Search results for: moving average strategy.

Authors: M. F. Wu, F. T. Cheng, C. S. Wu, M. C. Tan

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It is a critical time to upgrade technology and increase value added with manufacturing skills developing and management strategies that will highly satisfy the customers need in the precision machinery global market. In recent years, the supply side, each precision machinery manufacturers in each country are facing the pressures of price reducing from the demand side voices that pushes the high-end precision machinery manufacturers adopts low-cost and high-quality strategy to retrieve the market. Because of the trend of the global market, the manufacturers must take price reducing strategies and upgrade technology of low-end machinery for differentiations to consolidate the market.By using six key success factors (KSFs), customer perceived value, customer satisfaction, customer service, product design, product effectiveness and machine structure quality are causal conditions to explore the impact of competitive advantage of the enterprise, such as overall profitability and product pricing power. This research uses key success paths (KSPs) approach and f/s QCA software to explore various combinations of causal relationships, so as to fully understand the performance level of KSFs and business objectives in order to achieve competitive advantage. In this study, the combination of a causal relationships, are called Key Success Paths (KSPs). The key success paths guide the enterprise to achieve the specific outcomes of business. The findings of this study indicate that there are thirteen KSPs to achieve the overall profitability, sixteen KSPs to achieve the product pricing power and seventeen KSPs to achieve both overall profitability and pricing power of the enterprise. The KSPs provide the directions of resources integration and allocation, improve utilization efficiency of limited resources to realize the continuous vision of the enterprise.

Keywords: Precision Machinery Industry, Key Success Factors (KSPs), Key Success Paths (KSPs), Overall Profitability, Product Pricing Power, Competitive Advantages.

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Authors: B. Golchin, N. Riahi

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One of the most significant issues as attended a lot in recent years is that of recognizing the sentiments and emotions in social media texts. The analysis of sentiments and emotions is intended to recognize the conceptual information such as the opinions, feelings, attitudes and emotions of people towards the products, services, organizations, people, topics, events and features in the written text. These indicate the greatness of the problem space. In the real world, businesses and organizations are always looking for tools to gather ideas, emotions, and directions of people about their products, services, or events related to their own. This article uses the Twitter social network, one of the most popular social networks with about 420 million active users, to extract data. Using this social network, users can share their information and opinions about personal issues, policies, products, events, etc. It can be used with appropriate classification of emotional states due to the availability of its data. In this study, supervised learning and deep neural network algorithms are used to classify the emotional states of Twitter users. The use of deep learning methods to increase the learning capacity of the model is an advantage due to the large amount of available data. Tweets collected on various topics are classified into four classes using a combination of two Bidirectional Long Short Term Memory network and a Convolutional network. The results obtained from this study with an average accuracy of 93%, show good results extracted from the proposed framework and improved accuracy compared to previous work.

Keywords: emotion classification, sentiment analysis, social networks, deep neural networks

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Authors: Yu Zhang, Ye Tian, Fang Ye Yixuan Kang

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The capacity of conventional cellular networks has reached its upper bound and it can be well handled by introducing femtocells with low-cost and easy-to-deploy. Spectrum interference issue becomes more critical in peace with the value-added multimedia services growing up increasingly in two-tier cellular networks. Spectrum allocation is one of effective methods in interference mitigation technology. This paper proposes a game-theory-based on OFDMA downlink spectrum allocation aiming at reducing co-channel interference in two-tier femtocell networks. The framework is formulated as a non-cooperative game, wherein the femto base stations are players and frequency channels available are strategies. The scheme takes full account of competitive behavior and fairness among stations. In addition, the utility function reflects the interference from the standpoint of channels essentially. This work focuses on co-channel interference and puts forward a negative logarithm interference function on distance weight ratio aiming at suppressing co-channel interference in the same layer network. This scenario is more suitable for actual network deployment and the system possesses high robustness. According to the proposed mechanism, interference exists only when players employ the same channel for data communication. This paper focuses on implementing spectrum allocation in a distributed fashion. Numerical results show that signal to interference and noise ratio can be obviously improved through the spectrum allocation scheme and the users quality of service in downlink can be satisfied. Besides, the average spectrum efficiency in cellular network can be significantly promoted as simulations results shown.

Keywords: Femtocell networks, game theory, interference mitigation, spectrum allocation.

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Authors: Shobhit Mittal

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Headcount budgeting stands as a pivotal element in organizational financial management, extending beyond traditional budgeting to encompass strategic resource allocation for workforce-related expenses. This process is integral to maintaining financial stability and fostering a productive workforce, requiring a comprehensive analysis of factors such as market trends, business growth projections, and evolving workforce skill requirements. It demands a collaborative approach, primarily involving Human Resources (HR) and finance departments, to align workforce planning with an organization's financial capabilities and strategic objectives. The dynamic nature of headcount budgeting necessitates continuous monitoring and adjustment in response to economic fluctuations, business strategy shifts, technological advancements, and market dynamics. Its significance in talent management is also highlighted, aligning financial planning with talent acquisition and retention strategies to ensure a competitive edge in the market. The consequences of incorrect headcount budgeting are explored, showing how it can lead to financial strain, operational inefficiencies, and hindered strategic objectives. Examining case studies like IBM's strategic workforce rebalancing and Microsoft's shift for long-term success, the importance of aligning headcount budgeting with organizational goals is underscored. These examples illustrate that effective headcount budgeting transcends its role as a financial tool, emerging as a strategic element crucial for an organization's success. This necessitates continuous refinement and adaptation to align with evolving business goals and market conditions, highlighting its role as a key driver in organizational success and sustainability.

Keywords: Strategic planning, fiscal budget, headcount planning, resource allocation, financial management, decision-making, operational efficiency, risk management, headcount budget.

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Authors: Chua Bee Seok, Getrude Cosmas, Jasmine Adela Mutang, Shazia Iqbal Hashmi

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The aim of this study was to determine the factor structure and psychometric properties (i.e., reliability and convergent validity) of the Employee Trust Scale, a newly created instrument by the researchers. The Employee Trust Scale initially contained 82 items to measure employees’ trust toward their supervisors. A sample of 818 (343 females, 449 males) employees were selected randomly from public and private organization sectors in Kota Kinabalu, Sabah, Malaysia. Their ages ranged from 19 to 67 years old with a mean of 34.55 years old. Their average tenure with their current employer was 11.2 years (s.d. = 7.5 years). The respondents were asked to complete the Employee Trust Scale, as well as a managerial trust questionnaire from Mishra. The exploratory factor analysis on employees’ trust toward their supervisor’s extracted three factors, labeled ‘trustworthiness’ (32 items), ‘position status’ (11 items) and ‘relationship’ (6 items) which accounted for 62.49% of the total variance. Trustworthiness factors were re-categorized into three sub factors: competency (11 items), benevolence (8 items) and integrity (13 items). All factors and sub factors of the scales demonstrated clear reliability with internal consistency of Cronbach’s Alpha above .85. The convergent validity of the Scale was supported by an expected pattern of correlations (positive and significant correlation) between the score of all factors and sub factors of the scale and the score on the managerial trust questionnaire, which measured the same construct. The convergent validity of Employee Trust Scale was further supported by the significant and positive inter-correlation between the factors and sub factors of the scale. The results suggest that the Employee Trust Scale is a reliable and valid measure. However, further studies need to be carried out in other groups of sample as to further validate the Scale.

Keywords: Employees trust scale, position status, psychometric properties, relationship, trustworthiness.

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Authors: Elvin Çomo, Edlira Tako, Albana Hasimi, Rrapo Ormeni, Olger Gjuzi, Mirela Ndrita

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In Albania, only low-enthalpy geothermal springs and wells are known, the temperatures of some of them are almost at the upper limits of low enthalpy, reaching over 60 °C. These resources can be used to improve the country's energy balance, as well as for profitable economic purposes. The region of Elbasan has the greatest geothermal energy potential in Albania. This basin is one of the most known and most used thermal springs in our country. This area is a surface with a number of sources, located in the form of a chain, in the sector between Llixha and Hidraj and constitutes a thermo-mineral basin with stable discharge and high temperature. The sources of Elbasan Springs, with the current average flow of thermo mineral water of 12-18 l/s and its temperature 55-65 oC, have specific reserves of 39.6 GJ/m2 and potential power to install 2760 kW potential power. For the assessment of physicochemical parameters and heavy metals, water samples were taken at 5 monitoring stations throughout 2022. The levels of basic parameters were analyzed using ISO, EU and APHA standard methods. This study presents the current state of the physicochemical parameters of this thermal basin, the evaluation of these parameters for curative activities and for industrial processes, as well as the integrated utilization of geothermal energy. Thermomineral waters can be utilized for heating homes in the surrounding area or further, depending on the flow from the source or geothermal well. There is awareness among Albanian investors, medical researchers, and the community about the high economic and therapeutic efficiency of the integrated use of geothermal energy in the region and the development of the tourism sector. An analysis of the negative environmental impact from the use of thermal water is also provided.

Keywords: Geothermal energy, Llixha, physicochemical parameters, thermal water.

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Authors: M. Seguini, D. Nedjar

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An accuracy nonlinear analysis of a deep beam resting on elastic perfectly plastic soil is carried out in this study. In fact, a nonlinear finite element modeling for large deflection and moderate rotation of Euler-Bernoulli beam resting on linear and nonlinear random soil is investigated. The geometric nonlinear analysis of the beam is based on the theory of von Kàrmàn, where the Newton-Raphson incremental iteration method is implemented in a Matlab code to solve the nonlinear equation of the soil-beam interaction system. However, two analyses (deterministic and probabilistic) are proposed to verify the accuracy and the efficiency of the proposed model where the theory of the local average based on the Monte Carlo approach is used to analyze the effect of the spatial variability of the soil properties on the nonlinear beam response. The effect of six main parameters are investigated: the external load, the length of a beam, the coefficient of subgrade reaction of the soil, the Young’s modulus of the beam, the coefficient of variation and the correlation length of the soil’s coefficient of subgrade reaction. A comparison between the beam resting on linear and nonlinear soil models is presented for different beam’s length and external load. Numerical results have been obtained for the combination of the geometric nonlinearity of beam and material nonlinearity of random soil. This comparison highlighted the need of including the material nonlinearity and spatial variability of the soil in the geometric nonlinear analysis, when the beam undergoes large deflections.

Keywords: Finite element method, geometric nonlinearity, material nonlinearity, soil-structure interaction, spatial variability.

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Authors: T. Holden, G. Tremberger, Jr, E. Cheung, R. Subramaniam, R. Sullivan, N. Gadura, P. Schneider, P. Marchese, A. Flamholz, T. Cheung, D. Lieberman

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A nucleotide sequence can be expressed as a numerical sequence when each nucleotide is assigned its proton number. A resulting gene numerical sequence can be investigated for its fractal dimension in terms of evolution and chemical properties for comparative studies. We have investigated such nucleotide fluctuation in the 16S rRNA gene of archaea thermophiles. The studied archaea thermophiles were archaeoglobus fulgidus, methanothermobacter thermautotrophicus, methanocaldococcus jannaschii, pyrococcus horikoshii, and thermoplasma acidophilum. The studied five archaea-euryarchaeota thermophiles have fractal dimension values ranging from 1.93 to 1.97. Computer simulation shows that random sequences would have an average of about 2 with a standard deviation about 0.015. The fractal dimension was found to correlate (negative correlation) with the thermophile-s optimal growth temperature with R2 value of 0.90 (N =5). The inclusion of two aracheae-crenarchaeota thermophiles reduces the R2 value to 0.66 (N = 7). Further inclusion of two bacterial thermophiles reduces the R2 value to 0.50 (N =9). The fractal dimension is correlated (positive) to the sequence GC content with an R2 value of 0.89 for the five archaea-euryarchaeota thermophiles (and 0.74 for the entire set of N = 9), although computer simulation shows little correlation. The highest correlation (positive) was found to be between the fractal dimension and di-nucleotide Shannon entropy. However Shannon entropy and sequence GC content were observed to correlate with optimal growth temperature having an R2 of 0.8 (negative), and 0.88 (positive), respectively, for the entire set of 9 thermophiles; thus the correlation lacks species specificity. Together with another correlation study of bacterial radiation dosage with RecA repair gene sequence fractal dimension, it is postulated that fractal dimension analysis is a sensitive tool for studying the relationship between genotype and phenotype among closely related sequences.

Keywords: Fractal dimension, archaea thermophiles, Shannon entropy, GC content

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Authors: Diptendu Das, Vikas Kumar Rahi, V. A. Juvekar, R. Bhattacharya

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Extraction of Fe(III) from aqueous solution using Trin- butyl Phosphate (TBP) as carrier needs a highly acidic medium (>6N) as it favours formation of chelating complex FeCl3.TBP. Similarly, stripping of Iron(III) from loaded organic solvents requires neutral pH or alkaline medium to dissociate the same complex. It is observed that TBP co-extracts acids along with metal, which causes reversal of driving force of extraction and iron(III) is re-extracted back from the strip phase into the feed phase during Liquid Emulsion Membrane (LEM) pertraction. Therefore, rate of extraction of different mineral acids (HCl, HNO3, H2SO4) using TBP with and without presence of metal Fe(III) was examined. It is revealed that in presence of metal acid extraction is enhanced. Determination of mass transfer coefficient of both acid and metal extraction was performed by using Bulk Liquid Membrane (BLM). The average mass transfer coefficient was obtained by fitting the derived model equation with experimentally obtained data. The mass transfer coefficient of the mineral acid extraction is in the order of kHNO3 = 3.3x10-6m/s > kHCl = 6.05x10-7m/s > kH2SO4 = 1.85x10-7m/s. The distribution equilibria of the above mentioned acids between aqueous feed solution and a solution of tri-n-butyl-phosphate (TBP) in organic solvents have been investigated. The stoichiometry of acid extraction reveals the formation of TBP.2HCl, HNO3.2TBP, and TBP.H2SO4 complexes. Moreover, extraction of Iron(III) by TBP in HCl aqueous solution forms complex FeCl3.TBP.2HCl while in HNO3 medium forms complex 3FeCl3.TBP.2HNO3

Keywords: Bulk Liquid Membrane (BLM) Transport, Iron(III) extraction, Tri-n-butyl Phosphate, Mass Transfer coefficient.

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Authors: Sevgi Özlem Bulu, Arif Furkan Mendi, Tolga Erol, İzzet Gökhan Özbilgin

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The rapid progress of technology in today's competitive conditions has also accelerated companies' technology development activities. As a result, companies are paying more attention to R&D studies and are beginning to allocate a larger share to R&D projects. A more systematic, comprehensive, target-oriented implementation of R&D studies is crucial for the company to achieve successful results. As a consequence, Technology Roadmap (TRM) is gaining importance as a management tool. It has critical prospects for achieving medium and long term success as it contains decisions about past business, future plans, technological infrastructure. When studies on TRM are examined, projects to be placed on the roadmap are selected by many different methods. Generally preferred methods are based on multi-criteria decision making methods. Management of selected projects becomes an important point after the selection phase of the projects. At this stage, TRM are used. TRM can be created in many different ways so that each institution can prepare its own Technology Roadmap according to their strategic plan. Depending on the intended use, there can be TRM with different layers at different sizes. In the evaluation phase of the R&D projects and in the creation of the TRM, HAVELSAN, Turkey's largest defense company in the software field, carries out this process with great care and diligence. At the beginning, suggested R&D projects are evaluated by the Technology Management Board (TMB) of HAVELSAN in accordance with the company's resources, objectives, and targets. These projects are presented to the TMB periodically for evaluation within the framework of certain criteria by board members. After the necessary steps have been passed, the approved projects are added to the time-based TRM, which is composed of four layers as market, product, project and technology. The use of a four-layered roadmap provides a clearer understanding and visualization of company strategy and objectives. This study demonstrates the benefits of using TRM, four-layered Technology Roadmapping and the possibilities for the institutions in the defense industry.

Keywords: Project selection, R&D in defense industry, R&D project selection, technology roadmapping.

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Authors: D. Mokhtari

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Any variation in environmental characteristics of geomorphosites would lead to destabilisation of their geotouristic values all around the planet. The Urmia lake, with an area of approximately 5,500 km2 and a catchment area of 51,876 km2, and to which various reasons over time, especially in the last fifty years have seen a sharp decline and have decreased by about 93 % in two recent decades. These variations are not only driving significant changes in the morphology and ecology of the present lake landscape, but at the same time are shaping newly formed morphologies, which vanished some valuable geomorphosites or develop into smaller geomorphosites with significant value from a scientific and cultural point of view. This paper analyses and discusses features and evolution in several representative coastal and island geomorphosites. For this purpose, a total of 23 geomorphosites were studied in two data series (1963 and 2015) and the respective data were compared and analysed. The results showed, the total loss in geomorphosites area in a half century amounted to a loss of more than 90% of the valuable geomorphosites. Moreover, the comparison between the mean yearly value of coastal area lost over the entire period and the yearly average calculated for the shorter period (1998- 2014) clearly indicates a pattern of acceleration. This acceleration in the rate of reduction in lake area was seen in most of the southern half of the lake. In the region as well, the general water-level falling is not only causing the loss of a significant water resource, which is followed by major impact on regional ecosystems, but is also driving the most marked recent (last century) changes in the geotouristic landscapes. In fact, the disappearance of geomorphosites means the loss of tourism phenomenon. In this context attention must be paid to the question of conservation. The action needed to safeguard geomorphosites includes: 1) Preventive action, 2) Corrective action, and 3) Sharing knowledge.

Keywords: Changing lake, environmental changes, geomorphosite, northwest of Iran, Urmia lake.

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Authors: Kanokkan Titipornpun, Tripob Bhongsuwan, Jan Gimsa

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The Ko Samui district of Surat Thani province is located in the high amounts of equivalent uranium in the ground surface that is the source of radon. Our research in the Ko Samui district aimed at comparing the indoor radon concentrations between dwellings and workplaces. Measurements of indoor radon concentrations were carried out in 46 dwellings and 127 workplaces, using CR-39 alpha-track detectors in closed-cup. A total of 173 detectors were distributed in 7 sub-districts. The detectors were placed in bedrooms of dwellings and workrooms of workplaces. All detectors were exposed to airborne radon for 90 days. After exposure, the alpha tracks were made visible by chemical etching before they were manually counted under an optical microscope. The track densities were assumed to be correlated with the radon concentration levels. We found that the radon concentrations could be well described by a log-normal distribution. Most concentrations (37%) were found in the range between 16 and 30 Bq.m^-3. The radon concentrations in dwellings and workplaces varied from a minimum of 11 Bq.m^-3 to a maximum of 305 Bq.m^-3. The minimum (11 Bq.m^-3) and maximum (305 Bq.m^-3) values of indoor radon concentrations were found in a workplace and a dwelling, respectively. Only for four samples (3%), the indoor radon concentrations were found to be higher than the reference level recommended by the WHO (100 Bq.m^-3). The overall geometric mean in the surveyed area was 32.6±1.65 Bq.m^-3, which was lower than the worldwide average (39 Bq.m^-3). The statistic comparison of the geometric mean indoor radon concentrations between dwellings and workplaces showed that the geometric mean in dwellings (46.0±1.55 Bq.m^-3) was significantly higher than in workplaces (28.8±1.58 Bq.m^-3) at the 0.05 level. Moreover, our study found that the majority of the bedrooms in dwellings had a closed atmosphere, resulting in poorer ventilation than in most of the workplaces that had access to air flow through open doors and windows at daytime. We consider this to be the main reason for the higher geometric mean indoor radon concentration in dwellings compared to workplaces.

Keywords: CR-39 detector, indoor radon, radon in dwelling, radon in workplace.

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Authors: Xiaoshu Lu, Esa-Pekka Takala, Risto Toivonen

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This paper systematically investigates the timedependent health outcomes for office staff during computer work using the developed mathematical model. The model describes timedependent health outcomes in multiple body regions associated with computer usage. The association is explicitly presented with a doseresponse relationship which is parametrized by body region parameters. Using the developed model we perform extensive investigations of the health outcomes statically and dynamically. We compare the risk body regions and provide various severity rankings of the discomfort rate changes with respect to computer-related workload dynamically for the study population. Application of the developed model reveals a wide range of findings. Such broad spectrum of investigations in a single report literature is lacking. Based upon the model analysis, it is discovered that the highest average severity level of the discomfort exists in neck, shoulder, eyes, shoulder joint/upper arm, upper back, low back and head etc. The biggest weekly changes of discomfort rates are in eyes, neck, head, shoulder, shoulder joint/upper arm and upper back etc. The fastest discomfort rate is found in neck, followed by shoulder, eyes, head, shoulder joint/upper arm and upper back etc. Most of our findings are consistent with the literature, which demonstrates that the developed model and results are applicable and valuable and can be utilized to assess correlation between the amount of computer-related workload and health risk.

Keywords: Computer-related workload, health outcomes, dynamic association, dose-response relationship, systematic analysis.

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Authors: Sourabh Jain, Sukhvir Singh Jain, Gaurav V. Jain

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Intelligent Transportation System (ITS) is the application of technology for developing a user–friendly transportation system for urban areas in developing countries. The goal of urban corridor management using ITS in road transport is to achieve improvements in mobility, safety, and the productivity of the transportation system within the available facilities through the integrated application of advanced monitoring, communications, computer, display, and control process technologies, both in the vehicle and on the road. This paper attempts to present the past studies regarding several ITS available that have been successfully deployed in urban corridors of India and abroad, and to know about the current scenario and the methodology considered for planning, design, and operation of Traffic Management Systems. This paper also presents the endeavor that was made to interpret and figure out the performance of the 27.4 Km long study corridor having eight intersections and four flyovers. The corridor consisting of 6 lanes as well as 8 lanes divided road network. Two categories of data were collected on February 2016 such as traffic data (traffic volume, spot speed, delay) and road characteristics data (no. of lanes, lane width, bus stops, mid-block sections, intersections, flyovers). The instruments used for collecting the data were video camera, radar gun, mobile GPS and stopwatch. From analysis, the performance interpretations incorporated were identification of peak hours and off peak hours, congestion and level of service (LOS) at mid blocks, delay followed by the plotting speed contours and recommending urban corridor management strategies. From the analysis, it is found that ITS based urban corridor management strategies will be useful to reduce congestion, fuel consumption and pollution so as to provide comfort and efficiency to the users. The paper presented urban corridor management strategies based on sensors incorporated in both vehicles and on the roads.

Keywords: Congestion, ITS Strategies, Mobility, Safety.

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Authors: Amirali Shirazibeheshti, Tarik Radwan, Alireza Ettefaghian, Farbod Khanizadeh, George Wilson, Cristina Luca

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Anticholinergic medication has been associated with events such as falls, delirium, and cognitive impairment in older patients. To further assess this, anticholinergic burden scores have been developed to quantify risk. A risk model based on clustering was deployed in a healthcare management system to cluster patients into multiple risk groups according to anticholinergic burden scores of multiple medicines prescribed to patients to facilitate clinical decision-making. To do so, anticholinergic burden scores of drugs were extracted from the literature which categorizes the risk on a scale of 1 to 3. Given the patients’ prescription data on the healthcare database, a weighted anticholinergic risk score was derived per patient based on the prescription of multiple anticholinergic drugs. This study was conducted on 300,000 records of patients currently registered with a major regional UK-based healthcare provider. The weighted risk scores were used as inputs to an unsupervised learning algorithm (mean-shift clustering) that groups patients into clusters that represent different levels of anticholinergic risk. This work evaluates the association between the average risk score and measures of socioeconomic status (index of multiple deprivation) and health (index of health and disability). The clustering identifies a group of 15 patients at the highest risk from multiple anticholinergic medication. Our findings show that this group of patients is located within more deprived areas of London compared to the population of other risk groups. Furthermore, the prescription of anticholinergic medicines is more skewed to female than male patients, suggesting that females are more at risk from this kind of multiple medication. The risk may be monitored and controlled in a healthcare management system that is well-equipped with tools implementing appropriate techniques of artificial intelligence.

Keywords: Anticholinergic medication, socioeconomic status, deprivation, clustering, risk analysis.

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Authors: Shahram Nowrouzieh, Abbas Rezaei Asl, Mohamad Ali Jafari

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Cotton, as a strategic crop, plays an important role in providing human food and clothing need, because of its oil, protein, and fiber. Iran has been one of the largest cotton producers in the world in the past, but unfortunately, for economic reasons, its production is reduced now. One of the ways to reduce the cost of cotton production is to expand the mechanization of cotton harvesting. Iranian farmers do not accept the function of cotton harvesters. One reason for this lack of acceptance of cotton harvesting machines is the number of field losses on these machines. So, the majority of cotton fields are harvested by hand. Although the correct setting of the harvesting machine is very important in the cotton losses, the morphological properties of the cotton plant also affect the performance of cotton harvesters. In this study, the effect of some cotton morphological properties such as the height of the cotton plant, number, and length of sympodial and monopodial branches, boll dimensions, boll weight, number of carpels and bracts angle were evaluated on the performance of cotton picker. In this research, the efficiency of John Deere 9920 spindle Cotton picker is investigated on five different Iranian cotton cultivars. The results indicate that there was a significant difference between the five cultivars in terms of machine harvest efficiency. Golestan cultivar showed the best cotton harvester performance with an average of 87.6% of total harvestable seed cotton and Khorshid cultivar had the least cotton harvester performance. The principal component analysis showed that, at 50.76% probability, the cotton picker efficiency is affected by the bracts angle positively and by boll dimensions, the number of carpels and the height of cotton plants negatively. The seed cotton remains (in the plant and on the ground) after harvester in PCA scatter plot were in the same zone with boll dimensions and several carpels.

Keywords: Cotton, bract, harvester, carpel.

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Authors: Diana Flores Galindo, Richard Gil Herrera

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Nowadays, Lean Manufacturing and Industry 4.0 are very important in every country. One of the main benefits is continued market presence. It has been identified that there is a need to change existing educational programs, as well as update the knowledge and skills of existing employees. It should be borne in mind that behind each technological improvement, there is a human being. Human talent cannot be neglected. The main objectives of this article are to review the link between Lean Manufacturing, the incorporation of Industry 4.0 and the steps to follow to implement it; analyze the current situation and study the implications and benefits of this new trend, with a particular focus on Mexico. Lean Manufacturing and Industry 4.0 implementation waves must always take care of the most important capital – intellectual capital. The methodology used in this article comprised the following steps: reviewing the reality of the fourth industrial revolution, reviewing employees’ skills on the journey to become world-class, and analyzing the situation in Mexico. Lean Manufacturing and Industry 4.0 were studied not as exclusive concepts, but as complementary ones. The methodological framework used is focused on motivating companies’ collaborators to guarantee common results, innovate, and remain in the market in the face of new requirements from company stakeholders. The key findings were that both trends emphasize the need to improve communication across the entire company and incorporate new technologies into everyday work, from the shop floor to administrative staff, to help improve processes. Taking care of people, activities and processes will bring a company success. In the specific case of Mexico, companies in all sectors need to be aware of and implement technological improvements according to their specific needs. Low-cost labor represents one of the most typical barriers. In conclusion, companies must build a roadmap according to their strategy and needs to achieve their short, medium- and long-term goals.

Keywords: Lean management, lean manufacturing, industry 4.0, motivation, SWOT analysis, Hoshin Kanri.

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Authors: Bryce Benson, Sooin Lee, Ashwin Belle

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Unrecognized or delayed identification of patient deterioration is a key cause of in-hospitals adverse events. Clinicians rely on vital signs monitoring to recognize patient deterioration. However, due to ever increasing nursing workloads and the manual effort required, vital signs tend to be measured and recorded intermittently, and inconsistently causing large gaps during patient monitoring. Additionally, during deterioration, the body’s autonomic nervous system activates compensatory mechanisms causing the vital signs to be lagging indicators of underlying hemodynamic decline. This study analyzes the predictive efficacy of the Analytic for Hemodynamic Instability (AHI) system, an automated tool that was designed to help clinicians in early identification of deteriorating patients. The lead time analysis in this retrospective observational study assesses how far in advance AHI predicted deterioration prior to the start of an episode of hemodynamic instability (HI) becoming evident through vital signs? Results indicate that of the 362 episodes of HI in this study, 308 episodes (85%) were correctly predicted by the AHI system with a median lead time of 57 minutes and an average of 4 hours (240.5 minutes). Of the 54 episodes not predicted, AHI detected 45 of them while the episode of HI was ongoing. Of the 9 undetected, 5 were not detected by AHI due to either missing or noisy input ECG data during the episode of HI. In total, AHI was able to either predict or detect 98.9% of all episodes of HI in this study. These results suggest that AHI could provide an additional ‘pair of eyes’ on patients, continuously filling the monitoring gaps and consequently giving the patient care team the ability to be far more proactive in patient monitoring and adverse event management.

Keywords: Clinical deterioration prediction, decision support system, early warning system, hemodynamic status, physiologic monitoring.

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Authors: Faiza Belbachir, Thibault Schienhinski

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The massive development of online social networks allows users to post and share their opinions on various topics. With this huge volume of opinion, it is interesting to extract and interpret these information for different domains, e.g., product and service benchmarking, politic, system of recommendation. This is why opinion detection is one of the most important research tasks. It consists on differentiating between opinion data and factual data. The difficulty of this task is to determine an approach which returns opinionated document. Generally, there are two approaches used for opinion detection i.e. Lexical based approaches and Machine Learning based approaches. In Lexical based approaches, a dictionary of sentimental words is used, words are associated with weights. The opinion score of document is derived by the occurrence of words from this dictionary. In Machine learning approaches, usually a classifier is trained using a set of annotated document containing sentiment, and features such as n-grams of words, part-of-speech tags, and logical forms. Majority of these works are based on documents text to determine opinion score but dont take into account if these texts are really correct. Thus, it is interesting to exploit other information to improve opinion detection. In our work, we will develop a new way to consider the opinion score. We introduce the notion of trust score. We determine opinionated documents but also if these opinions are really trustable information in relation with topics. For that we use lexical SentiWordNet to calculate opinion and trust scores, we compute different features about users like (numbers of their comments, numbers of their useful comments, Average useful review). After that, we combine opinion score and trust score to obtain a final score. We applied our method to detect trust opinions in TRIPADVISOR collection. Our experimental results report that the combination between opinion score and trust score improves opinion detection.

Keywords: Tripadvisor, Opinion detection, SentiWordNet, trust score.

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Authors: Dongxiao Sun-Waterhouse, Shiji Nair, Reginald Wibisono, Sandhya S. Wadhwa, Carl Massarotto, Duncan I. Hedderley, Jing Zhou, Sara R. Jaeger, Virginia Corrigan

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Attempts to add fibre and polyphenols (PPs) into popular beverages present challenges related to the properties of finished products such as smoothies. Consumer acceptability, viscosity and phenolic composition of smoothies containing high levels of fruit fibre (2.5-7.5 g per 300 mL serve) and PPs (250-750 mg per 300 mL serve) were examined. The changes in total extractable PP, vitamin C content, and colour of selected smoothies over a storage stability trial (4°C, 14 days) were compared. A set of acidic aqueous model beverages were prepared to further examine the effect of two different heat treatments on the stability and extractability of PPs. Results show that overall consumer acceptability of high fibre and PP smoothies was low, with average hedonic scores ranging from 3.9 to 6.4 (on a 1-9 scale). Flavour, texture and overall acceptability decreased as fibre and polyphenol contents increased, with fibre content exerting a stronger effect. Higher fibre content resulted in greater viscosity, with an elevated PP content increasing viscosity only slightly. The presence of fibre also aided the stability and extractability of PPs after heating. A reduction of extractable PPs, vitamin C content and colour intensity of smoothies was observed after a 14-day storage period at 4°C. Two heat treatments (75°C for 45 min or 85°C for 1 min) that are normally used for beverage production, did not cause significant reduction of total extracted PPs. It is clear that high levels of added fibre and PPs greatly influence the consumer appeal of smoothies, suggesting the need to develop novel formulation and processing methods if a satisfactory functional beverage is to be developed incorporating these ingredients.

Keywords: Apple fibre, apple and blackcurrant polyphenols, consumer acceptability, functional foods, stability.

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Authors: Amit Chhabra, Gurvinder Singh, Sandeep Singh Waraich, Bhavneet Sidhu, Gaurav Kumar

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Decrease in hardware costs and advances in computer networking technologies have led to increased interest in the use of large-scale parallel and distributed computing systems. One of the biggest issues in such systems is the development of effective techniques/algorithms for the distribution of the processes/load of a parallel program on multiple hosts to achieve goal(s) such as minimizing execution time, minimizing communication delays, maximizing resource utilization and maximizing throughput. Substantive research using queuing analysis and assuming job arrivals following a Poisson pattern, have shown that in a multi-host system the probability of one of the hosts being idle while other host has multiple jobs queued up can be very high. Such imbalances in system load suggest that performance can be improved by either transferring jobs from the currently heavily loaded hosts to the lightly loaded ones or distributing load evenly/fairly among the hosts .The algorithms known as load balancing algorithms, helps to achieve the above said goal(s). These algorithms come into two basic categories - static and dynamic. Whereas static load balancing algorithms (SLB) take decisions regarding assignment of tasks to processors based on the average estimated values of process execution times and communication delays at compile time, Dynamic load balancing algorithms (DLB) are adaptive to changing situations and take decisions at run time. The objective of this paper work is to identify qualitative parameters for the comparison of above said algorithms. In future this work can be extended to develop an experimental environment to study these Load balancing algorithms based on comparative parameters quantitatively.

Keywords: SLB, DLB, Host, Algorithm and Load.

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Authors: P. R. Prabhu, S. M. Kulkarni, S. S. Sharma, K. Jagannath, Achutha Kini U.

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In the present study, response surface methodology has been used to optimize turn-assisted deep cold rolling process of AISI 4140 steel. A regression model is developed to predict surface hardness and surface roughness using response surface methodology and central composite design. In the development of predictive model, deep cold rolling force, ball diameter, initial roughness of the workpiece, and number of tool passes are considered as model variables. The rolling force and the ball diameter are the significant factors on the surface hardness and ball diameter and numbers of tool passes are found to be significant for surface roughness. The predicted surface hardness and surface roughness values and the subsequent verification experiments under the optimal operating conditions confirmed the validity of the predicted model. The absolute average error between the experimental and predicted values at the optimal combination of parameter settings for surface hardness and surface roughness is calculated as 0.16% and 1.58% respectively. Using the optimal processing parameters, the surface hardness is improved from 225 to 306 HV, which resulted in an increase in the near surface hardness by about 36% and the surface roughness is improved from 4.84µm to 0.252 µm, which resulted in decrease in the surface roughness by about 95%. The depth of compression is found to be more than 300µm from the microstructure analysis and this is in correlation with the results obtained from the microhardness measurements. Taylor hobson talysurf tester, micro vickers hardness tester, optical microscopy and X-ray diffractometer are used to characterize the modified surface layer. 

Keywords: Surface hardness, response surface methodology, microstructure, central composite design, deep cold rolling, surface roughness.

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Authors: Anand B. Desamala, Ashok Kumar Dasamahapatra, Tapas K. Mandal

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In the present work, detailed analysis on flow characteristics of a pair of immiscible liquids through horizontal pipeline is simulated by using ANSYS FLUENT 6.2. Moderately viscous oil and water (viscosity ratio = 107, density ratio = 0.89 and interfacial tension = 0.024 N/m) have been taken as system fluids for the study. Volume of Fluid (VOF) method has been employed by assuming unsteady flow, immiscible liquid pair, constant liquid properties, and co-axial flow. Meshing has been done using GAMBIT. Quadrilateral mesh type has been chosen to account for the surface tension effect more accurately. From the grid independent study, we have selected 47037 number of mesh elements for the entire geometry. Simulation successfully predicts slug, stratified wavy, stratified mixed and annular flow, except dispersion of oil in water, and dispersion of water in oil. Simulation results are validated with horizontal literature data and good conformity is observed. Subsequently, we have simulated the hydrodynamics (viz., velocity profile, area average pressure across a cross section and volume fraction profile along the radius) of stratified wavy and annular flow at different phase velocities. The simulation results show that in the annular flow, total pressure of the mixture decreases with increase in oil velocity due to the fact that pipe cross section is completely wetted with water. Simulated oil volume fraction shows maximum at the centre in core annular flow, whereas, in stratified flow, maximum value appears at upper side of the pipeline. These results are in accord with the actual flow configuration. Our findings could be useful in designing pipeline for transportation of crude oil.

Keywords: CFD, Horizontal pipeline, Oil-water flow, VOF technique.

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Authors: Manfred Szerencsits, Christine Weinberger, Maximilian Kuderna, Franz Feichtinger, Eva Erhart, Stephan Maier

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Cover or catch crops have beneficial effects for soil, water, erosion, etc. If harvested, they also provide feedstock for biogas without competition for arable land in regions, where only one main crop can be produced per year. On average gross energy yields of approx. 1300 m³ methane (CH₄) ha^-1 can be expected from 4.5 tonnes (t) of cover crop dry matter (DM) in Austria. Considering the total energy invested from cultivation to compression for biofuel use a net energy yield of about 1000 m³ CH₄ ha^-1 is remaining. With the straw of grain maize or Corn Cob Mix (CCM) similar energy yields can be achieved. In comparison to catch crops remaining on the field as green manure or to complete fallow between main crops the effects on soil, water and climate can be improved if cover crops are harvested without soil compaction and digestate is returned to the field in an amount equivalent to cover crop removal. In this way, the risk of nitrate leaching can be reduced approx. by 25% in comparison to full fallow. The risk of nitrous oxide emissions may be reduced up to 50% by contrast with cover crops serving as green manure. The effects on humus content and erosion are similar or better than those of cover crops used as green manure when the same amount of biomass was produced. With higher biomass production the positive effects increase even if cover crops are harvested and the only digestate is brought back to the fields. The ecological footprint of arable farming can be reduced by approx. 50% considering the substitution of natural gas with CH₄ produced from cover crops.

Keywords: Biogas, cover crops, catch crops, land use competition, sustainable agriculture.

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Authors: Adel Dalilottojari, Bahman Delalat, Frances J. Harding, Michaelia P. Cockshell, Claudine S. Bonder, Nicolas H. Voelcker

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Endothelial Progenitor Cell (EPC) based therapies continue to be of interest to treat ischemic events based on their proven role to promote blood vessel formation and thus tissue re-vascularisation. Current strategies for the production of clinical-grade EPCs requires the in vitro isolation of EPCs from peripheral blood followed by cell expansion to provide sufficient quantities EPCs for cell therapy. This study aims to examine the use of different biomolecules to significantly improve the current strategy of EPC capture and expansion on collagen type I (Col I). In this study, four different biomolecules were immobilised on a surface and then investigated for their capacity to support EPC capture and proliferation. First, a cell microarray platform was fabricated by coating a glass surface with epoxy functional allyl glycidyl ether plasma polymer (AGEpp) to mediate biomolecule binding. The four candidate biomolecules tested were Col I, collagen type II (Col II), collagen type IV (Col IV) and vascular endothelial growth factor A (VEGF-A), which were arrayed on the epoxy-functionalised surface using a non-contact printer. The surrounding area between the printed biomolecules was passivated with polyethylene glycol-bisamine (A-PEG) to prevent non-specific cell attachment. EPCs were seeded onto the microarray platform and cell numbers quantified after 1 h (to determine capture) and 72 h (to determine proliferation). All of the extracellular matrix (ECM) biomolecules printed demonstrated an ability to capture EPCs within 1 h of cell seeding with Col II exhibiting the highest level of attachment when compared to the other biomolecules. Interestingly, Col IV exhibited the highest increase in EPC expansion after 72 h when compared to Col I, Col II and VEGF-A. These results provide information for significant improvement in the capture and expansion of human EPC for further application.

Keywords: Cardiovascular disease, cell microarray platform, cell therapy, endothelial progenitor cells, high throughput screening.

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Authors: Alaa Hussein Wadi

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The principal objective of a water treatment plant is to produce water that satisfies a set of drinking water quality standards at a reasonable price to the consumers. The gravel-bed flocculator provide a simple and inexpensive design for flocculation in small water treatment plants (less than 5000 m3/day capacity). The packed bed of gravel provides ideal conditions for the formation of compact settleable flocs because of continuous recontact provided by the sinuous flow of water through the interstices formed by the gravel. The field data which were obtained from the operation of the water supply treatment unit cover the physical, chemical and biological water qualities of the raw and settled water as obtained by the operation of the treatment unit. The experiments were carried out with the aim of assessing the efficiency of the gravel filter in removing the turbidity, pathogenic bacteria, from the raw water. The water treatment plant, which was constructed for the treatment of river water, was in principle a rapid sand filter. The results show that the average value of the turbidity level of the settled water was 4.83 NTU with a standard deviation of turbidity 2.893 NTU. This indicated that the removal efficiency of the sedimentation tank (gravel filter) was about 67.8 %. for pH values fluctuated between 7.75 and 8.15, indicating the alkaline nature of the raw water of the river Shatt Al-Hilla, as expected. Raw water pH is depressed slightly following alum coagulation. The pH of the settled water ranged from 7.75 to a maximum of 8.05. The bacteriological tests which were carried out on the water samples were: total coliform test, E-coli test, and the plate count test. In each test the procedure used was as outlined in the Standard Methods for the Examination of Water and Wastewater (APHA, AWWA, and WPCF, 1985). The gravel filter exhibit a low performance in removing bacterial load. The percentage bacterial removal, which is maximum for total plate count (19%) and minimum for total coliform (16.82%).

Keywords: Gravel bed flocculator, turbidity, total coliform.

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Authors: Laurent Pitteloud, Jörg Meier

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Piled raft foundations represent an efficient and reliable technique for transferring high vertical and horizontal loads to the subsoil. Piled raft foundations were success­fully implemented for several high-rise buildings world­wide over the last decades. For the structural design of this foundation type the stiffnesses of both the piles and the raft have to be deter­mined for the static (e.g. dead load, live load) and the dynamic load cases (e.g. earthquake). In this context the question often arises, to which proportion wind loads are to be considered as dynamic loads. Usually a piled raft foundation has to be monitored in order to verify the design hypotheses. As an additional benefit, the analysis of this monitoring data may lead to a better under­standing of the behaviour of this foundation type for future projects in similar subsoil conditions. In case the measurement frequency is high enough, one may also draw conclusions on the effect of wind loading on the piled raft foundation. For a 41-storey office building in Basel, Switzerland, the preliminary design showed that a piled raft foundation was the best solution to satisfy both design requirements, as well as economic aspects. A high-frequency monitoring of the foundation including pile loads, vertical stresses under the raft, as well as pore water pressures was performed over 5 years. In windy situations the analysis of the measure­ments shows that the pile load increment due to wind consists of a static and a cyclic load term. As piles and raft react with different stiffnesses under static and dynamic loading, these measure­ments are useful for the correct definition of stiffnesses of future piled raft foundations. This paper outlines the design strategy and the numerical modelling of the aforementioned piled raft foundation. The measurement results are presented and analysed. Based on the findings, comments and conclusions on the definition of pile and raft stiffnesses for vertical and wind loading are proposed.

Keywords: Dynamic loading, high-frequency monitoring, piled raft foundations, wind loading.

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Authors: Svetlana Cojocaru, Mircea Petic, Inga Titchiev

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Humanity faces more and more often with different social disasters, which in turn can generate new accidents and catastrophes. To mitigate their consequences, it is important to obtain early possible signals about the events which are or can occur and to prepare the corresponding scenarios that could be applied. Our research is focused on solving two problems in this domain: identifying signals related that an accident occurred or may occur and mitigation of some consequences of disasters. To solve the first problem, methods of selecting and processing texts from global network Internet are developed. Information in Romanian is of special interest for us. In order to obtain the mentioned tools, we should follow several steps, divided into preparatory stage and processing stage. Throughout the first stage, we manually collected over 724 news articles and classified them into 10 categories of social disasters. It constitutes more than 150 thousand words. Using this information, a controlled vocabulary of more than 300 keywords was elaborated, that will help in the process of classification and identification of the texts related to the field of social disasters. To solve the second problem, the formalism of Petri net has been used. We deal with the problem of inhabitants’ evacuation in useful time. The analysis methods such as reachability or coverability tree and invariants technique to determine dynamic properties of the modeled systems will be used. To perform a case study of properties of extended evacuation system by adding time, the analysis modules of PIPE such as Generalized Stochastic Petri Nets (GSPN) Analysis, Simulation, State Space Analysis, and Invariant Analysis have been used. These modules helped us to obtain the average number of persons situated in the rooms and the other quantitative properties and characteristics related to its dynamics.

Keywords: Lexicon of disasters, modelling, Petri nets, text annotation, social disasters.

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Authors: Yehjune Heo

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As biometric systems become widely deployed, the security of identification systems can be easily attacked by various spoof materials. This paper contributes to finding a reliable and practical anti-spoofing method using Convolutional Neural Networks (CNNs) based on the types of loss functions and optimizers. The types of CNNs used in this paper include AlexNet, VGGNet, and ResNet. By using various loss functions including Cross-Entropy, Center Loss, Cosine Proximity, and Hinge Loss, and various loss optimizers which include Adam, SGD, RMSProp, Adadelta, Adagrad, and Nadam, we obtained significant performance changes. We realize that choosing the correct loss function for each model is crucial since different loss functions lead to different errors on the same evaluation. By using a subset of the Livdet 2017 database, we validate our approach to compare the generalization power. It is important to note that we use a subset of LiveDet and the database is the same across all training and testing for each model. This way, we can compare the performance, in terms of generalization, for the unseen data across all different models. The best CNN (AlexNet) with the appropriate loss function and optimizers result in more than 3% of performance gain over the other CNN models with the default loss function and optimizer. In addition to the highest generalization performance, this paper also contains the models with high accuracy associated with parameters and mean average error rates to find the model that consumes the least memory and computation time for training and testing. Although AlexNet has less complexity over other CNN models, it is proven to be very efficient. For practical anti-spoofing systems, the deployed version should use a small amount of memory and should run very fast with high anti-spoofing performance. For our deployed version on smartphones, additional processing steps, such as quantization and pruning algorithms, have been applied in our final model.

Keywords: Anti-spoofing, CNN, fingerprint recognition, loss function, optimizer.

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Authors: Wang Yichen, Haruka Yamashita

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In recent years, in the field of sports, decision making such as member in the game and strategy of the game based on then analysis of the accumulated sports data are widely attempted. In fact, in the NBA basketball league where the world's highest level players gather, to win the games, teams analyze the data using various statistical techniques. However, it is difficult to analyze the game data for each play such as the ball tracking or motion of the players in the game, because the situation of the game changes rapidly, and the structure of the data should be complicated. Therefore, it is considered that the analysis method for real time game play data is proposed. In this research, we propose an analytical model for "determining the optimal lineup composition" using the real time play data, which is considered to be difficult for all coaches. In this study, because replacing the entire lineup is too complicated, and the actual question for the replacement of players is "whether or not the lineup should be changed", and “whether or not Small Ball lineup is adopted”. Therefore, we propose an analytical model for the optimal player selection problem based on Small Ball lineups. In basketball, we can accumulate scoring data for each play, which indicates a player's contribution to the game, and the scoring data can be considered as a time series data. In order to compare the importance of players in different situations and lineups, we combine RNN (Recurrent Neural Network) model, which can analyze time series data, and NN (Neural Network) model, which can analyze the situation on the field, to build the prediction model of score. This model is capable to identify the current optimal lineup for different situations. In this research, we collected all the data of accumulated data of NBA from 2019-2020. Then we apply the method to the actual basketball play data to verify the reliability of the proposed model.

Keywords: Recurrent Neural Network, players lineup, basketball data, decision making model.

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