Difficult Area Research Articles

Three Step Authentication of Brain Tumour Segmentation Using Hybrid Active Contour Model and Discrete Wavelet Transform

An innovative imaging research is expected in the medical field due to the challenges and inaccuracies in diagnosing the life-threatened harmful tumours. Brain tumor diagnosis is one of the most difficult areas of study in diagnostic imaging, with the maximum fine for a small glitch given the patients survival rate. Conventionally, biopsy method is used to identify the tumour tissues from the brain's soft tissues by the medical researchers (or) practitioners and it is unproductive due to: (i) it requires more time, and (ii) it may have errors. This paper presents the three-stage authentication-based hybrid brain tumour segmentation process and it makes the detection more accrual. Primarily, tumour area is segmented from a magnetic resonance image and after that when comparing a differentiated segment of an image to the actual image, an improved active contour model is employed to achieve a good match. In addition, discrete wavelet transform is used for the features extraction which leads to improve the accuracy and robustness in the tumour diagnosis. Finally, RELM classifier is used for precise classification of brain tumours. The most effective section of our method is checking the status of the tumour through finding the tumour region. The results are evaluated through new dataset, and it demonstrates that the suggested approach is more efficient than the alternatives as well as provides 96.25% accuracy.

The Picture and the Frame: Understanding a Contested Landscape

AbstractThe Californian terrain is formed of many ‘contested landscapes’ – by different communities, the advantaged and the disadvantaged. San Francisco‐based writer Grace Mitchell Tada describes the work of architect, artist, designer and educator Walter Hood and his studio's forays into these difficult areas.

Knowledge Extraction and Discovery about Web System Based on the Benchmark Application of Online Stock Trading System.

Predicting workload characteristics could help web systems achieve elastic scaling and reliability by optimizing servers' configuration and ensuring Quality of Service, such as increasing or decreasing used resources. However, a successful analysis using a simulation model and recognition and prediction of the behavior of the client presents a challenging task. Furthermore, the network traffic characteristic is a subject of frequent changes in modern web systems and the huge content of system logs makes it a difficult area for data mining research. In this work, we investigate prepared trace contents that are obtained from the benchmark of the web system. The article proposes traffic classification on the web system that is used to find the behavior of client classes. We present a case study involving workload analysis of an online stock trading application that is run in the cloud, and that processes requests from the designed generator. The results show that the proposed analysis could help us better understand the requests scenario and select the values of system and application parameters. Our work is useful for practitioners and researchers of log analysis to enhance service reliability.

Work Adjustment in an Employment Program for Colombian People Involved in Armed Conflict: A Multilevel Mixed-Methods Case Study

Work plays a significant role in societies; however, currently, work is a particularly difficult area for those in the most vulnerable social categories who have been heavily affected by the COVID-19 pandemic. Because there is scarce research on labor integration of people affected by armed conflicts from work adjustment (WA) perspectives, we have developed research to understand the relationship between people and their work setting in an employment program inspired in supported employment models (SEMs). To achieve this, a nonexperimental mixed-methods research design with a convergent parallel approach and multilevel design was developed. The results show that the work-adjustment approach is a useful framework with which to understand the relationship between the work setting and individuals. The conclusions of the research are as follows: (1) people who have been involved in armed conflicts can develop attitudes and abilities to properly develop their work; (2) the configuration of a labor-inclusion model is related to the results in the medium and long term, both in the program itself and in its participants and society; (3) the SEMs contribute to the effective inclusion of people affected by armed conflicts, which have low skills, scarce social contacts, and low educational levels.

TEXT ENCODER USING NEURAL NETWORK

One of the active and difficult study areas in the world of pattern recognition and image processing has been handwriting recognition.It is an effort to use neural networks to recognise handwritten English alphabets.The neural network is trained using several character data sets. Classification and recognition are performed using the trained network.Character recognition (CR) has undergone substantial research over the past 50 years and has advanced to the point where it can develop technology-driven applications.Designing an expert system for "HCR(English) using Neural Network" is the primary goal of this research. utilizing an Artificial Neural Network technique, is capable of accurately identifying a certain character of type format.Given a specific initial state (data input), neural computers are taught (not programmed) to either classify the input data into one of the many classes or to cause the original data to grow in such a way that a specific desirable attribute is optimized. Keywords: Character recognition, Neural Network, Trained dataset, Image processing.

Use of a biological scaffold in the cleavage area in complex revision breast augmentation: A surgical technique and case series

BackgroundBilateral breast augmentation has been the top surgical procedure performed worldwide by plastic surgeons for the past 5 years. Complex breast revision patients are challenging, with the cleavage area being one of the most difficult areas to navigate. We present a novel technique for using biological scaffolds in revision breast augmentation surgery. MethodsA step-by-step surgical technique is presented, combined with a series of 11 cases where either SurgiMend® acellular dermal matrix (ADM) or GalaFLEX mesh was used specifically in the medial cleavage area to correct a difficult to manage soft tissue contour deformity. ResultsEleven patients underwent revision breast augmentation with the use of the biological scaffolds in the medial cleavage area. The mean age was 43 years with a range of 29–68 years. All replacement breast implants were anatomical-shaped, medium profile, polyurethane-coated implants. GalaFLEX® mesh was used in six patients; five patients received SurgiMend® ADM. Mastopexy was performed in 8/11 patients. There were two complications in the same patient in this series, one emergency return to theater for bleeding and one minor scar revision. ConclusionsRevision breast augmentation surgery includes a smorgasbord of options that can be used individually or in combination, such as full or partial capsulectomy, removal alone or replacement of the implant, change to the tissue plane of where the implant sits, mastopexy, and fat transfer. In addition to these recognized treatments, we would like to advocate the option of a biological scaffold for extra support of the cleavage area in complex revision cases.

3D BUILDING MODELS DEVELOPMENT BASED ON DATA FUSION – CURRENT STATUS

Abstract. For the past years, a better and complete 3D building model has been intensely studied. To get a 3D building model as desired, it is known to use data fusion which is a technique of 3D dataset combination. Data fusion is conducted to overcome the limitations of each measurement technique in obtaining data. This paper aims to show the status of 3D building models development that is generated from two or more datasets by using data fusion technique. From several works of data fusion, it is observed the development of data fusion related things like various technologies, methods, and accuracy. The technology used varies for data fusion, for both air and ground based measurements. Technologies such as Terrestrial Laser Scanning (TLS) and close-range photogrammetry are the most appropriate surveying methods to generate accurate and high-resolution models. Meanwhile, recent technology of mobile laser scanning makes scans more quickly and offers more convenience to obtain data in a difficult area. Furthermore, mobile laser scanning has higher completeness data than photogrammetry data. For future work, mobile laser scanning data is be considered to use in data fusion. In term of accuracy, several works agreed that data fusion is a better way to have more complete 3D building models with high accuracy. Related to data processing of data fusion, most of algorithms have disadvantage in accelerating the data fusion time. Therefore, an algorithm to shorten the processing time needs to be created.

Machine learning and deep learning approaches in IoT.

The internet is a booming sector for exchanging information because of all the gadgets in today's world. Attacks on Internet of Things (IoT) devices are alarming as these devices evolve. The two primary areas of the IoT that should be secure in terms of authentication, authorization, and data privacy are the IoMT (Internet of Medical Things) and the IoV (Internet of Vehicles). IoMT and IoV devices monitor real-time healthcare and traffic trends to protect an individual's life. With the proliferation of these devices comes a rise in security assaults and threats, necessitating the deployment of an IPS (intrusion prevention system) for these systems. As a result, machine learning and deep learning technologies are utilized to identify and control security in IoMT and IoV devices. This research study aims to investigate the research fields of current IoT security research trends. Papers about the domain were searched, and the top 50 papers were selected. In addition, research objectives are specified concerning the problem, which leads to research questions. After evaluating the associated research, data is retrieved from digital archives. Furthermore, based on the findings of this SLR, a taxonomy of IoT subdomains has been given. This article also identifies the difficult areas and suggests ideas for further research in the IoT.

Analysis of Students’ Problems in Writing Procedure Text at The Tenth Grade Students of SMA Negeri 1 Sepang

Writing is one of the basic English language abilities that should be mastered by English Learners. However, many Indonesian students, especially at the High School level, face difficulties in writing. Evidently, in the context of this study was conducted to find out students’ abilities and to explore the main problems faced by students in writing procedure texts. The method of this research was descriptive qualitative research. The sample of this research was 29 students of class X IPA2 at SMA Negeri 1 Sepang. Form of writing procedure text was used as the instrument to collect the data and a documentation technique was applied to collect the data. Afterward, the data were analyzed with a rubric analytical scale by brown (2007). The result showed that 13,8% of students were in a very good level, 17.2% of students in a good level, 17.2% of students in a fair level, and 51.6% of students were in a poor level. Therefore, 24.1% of students are classified in the poor level of language features category which means, language features are the most difficult area faced by the tenth-grade students of SMA Negeri 1 Sepang with the number frequency 24.1% students in a poor level.

Prospective evaluation of multidimensional health-related quality of life after endoscopic endonasal surgery for pituitary adenomas using the endoscopic endonasal sinus and skull base surgery questionnaire.

Social functioning is an important factor in the evaluation of postoperative health-related quality of life (HRQoL) for pituitary adenoma patients. In a prospective cohort study multidimensional HRQoL of non-functioning (NFA) and functioning (FA) pituitary adenoma patients were evaluated following endoscopic endonasal surgery using the endoscopic endonasal sinus and skull base surgery questionnaire (EES-Q). Prospectively, 101 patients were included. The EES-Q was completed preoperatively and postoperatively (2 weeks, 3months, 1year). Sinonasal complaints were completed daily during the first week postoperatively. Preoperative and postoperative scores were compared. A generalized estimating equation (uni- and multivariate) analysis was performed to identify significant HRQoL changes related to selected covariates. Two weeks postoperatively, physical (p < .05) and social (p < .05) HRQoL are worse and psychological (p < .05) HRQoL improved compared with preoperatively. Three months postoperatively, psychological HRQoL (p=.01) trended back to baseline and no differences in physical or social HRQoL were reported. One year postoperatively, psychological (p=.02) and social (p=.04) HRQoL improved while physical HRQoL remained stable. FA patients report a worse HRQoL preoperatively (social, p < .05) and 3months postoperatively (social, p < .02 and psychological, p < .02). Sinonasal complaints peak in the first days postoperatively and gradually return to presurgical levels 3months postoperatively. The EES-Q provides meaningful information on multidimensional HRQoL to improve patient-centred health care. Social functioning remains the most difficult area in which to achieve improvements. Despite the relatively modest sample size, there is some indication that the FA group continues to show a downward trend (and thus improvement) even after 3months, when most other parameters reach stability. Level II-B.

Species diversity deflation: Insight into taxonomic validity of Garra species (Teleostei: Cyprinidae) from Dhofar Region in the Arabian Peninsula using an integrated morpho-molecular approach

Garra is the most species-rich genus of freshwater fishes in the Arabian Peninsula, including Oman, which has eight recognized, species restricted mainly to the Hajar and Dhofar mountains. Garra species from the Dhofar region in Oman are reviewed based on integrated morphological and molecular (COI) data of newly collected fishes from the type localities of G. sindhae and G. smartae, and a new population from Wadi Laggashalyon. No diagnostic character was found to distinguish the two species and the Laggashalyon population as distinct taxa. Garra dunsirei, another species endemic to a sinkhole at Tawi Attair, a very difficult area to access at a depth of about 211 m, was examined here based on the GenBank data and the diagnostic characters given in the original descriptions of the studied Garra species. In addition, the phylogenetic tree placed the sequenced Omani Garra fishes into nine groups with K2P sequence divergence of 0.8% (G. smartae and G. smartae_Laggasaylon); 1.2% (G. smartae and G. sindhae), and 14.5% (G. Shamal and G. dunsirei) in their COI barcode region. A molecular species delimitation approach using PTP, also detected one entity for Garra species from the Dhofar region (G. dunsirei, G. sindhae and the both populations of G. smartae), which is consistent with our morphological data. Therefore, based on absence of diagnostic characters, low genetic distance, and molecular species delimitation approach, we treat G. sindhae and G. smartae as junior synonyms of G. dunsirei.

Airborne Millimeter-Wave InSAR Terrain Mapping Experiments Based on Automatic Extraction and Interferometric Calibration of Tie-Points

Limited by meteorological conditions, airspace, complex terrain and other factors, airborne millimeter-wave InSAR will inevitably face the situation of no control point layout when acquiring terrain data in the difficult mapping areas in Southwest China, which increases the difficulty of subsequent data processing. Moreover, the layout of control points in difficult mapping areas consumes a lot of manpower and time, which is not suitable for large-scale high-precision topographic mapping. To solve these problems, this paper proposes an automatic extraction of tie-points and interferometric calibration technology based on tie-points. This technology develops the automatic extraction algorithm of tie-points based on SAR + SIFT + RANSAC to obtain evenly distributed tie-points of adjacent images, and uses the evenly distributed tie-points as real known points to recalibrate the interference parameters, then carries out elevation transfer and elevation inversion through the tie-points of overlapping areas, thus realizing high-precision mapping without control points for airborne millimeter-wave InSAR. This paper uses measured data to verify the technology, and compares it with the areas with control points and marking points. The comparison results of elevation accuracy prove the feasibility and effectiveness of this method. This paper also discusses the difficulties in the treatment of typical areas, such as water areas, urban areas and mountain areas, and gives reasonable solutions that have good engineering application value.

The legal relevance of a minor patient’s wish to die: a temporality-related exploration of end-of-life decisions in pediatric care

Decisions regarding the end-of-life of minor patients are amongst the most difficult areas of decision-making in pediatric health care. In this field of medicine, such decisions inevitably occur early in human life, which makes one aware of the fact that any life—young or old—cannot escape its temporal nature. Belgium and the Netherlands have adopted domestic regulations, which conditionally permit euthanasia and physician-assisted suicide in minors who experience hopeless and unbearable suffering. One of these conditions states that the minor involved must be legally competent and able to express an authentic and lasting wish to die. This contribution is different from other legal texts on end-of-life decisions in modern health care. Foremost, it deals with the role time-bound components play in our views on the permissibility of such decisions with regard to minor patients. While other disciplines provide profound reflections on this issue, from a legal point of view this side has hardly been explored, let alone examined with regard to its relevance for the legal permissibility of end-of-life decisions in pediatrics. Therefore, the manuscript inquires whether there are legal lessons to be learned if we look more closely to temporality-related aspects of these end-of-life decisions, particularly in connection to a minor patient’s assumable ability to choose death over an agonizing existence.

A Cross-Sectional Analysis of Intimacy Problems, Stress Levels, and Couple Satisfaction among Women with Thrombophilia Affected by Recurrent Pregnancy Loss.

Recurrent pregnancy loss (RPL) is one of the most challenging and difficult areas of reproductive treatment due to the immense emotional suffering inflicted on families and couples affected by RPL. As a result, it is predicted that couples experiencing recurrent pregnancy loss would have an increase in marital problems, stress levels, and anxiety, preventing them from achieving their family goals. The current cross-sectional study aimed to target pregnant women with thrombophilia with a history of RPL to observe their intimacy problems, stress levels, and couple satisfaction by completing a series of digital questionnaires. These patients were considered as the reference group, while the control group was formed by other women with thrombophilia and a history of RPL who eventually achieved pregnancy and gave birth. A total of 238 complete questionnaires were recorded (157 in the reference group and 81 in the control group). It was observed that women in the reference group who did not give birth had a significantly higher proportion of three or more pregnancy attempts (54.1% vs. 39.5%) and a significantly higher proportion of three more pregnancy losses (68.8% vs. 55.6%). It was observed that patients in the reference group were more likely to be emotion-oriented (42.7% vs. 27.2%). Also, women in the reference group had higher levels of dissatisfaction and lower levels of self-acceptance, pleasure, and marital quality scores. The total SII and DSCS scores were significantly lower than women with thrombophilia with a history of RPL who eventually gave birth. Women from the reference group had significantly greater intimacy problems and stress levels while having lower openness scores and self-esteem scores than women in the control group. It is possible that women with thrombophilia and recurrent pregnancy loss are more dissatisfied with their marriages than those who subsequently had one child. Since the financial status of those who achieved pregnancy was observed to be higher, it is likely that they achieved pregnancy by ART interventions, as they reported in questionnaires. It is important to target families afflicted by thrombophilia and other reasons for infertility to ease their access to ART therapies. By achieving their objectives, affected families will minimize dissatisfaction, divorce rates, and stress.

Emergency remote teaching of foreign languages at Saudi universities: Teachers' reported challenges, coping strategies and training needs.

Though considerable research has been reported on COVID-19-related distance education, some dimensions of remote foreign language teaching experiences during the pandemic crisis remain to be explored. The study reported in this paper investigated Saudi university foreign language teachers' accumulated experiences and reflective beliefs of emergency remote instruction. The study focused specifically on: a) the general educational challenges the teachers encountered and their attempts to overcome them; b) the teachers' perceived difficulties in remotely teaching and assessing foreign language areas and their strategies for coping with them; and c) their reflective evaluation of remote foreign language teaching after doing it for three academic terms. Questionnaire data was collected from 112 teachers of Arabic and English as foreign languages, and semi-structured interviews were conducted with 14 teachers. The analysis of both data types showed that the participants had a number of general educational and language-teaching-specific challenges in their COVID-19-related remote teaching. The teachers generally viewed the remote assessment of language areas is a more challenging task than teaching them. Reading was rated as the least difficult language area to teach and assess remotely, whereas writing was the most difficult one. The teachers reported using various coping strategies to overcome the educational and language teaching-specific challenges. They perceived their remote teaching experiences positively, but reported their needs for further training in developing better online assessment methods, using different teaching platforms and technological tools, and managing classroom interactions. The paper ends by discussing the results of the study and their implications.

A special call from inclusive classroom teachers of Turkish students with specific learning disabilities (SLD): “I don’t want them to dissappear!”

Students with specific learning disabilities continue their education in an inclusive environment in Türkiye. Teachers play an important role in effectively teaching students in inclusive settings. Teachers' classroom practices in reading, the most difficult academic area for students with specific learning disabilities, are critical for achieving successful results. There is a limited number of studies on this subject. This study aims to analyse the requirements, problems, and opinions of inclusive primary school teachers who teach students with specific learning disabilities. A qualitative research method was used in this study. The data were collected via semi-structured interviews with 11 inclusive classroom teachers in a study group and analysed through the content analysis method. The results show that the resources required for teaching students with specific learning disabilities in reading are insufficient and that the students need reading improvement programs. In addition, the teachers stated that the additional resources to support the students’ reading skills should consist of short, fun, and interesting texts.

Fabrication of 3D-Printed Implant for Two-Stage Ear Reconstruction Surgery and Its Clinical Application.

Ear reconstruction is one of the most difficult areas in the field of reconstructive surgery. Due to limitations of the current practice, a novel method of auricular reconstruction is needed. Major advancements in three-dimensional (3D) printing technique have rendered the process of ear reconstruction more favorable. Herein, we present our experience in designing and clinically using 3D implants in both 1st and 2nd stage ear reconstruction surgery. After obtaining 3D CT data from each patient, a 3D geometric ear model was created using mirroring and segmentation processes. The 3D-printed implant design resembles but does not exactly match the normal ear shape, and can be inserted in harmony with the currently used surgical technique. The 2nd stage implant was designed to minimize dead space and support the posterior ear helix. The 3D implants were finally fabricated with a 3D printing system and used in ear reconstruction surgery in our institute. The 3D implants were manufactured for application to the currently used two-stage technique while maintaining the shape of the patient's normal ear. The implants were successfully used for ear reconstruction surgery in microtia patients. A few months later, the 2nd stage implant was used in the 2nd stage operation. The authors were able to design, fabricate, and apply patient-specific 3D-printed ear implants for 1st and 2nd stage ear reconstruction surgeries. This design, combined with 3D bioprinting technique, may be a future alternative for ear reconstruction.

Real-Life Effectiveness of Tildrakizumab in Chronic Palmo Plantar Psoriasis: A Case Series of 7 Patients with 28 weeks of Follow Up

Palmo-plantar psoriasis (PPP) is highly debilitating and difficult to treat impairing quality of life of patients. Tildrakizumab is an anti-IL23p19 subunit monoclonal antibody approved for the treatment of moderate-severe chronic plaque psoriasis in adult candidates for systemic therapy. Objective of this study is to investigate the safety and efficacy of tildrakizumab in the management of palmo-plantar psoriasis. A total of 7 adults patients with moderate to severe PPP were retrospective analysed. Tildrakizumab 100 mg was administered at weeks 0, 4 and then every 12 weeks, by subcutaneous injection. Patients were visited at baseline, at week 16 and at week 28. Safety and efficacy were assessed at weeks 0, 16 and 28. Physician's Global Assessment (PGA) and Palmoplantar Pustular Psoriasis Area and Severity Index (PPPASI) clinical score were used to measure the efficacy. The mean PGA score was reduced from 3.6 at baseline to 1.7 after 16 weeks and 1.3 after 28 weeks. The mean PPPASI score was reduced from 19.2 at baseline to 9.2 after 16 weeks and 5.2 after 28 weeks. In conclusion tildrakizumab represents a safe and effective treatment for psoriasis even in difficult areas such as the palms and soles.

Energy-Efficient Routing Using Novel Optimization with Tabu Techniques for Wireless Sensor Network

Wireless Sensor Network (WSN) consists of a group of limited energy source sensors that are installed in a particular region to collect data from the environment. Designing the energy-efficient data collection methods in large-scale wireless sensor networks is considered to be a difficult area in the research. Sensor node clustering is a popular approach for WSN. Moreover, the sensor nodes are grouped to form clusters in a cluster-based WSN environment. The battery performance of the sensor nodes is likewise constrained. As a result, the energy efficiency of WSNs is critical. In specific, the energy usage is influenced by the loads on the sensor node as well as it ranges from the Base Station (BS). Therefore, energy efficiency and load balancing are very essential in WSN. In the proposed method, a novel Grey Wolf Improved Particle Swarm Optimization with Tabu Search Techniques (GW-IPSO-TS) was used. The selection of Cluster Heads (CHs) and routing path of every CH from the base station is enhanced by the proposed method. It provides the best routing path and increases the lifetime and energy efficiency of the network. End-to-end delay and packet loss rate have also been improved. The proposed GW-IPSO-TS method enhances the evaluation of alive nodes, dead nodes, network survival index, convergence rate, and standard deviation of sensor nodes. Compared to the existing algorithms, the proposed method outperforms better and improves the lifetime of the network.

Метод мутации сложноструктурированных входных данных при фаззинг-тестировании JavaScript интерпретаторов

Fuzzing of JavaScript engines is one of the most difficult areas in web-browser testing due to the complexity of input data generating. JavaScript engines process JavaScript code on a web page and require constant support for new language standards and increasing complexity in their architecture. The most common fuzzers today are not able to effectively mutate complexly structured input data during fuzzing. Generating JavaScript code from scratch does not allow encapsulating the necessary semantics, and current mutators quickly destroy the syntax and semantics of the input data language. This article presents a new mutation strategy that preserves the syntax and semantics of the input data by modifying the AST of JavaScript code fragments. This method allows you to efficiently generate diverse and correct input data, which can lead to the identification of errors and vulnerabilities in JavaScript engines. This method can be used to improve the security of web browsers and ensure reliable interpretation of JavaScript code.