Search results for: socioeconomic features

Authors: Sadia Basar, Naila Habib, Awais Adnan

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The paper presents the Technique for Image Segmentation Using K-Means Clustering Classification. The presented algorithms were specific, however, missed the neighboring information and required high-speed computerized machines to run the segmentation algorithms. Clustering is the process of partitioning a group of data points into a small number of clusters. The proposed method is content-aware and feature extraction method which is able to run on low-end computerized machines, simple algorithm, required low-quality streaming, efficient and used for security purpose. It has the capability to highlight the boundary and the object. At first, the user enters the data in the representation of the input. Then in the next step, the digital image is converted into groups clusters. Clusters are divided into many regions. The same categories with same features of clusters are assembled within a group and different clusters are placed in other groups. Finally, the clusters are combined with respect to similar features and then represented in the form of segments. The clustered image depicts the clear representation of the digital image in order to highlight the regions and boundaries of the image. At last, the final image is presented in the form of segments. All colors of the image are separated in clusters.

Keywords: clustering, image segmentation, K-means function, local and global minimum, region

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Authors: Daniel M. Wolff, Patricia Gray, Rafael de la Parra Venegas

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An unsupervised machine listening system is constructed and applied to a dataset of 17,195 30-second marine hydrophone recordings. The system is then heuristically supplemented with anecdotal listening, contextual recording information, and supervised learning techniques to reduce the number of false positives. Features for classification are assembled by extracting the following data from each of the audio files: the spectral centroid, root-mean-squared values for each frequency band of a 10-octave filter bank, and mel-frequency cepstral coefficients in 5-second frames. In this way both time- and frequency-domain information are contained in the features to be passed to a clustering algorithm. Classification is performed using the k-means algorithm and then a k-nearest neighbors search. Different values of k are experimented with, in addition to different combinations of the available feature sets. Hypothesized class labels are 'primarily anthrophony' and 'primarily biophony', where the best class result conforming to the former label has 104 members after heuristic pruning. This demonstrates how a large audio dataset has been made more tractable with machine learning techniques, forming the foundation of a framework designed to acoustically monitor and gauge biological and anthropogenic activity in a marine environment.

Keywords: anthrophony, hydrophone, k-means, machine learning

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Authors: Mumtaz Ali, Hamzullah Khan, Khalid Khanzada, Shahid Ayub, Aurangzeb Wazir

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Objective: To analyse the death of patients treated in neuro-surgical ICU for severe head injuries from different perspectives. The evaluation of the data so obtained to help improve the health care delivery to this group of patients in ICU. Study Design: It is a descriptive study based on retrospective analysis of patients presenting to neuro-surgical ICU in Lady Reading Hospital, Peshawar. Study Duration: It covered the period between 1st January 2009 to 31st December 2009. Material and Methods: The Clinical record of all the patients presenting with the clinical radiological and surgical features of severe head injuries, who expired in neuro-surgical ICU was collected. A separate proforma which mentioned age, sex, time of arrival and death, causes of head injuries, the radiological features, the clinical parameters, the surgical and non surgical treatment given was used. The average duration of stay and the demographic and domiciliary representation of these patients was noted. The record was analyzed accordingly for discussion and recommendations. Results: Out of the total 112 (n-112) patients who expired in one year in the neuro-surgical ICU the young adults made up the majority 64 (57.14%) followed by children, 34 (30.35%) and then the elderly age group: 10 (8.92%). Road traffic accidents were the major cause of presentation, 75 (66.96%) followed by history of fall; 23 (20.53%) and then the fire arm injuries; 13 (11.60%). The predominant CT scan features of these patients on presentation was cerebral edema, and midline shift (diffuse neuronal injuries). 46 (41.07%) followed by cerebral contusions. 28 (25%). The correctable surgical causes were present only in 18 patients (16.07%) and the majority 94 (83.92%) were given conservative management. Of the 69 (n=69) patients in which CT scan was repeated; 62 (89.85%) showed worsening of the initial CT scan abnormalities while in 7 cases (10.14%) the features were static. Among the non surgical cases both ventilatory therapy in 7 (6.25%) and tracheostomy in 39 (34.82%) failed to change the outcome. The maximum stay in the neuro ICU leading upto the death was 48 hours in 35 (31.25%) cases followed by 31 (27.67%) cases in 24 hours; 24 (21.42%) in one week and 16 (14.28%) in 72 hours. Only 6 (5.35%) patients survived more than a week. Patients were received from almost all the districts of NWFP except. The Hazara division. There were some Afghan refugees as well. Conclusion: Mortality following the head injuries is alarmingly high despite repeated claims about the professional and administrative improvement. Even places like ICU could not change the out come according to the desired aims and objectives in the present set up. A rethinking is needed both at the individual and institutional level among the concerned quarters with a clear aim at the more scientific grounds. Only then one can achieve the desired results.

Keywords: Glasgow Coma Scale, pediatrics, geriatrics, Peshawar

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Authors: Adino Andaregie, Isao Takagi, Hirohisa Shimura, Mitsuko Chikasada, Shinjiro Sato, Solomon Addisu

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Context: The prevalence of undernutrition in developing countries like Ethiopia has become a significant issue. In this regard, finding alternative nutritional supplements seems to be a practical solution. Spirulina, a highly nutritious microalgae, offers a valuable option as it is a rich source of various essential nutrients. The study aimed to establish the factors affecting urban Ethiopian consumers' consumption intention of Spirulina-fortified bread. Research Aim: The primary purpose of this research is to identify the behavioral and socioeconomic factors impacting the intention of urban Ethiopian consumers to eat Spirulina-fortified bread. Methodology: The research utilized a quantitative approach wherein a structured questionnaire was created and distributed among 361 urban consumers via an online platform. The theory of planned behavior (TPB) was used as a conceptual framework, and confirmatory factor analysis (CFA) and structural equation modelling (SEM) were employed for data analysis. Findings: The study results revealed that attitude towards the supplement, subjective norms, and perceived behavioral control were the critical factors influencing the consumption intention of Spirulina-fortified bread. Moreover, age, physical exercise, and prior knowledge of Spirulina as a food ingredient were also found to have a significant influence. Theoretical Importance: The study contributes towards the understanding of consumer behavior and factors affecting the purchase intentions of Spirulina-fortified bread in urban Ethiopia. The use of TPB as a theoretical framework adds a vital aspect to the study as it provides helpful insights into the factors affecting intentions towards this functional food. Data Collection and Analysis Procedures: The data collection process involved the creation of a structured questionnaire, which was distributed online to urban Ethiopian consumers. Once data was collected, CFA and SEM were utilized to analyze the data and identify the factors impacting consumer behavior. Questions Addressed: The study aimed to address the following questions: (1) What are the behavioral and socioeconomic factors impacting urban Ethiopian consumers' consumption intention of Spirulina-fortified bread? (2) To what extent do attitude towards the supplement, subjective norms, and perceived behavioral control affect the purchase intention of Spirulina-fortified bread? (3) What role does age, education, income, physical exercise, and prior knowledge of Spirulina as a food ingredient play in the purchase intention of Spirulina-fortified bread among urban Ethiopian consumers? Conclusion: The study concludes that attitude towards the supplement, subjective norms, and perceived behavioral control are significant factors influencing urban Ethiopian consumers’ consumption intention of Spirulina-fortified bread. Moreover, age, education, income, physical exercise, and prior knowledge of Spirulina as a food ingredient also play a significant role in determining purchase intentions. The findings provide valuable insights for developing effective marketing strategies for Spirulina-fortified functional foods targeted at different consumer segments.

Keywords: spirulina, consumption, factors, intention, consumers, behavior

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Authors: Hala M. El-hanbuli, Mohammed F. Darweesh

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The incidence rates of any tumor vary hugely with geographical location. Basal Cell Carcinoma (BCC) is one of the most common skin cancer that has many histopathologic subtypes. Objective: The aim was to study the histopathological features of BCC cases that were received in the Pathology Department, Kasr El-Aini hospital, Cairo University, Egypt during the period from Jan 2004 to Dec 2013 and to evaluate the clinical characters through the patient data available in the request sheets. Methods: Slides and data of BCC cases were collected from the archives of the pathology department, Kasr El-Aini hospital. Revision of all available slides and histological classification of BCC according to WHO (2006) was done. Results: A total number of 310 cases of BCC representing about 65% from the total number of malignant skin tumors examined during the 10-years duration in the department. The age ranged from 8 to 84 years, the mean age was (55.7 ± 15.5). Most of the patients (85%) were above the age of 40 years. There was a slight male predominance (55%). Ulcerated BCC was the most common gross picture (60%), followed by nodular lesion (30%) and finally the ulcerated nodule (10%). Most of the lesions situated in the high-risk sites (77%) where the nose was the most common site (35%) followed by the periocular area (22%), then periauricular (15%) and finally perioral (5%). No lesion was reported outside the head. The tumor size was less than 2 centimeters in 65% of cases, and from 2-5 centimeters in the lesions' greatest dimension in the rest of cases. Histopathological reclassification revealed that the nodular BCC was the most common (68%) followed by the pigmented nodular (18.75%). The histologic high-risk groups represented (7.5%) about half of them (3.75%) being basosquamous carcinoma. The total incidence for multiple BCC and 2nd primary was 12%. Recurrent BCC represented 8%. All of the recurrent lesions of BCC belonged to the histologic high-risk group. Conclusion: Basal Cell Carcinoma is the most common skin cancer in the 10-year survey. Histopathological diagnosis and classification of BCC cases are essential for the determination of the tumor type and its biological behavior.

Keywords: basal cell carcinoma, high risk, histopathological features, statistical analysis

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Authors: Francine Siy, Stephen Buñi

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Safety plays a significant role in everyone’s life on a day-to-day basis. We wish ourselves and our loved ones their safety as we all venture out on our daily commute. The road is undeniably dangerous and unpredictable, with abundant traffic collisions and pedestrians experiencing various injuries. For bicycle users, the risk of accidents is even more exacerbated, and injuries may be severe. Even when cyclists try their best to be safe and protected, the possibility of encountering danger is always there. Despite being equipped with protective gear, safety is never guaranteed. Cyclists often settle for helmets and standard reflector vests to establish a presence on the road. There are different types of vests available, depending on the profession. However, traditional reflector vests, mostly seen on construction workers and traffic enforcers, were not designed for riders and their protection from injuries. With insufficient protection for riders, they need access to ergonomically designed equipment and accessories that suit the riders and cater to their needs. This research aimed to offer a protective vest with safety features for riders that is comfortable, effective, durable, and intuitive. This sheds light and addresses the safety of the biker population, which continuously grows through the years. The product was designed and developed by gathering data and using the cognitive mapping method to ensure that all qualitative and quantitative data were considered in this study to improve other existing products that do not have the proper design considerations. It is known that available equipment for cyclists is often sold separately or lacks the safety features for cyclists traversing open roads. Each safety feature like the headlights, reflectors, signal or rear lights, zipper pouch, body camera attachment, and wireless remote control all play a particular role in helping cyclists embark on their daily commute. These features aid in illumination, visibility, easy maneuvering, convenience, and security, allowing cyclists to go for a safer ride that is of use throughout the day. The product is designed and produced effectively and inexpensively without sacrificing the quality and purpose of its usage.

Keywords: bicycle accessory, protective gear, safety, transport, visibility

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Authors: Mohammed Habchi, Sidi Mohammed Mesli, Rafik Benallal, Mohammed Kotbi

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On the basis of four partial correlation functions and some geometric constraints obtained from neutron scattering experiments, a Reverse Monte Carlo (RMC) simulation has been performed in the study of the aqueous electrolyte LiCl6H2O at the glassy state. The obtained 3-dimensional model allows computing pair radial and orientational distribution functions in order to explore the structural features of the system. Unrealistic features appeared in some coordination peaks. To remedy to this, we use the Hybrid Reverse Monte Carlo (HRMC), incorporating an additional energy constraint in addition to the usual constraints derived from experiments. The energy of the system is calculated using an Environment Dependence Interaction Potential (EDIP). Ions effects is studied by comparing correlations between water molecules in the solution and in pure water at room temperature Our results show a good agreement between experimental and computed partial distribution functions (PDFs) as well as a significant improvement in orientational distribution curves.

Keywords: LiCl6H2O, glassy state, RMC, HRMC

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Authors: Kenan Saatcioglu, Fatma Koc

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When the immigration is considered, it has been found that communities were continuously influenced by the immigrations from the date of the emergence of mankind until the day. The political, social and economic reasons seen at the various periods caused the communities go to new places from where they have lived before. Immigrations have occurred as a result of unequal opportunities among communities, social exclusion and imposition, compulsory homeland emerging politically, exile and war. Immigration is a social tool that is defined as a geographical relocation of people from a housing unit (city, village etc.) to another to spend all or part of their future lives. Immigrations have an effect on the history of humanity directly or indirectly, revealing new dimensions for communities to evaluate the concept of homeland. With these immigrations, communities carried their cultural values to their new settlements leading to a new interaction process. With this interaction process both migrant and native community cultures were reshaped and richer cultural values emerged. The clothes of these communities are amongst the most important visual evidence of this rich cultural interaction. As a result of these immigrations, communities affected each other culture’s clothing mutually and they started adding features of other cultures to the garments of its own, resulting new clothing cultures in time. The cultural and historical differences between these communities are seem to be the most influential factors of keeping the clothing cultures of the people alive. The most important and tragic of these immigrations took place after the Turkish War of Independence that was fought against Greece in 1922. The concept of forced immigration was a result of Lausanne Peace Treaty, which was signed between Turkish and Greek governments on 30th January 1923. As a result Greek Orthodoxes, who lived in Turkey (Anatolia and Thrace) and Muslim Turks, who lived in Greece were forced to immigrate. In this study, clothing features of Greek Orthodox woman immigrants who emigrated from Turkey to Greece in the period of the ‘1923 Greek-Turkish Population Exchange’ are aimed to be examined. In the study using the descriptive research method, before the ‘1923 Greek-Turkish Population Exchange’, the clothings belong to Greek Orthodox woman immigrants who lived in ‘Konya (Iconium)’ region in the Ottoman Empire, are discussed. In the study that is based on two different clothings belonging to ‘Konya (Iconium)’ region in the clothing collection archive at the ‘National Historical Museum’ in Greece, clothings of the Greek Orthodox woman immigrants are discussed with cultural norms, beliefs, values as well as in terms of form, ornamentation and dressing styles. Technical drawings are provided demonstrating formal features of the clothing parts that formed clothing integrity and their properties are described with the use of related literature in this study. This study is of importance that that it contains Greek Orthodox refugees’ clothings that are found in the clothing collection archive at the ‘National Historical Museum’ in Greece reflecting the cultural identities, providing information and documentation on the clothing features of the ‘1923 Greek-Turkish Population Exchange’.

Keywords: clothing, Greece, Greek Orthodoxes, immigration, national historical museum, Turkey

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Authors: José Leandro Melgar Néris, Claudinéia Brazil, Luciane Teresa Salvi, Isabel Cristina Damin

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The impact the climate change is not recent, the main variable in the hydrological cycle is the sequence and shortage of a drought, which has a significant impact on the socioeconomic, agricultural and environmental spheres. This study aims to characterize and quantify, based on precipitation climatic projections, the rainy and dry events in the region of the Uruguay River Basin, through the Standardized Precipitation Index (SPI). The database is the image that is part of the Intercomparison of Model Models, Phase 5 (CMIP5), which provides condition prediction models, organized according to the Representative Routes of Concentration (CPR). Compared to the normal set of climates in the Uruguay River Watershed through precipitation projections, seasonal precipitation increases for all proposed scenarios, with a low climate trend. From the data of this research, the idea is that this article can be used to support research and the responsible bodies can use it as a subsidy for mitigation measures in other hydrographic basins.

Keywords: climate change, climatic model, dry events, precipitation projections

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Authors: Eyal Boers

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This paper shall demonstrate how films can offer a valuable and innovative approach to the study of images, stereotypes, and national identity. "Black Book" ("Zwartboek", 2006), a World War Two film directed by Paul Verhoeven, tells the story of Rachel Stein, a young Jewish woman who becomes a member of a resistance group in the Netherlands. The main hypothesis in this paper maintains that Rachel's character possesses both features of the Dutch prototype (a white, secular, sexual, freedom-loving individualist who seems "Dutch" enough to be accepted into a Dutch resistance group and even infiltrate the local Nazi headquarters) and features which can be defined as specifically Jewish (a black-haired victim persecuted by the Nazis, transforming herself into a gentile, while remaining loyal to her fellow Jews and ultimately immigrating to Israel and becoming a Hebrew teacher in a Kibbutz). Finally, this paper claims that Rachel's "Dutchness" is symptomatic of Dutch nostalgia in the 21st century for the Jews as "others" who blend into dominant Dutch culture, while Rachel's "Jewish Otherness" reflects a transnational identity – one that is always shifting and traverses cultural and national boundaries. In this sense, a film about Dutch Jews in the Second World War reflects on issues of identity in the 21st Century.

Keywords: Dutch, film, stereotypes, identity

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Authors: B. Farahani, R. Fadil, A. Aboonabi, B. Hoffmann, J. Loscheider, K. Tavakolian, S. Arzanpour

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Wheelchair users spend long hours in a sitting position, and selecting the right cushion is highly critical in preventing pressure ulcers in that demographic. Pressure mapping systems (PMS) are typically used in clinical settings by therapists to identify the sitting profile and pressure points in the sitting area to select the cushion that fits the best for the users. A PMS is a flexible mat composed of arrays of distributed networks of flexible sensors. The output of the PMS systems is a color-coded image that shows the intensity of the pressure concentration. Therapists use the PMS images to compare different cushions fit for each user. This process is highly subjective and requires good visual memory for the best outcome. This paper aims to develop an image processing technique to analyze the images of PMS and provide an objective measure to assess the cushions based on their pressure distribution mappings. In this paper, we first reviewed the skeletal anatomy of the human sitting area and its relation to the PMS image. This knowledge is then used to identify the important features that must be considered in image processing. We then developed an algorithm based on those features to analyze the images and rank them according to their fit to the users' needs.

Keywords: dynamic cushion, image processing, pressure mapping system, wheelchair

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Authors: Fatemeh Yazdandoust

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Sustainability is a growing concern in architecture and urban planning due to the environmental impact of the built environment. Ecological challenges persist despite the proliferation of sustainable design strategies, prompting a critical reevaluation of existing approaches. This study examines sustainable design practices, focusing on the origins and processes of production, environmental impact, and socioeconomic dimensions. It also discusses ‘cleantech’ initiatives, which often prioritize profitability over ecological stewardship. The study advocates for a paradigm shift in urban design towards greater adaptability, complexity, and inclusivity, embracing porosity, incompleteness, and seed planning. This holistic approach emphasizes citizen participation and bottom-up interventions, reimagining urban spaces as evolving ecosystems. The study calls for a reimagining of sustainability that transcends conventional green design concepts, promoting a more resilient and inclusive built environment through an open system approach grounded in adaptability, diversity, and equity principles.

Keywords: sustainability, clean-tech, open system design, sustainable design

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Authors: Rajpal Kaur, Pooja Choudhary

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Biometrics, which refers to identifying an individual based on his or her physiological or behavioral characteristics, has the capabilities to the reliably distinguish between an authorized person and an imposter. The Signature recognition systems can categorized as offline (static) and online (dynamic). This paper presents Surf Feature based recognition of offline signatures system that is trained with low-resolution scanned signature images. The signature of a person is an important biometric attribute of a human being which can be used to authenticate human identity. However the signatures of human can be handled as an image and recognized using computer vision and HMM techniques. With modern computers, there is need to develop fast algorithms for signature recognition. There are multiple techniques are defined to signature recognition with a lot of scope of research. In this paper, (static signature) off-line signature recognition & verification using surf feature with HMM is proposed, where the signature is captured and presented to the user in an image format. Signatures are verified depended on parameters extracted from the signature using various image processing techniques. The Off-line Signature Verification and Recognition is implemented using Mat lab platform. This work has been analyzed or tested and found suitable for its purpose or result. The proposed method performs better than the other recently proposed methods.

Keywords: offline signature verification, offline signature recognition, signatures, SURF features, HMM

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Authors: Abe Degale D., Cheng Jian

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When creating automated video surveillance systems, violent action recognition is crucial. In recent years, hand-crafted feature detectors have been the primary method for achieving violence detection, such as the recognition of fighting activity. Researchers have also looked into learning-based representational models. On benchmark datasets created especially for the detection of violent sequences in sports and movies, these methods produced good accuracy results. The Hockey dataset's videos with surveillance camera motion present challenges for these algorithms for learning discriminating features. Image recognition and human activity detection challenges have shown success with deep representation-based methods. For the purpose of detecting violent images and identifying aggressive human behaviours, this research suggested a deep representation-based model using the transfer learning idea. The results show that the suggested approach outperforms state-of-the-art accuracy levels by learning the most discriminating features, attaining 99.34% and 99.98% accuracy levels on the Hockey and Movies datasets, respectively.

Keywords: violence detection, faster RCNN, transfer learning and, surveillance video

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Authors: Francesco Colcerasa, Fabio Pisani

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We contribute to the subjective well-being literature testing the relationship between life satisfaction and inequality of opportunity in health, measured through the Human Opportunity Index calculated at the national level using individual socio-economic data from the cross-country European Social Survey sample. We compute several indexes of opportunity inequality in health, each obtained according to a different combination of circumstances (gender, immigrant status, parents’ education). We find a robust and significant relationship where life satisfaction is higher in correspondence with low levels of health opportunity inequality. The result is twofold. On the one hand, the importance of the well-being of other types of inequality than income inequality emerges. On the other hand, the socioeconomic roots of inequality in health are investigated, suggesting that circumstances at birth have a role in future well-being. Several rationales for the nexus between life satisfaction and inequality of opportunity in health are possible, which we investigate by splitting the sample. Among others, we find a prominent role of pro-social preferences – formalized as interest towards own offspring (which can be interpreted as intergenerational justice) – as a mediating factor of the relationship.

Keywords: Inequality of opportunity, subjective wellbeing, health, health inequality, inequality of opportunity in health

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Authors: Elia Favarelli, Enrico Testi, Andrea Giorgetti

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Autonomous structural health monitoring (SHM) of many structures and bridges became a topic of paramount importance for maintenance purposes and safety reasons. This paper proposes a set of machine learning (ML) tools to perform automatic feature selection and detection of anomalies in a bridge from vibrational data and compare different feature extraction schemes to increase the accuracy and reduce the amount of data collected. As a case study, the Z-24 bridge is considered because of the extensive database of accelerometric data in both standard and damaged conditions. The proposed framework starts from the first four fundamental frequencies extracted through operational modal analysis (OMA) and clustering, followed by density-based time-domain filtering (tracking). The fundamental frequencies extracted are then fed to a dimensionality reduction block implemented through two different approaches: feature selection (intelligent multiplexer) that tries to estimate the most reliable frequencies based on the evaluation of some statistical features (i.e., mean value, variance, kurtosis), and feature extraction (auto-associative neural network (ANN)) that combine the fundamental frequencies to extract new damage sensitive features in a low dimensional feature space. Finally, one class classifier (OCC) algorithms perform anomaly detection, trained with standard condition points, and tested with normal and anomaly ones. In particular, a new anomaly detector strategy is proposed, namely one class classifier neural network two (OCCNN2), which exploit the classification capability of standard classifiers in an anomaly detection problem, finding the standard class (the boundary of the features space in normal operating conditions) through a two-step approach: coarse and fine boundary estimation. The coarse estimation uses classics OCC techniques, while the fine estimation is performed through a feedforward neural network (NN) trained that exploits the boundaries estimated in the coarse step. The detection algorithms vare then compared with known methods based on principal component analysis (PCA), kernel principal component analysis (KPCA), and auto-associative neural network (ANN). In many cases, the proposed solution increases the performance with respect to the standard OCC algorithms in terms of F1 score and accuracy. In particular, by evaluating the correct features, the anomaly can be detected with accuracy and an F1 score greater than 96% with the proposed method.

Keywords: anomaly detection, frequencies selection, modal analysis, neural network, sensor network, structural health monitoring, vibration measurement

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Authors: Nitza Davidovitch, Yael Yossel-Eisenbach

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The purpose of the study was to inquire whether there was a change in the shaping of undergraduate students’ digitally-oriented study pattern in the pre-Covid (2016-2017) versus post-Covid period (2022-2023), as affected by three factors: social background characteristics, high school, and academic background characteristics. These two-time points were cauterized by dramatic changes in teaching and learning at institutions of higher education. The data were collected via cross-sectional surveys at two-time points, in the 2016-2017 academic school year (N=443) and in the 2022-2023 school year (N=326). The questionnaire was distributed on social media and it includes questions on demographic background characteristics, previous studies in high school and present academic studies, and questions on learning and reading habits. Method of analysis: A. Statistical descriptive analysis, B. Mean comparison tests were conducted to analyze the variations in the mean score for the digitally-oriented learning pattern variable at two-time points (pre- and post-Covid) in relation to each of the independent variables. C. Analysis of variance was performed to test the main effects and the interactions. D. Applying linear regression, the research aimed to examine the combined effect of the independent variables on shaping students' digitally-oriented learning habits. The analysis includes four models. In all four models, the dependent variable is students’ perception of digitally oriented learning. The first model included social background variables; the second model included scholastic background as well. In the third model, the academic background variables were added, and the fourth model includes all the independent variables together with the variable of period (pre- and post-COVID). E. Factor analysis confirms using the principal component method with varimax rotation; the variables were constructed by a weighted mean of all the relevant statements merged to form a single variable denoting a shared content world. The research findings indicate a significant rise in students’ perceptions of digitally-oriented learning in the post-COVID period. From a gender perspective, the impact of COVID on shaping a digital learning pattern was much more significant for female students. The socioeconomic status perspective is eliminated when controlling for the period, and the student’s job is affected - more than all other variables. It may be assumed that the student’s work pattern mediates effects related to the convenience offered by digital learning regarding distance and time. The significant effect of scholastic background on shaping students’ digital learning patterns remained stable, even when controlling for all explanatory variables. The advantage that universities had over colleges in shaping a digital learning pattern in the pre-COVID period dissipated. Therefore, it can be said that after COVID, there was a change in how colleges shape students’ digital learning patterns in such a way that no institutional differences are evident with regard to shaping the digital learning pattern. The study shows that period has a significant independent effect on shaping students’ digital learning patterns when controlling for the explanatory variables.

Keywords: learning pattern, COVID, socioeconomic status, digital learning

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Authors: Kay Thinzar Phu, Lwin Lwin Oo

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In an intelligent transport system and advanced driver assistance system, the developing of real-time traffic sign detection and recognition (TSDR) system plays an important part in recent research field. There are many challenges for developing real-time TSDR system due to motion artifacts, variable lighting and weather conditions and situations of traffic signs. Researchers have already proposed various methods to minimize the challenges problem. The aim of the proposed research is to develop an efficient and effective TSDR in real time. This system proposes an adaptive thresholding method based on RGB color for traffic signs detection and new features for traffic signs recognition. In this system, the RGB color thresholding is used to detect the blue and yellow color traffic signs regions. The system performs the shape identify to decide whether the output candidate region is traffic sign or not. Lastly, new features such as termination points, bifurcation points, and 90’ angles are extracted from validated image. This system uses Myanmar Traffic Sign dataset.

Keywords: adaptive thresholding based on RGB color, blue color detection, feature extraction, yellow color detection

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Authors: Parisa Golbayani, Dan Wang, Ionut¸ Florescu

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In this work we implement machine learning techniques to financial statement reports in order to asses company’s credit rating. Specifically, the work analyzes the performance of four neural network architectures (MLP, CNN, CNN2D, LSTM) in predicting corporate credit rating as issued by Standard and Poor’s. The paper focuses on companies from the energy, financial, and healthcare sectors in the US. The goal of this analysis is to improve application of machine learning algorithms to credit assessment. To accomplish this, the study investigates three questions. First, we investigate if the algorithms perform better when using a selected subset of important features or whether better performance is obtained by allowing the algorithms to select features themselves. Second, we address the temporal aspect inherent in financial data and study whether it is important for the results obtained by a machine learning algorithm. Third, we aim to answer if one of the four particular neural network architectures considered consistently outperforms the others, and if so under which conditions. This work frames the problem as several case studies to answer these questions and analyze the results using ANOVA and multiple comparison testing procedures.

Keywords: convolutional neural network, long short term memory, multilayer perceptron, credit rating

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Authors: Akeel Noori Al-Mulla Hwaish

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The environmental impact, economics, social and cultural factors, and the processes by which people define history and meaning had influenced the dynamic shape and character of the traditional Islamic Arabic city. Therefore, in regard to the period when Islam was at its peak (7th- 13th Centuries), Islamic city wasn’t the highly dynamited at the scale of buildings and city planning that demonstrates a distinguished city as an ‘Islamic’ as appeared after centuries when the function of the buildings and their particular arrangement and planning scheme in relation to one another that defined an Islamic city character. The architectural features of the urban fabric of the traditional Arabic Islamic city are a ‎reflection of the spiritual, social, and cultural characteristics of the people. It is a ‎combination of Islamic values ‘Din’ and life needs ‘Dunia’ as Prophet Muhammad built the first Mosque in ‎Madinah in the 1st year of his migration to it, then the Suq or market on 2nd of Hijrah, attached to ‎the mosque to signify the birth of a new Muslims community which considers both, ‎‎’Din’ and ‘Dunia’ and initiated nucleus for what which called after that as an ‘Islamic’ city. This research will discuss the main characteristics and components of the traditional Arab cities and demonstrate the impact of the Islamic values on shaping the planning layout and general built environment features of the early traditional Arab cities.

Keywords: urban, Islamic, Arabic, city

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Authors: Ajitesh Pal, Arpan Datta Roy, H. K. Pratihari

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The different illegal firearms crudely made by skilled gunsmith from scrap materials are popularly known as country made firearms. Such firearms along with improvised ammunition are clandestinely marketed at the cheaper price without any license to the extremist group, criminal, poachers and firearm lovers. As per National Crime Records Bureau (NCRB), MHA, Govt of India about 80% firearm cases are committed by country made/improvised firearms. The ballistic division of the laboratory has examined a good number of cases. The analysis of firearm cases received for forensic examination revealed that 7.65mm calibre pistols mostly improvised firearm are commonly used in firearm related crime cases. In the present communication, physical parameters and other characteristics features of some 7.65mm calibre pistols have been discussed in detail. The detailed study on country made (CM) firearm will help to prepare a database related to type of material used, origin of the raw material and tools used for inscription. The study also includes to establish the chemistry of propellants & head stamp pattern. The database will be helpful to the firearm examiners, researchers, students pursuing study on forensic science as reference material.

Keywords: improvised pistol, stringent gun law, working mechanism, parameters, database

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Authors: Ebenezer O. Olaniyi, Oyebade K. Oyedotun, Khashman Adnan

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In the food industry high quality production is required within a limited time to meet up with the demand in the society. In this research work, we have developed a model which can be used to replace the human operator due to their low output in production and slow in making decisions as a result of an individual differences in deciding the defective and healthy banana. This model can perform the vision attributes of human operators in deciding if the banana is defective or healthy for food production based. This research work is divided into two phase, the first phase is the image processing where several image processing techniques such as colour conversion, edge detection, thresholding and morphological operation were employed to extract features for training and testing the network in the second phase. These features extracted in the first phase were used in the second phase; the classification system phase where the multilayer perceptron using backpropagation neural network was employed to train the network. After the network has learned and converges, the network was tested with feedforward neural network to determine the performance of the network. From this experiment, a recognition rate of 97% was obtained and the time taken for this experiment was limited which makes the system accurate for use in the food industry.

Keywords: banana, food processing, identification system, neural network

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Authors: Sanjay Saraf

Abstract:

The oral cavity can be the site for early manifestations of mucocutaneous disorders (MD) or the only site for occurrence of these disorders. It can also exhibit oral lesions with simultaneous associated skin lesions. The MD involving the oral mucosa commonly presents with signs such as ulcers, vesicles and bullae. The unique environment of the oral cavity may modify these signs of the disease, thereby making the clinical diagnosis an arduous task. In addition to the unique environment of oral cavity, the overlapping of the signs of various mucocutaneous disorders, also makes the clinical diagnosis more intricate. The aim of this review is to present the oral signs of dermatological disorders having common oral involvement and emphasize their importance in early detection of the systemic disorders. The aim is also to highlight the necessity of oral examination by a dermatologist while examining the skin lesions. Prior to the oral examination, it must be imperative for the dermatologists and the dental clinicians to have the knowledge of oral anatomy. It is also important to know the impact of various diseases on oral mucosa, and the characteristic features of various oral mucocutaneous lesions. An initial clinical oral examination is may help in the early diagnosis of the MD. Failure to identify the oral manifestations may reduce the likelihood of early treatment and lead to more serious problems. This paper reviews the oral manifestations of immune mediated dermatological disorders with common oral manifestations.

Keywords: dermatological investigations, genodermatosis, histological features, oral examination

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Authors: A. Baqqal, O. Abduhamid, H. Abdul-Hameed, T. Messager, G. Ayoub

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In this contribution, the effect of crystal content on the cyclic response of semi-crystalline polyethylene is studied over a large strain range. Experimental observations on a high-density polyethylene with 72% crystal content and an ultralow density polyethylene with 15% crystal content are reported. The cyclic stretching does appear a thermoplastic-like response for high crystallinity and an elastomeric-like response for low crystallinity, both characterized by a stress-softening, a hysteresis and a residual strain, whose amount depends on the crystallinity and the applied strain. Based on the experimental observations, a unified viscoelastic-viscoplastic constitutive model capturing the polyethylene cyclic response features is proposed. A two-phase representation of the polyethylene microstructure allows taking into consideration the effective contribution of the crystalline and amorphous phases to the intermolecular resistance to deformation which is coupled, to capture the strain hardening, to a resistance to molecular orientation. The polyethylene cyclic response features are captured by introducing evolution laws for the model parameters affected by the microstructure alteration due to the cyclic stretching.

Keywords: cyclic loading unloading, polyethylene, semi-crystalline polymer, viscoelastic-viscoplastic constitutive model

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Authors: Fatma El-Zahraa El-Taher, Ayman Taha, Jane Courtney, Susan Mckeever

Abstract:

Understanding road networks plays an important role in navigation applications such as self-driving vehicles and route planning for individual journeys. Intersections of roads are essential components of road networks. Understanding the features of an intersection, from a simple T-junction to larger multi-road junctions, is critical to decisions such as crossing roads or selecting the safest routes. The identification and profiling of intersections from satellite images is a challenging task. While deep learning approaches offer the state-of-the-art in image classification and detection, the availability of training datasets is a bottleneck in this approach. In this paper, a labelled satellite image dataset for the intersection recognition problem is presented. It consists of 14,692 satellite images of Washington DC, USA. To support other users of the dataset, an automated download and labelling script is provided for dataset replication. The challenges of construction and fine-grained feature labelling of a satellite image dataset is examined, including the issue of how to address features that are spread across multiple images. Finally, the accuracy of the detection of intersections in satellite images is evaluated.

Keywords: satellite images, remote sensing images, data acquisition, autonomous vehicles

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Authors: Shadab Bahreini

Abstract:

Public transportation is one of the most important aspects of cities, which impacts various factors of the Quality of Life (QoL) of citizens. A passenger's experience is influenced by a variety of indicators in addition to the cost and safety of the trip. This article intends to investigate how QoL is affected by public transport in an urban environment by introducing a literature review of QoL and Quality of Urban Life (QoUL), investigating the intersection of QoL and public transport, and reviewing the background theory for Transport Quality of Life (TQoL). The article proposes a Public Transport Quality of Life (PTQoL) framework comprised of a set of indicators that measure how public transport impacts QoL across personal (physical and mental), socioeconomic, and environmental dimensions. The study proposes using the framework to evaluate objective or subjective factors affecting a person's QoL regarding public transport. Finally, it concludes that public transport is a key component in shaping QoL in urban environments and that policymakers and urban planners should use the PTQoL framework to make evidence-based decisions to improve public transport systems and their impact on QoL.

Keywords: public transport, quality of life, subjective and objective indicators, urban environment

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Authors: Sumudu Sameera Perera Kimmantudawage, Chapal Khasnabis

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Technology is changing at a rapid rate, with innovations in robotics being hailed and tested in countries such as Japan, the United States and Australia, however the conversation in a public health context is stagnant. While obvious barriers to robotics use in low and middle-income countries and regions exist, the avoidance of attempting to address these regions of the world may potentially lead to an ever-increasing divide between those of high income countries and those of less. A systematic review was undertaken to determine the number of projects involving research, development and testing of robotics considered low and middle-income regions. Major findings indicate that an overwhelmingly significant number of projects failed to consider low and middle-income countries or regions. These results are unsurprising however alarming, as bridging the divide is an important step forward in achieving the UN Sustainable Development Goals by 2030. It is hoped that this research would spawn future robotics research that focusses on lower and middle-income regions.

Keywords: assistive technology, health equality, robotics, socioeconomic

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Authors: Hironori Karachi, Haruka Yamashita

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Recently, the system of quick response (QR) code is getting popular. Many companies introduce new QR code payment services and the services are competing with each other to increase the number of users. For increasing the number of users, we should grasp the difference of feature of the demographic information, usage information, and value of users between services. In this study, we conduct an analysis of real-world data provided by Nomura Research Institute including the demographic data of users and information of users’ usages of two services; LINE Pay, and PayPay. For analyzing such data and interpret the feature of them, Nonnegative Matrix Factorization (NMF) is widely used; however, in case of the target data, there is a problem of the missing data. EM-algorithm NMF (EMNMF) to complete unknown values for understanding the feature of the given data presented by matrix shape. Moreover, for comparing the result of the NMF analysis of two matrices, there is Discriminant NMF (DNMF) shows the difference of users features between two matrices. In this study, we combine EMNMF and DNMF and also analyze the target data. As the interpretation, we show the difference of the features of users between LINE Pay and Paypay.

Keywords: data science, non-negative matrix factorization, missing data, quality of services

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Authors: Ning Kang, Marius Doornenbal

Abstract:

Funding is a very important – if not crucial – resource for research projects. Usually, funding organizations will publish a description of the funded research to describe the scope of the funding award. Logically, we would expect research outcomes to align with this funding award. For that reason, we might be able to predict future research topics based on present funding award data. That said, it remains to be shown if and how future research topics can be predicted by using the funding information. In this paper, we extract funding project information and their generated paper abstracts from the Gateway to Research database as a group, and use the papers from the same domains and publication years in the Scopus database as a baseline comparison group. We annotate both the project awards and the papers resulting from the funded projects with linguistic features (noun phrases), and then calculate tf-idf and cosine similarity between these two set of features. We show that the cosine similarity between the project-generated papers group is bigger than the project-baseline group, and also that these two groups of similarities are significantly different. Based on this result, we conclude that the funding information actually correlates with the content of future research output for the funded project on the topical level. How funding really changes the course of science or of scientific careers remains an elusive question.

Keywords: natural language processing, noun phrase, tf-idf, cosine similarity

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Authors: Ting-Yu Hsu, Shyu-Yu Wu, Shieh-Kung Huang, Hung-Wei Chiang, Kung-Chun Lu, Pei-Yang Lin, Kuo-Liang Wen

Abstract:

Regional earthquake early warning (EEW) systems are not suitable for Taiwan, as most destructive seismic hazards arise due to in-land earthquakes. These likely cause the lead-time provided by regional EEW systems before a destructive earthquake wave arrives to become null. On the other hand, an on-site EEW system can provide more lead-time at a region closer to an epicenter, since only seismic information of the target site is required. Instead of leveraging the information of several stations, the on-site system extracts some P-wave features from the first few seconds of vertical ground acceleration of a single station and performs a prediction of the oncoming earthquake intensity at the same station according to these features. Since seismometers could be triggered by non-earthquake events such as a passing of a truck or other human activities, to reduce the likelihood of false alarms, a seismometer was installed at three different locations on the same site and the performance of the EEW system for these three sensor locations were discussed. The results show that the location on the ground of the first floor of a school building maybe a good choice, since the false alarms could be reduced and the cost for installation and maintenance is the lowest.

Keywords: earthquake early warning, on-site, seismometer location, support vector machine

Procedia PDF Downloads 230