Search results for: function of the country image

Authors: Skyler Kim

Abstract:

An early diagnosis of leukemia has always been a challenge to doctors and hematologists. On a worldwide basis, it was reported that there were approximately 350,000 new cases in 2012, and diagnosing leukemia was time-consuming and inefficient because of an endemic shortage of flow cytometry equipment in current clinical practice. As the number of medical diagnosis tools increased and a large volume of high-quality data was produced, there was an urgent need for more advanced data analysis methods. One of these methods was the AI approach. This approach has become a major trend in recent years, and several research groups have been working on developing these diagnostic models. However, designing and implementing a leukemia diagnostic system in real clinical environments based on a deep learning approach with larger sets remains complex. Leukemia is a major hematological malignancy that results in mortality and morbidity throughout different ages. We decided to select acute lymphocytic leukemia to develop our diagnostic system since acute lymphocytic leukemia is the most common type of leukemia, accounting for 74% of all children diagnosed with leukemia. The results from this development work can be applied to all other types of leukemia. To develop our model, the Kaggle dataset was used, which consists of 15135 total images, 8491 of these are images of abnormal cells, and 5398 images are normal. In this paper, we design and implement a leukemia diagnostic system in a real clinical environment based on deep learning approaches with larger sets. The proposed diagnostic system has the function of detecting and classifying leukemia. Different from other AI approaches, we explore hybrid architectures to improve the current performance. First, we developed two independent convolutional neural network models: VGG19 and ResNet50. Then, using both VGG19 and ResNet50, we developed a hybrid deep learning architecture employing transfer learning techniques to extract features from each input image. In our approach, fusing the features from specific abstraction layers can be deemed as auxiliary features and lead to further improvement of the classification accuracy. In this approach, features extracted from the lower levels are combined into higher dimension feature maps to help improve the discriminative capability of intermediate features and also overcome the problem of network gradient vanishing or exploding. By comparing VGG19 and ResNet50 and the proposed hybrid model, we concluded that the hybrid model had a significant advantage in accuracy. The detailed results of each model’s performance and their pros and cons will be presented in the conference.

Keywords: acute lymphoblastic leukemia, hybrid model, leukemia diagnostic system, machine learning

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Authors: Yanjun Chen, Chuanping Hu, Jie Shao, Lin Mei, Chongyang Zhang

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Traditional image classification is based on encoding scheme (e.g. Fisher Vector, Vector of Locally Aggregated Descriptor) with low-level image features (e.g. SIFT, HoG). Compared to these low-level local features, deep convolutional features obtained at the mid-level layer of convolutional neural networks (CNN) have richer information but lack of geometric invariance. For scene classification, there are scattered objects with different size, category, layout, number and so on. It is crucial to find the distinctive objects in scene as well as their co-occurrence relationship. In this paper, we propose a method to take advantage of both deep convolutional features and the traditional encoding scheme while taking object-centric and scene-centric information into consideration. First, to exploit the object-centric and scene-centric information, two CNNs that trained on ImageNet and Places dataset separately are used as the pre-trained models to extract deep convolutional features at multiple scales. This produces dense local activations. By analyzing the performance of different CNNs at multiple scales, it is found that each CNN works better in different scale ranges. A scale-wise CNN adaption is reasonable since objects in scene are at its own specific scale. Second, a fisher kernel is applied to aggregate a global representation at each scale and then to merge into a single vector by using a post-processing method called scale-wise normalization. The essence of Fisher Vector lies on the accumulation of the first and second order differences. Hence, the scale-wise normalization followed by average pooling would balance the influence of each scale since different amount of features are extracted. Third, the Fisher vector representation based on the deep convolutional features is followed by a linear Supported Vector Machine, which is a simple yet efficient way to classify the scene categories. Experimental results show that the scale-specific feature extraction and normalization with CNNs trained on object-centric and scene-centric datasets can boost the results from 74.03% up to 79.43% on MIT Indoor67 when only two scales are used (compared to results at single scale). The result is comparable to state-of-art performance which proves that the representation can be applied to other visual recognition tasks.

Keywords: deep convolutional features, Fisher Vector, multiple scales, scale-specific normalization

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Authors: Mouna Zitouni, Mariem Tounsi

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This research introduces an application of the Riesz mixture model for medical image segmentation for accurate diagnosis and treatment of brain tumors. We propose a pixel classification technique based on the Riesz distribution, derived from an extended Bartlett decomposition. To our knowledge, this is the first study addressing this approach. The Expectation-Maximization algorithm is implemented for parameter estimation. A comparative analysis, using both synthetic and real brain images, demonstrates the superiority of the Riesz model over a recent method based on the Wishart distribution.

Keywords: EM algorithm, segmentation, Riesz probability distribution, Wishart probability distribution

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Authors: Sanaz Farhangi, Habib Alipour

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The main objective of this paper is to explore how social media as a critical platform would increase the interactions between the tourism sector and stakeholders. Nowadays, human interactions through social media in many areas, especially in tourism, provide various experiences and information that users share and discuss. Organizations and firms can gain customer loyalty through social media platforms, albeit consumers' negative image of the product or services. Such a negative image can be reduced through constant communication between produces and consumers, especially with the availability of the new technology. Therefore, effective management of customer relationships in social media creates an extraordinary opportunity for organizations to enhance value and brand loyalty. In this study, we seek to develop a conceptual model for addressing factors such as social media, SCRM, and customer engagement affecting brand loyalty and diminish co-destruction. To support this model, we scanned the relevant literature using a comprehensive category of ideas in the context of marketing and customer relationship management. This will allow exploring whether there is any relationship between social media, customer engagement, social customer relationship management (SCRM), co-destruction, and brand loyalty. SCRM has been explored as a moderating factor in the relationship between customer engagement and social media to secure brand loyalty and diminish co-destruction of the company’s value. Although numerous studies have been conducted on the impact of social media on customers and marketing behavior, there are limited studies for investigating the relationship between SCRM, brand loyalty, and negative e-WOM, which results in the reduction of the co-destruction of value by customers. This study is an important contribution to the tourism and hospitality industry in orienting customer behavior in social media using SCRM. This study revealed that through social media platforms, management can generate discussion and engagement about the product and services, which facilitates customers feeling in an appositive way towards the firm and its product. Study has also revealed that customers’ complaints through social media have a multi-purpose effect; it can degrade the value of the product, but at the same time, it will motivate the firm to overcome its weaknesses and correct its shortcomings. This study has also implications for the managers and practitioners, especially in the tourism and hospitality sector. Future research direction and limitations of the research were also discussed.

Keywords: brand loyalty, co-destruction, customer engagement, SCRM, tourism and hospitality

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Authors: Sigal Gat-Lazer, Ronny Geva, Dan Ramon, Eitan Gur, Daniel Stein

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Introduction: Eating disorders (ED) are common psychopathologies which involve distorted body image and eating disturbances. Binge-purge eating disorders (B/P ED) are characterized by repetitive events of binge eating followed by purges. Patients with B/P ED behavior may be seen as impulsive especially when relate to food stimulation and affective conditions. The current study included innovative modification of the day-night task targeted to assess inhibitory control among patients with B/P ED. Methods: This prospective study included 50 patients with B/P ED during acute phase of illness (T1) upon their admission to specialized ED department in tertiary center. 34 patients repeated the study towards discharge to ambulatory care (T2). Treatment effect was evaluated by BMI and emotional questionnaires regarding depression and anxiety by the Beck Depression Inventory and State Trait Anxiety Inventory questionnaires. Control group included 36 healthy controls with matched demographic parameters who performed both T1 and T2 assessments. The current modification is based on the emotional day-night task (EDNT) which involves five emotional stimulation added to the sun and moon pictures presented to participants. In the current study, we designed the food-emotional modification day night task (F-EDNT) food stimulations of egg and banana which resemble the sun and moon, respectively, in five emotional states (angry, sad, happy, scrambled and neutral). During this computerized task, participants were instructed to push on “day” bottom in response to moon and banana stimulations and on “night” bottom when sun and egg were presented. Accuracy (A) and reaction time (RT) were evaluated and compared between EDNT and F-EDNT as a reflection of participants’ inhibitory control. Results: Patients with B/P ED had significantly improved BMI, depression and anxiety scores on T2 compared to T1 (all p<0.001). Task performance was similar among patients and controls in the EDNT without significant A or RT differences in both T1 and T2. On F-EDNT during T1, B/P ED patients had significantly reduced accuracy in 4/5 emotional stimulation compared to controls: angry (73±25% vs. 84±15%, respectively), sad (69±25% vs. 80±18%, respectively), happy (73±24% vs. 82±18%, respectively) and scrambled (74±24% vs. 84±13%, respectively, all p<0.05). Additionally, patients’ RT to food stimuli was significantly faster compared to neutral ones, in both cry and neutral emotional stimulations (356±146 vs. 400±141 and 378±124 vs. 412±116 msec, respectively, p<0.05). These significant differences between groups as a function of stimulus type were diminished on T2. Conclusion: Having to process food related content, in particular in emotional context seems to be impaired in patients with B/P ED during the acute phase of their illness and elicits greater impulsivity. Innovative modification using such procedures seem to be sensitive to patients’ illness phase and thus may be implemented during screening and follow up through the clinical management of these patients.

Keywords: binge purge eating disorders, day night task modification, eating disorders, food related stimulations

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Authors: Mamidi Ramakrishna Rao

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Doubly-fed induction generator (DFIG) is currently the choice for many wind turbines. These generators, when connected to the grid through a converter, is subjected to varied power system conditions like voltage variation, frequency variation, short circuit fault conditions, etc. Further, many countries like Canada, Germany, UK, Scotland, etc. have distinct grid codes relating to wind turbines. Accordingly, following the network faults, wind turbines have to supply a definite reactive current. To satisfy the requirements including reactive current capability, an optimum electrical design becomes a mandate for DFIG to function. This paper intends to optimize the equivalent circuit parameters of an electrical design for satisfactory DFIG performance. Direct search method has been used for optimization of the parameters. The variables selected include electromagnetic core dimensions (diameters and stack length), slot dimensions, radial air gap between stator and rotor and winding copper cross section area. Optimization for 2 MW DFIG has been executed separately for three objective functions - maximum reactive power capability (Case I), maximum efficiency (Case II) and minimum weight (Case III). In the optimization analysis program, voltage variations (10%), power factor- leading and lagging (0.95), speeds for corresponding to slips (-0.3 to +0.3) have been considered. The optimum designs obtained for objective functions were compared. It can be concluded that direct search method of optimization helps in determining an optimum electrical design for each objective function like efficiency or reactive power capability or weight minimization.

Keywords: direct search, DFIG, equivalent circuit parameters, optimization

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Authors: Nurkhairul Bariyah Baharun, Afzan Adam, Reena Rahayu Md Zin

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Tumor microenvironment (TME) in breast cancer is mainly composed of cancer cells, immune cells, and stromal cells. The interaction between cancer cells and their microenvironment plays an important role in tumor development, progression, and treatment response. The TME in breast cancer includes tumor-infiltrating lymphocytes (TILs) that are implicated in killing tumor cells. TILs can be found in tumor stroma (sTILs) and within the tumor (iTILs). TILs in triple negative breast cancer (TNBC) have been demonstrated to have prognostic and potentially predictive value. The international Immune-Oncology Biomarker Working Group (TIL-WG) had developed a guideline focus on the assessment of sTILs using hematoxylin and eosin (H&E)-stained slides. According to the guideline, the pathologists use “eye balling” method on the H&E stained- slide for sTILs assessment. This method has low precision, poor interobserver reproducibility, and is time-consuming for a comprehensive evaluation, besides only counted sTILs in their assessment. The TIL-WG has therefore recommended that any algorithm for computational assessment of TILs utilizing the guidelines provided to overcome the limitations of manual assessment, thus providing highly accurate and reliable TILs detection and classification for reproducible and quantitative measurement. This study is carried out to develop a TNBC digital whole slide image (WSI) dataset from H&E-stained slides and IHC (CD4+ and CD8+) stained slides. TNBC cases were retrieved from the database of the Department of Pathology, Hospital Canselor Tuanku Muhriz (HCTM). TNBC cases diagnosed between the year 2010 and 2021 with no history of other cancer and available block tissue were included in the study (n=58). Tissue blocks were sectioned approximately 4 µm for H&E and IHC stain. The H&E staining was performed according to a well-established protocol. Indirect IHC stain was also performed on the tissue sections using protocol from Diagnostic BioSystems PolyVue™ Plus Kit, USA. The slides were stained with rabbit monoclonal, CD8 antibody (SP16) and Rabbit monoclonal, CD4 antibody (EP204). The selected and quality-checked slides were then scanned using a high-resolution whole slide scanner (Pannoramic DESK II DW- slide scanner) to digitalize the tissue image with a pixel resolution of 20x magnification. A manual TILs (sTILs and iTILs) assessment was then carried out by the appointed pathologist (2 pathologists) for manual TILs scoring from the digital WSIs following the guideline developed by TIL-WG 2014, and the result displayed as the percentage of sTILs and iTILs per mm² stromal and tumour area on the tissue. Following this, we aimed to develop an automated digital image scoring framework that incorporates key elements of manual guidelines (including both sTILs and iTILs) using manually annotated data for robust and objective quantification of TILs in TNBC. From the study, we have developed a digital dataset of TNBC H&E and IHC (CD4+ and CD8+) stained slides. We hope that an automated based scoring method can provide quantitative and interpretable TILs scoring, which correlates with the manual pathologist-derived sTILs and iTILs scoring and thus has potential prognostic implications.

Keywords: automated quantification, digital pathology, triple negative breast cancer, tumour infiltrating lymphocytes

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Authors: Zdzislaw Kaminski, Zbigniew Czyz, Krzysztof Skiba

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This paper discusses the CFD simulation of a flow around a rotor of a Vertical Axis Wind Turbine. Numerical simulation, unlike experiments, enables us to validate project assumptions when it is designed and avoid a costly preparation of a model or a prototype for a bench test. CFD simulation enables us to compare characteristics of aerodynamic forces acting on rotor working surfaces and define operational parameters like torque or power generated by a turbine assembly. This research focused on the rotor with the blades capable of modifying their working surfaces, i.e. absorbing wind kinetic energy. The operation of this rotor is based on adjusting angular aperture α of the top and bottom parts of the blades mounted on an axis. If this angular aperture α increases, the working surface which absorbs wind kinetic energy also increases. The operation of turbines is characterized by parameters like the angular aperture of blades, power, torque, speed for a given wind speed. These parameters have an impact on the efficiency of assemblies. The distribution of forces acting on the working surfaces in our turbine changes according to the angular velocity of the rotor. Moreover, the resultant force from the force acting on an advancing blade and retreating blade should be as high as possible. This paper is part of the research to improve an efficiency of a rotor assembly. Therefore, using simulation, the courses of the above parameters were studied in three full rotations individually for each of the blades for three angular apertures of blade working surfaces, i.e. 30 °, 60 °, 90 °, at three wind speeds, i.e. 4 m / s, 6 m / s, 8 m / s and rotor speeds ranging from 100 to 500 rpm. Finally, there were created the characteristics of torque coefficients and power as a function of time for each blade separately and for the entire rotor. Accordingly, the correlation between the turbine rotor power as a function of wind speed for varied values of rotor rotational speed. By processing this data, the correlation between the power of the turbine rotor and its rotational speed for each of the angular aperture of the working surfaces was specified. Finally, the optimal values, i.e. of the highest output power for given wind speeds were read. The research results in receiving the basic characteristics of turbine rotor power as a function of wind speed for the three angular apertures of the blades. Given the nature of rotor operation, the growth in the output turbine can be estimated if angular aperture of the blades increases. The controlled adjustment of angle α enables a smooth adjustment of power generated by a turbine rotor. If wind speed is significant, this type of adjustment enables this output power to remain at the same level (by reducing angle α) with no risk of damaging a construction. This work has been financed by the Polish Ministry of Science and Higher Education.

Keywords: computational fluid dynamics, numerical analysis, renewable energy, wind turbine

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Authors: Alami Ilyass, Loubna Kharchoufa, Elachouri Mostafa

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The two great realms of living diversity are cultural and biological. Today, both are being lost at an alarming rate. Of all the Earth’s biological diversity, plant kingdom is of high significance, and most essential to human welfare, in fact, medicinal plants are extensively exploited for countless purposes. Among these multiple uses, medicinal plants are the most important source of medicine for humankind healthcare and well being. In recent years there has been a great surge of public interest in the use of herbs and plants. Some scientists have viewed this phenomenon as a modern “herbal renaissance”. The importance of plants as medicines in developed and developing countries has recently been acknowledged by the United Nations (UN). However, to date fewer than 5% of the approximately 250,000 species of higher plants have been exhaustively studied for their potential pharmacological activity. A number of drugs from ethnobotanical leads have provided significant milestones in Western medicine. Despite this success, pharmacognosy research on Moroccan flora needs more studies aimed at the exploration of their therapeutic potential. A major weakness is the absence of strong funding agencies in the country, and a real national drug discovery program. Moreover, the lack of the coordination between different universities and research institutions leads, in most cases, to a waste of time, money and efforts of many researchers. In this work, we focus our attention on research into traditional indigenous medicinal plants in Morocco. Three parts constitute the head lines of this work: In the first one, we take up Moroccan biodiversity matter, the second part is devoted principally to the state of research into medicinal plants by Moroccan scholars and the last one is consecrated to the debate of factors which handicap the progress of research on phytomedicine in Morocco. The objectives of the present study are twofold: first, to highlight the state of the medicinal plants researches in Morocco. Second goal is to assess and correlate the levels of knowledge of the local flora to the research on medicinal plants to attempt to build capacity for research within Moroccan Scientific community at rate of developing country.

Keywords: Morocco, medicinal plants, ethnobotanical, pharmacognosy, phytomedicine

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Authors: Celine Davis

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The novel coronavirus 2019 (COVID-19) is an infectious disease caused by the virus SARS-CoV-2, which has detrimental respiratory, cardiovascular, and neurological effects impacting over one million lives in the United States. New researches has emerged indicating long-term neurologic consequences in those who survive COVID-19 infections, including more than seven million Americans and another 27 million people worldwide. These consequences include attentional deficits, memory impairments, executive function deficits and aphasia-like symptoms which fall within the purview of speech-language pathology. The National Health Interview Survey (NHIS) is a comprehensive annual survey conducted by the National Center for Health Statistics (NCHS), a branch of the Centers for Disease Control and Prevention (CDC) in the United States. The NHIS is one of the most significant sources of health-related data in the country and has been conducted since 1957. The longitudinal nature of the study allows for analysis of trends in various variables over the years, which can be essential for understanding societal changes and making treatment recommendations. This current study will utilize NHIS data from 2020-2022 which contained interview questions specifically related to COVID-19. Adult cases of individuals between the ages of 18-50 diagnosed with COVID-19 in the United States during 2020-2022 will be identified using the National Health Interview Survey (NHIS). Multiple regression analysis of self-reported data confirming COVID-19 infection status and challenges with concentration, communication, and memory will be performed. Latent class analysis will be utilized to identify subgroups in the population to indicate whether certain demographic groups have higher susceptibility to cognitive-linguistic deficits associated with COVID-19. Completion of this study will reveal whether there is an association between confirmed COVID-19 diagnosis and heightened incidence of cognitive deficits and subsequent implications, if any, on activities of daily living. This study is distinct in its aim to utilize national survey data to explore the relationship between confirmed COVID-19 diagnosis and the prevalence of cognitive-communication deficits with a secondary focus on resulting activity limitations. To the best of the author’s knowledge, this will be the first large-scale epidemiological study investigating the associations between cognitive-linguistic deficits, COVID-19 and implications on activities of daily living in the United States population. These findings will highlight the need for targeted interventions and support services to address the cognitive-communication needs of individuals recovering from COVID-19, thereby enhancing their overall well-being and functional outcomes.

Keywords: cognition, COVID-19, language, limitations, memory, NHIS

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Authors: Aungkana Kmonpetch

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Protection of trafficked victims and partnership among stakeholders are established as core principles in 5P’ strategies in international and national anti-human trafficking policies. In this article, it is of interest to discuss how the role of public-private partnerships in promoting the occupation development for employment in wage will enhance the better protection for victims of trafficking who affirmatively decide they want a criminal justice intervention, using Thailand as a case. Most of the victims who have accepted to be witness in the criminal justice system have lost income during their absence from work. The analysis of Thailand case is based on two methodological approaches: 1) interview with victims of trafficking, protection authorities, service providers, trainers and teachers, social workers, NGOs, police, prosecutors, business owners and enterprises, ILO, UNDP etc.; 2) create collaborative effort through workshops/consultation meetings in participation of all stakeholders – governmental agencies, private organizations, UN and international agencies. The linking of protection and partnership is anchored in international conventions and human trafficking directives. While this is actually framed as a responsive advantage for 5P strategies of anti-human trafficking – prevention, protection, persecution, punishment, and partnership, in reality, there might have more practical requirements of care and support. The article addresses how the partnership between governmental agencies and private organizations provide opportunities for trafficked victims to engage in high-skilled occupational development such as Silk-Sewing and Tailoring. The discussion is also focused how this approach of capacity building of the trainer for trainee, be enable the trafficked victims to cultivate the practices of high-skilled training to engage them into the business of social enterprise with employment in wage. The partnership coordination draws specifically to two aspects: firstly, to formulate appropriate assistance for promotion and protection of human rights of the trafficked victims in response to the 5P’ strategies of anti-human trafficking policy; secondly, to empower them to settle some economic stability for livelihood opportunity in the country of origin on their return and reintegration. Therefore, they can define how they want to move forward to prevent them at risk of vulnerable situations where they might being trafficked again or going on to work in exploitative conditions. It strengthens proper access to protection and assistance, depending on how the incentive of protection for cooperation is perceived to be and how useful the capacity building in occupation development for employment in wage will be implemented practically both in the host country and in the country of origin. This also brings into question how the victim of trafficking are able to access to the trade of market and are supported the employment opportunity according to the concept of decent work as they are constituted as witnesses. We discuss these issues in the area of a broader literature on social protection, economic security, gender, law, and victimhood.

Keywords: employment opportunity, occupation development, protection for victim of trafficking, public-private partnership

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Authors: Hasti Abbasi

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Creative writers have long followed the tradition of romantic exile, looking inward in an attempt to construct new viewpoints through the power of imagination. The writer, who attempts to resist uncertainty and locate her place in the new country through writing, resists creativity itself. For a writer, certain satisfaction can be achieved through producing a creative art away from the anxiety of the sense of dislocation. Dislocation, whether enforced or self-inflicted, could in many ways be a disaster but it could also cultivate a greater creative capacity and be a source of creative expression. This paper will investigate the idea of the creative writer as exiled self through reflections on the relationship between dislocation and writing.

Keywords: dislocation, creative writing, remaking identity, exile literature

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Authors: Victor Bloch, Eerikki Kaila, Reetta Palva

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Field robots are an important tool for enhancing efficiency and decreasing the climatic impact of food production. There exists a number of commercial field robots; however, since this technology is still new, the robot advantages and limitations, as well as methods for optimal using of robots, are still unclear. In this study, the performance of a commercial field robot for seeding and weeding was assessed. A research 2-ha sugar beet field with 0.5m row width was used for testing, which included robotic sowing of sugar beet and weeding five times during the first two months of the growing. About three and five percent of the field were used as untreated and chemically weeded control areas, respectively. The plant detection was based on the exact plant location without image processing. The robot was equipped with six seeding and weeding tools, including passive between-rows harrow hoes and active hoes cutting inside rows between the plants, and it moved with a maximal speed of 0.9 km/h. The robot's performance was assessed by image processing. The field images were collected by an action camera with a height of 2 m and a resolution 27M pixels installed on the robot and by a drone with a 16M pixel camera flying at 4 m height. To detect plants and weeds, the YOLO model was trained with transfer learning from two available datasets. A preliminary analysis of the entire field showed that in the areas treated by the robot, the weed average density varied across the field from 6.8 to 9.1 weeds/m² (compared with 0.8 in the chemically treated area and 24.3 in the untreated area), the weed average density inside rows was 2.0-2.9 weeds / m (compared with 0 on the chemically treated area), and the emergence rate was 90-95%. The information about the robot's performance has high importance for the application of robotics for field tasks. With the help of the developed method, the performance can be assessed several times during the growth according to the robotic weeding frequency. When it’s used by farmers, they can know the field condition and efficiency of the robotic treatment all over the field. Farmers and researchers could develop optimal strategies for using the robot, such as seeding and weeding timing, robot settings, and plant and field parameters and geometry. The robot producers can have quantitative information from an actual working environment and improve the robots accordingly.

Keywords: agricultural robot, field robot, plant detection, robot performance

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Authors: I. Yalcin Enis, J. Vojtech, T. Gok Sadikoglu

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In this study, polycaprolactone (PCL) was dissolved in chloroform: ethanol solvent system at a concentration of 18 w/v %. 1, 2, 4, and 6 droplets of formic acid were added to the prepared 10ml PCL-chloroform:ethanol solutions separately. Fibrous webs were produced by electrospinning technique. Morphology of the webs was investigated by using scanning electron microscopy (SEM) whereas fiber diameters were measured by Image J Software System. The effect of formic acid addition to the mostly used chloroform solvent on fiber morphology was examined.

Keywords: chloroform, electrospinning, formic acid polycaprolactone, fiber

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Authors: Kathrin F. Schneider, Luis Xavier Unda Galarza

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In our modern world, few are the areas that are not permeated by digitalization: we use digital tools for work, study, entertainment, and daily life. Since technology changes rapidly, skills must adapt to the new reality, which gives a dynamic dimension to the set of skills necessary for people's academic, professional, and personal success. The concept of 21st-century digital skills, which includes skills such as collaboration, communication, digital literacy, citizenship, problem-solving, critical thinking, interpersonal skills, creativity, and productivity, have been widely discussed in the literature. Digital transformation has opened many economic opportunities for entrepreneurs for the development of their products, financing possibilities, and product distribution. One of the biggest advantages is the reduction in cost for the entrepreneur, which has opened doors not only for the entrepreneur or the entrepreneurial team but also for corporations through intrapreneurship. The development of students' general literacy level and their digital competencies is crucial for improving the effectiveness and efficiency of the learning process, as well as for students' adaptation to the constantly changing labor market. The digital economy allows a free substantial increase in the supply share of conditional and also innovative products; this is mainly achieved through 5 ways to reduce costs according to the conventional digital economy: search costs, replication, transport, tracking, and verification. Digital entrepreneurship worldwide benefits from such achievements. There is an expansion and democratization of entrepreneurship thanks to the use of digital technologies. The digital transformation that has been taking place in recent years is more challenging for developing countries, as they have fewer resources available to carry out this transformation while offering all the necessary support in terms of cybersecurity and educating their people. The degree of digitization (use of digital technology) in a country and the levels of digital literacy of its people often depend on the economic level and situation of the country. Telefónica's Digital Life Index (TIDL) scores are strongly correlated with country wealth, reflecting the greater resources that richer countries can contribute to promoting "Digital Life". According to the Digitization Index, Ecuador is in the group of "emerging countries", while Chile, Colombia, Brazil, Argentina, and Uruguay are in the group of "countries in transition". According to Herrera Espinoza et al. (2022), there are startups or digital ventures in Ecuador, especially in certain niches, but many of the ventures do not exceed six months of creation because they arise out of necessity and not out of the opportunity. However, there is a lack of relevant research, especially empirical research, to have a clearer vision. Through a self-report questionnaire, the digital skills of students will be measured in an Ecuadorian private university, according to the skills identified as the six 21st-century skills. The results will be put to the test against the variable of the intention to start a digital venture measured using the theory of planned behavior (TPB). The main hypothesis is that high digital competence is positively correlated with the intention to start digital entrepreneurship.

Keywords: new literacies, digital transformation, 21st century skills, theory of planned behavior, digital entrepreneurship

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Authors: Ami Fadhillah Amir Abdul Nasir, Amanda C. Niehaus, Skye F. Cameron, Frank A. Von Hippel, John Postlethwait​, Robbie S. Wilson

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For suicidal breeders, the physiological stresses and energetic costs of breeding are fatal. Environmental stressors such as pollution should compound these costs, yet suicidal breeding is so rare among mammals that this is unknown. Here, we explored the consequences of metal contamination to the health, aging and performance of endangered, suicidally-breeding northern quolls (Dasyurus hallucatus) living near an active manganese mine on Groote Eylandt, Northern Territory, Australia. We found respirable manganese dust at levels exceeding international recommendations even 20km from mining sites and substantial accumulation of manganese within quolls’ hair, testes, and in two brain regions—the neocortex and cerebellum, responsible for sensory perception and motor function, respectively. Though quolls did not differ in sprint speeds, motor skill, or manoeuvrability, those with higher accumulation of manganese crashed at lower speeds during manoeuvrability tests, indicating a potential effect on sight or cognition. Immune function and telomere length declined over the breeding season, as expected with ageing, but manganese contamination exacerbated immune declines and suppressed cortisol. Unexpectedly, male quolls with higher levels of manganese had longer telomeres, supporting evidence of unusual telomere dynamics among Dasyurids—though whether this affects their lifespan is unknown. We posit that sublethal contamination via pollution, mining, or urbanisation imposes physiological costs on wildlife that may diminish reproductive success or survival.

Keywords: ecotoxicology, heavy metal, manganese, telomere length, cortisol, locomotor

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Authors: Joshua Buli, David Pietrowski, Samuel Britton

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Processing SAR data usually requires constraints in extent in the Fourier domain as well as approximations and interpolations onto a planar surface to form an exploitable image. This results in a potential loss of data requires several interpolative techniques, and restricts visualization to two-dimensional plane imagery. The data can be interpolated into a ground plane projection, with or without terrain as a component, all to better view SAR data in an image domain comparable to what a human would view, to ease interpretation. An alternate but computationally heavy method to make use of more of the data is the basis of this research. Pre-processing of the SAR data is completed first (matched-filtering, motion compensation, etc.), the data is then range compressed, and lastly, the contribution from each pulse is determined for each specific point in space by searching the time history data for the reflectivity values for each pulse summed over the entire collection. This results in a per-3D-point reflectivity using the entire collection domain. New advances in GPU processing have finally allowed this rapid projection of acquired SAR data onto any desired reference surface (called backprojection). Mathematically, the computations are fast and easy to implement, despite limitations in SAR phase history data size and 3D-point cloud size. Backprojection processing algorithms are embarrassingly parallel since each 3D point in the scene has the same reflectivity calculation applied for all pulses, independent of all other 3D points and pulse data under consideration. Therefore, given the simplicity of the single backprojection calculation, the work can be spread across thousands of GPU threads allowing for accurate reflectivity representation of a scene. Furthermore, because reflectivity values are associated with individual three-dimensional points, a plane is no longer the sole permissible mapping base; a digital elevation model or even a cloud of points (collected from any sensor capable of measuring ground topography) can be used as a basis for the backprojection technique. This technique minimizes any interpolations and modifications of the raw data, maintaining maximum data integrity. This innovative processing will allow for SAR data to be rapidly brought into a common reference frame for immediate exploitation and data fusion with other three-dimensional data and representations.

Keywords: backprojection, data fusion, exploitation, three-dimensional, visualization

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Authors: Zhuoran Li, Guan Qin

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A robust and efficient compositional equilibrium characterization model for hydrate-containing systems is required, especially for time-critical simulations such as subsea pipeline flow assurance analysis, compositional simulation in hydrate reservoirs etc. A multiphase flash calculation framework, which combines Gibbs energy minimization function and cubic plus association (CPA) EoS, is developed to describe the highly non-ideal phase behavior of hydrate-containing systems. A non-iterative eigenvalue problem-solving approach for the trust-region sub-problem is selected to guarantee efficiency. The developed flash model is based on the state-of-the-art objective function proposed by Michelsen to minimize the Gibbs energy of the multiphase system. It is conceivable that a hydrate-containing system always contains polar components (such as water and hydrate inhibitors), introducing hydrogen bonds to influence phase behavior. Thus, the cubic plus associating (CPA) EoS is utilized to compute the thermodynamic parameters. The solid solution theory proposed by van der Waals and Platteeuw is applied to represent hydrate phase parameters. The trust-region method combined with the trust-region sub-problem non-iterative eigenvalue problem-solving approach is utilized to ensure fast convergence. The developed multiphase flash model's accuracy performance is validated by three available models (one published and two commercial models). Hundreds of published hydrate-containing system equilibrium experimental data are collected to act as the standard group for the accuracy test. The accuracy comparing results show that our model has superior performances over two models and comparable calculation accuracy to CSMGem. Efficiency performance test also has been carried out. Because the trust-region method can determine the optimization step's direction and size simultaneously, fast solution progress can be obtained. The comparison results show that less iteration number is needed to optimize the objective function by utilizing trust-region methods than applying line search methods. The non-iterative eigenvalue problem approach also performs faster computation speed than the conventional iterative solving algorithm for the trust-region sub-problem, further improving the calculation efficiency. A new thermodynamic framework of the multiphase flash model for the hydrate-containing system has been constructed in this work. Sensitive analysis and numerical experiments have been carried out to prove the accuracy and efficiency of this model. Furthermore, based on the current thermodynamic model in the oil and gas industry, implementing this model is simple.

Keywords: equation of state, hydrates, multiphase equilibrium, trust-region method

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Authors: Vipul M. Patel, Hemantkumar B. Mehta

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Technological innovations in electronic world demand novel, compact, simple in design, less costly and effective heat transfer devices. Closed Loop Pulsating Heat Pipe (CLPHP) is a passive phase change heat transfer device and has potential to transfer heat quickly and efficiently from source to sink. Thermal performance of a CLPHP is governed by various parameters such as number of U-turns, orientations, input heat, working fluids and filling ratio. The present paper is an attempt to predict the thermal performance of a CLPHP using Artificial Neural Network (ANN). Filling ratio and heat input are considered as input parameters while thermal resistance is set as target parameter. Types of neural networks considered in the present paper are radial basis, generalized regression, linear layer, cascade forward back propagation, feed forward back propagation; feed forward distributed time delay, layer recurrent and Elman back propagation. Linear, logistic sigmoid, tangent sigmoid and Radial Basis Gaussian Function are used as transfer functions. Prediction accuracy is measured based on the experimental data reported by the researchers in open literature as a function of Mean Absolute Relative Deviation (MARD). The prediction of a generalized regression ANN model with spread constant of 4.8 is found in agreement with the experimental data for MARD in the range of ±1.81%.

Keywords: ANN models, CLPHP, filling ratio, generalized regression, spread constant

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Authors: Yude Wu

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Mongolia, grappling with significant socio-economic challenges, faces pressing issues of inequality and poverty, as evidenced by a high Gini coefficient and the highest poverty rate among the top 20 largest Asian countries. Despite government efforts, Mongolia's poverty rate experienced only a slight reduction from 29.6 percent in 2016 to 27.8 percent in 2020. PEER countries, such as South Africa, Botswana, Kazakhstan, and Peru, share characteristics with Mongolia, including reliance on the mining industry and classification as lower middle-income countries. Successful transitions of these countries to upper middle-income status between 1994 and the 2010s provide valuable insights. Drawing on secondary analyses of existing research and PEER country profiles, the study evaluates past policies, identifies gaps in current approaches, and proposes recommendations to combat poverty sustainably. The hypothesis includes a reliance on the mining industry and a transition from lower to upper middle-income status. Policies from these countries, such as the GEAR policy in South Africa and economic diversification in Botswana, offer insights into Mongolia's development. This essay aims to illuminate the multidimensional nature of underdevelopment in Mongolia through a secondary analysis of existing research and PEER country profiles, evaluating past policies, identifying gaps in current approaches, and providing recommendations for sustainable progress. Drawing inspiration from PEER countries, Mongolia can implement policies such as economic diversification to reduce vulnerability and create stable job opportunities. Emphasis on infrastructure, human capital, and strategic partnerships for Foreign Direct Investment (FDI) aligns with successful strategies implemented by PEER countries, providing a roadmap for Mongolia's development objectives.

Keywords: inequality, PEER countries, comparative analysis, nomadic animal husbandry, sustainable growth

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Authors: Anjan Hazra, Nirjhar Dasgupta, Chandan Sengupta, Sauren Das

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Tea (Camellia sinensis) has received substantial attention from the scientific world time to time, not only for its commercial importance, but also for its demand to the health-conscious people across the world for its extensive use as potential sources of antioxidant supplement. These health-benefit traits primarily rely on some regulatory networks of different metabolic pathways. Development of microsatellite markers from the conserved genomic regions is being worthwhile for studying the genetic diversity of closely related species or self-pollinated species. Although several SSR markers have been reported, in tea the trait-specific Simple Sequence Repeats (SSRs) are yet to be identified, which can be used for marker assisted breeding technique. MicroRNAs are endogenous, noncoding, short RNAs directly involved in regulating gene expressions at the post-transcriptional level. It has been found that diversity in miRNA gene interferes the formation of its characteristic hair pin structure and the subsequent function. In the present study, the precursors of small regulatory RNAs (microRNAs) has been fished out from tea Expressed Sequence Tag (EST) database. Furthermore, the simple sequence repeat motifs within the putative miRNA precursor genes are also identified in order to experimentally validate their existence and function. It is already known that genic-SSR markers are very adept and breeder-friendly source for genetic diversity analysis. So, the potential outcome of this in-silico study would provide some novel clues in understanding the miRNA-triggered polymorphic genic expression controlling specific metabolic pathways, accountable for tea quality.

Keywords: micro RNA, simple sequence repeats, tea quality, trait specific marker

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Authors: Jonardan Koner, Avinash Purandare

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In today’s globalized world international business is a very key area for the country's growth. Some of the strategic areas for holding up a country’s international business to grow are in the areas of connecting Ports, Road Network, and Rail Network. India’s International Business is booming both in Exports as well as Imports. Ports play a very central part in the growth of international trade and ensuring competitive ports is of critical importance. India has a long coastline which is a big asset for the country as it has given the opportunity for development of a large number of major and minor ports which will contribute to the maritime trades’ development. The National Economic Development of India requires a well-functioning seaport system. To know the comparative strength of Indian ports over South-east Asian similar ports, the study is considering the objectives of (I) to identify the key parameters of an international mega container port, (II) to compare the five selected container ports (JNPT, Chennai, Singapore, Dubai, and Colombo Ports) according to user of the ports and iii) to measure the growth of selected five container ports’ throughput over time and their comparison. The study is based on both primary and secondary databases. The linear time trend analysis is done to show the trend in quantum of exports, imports and total goods/services handled by individual ports over the years. The comparative trend analysis is done for the selected five ports of cargo traffic handled in terms of Tonnage (weight) and number of containers (TEU’s). The comparative trend analysis is done between containerized and non-containerized cargo traffic in the five selected five ports. The primary data analysis is done comprising of comparative analysis of factor ratings through bar diagrams, statistical inference of factor ratings for the selected five ports, consolidated comparative line charts of factor rating for the selected five ports, consolidated comparative bar charts of factor ratings of the selected five ports and the distribution of ratings (frequency terms). The linear regression model is used to forecast the container capacities required for JNPT Port and Chennai Port by the year 2030. Multiple regression analysis is carried out to measure the impact of selected 34 explanatory variables on the ‘Overall Performance of the Port’ for each of the selected five ports. The research outcome is of high significance to the stakeholders of Indian container handling ports. Indian container port of JNPT and Chennai are benchmarked against international ports such as Singapore, Dubai, and Colombo Ports which are the competing ports in the neighbouring region. The study has analysed the feedback ratings for the selected 35 factors regarding physical infrastructure and services rendered to the port users. This feedback would provide valuable data for carrying out improvements in the facilities provided to the port users. These installations would help the ports’ users to carry out their work in more efficient manner.

Keywords: throughput, twenty equivalent units, TEUs, cargo traffic, shipping lines, freight forwarders

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Authors: Hilal Al Shamsi, Abdullah Almutairi

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Introduction: As primary healthcare centres play an important role in implementing Saudi Arabia’s health strategy, this paper offers a review of publications on the quality of the country’s primary health care. With the aim of deciding on solutions for improvement, it provides an overview of healthcare quality in this context and indicates barriers to quality. Method: Using two databases, ProQuest and Scopus, data extracted from published articles were systematically analysed for determining the care quality in Saudi primary health centres and obstacles to achieving higher quality. Results: Twenty-six articles met the criteria for inclusion in this review. The components of healthcare quality were examined in terms of the access to and effectiveness of interpersonal and clinical care. Good access and effective care were identified in such areas as maternal health care and the control of epidemic diseases, whereas poor access and effectiveness of care were shown for chronic disease management programmes, referral patterns (in terms of referral letters and feedback reports), health education and interpersonal care (in terms of language barriers). Several factors were identified as barriers to high-quality care. These included problems with evidence-based practice implementation, professional development, the use of referrals to secondary care and organisational culture. Successful improvements have been implemented by other systems, such as mobile medical units, electronic referrals, online translation tools and mobile devices and their applications; these can be implemented in Saudi Arabia for improving the quality of the primary healthcare system in this country. Conclusion: The quality of primary health care in Saudi Arabia varies among the different services. To improve quality, management programmes and organisational culture must be promoted in primary health care. Professional development strategies are also needed for improving the skills and knowledge of healthcare professionals. Potential improvements can be implemented to improve the quality of the primary health system.

Keywords: quality, primary health care, Saudi Arabia, health centres, general medical

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Authors: Ragy Raafat Gaber Attaalla

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For cardiovascular illness, oral P2Y12 inhibitors including clopidogrel, prasugrel, and ticagrelor are frequently recommended. Each of these medications has advantages and disadvantages. In the absence of genotyping, it has been demonstrated that the stronger platelet aggregation inhibitors prasugrel and ticagrelor are superior than clopidogrel at preventing significant adverse cardiovascular events following an acute coronary syndrome and percutaneous coronary intervention (PCI). Both, nevertheless, come with a higher risk of bleeding unrelated to a coronary artery bypass. As a prodrug, clopidogrel needs to be bioactivated, principally by the CYP2C19 enzyme. A CYP2C19 no function allele and diminished or absent CYP2C19 enzyme activity are present in about 30% of people. The reduced exposure to the active metabolite of clopidogrel and reduced inhibition of platelet aggregation among clopidogrel-treated carriers of a CYP2C19 no function allele likely contributed to the reduced efficacy of clopidogrel in clinical trials. Clopidogrel's pharmacogenetic results are strongest when used in conjunction with PCI, but evidence for other indications is growing. One of the most typical examples of clinical pharmacogenetic application is CYP2C19 genotype-guided antiplatelet medication following PCI. Guidance is available from expert consensus groups and regulatory bodies to assist with incorporating genetic information into P2Y12 inhibitor prescribing decisions. Here, we examine the data supporting genotype-guided P2Y12 inhibitor selection's effects on clopidogrel response and outcomes and discuss tips for pharmacogenetic implementation. We also discuss procedures for using genotype data to choose P2Y12 inhibitor therapies as well as any unmet research needs. Finally, choosing a P2Y12 inhibitor medication that optimally balances the atherothrombotic and bleeding risks may be influenced by both clinical and genetic factors.

Keywords: inhibitors, cardiovascular events, coronary intervention, pharmacogenetic implementation

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Authors: Abhishek Bhardwaj, Manish Kumar Bajpai

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An image with its content and schema of colors presents an effective mode of information sharing and processing. By changing its color schema different visions and prospect are discovered by the users. This phenomenon of color transfer is being used by Social media and other channel of entertainment. Reinhard et al’s algorithm was the first one to solve this problem of color transfer. In this paper, we make this algorithm efficient by introducing domain parallelism among different processors. We also comment on the factors that affect the speedup of this problem. In the end by analyzing the experimental data we claim to propose a novel and efficient parallel Reinhard’s algorithm.

Keywords: Reinhard et al’s algorithm, color transferring, parallelism, speedup

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Authors: Hang T. T. Truong, Ronald S. Laura, Kylie Shaw

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Within Vietnam's system of higher education, its schools of business play a vital role in supporting the country’s economic objectives. However, the crucial contribution of soft skills for maximal success within the business sector has to date not been adequately recognized by its business schools. This being so, the development of the business school curriculum in Vietnam has not been able to 'catch up', so to say, with the burgeoning need of students for a comprehensive soft skills program designed to meet the national and global business objectives of their potential employers. The burden of the present paper is first to reveal the results of our survey in Vietnam which make explicit the extent to which major Vietnamese industrial employers’ value the potential role that soft skill competencies can play in maximizing business success. Our final task will be to determine which soft skills employers discern as best serving to maximize the economic interests of Vietnam within the global marketplace. Semi-structured telephone interviews have been conducted with the 15 representative Head Employers of Vietnam's reputedly largest and most successful of the diverse business enterprises across Vietnam. The findings of the study indicate that all respondents highly value the increasing importance of soft skills in business success. Our critical analysis of respondent data reveals that 19 essential soft skills are deemed by employers as integral to business workplace efficacy and should thus be integrated into the formal business curriculum. We are confident that our study represents the first comprehensive and specific survey yet undertaken within the business sector in Vietnam which accesses and analyses the opinions of representative employers from major companies across the country in regard to the growing importance of 19 specific soft skills essential for maximizing overall business success. Our research findings also reveal that the integration into business school curriculums nationwide of the soft skills we have identified is of paramount importance to advance the national and global economic interests of Vietnam.

Keywords: business curriculum, business graduates, employers’ perception, soft skills

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Authors: Salisu Gidado Dalibi, Sadiq Gumi Abubakar, JingChun Feng

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Nigeria’s population is about 190 million and is on the increase annually making it the seventh most populated nation in the world and first in Africa. This population growth comes with its prospects, needs, and challenges especially on the existing and future infrastructure. Infrastructure refers to structures, systems, and facilities serving the economy of a country, city, town, businesses, industries, etc. These include roads, railways lines, bridges, tunnels, ports, stadiums, dams and water projects, power generation plants and distribution grids, information, and communication technology (ICT), etc. The Nigerian government embarked on several infrastructural development projects (IDPs) to address the deficit as the present infrastructure cannot cater to the needs nor sustain the country. However, delivering such IDPs have not been smooth; comes with challenges from within and outside the project; frequent delays and abandonment. Thus, affecting all the stakeholders involved. Hence, the aim of this paper is to identify and assess the factors that are hindering the effective delivery of IDPs in Nigeria’s built environment with the view to offer more insight into such factors, and ways to address them. The methodology adopted in this study involves the use of secondary sources of data from several materials (official publications, journals, newspapers, internet, etc.) were reviewed within the IDPs field by laying more emphasis on Nigeria’s cases. The hindrance factors in this regard were identified which forms the backbone of the questionnaire. A pilot survey was used to test its suitability; after which it was randomly administered to various project professionals in Nigeria’s construction industry using a 5-point Likert scale format to ascertain the impact of these hindrances. Cronbach’s Alpha reliability test, mean item score computations, relative importance indices, T-test, Chi-Square statistics were used for data analyses. The results outline the impact of various internal, external and project related factors that are hindering IDPs within Nigeria’s built environment.

Keywords: built environment, development, factors, hindrances, infrastructure, Nigeria, project

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Authors: Neda Orak, Mostafa Zarei

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Environmental assessment is an important session in environment management. Since various methods and techniques have been produces and implemented. Remote sensing (RS) is widely used in many scientific and research fields such as geology, cartography, geography, agriculture, forestry, land use planning, environment, etc. It can show earth surface objects cyclical changes. Also, it can show earth phenomena limits on basis of electromagnetic reflectance changes and deviations records. The research has been done on mangrove forests assessment by RS techniques. Mangrove forests quantitative analysis in Basatin and Bidkhoon estuaries was the aim of this research. It has been done by Landsat satellite images from 1975- 2013 and match to ground control points. This part of mangroves are the last distribution in northern hemisphere. It can provide a good background to improve better management on this important ecosystem. Landsat has provided valuable images to earth changes detection to researchers. This research has used MSS, TM, +ETM, OLI sensors from 1975, 1990, 2000, 2003-2013. Changes had been studied after essential corrections such as fix errors, bands combination, georeferencing on 2012 images as basic image, by maximum likelihood and IPVI Index. It was done by supervised classification. 2004 google earth image and ground points by GPS (2010-2012) was used to compare satellite images obtained changes. Results showed mangrove area in bidkhoon was 1119072 m2 by GPS and 1231200 m2 by maximum likelihood supervised classification and 1317600 m2 by IPVI in 2012. Basatin areas is respectively: 466644 m2, 88200 m2, 63000 m2. Final results show forests have been declined naturally. It is due to human activities in Basatin. The defect was offset by planting in many years. Although the trend has been declining in recent years again. So, it mentioned satellite images have high ability to estimation all environmental processes. This research showed high correlation between images and indexes such as IPVI and NDVI with ground control points.

Keywords: IPVI index, Landsat sensor, maximum likelihood supervised classification, Nayband National Park

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Authors: Dor Oppenheim, Yael Edan, Guy Shani

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This paper presents an image analysis algorithm to detect and count yellow tomato flowers in a greenhouse with uneven illumination conditions, complex growth conditions and different flower sizes. The algorithm is designed to be employed on a drone that flies in greenhouses to accomplish several tasks such as pollination and yield estimation. Detecting the flowers can provide useful information for the farmer, such as the number of flowers in a row, and the number of flowers that were pollinated since the last visit to the row. The developed algorithm is designed to handle the real world difficulties in a greenhouse which include varying lighting conditions, shadowing, and occlusion, while considering the computational limitations of the simple processor in the drone. The algorithm identifies flowers using an adaptive global threshold, segmentation over the HSV color space, and morphological cues. The adaptive threshold divides the images into darker and lighter images. Then, segmentation on the hue, saturation and volume is performed accordingly, and classification is done according to size and location of the flowers. 1069 images of greenhouse tomato flowers were acquired in a commercial greenhouse in Israel, using two different RGB Cameras – an LG G4 smartphone and a Canon PowerShot A590. The images were acquired from multiple angles and distances and were sampled manually at various periods along the day to obtain varying lighting conditions. Ground truth was created by manually tagging approximately 25,000 individual flowers in the images. Sensitivity analyses on the acquisition angle of the images, periods throughout the day, different cameras and thresholding types were performed. Precision, recall and their derived F1 score were calculated. Results indicate better performance for the view angle facing the flowers than any other angle. Acquiring images in the afternoon resulted with the best precision and recall results. Applying a global adaptive threshold improved the median F1 score by 3%. Results showed no difference between the two cameras used. Using hue values of 0.12-0.18 in the segmentation process provided the best results in precision and recall, and the best F1 score. The precision and recall average for all the images when using these values was 74% and 75% respectively with an F1 score of 0.73. Further analysis showed a 5% increase in precision and recall when analyzing images acquired in the afternoon and from the front viewpoint.

Keywords: agricultural engineering, image processing, computer vision, flower detection

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Authors: Ani Eda Njwe

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Cameroon is a bilingual and bijural country in West and Central Africa. The current president has been in power since 1982, which makes him the longest-serving president in the world. The length of his presidency is one of the major causes of the ongoing political instability in the country. The preamble of the Cameroonian constitution commits Cameroon to respect international law and human rights. It provides that these laws should be translated into national laws, and respected by all spheres of government and public service. Cameroon is a signatory of several international human rights laws and conventions. In theory, the citizens of Cameroon have adequate legal protection against the violation of their human rights for political reasons. The ongoing political crisis in Cameroon erupted after the Anglophone lawyers and teachers launched a protest against the hiring of Francophone judges in Anglophone courts; and the hiring of Francophone teachers in Anglophone schools. In retaliation, the government launched a military crackdown on protesters and civilians, conducted arbitrary arrests on Anglophones, raped and maimed civilians, and declared a state of emergency in the Anglophone provinces. This infuriated the Anglophone public, causing them to create a secessionist movement, requesting the Independence of Anglophone Cameroon and demanding a separate country called Ambazonia. The Ambazonian armed rebel forces have ever since launched guerrilla attacks on government troops. This fighting has deteriorated into a war between the Ambazonians and the Cameroon government. The arbitrary arrests and unlawful imprisonments have continued, causing the closure of Anglophone schools since November 2016. In October 2018, Cameroon held presidential elections. Before the electoral commission announced the results, the opposition leader, a Francophone, declared himself winner, following a leak of the polling information. This led to his imprisonment. This research has the objective of finding out whether the government’s reactions to protesters and opposition is lawful, under national and international laws. This research will also verify if the prison conditions of political prisoners meet human rights standards. Furthermore, this research seeks detailed information obtained from current political prisoners and detainees on their experiences. This research also aims to highlight the effort being made internationally, towards bringing awareness and finding a resolution to the war in Cameroon. Finally, this research seeks to elucidate on the efforts which human rights organisations have made, towards overseeing the respect of human rights in Cameroon. This research adopts qualitative methods, whereby data were collected using semi-structured interviews of political detainees, and questionnaires. Also, data was collected from secondary sources such as; scholarly articles, newspaper articles, web sources, and human rights reports. From the data collected, the findings were analysed using the content analysis research technique. From the deductions, recommendations have been made, which human rights organisations, activists, and international bodies can implement, to cause the Cameroonian government to stop unlawful arrests and reinstate the respect of human rights and the rule of law in Cameroon.

Keywords: arbitrary arrests, Cameroon, human rights, political

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