Search results for: negative data

Authors: Anu Malhotra

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An Ad-hoc network is one that is an autonomous, self configuring network made up of mobile nodes connected via wireless links. Ad-hoc networks often consist of nodes, mobile hosts (MH) or mobile stations (MS, also serving as routers) connected by wireless links. Different routing protocols are used for data transmission in between the nodes in an adhoc network. In this paper two protocols (OLSR and AODV) are analyzed on the basis of two parameters i.e. time delay and throughput with different data rates. On the basis of these analysis, we observed that with same data rate, AODV protocol is having more time delay than the OLSR protocol whereas throughput for the OLSR protocol is less compared to the AODV protocol.

Keywords: routing adhoc, mobile hosts, mobile stations, OLSR protocol, AODV protocol

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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: 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: Shreya Srivastava, Sagnik Dey

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Aerosol direct radiative forcing (ADRF) refers to the alteration of the Earth's energy balance from the scattering and absorption of solar radiation by aerosol particles. India experiences substantial ADRF due to high aerosol loading from various sources. These aerosols' radiative impact depends on their physical characteristics (such as size, shape, and composition) and atmospheric distribution. Quantifying ADRF is crucial for understanding aerosols’ impact on the regional climate and the Earth's radiative budget. In this study, we have taken radiation data from Clouds and the Earth’s Radiant Energy System (CERES, spatial resolution=1ox1o) for 22 years (2000-2021) over the Indian subcontinent. Except for a few locations, the short-wave DARF exhibits aerosol cooling at the TOA (values ranging from +2.5 W/m2 to -22.5W/m2). Cooling due to aerosols is more pronounced in the absence of clouds. Being an aerosol hotspot, higher negative ADRF is observed over the Indo-Gangetic Plain (IGP). Aerosol Forcing Efficiency (AFE) shows a decreasing seasonal trend in winter (DJF) over the entire study region while an increasing trend over IGP and western south India during the post-monsoon season (SON) in clear-sky conditions. Analysing atmospheric heating and AOD trends, we found that only the aerosol loading is not governing the change in atmospheric heating but also the aerosol composition and/or their vertical profile. We used a Multi-angle Imaging Spectro-Radiometer (MISR) Level-2 Version 23 aerosol products to look into aerosol composition. MISR incorporates 74 aerosol mixtures in its retrieval algorithm based on size, shape, and absorbing properties. This aerosol mixture information was used for analysing long-term changes in aerosol composition and dominating aerosol species corresponding to the aerosol forcing value. Further, ADRF derived from this method is compared with around 35 studies across India, where a plane parallel Radiative transfer model was used, and the model inputs were taken from the OPAC (Optical Properties of Aerosols and Clouds) utilizing only limited aerosol parameter measurements. The result shows a large overestimation of TOA warming by the latter (i.e., Model-based method).

Keywords: aerosol radiative forcing (ARF), aerosol composition, MISR, CERES, SBDART

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Authors: Nan Xu

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In airlines, the crew scheduling problem is usually decomposed into two stages: crew pairing and crew rostering. In the crew pairing stage, pairings are generated such that each flight is covered by exactly one pairing and the overall cost is minimized. In the crew rostering stage, the pairings generated in the crew pairing stage are combined with off days, training and other breaks to create individual work schedules. The paper focuses on cabin crew rostering problem, which is challenging due to the extremely large size and the complex working rules involved. In our approach, the objective of rostering consists of two major components. The first is to minimize the number of unassigned pairings and the second is to ensure the fairness to crew members. There are two measures of fairness to crew members, the number of overnight duties and the total fly-hour over a given period. Pairings should be assigned to each crew member so that their actual overnight duties and fly hours are as close to the expected average as possible. Deviations from the expected average are penalized in the objective function. Since several small deviations are preferred than a large deviation, the penalization is quadratic. Our model of the airline crew rostering problem is based on column generation. The problem is decomposed into a master problem and subproblems. The mater problem is modeled as a set partition problem and exactly one roster for each crew is picked up such that the pairings are covered. The restricted linear master problem (RLMP) is considered. The current subproblem tries to find columns with negative reduced costs and add them to the RLMP for the next iteration. When no column with negative reduced cost can be found or a stop criteria is met, the procedure ends. The subproblem is to generate feasible crew rosters for each crew member. A separate acyclic weighted graph is constructed for each crew member and the subproblem is modeled as resource constrained shortest path problems in the graph. Labeling algorithm is used to solve it. Since the penalization is quadratic, a method to deal with non-additive shortest path problem using labeling algorithm is proposed and corresponding domination condition is defined. The major contribution of our model is: 1) We propose a method to deal with non-additive shortest path problem; 2) Operation to allow relaxing some soft rules is allowed in our algorithm, which can improve the coverage rate; 3) Multi-thread techniques are used to improve the efficiency of the algorithm when generating Line-of-Work for crew members. Here a column generation based algorithm for the airline cabin crew rostering problem is proposed. The objective is to assign a personalized roster to crew member which minimize the number of unassigned pairings and ensure the fairness to crew members. The algorithm we propose in this paper has been put into production in a major airline in China and numerical experiments show that it has a good performance.

Keywords: aircrew rostering, aircrew scheduling, column generation, SPPRC

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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: Farizy Yunaz, Catur Sasongko

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This research aims to provide the empirical evidence regarding cost stickiness behavior and its determinants on listed manufacturing companies. Hypothesis testing is performed using pooled least square method. The result concludes that there is cost stickiness behavior in selling, general and administrative costs. In term of determinants, firm-specific adjustment costs measured by asset intensity and employee intensity have significant positive impact on the level of cost stickiness. Meanwhile, earnings target and leverage have significant negative impact on the level of cost stickiness. However, the management empire building incentives measured by free cash flow has no significant positive impact.

Keywords: adjustment cost, cost behavior, cost stickiness, earnings target, leverage, management empire building incentive

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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: Yifan Lu, Ying Cui, Ying Zhu, Edward S. Lu, Rebecca Zeng, Rohan Bajaj, Raviv Katz, Rongrong Le, Jay C. Wang, John B. Miller

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Purpose: Retinal artery occlusion (RAO) is an ophthalmic emergency that can lead to poor visual outcome and is associated with an increased risk of cerebral stroke and cardiovascular events. Fluorescein angiography (FA) is the traditional diagnostic tool for RAO; however, wide-field swept-source optical coherence tomography angiography (WF SS-OCTA), as a nascent imaging technology, is able to provide quick and non-invasive angiographic information with a wide field of view. In this study, we looked for associations between OCT-A vascular metrics and visual acuity in patients with prior diagnosis of RAO. Methods: Patients with diagnoses of central retinal artery occlusion (CRAO) or branched retinal artery occlusion (BRAO) were included. A 6mm x 6mm Angio and a 15mm x 15mm AngioPlex Montage OCT-A image were obtained for both eyes in each patient using the Zeiss Plex Elite 9000 WF SS-OCTA device. Each 6mm x 6mm image was divided into nine Early Treatment Diabetic Retinopathy Study (ETDRS) subfields. The average measurement of the central foveal subfield, inner ring, and outer ring was calculated for each parameter. Non-perfusion area (NPA) was manually measured using 15mm x 15mm Montage images. A linear regression model was utilized to identify a correlation between the imaging metrics and visual acuity. A P-value less than 0.05 was considered to be statistically significant. Results: Twenty-five subjects were included in the study. For RAO eyes, there was a statistically significant negative correlation between vision and retinal thickness as well as superficial capillary plexus vessel density (SCP VD). A negative correlation was found between vision and deep capillary plexus vessel density (DCP VD) without statistical significance. There was a positive correlation between vision and choroidal thickness as well as choroidal volume without statistical significance. No statistically significant correlation was found between vision and the above metrics in contralateral eyes. For NPA measurements, no significant correlation was found between vision and NPA. Conclusions: This is the first study to our best knowledge to investigate the utility of WF SS-OCTA in RAO and to demonstrate correlations between various retinal vascular imaging metrics and visual outcomes. Further investigations should explore the associations between these imaging findings and cardiovascular risk as RAO patients are at elevated risk for symptomatic stroke. The results of this study provide a basis to understand the structural changes involved in visual outcomes in RAO. Furthermore, they may help guide management of RAO and prevention of cerebral stroke and cardiovascular accidents in patients with RAO.

Keywords: OCTA, swept-source OCT, retinal artery occlusion, Zeiss Plex Elite

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Authors: Estibe Dagne Mekonnen

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In recent years, the prevalence of undernourishment was 30 percent for sub-Saharan Africa, compared with 16 percent for Asia and the Pacific (Ali, 2011). In Ethiopia, almost 40 percent of the total population in the country and 57 percent of Addis Ababa population lives below the international poverty line of US$ 1.25 per day (UNICEF, 2009). This study aims to analyze the determinant of household food secrity in Addis Ababa city administration. Primary data were collected from a survey of 256 households in the selected sub-city, namely Addis Ketema, Arada, and Kolfe Keranio, in the year 2022. Both Purposive and multi-stage cluster random sampling procedures were employed to select study areas and respondents. Descriptive statistics and order logistic regression model were used to test the formulated hypotheses. The result reveals that out of the total sampled households, 25% them were food secured, 13% were mildly food insecure, 26% were moderately food insecure and 36% were severely food insecure. The study indicates that household family size, house ownership, household income, household food source, household asset possession, household awareness on inflation, household access to social protection program, household access to credit and saving and household access to training and supervision on food security have a positive and significant effect on the likelihood of household food security status. However, marital status of household head, employment sector of household head, dependency ratio and household’s nonfood expenditure has a negative and significant influence on household food security status. The study finally suggests that the government in collaboration with financial institutions and NGO should work on sustaining household food security by creating awareness, providing credit, facilitate rural-urban linkage between producer and consumer and work on urban infrastructure improvement. Moreover, the governments also work closely and monitor consumer good suppliers, if possible find a way to subsidize consumable goods to more insecure households and make them to be food secured. Last but not least, keeping this country’s peace will play a crucial role to sustain food security.

Keywords: determinants, household, food security, order logit model, Addis Ababa

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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: Asma Naim, Warda Mushtaq

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Staphylococcus species are the most versatile and adaptive organism. They are widespread and naturally found on the skin, mucosa and nose in humans. Among these, Staphylococcus aureus is the most important species. These organisms act as opportunistic pathogens and can infect various organs of the host, causing minor skin infection to severe toxin mediated diseases, and life threatening nosocomial infections. Staphylococcus aureus has acquired resistance against β-lactam antibiotics by the production of β-lactamase, and Methicillin-Resistant Staphylococcus aureus (MRSA) strains have also been reported with increasing frequency. MRSA strains have been associated with nosocomial as well as community acquired infections. Medicinal plants have enormous potential as antimicrobial substances and have been used in traditional medicine. Search for medicinally valuable plants with antimicrobial activity is being emphasized due to increasing antibiotic resistance in bacteria. In the present study, the antibacterial potential of Rosmarinus officinalis (Rosemary) and Murraya koenigii (curry leaves) was evaluated. These are common household herbs used in food as enhancer of flavor and aroma. The crude aqueous infusion, decoction and ethanolic extracts of curry leaves and rosemary and essential oil of rosemary were investigated in the present study for antibacterial activity against multi-drug resistant Staphylococcus strains using well diffusion method. In the present study, 60 Multi-drug resistant clinical isolates of S. aureus (43) and Coagulase Negative Staphylococci (CoNS) (17) were screened against different concentrations of crude extracts of Rosmarinus officinalis and Murraya koenigii. Out of these 60 isolates, 43 were sensitive to the aqueous infusion of rosemary; 23 to aqueous decoction and 58 to ethanolic extract whereas, 24 isolates were sensitive to the essential oil. In the case of the curry leaves, no antibacterial activity was observed in aqueous infusion and decoction while only 14 isolates were sensitive to the ethanolic extract. The aqueous infusion of rosemary (50% concentration) exhibited a zone of inhibition of 21(±5.69) mm. against CoNS and 17(±4.77) mm. against S. aureus, the zone of inhibition of 50% concentration of aqueous decoction of rosemary was also larger against CoNS 17(±5.78) mm. then S. aureus 13(±6.91) mm. and the 50% concentrated ethanolic extract showed almost similar zone of inhibition in S. aureus 22(±3.61) mm. and CoNS 21(±7.64) mm. whereas, the essential oil of rosemary showed greater zone of inhibition against S. aureus i.e., 16(±4.67) mm. while CoNS showed 15(±6.94) mm. These results show that ethanolic extract of rosemary has significant antibacterial activity. Aqueous infusion and decoction of curry leaves revealed no significant antibacterial potential against all Staphylococcal species and ethanolic extract also showed only a weak response. Staphylococcus strains were susceptible to crude extracts and essential oil of rosemary in a dose depend manner, where the aqueous infusion showed highest zone of inhibition and ethanolic extract also demonstrated antistaphylococcal activity. These results demonstrate that rosemary possesses antistaphylococcal activity.

Keywords: antibacterial activity, curry leaves, multidrug resistant, rosemary, S. aureus

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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: Yu Du, Jian-Guo Wang

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Green consumption is a key link to develop the ecological economy, and consumers are vital to carry out green consumption. With environmental awareness gradually being aroused, consumers often fail to turn their positive attitude into actual green consumption behavior. According to behavior reasoning theory, reasons for adoption have a direct (positive) influence on consumers’ attitude while reasons against adoption have a direct (negative) influence on consumers’ adoption intentions, the incongruous coexistence of which leads to the attitude-behavior gap of green consumption. Based on behavior reasoning theory, this research integrates reasons for adoption and reasons against adoption into a proposed model, in which reasons both for and against green consumption mediate the relationship between consumer’ values, attitudes, and behavioral intentions. It not only extends the conventional theory of reasoned action but also provides a reference for the government and enterprises to design the repairing strategy of green consumption attitude-behavior gap.

Keywords: green product, attitude-behavior gap, behavior reasoning theory, green consumption, SEM

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Authors: Leei Wong

Abstract:

Changes in globalized contexts precipitate changing perceptions concerning linguistic politeness practices. Within these changing contexts, misunderstanding or stereotypification of politeness norms may lead to negative consequences such as hostility or even communication breakdown. With China’s rising influence, the country is offering a vast potential market for global economic development and diplomatic relations and opportunities for intercultural interaction, and many outside China are subsequently learning Chinese. These trends bring both opportunities and pitfalls for intercultural communication, including within the important field of politeness awareness. One internationally recognized benchmark for the study and classification of languages – the updated 2018 CEFR (Common European Framework of Reference for Language) Companion Volume New Descriptors (CEFR/CV) – classifies politeness as a B1 (or intermediate) level descriptor on the scale of Politeness Conventions. This provides some indication of the relevance of politeness awareness within new globalized contexts for fostering better intercultural communication. This study specifically examines Bald on record politeness strategies presented in current beginner TCAL textbooks used in Australian tertiary education through content-analysis. The investigation in this study involves the purposive sampling of commercial textbooks published in America and China followed by interpretive content analysis. The philosophical position of this study is therefore located within an interpretivist ontology, with a subjectivist epistemological perspective. It sets out with the aim to illuminate the characteristics of Chinese Bald on record strategies that are deemed significant in the present-world context through Chinese textbook writers and curriculum designers. The data reveals significant findings concerning politeness strategies in beginner stage curriculum, and also opens the way for further research on politeness strategies in intermediate and advanced level textbooks for additional language learners. This study will be useful for language teachers, and language teachers-in-training, by generating awareness and providing insights and advice into the teaching and learning of Bald on record politeness strategies. Authors of textbooks may also benefit from the findings of this study, as awareness is raised of the need to include reference to understanding politeness in language, and how this might be approached.

Keywords: linguistic politeness, higher education, Chinese language, additional language

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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: K. Masera, A. K. Hossain

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Hardly any neat biodiesel satisfies the European EN14214 standard for compression ignition engine application. To satisfy the EN14214 standard, various additives are doped into biodiesel; however, biodiesel additives might cause other problems such as increase in the particular emission and increased specific fuel consumption. In addition, the additives could be expensive. Considering the increasing level of greenhouse gas GHG emissions and fossil fuel depletion, it is forecasted that the use of biodiesel will be higher in the near future. Hence, the negative aspects of the biodiesel additives will likely to gain much more importance and need to be replaced with better solutions. This study aims to satisfy the European standard EN14214 by blending the biodiesels derived from sustainable feedstocks. Waste Cooking Oil (WCO) and Animal Fat Oil (AFO) are two sustainable feedstocks in the EU (including the UK) for producing biodiesels. In the first stage of the study, these oils were transesterified separately and neat biodiesels (W100 & A100) were produced. Secondly, the biodiesels were blended together in various ratios: 80% WCO biodiesel and 20% AFO biodiesel (W80A20), 60% WCO biodiesel and 40% AFO biodiesel (W60A40), 50% WCO biodiesel and 50% AFO biodiesel (W50A50), 30% WCO biodiesel and 70% AFO biodiesel (W30A70), 10% WCO biodiesel and 90% AFO biodiesel (W10A90). The prepared samples were analysed using Thermo Scientific Trace 1300 Gas Chromatograph and ISQ LT Mass Spectrometer (GC-MS). The GS-MS analysis gave Fatty Acid Methyl Ester (FAME) breakdowns of the fuel samples. It was found that total saturation degree of the samples was linearly increasing (from 15% for W100 to 54% for A100) as the percentage of the AFO biodiesel was increased. Furthermore, it was found that WCO biodiesel was mainly (82%) composed of polyunsaturated FAMEs. Cetane numbers, iodine numbers, calorific values, lower heating values and the densities (at 15 ^oC) of the samples were estimated by using the mass percentages data of the FAMEs. Besides, kinematic viscosities (at 40 °C and 20 °C), densities (at 15 °C), heating values and flash point temperatures of the biomixture samples were measured in the lab. It was found that estimated and measured characterisation results were comparable. The current study concluded that biomixture fuel samples W60A40 and W50A50 were perfectly satisfying the European EN 14214 norms without any need of additives. Investigation on engine performance, exhaust emission and combustion characteristics will be conducted to assess the full feasibility of the proposed biomixture fuels.

Keywords: biodiesel, blending, characterisation, CI engine

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Authors: Syeda Fahria Hoque Mimmi, Aparna Islam

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Genetically engineered (GE) plants are the need of time for increased demand for food. A complete set of regulations need to be followed from the development of a GE plant to its release into the environment. The whole regulation system is categorized into separate stages for maintaining the proper biosafety. Environmental risk assessment (ERA) is one of such crucial stages in the whole process. ERA identifies potential risks and their impacts through science-based evaluation where it is done in a case-by-case study. All the countries which deal with GE plants follow specific guidelines to conduct a successful ERA. In this study, ERA guidelines of 4 developing and 4 developed countries, including Bangladesh, were compared. ERA guidelines of countries such as India, Canada, Australia, the European Union, Argentina, Brazil, and the US were considered as a model to conduct the comparison study with Bangladesh. Initially, ten parameters were detected to compare the required data and information among all the guidelines. Surprisingly, an adequate amount of data and information requirements (e.g., if the intended modification/new traits of interest has been achieved or not, the growth habit of GE plants, consequences of any potential gene flow upon the cultivation of GE plants to sexually compatible plant species, potential adverse effects on the human health, etc.) matched between all the countries. However, a few differences in data requirement (e.g., agronomic conventions of non-transformed plants, applicants should clearly describe experimental procedures followed, etc.) were also observed in the study. Moreover, it was found that only a few countries provide instructions on the quality of the data used for ERA. If these similarities are recognized in a more framed manner, then the approval pathway of GE plants can be shared.

Keywords: GE plants, ERA, harmonization, ERA guidelines, Information and data requirements

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Authors: Chen Jun

Abstract:

This study investigates the impact of family involvement, a pivotal factor shaping the management structure of family firms, on the firm’s innovation outputs. The independent variable focuses on the percentage number of family members serving as directors, supervisors and senior management. Our hypothesis suggests that family involvement tends to make management more conservative, thereby increasing the likelihood of impeding innovation investments and resulting in adverse effects on innovation output. Our findings reveal that Chinese family firms with high family involvement exhibit poorer innovation outputs compared to those with lower family involvement. Subsample analyses indicate that this negative influence of family involvement on innovation output is strengthened as the firm faces higher industry competition and a low marketization context. The findings of our paper contribute to the literature on family involvement by empirically illustrating how family involvement hinders innovation efforts and performance in Chinese family firms.

Keywords: family firm, family involvement, firm innovation, Chinese family firm

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Authors: Lukholo Raxangana

Abstract:

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: P. S. BEDI* , Neavty Thakur, Balvınder Sıngh

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In the present study an attempt has been made to prepare the crude extracts of leaves and stem of ‘Girardinia heterophylla’ by using various solvents like petroleum ether, ethanol and double distilled water. The samples were given the code NGLS 1, NGLS 2, NGLS 3, NGSS 1, NGSS 2 and NGSS 3 respectively. All the extracts were used to study their antimicrobial activity against gram positive bacteria eg. Bacillus subtilis, Gram negative bacteria eg. E. coli, K. pneumonia and antifungal activity against Aspergillus niger. The results of the antimicrobial activity showed that all the crude extracts of the plant posseses antibacterial activity. Maximum antibacterial activity was shown by NGLS 2, NGLS 3 and NGSS 3 against K. pneumonia. The growth of fungus A. niger was also inhibited by all the crude extracts. Maximum inhibition was shown by NGSS 2 followed by NGSS 1.

Keywords: Girardinia heterophylla, leaves and stem extracts, Antibacterial activity, antifungal activity.

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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: Tydra Preyear, Victor Clincy

Abstract:

Quantum computing presents many computational advantages over classical computing methods due to the utilization of quantum mechanics. The capability of this computing infrastructure poses threats to standard cryptographic systems such as RSA and AES, which are designed for classical computing environments. This paper discusses the impact that quantum computing has on cryptography, while focusing on the evolution from classical cryptographic concepts to quantum and post-quantum cryptographic concepts. Standard Cryptography is essential for securing data by utilizing encryption and decryption methods, and these methods face vulnerability problems due to the advancement of quantum computing. In order to counter these vulnerabilities, the methods that are proposed are quantum cryptography and post-quantum cryptography. Quantum cryptography uses principles such as the uncertainty principle and photon polarization in order to provide secure data transmission. In addition, the concept of Quantum key distribution is introduced to ensure more secure communication channels by distributing cryptographic keys. There is the emergence of post-quantum cryptography which is used for improving cryptographic algorithms in order to be more secure from attacks by classical and quantum computers. Throughout this exploration, the paper mentions the critical role of the advancement of cryptographic methods to keep data integrity and privacy safe from quantum computing concepts. Future research directions that would be discussed would be more effective cryptographic methods through the advancement of technology.

Keywords: quantum computing, quantum cryptography, cryptography, data integrity and privacy

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Authors: Prateek Saxena, Sanjeev Singh, Julius Roy

Abstract:

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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