Search results for: classification quality

Authors: Seyedeh Mandan Kazzazi, Elena Kranioti

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In the field of human osteology, sex estimation is an important step in developing biological profile. There are a number of methods that can be used to estimate the sex of human remains varying from visual assessments to metric analysis of sexually dimorphic traits. Teeth are one of the most durable physical elements in human body that can be used for this purpose. The present study investigated the utility of cervical measurements for sex estimation through discriminant analysis. The permanent molar teeth of 75 skeletons (28 females and 52 males) from Hasanlu site in North-western Iran were studied. Cervical mesiodistal and buccolingual measurements were taken from both maxillary and mandibular first and second molars. Discriminant analysis was used to evaluate the accuracy of each diameter in assessing sex. The results showed that males had statistically larger teeth than females for maxillary and mandibular molars and both measurements (P < 0.05). The range of classification rate was from (75.7% to 85.5%) for the original and cross-validated data. The most dimorphic teeth were maxillary and mandibular second molars providing 85.5% and 83.3% correct classification rate respectively. The data generated from the present study suggested that cervical mesiodistal and buccolingual measurements of the molar teeth can be useful and reliable for sex estimation in Iranian archaeological populations.

Keywords: cervical measurements, Hasanlu, premolars, sex estimation

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Authors: Jordan Chamarande, Lisiane Cunat, Corentine Alauzet, Catherine Cailliez-Grimal

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Gut microbiota (GM) is now considered a new organ mainly due to the microorganism’s specific biochemical interaction with its host. Although mechanisms underlying host-microbiota interactions are not fully described, it is now well-defined that cell surface molecules and structures of the GM play a key role in such relation. The study of surface structures of GM members is also fundamental for their role in the establishment of species in the versatile and competitive environment of the digestive tract and as a potential virulence factor. Among these structures are capsular polysaccharides (CPS), fimbriae, pili and lipopolysaccharides (LPS), all well-described for their central role in microorganism colonization and communication with host epithelium. The health-promoting Parabacteroides distasonis, which is part of the core microbiome, has recently received a lot of attention, showing beneficial properties for its host and as a new potential biotherapeutic product. However, to the best of the authors’ knowledge, the cell surface molecules and structures of P. distasonis that allow its maintain within the GM are not identified. Moreover, although P. distasonis is strongly recognized as intestinal commensal species with benefits for its host, it has also been recognized as an opportunistic pathogen. In this study, we reported gene clusters potentially involved in the synthesis of the capsule, fimbriae-like and pili-like cell surface structures in 26 P. distasonis genomes and applied the new RfbA-Typing classification in order to better understand and characterize the beneficial/pathogenic behaviour related to P. distasonis strains. In context, 2 different types of fimbriae, 3 of pilus and up to 14 capsular polysaccharide loci, have been identified over the 26 genomes studied. Moreover, the addition of data to the rfbA-Type classification modified the outcome by rearranging rfbA genes and adding a fifth group to the classification. In conclusion, the strain variability in terms of external proteinaceous structure could explain the inter-strain differences previously observed in P. distasonis adhesion capacities and its potential pathogenicity.

Keywords: gut microbiota, Parabacteroides distasonis, capsular polysaccharide, fimbriae, pilus, O-antigen, pathogenicity, probiotic, comparative genomics

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Authors: Zbigniew Olczykowski

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The paper presents the impact of work on the electric arc furnace power grid. The arc furnace operating will be modeled at different power conditions of steelworks. The paper will describe how to determine the increase in voltage fluctuations caused by working in parallel arc furnaces. The analysis of indicators characterizing the quality of electricity recorded during several cycles of measurement made at the same time at three points grid, with different power and different short-circuit rated voltage, will be carried out. The measurements analysis presented in this paper were conducted in the mains of one of the Polish steel. The indicators characterizing the quality of electricity was recorded during several cycles of measurement while making measurements at three points of different power network short-circuit power and various voltage ratings. Measurements of power quality indices included the one-week measurement cycles in accordance with the EN-50160. Data analysis will include the results obtained during the simultaneous measurement of three-point grid. This will determine the actual propagation of interference generated by the device. Based on the model studies and measurements of quality indices of electricity we will establish the effect of a specific arc on the mains. The short-circuit power network’s minimum value will also be estimated, this is necessary to limit the voltage fluctuations generated by arc furnaces.

Keywords: arc furnaces, long-term flicker, measurement and modeling of power quality, voltage fluctuations

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Authors: Sonia Mannan, M. Jobair Alam

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The concept of palliative care in Bangladesh largely remained limited to the sympathetic caring of patients with a life-limiting illness. Quality of Life (QoL) issues are rarely practiced in Bangladesh. Furthermore, palliative medicine, in the perspective of holistic palliative care service, does not have its proper recognition in Bangladesh. Apart from those socio-medical aspects, palliative care patients face legal issues that impact their quality of life, including access to health services and social benefits and dealing with other life-transactions of the patients and their families (such as disposing of property; planning for children). This paper is an attempt to articulate these legal dimensions of the right to palliative care in the context of Bangladesh. The major focus of this paper will be founded on the doctrinal analysis of the constitutional provisions and other relevant legislation on the right to health and their judicial interpretation, which is argued to offer a meaningful space for the right to palliative care. This paper will also investigate the gaps in the said legal framework to better secure such care. In conclusion, a few recommendations are made so that the palliative care practices in Bangladesh are better aligned with international standards, and it can respond more humanely to the patients who need palliative care.

Keywords: Bangladesh, constitution, legal regime, palliative care, quality of life

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Authors: Tewelde Gebreslassie Gebreanenia, Frie Ayalew Yimam, Seada Hussen Adem

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Patient safety and quality of care are essential goals of health care delivery, but they are often compromised by human errors, system failures, or resource constraints. In a variety of healthcare contexts, artificial intelligence (AI), a quickly developing field, can provide fresh approaches to enhancing patient safety and treatment quality. Artificial Intelligence (AI) has the potential to decrease errors and enhance patient outcomes by carrying out tasks that would typically require human intelligence. These tasks include the detection and prevention of adverse events, monitoring and warning patients and clinicians about changes in vital signs, symptoms, or risks, offering individualized and evidence-based recommendations for diagnosis, treatment, or prevention, and assessing and enhancing the effectiveness of health care systems and services. This study examines the state-of-the-art and potential future applications of AI-based technologies for enhancing patient safety and care quality, as well as the opportunities and problems they present for patients, policymakers, researchers, and healthcare providers. In order to ensure the safe, efficient, and responsible application of AI in healthcare, the paper also addresses the ethical, legal, social, and technical challenges that must be addressed and regulated.

Keywords: artificial intelligence, health care, human intelligence, patient safty, quality of care

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Authors: Aniket Alam, Sravya Gurram

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This paper proposes a categorization of sport that is based on the system of rules that a sport must adhere to. We focus on these systems of rules to examine how a winner is produced in different sports. The rules of a sport dictate the game play and the direction it takes. We propose to break down the game play into events. At this junction, we observe two kinds of events that constitute the game play of a sport –ones that follow sequential logic and ones that do not. Our focus is pertained to sports that are comprised of sequential events. To examine these events further, to understand how a winner emerges, we take the help of finite-state automaton from the theory of computation (Automata theory). We showcase how sequential sports are eligible to be represented as finite state machines. We depict these finite state machines as state diagrams. We examine these state diagrams to observe how a team/player reaches the final states of the sport, with a special focus on one final state –the final state which determines the winner. This exercise has been carried out for the following sports: Hurdles, Track, Shot Put, Long Jump, Bowling, Badminton, Pacman and Weightlifting (Snatch). Based on our observations of how this final state of winning is achieved, we propose a categorization of sports.

Keywords: sport classification, sport modelling, ontology, automata theory

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Authors: Kritiyaporn Kunsook

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Machine learning algorithms (MLAs) such us artificial neural networks (ANNs), decision tree, support vector machines (SVMs), Naïve Bayes, and ensemble classifier by voting are powerful data driven methods that are relatively less widely used in the mapping of technique of system, and thus have not been comparatively evaluated together thoroughly in this field. The performances of a series of MLAs, ANNs, decision tree, SVMs, Naïve Bayes, and ensemble classifier by voting in technique of hydroponic systems prospectively modeling are compared based on the accuracy of each model. Classification of hydroponic systems only covers the test samples from vegetables grown with Nutrient film technique (NFT) and Deep flow technique (DFT). The feature, which are the characteristics of vegetables compose harvesting height width, temperature, require light and color. The results indicate that the classification performance of the ANNs is 98%, decision tree is 98%, SVMs is 97.33%, Naïve Bayes is 96.67%, and ensemble classifier by voting is 98.96% algorithm respectively.

Keywords: artificial neural networks, decision tree, support vector machines, naïve Bayes, ensemble classifier by voting

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Authors: Katerina Koliou, Scott Parr, Evangelos Kaisar

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The surface transportation of freight is particularly vulnerable to storm and hurricane disasters, while at the same time, it is the primary transportation mode for delivering medical supplies, fuel, water, and other essential goods. To better plan for commercial vehicles during an evacuation, it is necessary to understand how these vehicles travel during an evacuation and determine if this travel is different from the general public. The research investigation used Florida's statewide continuous-count station traffic volumes, where then compared between years, to identify locations where traffic was moving differently during the evacuation. The data was then used to identify days on which traffic was significantly different between years. While the literature on auto-based evacuations is extensive, the consideration of freight travel is lacking. To better plan for commercial vehicles during an evacuation, it is necessary to understand how these vehicles travel during an evacuation and determine if this travel is different from the general public. The goal of this research was to investigate the movement of vehicles by classification, with an emphasis on freight during two major evacuation events: hurricanes Irma (2017) and Michael (2018). The methodology of the research was divided into three phases: data collection and management, spatial analysis, and temporal comparisons. Data collection and management obtained continuous-co station data from the state of Florida for both 2017 and 2018 by vehicle classification. The data was then processed into a manageable format. The second phase used geographic information systems (GIS) to display where and when traffic varied across the state. The third and final phase was a quantitative investigation into which vehicle classifications were statistically different and on which dates statewide. This phase used a two-sample, two-tailed t-test to compare sensor volume by classification on similar days between years. Overall, increases in freight movement between years prevented a more precise paired analysis. This research sought to identify where and when different classes of vehicles were traveling leading up to hurricane landfall and post-storm reentry. Of the more significant findings, the research results showed that commercial-use vehicles may have underutilized rest areas during the evacuation, or perhaps these rest areas were closed. This may suggest that truckers are driving longer distances and possibly longer hours before hurricanes. Another significant finding of this research was that changes in traffic patterns for commercial-use vehicles occurred earlier and lasted longer than changes for personal-use vehicles. This finding suggests that commercial vehicles are perhaps evacuating in a fashion different from personal use vehicles. This paper may serve as the foundation for future research into commercial travel during evacuations and explore additional factors that may influence freight movements during evacuations.

Keywords: evacuation, freight, travel time, evacuation

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Authors: Marcus C. Garcia, Giselle C. Guimarães, Luciana H. Yamane, Renato R. Siman

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The environmental indicators and the classification of beach waste are essential tools to diagnose the current situation and to indicate ways to improve the quality of this environment. The purpose of this paper was to perform a quali-quantitative analysis of the beach waste on the Curva da Jurema Beach (Espírito Santo - Brazil). Three transects were used with equidistant positioning over the total length of the beach for the solid waste collection. Solid wastes were later classified according to their use and primary raw material from the low and high summer season. During the low season, average values of 7.10 items.m^-1, 18.22 g.m^-1 and 0.91 g.m^-2 were found for the whole beach, and transect 3 contributed the most waste, with the total sum of items equal to 999 (49%), a total mass of 5.62 kg and a total volume of 21.31 L. During the high summer season, average values of 8.22 items.m^-1, 54.40 g.m^-1 and 2.72 g.m^-2 were found, with transect 2 contributing the most to the total sum with 1,212 items (53%), a total mass of 10.76 kg and a total volume of 51.99 L. Of the total collected, plastic materials represented 51.4% of the total number of items, 35.9% of the total mass and 68% of the total volume. The implementation of reactive and proactive measures is necessary so that the management of the solid wastes on Curva da Jurema Beach is in accordance with principles of sustainability.

Keywords: beach solid waste, environmental indicators, quali-quantitative analysis, waste management

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Authors: Adebola Ajayi, Olakunle M. Makanjuola

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The effects of particle sizes of maize flour on the quality of traditional maize snack (Kokoro) were investigated. Maize flour of different sieve mesh sizes of 1.00mm, 1.9 mm, 1.4 mm, 1.68 mm and 2.0 mm was used to produce Kokoro. The samples were analysed for protein, fat, moisture content, crude fibre, ash and sensory evaluation. The various mixture obtained were separately processed into snacks following essential traditional method of production. The result of the sensory evaluation showed that Kokoro of sample 546 using 1.0mm mesh sieve size was the most preferred and sample 513 using 2.00 was least preferred. The result revealed that the more the maize was well blended the more acceptable the product is to the consumer.

Keywords: particle sizes, maize flour, quality, Kokoro

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Authors: Suleiman Hassan Otuoze, Dexter Vernon Lloyd Hunt, Ian Jefferson

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Urbanization has continued to widen the gap between demand and resources available to provide resilient and sustainable transport services in many fast-growing developing countries' cities. Transport demand management is a decision-based optimization concept for both benchmarking and ensuring efficient use of transport resources. This study assesses the service quality of infrastructure and mobility services in the Nigerian cities of Kano and Lagos through five dimensions of quality (i.e., Tangibility, Reliability, Responsibility, Safety Assurance and Empathy). The methodology adopts a hybrid AHP-SERVQUAL model applied on questionnaire surveys to gauge the quality of satisfaction and the views of experts in the field. The AHP results prioritize tangibility, which defines the state of transportation infrastructure and services in terms of satisfaction qualities and intervention decision weights in the two cities. The results recorded ‘unsatisfactory’ indices of quality of performance and satisfaction rating values of 48% and 49% for Kano and Lagos, respectively. The satisfaction indices are identified as indicators of low performances of transportation demand management (TDM) measures and the necessity to re-order priorities and take proactive steps towards infrastructure. The findings pilot a framework for comparative assessment of recognizable standards in transport services, best ethics of management and a necessity of quality infrastructure to guarantee both resilient and sustainable urban mobility.

Keywords: transportation demand management, multi-criteria decision support, transport infrastructure, service quality, sustainable transport

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Authors: Mona K. Fehling, Jakob Unger, Dietmar J. Hecker, Bernhard Schick, Joerg Lohscheller

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Voice disorders origin from disturbances of the vibration patterns of the two vocal folds located within the human larynx. Consequently, the visual examination of vocal fold vibrations is an integral part within the clinical diagnostic process. For an objective analysis of the vocal fold vibration patterns, the two-dimensional vocal fold dynamics are captured during sustained phonation using an endoscopic high-speed camera. In this work, we present an approach allowing a fully automatic analysis of the high-speed video data including a computerized classification of healthy and pathological voices. The approach bases on a wavelet-based analysis of so-called phonovibrograms (PVG), which are extracted from the high-speed videos and comprise the entire two-dimensional vibration pattern of each vocal fold individually. Using a principal component analysis (PCA) strategy a low-dimensional feature set is computed from each phonovibrogram. From the PCA-space clinically relevant measures can be derived that quantify objectively vibration abnormalities. In the first part of the work it will be shown that, using a machine learning approach, the derived measures are suitable to distinguish automatically between healthy and pathological voices. Within the approach the formation of the PCA-space and consequently the extracted quantitative measures depend on the clinical data, which were used to compute the principle components. Therefore, in the second part of the work we proposed a strategy to achieve a normalization of the PCA-space by registering the PCA-space to a coordinate system using a set of synthetically generated vibration patterns. The results show that owing to the normalization step potential ambiguousness of the parameter space can be eliminated. The normalization further allows a direct comparison of research results, which bases on PCA-spaces obtained from different clinical subjects.

Keywords: Wavelet-based analysis, Multiscale product, normalization, computer assisted classification, high-speed laryngoscopy, vocal fold analysis, phonovibrogram

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Authors: Carmen E. Zapata, José F. Jiménez, Mauricio Ramiréz, Natalia A. Cano

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The majority of the urban areas in Latin America face the challenges associated with city planning and development problems, attributed to human, technical, and economical factors; therefore, we cannot ignore the issues related to climate change because the city modifies the natural landscape in a significant way transforming the radiation balance and heat content in the urbanized areas. These modifications provoke changes in the temperature distribution known as “the heat island effect”. According to this phenomenon, we have the need to conceive the urban planning based on climatological patterns that will assure its sustainable functioning, including the particularities of the climate variability. In the present study, it is identified the Local Climate Zones (LCZ) in the Metropolitan Area of the Aburrá Valley (Colombia) with the objective of relocate the air quality monitoring stations as a partial solution to the problem of how to measure representative air quality levels in a city for a local scale, but with instruments that measure in the microscale.

Keywords: air quality, monitoring, local climatic zones, valley, monitoring stations

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Authors: Patrizia Bonaventura, Magda Di Renzo

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This project aims to measure and assess the voice quality in children with autism. Few previous studies exist which have analyzed the voice quality of individuals with autism: abnormal voice characteristics have been found, like a high pitch, great pitch range, and sing-song quality. Existing studies did not focus specifically on Italian-speaking children’s voices and provided analysis of a few acoustic parameters. The present study aimed to gather more data and to perform acoustic analysis of the voice of children with autism in order to identify patterns of abnormal voice features that might shed some light on the causes of the dysphonia and possibly be used to create a pediatric assessment tool for early identification of autism. The participants were five native Italian-speaking boys with autism between the age of 4 years and 10 years (mean 6.8 ± SD 1.4). The children had a diagnosis of autism, were verbal, and had no other comorbid conditions (like Down syndrome or ADHD). The voices of the autistic children were recorded in the production of sustained vowels [ah] and [ih] and of sentences from the Italian version of the CAPE-V voice assessment test. The following voice parameters, representative of normal quality, were analyzed by acoustic spectrography through Praat: Speaking Fundamental Frequency, F0 range, average intensity, and dynamic range. The results showed that the pitch parameters (Speaking Fundamental Frequency and F0 range), as well as the intensity parameters (average intensity and dynamic range), were significantly different from the relative normal reference thresholds. Also, variability among children was found, so confirming a tendency revealed in previous studies of individual variation in these aspects of voice quality. The results indicate a general pattern of abnormal voice quality characterized by a high pitch and large variations in pitch and intensity. These acoustic voice characteristics found in Italian-speaking autistic children match those found in children speaking other languages, indicating that autism symptoms affecting voice quality might be independent of the native language of the children.

Keywords: autism, voice disorders, speech science, acoustic analysis of voice

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Authors: Rahil Bahrami, Kaveh Ashenayi

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This paper presents a systematic classification and comparative analysis of non-isolated bi-directional DC-DC converters. The increasing demand for efficient energy conversion in diverse applications has spurred the development of various converter topologies. In this study, we categorize bi-directional converters into three distinct classes: Inverting, Non-Inverting, and Interleaved. Each category is characterized by its unique operational characteristics and benefits. Furthermore, a practical comparison is conducted by evaluating the results of simulation of each bi-directional converter. BDCs can be classified into isolated and non-isolated topologies. Non-isolated converters share a common ground between input and output, making them suitable for applications with minimal voltage change. They are easy to integrate, lightweight, and cost-effective but have limitations like limited voltage gain, switching losses, and no protection against high voltages. Isolated converters use transformers to separate input and output, offering safety benefits, high voltage gain, and noise reduction. They are larger and more costly but are essential for automotive designs where safety is crucial. The paper focuses on non-isolated systems.The paper discusses the classification of non-isolated bidirectional converters based on several criteria. Common factors used for classification include topology, voltage conversion, control strategy, power capacity, voltage range, and application. These factors serve as a foundation for categorizing converters, although the specific scheme might vary depending on contextual, application, or system-specific requirements. The paper presents a three-category classification for non-isolated bi-directional DC-DC converters: inverting, non-inverting, and interleaved. In the inverting category, converters produce an output voltage with reversed polarity compared to the input voltage, achieved through specific circuit configurations and control strategies. This is valuable in applications such as motor control and grid-tied solar systems. The non-inverting category consists of converters maintaining the same voltage polarity, useful in scenarios like battery equalization. Lastly, the interleaved category employs parallel converter stages to enhance power delivery and reduce current ripple. This classification framework enhances comprehension and analysis of non-isolated bi-directional DC-DC converters. The findings contribute to a deeper understanding of the trade-offs and merits associated with different converter types. As a result, this work aids researchers, practitioners, and engineers in selecting appropriate bi-directional converter solutions for specific energy conversion requirements. The proposed classification framework and experimental assessment collectively enhance the comprehension of non-isolated bi-directional DC-DC converters, fostering advancements in efficient power management and utilization.The simulation process involves the utilization of PSIM to model and simulate non-isolated bi-directional converter from both inverted and non-inverted category. The aim is to conduct a comprehensive comparative analysis of these converters, considering key performance indicators such as rise time, efficiency, ripple factor, and maximum error. This systematic evaluation provides valuable insights into the dynamic response, energy efficiency, output stability, and overall precision of the converters. The results of this comparison facilitate informed decision-making and potential optimizations, ensuring that the chosen converter configuration aligns effectively with the designated operational criteria and performance goals.

Keywords: bi-directional, DC-DC converter, non-isolated, energy conversion

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Authors: Qingxin Chen, Liben Jiang, Andrew Smith, Karim Hadjri

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Since 2007, the Chinese food industry has undergone serious food contamination in the baby dairy industry, especially milk powder contamination. One of the milk powder products was found to contain melamine and a significant number (294,000) of babies were affected by kidney stones. Due to growing concerns among consumers about food safety and protection, and high pressure from central government, companies must take radical action to ensure food quality protection through the use of an appropriate quality management system. Previously, though researchers have investigated the health and safety aspects of food industries and products, quality issues concerning food products in China have been largely over-looked. Issues associated with baby dairy products and their quality issues have not been discussed in depth. This paper investigates the impact of quality management systems on the Chinese baby dairy product industry. A literature review was carried out to analyse the use of quality management systems within the Chinese milk power market. Moreover, quality concepts, relevant standards, laws, regulations and special issues (such as Melamine, Flavacin M1 contamination) have been analysed in detail. A qualitative research approach is employed, whereby preliminary analysis was conducted by interview, and data analysis based on interview responses from four selected Chinese baby dairy product companies was carried out. Through the analysis of literature review and data findings, it has been revealed that for quality management system that has been designed by many practitioners, many theories, models, conceptualisation, and systems are present. These standards and procedures should be followed in order to provide quality products to consumers, but the implementation is lacking in the Chinese baby dairy industry. Quality management systems have been applied by the selected companies but the implementation still needs improvement. For instance, the companies have to take measures to improve their processes and procedures with relevant standards. The government need to make more interventions and take a greater supervisory role in the production process. In general, this research presents implications for the regulatory bodies, Chinese Government and dairy food companies. There are food safety laws prevalent in China but they have not been widely practiced by companies. Regulatory bodies must take a greater role in ensuring compliance with laws and regulations. The Chinese government must also play a special role in urging companies to implement relevant quality control processes. The baby dairy companies not only have to accept the interventions from the regulatory bodies and government, they also need to ensure that production, storage, distribution and other processes will follow the relevant rules and standards.

Keywords: baby dairy product, food quality, milk powder contamination, quality management system

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Authors: Muciz Özcan, Mustafa Sacid Endiz, Veysel Alver

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In this paper we present a new approach to the boom welding related to the mobile cranes manufacturing, implementing a new method in order to get homogeneous welding quality and reduced energy usage during booms production. We aim to get the realization of the same welding quality carried out on the boom in every region during the manufacturing process and to detect the possible welding errors whether they could be eliminated using laser sensors. We determine the position of the welding region directly through our system and with the help of the welding oscillator we are able to perform a proper boom welding. Errors that may occur in the welding process can be observed by monitoring and eliminated by means of an operator. The major modification in the production of the crane booms will be their form of the booms. Although conventionally, more than one welding is required to perform this process, with the suggested concept, only one particular welding is sufficient, which will be more energy and environment-friendly. Consequently, as only one welding is needed for the manufacturing of the boom, the particular welding quality becomes more essential. As a way to satisfy the welding quality, a welding manipulator was made and fabricated. By using this welding manipulator, the risks of involving dangerous gases formed during the welding process for the operator and the surroundings are diminished as much as possible.

Keywords: boom welding, seam tracking, energy saving, global warming

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Authors: Musoke Ivan, Birungi Racheal

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The construction trend is characterized by increased use of modern methods yet traditional methods are cheaper in terms of costs, in addition to the benefits it offers to the construction sector, like providing more jobs that could have been worked with the intensive machines. The purpose of this research was to assess the influence of using Traditional methods of construction (TMC) on the costs and quality of building structures and determine the different ways. Traditional methods of construction (TMC) can be applicable and integrated into the construction trend, and propose ways how this can be a success. The study adopted a quantitative method approach targeting various construction professionals like Architects, Quantity surveyors, Engineers, and Construction Managers. Questionnaires and analyses of literature were used to obtain research data and findings. Simple random sampling was used to select 40 construction professionals to which questionnaires were administered. The data was then analyzed using Microsoft Excel. The findings of the research indicate that Traditional methods of construction (TMCs) in Uganda are cheaper in terms of costs, but the quality is still low. This is attributed to a lack of skilled labour and efficient supervision while undertaking tasks leading to low quality. The study identifies strategies that would improve Traditional methods of construction (TMC), which include the employment of skilled manpower and effective supervision. It also identifies the need by stakeholders like the government, clients, and professionals to appreciate Traditional methods of construction (TMCs) and allow for a levelled ground for Traditional Methods of Construction and Modern methods of construction (MMCs).

Keywords: traditional methods of construction, integration, cost, quality

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Authors: Silvia Portarena, Chiara Anselmi, Chiara Baldacchini, Enrico Brugnoli

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Extra virgin olive oil (EVOO) is a complex matrix mainly composed by fatty acid and other minor compounds, among which carotenoids are well known for their antioxidative function that is a key mechanism of protection against cancer, cardiovascular diseases, and macular degeneration in humans. EVOO composition in terms of such constituents is generally the result of a complex combination of genetic, agronomical and environmental factors. To selectively improve the quality of EVOOs, the role of each factor on its biochemical composition need to be investigated. By selecting fruits from four different cultivars similarly grown and harvested, it was demonstrated that Raman spectroscopy, combined with chemometric analysis, is able to discriminate the different cultivars, also as a function of the harvest date, based on the relative content and composition of fatty acid and carotenoids. In particular, a correct classification up to 94.4% of samples, according to the cultivar and the maturation stage, was obtained. Moreover, by using gas chromatography and high-performance liquid chromatography as reference techniques, the Raman spectral features further allowed to build models, based on partial least squares regression, that were able to predict the relative amount of the main fatty acids and the main carotenoids in EVOO, with high coefficients of determination. Besides genetic factors, climatic parameters, such as light exposition, distance from the sea, temperature, and amount of precipitations could have a strong influence on EVOO composition of both major and minor compounds. This suggests that the Raman spectra could act as a specific fingerprint for the geographical discrimination and authentication of EVOO. To understand the influence of environment on EVOO Raman spectra, samples from seven regions along the Italian coasts were selected and analyzed. In particular, it was used a dual approach combining Raman spectroscopy and isotope ratio mass spectrometry (IRMS) with principal component and linear discriminant analysis. A correct classification of 82% EVOO based on their regional geographical origin was obtained. Raman spectra were obtained by Super Labram spectrometer equipped with an Argon laser (514.5 nm wavelenght). Analyses of stable isotope content ratio were performed using an isotope ratio mass spectrometer connected to an elemental analyzer and to a pyrolysis system. These studies demonstrate that RR spectroscopy is a valuable and useful technique for the analysis of EVOO. In combination with statistical analysis, it makes possible the assessment of specific samples’ content and allows for classifying oils according to their geographical and varietal origin.

Keywords: authentication, chemometrics, olive oil, raman spectroscopy

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Authors: Olivia Borgue, Massimo Panarotto, Ola Isaksson

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This article presents a neural networks-based strategy for reducing the need for support structures when designing for additive manufacturing (AM). Additive manufacturing is a relatively new and immature industrial technology, and the information to make confident decisions when designing for AM is limited. This lack of information impacts especially the early stages of engineering design, for instance, it is difficult to actively consider the support structures needed for manufacturing a part. This difficulty is related to the challenge of designing a product geometry accounting for customer requirements, manufacturing constraints and minimization of support structure. The approach presented in this article proposes an automatized geometry modification technique for reducing the use of the support structures while designing for AM. This strategy starts with a neural network-based strategy for shape recognition to achieve product classification, using an STL file of the product as input. Based on the classification, an automatic part geometry modification based on MATLAB© is implemented. At the end of the process, the strategy presents different geometry modification alternatives depending on the type of product to be designed. The geometry alternatives are then evaluated adopting a QFD-like decision support tool.

Keywords: additive manufacturing, engineering design, geometry modification optimization, neural networks

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Authors: Jamshed Ahmad, Abdul Wahid Khan, Javed Ali Khan

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Managing software quality requirements change management is a difficult task in the field of software engineering. Avoiding incoming changes result in user dissatisfaction while accommodating to many requirement changes may delay product delivery. Poor requirements management is solely considered the primary cause of the software failure. It becomes more challenging in global software outsourcing. Addressing success factors in quality requirement change management is desired today due to the frequent change requests from the end-users. In this research study, success factors are recognized and scrutinized with the help of a systematic literature review (SLR). In total, 16 success factors were identified, which significantly impacted software quality requirement change management. The findings show that Proper Requirement Change Management, Rapid Delivery, Quality Software Product, Access to Market, Project Management, Skills and Methodologies, Low Cost/Effort Estimation, Clear Plan and Road Map, Agile Processes, Low Labor Cost, User Satisfaction, Communication/Close Coordination, Proper Scheduling and Time Constraints, Frequent Technological Changes, Robust Model, Geographical distribution/Cultural differences are the key factors that influence software quality requirement change. The recognized success factors and validated with the help of various research methods, i.e., case studies, interviews, surveys and experiments. These factors are then scrutinized in continents, database, company size and period of time. Based on these findings, requirement change will be implemented in a better way.

Keywords: global software development, requirement engineering, systematic literature review, success factors

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Authors: Luis F. Bianchessi, Gustavo G. Shimamoto, Matthieu Tubino

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The use of biodiesel has been diffused in Brazil and all over the world by the trading of biodiesel (B100). In Brazil, the diesel oil currently being sold is a blend, containing 7% biodiesel (B7). In this context, it is necessary to develop methods capable of identifying this blend composition, especially regarding the biodiesel quality used for making these blends. In this study, hydrogen nuclear magnetic resonance spectra (1H-NMR) are proposed as a form of identifying and confirming the quality of type B10 blends (10% of biodiesel and 90% of diesel). Furthermore, the presence of vegetable oils, which may be from fuel adulteration or as an evidence of low degree of transesterification conversion during the synthesis of B100, may also be identified. Mixtures of diesel, vegetable oils and their respective biodiesel were prepared. Soybean oil and macauba kernel oil were used as raw material. The diesel proportion remained fixed at 90%. The other proportion (10%) was varied in terms of vegetable oil and biodiesel. The 1H-NMR spectra were obtained for each one of the mixtures, in order to find a correlation between the spectra and the amount of biodiesel, as well as the amount of residual vegetable oil. The ratio of the integral of the methylenic hydrogen H-2 of glycerol (exclusive of vegetable oil) with respect to the integral of the olefinic hydrogens (present in vegetable oil and biodiesel) was obtained. These ratios were correlated with the percentage of vegetable oil in each mixture, from 0% to 10%. The obtained correlation could be described by linear relationships with R2 of 0.9929 for soybean biodiesel and 0.9982 for macauba kernel biodiesel. Preliminary results show that the technique can be used to monitor the biodiesel quality in commercial diesel-biodiesel blends, besides indicating possible adulteration.

Keywords: biodiesel, diesel, biodiesel quality, adulteration

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Authors: Louis Placido F. Lachica

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Freshman year in college, being a transition from high school to college, requires students to adjust by equipping themselves with competencies that will make them survive in college. This study conducted at in a state university in the Philippines aimed to determine the quality of school life and linguistic intelligence of 214 randomly selected college freshmen. Frequency counts and percentages were used to analyze quality of school life and linguistic intelligence. The chi-square test was utilized to determine significant relationship between quality of school life and linguistic intelligence and selected demographic variables. Results on quality of school life revealed that availability of religious books and paperbacks at home were significantly related to relationship with teachers. None of the selected demographic characteristics were significantly related to sense of achievement. Parents’ highest educational attainment was significantly related with opportunity at school. The availability of general references and song hits were significantly and highly significantly related to sense of identity which means that these promoted their sense of identity since their peers also preferred its availability. Type of high school graduated from was significantly related with students’ self-esteem. Graduates of public high schools have higher boosted self-esteem than those from private high schools. Both type of high school graduated from and reading materials available at home (religious books) had a highly significant relationship with linguistic intelligence. In addition, there was a significant relationship between time spent in reading per day and linguistic intelligence. There was a highly significant relationship between quality of school life in terms of relationship with teachers and sense of achievement with linguistic intelligence. Further, sense of identity and linguistic intelligence were significantly related.

Keywords: quality of school life, linguistic intelligence, college freshmen, state university

Procedia PDF Downloads 339

Authors: Dominique Parrish

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Globally, higher education institutions are responsible for the quality assurance and accreditation of their educational programmes (Courses). The primary purpose of these activities is to ensure that the educational standards of the governing higher education authority are met and the quality of the education provided to students is assured. Despite policies and frameworks being established in many countries, to improve the veracity and accountability of quality assurance and accreditation processes, there are reportedly still mistakes, gaps and deficiencies in these processes. An analysis of Australian universities’ quality assurance and accreditation processes noted that significant improvements were needed in managing these processes and ensuring that review recommendations were implemented. It has also been suggested that the following principles are critical for higher education quality assurance and accreditation to be effective and sustainable: academic standards and performance outcomes must be defined, attainable and monitored; those involved in providing the higher education must assume responsibility for the associated quality assurance and accreditation; potential academic risks must be identified and management solutions developed; and the expectations of the public, governments and students should be considered and incorporated into Course enhancements. This phenomenological study, which was conducted in a Faculty of Science, Medicine and Health in an Australian university, sought to systematically and iteratively develop an effective quality assurance and accreditation process that integrated the evidence-based principles of success and promoted meaningful and sustainable change. Qualitative evaluative feedback was gathered, over a period of eleven months (January - November 2014), from faculty staff engaged in the quality assurance and accreditation of forty-eight undergraduate and postgraduate Courses. Reflexive analysis was used to analyse the data and inform ongoing modifications and developments to the assurance and accreditation process as well as the associated supporting resources. The study resulted in the development of a formal quality assurance and accreditation process together with a suite of targeted resources that were identified as critical for success. The research findings also provided some insights into the institutional enablers that were antecedents to successful quality assurance and accreditation processes as well as meaningful change in the educational practices of academics. While longitudinal data will be collected to further assess the value of the assurance and accreditation process on educational quality, early indicators are that there has been a change in the pedagogical perspectives and activities of academic staff and growing momentum to explore opportunities to further enhance and develop Courses. This presentation will explain the formal quality assurance and accreditation process as well as the component parts, which resulted from this study. The targeted resources that were developed will be described, the pertinent factors that contributed to the success of the process will be discussed and early indicators of sustainable academic change as well as suggestions for future research will be outlined.

Keywords: academic standards, quality assurance and accreditation, phenomenological study, process, resources

Procedia PDF Downloads 358

Authors: Nurliani, Ida Rosada

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The national rice consumption keeps increasing along with raising income of the households and the rapid growth of population. However, food availability, particularly rice, is limited. Impacts of rice-field conversion have run cumulatively, as we can see on potential losses of rice and crops production, as well as work opportunity that keeps increasing year-by-year. Therefore, it requires policy recommendation to control rice-field conversion through economic, social, and ecological approaches. The research was a survey method intended to: (1) Identify internal factors; quality and productivity of the land as the cause of land conversion, (2) Identify external factors of land conversion, value of the rice-field and the competitor’s land, workforce absorption, and regulation, as well as (3) Formulate strategies in controlling rice-field conversion. Population of the research was farmers who applied land conversion at Pangkep Regency, South Sulawesi. Samples were determined using the incidental sampling method. Data analysis used productivity analysis, land quality analysis, total economic value analysis, and SWOT analysis. Results of the research showed that the quality of rice-field was low as well as productivity of the grains (unhulled-rice). So that, average productivity of the grains and quality of rice-field were low as well. Total economic value of rice-field was lower than the economic value of the embankment. Workforce absorption value on rice-field was higher than on the embankment. Strategies in controlling such rice-field conversion can be done by increasing rice-field productivity, improving land quality, applying cultivation technique of specific location, improving the irrigation lines, and socializing regulation and sanction about the transfer of land use.

Keywords: land conversion, quality of rice-field, productivity, land economic value.

Procedia PDF Downloads 259

Authors: Aya Salama

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Digital Twin is an emerging research topic that attracted researchers in the last decade. It is used in many fields, such as smart manufacturing and smart healthcare because it saves time and money. It is usually related to other technologies such as Data Mining, Artificial Intelligence, and Machine Learning. However, Human digital twin (HDT), in specific, is still a novel idea that still needs to prove its feasibility. HDT expands the idea of Digital Twin to human beings, which are living beings and different from the inanimate physical entities. The goal of this research was to create a Human digital twin that is responsible for real-time human replies automation by simulating human behavior. For this reason, clustering, supervised classification, topic extraction, and sentiment analysis were studied in this paper. The feasibility of the HDT for personal replies generation on social messaging applications was proved in this work. The overall accuracy of the proposed approach in this paper was 63% which is a very promising result that can open the way for researchers to expand the idea of HDT. This was achieved by using Random Forest for clustering the question data base and matching new questions. K-nearest neighbor was also applied for sentiment analysis.

Keywords: human digital twin, sentiment analysis, topic extraction, supervised machine learning, unsupervised machine learning, classification, clustering

Procedia PDF Downloads 74

Authors: Suresh Palla, Kalpna Sharma, Gaurav Bhatnagar, S. K. Chaturvedi, B. N. Mohapatra

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Determining the content of free lime is especially important to judge reactivity of the raw materials and clinker quality. The free lime limit isn’t the same for all cements; it depends on several factors, especially the temperature reached during the cooking and the grain size distribution in cement after grinding. Estimation of free lime by conventional method is influenced by the presence of portlandite and misleads the actual free lime content in the clinker for quality check up conditions. To ensure the product quality according to the standard specifications in terms of within the quality limits or not, a reliable, precise, and very reproducible method to quantify the relative phase abundances in the Portland Cement clinker and Portland Cements is to use X-ray diffraction (XRD) in combination with the Rietveld method. In the present study, a methodology was proposed using XRD to validate the obtained results of free lime by conventional method. The XRD and TG/DTA results confirm the presence of portlandite in the clinker to take the decision on the obtained free lime results through conventional method.

Keywords: free lime, quantitative phase analysis, conventional method, x ray diffraction

Procedia PDF Downloads 117

Authors: Hannah Patricia S., Louise Margarrette R., Josking Oliver L., Denisse Katrina C., Justine Kali O.

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Aims: In the Philippines, there has been an astronomical increase in the population of elderly sent to nursing home facilities which has been studied to induce despair and loss of self-worth. Nurses in institutionalized facilities generally care for the elderly. Although supportive group therapy has been explored to mend this psychological disparity, nursing research has limited published studies about this in the institutionalized setting. Hence, the study determined the effectiveness of supportive group therapy in depression, self-esteem and quality of life among institutionalized elderly. Methodology: A one-group pre-test-post-test design was conducted among 20-purposively selected institutionalized elderly after the Ethics Research Board approval. All eligible participants underwent the supportive group therapy after being subdivided into session groups. The Geriatric Depression Scale, which has a Cronbach’s alpha coefficient of 0.90; the Rosenberg Self-Esteem, which has a Cronbach’s alpha coefficient = 0.84; and the Older People Quality of Life, which has a Cronbach’s alpha coefficient =0.88, were utilized to measure depression, self-esteem, and quality of life, respectively. Descriptive statistics and Repeated Measures-Multivariate Analysis of Variance (RM-MANOVA) analyzed gathered data. Results: Results showed that the supportive group therapy significantly decreased post-test depression scores (F(1,19)=78.69,p=0.0001,partial η2=0.805), significantly improved post-test self-esteem score (F(1,19)=28.07,p=0.0001,partial η2=0.596), and significantly increased the post-test quality of life (F(1,19)=79.73,p=0.0001,partial η2=0.808) after the intervention has been rendered. Conclusion: Supportive group therapy is effective in alleviating depression and in improving self-esteem and quality of life among institutionalized elderly and can be utilized by nursing homes as an intervention to improve the over-all psychosocial status of elderly patients.

Keywords: supportive group therapy, institutionalized elderly, depression, self-esteem, quality of life

Procedia PDF Downloads 408

Authors: George Hanna Abdelmelek Henien

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Quality and safety issues are common in Ethiopia's food processing industry, which can negatively impact consumers' health and livelihoods. The country is known for its various agricultural products that are important to the economy. However, food quality and safety policies and management practices in the food processing industry have led to many health problems, foodborne illnesses and economic losses. This article aims to show the causes and consequences of food safety and quality problems in the food processing industry in Ethiopia and discuss possible solutions to solve them. One of the main reasons for food quality and safety in Ethiopia's food processing industry is the lack of adequate regulation and enforcement mechanisms. Inadequate food safety and quality policies have led to inefficiencies in food production. Additionally, the failure to monitor and enforce existing regulations has created a good opportunity for unscrupulous companies to engage in harmful practices that endanger the lives of citizens. The impact on food quality and safety is significant due to loss of life, high medical costs, and loss of consumer confidence in the food processing industry. Foodborne diseases such as diarrhoea, typhoid and cholera are common in Ethiopia, and food quality and safety play an important role in . Additionally, food recalls due to contamination or contamination often cause significant economic losses in the food processing industry. To solve these problems, the Ethiopian government began taking measures to improve food quality and safety in the food processing industry. One of the most prominent initiatives is the Ethiopian Food and Drug Administration (EFDA), which was established in 2010 to monitor and control the quality and safety of food and beverage products in the country. EFDA has implemented many measures to improve food safety, such as carrying out routine inspections, monitoring the import of food products and implementing labeling requirements. Another solution that can improve food quality and safety in the food processing industry in Ethiopia is the implementation of food safety management system (FSMS). FSMS is a set of procedures and policies designed to identify, assess and control food safety risks during food processing. Implementing a FSMS can help companies in the food processing industry identify and address potential risks before they harm consumers. Additionally, implementing an FSMS can help companies comply with current safety and security regulations. Consequently, improving food safety policy and management system in Ethiopia's food processing industry is important to protect people's health and improve the country's economy. . Addressing the root causes of food quality and safety and implementing practical solutions that can help improve the overall food safety and quality in the country, such as establishing regulatory bodies and implementing food management systems.

Keywords: food quality, food safety, policy, management system, food processing industry food traceability, industry 4.0, internet of things, block chain, best worst method, marcos

Procedia PDF Downloads 27

Authors: Adrian-Gabriel Chifu, Sebastien Fournier

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One of the challenges of natural language understanding is to deal with the subjectivity of sentences, which may express opinions and emotions that add layers of complexity and nuance. Sentiment analysis is a field that aims to extract and analyze these subjective elements from text, and it can be applied at different levels of granularity, such as document, paragraph, sentence, or aspect. Aspect-based sentiment analysis is a well-studied topic with many available data sets and models. However, there is no clear definition of what makes a sentence difficult for aspect-based sentiment analysis. In this paper, we explore this question by conducting an experiment with three data sets: ”Laptops”, ”Restaurants”, and ”MTSC” (Multi-Target-dependent Sentiment Classification), and a merged version of these three datasets. We study the impact of domain diversity and syntactic diversity on difficulty. We use a combination of classifiers to identify the most difficult sentences and analyze their characteristics. We employ two ways of defining sentence difficulty. The first one is binary and labels a sentence as difficult if the classifiers fail to correctly predict the sentiment polarity. The second one is a six-level scale based on how many of the top five best-performing classifiers can correctly predict the sentiment polarity. We also define 9 linguistic features that, combined, aim at estimating the difficulty at sentence level.

Keywords: sentiment analysis, difficulty, classification, machine learning

Procedia PDF Downloads 58