Search results for: Global Accuracy Indicator (GAI)

Authors: Noor Zainab Habib, Ibrahim Kamaruddin, Madzlan Napiah

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This paper present a part of research conducted to investigate the creep behavior of bituminous concrete mixture prepared with well graded using the dynamic creep test. The samples were prepared from unmodified control mix and Polypropylene modified bituminous mix. Unmodified or control mix was prepared with 80/100 grade bitumen while polypropylene modified mix was prepared using polypropylene PP polymer as modifier, blended with 80/100 Pen bitumen. The concentration of polymer in the blend was kept at 1%, 2%, and 3% by weight of bitumen content. For Dynamic Creep Test, Marshall Specimen were prepared at optimum bitumen content and then tested using IPC Global Universal Testing Machine (UTM), in order to investigate the creep stiffness of both modified and control mix. From the results obtained it was found that 1% and 2% PP modified bituminous mix offer better results in comparison to control and 3% PP modified mix samples. The results verify all the findings of empirical and viscosity test results which indicates that polymer modification induces stiffening effect in the binder. Enhanced viscous component of the binder was considered responsible for this change which eventually enhances the mechanical strength of the modified bituminous mixes.

Keywords: polymer modified bitumen, stiffness, creep, viscosity

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Authors: Lamia Bouzgarrou, Amira Omrane, Leila Mrabet, Taoufik Khalfallah

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Background and aims: School accidents are one of the leading causes of morbidity and mortality among pupils and students. Indeed, they may induce an elevated number of lost school days, heavy emotional and physical disabilities, and financial costs on the victims and their families. This study aims to evaluate the annual incidence of school accidents in the central Tunisian governorate of Mahdia and to identify the epidemiological profile of victims and risk factors of these accidents. Methods: A retrospective study was conducted over the period of 5 school years, focusing on school accidents that occurred in public educational institutions (primary, basic, secondary and university) in the governorate of Mahdia (area = 2 966 km² and number of inhabitants in 2014 = 410 812). All accidents declared near the only official insurance of this type of injuries (MASU: Mutual School and University Accidents), and initially taken in charge at the University Hospital of Mahdia were included. Data was collected from the MASU reporting forms and the medical records of emergency and other specialized hospital departments. Results: With 3248 identified victims, the annual incidence of school accidents was equal to 0.69 per 100 pupils and students per year. The average age of victims was 14.51 ± 0.059 years and the sex ratio was 1.58. Pupils aged between 12 and 15 years, were concerned by 46.7% of the identified accidents. The practice of sports was the most relevant circumstances of these accidents (76.2 %). In 56.58 % of cases, falls were the leading mechanism. Bruises and fractures were the most frequent lesions (32.43 % and 30.51 %). Serious school accidents were noted in 28% of cases with hospitalization in 2.27 % of them. The average lost school days, was 12.23±1.73 days. Accidents occurring during sports or leisure activities were significantly more serious (p= 0.021). Furthermore, the frequency of hospitalization was significantly higher among boys (2.81% vs. 1.43%; p= 0.035), students ≤11 years (p= 0.008), and following crush trauma (p= 0.000). In addition, the surgical interventions were statistically more frequent among male victims (p=0.00), accidents occurring during physical education sessions (p=0.000); those associated to falls (p=0.000) and to crushes mechanisms (p=0.002), and injuries affecting lower limbs (p=0.000). Following this Multi-varied analysis concluded that the severity of school accident is correlated to the activity practiced during the trauma and the geographical location of the school. Conclusion: Children and adolescents are one of the most vulnerable groups against incidents with the risk of permanent disability, mainly related to the perturbation of the growth process and physiological limitations. Our five-year study, objectified a real elevate incidence of school accident among children and adolescents, with a considerable rate of severe injuries. In any community, the promotion of adolescents and children’s health is an important indicator of the public health level. Thus, it’s important to develop a multidisciplinary prevention strategy of school accident, based on safety and security rules and adapted to the specificity of our context.

Keywords: children and adolescents, children health, injuries and disability, school accident

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Authors: Ren Moses, Jaqueline Masaki

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This paper addresses the need for accurate and updated vehicle classification system through a thorough evaluation of vehicle class categories to identify errors arising from the existing system and proposing modifications. The data collected from two permanent traffic monitoring sites in Florida were used to evaluate the performance of the existing vehicle classification table. The vehicle data were collected and classified by the automatic vehicle classifier (AVC), and a video camera was used to obtain ground truth data. The Federal Highway Administration (FHWA) vehicle classification definitions were used to define vehicle classes from the video and compare them to the data generated by AVC in order to identify the sources of misclassification. Six types of errors were identified. Modifications were made in the classification table to improve the classification accuracy. The results of this study include the development of updated vehicle classification table with a reduction in total error by 5.1%, a step by step procedure to use for evaluation of vehicle classification studies and recommendations to improve FHWA 13-category rule set. The recommendations for the FHWA 13-category rule set indicate the need for the vehicle classification definitions in this scheme to be updated to reflect the distribution of current traffic. The presented results will be of interest to States’ transportation departments and consultants, researchers, engineers, designers, and planners who require accurate vehicle classification information for planning, designing and maintenance of transportation infrastructures.

Keywords: vehicle classification, traffic monitoring, pavement design, highway traffic

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Authors: Jinrui Zhang, Tianlong Yang, Ying Pan

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Methane and carbon dioxide are major greenhouse gases contributor. CO₂ dry reforming of methane (DRM) for syngas production is a promising approach to reducing global CO₂ emission and extensive utilization of natural gas. However, the reported catalysts endured rapid deactivation due to severe carbon deposition at high temperature. Here, CO₂ reduction by CH4 on hexagonal nano-nickel flakes packed by porous SiO₂ (Ni@SiO₂) catalysts driven by thermal and solar light are tested. High resistance to carbon deposition and higher reactive activity are demonstrated under focused solar light at moderate temperature (400-500 ℃). Furthermore, the photocatalytic DRM under different wavelength is investigated, and even IR irradiation can enhance the catalytic activity. The mechanism of light-enhanced reaction reactivity and equilibrium is investigated by Infrared and Raman spectroscopy, and the unique reaction pathway with light is depicted. The photo-enhanced DRM provides a promising method of renewable solar energy conversion and CO₂ emission reduction due to the excellent activity and durability.

Keywords: CO₂ emission reduction, methane, photocatalytic DRM, resistance to carbon deposition, syngas

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Authors: Ngan Nguyen

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The study analyses adjectives collocating with the word ‘education’ in the American language of the Corpus of Global Web-based English using a combination of corpus linguistic and discourse analytical methods to examine not only language patterns but also social political ideologies around the topic. Significant conclusions are deduced: (1) there are a large number of adjectival collocates of the word education which have been identified and classified into four categories representing four different aspects of education: level, quality, forms and types of education; (2) education, as in combination with three first categories, carries the meaning as the act and process of teaching and learning while with the last category having the meaning of a particular kind of teaching or training; (3) higher education is the topic that gains most concerns from the American public; (4) five most significant ideologies are discovered from the corpus: higher education associates with financial affairs, higher education is an industry, monetary policy of the government on higher education, people require greater accessibility to higher education and people value higher education. The study contributes to the field of developing meanings of words through corpus analysis and the field of discourse analysis.

Keywords: adjectival collocation, American context, corpus linguistics, discourse analysis, education

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Authors: Muhammad Afzal, Muhammad Sajjad

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Climate change has become a global environmental challenge and it has affected the world’s economy. Its impact is widespread across all major sectors of the economy i.e. agriculture, industry, and services sectors. This study attempts to measure the long run as well as the short-run dynamic between energy; environment and economic growth by using Autoregressive Distributed Lag (ARDL) bound testing approach at aggregate as well as sectoral level. We measured the causal relationship between electricity consumption, fuel consumption, CO₂ emission, and real Gross Domestic Product (GDP) for the period of 1980 to 2016 for Pakistan. Our co-integration results reveal that all the variables are co-integrated at aggregate as well as at sectoral level. Electricity consumption shows two-way casual relation at for industry, services and aggregate level. The inverted U-Curve hypothesis tested the relationship between greenhouse gas emissions and per capita GDP and results supported the Environment Kuznet Curve (EKC) hypothesis. This study cannot ignore the importance of energy for economic growth but prefers to focus on renewable and green energy to pave on the trajectory of development.

Keywords: climate change, economic growth, energy, environment

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Authors: Dylan Santos De Pinho, Nabil Ouerhani

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Energy consumption of machine-tools is becoming critical for machine-tool builders and end-users because of economic, ecological and legislation-related reasons. Many machine-tool builders are seeking for solutions that allow the reduction of energy consumption of machine-tools while preserving the same productivity rate and the same quality of machined parts. In this paper, we present the first results of a project conducted jointly by academic and industrial partners to reduce the energy consumption of a Swiss-Type lathe. We employ genetic algorithms to find optimal machining parameters – the set of parameters that lead to the best trade-off between energy consumption, part quality and tool lifetime. Three main machining process parameters are considered in our optimization technique, namely depth of cut, spindle rotation speed and material feed rate. These machining process parameters have been identified as the most influential ones in the configuration of the Swiss-type machining process. A state-of-the-art multi-objective genetic algorithm has been used. The algorithm combines three fitness functions, which are objective functions that permit to evaluate a set of parameters against the three objectives: energy consumption, quality of the machined parts, and tool lifetime. In this paper, we focus on the investigation of the fitness function related to energy consumption. Four different energy consumption related fitness functions have been investigated and compared. The first fitness function refers to the Kienzle cutting force model. The second fitness function uses the Material Removal Rate (RMM) as an indicator of energy consumption. The two other fitness functions are non-deterministic, learning-based functions. One fitness function uses a simple Neural Network to learn the relation between the process parameters and the energy consumption from experimental data. Another fitness function uses Lasso regression to determine the same relation. The goal is, then, to find out which fitness functions predict best the energy consumption of a Swiss-Type machining process for the given set of machining process parameters. Once determined, these functions may be used for optimization purposes – determine the optimal machining process parameters leading to minimum energy consumption. The performance of the four fitness functions has been evaluated. The Tornos DT13 Swiss-Type Lathe has been used to carry out the experiments. A mechanical part including various Swiss-Type machining operations has been selected for the experiments. The evaluation process starts with generating a set of CNC (Computer Numerical Control) programs for machining the part at hand. Each CNC program considers a different set of machining process parameters. During the machining process, the power consumption of the spindle is measured. All collected data are assigned to the appropriate CNC program and thus to the set of machining process parameters. The evaluation approach consists in calculating the correlation between the normalized measured power consumption and the normalized power consumption prediction for each of the four fitness functions. The evaluation shows that the Lasso and Neural Network fitness functions have the highest correlation coefficient with 97%. The fitness function “Material Removal Rate” (MRR) has a correlation coefficient of 90%, whereas the Kienzle-based fitness function has a correlation coefficient of 80%.

Keywords: adaptive machining, genetic algorithms, smart manufacturing, parameters optimization

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Authors: Erfan Ghasemi, Mohammadreza Khani, Hamidreza Mahmoudi, Mohammad Ali Nilforoushzadeh, Babak Shokri, Pouria Akbartehrani

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Given the global significance of treating infectious wounds, the goal of this study is to use spark plasma as a new treatment for infectious wounds. To generate spark plasma, a high-voltage (7 kV) and high-frequency (75 kHz) source was used. Infectious wounds in the peritoneum of mice were divided into control and plasma-treated groups at random. The plasma-treated animals received plasma radiation every 4 days for 12 days, for 60 seconds each time. On the 15th day after the first session, the wound in the plasma-treated group had completely healed. The spectra of spark plasma emission and tissue properties were studied. The mechanical resistance of the wound healed in the plasma treatment group was considerably higher than in the control group (p<0.05), according to the findings. Furthermore, histological evidence suggests that wound re-epithelialization is faster in comparison to controls. Angiogenesis and fibrosis (collagen production) were also dramatically boosted in the plasma-treated group, whereas the stage of wound healing inflammation was significantly reduced. Plasma therapy accelerated wound healing by causing considerable wound constriction. The results of this investigation show that spark plasma has an influence on the treatment of infectious wounds.

Keywords: infectious wounds, mice, spark plasma, treatment

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Authors: Tomas Trainys, Algimantas Venckauskas

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Application of biometric features to the cryptography for human identification and authentication is widely studied and promising area of the development of high-reliability cryptosystems. Biometric cryptosystems typically are designed for patterns recognition, which allows biometric data acquisition from an individual, extracts feature sets, compares the feature set against the set stored in the vault and gives a result of the comparison. Preprocessing and fusion of biometric data are the most important phases in generating a feature vector for key generation or authentication. Fusion of biometric features is critical for achieving a higher level of security and prevents from possible spoofing attacks. The paper focuses on the tasks of initial processing and fusion of multiple representations of finger vein modality patterns. These tasks are solved by applying conventional image preprocessing methods and machine learning techniques, Convolutional Neural Network (SVM) method for image segmentation and feature extraction. An article presents a method for generating sets of biometric features from a finger vein network using several instances of the same modality. Extracted features sets were fused at the feature level. The proposed method was tested and compared with the performance and accuracy results of other authors.

Keywords: bio-cryptography, biometrics, cryptographic key generation, data fusion, information security, SVM, pattern recognition, finger vein method.

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Authors: Mustafa M. Donma, Orkide Donma

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Cardiovascular pathology is one of the expected consequences of excessive fat gain. The role of zinc in thyroid hormone metabolism is an important matter. The concentrations of both thyroid stimulating hormone (TSH) and zinc are subject to variation in obese individuals. Zinc exhibits protective effects on cardiovascular health and is inversely correlated with cardiovascular markers in childhood obesity. The association between subclinical hypothyroidism (SCHT) and metabolic disorders is under investigation due to its clinical importance. Underactive thyroid gland causes high TSH levels. Subclinical hypothyroidism is defined as the elevated serum TSH levels in the presence of normal free thyroxin (T4) concentrations. The aim of this study was to evaluate the associations between TSH levels and zinc concentrations in morbid obese (MO) children exhibiting SCHT. The possibility of using the probable association between these parameters was also evaluated for the discrimination of metabolic syndrome positive (MetS+) and metabolic syndrome negative (MetS-) groups. Forty-two children were present in each group. Informed consent forms were obtained. Institutional Ethics Committee approved the study protocol. Tables prepared by World Health Organization were used for the definition of MO children. Children, whose age- and sex-dependent body mass index percentile values were above 99, were defined as MO. Children with at least two MetS components were included in MOMetS+ group. Elevated systolic/diastolic blood pressure values, increased fasting blood glucose, triglycerides (TRG)/decreased high density lipoprotein-cholesterol (HDL-C) concentrations in addition to central obesity were listed as MetS components. Anthropometric measures were recorded. Routine biochemical analyses were performed. Thirteen and fifteen children had SCHT in MOMetS- and MOMetS+ groups, respectively. Statistical analyses were performed. p<0.05 was accepted as statistically significant. In MOMetS- and MOMetS+ groups, TSH levels were 4.1±2.9 mU/L and 4.6±3.1 mU/L, respectively. Corresponding values for SCHT cases in these groups were 7.3±3.1 mU/L and 8.0±2.7 mU/L. Free T4 levels were within normal limits. Zinc concentrations were negatively correlated with TSH levels in both groups. The significant negative correlation calculated in MOMetS+ group (r= -0.909; p<0.001) was much stronger than that found in MOMetS- group (r= -0.706; p<0.05). This strong correlation (r= -0.909; p<0.001) calculated for cases with SCHT in MOMetS+ group was much lower (r= -0.793; p<0.001) when all MOMetS+ cases were considered. Zinc is closely related to T4 and TSH therefore, it participates in thyroid hormone metabolism. Since thyroid hormones are required for zinc absorption, hypothyroidism can lead to zinc deficiency. The presence of strong correlations between TSH and zinc in SCHT cases found in both MOMetS- and MOMetS+ groups pointed out that MO children were under the threat of cardiovascular pathologies. The detection of the much stronger correlation in MOMetS+ group in comparison with the correlation found in MOMetS- group was the indicator of greater cardiovascular risk due to the presence of MetS. In MOMetS+ group, correlation in SCHT cases found higher than correlation calculated for all cases confirmed much higher cardiovascular risk due to the contribution of SCHT.

Keywords: cardiovascular risk, children, morbid obesity, subclinical hypothyroidism, zinc

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Authors: Benedict Okundaye, Patricia Tzortzopoulos, Yun Gao

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Scholars and international organisations have contended that developing nations lack the technical expertise, infrastructure, and ability to cope with or prepare for the neighbourhood’s sustainable development as Sustainable Development Goals, mainly targeting goal 11 unimpressive accomplishments. Both wealthy and impoverished communities are facing increasing issues due to rapid urbanisation and pandemics, particularly in Africa. The global neighbourhood challenges, especially in developing countries such as South Africa, include pollution poverty, energy poverty, digital poverty, environmental degradation, social exclusion, and socioeconomic inequalities. With the problematic international sustainability assessment tools lingering, few researchers have produced frameworks to engage the local contexts, but improvements are still required. This research anchors on developing a people-centred, flexible, and adaptable neighbourhood sustainability assessment framework that becomes a tool to assess the characteristics of neighbourhood sustainability in South Africa. The conceptual framework employs a variety of approaches, including broader dimensional factors, a closed-ended questionnaire, and statistical analysis to improve on and complement other existing frameworks.

Keywords: participation, development, inclusion, urbanism, cities, resilience

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Authors: Ying Yu, Wen-Chi Kuo, Tung-Jung Sung

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The Product-Service System (PSS) has received widespread attention due to the increasing global competition in manufacturing and service markets. Today’s smart products and services are driven by Internet of things (IoT) technologies which will promote the transformation from traditional PSS to smart PSS. Although the smart PSS has some of technological achievements in businesses, it often ignores the real demands of target users when using products and services. Therefore, designers should know and learn the User Experience (UX) of smart products, services and systems. However, both of academia and industry still lack relevant development experience of smart PSS since it is an emerging field. In doing so, this is a case study of Xiaomi’s Chunmi, the largest IoT platform in the world, and addresses the two major issues: (1) why Chunmi should develop smart PSS strategies with UX; and (2) how Chunmi could successfully implement the strategic objectives of smart PSS through the design. The case study results indicated that: (1) the smart PSS can distinguish competitors by their unique UX which is difficult to duplicate; (2) early user engagement is crucial for the success of smart PSS; and (3) interaction, expectation, and enjoyment can be treated as a three-dimensional evaluation of UX design for smart PSS innovation. In conclusion, the smart PSS can gain competitive advantages through good UX design in the market.

Keywords: design, smart PSS, user experience, user engagement

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Authors: C. B. Le, V. N. Pham

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In modern data analysis, multi-source data appears more and more in real applications. Multi-source data clustering has emerged as a important issue in the data mining and machine learning community. Different data sources provide information about different data. Therefore, multi-source data linking is essential to improve clustering performance. However, in practice multi-source data is often heterogeneous, uncertain, and large. This issue is considered a major challenge from multi-source data. Ensemble is a versatile machine learning model in which learning techniques can work in parallel, with big data. Clustering ensemble has been shown to outperform any standard clustering algorithm in terms of accuracy and robustness. However, most of the traditional clustering ensemble approaches are based on single-objective function and single-source data. This paper proposes a new clustering ensemble method for multi-source data analysis. The fuzzy optimized multi-objective clustering ensemble method is called FOMOCE. Firstly, a clustering ensemble mathematical model based on the structure of multi-objective clustering function, multi-source data, and dark knowledge is introduced. Then, rules for extracting dark knowledge from the input data, clustering algorithms, and base clusterings are designed and applied. Finally, a clustering ensemble algorithm is proposed for multi-source data analysis. The experiments were performed on the standard sample data set. The experimental results demonstrate the superior performance of the FOMOCE method compared to the existing clustering ensemble methods and multi-source clustering methods.

Keywords: clustering ensemble, multi-source, multi-objective, fuzzy clustering

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Authors: S. Aswath, Chinmaya Krishna Tilak, Amal Suresh, Ganesh Udupa

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There are technologies to control a humanoid robot in many ways. But the use of Electromyogram (EMG) electrodes has its own importance in setting up the control system. The EMG based control system helps to control robotic devices with more fidelity and precision. In this paper, development of an electromyogram based interface for human gesture recognition for the control of a humanoid robot is presented. To recognize control signs in the gestures, a single channel EMG sensor is positioned on the muscles of the human body. Instead of using a remote control unit, the humanoid robot is controlled by various gestures performed by the human. The EMG electrodes attached to the muscles generates an analog signal due to the effect of nerve impulses generated on moving muscles of the human being. The analog signals taken up from the muscles are supplied to a differential muscle sensor that processes the given signal to generate a signal suitable for the microcontroller to get the control over a humanoid robot. The signal from the differential muscle sensor is converted to a digital form using the ADC of the microcontroller and outputs its decision to the CM-530 humanoid robot controller through a Zigbee wireless interface. The output decision of the CM-530 processor is sent to a motor driver in order to control the servo motors in required direction for human like actions. This method for gaining control of a humanoid robot could be used for performing actions with more accuracy and ease. In addition, a study has been conducted to investigate the controllability and ease of use of the interface and the employed gestures.

Keywords: electromyogram, gesture, muscle sensor, humanoid robot, microcontroller, Zigbee

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Authors: Julia Desiree Velastegui Caceres, Luis Alejandro Velastegui Caceres, Oswaldo Padilla, Eduardo Kirby, Francisco Guerrero, Theofilos Toulkeridis

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It is fundamental to conserve sites of natural and cultural heritage with any available technique or existing methodology of preservation in order to sustain them for the following generations. We propose a further skill to protect the actual view of such sites, in which with high technology instrumentation we are able to digitally preserve natural and cultural heritages applied in Ecuador. In this project the use of laser technology is presented for three-dimensional models, with high accuracy in a relatively short period of time. In Ecuador so far, there are not any records on the use and processing of data obtained by this new technological trend. The importance of the project is the description of the methodology of the laser scanner system using the Faro Laser Scanner Focus 3D 120, the method for 3D modeling of geospatial data and the development of virtual environments in the areas of Cultural and Natural Heritage. In order to inform users this trend in technology in which three-dimensional models are generated, the use of such tools has been developed to be able to be displayed in all kinds of digitally formats. The results of the obtained 3D models allows to demonstrate that this technology is extremely useful in these areas, but also indicating that each data campaign needs an individual slightly different proceeding starting with the data capture and processing to obtain finally the chosen virtual environments.

Keywords: laser scanner system, 3D model, cultural heritage, natural heritage

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Authors: Shima Behkami, Nor Shahirul Umirah Idris, Sharifuddin Md. Zain, Kah Hin Low, Mehrdad Gholami, Nima A. Behkami, Ahmad Firdaus Kamaruddin

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In this work, Inductively Coupled Plasma Mass Spectrometry (ICP-MS), Isotopic Ratio Mass Spectrometry (IRMS) and Ultrasound Milko Tester were used to study milk samples obtained from various geographical locations in Malaysia. ICP-MS was used to determine the concentration of trace elements in milk, water and soil samples obtained from seven dairy farms at different geographical locations in peninsular Malaysia. IRMS was used to analyze the milk samples for isotopic ratios of δ13C, 15N and 18O. Nutritional parameters in the milk samples were determined using an ultrasound milko tester. Data obtained from these measurements were evaluated by Principal Component Analysis (PCA) and Hierarchical Analysis (HA) as a preliminary step in determining geographical origin of these milk samples. It is observed that the isotopic ratios and a number of the nutritional parameters are responsible for the discrimination of the samples. It was also observed that it is possible to determine the geographical origin of these milk samples solely by the isotopic ratios of δ13C, 15N and 18O. The accuracy of the geographical discrimination is demonstrated when several milk samples from a milk factory taken from one of the regions under study were appropriately assigned to the correct PCA cluster.

Keywords: inductively coupled plasma mass spectroscopy ICP-MS, isotope ratio mass spectroscopy IRMS, ultrasound, principal component analysis, hierarchical analysis, geographical origin, milk

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Authors: Hanadi Al-Mubaraki, Michael Busler

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Both in the developed and developing countries as well as Gulf Cooperation Council (GCC), the small and medium-sized enterprises (SMEs) proven to be main drivers of jobs creation and tools to accelerate economic development and economic diversification. This paper seeks to investigate and identify the strengths and weakness of SME as a veritable tool in economic development. A survey method was used to gather data from 171 SME from Gulf Cooperation Council (GCC). The research methodology uses a quantitative approach (survey) while data were collected with a structured questionnaire and analyzed with several descriptive statistics. The results of the study, therefore, will present sets of the strengths of SME in GCC such as 1) government supported local products (59%), 2) promoting SME local products rather than international products (47%), 3) reduce the legal and administrative procedures of SME establishment (46%) and weakness of SME in GCC such as: 1) lack of funding during the initial phase of the project (46%), 2) lack of liquidity during project continuity (39%), and 3) strong competition in the domestic and global market (38%). The study findings will be guidelines for academia and practitioners such as governments, policymakers, funded organizations, universities and strategic institutions for successful implementation.

Keywords: SME, economic development, GCC, strengths and weaknesses

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Authors: Kaaryn M. Cater

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Students with sensory processing sensitivity (SPS), Meares-Irlen Syndrome (MIS) and dyslexia can become overwhelmed and struggle to thrive in traditional tertiary learning environments. An estimated 50% of tertiary students who disclose learning related issues are dyslexic. This study explores the relationship between SPS, MIS and dyslexia. Baseline measures will be analysed to establish any correlation between these three minority methods of information processing. SPS is an innate sensitivity trait found in 15-20% of the population and has been identified in over 100 species of animals. Humans with SPS are referred to as Highly Sensitive People (HSP) and the measure of HSP is a 27 point self-test known as the Highly Sensitive Person Scale (HSPS). A 2016 study conducted by the author established base-line data for HSP students in a tertiary institution in New Zealand. The results of the study showed that all participating HSP students believed the knowledge of SPS to be life-changing and useful in managing life and study, in addition, they believed that all tutors and in-coming students should be given information on SPS. MIS is a visual processing and perception disorder that is found in approximately 10% of the population and has a variety of symptoms including visual fatigue, headaches and nausea. One way to ease some of these symptoms is through the use of colored lenses or overlays. Dyslexia is a complex phonological based information processing variation present in approximately 10% of the population. An estimated 50% of dyslexics are thought to have MIS. The study exploring possible correlations between these minority forms of information processing is due to begin in February 2017. An invitation will be extended to all first year students enrolled in degree programmes across all faculties and schools within the institution. An estimated 900 students will be eligible to participate in the study. Participants will be asked to complete a battery of on-line questionnaires including the Highly Sensitive Person Scale, the International Dyslexia Association adult self-assessment and the adapted Irlen indicator. All three scales have been used extensively in literature and have been validated among many populations. All participants whose score on any (or some) of the three questionnaires suggest a minority method of information processing will receive an invitation to meet with a learning advisor, and given access to counselling services if they choose. Meeting with a learning advisor is not mandatory, and some participants may choose not to receive help. Data will be collected using the Question Pro platform and base-line data will be analysed using correlation and regression analysis to identify relationships and predictors between SPS, MIS and dyslexia. This study forms part of a larger three year longitudinal study and participants will be required to complete questionnaires at annual intervals in subsequent years of the study until completion of (or withdrawal from) their degree. At these data collection points, participants will be questioned on any additional support received relating to their minority method(s) of information processing. Data from this study will be available by April 2017.

Keywords: dyslexia, highly sensitive person (HSP), Meares-Irlen Syndrome (MIS), minority forms of information processing, sensory processing sensitivity (SPS)

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Authors: Ahlem Setrallah

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Environment has become a phenomenon directly linked to security in recent decades. This security aspect of environment is justified by the challenges that environment problems can have on human life and thus security especially within the scope of human security that is based mainly on the individual rather than on the state. Because Africa is not safe from the global warming and all its consequences on environment, this continent has witnessed many crises related to environment and that have had direct impact on security in Africa. One of those crises is environmental displacement or immigration which was caused by natural disasters like draught, desertification and food shortage to name but a few. This paper aims at shedding light at some important cases in the Africa focusing mainly on the Sahel region. The main research questions that we are trying to answer are the following: 1-What is the relationship between environment and forced immigration in the Sahel region? 2-What is the impact of environmental immigration on Security in the region? 3-How have the states in this region reacted to this crisis? 4-Is the measures taken by those states adequate or not? 5- How to remedy for the limitations of those measures? The paper is based on case study methodology as a way to better understand the relationship between security and environment using library research for data collection and analysis. This paper aims also at presenting some suggesting regarding possible ways of reducing the negative impact of environmental immigration.

Keywords: environment, refugees, Sahel region, security

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Authors: Yessengeldy Kuanyshpayev

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Now in some countries of the world the cellular market is on the point of saturation, in others - positive dynamics of development kept on. The reasons for it are also different, but there are united by their general susceptibility to innovation changes, if they are really innovative. If to take as an example the cellular market of Kazakhstan it is defined by the low percent of smart phones at consumers, the low population density, undercapacity of the 3G channel, and absence of universal access to the LTE technology that limits dynamical growth of this branch. These moments are aggravated by failures of starting commercial projects by private companies which prevent to be implemented and widely adopted to a new product among consumers. The object of the research is possible integration of wireless and program technologies at which introduction the idea can regenerate in an innovation. The analysis of existing projects in the market and the possible union of the technologies through a prism of theoretical bases of innovative activity shows that efficiency of the company by development and introduction of innovations is possible only thanks to strict observance of all terms and conditions of the innovative process which main term is profit. Despite that fact that on a global scale the innovativeness issue of companies is very popular, there are no research about possibility of innovative breaks in the field of wireless access to the Internet in the cellular market of Kazakhstan.

Keywords: innovation, the effectiveness of company, commercialization, cellular market

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Authors: Murat Colak, Berkay Cakir Saridogan

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Since the dawn of modern corporations, almost every single employee has been working in the same loop, which contains three basic steps: going to work, providing the needs for the work, and getting back home. Only a small amount of people were able to break that standard and live outside the box. As the 2019 pandemic hit the Earth and most companies shut down their physical offices, that loop had to change for everyone. This means that the old management styles had to be significantly re-arranged to the "work from home" type of business methods. The methods include online conferences and meetings, time and task tracking using algorithms, globalization of the work, and, most importantly, remote working. After the global epidemic started, even the tech giants were concerned. Now, it can be seen those technology companies have an incredible step-up in their shares compared to the other companies because they know how to manage such situations even better than every other industry. This study aims to take the old traditional management styles in big companies and compare them with the post-covid methods (2019-2022). As a result of this comparison made using the annual reports and shared statistics, this study aims to explain why the winners of this crisis are the technology companies.

Keywords: Covid-19, technology companies, business models, remote work

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Authors: Brandon Foggo, Nanpeng Yu

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Power distribution circuits undergo frequent network topology changes that are often left undocumented. As a result, the documentation of a circuit’s connectivity becomes inaccurate with time. The lack of reliable circuit connectivity information is one of the biggest obstacles to model, monitor, and control modern distribution systems. To enhance the reliability and efficiency of electric power distribution systems, the circuit’s connectivity information must be updated periodically. This paper focuses on one critical component of a distribution circuit’s topology - the secondary transformer to phase association. This topology component describes the set of phase lines that feed power to a given secondary transformer (and therefore a given group of power consumers). Finding the documentation of this component is call Phase Identification, and is typically performed with physical measurements. These measurements can take time lengths on the order of several months, but with supervised learning, the time length can be reduced significantly. This paper compares several such methods applied to Phase Identification for a large range of real distribution circuits, describes a method of training data selection, describes preprocessing steps unique to the Phase Identification problem, and ultimately describes a method which obtains high accuracy (> 96% in most cases, > 92% in the worst case) using only 5% of the measurements typically used for Phase Identification.

Keywords: distribution network, machine learning, network topology, phase identification, smart grid

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Authors: Kapse Swapnil, K. Shankar

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Aiming at optimizing the weight and deflection of cantilever beam subjected to maximum stress and maximum deflection, Multi-objective Particle Swarm Optimization (MOPSO) with Utopia Point based local search is implemented. Utopia point is used to govern the search towards the Pareto Optimal set. The elite candidates obtained during the iterations are stored in an archive according to non-dominated sorting and also the archive is truncated based on least crowding distance. Local search is also performed on elite candidates and the most diverse particle is selected as the global best. This method is implemented on standard test functions and it is observed that the improved algorithm gives better convergence and diversity as compared to NSGA-II in fewer iterations. Implementation on practical structural problem shows that in 5 to 6 iterations, the improved algorithm converges with better diversity as evident by the improvement of cantilever beam on an average of 0.78% and 9.28% in the weight and deflection respectively compared to NSGA-II.

Keywords: Utopia point, multi-objective particle swarm optimization, local search, cantilever beam

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Authors: S. Visetpotjanakit, N. Nakkaew

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Determination of ⁹⁰Sr in environmental samples has been widely developed with several radioanlytical methods and radiation measurement techniques since ⁹⁰Sr is one of the most hazardous radionuclides produced from nuclear reactors. Liquid extraction technique using di-(2-ethylhexyl) phosphoric acid (HDEHP) to separate and purify ⁹⁰Y and Cherenkov counting using liquid scintillation counter to determine ⁹⁰Y in secular equilibrium to ⁹⁰Sr was developed and performed at our institute, the Office of Atoms for Peace. The approach is inexpensive, non-laborious, and fast to analyse ⁹⁰Sr in environmental samples. To validate our analytical performance for the accurate and precise criteria, determination of ⁹⁰Sr using the IAEA-TEL-2016-04 ALMERA proficiency test samples were performed for statistical evaluation. The experiment used two spiked tap water samples and one naturally contaminated spruce needles sample from Austria collected shortly after the Chernobyl accident. Results showed that all three analyses were successfully passed in terms of both accuracy and precision criteria, obtaining “Accepted” statuses. The two water samples obtained the measured results of 15.54 Bq/kg and 19.76 Bq/kg, which had relative bias 5.68% and -3.63% for the Maximum Acceptable Relative Bias (MARB) 15% and 20%, respectively. And the spruce needles sample obtained the measured results of 21.04 Bq/kg, which had relative bias 23.78% for the MARB 30%. These results confirm our analytical performance of ⁹⁰Sr determination in water and spruce needles samples using the same developed method.

Keywords: ALMERA proficiency test, Cerenkov counting, determination of 90Sr, environmental samples

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Authors: Stephane Laussac, Jacques Piazzola, Gilles Tedeschi

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Estimation of the impact of atmospheric aerosols on the climate evolution is an important scientific challenge. One of a major source of particles is constituted by the oceans through the generation of sea-spray aerosols. In coastal areas, marine aerosols can affect air quality through their ability to interact chemically and physically with other aerosol species and gases. The integration of accurate sea-spray emission terms in modeling studies is then required. However, it was found that sea-spray concentrations are not represented with the necessary accuracy in some situations, more particularly at short fetch. In this study, the WRF-Chem model was implemented on a North-Western Mediterranean coastal region. WRF-Chem is the Weather Research and Forecasting (WRF) model online-coupled with chemistry for investigation of regional-scale air quality which simulates the emission, transport, mixing, and chemical transformation of trace gases and aerosols simultaneously with the meteorology. One of the objectives was to test the ability of the WRF-Chem model to represent the fine details of the coastal geography to provide accurate predictions of sea spray evolution for different fetches and the anthropogenic aerosols. To assess the performance of the model, a comparison between the model predictions using a local emission inventory and the physicochemical analysis of aerosol concentrations measured for different wind direction on the island of Porquerolles located 10 km south of the French Riviera is proposed.

Keywords: sea-spray aerosols, coastal areas, sea-spray concentrations, short fetch, WRF-Chem model

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Authors: Tisciane Perpetuo e Oliveira, Dante Inga Narvaez, Marcelo Gradella Villalva

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Installations of solar photovoltaic systems have increased considerably in the last decade. Therefore, it has been noticed that monitoring of meteorological data (solar irradiance, air temperature, wind velocity, etc.) is important to predict the potential of a given geographical area in solar energy production. In this sense, the present work compares two computational tools that are capable of estimating the energy generation of a photovoltaic system through correlation analyzes of solar radiation data: PVsyst software and an algorithm based on the PVlib package implemented in MATLAB. In order to achieve the objective, it was necessary to obtain solar radiation data (measured and from a solarimetric database), analyze the decomposition of global solar irradiance in direct normal and horizontal diffuse components, as well as analyze the modeling of the devices of a photovoltaic system (solar modules and inverters) for energy production calculations. Simulated results were compared with experimental data in order to evaluate the performance of the studied methods. Errors in estimation of energy production were less than 30% for the MATLAB algorithm and less than 20% for the PVsyst software.

Keywords: energy production, meteorological data, irradiance decomposition, solar photovoltaic system

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Authors: Prateek Guleria, Shubham Sharma, Rakesh Kumar Shukla, Harshit Sharma

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Performance measurement of small and medium-sized businesses is the primary need for all companies to survive and thrive in a dynamic global company. A structured and systematic, integrated organization increases employee reliability, sustainability, and loyalty. This paper is a case study of a gear manufacturing industry that was facing the problem of rejection due to dents and damages in gear. The DMAIC cycle, along with different tools used in the research work includes SIPOC (Supply, Input, Process, Output, Control) Pareto analysis, Root & Cause analysis, and FMEA (Failure Mode and Effect Analysis). The six-sigma level was improved from 4.06 to 3.46, and the rejection rate was reduced from 7.44% to 1.56%. These findings highlighted the influence of a Lean Six Sigma module in the gear manufacturing unit, which has already increased operational quality and continuity to increase market success and meet customer expectations. According to the findings, applying lean six sigma tools will result in increased productivity. The results could assist businesses in deciding the quality tools that were likely to improve efficiency, competitiveness, and expense.

Keywords: six sigma, DMAIC, SIPOC, failure mode, effect analysis

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Authors: Rohit Sarin

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This paper is an attempt to prove the impact of storytelling for effective marketing and maintaining the reputation of the destination for long run. This notable aspect of heritage tourism is cultural exchange among the various communities who visit our country India. Every destination has a life cycle like the product known as destination life cycle. India is considered to be the hub of cultural heritage tourism; its cultural heritage tourism can be traced back to several centuries. Heritage tourism has gained the popularity of global cuisine activity. The statistics of 2014 reveals 903 million International Tourist in heritage tourism destination is done to know the impact of storytelling for their visit to particulars heritage tourism destination. SWOT analysis of the destination is undertaken for the research purpose. A collection of data from the travel agency was taken who visited the heritage tourism destination and were asked to fill questionnaire for the research purpose to know the impact of storytelling for their visit to destination. A total of 100 respondents filled the questionnaire. Likert scale was used in the paper also highlighted the scope, advantage and disadvantage of storytelling for effective marketing and reputation management.

Keywords: destination life cycle, heritage tourism, random sampling, reputation management, storytelling

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Authors: Victor Bodell, Lukas Ekstrom, Somayeh Aghanavesi

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Fuel consumption (FC) is one of the key factors in determining expenses of operating a heavy-duty vehicle. A customer may therefore request an estimate of the FC of a desired vehicle. The modular design of heavy-duty vehicles allows their construction by specifying the building blocks, such as gear box, engine and chassis type. If the combination of building blocks is unprecedented, it is unfeasible to measure the FC, since this would first r equire the construction of the vehicle. This paper proposes a machine learning approach to predict FC. This study uses around 40,000 vehicles specific and o perational e nvironmental c onditions i nformation, such as road slopes and driver profiles. A ll v ehicles h ave d iesel engines and a mileage of more than 20,000 km. The data is used to investigate the accuracy of machine learning algorithms Linear regression (LR), K-nearest neighbor (KNN) and Artificial n eural n etworks (ANN) in predicting fuel consumption for heavy-duty vehicles. Performance of the algorithms is evaluated by reporting the prediction error on both simulated data and operational measurements. The performance of the algorithms is compared using nested cross-validation and statistical hypothesis testing. The statistical evaluation procedure finds that ANNs have the lowest prediction error compared to LR and KNN in estimating fuel consumption on both simulated and operational data. The models have a mean relative prediction error of 0.3% on simulated data, and 4.2% on operational data.

Keywords: artificial neural networks, fuel consumption, friedman test, machine learning, statistical hypothesis testing

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Authors: Mariam Anwaar, Kiran B. Ahmad

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Borderline Personality Disorder (BPD) is an invasive presence of affect instability, disturbance in self-concept and attachment in relationships. The profound indicator is the dichotomous approach of the world in which the ego categorizes individuals, especially their significant others, into secure or threatful beings, leaving little room for a complex combination of characteristics in one person. This defense mechanism of splitting their world has been described through the explanatory model of unconscious conflict theorized by Sigmund Freud’s Electra Complex in the Phallic Stage. The central role is of the father with whom the daughter experiences penis envy, thus identifying with the mother’s characteristics to receive the father’s attention. However, Margret Mahler, an object relation theorist, elucidates the central role of the mother and that the split occurs during the pre-Electra complex stage. Amid the 14 and 24 months of the infant, it acknowledges the world away from the mother as they have developed milestones such as crawling. In such novelty, the infant crawls away from the mother creating a sense of independence (individuation). On the other hand, being distant causes anxiety, making them return to their original object of security (separation). In BPD, the separation-individuation stage is disrupted, due to contradictory actions of the caregiver, which results in splitting the object into negative and positive aspects, repressing the former and adhering to the latter for survival. Thus, with time, the ego distorts the reality into dichotomous categories, using the splitting defenses, and the mental representation of the self is distorted due to the internalization of the negative objects. The explanatory model was recognized in the case study of Fizza, at 21-year-old Pakistani female, residing in Karachi. Her marital status is single with an occupation being a dental student. Fizza lives in a nuclear family but is surrounded by her extended family as they all are in close vicinity. She came with the complaints of depressive symptoms for two-years along with self-harm due to severe family conflicts. Through the intervention of Dialectical Behavior Therapy (DBT), the self-harming actions were reduced, however, this libidinal energy transformed into claustrophobic symptoms and, along with this, Fizza has always experienced vivid dreams. A retrospective method of Jungian dream-analysis was applied to locate the origins of the splitting in the unconscious. The result was the revelation of a sexual harassment trauma at the age of six-years which was displaced in the form of self-harm. In addition to this, the presence of a conflict at the separation-individuation stage was detected during the dream-analysis, and it was the underlying explanation of the claustrophobic symptoms. This qualitative case study implicates the use of a patient’s subjective experiences, such as dreams, to journey through the spiral of the unconscious in order to not only detect repressed memories but to use them in psychotherapy as a means of healing the patient.

Keywords: borderline personality disorder, dream-analysis, Electra complex, separation-individuation, splitting, unconscious

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