Search results for: 3D plant data

Authors: Aref Aasi, Sadegh Mehdi Aghaei, Balaji Panchapakesan

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This work aims to evaluate the free and forced vibration of a beam with two end joints subjected to a concentrated moving mass and a load using the Euler-Bernoulli method. The natural frequency is calculated for different locations of the concentrated mass and load on the beam. The analytical results are verified by the experimental data. The variations of natural frequency as a function of the location of the mass, the effect of the forced frequency on the vibrational amplitude, and the displacement amplitude versus time are investigated. It is discovered that as the concentrated mass moves toward the center of the beam, the natural frequency of the beam and the relative error between experimental and analytical data decreases. There is a close resemblance between analytical data and experimental observations.

Keywords: Euler-Bernoulli beam, natural frequency, forced vibration, experimental setup

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Authors: Yi-Chun Huang, Kuan-Yun Chen, Chuang-Hung Lin

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Urban Green Belt and Blue is a part of the city landscape, it is an important constituent element of the urban environment and appearance. The Hsinchu East Gate Moat is situated in the center of the city, which not only has a wealth of historical and cultural resources, but also combines the Green Belt and the Blue Belt qualities at the same time. The Moat runs more than a thousand meters through the vital Green Belt and the Blue Belt in downtown, and each section is presented in different qualities of moat from south to north. The water area and the green belt of surroundings are presented linear and banded spread. The water body and the rich diverse river banks form an urban green belt of rich layers. The watercourse with green belt design lets users have connections with blue belts in different ways; therefore, the integration of Hsinchu East Gate and moat have become one of the unique urban landscapes in Taiwan. The study is based on the fact-finding case of Hsinchu East Gate Moat where situated in northern Taiwan, to research the impact between the SVF variation of the city and spatial sequence of Urban Green Belt and Blue landscape and visual analysis by constituent cross-section, and then comparing the influence of different leaf area index – the variable ecological factors to the degree of enclosure. We proceed to survey the landscape design of open space, to measure existing structural features of the plant canopy which contain the height of plants and branches, the crown diameter, breast-height diameter through access to diagram of Geographic Information Systems (GIS) and on-the-spot actual measurement. The north and south districts of blue green belt areas are divided 20 meters into a unit from East Gate Roundabout as the epicenter, and to set up a survey points to measure the SVF above the survey points; then we proceed to quantitative analysis from the data to calculate open landscape degree of enclosure. The results can be reference for the composition of future river landscape and the practical operation for dynamic space planning of blue and green belt landscape.

Keywords: sky view factor, degree of enclosure, spatial sequence, leaf area indices

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Authors: Sajmina Khatun, Monika Pebam, Aravind Kumar Rengan

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Photothermal therapy, a subset of nanomedicine, takes advantage of light-absorbing agents to generate localized heat, selectively eradicating cancer cells. This innovative approach minimizes damage to healthy tissues and offers a promising avenue for targeted cancer treatment. Unlike conventional therapies, photothermal therapy harnesses the power of light to combat malignancies precisely and effectively, showcasing its potential to revolutionize cancer treatment paradigms. The combined strengths of nanomedicine and photothermal therapy signify a transformative shift toward more effective, targeted, and tolerable cancer treatments in the medical landscape. Utilizing natural products becomes instrumental in formulating diverse bioactive medications owing to their various pharmacological properties attributed to the existence of phenolic structures, triterpenoids, and similar compounds. Hyptis suaveolens, commonly known as pignut, stands as an aromatic herb within the Lamiaceae family and represents a valuable therapeutic plant. Flourishing in swamps and alongside tropical and subtropical roadsides, these noxious weeds impede the development of adjacent plants. Hyptis suaveolens ranks among the most globally distributed alien invasive species. The present investigation revealed that a versatile, biodegradable liposome nanosystem (HIL NPs), incorporating bioactive molecules from Hyptis suaveolens, exhibits effective bioavailability to cancer cells, enabling tumor ablation upon near-infrared (NIR) laser exposure. The components within the nanosystem, specifically the bioactive molecules from Hyptis, function as anticancer agents, aiding in the photothermal ablation of highly metastatic lung cancer cells. Despite being a prolific weed impeding neighboring plant growth, Hyptis suaveolens showcases therapeutic benefits through its bioactive compounds. The obtained HIL NPs, characterized as a photothermally active liposome nanosystem, demonstrate a pronounced fluorescence absorption peak in the NIR range and achieve a high photothermal conversion efficiency under NIR laser irradiation. Transmission electron microscopy (TEM) and particle size analysis reveal that HIL NPs possess a spherical shape with a size of 141 ± 30 nm. Moreover, in vitro assessments of HIL NPs against lung cancer cell lines (A549) indicate effective anticancer activity through a combined cytotoxic effect and hyperthermia. Tumor ablation is facilitated by apoptosis induced by the overexpression of ɣ-H2AX, arresting cancer cell proliferation. Consequently, the multifunctional and biodegradable nanosystem (HIL NPs), incorporating bioactive compounds from Hyptis, provides valuable perspectives for developing an innovative therapeutic strategy originating from a challenging weed. This approach holds promise for potential applications in both bioimaging and the combined use of phyto-photothermal therapy for cancer treatment.

Keywords: bioactive liposome, hyptis suaveolens, photothermal therapy, lung cancer

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Authors: Yusuf Hesham Mohamed

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Introduction: Three-dimensional printing technology includes multiple procedures that fabricate three-dimensional objects through consecutively layering two-dimensional cross-sections on top of each other. 3D bioprinting is a promising field of 3D printing, which fabricates tissues and organs by accurately controlling the proper arrangement of diverse biological components. 3D bioprinting uses software and prints biological materials and their supporting components layer-by-layer on a substrate or in a tissue culture plate to produce complex live tissues and organs. 3D food printing is an emerging field of 3D bioprinting in which the 3D printed products are food products that are cheap, require less effort to produce, and have more desirable traits. The Aim of the Study is the development of an affordable 3D bioprinter by altering a locally made CNC instrument with an open-source platform to suit the 3D bio-printer purposes. Later, we went through applying the prototype in several applications regarding food technology and drug testing, including the organ-On-Chip. Materials and Methods: An off-the-shelf 3D printer was modified by designing and fabricating the syringe unit, which was designed on the basis of the Milli-fluidics system. Sodium alginate and gelatin hydrogels were prepared, followed by leaf cell suspension preparation from narrow sections of Fragaria’s viable leaves. The desired 3D structure was modeled, and 3D printing preparations took place. Cell-free and cell-laden hydrogels were printed at room temperature under sterile conditions. Post printing curing process was performed. The printed structure was further studied. Results: Positive results have been achieved using the altered 3D bioprinter where a 3D hydrogel construct of two layers made of the combination of sodium alginate to gelatin (15%: 0.5%) has been printed. DLP 3D printer was used to design the syringe component with a transparent PLA-Pro resin for the creation of a microfluidics system having two channels altered to the double extruder. The hydrogel extruder’s design was based on peristaltic pumps, which utilized a stepper motor. The design and fabrication were made using DIY-3D printed parts. Hard plastic PLA was the material utilized for printing. SEM was used to carry out the porous 3D construct imaging. Multiple physical and chemical tests were performed in order to ensure that the cell line was suitable for hosting. Fragaria plant was developed by suspending Fragaria’s cells from its leaves using the 3D bioprinter. Conclusion: 3D bioprinting is considered to be an emerging scientific field that can facilitate and improve many scientific tests and studies. Thus, having a 3D bioprinter in labs is considered to be an essential requirement. 3D bioprinters are very expensive; however, the fabrication of a 3D printer into a 3D bioprinter can lower the cost of the bioprinter. The 3D bioprinter implemented made use of peristaltic pumps instead of syringe-based pumps in order to extend the ability to print multiple types of materials and cells.

Keywords: scaffold, eco on chip, 3D bioprinter, DLP printer

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Authors: NeisaKuonuo Tungoe

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Tenyidie, also known as Angami, is spoken by the Angami tribe of Nagaland, North-East India, bordering Myanmar (Burma). It belongs to the Tibeto-Burman language group, falling under the Kuki-Chin-Naga sub-family. Tenyidie studies have seen random attempts at explaining the phonemic inventory of Tenyidie. Different scholars have variously emphasized the grammar or the history of Tenyidie. Many of these claims have been stimulating, but they were often based on a small amount of merely suggestive data or on auditory perception only. The principal objective of this paper is to analyse the affricate segments of Tenyidie as an acoustic study. There are seven categories to the inventory of Tenyidie; Plosives, Nasals, Affricates, Laterals, Rhotics, Fricatives, Semi vowels and Vowels. In all, there are sixty phonemes in the inventory. As mentioned above, the only prominent readings on Tenyidie or affricates in particular are only reflected through auditory perception. As noted above, this study aims to lay out the affricate segments based only on acoustic conclusions. There are seven affricates found in Tenyidie. They are: 1) Voiceless Labiodental Affricate - / pf /, 2) Voiceless Aspirated Labiodental Affricate- / pfh /, 3) Voiceless Alveolar Affricate - / ts /, 4) Voiceless Aspirated Alveolar Affricate - / tsh /, 5) Voiced Alveolar Affricate - / dz /, 6) Voiceless Post-Alveolar Affricate / tʃ / and 7) Voiced Post- Alveolar Affricate- / dʒ /. Since the study is based on acoustic features of affricates, five informants were asked to record their voice with Tenyidie phonemes and English phonemes. Throughout the study of the recorded data, PRAAT, a scientific software program that has made itself indispensible for the analyses of speech in phonetics, have been used as the main software. This data was then used as a comparative study between Tenyidie and English affricates. Comparisons have also been drawn between this study and the work of another author who has stated that there are only six affricates in Tenyidie. The study has been quite detailed regarding the specifics of the data. Detailed accounts of the duration and acoustic cues have been noted. The data will be presented in the form of spectrograms. Since there aren’t any other acoustic related data done on Tenyidie, this study will be the first in the long line of acoustic researches on Tenyidie.

Keywords: tenyidie, affricates, praat, phonemic inventory

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Authors: Alveena Khan

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The objective of this research is to explore students’ understanding about bullying and different bullying types. Nowadays bullying is considered as an important social issue around the world because it has long lasting effects on students’ lives. Sometimes due to bullying students commit suicide, they lose confidence and become isolated. This research used qualitative research approach. In order to generate data, triangulation was considered for the verification and reliability of the generated data. Semi-structured interview, non-participant observation, and case studies were conducted. This research focused on five major private colleges and 20 students (both female and male) participated in Rawalpindi, Pakistan. The data generated included approximately 45 hours of total interviews. Thematic analysis was used for data analysis and followed grounded theory to generate themes. The findings of the research highlights that bullying does prevail in studied private colleges, mostly in the form of verbal and physical bullying. No specific gender difference was found in experiencing verbal and physical bullying. Furthermore, from students’ point of view, college administrators are responsible to deal with bullying. The researcher suggests that there must be a proper check and balance system and anti-bullying programs should be held in colleges to create a protective and healthy environment in which students do not face bullying.

Keywords: bullying, college student, physical and verbal bullying, qualitative research

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Authors: Anna Triwijayati, Etsa Astridya Setiyati, Titik Desi Harsoyo

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Culture is the important determinant of human behavior and desire. Culture influences the consumer through the norms and values established by the society in which they live and reflect it. The cultural values of Javanese society certainly have united in the Javanese society behavior in consumption. This research is expected to give big enough theoretical benefits in the findings of cultural value in consumption in Javanese society. These can be an incentive in finding the local cultural value in many tribes in Indonesia, so one time, the local cultural value in Indonesia about consumption can be fundamental part in education and consumption practice in Indonesia. The approach used in this research is non positivist research or is known as qualitative approach. The method or type of research used in this research is ethnomethodology. The collection data is done in Central Java region. The research subject or informant is determined by the purposive technique by certain criteria determined by the researcher. The data is collected by deep interview and observation. Before the data analysis, the researcher does the storing method data stage and implements the data validity procedures. Then, the data is analyzed by the theme and interactive analysis technique. The Javanese Mataraman society has such consumption values such as has to be sufficient, be careful, economical, submit to the one who creates the life, the way life flow, and the present problem is thought in the present also. In the financial management for consumption, the consumer should have the simple life principles, has to be sufficient, has to be able to eat, has to be able to self-press, well-managed/diligent/accurate/careful, the open or transparent management, has the struggle effort, like to self-sacrifice and think about the future. The meaning of consumption value in family is centered to the submission and full-trust to God. These consumption values are applied in consumer behavior in self, family, investment and credit need in short term and long term perspective.

Keywords: values, consumer, consumption, Javanese Mataraman, ethnomethodology

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Authors: Arindam Chaudhuri

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Classification of data has been actively used for most effective and efficient means of conveying knowledge and information to users. The prima face has always been upon techniques for extracting useful knowledge from data such that returns are maximized. With emergence of huge datasets the existing classification techniques often fail to produce desirable results. The challenge lies in analyzing and understanding characteristics of massive data sets by retrieving useful geometric and statistical patterns. We propose a supervised parallel fuzzy rough support vector machine (PFRSVM) for data classification in cloud environment. The classification is performed by PFRSVM using hyperbolic tangent kernel. The fuzzy rough set model takes care of sensitiveness of noisy samples and handles impreciseness in training samples bringing robustness to results. The membership function is function of center and radius of each class in feature space and is represented with kernel. It plays an important role towards sampling the decision surface. The success of PFRSVM is governed by choosing appropriate parameter values. The training samples are either linear or nonlinear separable. The different input points make unique contributions to decision surface. The algorithm is parallelized with a view to reduce training times. The system is built on support vector machine library using Hadoop implementation of MapReduce. The algorithm is tested on large data sets to check its feasibility and convergence. The performance of classifier is also assessed in terms of number of support vectors. The challenges encountered towards implementing big data classification in machine learning frameworks are also discussed. The experiments are done on the cloud environment available at University of Technology and Management, India. The results are illustrated for Gaussian RBF and Bayesian kernels. The effect of variability in prediction and generalization of PFRSVM is examined with respect to values of parameter C. It effectively resolves outliers’ effects, imbalance and overlapping class problems, normalizes to unseen data and relaxes dependency between features and labels. The average classification accuracy for PFRSVM is better than other classifiers for both Gaussian RBF and Bayesian kernels. The experimental results on both synthetic and real data sets clearly demonstrate the superiority of the proposed technique.

Keywords: FRSVM, Hadoop, MapReduce, PFRSVM

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Authors: Grace Omowunmi Soyebi

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A computerized medical record system is a collection of medical information about a person that is stored on a computer. One principal problem of most hospitals in rural areas is using the file management system for keeping records. A lot of time is wasted when a patient visits the hospital, probably in an emergency, and the nurse or attendant has to search through voluminous files before the patient's file can be retrieved, this may cause an unexpected to happen to the patient. This Data Mining application is to be designed using a Structured System Analysis and design method which will help in a well-articulated analysis of the existing file management system, feasibility study, and proper documentation of the Design and Implementation of a Computerized medical record system. This Computerized system will replace the file management system and help to quickly retrieve a patient's record with increased data security, access clinical records for decision-making, and reduce the time range at which a patient gets attended to.

Keywords: programming, computing, data, innovation

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Authors: Gholamreza Farrokhi, Behzad Sani

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The goals of sustainable agricultural are development, improved nutrition, and food security. Sustainable agriculture must be developed that will meet today’s needs for food and other products, as well as preserving the vital natural resource base that will allow future generations to meet their needs. Sustainable development requires international cooperation and the effective use of technology. Access to sustainable sources of food will remain a preeminent challenge in the decades to come. Based upon current practice and consumption, agricultural production will have to increase by about 70% by 2050 to meet demand. Nuclear techniques are used in developing countries to increase production sustainably by breeding improved crops, enhancing livestock reproduction and nutrition, as well as controlling animal and plant pests and diseases. Post-harvest losses can be reduced and safety increased with nuclear technology. Soil can be evaluated with nuclear techniques to conserve and improve soil productivity and water management.

Keywords: food safety, food security, nuclear techniques, sustainable agriculture, sustainable future

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Authors: Victoria Siriaki Jorry, I. S. Mbalawata, Hayong Shin

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The main objective in a change detection problem is to develop algorithms for efficient detection of gradual and/or abrupt changes in the parameter distribution of a process or time series data. In this paper, we present a modified cumulative (MCUSUM) algorithm to detect the start and end of a time-varying linear drift in mean value of a time series data based on likelihood ratio test procedure. The design, implementation and performance of the proposed algorithm for a linear drift detection is evaluated and compared to the existing CUSUM algorithm using different performance measures. An approach to accurately approximate the threshold of the MCUSUM is also provided. Performance of the MCUSUM for gradual change-point detection is compared to that of standard cumulative sum (CUSUM) control chart designed for abrupt shift detection using Monte Carlo Simulations. In terms of the expected time for detection, the MCUSUM procedure is found to have a better performance than a standard CUSUM chart for detection of the gradual change in mean. The algorithm is then applied and tested to a randomly generated time series data with a gradual linear trend in mean to demonstrate its usefulness.

Keywords: average run length, CUSUM control chart, gradual change detection, likelihood ratio test

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Authors: Julia Ive, Lucia Specia

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Understanding and detecting toxicity is an important problem to support safer human interactions online. Our work focuses on the important problem of contextual toxicity detection, where automated classifiers are tasked with determining whether a short textual segment (usually a sentence) is toxic within its conversational context. We use “toxicity” as an umbrella term to denote a number of variants commonly named in the literature, including hate, abuse, offence, among others. Detecting toxicity in context is a non-trivial problem and has been addressed by very few previous studies. These previous studies have analysed the influence of conversational context in human perception of toxicity in controlled experiments and concluded that humans rarely change their judgements in the presence of context. They have also evaluated contextual detection models based on state-of-the-art Deep Learning and Natural Language Processing (NLP) techniques. Counterintuitively, they reached the general conclusion that computational models tend to suffer performance degradation in the presence of context. We challenge these empirical observations by devising better contextual predictive models that also rely on NLP data augmentation techniques to create larger and better data. In our study, we start by further analysing the human perception of toxicity in conversational data (i.e., tweets), in the absence versus presence of context, in this case, previous tweets in the same conversational thread. We observed that the conclusions of previous work on human perception are mainly due to data issues: The contextual data available does not provide sufficient evidence that context is indeed important (even for humans). The data problem is common in current toxicity datasets: cases labelled as toxic are either obviously toxic (i.e., overt toxicity with swear, racist, etc. words), and thus context does is not needed for a decision, or are ambiguous, vague or unclear even in the presence of context; in addition, the data contains labeling inconsistencies. To address this problem, we propose to automatically generate contextual samples where toxicity is not obvious (i.e., covert cases) without context or where different contexts can lead to different toxicity judgements for the same tweet. We generate toxic and non-toxic utterances conditioned on the context or on target tweets using a range of techniques for controlled text generation(e.g., Generative Adversarial Networks and steering techniques). On the contextual detection models, we posit that their poor performance is due to limitations on both of the data they are trained on (same problems stated above) and the architectures they use, which are not able to leverage context in effective ways. To improve on that, we propose text classification architectures that take the hierarchy of conversational utterances into account. In experiments benchmarking ours against previous models on existing and automatically generated data, we show that both data and architectural choices are very important. Our model achieves substantial performance improvements as compared to the baselines that are non-contextual or contextual but agnostic of the conversation structure.

Keywords: contextual toxicity detection, data augmentation, hierarchical text classification models, natural language processing

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Authors: Loveneet Kaur

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Introduction: Osteoarthritis (OA) is one of the leading causes of disability, and the knee is the most commonly affected joint in the body. The last resort for treatment of knee OA is Total Knee Replacement (TKR) surgery. Despite numerous advances in prosthetic design, patients do not reach normal function after surgery. Current surgical decisions are made on 2D radiographs and patient interviews. Aims: The aim of this study was to compare knee kinematics pre and post-TKR surgery using computer-animated images of patient-specific models under everyday conditions. Methods: 7 subjects were recruited for the study. Subjects underwent 3D gait analysis during 4 everyday activities and medical imaging of the knee joint pre- and one-month post-surgery. A 3D model was created from each of the scans, and the kinematic gait analysis data was used to animate the images. Results: Improvements were seen in a range of motion in all 4 activities 1-year post-surgery. The preoperative 3D images provide detailed information on the anatomy of the osteoarthritic knee. The postoperative images demonstrate potential future problems associated with the implant. Although not accurate enough to be of clinical use, the animated data can provide valuable insight into what conditions cause damage to both the osteoarthritic and prosthetic knee joints. As the animated data does not require specialist training to view, the images can be utilized across the fields of health professionals and manufacturing in the assessment and treatment of patients pre and post-knee replacement surgery. Future improvements in the collection and processing of data may yield clinically useful data. Conclusion: Although not yet of clinical use, the potential application of 3D animations of the knee joint pre and post-surgery is widespread.

Keywords: Orthoporosis, Ortharthritis, knee replacement, TKR

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Authors: Jiahao Tian, Michael D. Porter

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Law enforcement agencies are tasked with crime prevention and crime reduction under limited resources. Having an accurate temporal estimate of the crime rate would be valuable to achieve such a goal. However, estimation is usually complicated by the interval-censored nature of crime data. We cast the problem of intensity estimation as a Poisson regression using an EM algorithm to estimate the parameters. Two special penalties are added that provide smoothness over the time of day and day of the week. This approach presented here provides accurate intensity estimates and can also uncover day-of-week clusters that share the same intensity patterns. Anticipating where and when crimes might occur is a key element to successful policing strategies. However, this task is complicated by the presence of interval-censored data. The censored data refers to the type of data that the event time is only known to lie within an interval instead of being observed exactly. This type of data is prevailing in the field of criminology because of the absence of victims for certain types of crime. Despite its importance, the research in temporal analysis of crime has lagged behind the spatial component. Inspired by the success of solving crime-related problems with a statistical approach, we propose a statistical model for the temporal intensity estimation of crime with censored data. The model is built on Poisson regression and has special penalty terms added to the likelihood. An EM algorithm was derived to obtain maximum likelihood estimates, and the resulting model shows superior performance to the competing model. Our research is in line with the smart policing initiative (SPI) proposed by the Bureau Justice of Assistance (BJA) as an effort to support law enforcement agencies in building evidence-based, data-driven law enforcement tactics. The goal is to identify strategic approaches that are effective in crime prevention and reduction. In our case, we allow agencies to deploy their resources for a relatively short period of time to achieve the maximum level of crime reduction. By analyzing a particular area within cities where data are available, our proposed approach could not only provide an accurate estimate of intensities for the time unit considered but a time-variation crime incidence pattern. Both will be helpful in the allocation of limited resources by either improving the existing patrol plan with the understanding of the discovery of the day of week cluster or supporting extra resources available.

Keywords: cluster detection, EM algorithm, interval censoring, intensity estimation

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Authors: Dmitry Yu. Korulkin, Raissa A. Muzychkina

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Bioactive substances of plant origin can be one of the advanced means of solution to the issue of combined therapy to inflammation. The main advantages of medical plants are softness and width of their therapeutic effect on an organism, the absence of side effects and complications even if the used continuously, high tolerability by patients. Moreover, medial plants are often the only and (or) cost-effective sources of natural biologically active substances and medicines. Along with other biologically active groups of chemical compounds, essential oils with wide range of pharmacological effects became very ingrained in medical practice. Essential oil was obtained by the method hydrodistillation air-dry aerial part of Polygonum L. plants using Clevenger apparatus. Qualitative composition of essential oils was analyzed by chromatography-mass-spectrometry method using Agilent 6890N apparatus. The qualitative analysis is based on the comparison of retention time and full mass-spectra with respective data on components of reference oils and pure compounds, if there were any, and with the data of libraries of mass-spectra Wiley 7th edition and NIST 02. The main components of essential oil are for: Polygonum amphibium L. - γ-terpinene, borneol, piperitol, 1,8-cyneole, α-pinene, linalool, terpinolene and sabinene; Polygonum minus Huds. Fl. Angl. – linalool, terpinolene, camphene, borneol, 1,8-cyneole, α-pinene, 4-terpineol and 1-octen-3-ol; Polygonum alpinum All. – camphene, sabinene, 1-octen-3-ol, 4-carene, p- and o-cymol, γ-terpinene, borneol, -terpineol; Polygonum persicaria L. - α-pinene, sabinene, -terpinene, 4-carene, 1,8-cyneole, borneol, 4-terpineol. Antibacterial activity was researched relating to strains of gram-positive bacteria Staphylococcus aureus, Bacillus subtilis, Streptococcus agalacticae, relating to gram-negative strain Escherichia coli and to yeast fungus Сandida albicans using agar diffusion method. The medicines of comparison were gentamicin for bacteria and nystatin for yeast fungus Сandida albicans. It has been shown that Polygonum L. essential oils has moderate antibacterial effect to gram-positive microorganisms and weak antifungal activity to Candida albicans yeast fungus. At the second stage of our researches wound healing properties of ointment form of 3% essential oil was researched on the model of flat dermal wounds. To assess the influence of essential oil on healing processes the model of flat dermal wound. The speed of wound healing on rats of different groups was judged based on assessment the area of a wound from time to time. During research of wound healing properties disturbance of integral in neither group: general condition and behavior of animals, food intake, and excretion. Wound healing action of 3% ointment on base of Polygonum L. essential oil and polyethyleneglycol is comparable with the action of reference substances. As more favorable healing dynamics was observed in the experimental group than in control group, the tested ointment can be deemed more promising for further detailed study as wound healing means.

Keywords: antibacterial, antifungal, bioactive substances, essential oils, isolation, Polygonum L.

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Authors: A. S. Akinbani

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Overdependence on petroleum is causing set back in Nigeria economy. Field survey was carried out to assess the profitability and production of selected arable crops in six selected towns and villages of Ondo southwestern. Data were collected from 240 arable crop farmers with the aid of both primary and secondary data. Data were collected with the use of oral interview and structured questionnaires. Data collected were analyzed using both descriptive and inferential statistics. Forty farmers were randomly selected to give a total number of 240 respondents. 84 farmers interviewed had no formal education, 72 had primary education, 50 farmers attained secondary education while 38 attained beyond secondary education. The majority of the farmers hold less than 10 acres of land. The data collected from the field showed that 192 farmers practiced mixed cropping which includes mixtures of yam, cowpea, cocoyam, vegetable, cassava and maize while only 48 farmers practiced monocropping. Among the sampled farmers, 93% agreed that arable production is profitable while 7% disagreed. The findings show that managerial practices that conserve the soil fertility and reduce labor cost such as planting of leguminous crops and herbicide application instead of using hand held hoe for weeding should be encouraged. All the respondents agreed that yam, cowpea, cocoyam, sweet potato, rice, maize and vegetable production will solve the problem of hunger and increase standard of living compared with petroleum product that Nigeria relied on as means of livelihood.

Keywords: farmers, arable crop, cocoyam, respondents, maize

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Authors: Nkeiruka Queendarline Nwaizugbu

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The use of social media and mobile devices has become acceptable in virtually all areas of today’s world. Hence, this study is a survey that was carried out to find out if students and lecturers in public universities in Rivers State use social networking for educational purposes. The sample of the study comprised of 240 students and 99 lecturers from the University of Port Harcourt and the Rivers State University of science and Technology. The study had five research questions, two hypotheses and the instrument for data collection was a 4-point Likert-type rating scale questionnaire. The data was analysed using mean, standard deviation and z-test. The findings gotten from the analysed data shows that students participate in social networking using different types of web applications but they hardly use them for educational purposes. Some recommendations were also made.

Keywords: internet access, mobile learning, participation, social media, social networking, technology

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Authors: H. Sakamoto, Y. Nakagawara, S. Oguri

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Drought stress is a critical environmental factor that adversely affects crop productivity and quality. Because of their immobile nature, plants have evolved mechanisms to sense and respond to drought stress. We identified a novel locus of Arabidopsis, designated DRA1 (drought responsive ankyrin 1), whose disruption leads to increased drought stress tolerance. DRA1 encodes a transmembrane protein with an ankyrin repeat motif that has been implicated in diverse cellular processes such as signal transduction. RT-PCR analysis revealed that there were at least two splicing variants of DRA1 transcripts in wild type plants. In response to drought stress, the levels of DRA1 transcripts retaining second and third introns were increased, whereas these introns were removed under unstressed conditions. These results suggest that DRA1 protein may negatively regulate plant drought tolerance and that the expression of DRA1 is regulated in response to drought stress by alternative splicing.

Keywords: alternative splicing, ankyrin repeat, Arabidopsis, drought tolerance

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Authors: Adilah Abdul Ghapor, Yong Zulina Zubairi, A. H. M. R. Imon

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Missing value problem is common in statistics and has been of interest for years. This article considers two modern techniques in handling missing data for linear functional relationship model (LFRM) namely the Expectation-Maximization (EM) algorithm and Expectation-Maximization with Bootstrapping (EMB) algorithm using three performance indicators; namely the mean absolute error (MAE), root mean square error (RMSE) and estimated biased (EB). In this study, we applied the methods of imputing missing values in two types of LFRM namely the full model of LFRM and in LFRM when the slope is estimated using a nonparametric method. Results of the simulation study suggest that EMB algorithm performs much better than EM algorithm in both models. We also illustrate the applicability of the approach in a real data set.

Keywords: expectation-maximization, expectation-maximization with bootstrapping, linear functional relationship model, performance indicators

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Authors: Lukholo Raxangana

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Fourth Industrial Revolution (4IR)-era teaching offers in-service mathematics teachers opportunities to use blended approaches to engage learners while teaching mathematics. This study explores in-service high school teachers' experiences with a blended teaching approach to mathematics. This qualitative case study involved eight pre-service teachers from four selected schools in the Sedibeng West District of the Gauteng Province. The study used the community of inquiry model as its analytical framework for data analysis. Data collection was through semi-structured interviews and focus-group discussions to explore in-service teachers' experiences with the influence of blended teaching (BT) on learning mathematics. The study results are the impact of load-shedding, benefits of BT, and perceptions of in-service and hindrances of BT. Based on these findings, the study recommends that further research should focus on developing data-free BT tools to assist during load-shedding, regardless of location.

Keywords: bended teaching, teachers, in-service, and mathematics

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Authors: Michael Ajide Oyinloye

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The natural environment is made up of air, water and soil. The release of emission of industrial waste into anyone of the components of the environment causes pollution. Industrial pollution significantly threatens the inherent right of people, to the enjoyment of a safe and secure environment. The aim of this paper is to assess the effect of environmental pollution and health risks of residents living near Ewekoro Cement factory. The research made use of IKONOS imagery for Geographical Information System (GIS) to buffer and extract buildings that are less than 1 km to the plant, within 1 km to 5 km and above 5 km to the factory. Also, a questionnaire was used to elicit information on the socio-economic factors, the effect of environmental pollution on residents and measures adopted to control industrial pollution on the residents. Findings show that most buildings that between less than 1 km and 1 km to 5 km to the factory have high health risk in the study area. The study recommended total relocation for the residents of the study area to reduce risk health problems.

Keywords: environmental pollution, health risk, GIS, satellite imagery, ewekoro

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Authors: Maria Isabel Garcia-Planas, Maria Victoria Garcia-Camba

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The use of brain stem auditory evoked potential (BAEP) is a common way to study the auditory function of people, a way to learn the functionality of a part of the brain neuronal groups that intervene in the learning process by studying the behaviour of wave VI. The latest advances in neuroscience have revealed the existence of different brain activity in the learning process that can be highlighted through the use of innocuous, low-cost, and easy-access techniques such as, among others, the BAEP that can help us to detect early possible neurodevelopmental difficulties for their subsequent assessment and cure. To date and to the authors' best knowledge, only the latency data obtained, observing the first to V waves and mainly in the left ear, were taken into account. This work shows that it is essential to take into account both ears; with these latest data, it has been possible had diagnosed more precise some cases than with the previous data had been diagnosed as 'normal' despite showing signs of some alteration that motivated the new consultation to the specialist.

Keywords: ear, neurodevelopment, auditory evoked potentials, intervals of normality, learning disabilities

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Authors: Prateek Saxena, Sanjeev Singh, Julius Roy

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The security of the power distribution grid remains a paramount to the utility professionals while enhancing and making it more efficient. The most serious threat to the system can be maintaining the transformers, as the load is ever increasing with the addition of elements like electric vehicles. In this paper, intelligent transformer monitoring and grid management has been proposed. The engineering is done to use the evolving data from the smart meter for grid analytics and diagnostics for preventive maintenance. The two-tier architecture for hardware and software integration is coupled to form a robust system for the smart grid. The proposal also presents interoperable meter standards for easy integration. Distribution transformer analytics based on real-time data benefits utilities preventing outages, protects the revenue loss, improves the return on asset and reduces overall maintenance cost by predictive monitoring.

Keywords: electric vehicle charging, transformer monitoring, data analytics, intelligent grid

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Authors: Merve Aygün Esastürk, Deren Ataç Yılmaz, Görkem Oğur, Emre Özgen Kuzu, Sadık Ödemiş

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Hydrocracker plants are one of the most complicated and most profitable units in the refinery process. It takes long chain paraffinic hydrocarbons as feed and turns them into smaller and more valuable products, mainly kerosene and diesel under high pressure with the excess amount of hydrogen. Controlling the product qualities well directly contributes to the unit profit. Control of a plant is mainly based on PID and MPC controllers. Controlling the reaction section is important in terms of reaction severity. However, controlling the fractionation section is more crucial since the end products are separated in fractionation section. In this paper, the importance of well-configured base layer control mechanism, composed of PID controllers, is highlighted. For this purpose, two different base layer control scheme is applied in a hydrocracker fractionator column performances of schemes, which is a direct contribution to better product quality, are compared.

Keywords: controller, distillation, configuration selection, hydrocracker, model predictive controller, proportional-integral-derivative controller

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Authors: ChunYi Peng, Wei Hsuan CHeng, Shyh Kuang Ueng

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This study focuses on the application of self-organizing maps (SOM) technology in analyzing credit card transaction data, aiming to enhance the accuracy and efficiency of fraud detection. Som, as an artificial neural network, is particularly suited for pattern recognition and data classification, making it highly effective for the complex and variable nature of credit card transaction data. By analyzing transaction characteristics with SOM, the research identifies abnormal transaction patterns that could indicate potentially fraudulent activities. Moreover, this study has developed a specialized visualization tool to intuitively present the relationships between SOM analysis outcomes and transaction data, aiding financial institution personnel in quickly identifying and responding to potential fraud, thereby reducing financial losses. Additionally, the research explores the integration of SOM technology with composite intelligent system technologies (including finite state machines, fuzzy logic, and decision trees) to further improve fraud detection accuracy. This multimodal approach provides a comprehensive perspective for identifying and understanding various types of fraud within credit card transactions. In summary, by integrating SOM technology with visualization tools and composite intelligent system technologies, this research offers a more effective method of fraud detection for the financial industry, not only enhancing detection accuracy but also deepening the overall understanding of fraudulent activities.

Keywords: self-organizing map technology, fraud detection, information visualization, data analysis, composite intelligent system technologies, decision support technologies

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Authors: Jianfeng Hu

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Personal authentication based on electroencephalography (EEG) signals is one of the important field for the biometric technology. More and more researchers have used EEG signals as data source for biometric. However, there are some disadvantages for biometrics based on EEG signals. The proposed method employs entropy measures for feature extraction from EEG signals. Four type of entropies measures, sample entropy (SE), fuzzy entropy (FE), approximate entropy (AE) and spectral entropy (PE), were deployed as feature set. In a silhouettes calculation, the distance from each data point in a cluster to all another point within the same cluster and to all other data points in the closest cluster are determined. Thus silhouettes provide a measure of how well a data point was classified when it was assigned to a cluster and the separation between them. This feature renders silhouettes potentially well suited for assessing cluster quality in personal authentication methods. In this study, “silhouettes scores” was used for assessing the cluster quality of k-means clustering algorithm is well suited for comparing the performance of each EEG dataset. The main goals of this study are: (1) to represent each target as a tuple of multiple feature sets, (2) to assign a suitable measure to each feature set, (3) to combine different feature sets, (4) to determine the optimal feature weighting. Using precision/recall evaluations, the effectiveness of feature weighting in clustering was analyzed. EEG data from 22 subjects were collected. Results showed that: (1) It is possible to use fewer electrodes (3-4) for personal authentication. (2) There was the difference between each electrode for personal authentication (p<0.01). (3) There is no significant difference for authentication performance among feature sets (except feature PE). Conclusion: The combination of k-means clustering algorithm and silhouette approach proved to be an accurate method for personal authentication based on EEG signals.

Keywords: personal authentication, K-mean clustering, electroencephalogram, EEG, silhouettes

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Authors: Jagriti Mishra, Vasundhara Chaudhary

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Introduction: The case highlights various issues and challenges faced by Khanna Enterprises while conceptualizing and execution of launching Active Leisure wear in the domestic market, where different steps involved in the range planning and production have been elaborated. Although Khanna Enterprises was an established company which dealt in the production of knitted and woven garments, they took the risk of launching a new concept- Active Leisure wear for Millennials. Methodology: It is based on primary and secondary research where data collection has been done through survey, in-depth interviews and various reports, forecasts, and journals. Findings: The research through primary and secondary data and execution of active leisure wear substantiated the acceptance, not only by the millennials but also by the generation X. There was a demand of bigger sizes as well as more muted colours. Conclusion: The sales data paved the way for future product development in tune with the strengths of Khanna Enterprises.

Keywords: millennials, range planning, production, active leisure wear

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Authors: Bahareh Ansari

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Background: The Open Government Data (OGD) movement in the last decade has encouraged many government organizations around the world to make their data publicly available to advance democratic processes. But current open data platforms have not yet reached to their full potential in supporting all interested parties. To make the data useful and understandable for everyone, scholars suggested that opening the data should be supplemented by visualization. However, different visualizations of the same information can dramatically change an individual’s cognitive and emotional experience in working with the data. This study reviews the data visualization literature to create a list of the methods empirically tested to enhance users’ performance and experience in working with a visualization tool. This list can be used in evaluating the OGD visualization practices and informing the future open data initiatives. Methods: Previous reviews of visualization literature categorized the visualization outcomes into four categories including recall/memorability, insight/comprehension, engagement, and enjoyment. To identify the papers, a search for these outcomes was conducted in the abstract of the publications of top-tier visualization venues including IEEE Transactions for Visualization and Computer Graphics, Computer Graphics, and proceedings of the CHI Conference on Human Factors in Computing Systems. The search results are complemented with a search in the references of the identified articles, and a search for 'open data visualization,' and 'visualization evaluation' keywords in the IEEE explore and ACM digital libraries. Articles are included if they provide empirical evidence through conducting controlled user experiments, or provide a review of these empirical studies. The qualitative synthesis of the studies focuses on identification and classifying the methods, and the conditions under which they are examined to positively affect the visualization outcomes. Findings: The keyword search yields 760 studies, of which 30 are included after the title/abstract review. The classification of the included articles shows five distinct methods: interactive design, aesthetic (artistic) style, storytelling, decorative elements that do not provide extra information including text, image, and embellishment on the graphs), and animation. Studies on decorative elements show consistency on the positive effects of these elements on user engagement and recall but are less consistent in their examination of the user performance. This inconsistency could be attributable to the particular data type or specific design method used in each study. The interactive design studies are consistent in their findings of the positive effect on the outcomes. Storytelling studies show some inconsistencies regarding the design effect on user engagement, enjoyment, recall, and performance, which could be indicative of the specific conditions required for the use of this method. Last two methods, aesthetics and animation, have been less frequent in the included articles, and provide consistent positive results on some of the outcomes. Implications for e-government: Review of the visualization best-practice methods show that each of these methods is beneficial under specific conditions. By using these methods in a potentially beneficial condition, OGD practices can promote a wide range of individuals to involve and work with the government data and ultimately engage in government policy-making procedures.

Keywords: best practices, data visualization, literature review, open government data

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Authors: Minhee Son, Kyung Nam Kim

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This study explores the plan of the Korean and Japanese governments to transition into the hydrogen economy. Two motor companies, Hyundai Motor Company from Korea and Toyota from Japan, released the Hydrogen Fuel Cell Vehicle to monopolize the green energy automobile market. Although, they are the main countries which emit greenhouse gas, hydrogen energy can bring from a certain industry places, such as chemical plants and steel mills. Recent, the two countries have been focusing on the hydrogen industry including a fuel cell vehicle, a hydrogen station, a fuel cell plant, a residential fuel cell. The purpose of this paper is to find out the differences of the policies in the two countries to be hydrogen societies. We analyze the behavior of the public and private sectors in Korea and Japan about hydrogen energy and fuel cells for the transition of the hydrogen economy. Finally we show the similarities and differences of both countries in hydrogen fuel cells. And some cities have feature such as Hydrogen cities. Hydrogen energy can make impact environmental sustainability.

Keywords: fuel cell, hydrogen city, hydrogen fuel cell vehicle, hydrogen station, hydrogen energy

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Authors: David Levy

Abstract:

The newly released Distributed System Interface 3 (DSI3) Bus Standard specification defines 3 modulation levels from which 16 valid symbols are coded. This structure creates power consumption variations depending on the transmitted data of a factor of more than 2 between minimum and maximum. The power generation unit has to consider therefore the worst case maximum consumption all the time and be built accordingly. This paper proposes a method to reduce both the average current consumption and worst case current consumption. The transmitter randomizes the data using several pseudo-random sequences. It then estimates the energy consumption of the generated frames and selects to transmit the one which consumes the least. The transmitter also prepends the index of the pseudo-random sequence, which is not randomized, to allow the receiver to recover the original data using the correct sequence. We show that in the case that the frame occupies most of the DSI3 synchronization period, we achieve average power consumption reduction by up to 13% and the worst case power consumption is reduced by 17.7%.

Keywords: DSI3, energy, power consumption, randomization

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