Search results for: expert’s preference rating approach

Authors: Wang Liguang, Zhang Xueqing

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The build-operate-transfer (BOT) project delivery system has provided effective routes to mobilize private sector funds, innovative technologies, management skills and operational efficiencies for public infrastructure development and have been widely used in China during the last 20 years. Many BOT projects in China will be smoothly transferred to the government soon and the transfer stage, which is considered as the last stage, must be studied carefully and handled well to achieve the overall success of BOT projects. There will be many issues faced by both the public sector and private sector in the transfer stage of BOT projects, including project post-assessment, technology and documents transfer, personal training and staff transition, etc. and sometimes additional legislation is needed for future operation and management of facilities. However, most previous studies focused on the bidding, financing, and building and operation stages instead of transfer stage. This research identifies nine key issues in the transfer stage of BOT projects through a comprehensive study on three cases in China, and the expert interview and expert discussion meetings are held to validate the key issues and give detail analysis. A proposed framework of transfer management is prepared based on the experiences derived and lessons drawn from the case studies and expert interview and discussions, which is expected to improve the transfer management of BOT projects in practice.

Keywords: BOT project, key issues, transfer management, transfer stage

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Authors: Hanene Sahli, Aymen Mouelhi, Marwa Hajji, Amine Ben Slama, Mounir Sayadi, Farhat Fnaiech, Radhwane Rachdi

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Fetal abnormality is still a public health problem of interest to both mother and baby. Head defect is one of the most high-risk fetal deformities. Fetal head categorization is a sensitive task that needs a massive attention from neurological experts. In this sense, biometrical measurements can be extracted by gynecologist doctors and compared with ground truth charts to identify normal or abnormal growth. The fetal head biometric measurements such as Biparietal Diameter (BPD), Occipito-Frontal Diameter (OFD) and Head Circumference (HC) needs to be monitored, and expert should carry out its manual delineations. This work proposes a new approach to automatically compute BPD, OFD and HC based on morphological characteristics extracted from head shape. Hence, the studied data selected at the same Gestational Age (GA) from the fetal Ultrasound images (US) are classified into two categories: Normal and abnormal. The abnormal subjects include hydrocephalus, microcephaly and dolichocephaly anomalies. By the use of a support vector machines (SVM) method, this study achieved high classification for automated detection of anomalies. The proposed method is promising although it doesn't need expert interventions.

Keywords: biometric measurements, fetal head malformations, machine learning methods, US images

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Authors: M. Safa, A. Sabet, S. MacGillivray, M. Davidson, K. Kaczmarczyk, C. T. Haas, G. E. Gibson, D. Rayside

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To address construction project requirements and specifications, scholars and practitioners need to establish a taxonomy according to a scheme that best fits their need. While existing characterization methods are continuously being improved, new ones are devised to cover project properties which have not been previously addressed. One such method, the Project Definition Rating Index (PDRI), has received limited consideration strictly as a classification scheme. Developed by the Construction Industry Institute (CII) in 1996, the PDRI has been refined over the last two decades as a method for evaluating a project's scope definition completeness during front-end planning (FEP). The main contribution of this study is a review of practical project classification methods, and a discussion of how PDRI can be used to classify projects based on their readiness in the FEP phase. The proposed model has been applied to 59 construction projects in Ontario, and the results are discussed.

Keywords: project classification, project definition rating index (PDRI), risk, project goals alignment

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Authors: Felix Olajide Ibikunle

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Introductory Statement: Sustainable participation of teenagers in sport requires deliberate and concerted plan and managerial policy rooted in the “philosophy of catch them young”. At risk, teenagers need proper integration into societal aspiration: This direction will go a long way to streamline them into the security breach and attractive nuisance free lifestyles. Basic Methodology: The population consists of children within 13-19 years old. A proportionate sampling size technique of 60% was adopted to select seven zones out of 11 geo-political zones in the Ibadan metropolis. Qualitative information and interview were used to collect needed information. Majority of the teenagers were out of school, street hawkers, motor pack, touts, and unserious vocation apprentices. These groups have the potentials of security breaches in the metropolis and beyond. Five hundred and thirty-four (534) respondents were used for the study. They were drawn from Ojoo, Akingbile, and Moniya axis = 72, Agbowo, Ajibode, and Apete axis = 74; Akobo, Basorun, and Idi-ape axis 79; Wofun, Monatan, and Iyana-Church axis = 78; Molete, Oke-ado and Oke-Bola axis = 75; Beere, Odinjo, Elekuro axis = 77; Eleyele, Ologuneru, and Alesinloye axis = 79. Major Findings: Multiple regression was used to analyze the independent variables and percentage. The respondents average age was 15.6 years old, and with 100% male. The instrument(questionnaire) used yielded; sport preference (r = 0.72); intervention (r = 0.68) and the sustainable participation (r = 0.70).The relative contributions of sport preference on participation of at risk teenagers was (F-ratio = 1.067); Intervention contribution of sport on participation of at risk teenagers = produced (F-ratio of 12.095) was significant while sustainable participation of at risk teenager produced (F-ratio = 1.062) was significant. Closing Statement: The respondents’ sport preference stimulated their participation in sport. The intervention exposed at risk-teenagers to coaching, which activated their interest and participation in sport. While sustainable participation contributed positively to evolve at risk teenagers participation in their preferred sport.

Keywords: sport, preference, intervention, teenagers, sustainable, participation and risk teenagers

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Authors: Rina Yadav, Meng-Ting Tsai

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In the present scenario, sustainable buildings are in high demand. The essential decision for building sustainability is made during the design and preconstruction stages. Main objective of this study is reduction of unfavorable environmental impacts, which is a major cause of global warming. Based on this problem, to diminish the environmental hazards, present research study is applied to provide a guideline to designer that will be useful for material selection stage of designing. This can be achieved by using local available materials such as wood, mud, bamboos instead of cement, steel, concrete by reducing carbon dioxide emission. Energy simulation will be analyzed by software to get the comparable result. It will be encouraging and motivational for designer while using ecofriendly material to achieve points in Leadership in energy and environmental design (LEED) in green rating system.

Keywords: sustainability design, lead rating, LEED, building performance analyses

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Authors: Von Anthony G. Torio

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Motivation and research are significant determinants of a student’s success in the school and in future careers. This study aimed to give a picture of the physics motivation of students in a tertiary level institution, as well as their research area and working preference, to create a picture of the nature of the representative youths of today. It was found that male students have higher motivation than female students in all components of motivation with intrinsic motivation leading the six components of motivation. In addition, male students (M = 4.27; SD = 0.74) were found to have significantly higher motivation as compared to female students (M = 3.77; SD = 0.89) with a computed t(64) value of 2.41 with p < 0.05 and Cohen’s d of 0.61. The students’ preference to work in groups of three rather than working individually suggests that students of the batch have small working groups that they depend on rather than working alone. The majority of the students also preferred conducting studies on the social sciences.

Keywords: motivation, physics, research, physics motivation, physics education, Philippines

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Authors: Malik Abdul Jabbar Zen, Wiwik Misaco Yuniarti, Azisya Amalia Karimasari, Novita Priandini

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Zoonos is as an infectiontransmitted froma nimals to human sand vice versa currently having increased in the last 20 years. The experts/scientists predict that zoonosis will be a threat to the community in the future since it leads on 70% emerging infectious diseases (EID) and the high mortality of 50%-90%. The zoonosis’ spread from animal to human is caused by contaminated food known as foodborne disease. One World One Health, as the conceptual prevention toward zoonosis, requires the crossed disciplines cooperation to accelerate and streamlinethe handling ofanimal-based disease. E-Vet Smart Rapid System is an integrated innovation in the veterinary expertise application is able to facilitate the prevention, treatment, and educationagainst pandemic diseases and zoonosis. This system is constructed by Decision Support System (DSS) method provides a database of knowledge that is expected to facilitate the identification of disease rapidly, precisely, and accurately as well as to identify the deduction. The testingis conducted through a black box test case and questionnaire (N=30) by validity and reliability approach. Based on the black box test case reveals that E-Vet Rapid System is able to deliver the results in accordance with system design, and questionnaire shows that this system is valid (r > 0.361) and has a reliability (α > 0.3610).

Keywords: diagnosis, disease, expert systems, livestock, zoonosis

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Authors: Jinan Fiaidhi, Sabah Mohammed

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Diagnosing cataract severity is an important factor in deciding to undertake surgery. It is usually conducted by an ophthalmologist or through taking a variety of fundus photography that needs to be examined by the ophthalmologist. This paper carries out an investigation using a Siamese neural net that can be trained with small anchor samples to score cataract severity. The model used in this paper is based on a triplet loss function that takes the ophthalmologist best experience in rating positive and negative anchors to a specific cataract scaling system. This approach that takes the heuristics of the ophthalmologist is generally called the thick data approach, which is a kind of machine learning approach that learn from a few shots. Clinical Relevance: The lens of the eye is mostly made up of water and proteins. A cataract occurs when these proteins at the eye lens start to clump together and block lights causing impair vision. This research aims at employing thick data machine learning techniques to rate the severity of the cataract using Siamese neural network.

Keywords: thick data analytics, siamese neural network, triplet-loss model, few shot learning

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Authors: Marta Nawrocka

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In each of the legal proceedings, in which expert evidence is carried out, a major concern is the assessment of the evidential value of expert reports. Judicial institutions, while making decisions, rely heavily on the expert reports, because they usually do not possess 'special knowledge' from a certain fields of science which makes it impossible for them to verify the results presented in the processes. In handwriting studies, the standards of analysis are developed. They unify procedures used by experts in comparing signs and in constructing expert reports. However, the methods used by experts are usually of a qualitative nature. They rely on the application of knowledge and experience of expert and in effect give significant range of margin in the assessment. Moreover, the standards used by experts are still not very precise and the process of reaching the conclusions is poorly understood. The above-mentioned circumstances indicate that expert opinions in the field of handwriting analysis, for many reasons, may not be sufficiently reliable. It is assumed that this state of affairs has its source in a very low level of intersubjectivity of measuring scales and analysis procedures, which consist elements of this kind of analysis. Intersubjectivity is a feature of cognition which (in relation to methods) indicates the degree of consistency of results that different people receive using the same method. The higher the level of intersubjectivity is, the more reliable and credible the method can be considered. The aim of the conducted research was to determine the degree of intersubjectivity of the methods used by the experts from the scope of handwriting analysis. 30 experts took part in the study and each of them received two signatures, with varying degrees of readability, for analysis. Their task was to distinguish graphic characteristics in the signature, estimate the evidential value of the found characteristics and estimate the evidential value of the signature. The obtained results were compared with each other using the Alpha Krippendorff’s statistic, which numerically determines the degree of compatibility of the results (assessments) that different people receive under the same conditions using the same method. The estimation of the degree of compatibility of the experts' results for each of these tasks allowed to determine the degree of intersubjectivity of the studied method. The study showed that during the analysis, the experts identified different signature characteristics and attributed different evidential value to them. In this scope, intersubjectivity turned out to be low. In addition, it turned out that experts in various ways called and described the same characteristics, and the language used was often inconsistent and imprecise. Thus, significant differences have been noted on the basis of language and applied nomenclature. On the other hand, experts attributed a similar evidential value to the entire signature (set of characteristics), which indicates that in this range, they were relatively consistent.

Keywords: forensic sciences experts, handwriting analysis, inter-rater reliability, reliability of methods

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Authors: Hoang Vo Thi Minh, Duyen Nguyen Thi Phuong, Gerardo Van Halsema

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As one of the deltas which is extremely vulnerable to climate change, the Mekong Delta, Vietnam is facing many challenges that need to be addressed in strategic and holistic ways. In this study scope, a strategic delta planning is recently considered as a new vision of Adaptive Delta Management for the Mekong Delta. In Adaptive Delta Management, Room for the Rivers (RftR) has been formulated as a typical innovation, which is currently in need of careful consideration for implementing in the Mekong Delta’s planning process. This study then attempts to investigate the roles and analyze sociological aspects of the RftR as potential strategic 'soft' measure, in upstream of Hau River in An Phu district, An Giang province, especially in terms of its so-called multifunctions. The study applied social science approach embedded with a few qualitative methods including in-depth interviews and questionnaire distribution and conjoint analysis as a quantitative approach. The former mainly aims at gaining the local community’s perceptions about the RftR solution. The latter tries to gain farmers’ willingness to accept (WTA) with regard to their level of preference towards the three selected solutions which are considered as strategic plans for sustainably developing the MD. Qualitative data analysis shows that, farmers perceive RftR as very useful for their livelihoods due to its multifunctions as well as in terms of water management. The quantitative results illustrated that respondents expressed their WTAs on RftR as 84. 240 thousand VND / year. Amongst the three solutions that are analysed within this study (Floating rice for upper delta, Room for the Rivers for the Middle, and Shrimp-Mangrove integration for the coastal delta), RfrR was ranked as second preference from respondents. This result is not exactly reflecting the real values of these three mentioned solutions but showing a tendency that can be seen as a reference for the decision-makers in delta planning processes.

Keywords: strategic delta planning, room for the River, farmers’ perception, willingness-to-accept, local livelihoods

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Authors: Vinicius G. Goecks, Gregory M. Gremillion, William D. Nothwang

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Modern approaches to train intelligent agents rely on prolonged training sessions, high amounts of input data, and multiple interactions with the environment. This restricts the application of these learning algorithms in robotics and real-world applications, in which there is low tolerance to inadequate actions, interactions are expensive, and real-time processing and action are required. This paper addresses this issue introducing CyberSteer, a novel approach to efficiently design intrinsic reward functions based on human intention to guide deep reinforcement learning agents with no environment-dependent rewards. CyberSteer uses non-expert human operators for initial demonstration of a given task or desired behavior. The trajectories collected are used to train a behavior cloning deep neural network that asynchronously runs in the background and suggests actions to the deep reinforcement learning module. An intrinsic reward is computed based on the similarity between actions suggested and taken by the deep reinforcement learning algorithm commanding the agent. This intrinsic reward can also be reshaped through additional human demonstration or critique. This approach removes the need for environment-dependent or hand-engineered rewards while still being able to safely shape the behavior of autonomous robotic agents, in this case, based on human intention. CyberSteer is tested in a high-fidelity unmanned aerial vehicle simulation environment, the Microsoft AirSim. The simulated aerial robot performs collision avoidance through a clustered forest environment using forward-looking depth sensing and roll, pitch, and yaw references angle commands to the flight controller. This approach shows that the behavior of robotic systems can be shaped in a reduced amount of time when guided by a non-expert human, who is only aware of the high-level goals of the task. Decreasing the amount of training time required and increasing safety during training maneuvers will allow for faster deployment of intelligent robotic agents in dynamic real-world applications.

Keywords: human-robot interaction, intelligent robots, robot learning, semisupervised learning, unmanned aerial vehicles

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Authors: Hosein Hamisheh Bahar, Mohammad Hossein Fazel Zarandi, Akbar Esfahanipour

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In this paper, a hybrid expert system is developed by using fuzzy genetic network programming with reinforcement learning (GNP-RL). In this system, the frame-based structure of the system uses the trading rules extracted by GNP. These rules are extracted by using technical indices of the stock prices in the training time period. For developing this system, we applied fuzzy node transition and decision making in both processing and judgment nodes of GNP-RL. Consequently, using these method not only did increase the accuracy of node transition and decision making in GNP's nodes, but also extended the GNP's binary signals to ternary trading signals. In the other words, in our proposed Fuzzy GNP-RL model, a No Trade signal is added to conventional Buy or Sell signals. Finally, the obtained rules are used in a frame-based system implemented in Kappa-PC software. This developed trading system has been used to generate trading signals for ten companies listed in Tehran Stock Exchange (TSE). The simulation results in the testing time period shows that the developed system has more favorable performance in comparison with the Buy and Hold strategy.

Keywords: fuzzy genetic network programming, hybrid expert system, technical trading signal, Tehran stock exchange

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Authors: Olivia Rybak-Karkosz

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This paper's purpose was to present a case study on a questioned Claude Monet's signature forensic handwriting analysis. It is an example taken from the author’s experience as a court handwriting expert. A comparative study was conducted to determine whether the signature resembles similarities (and if so, to what measure) with the features representing the writing patterns and their natural variability typical for Claude Monet. It was conducted to check whether all writing features are within the writer's normal range of variation. The paper emphasizes the difficulties and challenges encountered by the forensic handwriting expert while analysing the questioned signature.

Keywords: artist’s signatures, authenticity of an artwork, forensic handwriting analysis, graphic-comparative method

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Authors: E. Rama Devi Jothilingam

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Diabetes mellitus is now one of the most common non communicable diseases globally. India leads the world with largest number of diabetic subjects earning the title "diabetes capital of the world". In order to reduce the mortality rate, a fuzzy expert system is designed to predict the severity of cardiac and renal problems of diabetic patients using fuzzy logic. Since uncertainty is inherent in medicine, fuzzy logic is used in this research work to remove the inherent fuzziness of linguistic concepts and uncertain status in diabetes mellitus which is the prime cause for the cardiac arrest and renal failure. In this work, the controllable risk factors "blood sugar, insulin, ketones, lipids, obesity, blood pressure and protein/creatinine ratio" are considered as input parameters and the "the stages of cardiac" (SOC)" and the stages of renal" (SORD) are considered as the output parameters. The triangular membership functions are used to model the input and output parameters. The rule base is constructed for the proposed expert system based on the knowledge from the medical experts. Mamdani inference engine is used to infer the information based on the rule base to take major decision in diagnosis. Mean of maximum is used to get a non fuzzy control action that best represent possibility distribution of an inferred fuzzy control action. The proposed system also classifies the patients with high risk and low risk using fuzzy c means clustering techniques so that the patients with high risk are treated immediately. The system is validated with Matlab and is used as a tracking system with accuracy and robustness.

Keywords: Diabetes mellitus, fuzzy expert system, Mamdani, MATLAB

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Authors: Sormeh Sharifi, Wasim Saman, Alemu Alemu, David Whaley

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Although various energy rating schemes and compulsory building codes are using around the world, there are increasing reports on overheating in energy efficient dwellings. Given that the cooling demand of buildings is rising globally because of the climate change, it is more likely that the overheating issue will be observed more. This paper studied the summer indoor temperature in eight air-conditioned multi-level houses in Adelaide which have complied with the Australian Nationwide Houses Energy Rating Scheme (NatHERS) minimum energy performance of 7.5 stars. Through monitored temperature, this study explores that overheating is experienced on 75.5% of top floors during cooling periods while the air-conditioners were running. This paper found that the energy efficiency regulations have significantly improved thermal comfort in low floors, but not on top floors, and the energy-efficient house is not necessarily adapted with the air temperature fluctuations particularly on top floors. Based on the results, this study suggests that the envelope of top floors for multi-level houses in South Australian context need new criteria to make the top floor more heat resistance in order to: preventing the overheating, reducing the summer pick electricity demand and providing thermal comfort. Some methods are used to improve the envelope of the eight case studies. The results demonstrate that improving roofs was the most effective part of the top floors envelope in terms of reducing the overheating.

Keywords: building code, climate change, energy-efficient building, energy rating, overheating, thermal comfort

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Authors: Till Gramberg, Max Kellner, Erwin Gross

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This paper presents a comprehensive investigation into the topic of smart services and IIoT-Platforms, focusing on their selection and prioritization in manufacturing organizations. First, a literature review is conducted to provide a basic understanding of the current state of research in the area of smart services. Based on discussed and established definitions, a definition approach for this paper is developed. In addition, value propositions for smart services are identified based on the literature and expert interviews. Furthermore, the general requirements for the provision of smart services are presented. Subsequently, existing approaches for the selection and development of smart services are identified and described. In order to determine the requirements for the selection of smart services, expert opinions from successful companies that have already implemented smart services are collected through semi-structured interviews. Based on the results, criteria for the evaluation of existing methods are derived. The existing methods are then evaluated according to the identified criteria. Furthermore, a novel method for the selection of smart services in manufacturing companies is developed, taking into account the identified criteria and the existing approaches. The developed concept for the method is verified in expert interviews. The method includes a collection of relevant smart services identified in the literature. The actual relevance of the use cases in the industrial environment was validated in an online survey. The required data and sensors are assigned to the smart service use cases. The value proposition of the use cases is evaluated in an expert workshop using different indicators. Based on this, a comparison is made between the identified value proposition and the required data, leading to a prioritization process. The prioritization process follows an established procedure for evaluating technical decision-making processes. In addition to the technical requirements, the prioritization process includes other evaluation criteria such as the economic benefit, the conformity of the new service offering with the company strategy, or the customer retention enabled by the smart service. Finally, the method is applied and validated in an industrial environment. The results of these experiments are critically reflected upon and an outlook on future developments in the area of smart services is given. This research contributes to a deeper understanding of the selection and prioritization process as well as the technical considerations associated with smart service implementation in manufacturing organizations. The proposed method serves as a valuable guide for decision makers, helping them to effectively select the most appropriate smart services for their specific organizational needs.

Keywords: smart services, IIoT, industrie 4.0, IIoT-platform, big data

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Authors: Santosh Sharma Parajuli, Diwas Manandhar

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Background: Perioperative pain management plays an integral part in patients undergoing cardiac surgery. We studied the effect of Erector Spinae Plane block on acute postoperative pain reduction and 24 hours opioid consumption in adult cardiac surgical patients. Methods: Twenty-five adult cardiac surgical patients who underwent cardiac surgery with sternotomy in whom ESP catheters were placed preoperatively were kept in group E, and the other 25 patients who had undergone cardiac surgery without ESP catheter and pain management done with conventional opioid injection were placed in group C. Fentanyl was used for pain management. The primary study endpoint was to compare the consumption of fentanyl and to assess the numeric rating scale in the postoperative period in the first 24 hours in both groups. Results: The 24 hours fentanyl consumption was 43.00±51.29 micrograms in the Erector Spinae Plane catheter group and 147.00±60.94 micrograms in the control group postoperatively which was statistically significant (p <0.001). The numeric rating scale was also significantly reduced in the Erector Spinae Plane group compared to the control group in the first 24 hours postoperatively. Conclusion: Erector Spinae Plane block is superior to the conventional opioid injection method for postoperative pain management in CABG patients. Erector Spinae Plane block not only decreases the overall opioid consumption but also the NRS score in these patients.

Keywords: erector, spinae, plane, numerical rating scale

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Authors: Rajesh Ranjan, Marimuthu Palaniswami, A. A. Hashmi

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With the changing lifestyle and environment around us, the prevalence of the critical and incurable disease has proliferated. One such condition is the neurological disorder which is rampant among the old age population and is increasing at an unstoppable rate. Most of the neurological disorder patients suffer from some movement disorder affecting the movement of their body parts. Tremor is the most common movement disorder which is prevalent in such patients that infect the upper or lower limbs or both extremities. The tremor symptoms are commonly visible in Parkinson’s disease patient, and it can also be a pure tremor (essential tremor). The patients suffering from tremor face enormous trouble in performing the daily activity, and they always need a caretaker for assistance. In the clinics, the assessment of tremor is done through a manual clinical rating task such as Unified Parkinson’s disease rating scale which is time taking and cumbersome. Neurologists have also affirmed a challenge in differentiating a Parkinsonian tremor with the pure tremor which is essential in providing an accurate diagnosis. Therefore, there is a need to develop a monitoring and assistive tool for the tremor patient that keep on checking their health condition by coordinating them with the clinicians and caretakers for early diagnosis and assistance in performing the daily activity. In our research, we focus on developing a system for automatic classification of tremor which can accurately differentiate the pure tremor from the Parkinsonian tremor using a wearable accelerometer-based device, so that adequate diagnosis can be provided to the correct patient. In this research, a study was conducted in the neuro-clinic to assess the upper wrist movement of the patient suffering from Pure (Essential) tremor and Parkinsonian tremor using a wearable accelerometer-based device. Four tasks were designed in accordance with Unified Parkinson’s disease motor rating scale which is used to assess the rest, postural, intentional and action tremor in such patient. Various features such as time-frequency domain, wavelet-based and fast-Fourier transform based cross-correlation were extracted from the tri-axial signal which was used as input feature vector space for the different supervised and unsupervised learning tools for quantification of severity of tremor. A minimum covariance maximum correlation energy comparison index was also developed which was used as the input feature for various classification tools for distinguishing the PT and ET tremor types. An automatic system for efficient classification of tremor was developed using feature extraction methods, and superior performance was achieved using K-nearest neighbors and Support Vector Machine classifiers respectively.

Keywords: machine learning approach for neurological disorder assessment, automatic classification of tremor types, feature extraction method for tremor classification, neurological movement disorder, parkinsonian tremor, essential tremor

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Authors: Ashfaq M. Naikwadi

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Decided cases of medical negligence, mostly are not settled in the lower courts. Majority of them reach up to the apex courts. This is mostly due to different interpretations of the term medical negligence. After studying various cases of medical negligence it is found that in most of the cases the doctors/hospitals are not held liable. There are different interpretations of law concerning medical services. Globally the principles deciding medical negligence are same, viz. Legal duty of care - breach of that duty - direct causation resulting in damages. Since ordinary negligence is not punishable by law, doctors/hospitals have defenses to save themselves from liability. Complaints of negligence come to the courts whose judges mostly are not oriented with medical services or health sciences. Matters of medical negligence are decided on the basic principles of reasonableness and prudence or by relying on the expert’s opinion. Deciding reasonableness or prudence is a complex issue in case of medical services. Again expert opinion is also questionable as an expert in case of medical negligence is appointed from the same field and same faculty. There is a chance of favoritism to the doctor/hospital. The concept of vicarious liability is not widely applied to in many of the medical negligence cases. Established cases used as precedents were studied to understand the basic principles in deciding medical negligence. This paper evaluates the present criteria in interpreting medical negligence and concludes with suggesting reforms required to be made in deciding matters of medical negligence under the consumer laws.

Keywords: consumer, doctors, laws, medical negligence

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Authors: Sri Rejeki Dwi Astuti, Suyanta

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The demanding of the asessment in learning process was impact by policy changes. Nowadays, the assessment not only emphasizes knowledge, but also skills and attitude. However, in reality there are many obstacles in measuring them. This paper aimed to describe how to develop instrument of integrated assessment as alternative assessment to measure critical thinking skills and science process skills in electrolyte solution and to describe instrument’s characteristic such as logic validity and construct validity. This instrument development used test development model by McIntire. Development process data was acquired based on development test step and was analyzed by qualitative analysis. Initial product was observed by three peer reviewer and six expert judgment (two subject matter expert, two evaluation expert and two chemistry teacher) to acquire logic validity test. Logic validity test was analyzed using Aiken’s formula. The estimation of construct validity was analyzed by exploratory factor analysis. Result showed that integrated assessment instrument has 0,90 of Aiken’s Value and all item in integrated assessment asserted valid according to construct validity.

Keywords: construct validity, critical thinking skills, integrated assessment instrument, logic validity, science process skills

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Authors: Rachel Goh, Alexander McNab, Brent Alsop, David O'Hare

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In a busy airport, the decision whether to take passengers aside and search their luggage for dangerous items can have important consequences. If an officer fails to search and stop a bag containing a dangerous object, a life-threatening incident might occur. But stopping a bag unnecessarily means that the officer might lose time searching the bag and face an angry passenger. Passengers’ bags, however, are often cluttered with personal belongings of varying shapes and sizes. It can be difficult to determine what is dangerous or not, especially if the decisions must be made quickly in cases of busy flight schedules. Additionally, the decision to search bags is often made with input from the surrounding officers on duty. This scenario raises several questions: 1) Past findings suggest that humans are more reliant on an automated aid when under time pressure in a visual search task, but does this translate to human-human reliance? 2) Are humans more likely to agree with another person if the person is assumed to be an expert or a novice in these ambiguous situations? In the present study, forty-one participants performed a simulated luggage-screening task. They were partnered with an advisor of two different statuses (expert vs. novice), but of equal accuracy (90% correct). Participants made two choices each trial: their first choice with no advisor input, and their second choice after advisor input. The second choice was made within either 2 seconds or 8 seconds; failure to do so resulted in a long time-out period. Under the 2-second time pressure, participants were more likely to disagree with their own first choice and agree with the expert advisor, regardless of whether the expert was right or wrong, but especially when the expert suggested that the bag was safe. The findings indicate a tendency for people to assume less responsibility for their decisions and defer to their partner, especially when a quick decision is required. This over-reliance on others’ opinions might have negative consequences in real life, particularly when relying on fallible human judgments. More awareness is needed regarding how a stressful environment may influence reliance on other’s opinions, and how better techniques are needed to make the best decisions under high stress and time pressure.

Keywords: advisors, decision-making, time pressure, trust

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Authors: Zaid Jamal Saeed Almahmoud

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Smart Grid is the vision of the future power system that combines advanced monitoring and communication technologies to provide energy in a smart, efficient, and user-friendly manner. This proposal considers a demand response model in the Smart Grid based on utility maximization. Given a set of consumers with conflicting preferences in terms of consumption and a utility company that aims to minimize the peak demand and match demand to supply, we study the problem of aggregating these preferences while modelling the problem as a game. We also investigate whether an equilibrium can be reached to maximize the social benefit. Based on such equilibrium, we propose a dynamic pricing heuristic that computes the equilibrium and sets the prices accordingly. The developed approach was analysed theoretically and evaluated experimentally using real appliances data. The results show that our proposed approach achieves a substantial reduction in the overall energy consumption.

Keywords: heuristics, smart grid, aggregation, mechanism design, equilibrium

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Authors: Zhicheng Han

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This study examines the correlation between knowledge of formulaic language, working memory (WM), and phonological short-term memory (PSTM) in Chinese L2 learners of English. This study investigates if WM and PSTM correlate differently to the acquisition of formulaic language, which may be relevant for the discourse around the conceptualization of formulas. Connectionist approaches have lead scholars to argue that formulas are form-meaning connections stored whole, making PSTM significant in the acquisitional process as it pertains to the storage and retrieval of chunk information. Generativist scholars, on the other hand, argued for active participation of interlanguage grammar in the acquisition and use of formulaic language, where formulas are represented in the mind but retain the internal structure built around a lexical core. This would make WM, especially the processing component of WM an important cognitive factor since it plays a role in processing and holding information for further analysis and manipulation. The current study asked L1 Chinese learners of English enrolled in graduate programs in China to complete a preference raking task where they rank their preference for formulas, grammatical non-formulaic expressions, and ungrammatical phrases with and without the lexical core in academic contexts. Participants were asked to rank the options in order of the likeliness of them encountering these phrases in the test sentences within academic contexts. Participants’ syntactic proficiency is controlled with a cloze test and grammar test. Regression analysis found a significant relationship between the processing component of WM and preference of formulaic expressions in the preference ranking task while no significant correlation is found for PSTM or syntactic proficiency. The correlational analysis found that WM, PSTM, and the two proficiency test scores have significant covariates. However, WM and PSTM have different predictor values for participants’ preference for formulaic language. Both storage and processing components of WM are significantly correlated with the preference for formulaic expressions while PSTM is not. These findings are in favor of the role of interlanguage grammar and syntactic knowledge in the acquisition of formulaic expressions. The differing effects of WM and PSTM suggest that selective attention to and processing of the input beyond simple retention play a key role in successfully acquiring formulaic language. Similar correlational patterns were found for preferring the ungrammatical phrase with the lexical core of the formula over the ones without the lexical core, attesting to learners’ awareness of the lexical core around which formulas are constructed. These findings support the view that formulaic phrases retain internal syntactic structures that are recognized and processed by the learners.

Keywords: formulaic language, working memory, phonological short-term memory, academic language

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Authors: Mehmet Yildiz, Mehmet Kale

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The primary aim of the present study was to identify the bilateral balance asymmetries when comparing the dominant (DL) vs. the non-dominant leg (NDL) in the collegian soccer players. The secondary aim was to compare the inter-limb asymmetry index (ASI) when differentiating by kicking preference (right-dominant vs. left-dominant). 34 right-dominant leg (RightDL) (age:21.12±1.85, height:174.50±5.18, weight:69.42±6.86) and 23 left-dominant leg (LeftDL), (age:21.70±2.03, height:176.2±6.27, weight:68.73±5.96) collegian football players were tested for bilateral static and dynamic balance. Balance ability was assessed by measuring centre of pressure deviation on a single leg. Single leg static and dynamic balance scores and inter-limb asymmetry index (ASI) were determined. Student t tests were used for the comparison of dominant and nondominant leg balance scores and RightDL and LeftDL football players’ inter-limb asymmetry index of the balance scores. The results showed that there were significant differences in the dynamic balance scores in favour of the nondominant leg, (DL:738±211 vs. NDL:606±226, p < 0.01). Also, it has been seen that LeftDL players have significantly higher inter-limb asymmetry index when compared with rightDL players for both static (rightDL:-7.07±94.91 vs. leftDL:-183.19±354.05, p < 0.01) and dynamic (rightDL: 1.73±49.65 vs. leftDL:27.08±23.34, p < 0.05) balance scores. In conclusion, bilateral dynamic balance asymmetries may be affected using single leg predominantly in the mobilization workouts. Because of having higher inter-limb asymmetry index, left-dominant leg players may be screened and trained to minimize balance asymmetry.

Keywords: bilateral balance, asymmetries, dominant leg, leg preference

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Authors: Seyedehfatemeh Golrizgashti, Seyedali Dalil

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The goal of this paper is proposing a supply chain value dashboard in home appliance manufacturing firms to create more value for all stakeholders via balanced scorecard approach. Balanced scorecard is an effective approach that managers have used to evaluate supply chain performance in many fields but there is a lack of enough attention to all supply chain stakeholders, improving value creation and, defining correlation between value indicators and performance measuring quantitatively. In this research the key stakeholders in home appliance supply chain, value indicators with respect to create more value for stakeholders and the most important metrics to evaluate supply chain value performance based on balanced scorecard approach have been selected via literature review. The most important indicators based on expert’s judgment acquired by in survey focused on creating more value for. Structural equation modelling has been used to disclose relations between value indicators and balanced scorecard metrics. The important result of this research is identifying effective value dashboard to create more value for all stakeholders in the supply chain via balanced scorecard approach and based on an empirical study covering ten home appliance manufacturing firms in Iran. Home appliance manufacturing firms can increase their stakeholder's satisfaction by using this value dashboard.

Keywords: supply chain management, balanced scorecard, value, structural modeling, stakeholders

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Authors: N. D'Amico, E. Grossi, B. Colombo, F. Rigiroli, M. Buscema, D. Fazzini, G. Cornalba, S. Papa

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Purpose: To characterize, through a radiomic approach, the nature of nodules considered non-specific by expert radiologists, recognized in magnetic resonance mammography (MRm) with T1-weighted (T1w) sequences with paramagnetic contrast. Material and Methods: 47 cases out of 1200 undergoing MRm, in which the MRm assessment gave uncertain classification (non-specific nodules), were admitted to the study. The clinical outcome of the non-specific nodules was later found through follow-up or further exams (biopsy), finding 35 benign and 12 malignant. All MR Images were acquired at 1.5T, a first basal T1w sequence and then four T1w acquisitions after the paramagnetic contrast injection. After a manual segmentation of the lesions, done by a radiologist, and the extraction of 150 radiomic features (30 features per 5 subsequent times) a machine learning (ML) approach was used. An evolutionary algorithm (TWIST system based on KNN algorithm) was used to subdivide the dataset into training and validation test and to select features yielding the maximal amount of information. After this pre-processing, different machine learning systems were applied to develop a predictive model based on a training-testing crossover procedure. 10 cases with a benign nodule (follow-up older than 5 years) and 18 with an evident malignant tumor (clear malignant histological exam) were added to the dataset in order to allow the ML system to better learn from data. Results: NaiveBayes algorithm working on 79 features selected by a TWIST system, resulted to be the best performing ML system with a sensitivity of 96% and a specificity of 78% and a global accuracy of 87% (average values of two training-testing procedures ab-ba). The results showed that in the subset of 47 non-specific nodules, the algorithm predicted the outcome of 45 nodules which an expert radiologist could not identify. Conclusion: In this pilot study we identified a radiomic approach allowing ML systems to perform well in the diagnosis of a non-specific nodule at MR mammography. This algorithm could be a great support for the early diagnosis of malignant breast tumor, in the event the radiologist is not able to identify the kind of lesion and reduces the necessity for long follow-up. Clinical Relevance: This machine learning algorithm could be essential to support the radiologist in early diagnosis of non-specific nodules, in order to avoid strenuous follow-up and painful biopsy for the patient.

Keywords: breast, machine learning, MRI, radiomics

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Authors: Pooja Kherudkar, Namdeo Hedaoo

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There are various causes for asphalt pavement distresses which can develop prematurely or with aging in services. These causes are not limited to aging of bitumen binder but include poor quality materials and construction, inadequate mix design, inadequate pavement structure design considering the traffic and lack of preventive maintenance. There is physical evidence available for each type of pavement distress. Distress in asphalt pavements can be categorized in different distress modes like fracture (cracking and spalling), distortion (permanent deformation and slippage), and disintegration (raveling and potholes). This study shows the importance of severity determination of distresses for the selection of appropriate preventive maintenance treatment. Distress analysis of the deteriorated roads was carried out. Four roads of urban flexible pavements from Pune city was selected as a case study. The roads were surveyed to detect the types, to measure the severity and extent of the distresses. Causes of distresses were investigated. The pavement condition rating values of the roads were calculated. These ranges of ratings were as follows; 1 for poor condition road, 1.1 to 2 for fair condition road and 2.1 to 3 for good condition road. Out of the four roads, two roads were found to be in fair condition and the other two were found in good condition. From the various preventive maintenance treatments like crack seal, fog seal, slurry seal, microsurfacing, surface dressing and thin hot mix/cold mix bituminous overlays, the effective maintenance treatments with respect to the surface condition and severity levels of the existing pavement were recommended.

Keywords: distress analysis, pavement condition rating, preventive maintenance treatments, surface distress measurement

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Authors: Guldana Zhigerbayeva, Ming Yang

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Transportation of hazardous materials (HAZMAT) is inevitable in the process industries. The statistics show a significant number of accidents has occurred during the transportation of HAZMAT. This makes risk management of HAZMAT transportation an important topic. The tree-based methods including fault-trees, event-trees and cause-consequence analysis, and Bayesian network, have been applied to risk management of HAZMAT transportation. However, there is limited work on the development of a systematic approach. The existing approaches fail to build up the linkages between the regulatory requirements and the safety measures development. The analysis of historical data from the past accidents’ report databases would limit our focus on the specific incidents and their specific causes. Thus, we may overlook some essential elements in risk management, including regulatory compliance, field expert opinions, and suggestions. A systematic approach is needed to translate the regulatory requirements of HAZMAT transportation into specified safety measures (both technical and administrative) to support the risk management process. This study aims to first adapt the House of Quality (HoQ) to House of Safety (HoS) and proposes a new approach- Safety Function Deployment (SFD). The results of SFD will be used in a multi-criteria decision-support system to develop find an optimal route for HazMats transportation. The proposed approach will be demonstrated through a hypothetical transportation case in Kazakhstan.

Keywords: hazardous materials, risk assessment, risk management, quality function deployment

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Authors: Mohammad Mahdi Hajiali

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Many of construction projects estimated in Iran have been influenced by the limitations of financial resources. As for Iran, a country that is developing, and to follow this development-oriented approach which many numbers of projects each year run in, if we can reduce the cost of projects by applying a method we will help greatly to minimize the cost of major construction projects and therefore projects will finish faster and more efficiently. One of the components of transportation infrastructure are roads that are considered to have a considerable share of the country budget. In addition, major budget of the related ministry is spending to repair, improve and maintain roads. Value Engineering is a simple and powerful methodology over the past six decades that has been successful in reducing the cost of many projects. Specific solution for using value engineering in the stage of project implementation is called value engineering change proposal (VECP). It was tried in this research to apply VECP in one of the road-building projects in Iran in order to enhance the value of this kind of projects and reduce their cost. In this case study after applying VECP, an idea was raised. It was about use of concrete pavement instead of hot mixed asphalt (HMA) and also using fiber in order to improve concrete pavement performance. VE group team made a decision that for choosing the best alternatives, get expert’s opinions in pavement systems and use Fuzzy TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) for ranking opinions of the experts. Finally, Jointed Plain Concrete Pavement (JPCP) was selected. Group also experimented concrete samples with available fibers in Iran and the results of experiments showed a significant increment in concrete specifications such as flexural strength. In the end, it was shown that by using of fiber-reinforced concrete pavement instead of asphalt pavement, we can achieve a significant saving in cost, time and also increment in quality, durability, and longevity.

Keywords: road-building projects, value engineering change proposal (VECP), Jointed Plain Concrete Pavement (JPCP), Fuzzy TOPSIS, fiber-reinforced concrete

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Authors: Masoumeh Mofarrah, Amir NahanMoghadam

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Higher oil prices and increasing oil demand are main reasons for great attention to Enhanced Oil Recovery (EOR). Comprehensive researches have been accomplished to develop, appraise, and improve EOR methods and their application. Recently, Artificial Intelligence (AI) gained popularity in petroleum industry that can help petroleum engineers to solve some fundamental petroleum engineering problems such as reservoir simulation, EOR project risk analysis, well log interpretation and well test model selection. This study presents a historical overview of most popular AI tools including neural networks, genetic algorithms, fuzzy logic, and expert systems in petroleum industry and discusses two case studies to represent the application of two mentioned AI methods for selecting an appropriate EOR method based on reservoir characterization infeasible and effective way.

Keywords: artificial intelligence, EOR, neural networks, expert systems

Procedia PDF Downloads 462