount of harmful waste sent to landfills. However, disposal of EOL products contributes to the problem and therefore is used as a last option. Number of EOL need to be estimated in order to fulfill the components demand. Then, disassembly process needs to be performed to extract individual components and subassemblies. Smart products, built with sensors embedded and network connectivity to enable the collection and exchange of data, utilize sensors that are implanted into products during production. These sensors are used for remanufacturers to predict an optimal warranty policy and time period that should be offered to customers who purchase remanufactured components and products. Sensor-provided data can help to evaluate the overall condition of a product, as well as the remaining lives of product components, prior to perform a disassembly process. In this paper, a multi-period disassembly-to-order (DTO) model is developed that takes into consideration the different system uncertainties. The DTO model is solved using Nonlinear Programming (NLP) in multiple periods. A DTO system is considered where a variety of EOL products are purchased for disassembly. The model’s main objective is to determine the best combination of EOL products to be purchased from every supplier in each period which maximized the total profit of the system while satisfying the demand. This paper also addressed the impact of sensor embedded products on the cost of warranties. Lastly, this paper presented and analyzed a case study involving various simulation conditions to illustrate the applicability of the model.

Keywords: closed-loop supply chains, environmentally conscious manufacturing, product recovery, reverse logistics

Procedia PDF Downloads 141

Authors: Arya Pirooz

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The effects of different fuels (DME, RME B100, and SME B100) on barrel engines were studied as a general, single dimensional investigation for characterization of these types of engines. A base computational model was created as reference point to be used as a point of comparison with different cases. The models were computed using the commercial computational fluid dynamics program, Diesel-RK. The base model was created using basic dimensions of the PAMAR-3 engine with inline unit injectors. Four fuel cases were considered. Optimized models were also considered for diesel and DME cases with respect to injection duration, fuel, injection timing, exhaust and intake port opening, CR, angular offset. These factors were optimized for highest BMEP, combined PM and NOx emissions, and highest SFC. Results included mechanical efficiency (eta_m), efficiency and power, emission characteristics, combustion characteristics. DME proved to have the highest performing characteristics in relation to diesel and RME fuels for this type of barrel engine.

Keywords: DME, RME, Diesel-RK, characterization, inline unit injector

Procedia PDF Downloads 480

Authors: Ahmad K. Samaila, Basant K. Jha

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This paper presents the effects of suction/injection of transient/steady natural convection flow of reactive viscous fluid in a vertical porous pipe. The mathematical model capturing the time dependent flow of viscous reactive fluid is solved using implicit finite difference method while the corresponding steady state model is solved using regular perturbation technique. Results of analytical and numerical solutions are reported for various parametric conditions to illustrate special features of the solutions. The coefficient of skin friction and rate of heat transfer are obtained and illustrated graphically. The numerical solution is shown to be in excellent agreement with the closed form analytical solution. It is interesting to note that time required to reach steady state is higher in case of injection in comparison to suction.

Keywords: porous pipe, reactive viscous fluid, transient natural-convective flow, analytical solution

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Authors: Mircea Pastrav, Horia Constantinescu

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The construction industry is currently trying to develop sustainable reinforced concrete structures. In trying to aid in the effort, the research presented in this paper aims to prove the efficiency of modified special hybrid moment frames composed of discretely jointed precast and post-tensioned concrete members. This aim is due to the fact that current design standards do not cover the spatial design of moment frame structures assembled by post-tensioning with special hybrid joints. This lack of standardization is coupled with the fact that previous experimental programs, available in scientific literature, deal mainly with plane structures and offer little information regarding spatial behavior. A spatial model of a modified hybrid moment frame is experimentally analyzed. The experimental results of a natural scale model test of a corner column-beams sub-structure, cut from an actual multilevel building tested to seismic type loading are presented in order to highlight the behavior of this type of structure. The test is performed under alternative cycles of imposed lateral displacements, up to a storey drift ratio of 0.035. Seismic response of the spatial model is discussed considering the acceptance criteria for reinforced concrete frame structures designed based on experimental tests, as well as some of its major sustainability features. The results obtained show an overall excellent behavior of the system. The joint detailing allows for quick and cheap repairs after an accidental event and a self-balancing behavior of the system that ensures it can be used almost immediately after an accidental event it.

Keywords: modified hybrid joint, seismic type loading response, self-balancing structure, acceptance criteria

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Authors: Azidah Abu Ziden, Adu Ifedayo Emmanuel

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This study investigated the optical board as an artificial technology for peer teaching in a Nigerian university. A design and development research (DDR) design was adopted, which entailed the planning and testing of instructional design models adopted to produce the optical board. This research population involved twenty-five (25) peer-teaching students at a Nigerian university consisting of theatre arts, religion, and language education-related disciplines. Also, using a random sampling technique, this study selected eight (8) students to work on the optical board. Besides, this study introduced a research instrument titled lecturer assessment rubric containing 30-mark metrics for evaluating students’ teaching with the optical board. In this study, it was discovered that the optical board affords students acquisition of self-employment skills through their exposure to the peer teaching course, which is a teacher training module in Nigerian universities. It is evident in this study that students were able to coordinate their design and effectively develop the optical board without lecturer’s interference. This kind of achievement in this research shows that the Nigerian university curriculum had been designed with contents meant to spur students to create jobs after graduation, and effective implementation of the readily available curriculum contents is enough to imbue students with the needed entrepreneurial skills. It was recommended that the Federal Government of Nigeria (FGN) must discourage the poor implementation of Nigerian university curriculum and invest more in the betterment of the readily available curriculum instead of considering a synonymously acclaimed new curriculum for regurgitated teaching and learning process.

Keywords: optical board, artificial technology, peer teaching, educational technology, Nigeria, Malaysia, university, glass, wood, electrical, improvisation

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Authors: Avi Shrivastava

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Title 42, an emergency health decree, has forced the federal authorities to turn away asylum seekers and all other border crossers since last year. When Title 42 was first deployed in immigration detention centers, where many migrants are held when they arrive at the U.S.-Mexico border, the Trump administration embraced it as a strategy. Expulsions Policy and New Border Challenges will be examined in regard to Title 42 concerns. Humanitarian measures for refugees arriving at the US-Mexico border are the focus of this article. To a large extent, this article addresses the implications of the United States' use of Title 42 in expelling refugees and the possible ramifications of doing away with it. A secondary data collecting strategy was used to gather the information for this study, allowing researchers to examine a large number of previously collected data sets. Information about Title 42 may be found in a variety of places, such as scholarly publications, newspapers, books, and the internet. The inquiry employed qualitative and explanatory research approaches. The claim that 1.7 million individuals were forced to leave the country as a result of it was withdrawn. Since CBP and ICE were limited in their ability to process deportees, it employed a very random patchwork technique in selecting the expelled individuals. As a consequence, repeat offenders, particularly those who were single, got a reduced punishment. The government will be compelled to focus on long-overdue but vital border enhancements if expulsions are halted. Title 42 provisions may help expedite the processing of asylum and other types of humanitarian relief. The government is prepared for an increase in arrivals, but ending the program would lead to a return to arrival levels seen during the Title 42 period.

Keywords: migrants, refugees, title 42, medical, trump administration

Procedia PDF Downloads 91

Authors: Sreejith Jayachandran, Mojtaba Ghods, Morteza Mohammadzaheri

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The modern busy world is running behind new embedded technologies based on computers and software; meanwhile, some people forget to do their health condition and regular medical check-ups. Some of them postpone medical check-ups due to a lack of time and convenience, while others skip these regular evaluations and medical examinations due to huge medical bills and hospital expenses. Engineers and medical experts have come together to give birth to a new device in the telemonitoring system capable of monitoring, checking, and evaluating the health status of the human body remotely through the internet for the needs of all kinds of people. The remote health monitoring device is a microcontroller-based embedded unit. Various types of sensors in this device are connected to the human body, and with the help of an Arduino UNO board, the required analogue data is collected from the sensors. The microcontroller on the Arduino board processes the analogue data collected in this way into digital data and transfers that information to the cloud, and stores it there, and the processed digital data is instantly displayed through the LCD attached to the machine. By accessing the cloud storage with a username and password, the concerned person’s health care teams/doctors and other health staff can collect this data for the assessment and follow-up of that patient. Besides that, the family members/guardians can use and evaluate this data for awareness of the patient's current health status. Moreover, the system is connected to a Global Positioning System (GPS) module. In emergencies, the concerned team can position the patient or the person with this device. The setup continuously evaluates and transfers the data to the cloud, and also the user can prefix a normal value range for the evaluation. For example, the blood pressure normal value is universally prefixed between 80/120 mmHg. Similarly, the RHMS is also allowed to fix the range of values referred to as normal coefficients. This IoT-based miniature system (11×10×10) cm³ with a low weight of 500 gr only consumes 10 mW. This smart monitoring system is manufactured with 100 GBP, which can be used not only for health systems, it can be used for numerous other uses including aerospace and transportation sections.

Keywords: embedded technology, telemonitoring system, microcontroller, Arduino UNO, cloud storage, global positioning system, remote health monitoring system, alert system

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Authors: Maomao Cao

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Objective: To test the performance of ctDNA methylation for the detection of liver cancer. Methods: A total of 1233 individuals have been recruited in 2017. 15 male and 15 female samples (including 10 cases of liver cancer) were randomly selected in the present study. CfDNA was extracted by MagPure Circulating DNA Maxi Kit. The concentration of cfDNA was obtained by Qubit™ dsDNA HS Assay Kit. A pre-constructed predictive model was used to analyze methylation data and to give a predictive score for each cfDNA sample. Individuals with a predictive score greater than or equal to 80 were classified as having liver cancer. CT tests were considered the gold standard. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) for the diagnosis of liver cancer were calculated. Results: 9 patients were diagnosed with liver cancer according to the prediction model (with high sensitivity and threshold of 80 points), with scores of 99.2, 91.9, 96.6, 92.4, 91.3, 92.5, 96.8, 91.1, and 92.2, respectively. The sensitivity, specificity, positive predictive value, and negative predictive value of ctDNA methylation for the diagnosis of liver cancer were 0.70, 0.90, 0.78, and 0.86, respectively. Conclusions: ctDNA methylation could be an acceptable diagnostic modality for the detection of liver cancer.

Keywords: liver cancer, ctDNA methylation, detection, diagnostic performance

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Authors: Huang Yajing

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Multimodal discourse refers to the phenomenon of using various senses such as hearing, vision, and touch to communicate through various means and symbolic resources such as language, images, sounds, and movements. With the development of modern technology and multimedia, language and technology have become inseparable, and foreign language teaching is becoming more and more modal. Teacher-student communication resorts to multiple senses and uses multiple symbol systems to construct and interpret meaning. The classroom is a semiotic space where multimodal discourses are intertwined. College English multi-modal teaching is to rationally utilize traditional teaching methods while mobilizing and coordinating various modern teaching methods to form a joint force to promote teaching and learning. Multimodal teaching makes full and reasonable use of various meaning resources and can maximize the advantages of multimedia and network environments. Based upon the above theories about multimodal discourse and multimedia technology, the present paper will propose a multi-modal teaching model for college English in China.

Keywords: multimodal discourse, multimedia technology, English education, applied linguistics

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Authors: K. Shafiei, A. Pirestani, G. Ghalamkari, S. Safavipour

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Use of GnRH or its agonists to increase conception rates should be based on an understanding of GnRH-induced biological effects on the reproductive-endocrine system. This effect may occur through GnRH-stimulated LH surge stimulating production of progesterone by corpus luteum.the aim of this study was to compare the effects on reproductive efficiency of a luteolytic dose of a synthetic prostaglandin Cloprostenol Sodium versus ainjectable progesterone and Luliberin- A on Follicle estrogen and progesterone levels.In this study, we used45 head of holstein dairy heifersin the three treatments, with 15 replicates per treatment were performed in random groups. all the heifers before the projects is began in two steps injection 3 mL CloprostenolSodium with an interval of 11 days been synchronized and 10 days later, second injection of prostaglandin was conducted after that we started below protocol:Control group (daily sodium chloride serum injection 1 cc), Group B: Day Zero, intramuscular injection of 15 mg Luliberin- A + every other day injection of 3 cc progesterone + day 7, injection of Cloprostenol Sodium+ day 9, injection of 15 mg Luliberin- A.Group C: similar to Grop B + daily injection of progesterone after that blood samples was collected and centrifuged.plasma were analysed by ELISA.the analysis of this study uses SPSS data software package and compared between the mean and LS Means LSD test at 5% significance level was used.The results of this study shows that maximum of progesterone plasma levels were in the control gruop (P ≥ 0.05).Therefore, daily injection of progesterone inhibit the growth CL. the most estrogen levels in plasma were in Group C (P ≥ 0.05) thus it can be concluded, rise in endogenous estrogen concentrations normally stimulates the preovulatory LH release in heifers.

Keywords: Luliberin- A, Cloprostenol Sodium, estrogen, progesterone, dairy heifers

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Authors: Seyfollah Fazlollahi, Ahmad Bayan Memar

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Background: A review of manpower planning includes a training analysis based on job descriptions and job specifications which looks carefully at training from the points of view of the company, its various departments and personnel. This may show weaknesses in some departments and as a result, training is needed for the staff. Purpose: The aim of this research is to investigate the effects of training on employee’s efficiency in different aspects of work. Methodology: This is a descriptive-survey study. Statistical population was 85 official employees of University of Qom, Iran. 70 of these individuals were selected on a statistical random sampling method using Morgan&Gorki table. The instrument used in this study was a questionnaire including 22 questions. Result: Findings in this study according to data analysis indicate that majority of respondents had positive attitude towards training programs, in the job or off the job. They believed that training programs promoted and enhanced their behavior positively which leads to high efficiency in their job. In fact, data support the main hypothesis that training has positive effects on job performance and efficiency. Conclusion: It is concluded from this study and other related researches that training (on the job and off the job) has positive and effective role in human development and labor as employee’s efficiency. Employees get acquainted with different tasks of a job. Group co-operation, creativity and innovation will be enforced. Training leads to job skills, increasing knowledge and information about a job. It also increases technical and conceptual human skills, which are important in an organization. We can also mention workers' increasing positive motivation toward their job, enforcement of coordinating moral, their good human relations and good contact with clients.

Keywords: training, work efficiency, employee, human relation, job satisfaction

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Authors: Najib K. Dankadai, Ahmad 'Athif Mohd Faudzi, Khairuddin Osman, Muhammad Rusydi Muhammad Razif, IIi Najaa Aimi Mohd Nordin

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Researches in soft actuators are now growing rapidly because of their adequacy to be applied in sectors like medical, agriculture, biological and welfare. This paper presents system identification (SI) and control of the force generated by a two chambers pneumatic soft actuator (PSA). A force mathematical model for the actuator was identified experimentally using data acquisition card and MATLAB SI toolbox. Two control techniques; a predictive functional control (PFC) and conventional proportional integral and derivative (PID) schemes are proposed and compared based on the identified model for the soft actuator flexible mechanism. Results of this study showed that both of the proposed controllers ensure accurate tracking when the closed loop system was tested with the step, sinusoidal and multi step reference input through MATLAB simulation although the PFC provides a better response than the PID.

Keywords: predictive functional control (PFC), proportional integral and derivative (PID), soft actuator, system identification

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Authors: Mona Lisa M. Oliveira, Nara A. Policarpo, Ana Luiza B. P. Barros, Carla A. Silva

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Selective catalytic reduction systems for nitrogen oxides reduction by ammonia has been the chosen technology by most of diesel vehicle (i.e. bus and truck) manufacturers in Brazil, as also in Europe. Furthermore, at some conditions, over-stoichiometric ammonia availability is also needed that increases the NH₃ slips even more. Ammonia (NH₃) by this vehicle exhaust aftertreatment system provides a maximum efficiency of NOx removal if a significant amount of NH₃ is stored on its catalyst surface. In the other words, the practice shows that slightly less than 100% of the NOx conversion is usually targeted, so that the aqueous urea solution hydrolyzes to NH₃ via other species formation, under relatively low temperatures. This paper presents a model based on neural networks integrated with a road vehicle simulator that allows to estimate NH₃-slip emission factors for different driving conditions and patterns. The proposed model generates high NH₃slips which are not also limited in Brazil, but more efforts needed to be made to elucidate the contribution of vehicle-emitted NH₃ to the urban atmosphere.

Keywords: ammonia slip, neural-network, vehicles emissions, SCR-NOx

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Authors: Owolabi Kolade Matthew

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In this work, we investigate both the analytical and numerical studies of the dynamical model comprising of three species system. We analyze the linear stability of stationary solutions in the one-dimensional multi-system modeling the interactions of two predators and one prey species. The stability analysis has a lot of implications for understanding the various spatiotemporal and chaotic behaviors of the species in the spatial domain. The analysis results presented have established the possibility of the three interacting species to coexist harmoniously, this feat is achieved by combining the local and global analyzes to determine the global dynamics of the system. In the presence of diffusion, a viable exponential time differencing method is applied to multi-species nonlinear time-dependent partial differential equation to address the points and queries that may naturally arise. The scheme is described in detail, and justified by a number of computational experiments.

Keywords: asymptotically stable, coexistence, exponential time differencing method, global and local stability, predator-prey model, nonlinear, reaction-diffusion system

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Authors: Ashkan Zakaryazad, Ekrem Duman

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A typical classification technique ranks the instances in a data set according to the likelihood of belonging to one (positive) class. A credit card (CC) fraud detection model ranks the transactions in terms of probability of being fraud. In fact, this approach is often criticized, because firms do not care about fraud probability but about the profitability or costliness of detecting a fraudulent transaction. The key contribution in this study is to focus on the profit maximization in the model building step. The artificial neural network proposed in this study works based on profit maximization instead of minimizing the error of prediction. Moreover, some studies have shown that the back propagation algorithm, similar to other gradient–based algorithms, usually gets trapped in local optima and swarm-based algorithms are more successful in this respect. In this study, we train our profit maximization ANN using the Migrating Birds optimization (MBO) which is introduced to literature recently.

Keywords: neural network, profit-based neural network, sum of squared errors (SSE), MBO, gradient descent

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Authors: M. A. Ansari, A. Hussain, A. Uddin

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A side weir is a flow diversion structure provided in the side wall of a channel to divert water from the main channel to a branch channel. The trapezoidal labyrinth weir is a special type of weir in which crest length of the weir is increased to pass higher discharge. Experimental and numerical studies related to the coefficient of discharge of trapezoidal labyrinth weir in an open channel have been presented in the present study. Group Method of Data Handling (GMDH) with the transfer function of quadratic polynomial has been used to predict the coefficient of discharge for the side trapezoidal labyrinth weir. A new model is developed for coefficient of discharge of labyrinth weir by regression method. Generalized models for predicting the coefficient of discharge for labyrinth weir using Group Method of Data Handling (GMDH) network have also been developed. The prediction based on GMDH model is more satisfactory than those given by traditional regression equations.

Keywords: discharge coefficient, group method of data handling, open channel, side labyrinth weir

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Authors: Mahesh Koti

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In this paper, we present a quantum transport study of a quantum dot in steady state in the presence of static gate potential. We consider a quantum dot coupled to the two metallic leads. The quantum dot under study is modeled through Anderson Impurity Model (AIM) with hopping parameter modulated through voltage drop between leads and the central dot region. Based on the Landauer's formula derived from Nonequilibrium Green's Function and Single Electron Theory, the essential ingredients of transport properties are revealed. We show that the results out of two approaches closely agree with each other. We demonstrate that Landauer current response derived from single electron approach converges with non-zero interaction through gate potential whereas Landauer current response derived from Nonequilibrium Green's Function (NEGF) hits a pole.

Keywords: Anderson impurity model (AIM), nonequilibrium Green's function (NEGF), Landauer's formula, single electron analysis

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Authors: Y. H. Wu, Ji-Yuan Lin, Yu-Ming Liou

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This study aims to set up the landslide susceptibility map of County Route 89 at Ren-Ai Township in Nantou County using the Instability Index Method and Logistic regression. Seven susceptibility factors including Slope Angle, Aspect, Elevation, Distance to fold, Distance to River, Distance to Road and Accumulated Rainfall were obtained by GIS based on the Typhoon Toraji landslide area identified by Industrial Technology Research Institute in 2001. To calculate the landslide percentage of each factor and acquire the weight and grade the grid by means of Instability Index Method. In this study, landslide susceptibility can be classified into four grades: high, medium high, medium low and low, in order to determine the advantages and disadvantages of the two models. The precision of this model is verified by classification error matrix and SRC curve. These results suggest that the logistic regression model is a preferred method than instability index in the assessment of landslide susceptibility. It is suitable for the landslide prediction and precaution in this area in the future.

Keywords: instability index method, logistic regression, landslide susceptibility, SRC curve

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Authors: N. R. P Withana, E. Auch

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The purpose of this study was to investigate perceptions of climate change risk to forest ecosystems and forest-based communities as well as perceived effectiveness of adaptation strategies for climate change as well as challenges for adaptation. Data was gathered using a pre-tested semi-structured questionnaire. Simple random selection technique was applied. For the majority of issues, the responses were obtained on multi-point Likert scales, and the scores provided were, in turn, used to estimate the means and other useful estimates. A composite knowledge index developed using correct responses to a set of self-rated statements were used to evaluate the issues. The mean of the knowledge index was 0.64. Also all respondents recorded values of the knowledge index above 0.25. Increase forest fire was perceived by respondents as the greatest risk to forest eco-system. Decrease access to water supplies was perceived as the greatest risk to livelihoods of forest based communities. The most effective adaptation strategy relevant to climate change risks to forest eco-systems and forest based communities livelihoods in Kathmandu valley in Nepal as perceived by the respondents was reforestation and afforestation. As well, lack of public awareness was perceived as the major limitation for climate change adaptation. However, perceived risks as well as effective adaptation strategies showed an inconsistent association with knowledge indicators and social-cultural variables. The results provide useful information to any party who involve with climate change issues in Nepal, since such attempts would be more effective once the people’s perceptions on these aspects are taken into account.

Keywords: climate change, risk perceptions, forest ecosystems, forest-based communities

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Authors: Mohamed Chakroun

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In this paper, we analyze the macroeconomic impacts of Oman’s strategy to transition to a green economy by 2050. Our objective is to determine the most effective climate policy instrument to facilitate this transition. By utilizing a Dynamic Stochastic General Equilibrium (DSGE) model, we assess the effectiveness of three climate policy tools: a carbon tax, subsidies to green assets, and taxes on brown assets. Our results indicate that a combination of a carbon tax, along with differentiated taxes and subsidies on green and brown assets, proves to the most effective policy in reducing emissions while maintaining macroeconomic stability. The findings of this study demonstrate the need for policymakers to balance the immediate goals of reducing emissions with the economic costs involved. Implementing a gradual transition strategy may be preferable as it allows for mitigating the negative economic impacts while facilitating the shift towards a green economy.

Keywords: green economy, carbon tax, DSGE model, climate policy, sustainable growth

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Authors: Ayse Inel Manav, Saliha Bozdogan Yesilot, Pinar Yesil Demirci, Gursel Oztunc

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Introduction: This study was conducted with a view to evaluating cognitive function level, depression, and quality of life of elderly people living in a nursing home. Methods: This study, which is cross-sectional and descriptive in nature, was conducted in the Nursing and Rehabilitation Center for the Elderly in Adana/Turkey between 1st of May and 1st of August, 2016. The participants included 118 elderly people who were chosen using simple random sampling method. The data were collected using the Personal Information Form, the Standardized Mini Mental State Exam (SMMSE), the Geriatric Depression Scale (GDS), and the World Health Organization Quality of Life-OLD (WHOQOL-OLD) module. The data were analyzed using IBM SPSS Statistics 22 (IBM, SPSS, Turkey) program. Results: Of all the participants, 36,4% (n=43) were female, 63,6% (n=75) were male, and average age was 74,08 ± 8,23 years. The participants’ SMMSE mean score was found 20,37 ± 7,08, GDS mean score was 14,92 ± 4,29, and WHOQOL-OLD module mean score was 69,76 ± 11,54. There was a negative, significant relationship between SMMSE and GDS scores, a positive relationship between WHOQOL-OLD module total scores and a negative, significant relationship between GDS scores and WHOQOL-OLD module total scores. Discussıon and Conclusion: Results showed that more than half of the elderly people living in the nursing home experienced cognitive deterioration and depression; and cognitive state, depression, and quality of life were found to be significantly related to each other.

Keywords: depression, cognitive function level, quality of life

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Authors: Shin Je Lee, Go Bong Choi, Jeong Cheol Seo, Jong Min Lee, Gibaek Lee

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Water pipe network is installed underground and once equipped; it is difficult to recognize the state of pipes when the leak or burst happens. Accordingly, post management is often delayed after the fault occurs. Therefore, the systematic fault management system of water pipe network is required to prevent the accident and minimize the loss. In this work, we develop online fault detection system of water pipe network using data of pipes such as flow rate or pressure. The transient model describing water flow in pipelines is presented and simulated using Matlab. The fault situations such as the leak or burst can be also simulated and flow rate or pressure data when the fault happens are collected. Faults are detected using statistical methods of fast Fourier transform and discrete wavelet transform, and they are compared to find which method shows the better fault detection performance.

Keywords: fault detection, water pipeline model, fast Fourier transform, discrete wavelet transform

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Authors: Saurabh Chanana, Monika Arora

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Demand response is getting increased attention these days due to the increase in electricity demand and introduction of renewable resources in the existing power grid. Traditionally demand response programs involve large industrial consumers but with technological advancement, demand response is being implemented for small residential and commercial consumers also. In this paper, demand response program aims to reduce the peak demand as well as overall energy consumption of the residential customers. Air conditioners are the major reason of peak load in residential sector in summer, so a dynamic model of air conditioning load with thermostat action has been considered for applying demand response programs. A programmable communicating thermostat (PCT) is a device that uses real time pricing (RTP) signals to control the thermostat setting. A new model incorporating PCT in air conditioning load has been proposed in this paper. Results show that introduction of PCT in air conditioner is useful in reducing the electricity payments of customers as well as reducing the peak demand.

Keywords: demand response, home energy management, programmable communicating thermostat, thermostatically controlled appliances

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Authors: Jia Xin Low, Keng Wah Choo

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This paper presents an automatic normal and abnormal heart sound classification model developed based on deep learning algorithm. MITHSDB heart sounds datasets obtained from the 2016 PhysioNet/Computing in Cardiology Challenge database were used in this research with the assumption that the electrocardiograms (ECG) were recorded simultaneously with the heart sounds (phonocardiogram, PCG). The PCG time series are segmented per heart beat, and each sub-segment is converted to form a square intensity matrix, and classified using convolutional neural network (CNN) models. This approach removes the need to provide classification features for the supervised machine learning algorithm. Instead, the features are determined automatically through training, from the time series provided. The result proves that the prediction model is able to provide reasonable and comparable classification accuracy despite simple implementation. This approach can be used for real-time classification of heart sounds in Internet of Medical Things (IoMT), e.g. remote monitoring applications of PCG signal.

Keywords: convolutional neural network, discrete wavelet transform, deep learning, heart sound classification

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Authors: Chen Niu, Xuesong Zhang, Dejiang Shang, Yongwei Liu

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Fishes can secrete high molecular weight fluid on their body skin to enable their rapid movement in the water. In this work, we employ a hybrid method that combines Computational Fluid Dynamics (CFD) and Finite Element Method (FEM) to investigate the effects of different mucus viscosities and injection velocities on fluctuation pressure in the boundary layer and flow-induced structural vibration noise of a flat plate model. To accurately capture the transient flow distribution on the plate surface, we use Large Eddy Simulation (LES) while the mucus inlet is positioned at a sufficient distance from the model to ensure effective coverage. Mucus injection is modeled using the Volume of Fluid (VOF) method for multiphase flow calculations. The results demonstrate that mucus control of pulsating pressure effectively reduces flow-induced structural vibration noise, providing an approach for controlling flow-induced noise in underwater vehicles.

Keywords: mucus, flow control, noise control, flow-induced noise

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Authors: Rupu Yang, Cong Toan Tran, Assaad Zoughaib

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The work provides an iterative nonlinear programming method to synthesize a heat exchanger network by manipulating the trade-offs between the heat load of process heat exchangers (HEs) and utilities. We consider for the synthesis problem two cases, the first one without fixed cost for HEs, and the second one with fixed cost. For the no fixed cost problem, the nonlinear programming (NLP) model with all the potential HEs is optimized to obtain the global optimum. For the case with fixed cost, the NLP model is iterated through adding/removing HEs. The method was applied in five case studies and illustrated quite well effectiveness. Among which, the approach reaches the lowest TAC (2,904,026$/year) compared with the best record for the famous Aromatic plants problem. It also locates a slightly better design than records in literature for a 10 streams case without fixed cost with only 1/9 computational time. Moreover, compared to the traditional mixed-integer nonlinear programming approach, the iterative NLP method opens a possibility to consider constraints (such as controllability or dynamic performances) that require knowing the structure of the network to be calculated.

Keywords: heat exchanger network, synthesis, NLP, optimization

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Authors: Sheela Tiwari, R. Naresh, R. Jha

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The paper presents an investigation into the effect of neural network predictive control of UPFC on the transient stability performance of a multi-machine power system. The proposed controller consists of a neural network model of the test system. This model is used to predict the future control inputs using the damped Gauss-Newton method which employs ‘backtracking’ as the line search method for step selection. The benchmark 2 area, 4 machine system that mimics the behavior of large power systems is taken as the test system for the study and is subjected to three phase short circuit faults at different locations over a wide range of operating conditions. The simulation results clearly establish the robustness of the proposed controller to the fault location, an increase in the critical clearing time for the circuit breakers and an improved damping of the power oscillations as compared to the conventional PI controller.

Keywords: identification, neural networks, predictive control, transient stability, UPFC

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Authors: Teresa Kupczyk, Selçuk Mustafa Özcan, Joanna Kubicka

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The paper presents results of specialist literature analysis concerning learning outcomes and student satisfaction as a factor of the necessary change in the Polish higher education system. The objective of the empirical research was to determine students’ assessment of learning outcomes, satisfaction of their expectations, as well as their satisfaction with lectures and practical classes held in the traditional form, e-learning and video-conference. The assessment concerned effectiveness of time spent at classes, usefulness of the delivered knowledge, instructors’ preparation and teaching skills, application of tools, studies curriculum, its adaptation to students’ needs and labour market, as well as studying conditions. Self-assessment of learning outcomes was confronted with assessment by lecturers. The indirect objective of the research was also to identify how students assessed their activity and commitment in acquisition of knowledge and their discipline in achieving education goals. It was analysed how the studies held affected the students’ willingness to improve their skills and assessment of their perspectives at the labour market. To capture the changes underway, the research was held at the beginning, during and after completion of the studies. The study group included 86 students of two editions of full-time studies majoring in Management and specialising in “Mega-event organisation”. The studies were held within the EU-funded project entitled “Responding to challenges of new markets – innovative managerial education”. The results obtained were analysed statistically. Average results and standard deviations were calculated. In order to describe differences between the studied variables present during the process of studies, as well as considering the respondents’ gender, t-Student test for independent samples was performed with the IBM SPSS Statistics 21.0 software package. Correlations between variables were identified by calculation of Pearson and Spearman correlation coefficients. Research results suggest necessity to introduce some changes in the teaching system applied at Polish higher education institutions, not only considering the obtained outcomes, but also impact on students’ willingness to improve their qualifications constantly, improved self-assessment among students and their opportunities at the labour market.

Keywords: higher education, learning outcomes, students, change

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Authors: Skyler Kim

Abstract:

An early diagnosis of leukemia has always been a challenge to doctors and hematologists. On a worldwide basis, it was reported that there were approximately 350,000 new cases in 2012, and diagnosing leukemia was time-consuming and inefficient because of an endemic shortage of flow cytometry equipment in current clinical practice. As the number of medical diagnosis tools increased and a large volume of high-quality data was produced, there was an urgent need for more advanced data analysis methods. One of these methods was the AI approach. This approach has become a major trend in recent years, and several research groups have been working on developing these diagnostic models. However, designing and implementing a leukemia diagnostic system in real clinical environments based on a deep learning approach with larger sets remains complex. Leukemia is a major hematological malignancy that results in mortality and morbidity throughout different ages. We decided to select acute lymphocytic leukemia to develop our diagnostic system since acute lymphocytic leukemia is the most common type of leukemia, accounting for 74% of all children diagnosed with leukemia. The results from this development work can be applied to all other types of leukemia. To develop our model, the Kaggle dataset was used, which consists of 15135 total images, 8491 of these are images of abnormal cells, and 5398 images are normal. In this paper, we design and implement a leukemia diagnostic system in a real clinical environment based on deep learning approaches with larger sets. The proposed diagnostic system has the function of detecting and classifying leukemia. Different from other AI approaches, we explore hybrid architectures to improve the current performance. First, we developed two independent convolutional neural network models: VGG19 and ResNet50. Then, using both VGG19 and ResNet50, we developed a hybrid deep learning architecture employing transfer learning techniques to extract features from each input image. In our approach, fusing the features from specific abstraction layers can be deemed as auxiliary features and lead to further improvement of the classification accuracy. In this approach, features extracted from the lower levels are combined into higher dimension feature maps to help improve the discriminative capability of intermediate features and also overcome the problem of network gradient vanishing or exploding. By comparing VGG19 and ResNet50 and the proposed hybrid model, we concluded that the hybrid model had a significant advantage in accuracy. The detailed results of each model’s performance and their pros and cons will be presented in the conference.

Keywords: acute lymphoblastic leukemia, hybrid model, leukemia diagnostic system, machine learning

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Authors: S. Jigna, K. Nanda Kumar, T. Anna

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Being a major contributor to the Indian economy and a critical facilitator for the country’s digital India vision, the Indian telecommunications industry is also a major source of employment for the country. Since the last few years, the Indian telecommunication service providers (TSPs), however, are facing business challenges related to increasing competition, losses, debts, and decreasing revenue. The strategic use of digital technologies for a successful digital transformation has the potential to equip organizations to meet these business challenges. Despite an increased focus on digital transformation, the telecom service providers globally, including Indian TSPs, have seen limited success so far. The purpose of this research was thus to identify the factors that are critical for the digital transformation and to what extent they influence the successful digital transformation of the Indian TSPs. The literature review of more than 300 digital transformation-related articles, mostly from 2013-2019, demonstrated a lack of an empirical model consisting of factors for the successful digital transformation of the TSPs. This study theorizes a research framework grounded in multiple theories, and a research model consisting of 7 constructs that may be influencing business success during the digital transformation of the organization was proposed. The questionnaire survey of senior managers in the Indian telecommunications industry was seeking to validate the research model. Based on 294 survey responses, the validation of the Structural equation model using the statistical tool ADANCO 2.1.1 was found to be robust. Results indicate that Digital Capabilities, Digital Strategy, and Corporate Level Data Strategy in that order has a strong influence on the successful Business Performance, followed by IT Function Transformation, Digital Innovation, and Transformation Management respectively. Even though Digital Organization did not have a direct significance on Business Performance outcomes, it had a strong influence on IT Function Transformation, thus affecting the Business Performance outcomes indirectly. Amongst numerous practical and theoretical contributions of the study, the main contribution for the Indian TSPs is a validated reference for prioritizing the transformation initiatives in their strategic roadmap. Also, the main contribution to the theory is the possibility to use the research framework artifact of the present research for quantitative validation in different industries and geographies.

Keywords: corporate level data strategy, digital capabilities, digital innovation, digital strategy

Procedia PDF Downloads 133