Search results for: advanced analytics
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2429

Search results for: advanced analytics

2249 Predicting Match Outcomes in Team Sport via Machine Learning: Evidence from National Basketball Association

Authors: Jacky Liu

Abstract:

This paper develops a team sports outcome prediction system with potential for wide-ranging applications across various disciplines. Despite significant advancements in predictive analytics, existing studies in sports outcome predictions possess considerable limitations, including insufficient feature engineering and underutilization of advanced machine learning techniques, among others. To address these issues, we extend the Sports Cross Industry Standard Process for Data Mining (SRP-CRISP-DM) framework and propose a unique, comprehensive predictive system, using National Basketball Association (NBA) data as an example to test this extended framework. Our approach follows a holistic methodology in feature engineering, employing both Time Series and Non-Time Series Data, as well as conducting Explanatory Data Analysis and Feature Selection. Furthermore, we contribute to the discourse on target variable choice in team sports outcome prediction, asserting that point spread prediction yields higher profits as opposed to game-winner predictions. Using machine learning algorithms, particularly XGBoost, results in a significant improvement in predictive accuracy of team sports outcomes. Applied to point spread betting strategies, it offers an astounding annual return of approximately 900% on an initial investment of $100. Our findings not only contribute to academic literature, but have critical practical implications for sports betting. Our study advances the understanding of team sports outcome prediction a burgeoning are in complex system predictions and pave the way for potential profitability and more informed decision making in sports betting markets.

Keywords: machine learning, team sports, game outcome prediction, sports betting, profits simulation

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2248 Advanced Techniques in Robotic Mitral Valve Repair

Authors: Abraham J. Rizkalla, Tristan D. Yan

Abstract:

Purpose: Durable mitral valve repair is preferred to a replacement, avoiding the need for anticoagulation or re-intervention, with a reduced risk of endocarditis. Robotic mitral repair has been gaining favour globally as a safe, effective, and reproducible method of minimally invasive valve repair. In this work, we showcase the use of the Davinci© Xi robotic platform to perform several advanced techniques, working synergistically to achieve successful mitral repair in advanced mitral disease. Techniques: We present the case of a Barlow type mitral valve disease with a tall and redundant posterior leaflet resulting in severe mitral regurgitation and systolic anterior motion. Firstly, quadrangular resection of P2 is performed to remove the excess and redundant leaflet. Secondly, a sliding leaflet plasty of P1 and P3 is used to reconstruct the posterior leaflet. To anchor the newly formed posterior leaflet to the papillary muscle, CV-4 Goretex neochordae are fashioned using the innovative string, ruler, and bulldog technique. Finally, mitral valve annuloplasty and closure of a patent foramen ovale complete the repair. Results: There was no significant residual mitral regurgitation and complete resolution of the systolic anterior motion of the mitral valve on post operative transoesophageal echocardiography. Conclusion: This work highlights the robotic approach to complex repair techniques for advanced mitral valve disease. Familiarity with resection and sliding plasty, neochord implantation, and annuloplasty allows the modern cardiac surgeon to achieve a minimally-invasive and durable mitral valve repair when faced with complex mitral valve pathology.

Keywords: robotic mitral valve repair, Barlow's valve, sliding plasty, neochord, annuloplasty, quadrangular resection

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2247 The Examination of Parents’ Perceptions and Motivations Regarding Type 1 Diabetes Management Technologies

Authors: Maria Dora Horvath, Norbert Buzas, Zsanett Tesch

Abstract:

Diabetes management poses many unique challenges for children and their parents. The use of a diabetes management device should not be one of these challenges as the purpose of these devices is to make the management more convenient. The objective of our study was to examine how demographical, psychological and diabetes-related factors determine the choices parents make regarding their child’s diabetes management technologies and how they perceive advanced devices. We conducted the study using an online questionnaire with 318 parents (mostly mothers). The questions of the survey were about demographical, diabetes-related and psychological factors (diabetes management problems, diabetes management competence). In addition, we asked the parents opinions about advanced diabetes management devices. We expanded our data with semi-structured in-depth interviews. 61 % of the participants Self-Monitored Blood Glucose (SMBG), and 39 % used a Continuous Glucose Monitoring System (CGM). Considering insulin administration, 58 % used Multiple Daily Insulin Injections (MDII) and 42 % used Continuous Subcutaneous Insulin Infusion (CSII). Parents who used diverse combinations of diabetes management devices showed significant differences in age (parents’ and child’s), the monthly cost of diabetes, the duration of diabetes, the highest level of education and average monthly household income. CGM users perceived diabetes management problems significantly more severe than SMBG users and CSII users felt significantly more competent in diabetes management than MDII users. Avoiding CGM use due to lack of financial resources was determined by diagnosis duration. While avoiding its use by the cause of the child rejecting, it was determined by the child’s age and diabetes competence. Using MDII instead of CSII because of the child’s rejection was determined by the monthly cost of diabetes and child’s age. We conducted a complex empirical study in which we examined perceptions and experiences of advanced and less advanced diabetes management technologies comprehensively. Our study highlights the factors that fundamentally influence parents’ motivations and choices about diabetes management technologies. These results could contribute to developing diabetes management technologies more suitable for children living with type 1 diabetes and their parents.

Keywords: advanced diabetes management technologies, children living with type 1 diabetes, diabetes management, motivation, parents

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2246 Atomic Scale Storage Mechanism Study of the Advanced Anode Materials for Lithium-Ion Batteries

Authors: Xi Wang, Yoshio Bando

Abstract:

Lithium-ion batteries (LIBs) can deliver high levels of energy storage density and offer long operating lifetimes, but their power density is too low for many important applications. Therefore, we developed some new strategies and fabricated novel electrodes for fast Li transport and its facile synthesis including N-doped graphene-SnO2 sandwich papers, bicontinuous nanoporous Cu/Li4Ti5O12 electrode, and binder-free N-doped graphene papers. In addition, by using advanced in-TEM, STEM techniques and the theoretical simulations, we systematically studied and understood their storage mechanisms at the atomic scale, which shed a new light on the reasons of the ultrafast lithium storage property and high capacity for these advanced anodes. For example, by using advanced in-situ TEM, we directly investigated these processes using an individual CuO nanowire anode and constructed a LIB prototype within a TEM. Being promising candidates for anodes in lithium-ion batteries (LIBs), transition metal oxide anodes utilizing the so-called conversion mechanism principle typically suffer from the severe capacity fading during the 1st cycle of lithiation–delithiation. Also we report on the atomistic insights of the GN energy storage as revealed by in situ TEM. The lithiation process on edges and basal planes is directly visualized, the pyrrolic N "hole" defect and the perturbed solid-electrolyte-interface (SEI) configurations are observed, and charge transfer states for three N-existing forms are also investigated. In situ HRTEM experiments together with theoretical calculations provide a solid evidence that enlarged edge {0001} spacings and surface "hole" defects result in improved surface capacitive effects and thus high rate capability and the high capacity is owing to short-distance orderings at the edges during discharging and numerous surface defects; the phenomena cannot be understood previously by standard electron or X-ray diffraction analyses.

Keywords: in-situ TEM, STEM, advanced anode, lithium-ion batteries, storage mechanism

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2245 Load Forecasting in Microgrid Systems with R and Cortana Intelligence Suite

Authors: F. Lazzeri, I. Reiter

Abstract:

Energy production optimization has been traditionally very important for utilities in order to improve resource consumption. However, load forecasting is a challenging task, as there are a large number of relevant variables that must be considered, and several strategies have been used to deal with this complex problem. This is especially true also in microgrids where many elements have to adjust their performance depending on the future generation and consumption conditions. The goal of this paper is to present a solution for short-term load forecasting in microgrids, based on three machine learning experiments developed in R and web services built and deployed with different components of Cortana Intelligence Suite: Azure Machine Learning, a fully managed cloud service that enables to easily build, deploy, and share predictive analytics solutions; SQL database, a Microsoft database service for app developers; and PowerBI, a suite of business analytics tools to analyze data and share insights. Our results show that Boosted Decision Tree and Fast Forest Quantile regression methods can be very useful to predict hourly short-term consumption in microgrids; moreover, we found that for these types of forecasting models, weather data (temperature, wind, humidity and dew point) can play a crucial role in improving the accuracy of the forecasting solution. Data cleaning and feature engineering methods performed in R and different types of machine learning algorithms (Boosted Decision Tree, Fast Forest Quantile and ARIMA) will be presented, and results and performance metrics discussed.

Keywords: time-series, features engineering methods for forecasting, energy demand forecasting, Azure Machine Learning

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2244 Advanced Oxidation Processes as a Pre-oxidation Step for Biological Treatment of Leachate from Technical Landfills

Authors: Ala Abdessemed, Mohamed Seddik Oussama Belahmadi, Nabil Charchar, Abdefettah Gherib, Bradai Fares, Boussadia Chouaib Nour El-Islem

Abstract:

Algerian cities are confronted with large quantities of waste generated by the disposal of household and similar residues in technical landfills (CET), such as the one in the location of Batna. The interaction between waste components and incoming water generates leachates rich in organic matter and trace elements, which require treatment before discharge. The aim of this study was to propose an effective process for treating the leachates, which were subjected to an initial chemical treatment using the (H₂O₂/UV) system. Optimal treatment conditions were determined at [H₂O₂] of 0.3 M and pH of 8.6. Next, two hybrid biological treatment systems were applied: hybrid system I (H₂O₂/UV/bacteria) and hybrid system II (H₂O₂/UV/bacteria/microalgae). The three processes resulted in the following degradation rates, expressed in terms of total organic carbon (TOC) 27.4% for the (H₂O₂/UV) system; 58.1% for the hybrid system I (H₂O₂/UV/Bacteria); 67.86% for the hybrid system II (H₂O₂/UV/Bacteria/Microalgae). This study demonstrates that a hybrid approach combining advanced oxidation processes and biological treatments is a highly effective alternative to achieve satisfactory treatment.

Keywords: leachate, landfill, advanced oxidation processes, biological treatment, bacteria, microalgae, total organic carbon

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2243 Burnback Analysis of Star Grain Using Level-Set Technique

Authors: Ali Yasin, Ali Kamran, Muhammad Safdar

Abstract:

In order to reduce the hefty cost involved in terms of time and project cost, the development and application of advanced numerical tools to address the burn-back analysis problem in solid rocket motor design and development is the need of time. Several advanced numerical schemes have been developed in recent times, but their usage in the design of propellant grain of solid rocket motors is very rare. In this paper, an advanced numerical technique named the Level-Set method has been utilized for the burn-back analysis of star grain to study the effect of geometrical parameters on ballistic performance indicators such as solid loading, neutrality, and sliver percentage. In the level set technique, simple finite difference methods may fail quickly and require more sophisticated non-oscillatory schemes for feasible long-time simulation. For internal ballistic calculations, a simplified equilibrium pressure method is utilized. Preliminary results of the operative conditions, for all the combustion time, of star grain burn-back using level set techniques are compared with published results using CAD technique to test the developed numerical model.

Keywords: solid rocket motor, internal ballistic, level-set technique, star grain

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2242 Primary Care Physicians in Urgent Care Centres of the United Kingdom

Authors: Mohammad Ansari, Ahmed Ismail, Satinder Mann

Abstract:

Overcrowding in Emergency departments (ED) of United Kingdom has become a common problem. Urgent Care centres were developed nearly a decade ago to reduce pressure on EDs. Unfortunately, the development of Urgent Care centres has failed to produce the projected effects. It was thought that nearly 40% patients attending ED would go to Urgent Care centres and these would be staffed by Primary care Physicians. Data reveals that no more than 20% patients were seen by Primary Care Physicians even when the Urgent Care Centre was based in the ED. This study was carried out at the ED of George Eliot Hospital, Nuneaton, UK where the Urgent Care centre was based in the ED and employed Primary Care Physicians with special interest in trauma for nearly one year. This was then followed by a Primary Care Physician and Advanced Nurse Practitioner. We compared the number of patients seen during these periods and the cost-effectiveness of the service.We randomly selected a week of patients seen by Primary Care Physicians with special interest in Trauma and by Primary Care Physicians and the Advanced Nurse Practitioner. We compared the number and type of patients seen during these two periods. Nearly 38% patients were seen by Primary care Physician with special interest in Trauma, whilst only 14.3% patients were seen by the Primary care Physician and Advanced Nurse Practitioner. The Primary Care Physicians with special interest in trauma were paid less. Our study confirmed that unless Primary Care Physicians are able to treat minor trauma and interpret x-rays, the urgent care service is not going to be cost effective. Numerous previous studies have shown that 15 to 20% patients attending ED can be treated by Primary Care Physicians who do not require any investigations for their management. It is advantageous to have Urgent Care Centres within the ED because if the patient deteriorates they can be transferred to ED. We recommend that the Urgent care Centres should be a part of ED. Our study shows that Urgent care Centres in the ED can be helpful and cost effective if staffed by either senior Emergency Physicians or Primary Care Physicians with special interest and experience in the management of minor trauma.

Keywords: urgent care centres, primary care physician, advanced nurse practitioner, trauma

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2241 Advanced Manufacturing Technology Adoption in Manufacturing Comapnies in Kenya

Authors: George Nyori Makari, J. M. Ogola

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Over the past few decades, manufacturing has evolved from a more labor-intensive set of mechanical processes to a sophisticated set of information based technology processes. With the existence of various advanced manufacturing technologies (AMTs), more and more functions or jobs are performed by these machines instead of human labour. This study was undertaken in order to research the extent of AMTs adoption in manufacturing companies in Kenya. In order to investigate a survey was conducted via questionnaires that were sent to 183 selected AMT manufacturing companies in Kenya. 92 companies responded positively. All the surveyed companies were found to have a measure of investment in at least two of the 14 types of AMTs investigated. In general the company surveyed showed that the level of AMT adoption in Kenya is very low with investments levels at a mean of 2.057 and integration levels at a mean of 1.639 in a scale of 1-5.

Keywords: AMT adoption, AMT investments, AMT integration, companies in Kenya

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2240 Advanced Technologies for Detector Readout in Particle Physics

Authors: Y. Venturini, C. Tintori

Abstract:

Given the continuous demand for improved readout performances in particle and dark matter physics, CAEN SpA is pushing on the development of advanced technologies for detector readout. We present the Digitizers 2.0, the result of the success of the previous Digitizers generation, combined with expanded capabilities and a renovation of the user experience introducing the open FPGA. The first product of the family is the VX2740 (64 ch, 125 MS/s, 16 bit) for advanced waveform recording and Digital Pulse Processing, fitting with the special requirements of Dark Matter and Neutrino experiments. In parallel, CAEN is developing the FERS-5200 platform, a Front-End Readout System designed to read out large multi-detector arrays, such as SiPMs, multi-anode PMTs, silicon strip detectors, wire chambers, GEM, gas tubes, and others. This is a highly-scalable distributed platform, based on small Front-End cards synchronized and read out by a concentrator board, allowing to build extremely large experimental setup. We plan to develop a complete family of cost-effective Front-End cards tailored to specific detectors and applications. The first one available is the A5202, a 64-channel unit for SiPM readout based on CITIROC ASIC by Weeroc.

Keywords: dark matter, digitizers, front-end electronics, open FPGA, SiPM

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2239 A Security Study for Smart Metering Systems

Authors: Musaab Hasan, Farkhund Iqbal, Patrick C. K. Hung, Benjamin C. M. Fung, Laura Rafferty

Abstract:

In modern societies, the smart cities concept raised simultaneously with the projection towards adopting smart devices. A smart grid is an essential part of any smart city as both consumers and power utility companies benefit from the features provided by the power grid. In addition to advanced features presented by smart grids, there may also be a risk when the grids are exposed to malicious acts such as security attacks performed by terrorists. Considering advanced security measures in the design of smart meters could reduce these risks. This paper presents a security study for smart metering systems with a prototype implementation of the user interfaces for future works.

Keywords: security design, smart city, smart meter, smart grid, smart metering system

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2238 Geographic Information System Cloud for Sustainable Digital Water Management: A Case Study

Authors: Mohamed H. Khalil

Abstract:

Water is one of the most crucial elements which influence human lives and development. Noteworthy, over the last few years, GIS plays a significant role in optimizing water management systems, especially after exponential developing in this sector. In this context, the Egyptian government initiated an advanced ‘GIS-Web Based System’. This system is efficiently designed to tangibly assist and optimize the complement and integration of data between departments of Call Center, Operation and Maintenance, and laboratory. The core of this system is a unified ‘Data Model’ for all the spatial and tabular data of the corresponding departments. The system is professionally built to provide advanced functionalities such as interactive data collection, dynamic monitoring, multi-user editing capabilities, enhancing data retrieval, integrated work-flow, different access levels, and correlative information record/track. Noteworthy, this cost-effective system contributes significantly not only in the completeness of the base-map (93%), the water network (87%) in high level of details GIS format, enhancement of the performance of the customer service, but also in reducing the operating costs/day-to-day operations (~ 5-10 %). In addition, the proposed system facilitates data exchange between different departments (Call Center, Operation and Maintenance, and laboratory), which allowed a better understanding/analyzing of complex situations. Furthermore, this system reflected tangibly on: (i) dynamic environmental monitor/water quality indicators (ammonia, turbidity, TDS, sulfate, iron, pH, etc.), (ii) improved effectiveness of the different water departments, (iii) efficient deep advanced analysis, (iv) advanced web-reporting tools (daily, weekly, monthly, quarterly, and annually), (v) tangible planning synthesizing spatial and tabular data; and finally, (vi) scalable decision support system. It is worth to highlight that the proposed future plan (second phase) of this system encompasses scalability will extend to include integration with departments of Billing and SCADA. This scalability will comprise advanced functionalities in association with the existing one to allow further sustainable contributions.

Keywords: GIS Web-Based, base-map, water network, decision support system

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2237 Gender Stereotypes in Reproductive Medicine with Regard to Parental Age

Authors: Monika Michałowska, Anna Alichniewicz

Abstract:

Detrimental outcomes of advanced maternal age on the chances of fertilization, pregnancy as well as mother and fetus health have been recognized for several decades. It seemed interesting to investigate whether there is a comparable awareness of the detrimental influence on the reproductive outcomes of late fatherhood, given that it has been already ten years since an intense and growing interest concerning later-age fatherhood commenced in medical research. To address that issue a two-step research was done. First, we performed a review of the subject literature to answer the following questions: 1) What age is defined as advanced?; 2) Is the same age defined as advanced in both genders?; 3) What terminology concerning age issues is used?; 4) Is the same age terminology used regarding both genders? The second part of our studies was devoted to the views of medical students. This part of our research comprised both quantitative and qualitative studies. Opinions of medical students in one of the Polish medical universities on several issues connected with assisted reproduction technology (ART) were gathered: 1) students’ attitude to in vitro fertilization (IVF) for women over 40 and for postmenopausal women; 2) students’ attitude to late fatherhood; 3) students’ reasoning given against acceptability of IVF procedure for all of these group of patients involved in an IVF procedure. Our analyses revealed that: First, there is no universal definition of the term ‘advanced age’; secondly, there is a general tendency to adopt different age limits depending on whether they refer to maternal or paternal age, but no justification is provided by the researchers explaining why they set different age limits for women and men; thirdly, the image of postponed fatherhood stands in stark contrast to postponed motherhood - while postponed fatherhood is frequently portrayed as a reasonable and conscious decision enabling a stable family environment for a child, the reasonableness of postponed motherhood is often questioned; finally, the bias regarding maternal versus paternal age is deeply embedded in medical students’ attitude to IVF for women over 40 and for postmenopausal women.

Keywords: gender stereotypes, reproductive medicine, maternal age, paternal age

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2236 The Predictors of Head and Neck Cancer-Head and Neck Cancer-Related Lymphedema in Patients with Resected Advanced Head and Neck Cancer

Authors: Shu-Ching Chen, Li-Yun Lee

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The purpose of the study was to identify the factors associated with head and neck cancer-related lymphoedema (HNCRL)-related symptoms, body image, and HNCRL-related functional outcomes among patients with resected advanced head and neck cancer. A cross-sectional correlational design was conducted to examine the predictors of HNCRL-related functional outcomes in patients with resected advanced head and neck cancer. Eligible patients were recruited from a single medical center in northern Taiwan. Consecutive patients were approached and recruited from the Radiation Head and Neck Outpatient Department of this medical center. Eligible subjects were assessed for the Symptom Distress Scale–Modified for Head and Neck Cancer (SDS-mhnc), Brief International Classification of Functioning, Disability and Health (ICF) Core Set for Head and Neck Cancer (BCSQ-H&N), Body Image Scale–Modified (BIS-m), The MD Anderson Head and Neck Lymphedema Rating Scale (MDAHNLRS), The Foldi’s Stages of Lymphedema (Foldi’s Scale), Patterson’s Scale, UCLA Shoulder Rating Scale (UCLA SRS), and Karnofsky’s Performance Status Index (KPS). The results showed that the worst problems with body HNCRL functional outcomes. Patients’ HNCRL symptom distress and performance status are robust predictors across over for overall HNCRL functional outcomes, problems with body HNCRL functional outcomes, and activity and social functioning HNCRL functional outcomes. Based on the results of this period research program, we will develop a Cancer Rehabilitation and Lymphedema Care Program (CRLCP) to use in the care of patients with resected advanced head and neck cancer.

Keywords: head and neck cancer, resected, lymphedema, symptom, body image, functional outcome

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2235 Self-Calibration of Fish-Eye Camera for Advanced Driver Assistance Systems

Authors: Atef Alaaeddine Sarraj, Brendan Jackman, Frank Walsh

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Tomorrow’s car will be more automated and increasingly connected. Innovative and intuitive interfaces are essential to accompany this functional enrichment. For that, today the automotive companies are competing to offer an advanced driver assistance system (ADAS) which will be able to provide enhanced navigation, collision avoidance, intersection support and lane keeping. These vision-based functions require an accurately calibrated camera. To achieve such differentiation in ADAS requires sophisticated sensors and efficient algorithms. This paper explores the different calibration methods applicable to vehicle-mounted fish-eye cameras with arbitrary fields of view and defines the first steps towards a self-calibration method that adequately addresses ADAS requirements. In particular, we present a self-calibration method after comparing different camera calibration algorithms in the context of ADAS requirements. Our method gathers data from unknown scenes while the car is moving, estimates the camera intrinsic and extrinsic parameters and corrects the wide-angle distortion. Our solution enables continuous and real-time detection of objects, pedestrians, road markings and other cars. In contrast, other camera calibration algorithms for ADAS need pre-calibration, while the presented method calibrates the camera without prior knowledge of the scene and in real-time.

Keywords: advanced driver assistance system (ADAS), fish-eye, real-time, self-calibration

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2234 Advanced Driver Assistance System: Veibra

Authors: C. Fernanda da S. Sampaio, M. Gabriela Sadith Perez Paredes, V. Antonio de O. Martins

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Today the transport sector is undergoing a revolution, with the rise of Advanced Driver Assistance Systems (ADAS), industry and society itself will undergo a major transformation. However, the technological development of these applications is a challenge that requires new techniques and great machine learning and artificial intelligence. The study proposes to develop a vehicular perception system called Veibra, which consists of two front cameras for day/night viewing and an embedded device capable of working with Yolov2 image processing algorithms with low computational cost. The strategic version for the market is to assist the driver on the road with the detection of day/night objects, such as road signs, pedestrians, and animals that will be viewed through the screen of the phone or tablet through an application. The system has the ability to perform real-time driver detection and recognition to identify muscle movements and pupils to determine if the driver is tired or inattentive, analyzing the student's characteristic change and following the subtle movements of the whole face and issuing alerts through beta waves to ensure the concentration and attention of the driver. The system will also be able to perform tracking and monitoring through GSM (Global System for Mobile Communications) technology and the cameras installed in the vehicle.

Keywords: advanced driver assistance systems, tracking, traffic signal detection, vehicle perception system

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2233 Choosing an Optimal Epsilon for Differentially Private Arrhythmia Analysis

Authors: Arin Ghazarian, Cyril Rakovski

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Differential privacy has become the leading technique to protect the privacy of individuals in a database while allowing useful analysis to be done and the results to be shared. It puts a guarantee on the amount of privacy loss in the worst-case scenario. Differential privacy is not a toggle between full privacy and zero privacy. It controls the tradeoff between the accuracy of the results and the privacy loss using a single key parameter called

Keywords: arrhythmia, cardiology, differential privacy, ECG, epsilon, medi-cal data, privacy preserving analytics, statistical databases

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2232 Medical Decision-Making in Advanced Dementia from the Family Caregiver Perspective: A Qualitative Study

Authors: Elzbieta Sikorska-Simmons

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Advanced dementia is a progressive terminal brain disease that is accompanied by a syndrome of difficult to manage symptoms and complications that eventually lead to death. The management of advanced dementia poses major challenges to family caregivers who act as patient health care proxies in making medical treatment decisions. Little is known, however, about how they manage advanced dementia and how their treatment choices influence the quality of patient life. This prospective qualitative study examines the key medical treatment decisions that family caregivers make while managing advanced dementia. The term ‘family caregiver’ refers to a relative or a friend who is primarily responsible for managing patient’s medical care needs and legally authorized to give informed consent for medical treatments. Medical decision-making implies a process of choosing between treatment options in response to patient’s medical care needs (e.g., worsening comorbid conditions, pain, infections, acute medical events). Family caregivers engage in this process when they actively seek treatments or follow recommendations by healthcare professionals. Better understanding of medical decision-making from the family caregiver perspective is needed to design interventions that maximize the quality of patient life and limit inappropriate treatments. Data were collected in three waves of semi-structured interviews with 20 family caregivers for patients with advanced dementia. A purposive sample of 20 family caregivers was recruited from a senior care center in Central Florida. The qualitative personal interviews were conducted by the author in 4-5 months intervals. The ethical approval for the study was obtained prior to the data collection. Advanced dementia was operationalized as stage five or higher on the Global Deterioration Scale (GDS) (i.e., starting with the GDS score of five, patients are no longer able survive without assistance due to major cognitive and functional impairments). Information about patients’ GDS scores was obtained from the Center’s Medical Director, who had an in-depth knowledge of each patient’s health and medical treatment history. All interviews were audiotaped and transcribed verbatim. The qualitative data analysis was conducted to answer the following research questions: 1) what treatment decisions do family caregivers make while managing the symptoms of advanced dementia and 2) how do these treatment decisions influence the quality of patient life? To validate the results, the author asked each participating family caregiver if the summarized findings accurately captured his/her experiences. The identified medical decisions ranged from seeking specialist medical care to end-of-life care. The most common decisions were related to arranging medical appointments, medication management, seeking treatments for pain and other symptoms, nursing home placement, and accessing community-based healthcare services. The most challenging and consequential decisions were related to the management of acute complications, hospitalizations, and discontinuation of treatments. Decisions that had the greatest impact on the quality of patient life and survival were triggered by traumatic falls, worsening psychiatric symptoms, and aspiration pneumonia. The study findings have important implications for geriatric nurses in the context of patient/caregiver-centered dementia care. Innovative nursing approaches are needed to support family caregivers to effectively manage medical care needs of patients with advanced dementia.

Keywords: advanced dementia, family caregiver, medical decision-making, symptom management

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2231 Revolutionizing Accounting: Unleashing the Power of Artificial Intelligence

Authors: Sogand Barghi

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The integration of artificial intelligence (AI) in accounting practices is reshaping the landscape of financial management. This paper explores the innovative applications of AI in the realm of accounting, emphasizing its transformative impact on efficiency, accuracy, decision-making, and financial insights. By harnessing AI's capabilities in data analysis, pattern recognition, and automation, accounting professionals can redefine their roles, elevate strategic decision-making, and unlock unparalleled value for businesses. This paper delves into AI-driven solutions such as automated data entry, fraud detection, predictive analytics, and intelligent financial reporting, highlighting their potential to revolutionize the accounting profession. Artificial intelligence has swiftly emerged as a game-changer across industries, and accounting is no exception. This paper seeks to illuminate the profound ways in which AI is reshaping accounting practices, transcending conventional boundaries, and propelling the profession toward a new era of efficiency and insight-driven decision-making. One of the most impactful applications of AI in accounting is automation. Tasks that were once labor-intensive and time-consuming, such as data entry and reconciliation, can now be streamlined through AI-driven algorithms. This not only reduces the risk of errors but also allows accountants to allocate their valuable time to more strategic and analytical tasks. AI's ability to analyze vast amounts of data in real time enables it to detect irregularities and anomalies that might go unnoticed by traditional methods. Fraud detection algorithms can continuously monitor financial transactions, flagging any suspicious patterns and thereby bolstering financial security. AI-driven predictive analytics can forecast future financial trends based on historical data and market variables. This empowers organizations to make informed decisions, optimize resource allocation, and develop proactive strategies that enhance profitability and sustainability. Traditional financial reporting often involves extensive manual effort and data manipulation. With AI, reporting becomes more intelligent and intuitive. Automated report generation not only saves time but also ensures accuracy and consistency in financial statements. While the potential benefits of AI in accounting are undeniable, there are challenges to address. Data privacy and security concerns, the need for continuous learning to keep up with evolving AI technologies, and potential biases within algorithms demand careful attention. The convergence of AI and accounting marks a pivotal juncture in the evolution of financial management. By harnessing the capabilities of AI, accounting professionals can transcend routine tasks, becoming strategic advisors and data-driven decision-makers. The applications discussed in this paper underline the transformative power of AI, setting the stage for an accounting landscape that is smarter, more efficient, and more insightful than ever before. The future of accounting is here, and it's driven by artificial intelligence.

Keywords: artificial intelligence, accounting, automation, predictive analytics, financial reporting

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2230 A Modularized Sensing Platform for Sensor Design Demonstration

Authors: Chun-Ming Huang, Yi-Jun Liu, Yi-Jie Hsieh, Jin-Ju Chue, Wei-Lin Lai, Chun-Yu Chen, Chih-Chyau Yang, Chien-Ming Wu

Abstract:

The market of wearable devices has been growing rapidly in two years. The integration of sensors and wearable devices has become the trend of the next technology products. Thus, the academics and industries are eager to cultivate talented persons in sensing technology. Currently, academic and industries have more and more demands on the integrations of versatile sensors and applications, especially for the teams who focus on the development of sensor circuit architectures. These teams tape-out many MEMs sensors chips through the chip fabrication service from National Chip Implementation Center (CIC). However, most of these teams are only able to focus on the circuit design of MEMs sensors; they lack the key support of further system demonstration. This paper follows the CIC’s main mission of promoting the chip/system advanced design technology and aims to establish the environments of the modularized sensing system platform and the system design flow with the measurement and calibration technology. These developed environments are used to support these research teams and help academically advanced sensor designs to perform the system demonstration. Thus, the research groups can promote and transfer their advanced sensor designs to industrial and further derive the industrial economic values. In this paper, the modularized sensing platform is proposed to enable the system demonstration for advanced sensor chip design. The environment of sensor measurement and calibration is established for academic to achieve an accurate sensor result. Two reference sensor designs cooperated with the modularized sensing platform are given to show the sensing system integration and demonstration. These developed environments and platforms are currently provided to academics in Taiwan, and so that the academics can obtain a better environment to perform the system demonstration and improve the research and teaching quality.

Keywords: modularized sensing platform, sensor design and calibration, sensor system, sensor system design flow

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2229 Inactivation of Semicarbazide-Sensitive Amine Oxidase Induces the Phenotypic Switch of Smooth Muscle Cells and Aggravates the Development of Atherosclerotic Lesions

Authors: Miao Zhang, Limin Liu, Feng Zhi, Panpan Niu, Mengya Yang, Xuemei Zhu, Ying Diao, Jun Wang, Ying Zhao

Abstract:

Background and Aims: Clinical studies have demonstrated that serum semicarbazide-sensitive amine oxidase (SSAO) activities positively correlate with the progression of atherosclerosis. The aim of the present study is to investigate the effect of SSAO inactivation on the development of atherosclerosis. Methods: Female LDLr knockout (KO) mice were given the Western-type diet for 6 and 9 weeks to induce the formation of early and advanced lesions, and semicarbazide (SCZ, 0.125%) was added into the drinking water to inactivate SSAO in vivo. Results: Despite no impact on plasma total cholesterol levels, abrogation of SSAO by SCZ not only resulted in the enlargement of both early (1.5-fold, p=0.0043) and advanced (1.8-fold, p=0.0013) atherosclerotic lesions, but also led to reduced/increased lesion contents of macrophages/smooth muscle cells (SMCs) (macrophage: ~0.74-fold, p=0.0002(early)/0.0016(advanced); SMC: ~1.55-fold, p=0.0003(early) /0.0001(advanced)), respectively. Moreover, SSAO inactivation inhibited the migration of circulating monocytes into peripheral tissues and reduced the amount of circulating Ly6Chigh monocytes (0.7-fold, p=0.0001), which may account for the reduced macrophage content in lesions. In contrast, the increased number of SMCs in lesions of SCZ-treated mice is attributed to an augmented synthetic vascular SMC phenotype switch as evidenced by the increased proliferation of SMCs and accumulation of collagens in vivo. Conclusion: SSAO inactivation by SCZ promotes the phenotypic switch of SMCs and the development of atherosclerosis. The enzymatic activity of SSAO may thus represent a potential target in the prevention and/or treatment of atherosclerosis.

Keywords: atherosclerosis, phenotype switch of smooth muscle cells, SSAO/VAP-1, semicarbazide

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2228 Dynamic Modeling of Advanced Wastewater Treatment Plants Using BioWin

Authors: Komal Rathore, Aydin Sunol, Gita Iranipour, Luke Mulford

Abstract:

Advanced wastewater treatment plants have complex biological kinetics, time variant influent flow rates and long processing times. Due to these factors, the modeling and operational control of advanced wastewater treatment plants become complicated. However, development of a robust model for advanced wastewater treatment plants has become necessary in order to increase the efficiency of the plants, reduce energy costs and meet the discharge limits set by the government. A dynamic model was designed using the Envirosim (Canada) platform software called BioWin for several wastewater treatment plants in Hillsborough County, Florida. Proper control strategies for various parameters such as mixed liquor suspended solids, recycle activated sludge and waste activated sludge were developed for models to match the plant performance. The models were tuned using both the influent and effluent data from the plant and their laboratories. The plant SCADA was used to predict the influent wastewater rates and concentration profiles as a function of time. The kinetic parameters were tuned based on sensitivity analysis and trial and error methods. The dynamic models were validated by using experimental data for influent and effluent parameters. The dissolved oxygen measurements were taken to validate the model by coupling them with Computational Fluid Dynamics (CFD) models. The Biowin models were able to exactly mimic the plant performance and predict effluent behavior for extended periods. The models are useful for plant engineers and operators as they can take decisions beforehand by predicting the plant performance with the use of BioWin models. One of the important findings from the model was the effects of recycle and wastage ratios on the mixed liquor suspended solids. The model was also useful in determining the significant kinetic parameters for biological wastewater treatment systems.

Keywords: BioWin, kinetic modeling, flowsheet simulation, dynamic modeling

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2227 An Overview of Nano-Particles Effect on Mechanical Properties of Composites

Authors: Ganiyu I. Lawal, Olatunde I. Sekunowo, Stephen I. Durowaye

Abstract:

Composites depending on the nature of their constituents and mode of production are regarded as one of the advanced materials that drive today’s technology. This paper attempts a short review of the subject matter with a general aim of pushing to the next level the frontier of knowledge as it impacts the technology of nano-particles manufacturing. The objectives entail an effort to; aggregate recent research efforts in this field, analyse research findings and observations, streamline research efforts and support industry in taking decision on areas of fund deployment. It is envisaged that this work will serve as a quick hand-on compendium material for researchers in this field and a guide to relevant government departments wishing to fund a research whose outcomes have the potential of improving the nation’s GDP.

Keywords: advanced materials, composites, mechanical properties, nano-particles

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2226 Study on Network-Based Technology for Detecting Potentially Malicious Websites

Authors: Byung-Ik Kim, Hong-Koo Kang, Tae-Jin Lee, Hae-Ryong Park

Abstract:

Cyber terrors against specific enterprises or countries have been increasing recently. Such attacks against specific targets are called advanced persistent threat (APT), and they are giving rise to serious social problems. The malicious behaviors of APT attacks mostly affect websites and penetrate enterprise networks to perform malevolent acts. Although many enterprises invest heavily in security to defend against such APT threats, they recognize the APT attacks only after the latter are already in action. This paper discusses the characteristics of APT attacks at each step as well as the strengths and weaknesses of existing malicious code detection technologies to check their suitability for detecting APT attacks. It then proposes a network-based malicious behavior detection algorithm to protect the enterprise or national networks.

Keywords: Advanced Persistent Threat (APT), malware, network security, network packet, exploit kits

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2225 Euthanasia in Dementia Cases: An Interview Study of Dutch Physicians' Experiences

Authors: J. E. Appel, R. N. Bouwmeester, L. Crombach, K. Georgieva, N. O’Shea, T. I. van Rijssel, L. Wingens

Abstract:

The Netherlands has a unique and progressive euthanasia law. Even people with advanced neurodegenerative diseases, like dementia, can request euthanasia when an Advanced Euthanasia Directive (AED) was written. Although the law sets some guidelines, in practice many complexities occur. Especially doctors experience difficult situations, as they have to decide whether euthanasia is justified. Research suggests that this leads to an emotional burden for them, due to feelings of isolation, fear of prosecution, as well as pressures from patient, family, or society. Existing literature, however, failed to address problems arising in dementia cases in particular, as well as possible sources of support. In order to investigate these issues, semi-structured in-depth interviews with 20 Dutch general practitioners and elderly care physicians will be conducted. Results are expected to be obtained by the end of December 2017.

Keywords: dementia, euthanasia, general practitioners, elderly care physicians, palliative care

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2224 Summer STEM Institute in Environmental Science and Data Sciencefor Middle and High School Students at Pace University

Authors: Lauren B. Birney

Abstract:

Summer STEM Institute for Middle and High School Students at Pace University The STEM Collaboratory NYC® Summer Fellows Institute takes place on Pace University’s New York City campus during July and provides the following key features for all participants: (i) individual meetings with Pace faculty to discuss and refine future educational goals; (ii) mentorship, guidance, and new friendships with program leaders; and (iii) guest lectures from professionals in STEM disciplines and businesses. The Summer STEM Institute allows middle school and high school students to work in teams to conceptualize, develop, and build native mobile applications that teach and reinforce skills in the sciences and mathematics. These workshops enhance students’STEM problem solving techniques and teach advanced methods of computer science and engineering. Topics include: big data and analytics at the Big Data lab at Seidenberg, Data Science focused on social and environmental advancement and betterment; Natural Disasters and their Societal Influences; Algal Blooms and Environmental Impacts; Green CitiesNYC; STEM jobs and growth opportunities for the future; renew able energy and sustainable infrastructure; and climate and the economy. In order to better align the existing Summer STEM, Institute with the CCERS model and expand the overall network, Pace is actively recruiting new content area specialists from STEM industries and private sector enterprises to participate in an enhanced summer institute in order to1) nurture student progress and connect summer learning to school year curriculum, 2) increase peer-to-peer collaboration amongst STEM professionals and private sector technologists, and 3) develop long term funding and sponsorship opportunities for corporate sector partners to support CCERS schools and programs directly.

Keywords: environmental restoration science, citizen science, data science, STEM

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2223 The Risks of 'Techtopia': Reviewing the Negative Lessons of Smart City Development

Authors: Amanda Grace Ahl, Matthew Brummer

Abstract:

‘Smart cities’ are not always as ‘smart’ as the term suggests, which is not often covered in the associated academic and public policy literatures. In what has become known as the smart city approach to urban planning, governments around the world are seeking to harness the power of information and communications technology with increasingly advanced data analytics to address major social, economic, and environmental issues reshaping the ways people live. The definitional and theoretical boundaries of the smart city framework are broad and at times ambiguous, as is empirical treatment of the topic. However, and for all the disparity, in investigating any number of institutional and policy prescriptions to the challenges faced by current and emerging metropoles, scholarly thought has hinged overwhelmingly on value-positive conceptions of informatics-centered design. From enhanced quality of services, to increased efficiency of resources, to improved communication between societal stakeholders, the smart city design is championed as a technological wellspring capable of providing answers to the systemic issues stymying a utopian image of the city. However, it is argued that this ‘techtopia’, has resulted in myopia within the discipline as to value-negative implications of such planning, such as weaknesses in practicality, scalability, social equity and affordability of solutions. In order to more carefully examine this observation - that ‘stupid’ represents an omitted variable bias in the study of ‘smart’ - this paper reviews critical cases of unsuccessful smart city developments. It is argued that also understanding the negative factors affiliated with the development processes is imperative for the advancement of theoretical foundations, policies, and strategies to further the smart city as an equitable, holistic urban innovation. What emerges from the process-tracing carried out in this study are distinctly negative lessons of smart city projects, the significance of which are vital for understanding how best to conceive smart urban planning in the 21st century.

Keywords: case study, city management, innovation system, negative lessons, smart city development

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2222 Challenges in E-Government: Conceptual Views and Solutions

Authors: Rasim Alguliev, Farhad Yusifov

Abstract:

Considering the international experience, conceptual and architectural principles of forming of electron government are researched and some suggestions were made. The assessment of monitoring of forming processes of electron government, intellectual analysis of web-resources, provision of information security, electron democracy problems were researched, conceptual approaches were suggested. By taking into consideration main principles of electron government theory, important research directions were specified.

Keywords: electron government, public administration, information security, web-analytics, social networks, data mining

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2221 Integrating Cyber-Physical System toward Advance Intelligent Industry: Features, Requirements and Challenges

Authors: V. Reyes, P. Ferreira

Abstract:

In response to high levels of competitiveness, industrial systems have evolved to improve productivity. As a consequence, a rapid increase in volume production and simultaneously, a customization process require lower costs, more variety, and accurate quality of products. Reducing time-cycle production, enabling customizability, and ensure continuous quality improvement are key features in advance intelligent industry. In this scenario, customers and producers will be able to participate in the ongoing production life cycle through real-time interaction. To achieve this vision, transparency, predictability, and adaptability are key features that provide the industrial systems the capability to adapt to customer demands modifying the manufacturing process through an autonomous response and acting preventively to avoid errors. The industrial system incorporates a diversified number of components that in advanced industry are expected to be decentralized, end to end communicating, and with the capability to make own decisions through feedback. The evolving process towards advanced intelligent industry defines a set of stages to empower components of intelligence and enhancing efficiency to achieve the decision-making stage. The integrated system follows an industrial cyber-physical system (CPS) architecture whose real-time integration, based on a set of enabler technologies, links the physical and virtual world generating the digital twin (DT). This instance allows incorporating sensor data from real to virtual world and the required transparency for real-time monitoring and control, contributing to address important features of the advanced intelligent industry and simultaneously improve sustainability. Assuming the industrial CPS as the core technology toward the latest advanced intelligent industry stage, this paper reviews and highlights the correlation and contributions of the enabler technologies for the operationalization of each stage in the path toward advanced intelligent industry. From this research, a real-time integration architecture for a cyber-physical system with applications to collaborative robotics is proposed. The required functionalities and issues to endow the industrial system of adaptability are identified.

Keywords: cyber-physical systems, digital twin, sensor data, system integration, virtual model

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2220 Micropollutant Carbamazepine: Its Occurrences, Toxicological Effects, and Possible Degradation Methods (Review)

Authors: Azad Khalid, Sifa Dogan

Abstract:

Because of its persistence in conventional treatment plants and broad prevalence in water bodies, the pharmaceutical chemical carbamazepine (CBZ) has been suggested as an anthropogenic marker to evaluate water quality. This study provides a thorough examination of the origins and occurrences of CBZ in water bodies, as well as the drug's toxicological effects and laws. Given CBZ's well-documented negative consequences on the human body when used medicinally, cautious monitoring in water is advised. CBZ residues in drinking water may enter embryos and newborns via intrauterine exposure or breast-feeding, causing congenital abnormalities and/or neurodevelopmental issues over time. The insufficiency of solo solutions was shown after an in-depth technical study of traditional and sophisticated treatment technologies. Nanofiltration and reverse osmosis membranes are more successful at removing CBZ than traditional activated sludge and membrane bioreactor techniques. Recent research has shown that severe chemical cleaning, which is essential to prevent membrane fouling, may lower long-term removal efficiency. Furthermore, despite the efficacy of activated carbon adsorption and advanced oxidation processes, a few issues such as chemical cost and activated carbon renewal must be carefully examined. Individual technology constraints lead to the benefits of combined and hybrid systems, namely the heterogeneous advanced oxidation process.

Keywords: carbamazepine, occurrence, toxicity, conventical treatment, advanced oxidation process (AOPs)

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