Abstract: In agricultural production and breeding, implementing automatic picking robot in orchard farming to reduce human labour and error is challenging. The core function of it is automatic identification based on machine vision. This paper focuses on apple detection and counting in orchards and implements several deep learning methods. Extensive datasets are used and a semi-automatic annotation method is proposed. The proposed deep learning models are in state-of-the-art YOLO family. In view of the essence of the models with various backbones, a multi-dimensional comparison in details is made in terms of counting accuracy, mAP and model memory, laying the foundation for realising automatic precision agriculture.
Abstract: Detecting subjectively biased statements is a vital task. This is because this kind of bias, when present in the text or other forms of information dissemination media such as news, social media, scientific texts, and encyclopedias, can weaken trust in the information and stir conflicts amongst consumers. Subjective bias detection is also critical for many Natural Language Processing (NLP) tasks like sentiment analysis, opinion identification, and bias neutralization. Having a system that can adequately detect subjectivity in text will boost research in the above-mentioned areas significantly. It can also come in handy for platforms like Wikipedia, where the use of neutral language is of importance. The goal of this work is to identify the subjectively biased language in text on a sentence level. With machine learning, we can solve complex AI problems, making it a good fit for the problem of subjective bias detection. A key step in this approach is to train a classifier based on BERT (Bidirectional Encoder Representations from Transformers) as upstream model. BERT by itself can be used as a classifier; however, in this study, we use BERT as data preprocessor as well as an embedding generator for a Bi-LSTM (Bidirectional Long Short-Term Memory) network incorporated with attention mechanism. This approach produces a deeper and better classifier. We evaluate the effectiveness of our model using the Wiki Neutrality Corpus (WNC), which was compiled from Wikipedia edits that removed various biased instances from sentences as a benchmark dataset, with which we also compare our model to existing approaches. Experimental analysis indicates an improved performance, as our model achieved state-of-the-art accuracy in detecting subjective bias. This study focuses on the English language, but the model can be fine-tuned to accommodate other languages.
Abstract: On February 15, 2012 off the Indian coast of Kerala, in position 091702N-0760180E by the oil tanker Enrica Lexie, flying the Italian flag, bursts of 5.56 x45 caliber shots were fired from assault rifles AR/70 Italian-made Beretta towards the Indian fisher boat St. Anthony. The shots that hit the St. Anthony fishing boat were six, of which two killed the Indian fishermen Ajesh Pink and Valentine Jelestine. From the analysis concerning the kinematic engagement of the two ships and from the autopsy and ballistic results of the Indian judicial authorities it is possible to reconstruct the trajectories of the six aforementioned shots. This essay reconstructs the trajectories of the six shots that cannot be of direct shooting but have undergone a rebound on the water. The investigation carried out scientifically demonstrates the rebound of the blows on the water, the gyrostatic deviation due to the rebound and the tumbling effect always due to the rebound as regards intermediate ballistics. In consideration of the four shots that directly impacted the fishing vessel, the current examination proves, with scientific value, that the trajectories could not be downwards but upwards. Also, the trajectory of two shots that hit to death the two fishermen could not be downwards but only upwards. In fact, this paper demonstrates, with scientific value: The loss of speed of the projectiles due to the rebound on the water; The tumbling effect in the ballistic medium within the two victims; The permanent cavities subject to the injury ballistics and the related ballistic trauma that prevented homeostasis causing bleeding in one case; The thermo-hardening deformation of the bullet found in Valentine Jelestine's skull; The upward and non-downward trajectories. The paper constitutes a tool in forensic ballistics in that it manages to reconstruct, from the final spot of the projectiles fired, all phases of ballistics like the internal one of the weapons that fired, the intermediate one, the terminal one and the penetrative structural one. In general terms the ballistics reconstruction is based on measurable parameters whose entity is contained with certainty within a lower and upper limit. Therefore, quantities that refer to angles, speed, impact energy and firing position of the shooter can be identified within the aforementioned limits. Finally, the investigation into the internal bullet track, obtained from any autopsy examination, offers a significant “lesson learned” but overall a starting point to contain or mitigate bleeding as a rescue from future gunshot wounds.
Abstract: Although Europe is on the threshold of a new industrial revolution called Industry 4.0, many believe that this will increase the flexibility of production, the mass adaptation of products to consumers and the speed of their service; it will also improve product quality and dramatically increase productivity. However, as expected, all the benefits of Industry 4.0 face many of the inevitable changes and challenges they pose. One of them is the inevitable transformation of current competition and business models. This article examines the possible results of competitive conversion from the classic Bertrand and Cournot models to qualitatively new competition based on innovation. Ability to deliver a new product quickly and the possibility to produce the individual design (through flexible and quickly configurable factories) by reducing equipment failures and increasing process automation and control is highly important. This study shows that the ongoing transformation of the competition model is changing the game. This, together with the creation of complex value networks, means huge investments that make it particularly difficult for small and medium-sized enterprises. In addition, the ongoing digitalization of data raises new concerns regarding legal obligations, intellectual property, and security.
Abstract: Edgeworth approximation is one of the most important statistical methods that has a considered contribution in the reduction of the sum of standard deviation of the independent variables’ coefficients in a Quantile Regression Model. This model estimates the conditional median or other quantiles. In this paper, we have applied approximating statistical methods in an economical problem. We have created and generated a quantile regression model to see how the profit gained is connected with the realized sales of the cosmetic products in a real data, taken from a local business. The Linear Regression of the generated profit and the realized sales was not free of autocorrelation and heteroscedasticity, so this is the reason that we have used this model instead of Linear Regression. Our aim is to analyze in more details the relation between the variables taken into study: the profit and the finalized sales and how to minimize the standard errors of the independent variable involved in this study, the level of realized sales. The statistical methods that we have applied in our work are Edgeworth Approximation for Independent and Identical distributed (IID) cases, Bootstrap version of the Model and the Edgeworth approximation for Bootstrap Quantile Regression Model. The graphics and the results that we have presented here identify the best approximating model of our study.
Abstract: Phosphorus is an essential nutrient for plant life which is most frequently found as phosphate in water. Once phosphate is found in abundance in surface water, a series of adverse effects on an ecosystem can be initiated. Therefore, a portable and reliable method is needed to monitor the phosphate concentrations in the field. In this paper, an inexpensive dip strip device with the ascorbic acid/antimony reagent dried on blotting paper along with wet chemistry is developed for the detection of low concentrations of phosphate in water. Ammonium molybdate and sulfuric acid are separately stored in liquid form so as to improve significantly the lifetime of the device and enhance the reproducibility of the device’s performance. The limit of detection and quantification for the optimized device are 0.134 ppm and 0.472 ppm for phosphate in water, respectively. The device’s shelf life, storage conditions, and limit of detection are superior to what has been previously reported for the paper-based phosphate detection devices.
Abstract: This study presents an investigation of diesel vehicle particulate-phase emissions with neat ultralow sulphur diesel (B0, ULSD) and 5% waste cooking oil-based biodiesel blend (B5) in Hong Kong. A Euro VI light duty diesel vehicle was tested under transient (New European Driving Cycle (NEDC)), steady-state and idling on a chassis dynamometer. Chemical analyses including organic carbon (OC), elemental carbon (EC), as well as 30 polycyclic aromatic hydrocarbons (PAHs) and 10 oxygenated PAHs (oxy-PAHs) were conducted. The OC fuel-based emission factors (EFs) for B0 ranged from 2.86 ± 0.33 to 7.19 ± 1.51 mg/kg, and those for B5 ranged from 4.31 ± 0.64 to 15.36 ± 3.77 mg/kg, respectively. The EFs of EC were low for both fuel blends (0.25 mg/kg or below). With B5, the EFs of total PAHs were decreased as compared to B0. Specifically, B5 reduced total PAH emissions by 50.2%, 30.7%, and 15.2% over NEDC, steady-state and idling, respectively. It was found that when B5 was used, PAHs and oxy-PAHs with lower molecular weight (2 to 3 rings) were reduced whereas PAHs/oxy-PAHs with medium or high molecular weight (4 to 7 rings) were increased. Our study suggests the necessity of taking atmospheric and health factors into account for biodiesel application as an alternative motor fuel.
Abstract: The impact of COVID-19 has a significant effect on all sectors of society globally. Health information technology (HIT) has become an effective health strategy in this age of distancing. In this regard, Mobile Health (mHealth) plays a critical role in managing patient and provider workflows during the COVID-19 pandemic. Therefore, the users' perception of service quality about mHealth services plays a significant role in shaping confidence and subsequent behaviors regarding the mHealth users' intention of use. This study's objective was to explore levels of user attributes analyzed by a qualitative method of how health practitioners and patients are satisfied or dissatisfied with using mHealth services; and analyzed the users' intention in the context of Taiwan during the COVID-19 pandemic. This research explores the experienced usability of a mHealth services during the Covid-19 pandemic. This study uses qualitative methods that include in-depth and semi-structured interviews that investigate participants' perceptions and experiences and the meanings they attribute to them. The five cases consisted of health practitioners, clinic staff, and patients' experiences using mHealth services. This study encourages participants to discuss issues related to the research question by asking open-ended questions, usually in one-to-one interviews. The findings show the positive and negative attributes of mHealth service quality. Hence, the significant importance of patients' and health practitioners' issues on several dimensions of perceived service quality is system quality, information quality, and interaction quality. A concept map for perceptions regards to emergency uses' intention of mHealth services process is depicted. The findings revealed that users pay more attention to "Medical care", "ease of use" and "utilitarian benefits" and have less importance for "Admissions and Convenience" and "Social influence". To improve mHealth services, the mHealth providers and health practitioners should better manage users' experiences to enhance mHealth services. This research contributes to the understanding of service quality issues in mHealth services during the COVID-19 pandemic.
Abstract: The requirement for maintaining data integrity in laboratory operations is critical for regulatory compliance. Automation of procedures reduces incidence of human errors. Quality control laboratories located in low-income economies may face some barriers in attempts to automate their processes. Since data from quality control tests on pharmaceutical products are used in making regulatory decisions, it is important that laboratory reports are accurate and reliable. Zinc Sulphate (ZnSO4) tablets is used in treatment of diarrhea in pediatric population, and as an adjunct therapy for COVID-19 regimen. Unfortunately, zinc content in these formulations is determined titrimetrically; a manual analytical procedure. The assay for ZnSO4 tablets involves time-consuming steps that contain mathematical formulae prone to calculation errors. To achieve consistency, save costs, and improve data integrity, validated spreadsheets were developed to simplify the two critical steps in the analysis of ZnSO4 tablets: standardization of 0.1M Sodium Edetate (EDTA) solution, and the complexometric titration assay procedure. The assay method in the United States Pharmacopoeia was used to create a process flow for ZnSO4 tablets. For each step in the process, different formulae were input into two spreadsheets to automate calculations. Further checks were created within the automated system to ensure validity of replicate analysis in titrimetric procedures. Validations were conducted using five data sets of manually computed assay results. The acceptance criteria set for the protocol were met. Significant p-values (p < 0.05, α = 0.05, at 95% Confidence Interval) were obtained from students’ t-test evaluation of the mean values for manual-calculated and spreadsheet results at all levels of the analysis flow. Right-first-time analysis and principles of data integrity were enhanced by use of the validated spreadsheet calculators in titrimetric evaluations of ZnSO4 tablets. Human errors were minimized in calculations when procedures were automated in quality control laboratories. The assay procedure for the formulation was achieved in a time-efficient manner with greater level of accuracy. This project is expected to promote cost savings for laboratory business models.
Abstract: The aim of this work was to recover phenolic compounds from grape skins produced in Greek varieties of the Ionian Islands in order to form the basis of calculations for their further utilization in the context of the circular economy. Isolation and further utilization of phenolic compounds is an important issue in winery by-products. For this purpose, 37 samples were collected, extracted, and analyzed in an attempt to provide the appropriate basis for their sustainable exploitation. Extraction of the bioactive compounds was held using an eco-friendly, non-toxic, and highly effective water-glycerol solvent system. Then, extracts were analyzed using UV-Vis, liquid chromatography-mass spectrometry (LC-MS), FTIR, and Raman spectroscopy. Also, total phenolic content and antioxidant activity were measured. LC-MS chromatography showed qualitative differences between different varieties. Peaks were attributed to monomeric 3-flavanols as well as monomeric, dimeric, and trimeric proanthocyanidins. The FT-IR and Raman spectra agreed with the chromatographic data and contributed to identifying phenolic compounds. Grape skins exhibited high total phenolic content (TPC), and it was proved that during vinification, a large number of polyphenols remained in the pomace. This study confirmed that grape skins from Ionian Islands are a promising source of bioactive compounds, suggesting their utilization under a bio-economic and environmental strategic framework.
Abstract: Among different droplet manipulations, controlled droplet-splitting is of great significance due to its ability to increase throughput and operational capability. Furthermore, unequal droplet-splitting can provide greater flexibility and a wider range of dilution factors. In this study, we developed two-dimensional, time-dependent complex fluid dynamics simulations to model droplet formation in a flow focusing device, followed by splitting in a Y-shaped junction with sub-channels of unequal widths. From the results obtained from the numerical study, we correlated the diameters of the droplets in the sub-channels to the Weber number, thereby demarcating the droplet splitting and non-splitting regimes.
Abstract: Radiant chilled ceiling (RCC) has been perceived to save more energy and provide better thermal comfort than the traditional air conditioning system. However, its application has been rather limited by some reasons e.g., the scarce information about the thermal characteristic in the radiant room and the local climate influence on the system performance, etc. To bridge such gap, an office-like experiment room with a RCC was constructed in the hot and humid climate of Thailand. This paper presents exemplarily results from the RCC experiments to give an insight into the thermal environment in a radiant room and the cooling load associated to maintain the room's comfort condition. It gave a demonstration of the RCC system operation for its application to achieve thermal comfort in offices in a hot humid climate, as well.
Abstract: Public green space promotes community health including daily activities, but these resources may not be available enough or may not equitably be distributed. This paper measures and compares the availability of public green spaces (PGS) among low, middle, and high-income neighborhoods in the Riyadh city. Additionally, it compares the total availability of PGS to WHO standard and Dubai availability of PGS per person. All PGS were mapped using geographical information systems, and total area availability of PGS compared to WHO and Dubai standards. To evaluate the significant differences in PGS availability across low, medium, and high-income Riyadh neighborhoods, we used a One-way ANOVA analysis of covariance to test the differences. As a result, by comparing PGS of Riyadh neighborhoods to WHO and Dubai-availability, it was found that Riyadh PGS were lower than the minimum standard of WHO and as well as Dubai. Riyadh has only 1.13 m2 per capita of PGS. The second finding, the availability of PGS, was significantly different among Riyadh neighborhoods based on socioeconomic status. The future development of PGS should be focused on increasing PGS availability and should be given priority to those low-income and unhealthy communities.
Abstract: A paradigm shift in container inventory management (CIM) is a long-awaited industry need. Virtual container yard (VCY) is a concept developed in 2013 and its primary objective is to minimize shipping transport cost through implementing container exchange between carriers. Shipping lines always try to maintain lower container idle time and provide higher customer satisfaction. However, it is disappointing to note that carriers turn a blind eye to the escalating cost resulted from the present inefficient CIM mechanism. The cost of empty container management is simply transferred to the importers and exporters as freight adjustments. It also creates an environmental hazard. Therefore, it has now become a problem for the society. Therefore, a paradigm shift may be required as the present CIM system is not working for common interests of human beings as it should be.
Abstract: We address the question of identifying the configuration
space singularities of linkages, i.e., points where the configuration
space is not locally a submanifold of Euclidean space. Because the
configuration space cannot be smoothly parameterized at such points,
these singularity types have a significantly negative impact on the
kinematics of the linkage. It is known that Jacobian methods do not
provide sufficient conditions for the existence of CS-singularities.
Herein, we present several additional algebraic criteria that provide
the sufficient conditions. Further, we use those criteria to analyze
certain classes of planar linkages. These examples will also show
how the presented criteria can be checked using algorithmic methods.
Abstract: One of the issues that arises with microscale lab-on-a-chip technology is that the laminar flow within the microchannels limits the mixing of fluids. To combat this, micromixers have been introduced as a means to try and incorporate turbulence into the flow to better aid the mixing process. This study presents an electroosmotic micromixer that balances vortex generation and degeneration with the inlet flow velocity to greatly increase the mixing efficiency. A comprehensive parametric study was performed to evaluate the role of the relevant parameters on the mixing efficiency. It was observed that the suggested micromixer is perfectly suited for biological applications due to its low pressure drop (below 10 Pa) and low shear rate. The proposed micromixer with optimized working parameters is able to attain a mixing efficiency of 95% in a span of 0.5 seconds using a frequency of 10 Hz, a voltage of 0.7 V, and an inlet velocity of 0.366 mm/s.
Abstract: There is an increasing interest in introducing computational thinking at an early age. Computational thinking, like mathematical thinking, engineering thinking, and scientific thinking, is a kind of analytical thinking. Learning computational thinking skills is not only to improve technological literacy, but also allows learners to equip with practicable skills such as problem-solving skills. As people realize the importance of computational thinking, the field of educational technology faces a problem: how to choose appropriate tools and activities to help students develop computational thinking skills. Robots are gradually becoming a popular teaching tool, as robots provide a tangible way for young children to access to technology, and controlling a robot through programming offers them opportunities to engage in developing computational thinking. This study explores whether the introduction of flowcharts into the robotics programming courses can help children convert natural language into a programming language more easily, and then to better cultivate their computational thinking skills. An experimental study was adopted with a sample of children ages six to seven (N = 16) participated, and a one-meter-tall humanoid robot was used as the teaching tool. Results show that children can master basic programming concepts through robotic courses. Children's computational thinking has been significantly improved. Besides, results suggest that flowcharts do have an impact on young children’s computational thinking skills development, but it only has a significant effect on the "sequencing" and "correspondence" skills. Overall, the study demonstrates that the humanoid robot and flowcharts have qualities that foster young children to learn programming and develop computational thinking skills.
Abstract: Non-polar a-plane AlGaN epilayers of high structural quality have been grown on r-sapphire substrate by using metalorganic chemical vapor deposition (MOCVD). A graded non-polar AlGaN buffer layer with variable aluminium concentration was used to improve the structural quality of the non-polar a-plane AlGaN epilayer. The characterisations were carried out by high-resolution X-ray diffraction (HR-XRD), atomic force microscopy (AFM) and Hall effect measurement. The XRD and AFM results demonstrate that the Al-composition-graded non-polar AlGaN buffer layer significantly improved the crystalline quality and the surface morphology of the top layer. A low root mean square roughness 1.52 nm is obtained from AFM, and relatively low background carrier concentration down to 3.9× cm-3 is obtained from Hall effect measurement.
Abstract: Predicting the actual cost and duration in construction projects concern a continuous and existing problem for the construction sector. This paper addresses this problem with modern methods and data available from past public construction projects. 39 bridge projects, constructed in Greece, with a similar type of available data were examined. Considering each project’s attributes with the actual cost and the actual duration, correlation analysis is performed and the most appropriate predictive project variables are defined. Additionally, the most efficient subgroup of variables is selected with the use of the WEKA application, through its attribute selection function. The selected variables are used as input neurons for neural network models through correlation analysis. For constructing neural network models, the application FANN Tool is used. The optimum neural network model, for predicting the actual cost, produced a mean squared error with a value of 3.84886e-05 and it was based on the budgeted cost and the quantity of deck concrete. The optimum neural network model, for predicting the actual duration, produced a mean squared error with a value of 5.89463e-05 and it also was based on the budgeted cost and the amount of deck concrete.
Abstract: The aim of this experimental and numerical study is to analyze the effects of acoustic streaming generated by 40 kHz ultrasonic waves on heat transfer in forced convection, with and without 40 PPI aluminum metal foam. Preliminary dynamic and thermal studies were done with COMSOL Multiphase, to see heat transfer enhancement degree by inserting a 40PPI metal foam (10 × 2 × 3 cm) on a heat sink, after having determined experimentally its permeability and Forchheimer's coefficient. The results obtained numerically are in accordance with those obtained experimentally, with an enhancement factor of 205% for a velocity of 0.4 m/s compared to an empty channel. The influence of 40 kHz ultrasound on heat transfer was also tested with and without metallic foam. Results show a remarkable increase in Nusselt number in an empty channel with an enhancement factor of 37,5%, while no influence of ultrasound on heat transfer in metal foam presence.