Search results for: image security

Authors: Chitrangi Gupta, Arvind Bhardwaj

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This study seeks to investigate and quantify the influence of various dimensions of supply chain management (namely, supplier relationships, compatibility, specifications and standards, delivery processes, and after-sales service) on distinct dimensions of healthcare service quality (specifically, responsiveness, trustworthiness, and security) within the operational framework of XYZ Superspeciality Hospital, situated in Delhi. The name of the Hospital is not being mentioned here because of the privacy policy of the hospital. The primary objective of this research is to elucidate the impact of supply chain management practices on the overall quality of healthcare services offered within hospital settings. Employing a quantitative research design, this study utilizes a hypothesis-testing approach to systematically discern the relationship between supply chain management dimensions and the quality of health services. The findings of this study underscore the significant influence exerted by supply chain management dimensions, specifically supplier relationships, specifications and standards, delivery processes, and after-sales service, on the enhancement of healthcare service quality. Moreover, the study's results reveal that demographic factors such as gender, qualifications, age, and experience do not yield discernible disparities in the relationship between supply chain management and healthcare service quality.

Keywords: supply chain management, healthcare, hospital operations, service delivery

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Authors: Serges Djoyou Kamga, Gerard Emmanuel Kamdem Kamga

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Any serious constitutionalism entails a system of government characterised by the separation of powers between the executive, the legislature, and the judiciary. The latter is generally in charge of upholding the rule of law and the respect for human rights which are vital for the functioning of any democracy. Therefore, for the judiciary to play its role as a watchdog, it should be independent from other branches of government. The aim of this paper is to examine the independence of the judiciary in South Africa after 20 of democracy. Defining judicial independence as the courts’ ability ‘to decide cases on the basis of established law and the merits of the case, without interference from other political or governmental agents’, the paper examines the extent to which the South African judiciary is independent after twenty years of democracy. As part of assessing the independence of the judiciary, the paper begins by looking at the situation during apartheid, then proceeds with an examination of the post-apartheid legal order. It also examines the institutional independence of the judiciary by looking into its day to day activities which revolve around its self-governance, or administrative and financial independence. In addition, the paper assesses the judges’ individual independence by examining whether judicial appointment, security of tenure, judges’ remuneration and disciplinary actions and the removal of judges from office do not contain loopholes that can hinder judicial independence. Ultimately, the chapter argues that although the South African model of judicial independence is yet to be perfect, it is a good practice that can be emulated by other African countries.

Keywords: judical independence, South Africa, democracy, separation of powers

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Authors: Jessica Lynne Hicksted

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Disability discrimination is a long-standing issue that, despite protections, continues to result in unemployment, underemployment, and lack of advancement for disabled persons. Visible stigma is researched substantially; however, less is known about the impact of stigma associated with identities that can be concealed. Although researchers have investigated this issue, currently there is no tool to measure this phenomenon. The purpose of this quantitative study was to create and validate a new tool to measure stigma associated with invisible disabilities. The study is grounded by Roberts’ conceptual model of professional image construction integrating social identity, impression management, and organizational behavior; Meisenbach’s stigma management communication theory addressing the vulnerabilities and resilience to stigma communication by focusing on how individuals encounter and react to perceived stigmas; and Kelley and Michela’s causal attribution theory. Participants included 1,412 adults in the United States 18 years or older currently employed or who have been employed within the last 5 years. Confirmatory factor analysis of the new Workplace Invisible Disabilities Experience scale showed excellent fit of the factor structure to the data, X₂/df = 1.855, CFI = .955, RMSEA = .045, p = .0001. The scale has three subscales, Ableism, Advocacy, and Acceptance, with excellent internal consistency reliability. Total score, Advocacy, and Acceptance were associated with intention to disclose. Implications for positive social change include helping organizations to understand the extent of invisible disability stigma that can help improve workplace performance and satisfaction.

Keywords: invisible disabilities, accommodations, acceptance, social change, workplace inclusion

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Authors: Nazirah Hassan, Andrew Kendrick

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This study investigates the prevalence of perpetration behavior and victimization in juvenile correctional institutions. It investigates the dimensions of institutional environments and explores which environmental features relate to perpetration behaviors. The project focused on two hundred and eighty nine male and female young offenders aged 12 to 21 years old, in eight juvenile institutions in Malaysia. The research collected quantitative and qualitative data using a mixed-method approach. All participants completed the scale version of Direct and Indirect Prisoner behavior Checklist (DIPC-SCALED) and the Measuring the Quality of Prison life (MQPL). In addition, twenty-four interviews were carried out which involved sixteen residents and eight institutional staff. The findings showed that 95 per cent reported at least one behavior indicative of perpetration, and 99 per cent reported at least one behavior indicative of victimization in the past month. The DIPC-SCALED scored significantly higher on the verbal sub-scale. In addition, factors such as harmony, staff professionalism, security, family and wellbeing showed significant relation to the perpetration behavior. In the interviews, the residents identified circumstances, which affected their behavior within the institutions. This reflected the choices and decisions about how to confront the institutional life. These findings are discussed in terms of existing literature and their practical implications are considered.

Keywords: juvenile institutions, incarcerated offenders, perpetration, victimization

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Authors: Virender Singh, Mathew Rees, Simon Hampton, Sivaram Annadurai

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Plant identification is a challenging task that aims to identify the family, genus, and species according to plant morphological features. Automated deep learning-based computer vision algorithms are widely used for identifying plants and can help users narrow down the possibilities. However, numerous morphological similarities between and within species render correct classification difficult. In this paper, we tested custom convolution neural network (CNN) and vision transformer (ViT) based models using the PyTorch framework to classify plants. We used a large dataset of 88,000 provided by the Royal Horticultural Society (RHS) and a smaller dataset of 16,000 images from the PlantClef 2015 dataset for classifying plants at genus and species levels, respectively. Our results show that for classifying plants at the genus level, ViT models perform better compared to CNN-based models ResNet50 and ResNet-RS-420 and other state-of-the-art CNN-based models suggested in previous studies on a similar dataset. ViT model achieved top accuracy of 83.3% for classifying plants at the genus level. For classifying plants at the species level, ViT models perform better compared to CNN-based models ResNet50 and ResNet-RS-420, with a top accuracy of 92.5%. We show that the correct set of augmentation techniques plays an important role in classification success. In conclusion, these results could help end users, professionals and the general public alike in identifying plants quicker and with improved accuracy.

Keywords: plant identification, CNN, image processing, vision transformer, classification

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Authors: Jameela Ali, Hamid A. Jalab, Loay E. George, Abdul Rahim Ahmad, Azizah Suliman, Karim Al-Jashamy

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Red blood cells (RBC) are the most common types of blood cells and are the most intensively studied in cell biology. The lack of RBCs is a condition in which the amount of hemoglobin level is lower than normal and is referred to as “anemia”. Abnormalities in RBCs will affect the exchange of oxygen. This paper presents a comparative study for various techniques for classifying the RBCs as normal, or abnormal (anemic) using WEKA. WEKA is an open source consists of different machine learning algorithms for data mining applications. The algorithm tested are Radial Basis Function neural network, Support vector machine, and K-Nearest Neighbors algorithm. Two sets of combined features were utilized for classification of blood cells images. The first set, exclusively consist of geometrical features, was used to identify whether the tested blood cell has a spherical shape or non-spherical cells. While the second set, consist mainly of textural features was used to recognize the types of the spherical cells. We have provided an evaluation based on applying these classification methods to our RBCs image dataset which were obtained from Serdang Hospital-alaysia, and measuring the accuracy of test results. The best achieved classification rates are 97%, 98%, and 79% for Support vector machines, Radial Basis Function neural network, and K-Nearest Neighbors algorithm respectively.

Keywords: K-nearest neighbors algorithm, radial basis function neural network, red blood cells, support vector machine

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Authors: Ricky Munyaradzi Mukonza

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E-government literature continues to grow as scholars and practitioners endeavour to understand this phenomenon. There are many facets of e-government that have been written about including its definition, adoption, and implementation and so on. However, more still needs to be known particularly in relation to how e-government is being adopted in different contexts. There could be many context specific factors that have a bearing on e-government adoption and in this paper focus is on attitudes and perceptions. Association between usage of e-government services and various perceptions such as ease of use, transparency, security, ease of understanding, communication, reliability, relevancy, perceived usefulness and perceived trust is examined. Within the Zimbabwean context and in particular the country’s local government sphere, such a study has not been done. The main aim of the paper is therefore to establish perceptions and attitudes towards e-government services among residents in Zimbabwe’s two local authorities. In terms of research methodology the paper is based on a Mixed Methods Approach (MMA) to collect and analyse data giving the researcher a holistic picture of the phenomenon being investigated. A sample of 785 residents from the two local authorities was used and these were selected using a combination of cluster and purposive sampling methods. A key finding in this paper is that a majority of respondents who have had the opportunity to use e-government services perceive the services to be easy to use, transparent, secure, easy to understand, reliable, relevant, useful and trustworthy. The paper, therefore, makes an important contribution on the relationship between residents’ perceptions and attitudes and e-government usage within the chosen cases.

Keywords: adoption, attitudes, e-government, perceptions

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Authors: Bhaumik Tyagi, Mandeep Kaur, Kanika Singla

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The advancement of blockchain has facilitated scholars to remodel e-voting systems for future generations. Server-side attacks like SQL injection attacks and DOS attacks are the most common attacks nowadays, where malicious codes are injected into the system through user input fields by illicit users, which leads to data leakage in the worst scenarios. Besides, quantum attacks are also there which manipulate the transactional data. In order to deal with all the above-mentioned attacks, integration of blockchain, convolutional neural network (CNN), and Quantum Key Distribution is done in this very research. The utilization of blockchain technology in e-voting applications is not a novel concept. But privacy and security issues are still there in a public and private blockchains. To solve this, the use of a hybrid blockchain is done in this research. This research proposed cryptographic signatures and blockchain algorithms to validate the origin and integrity of the votes. The convolutional neural network (CNN), a normalized version of the multilayer perceptron, is also applied in the system to analyze visual descriptions upon registration in a direction to enhance the privacy of voters and the e-voting system. Quantum Key Distribution is being implemented in order to secure a blockchain-based e-voting system from quantum attacks using quantum algorithms. Implementation of e-voting blockchain D-app and providing a proposed solution for the privacy of voters in e-voting using Blockchain, CNN, and Quantum Key Distribution is done.

Keywords: hybrid blockchain, secure e-voting system, convolutional neural networks, quantum key distribution, one-time pad

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Authors: Mahya Naghipoor

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Purpose: Non-small cell lung cancer (NSCLC) is the most common lung cancer type. Epidermal growth factor receptor (EGFR) mutation is the main reason which causes NSCLC. Computed tomography (CT) is used for diagnosis and prognosis of lung cancers because of low price and little invasion. Semantic analyses of qualitative CT features are based on visual evaluation by radiologist. However, the naked eye ability may not assess all image features. On the other hand, radiomics provides the opportunity of quantitative analyses for CT images features. The aim of this review study was comparing accuracy of semantic and radiomics features in prognosis of EGFR mutation in NSCLC. Methods: For this purpose, the keywords including: non-small cell lung cancer, epidermal growth factor receptor mutation, semantic, radiomics, feature, receiver operating characteristics curve (ROC) and area under curve (AUC) were searched in PubMed and Google Scholar. Totally 29 papers were reviewed and the AUC of ROC analyses for semantic and radiomics features were compared. Results: The results showed that the reported AUC amounts for semantic features (ground glass opacity, shape, margins, lesion density and presence or absence of air bronchogram, emphysema and pleural effusion) were %41-%79. For radiomics features (kurtosis, skewness, entropy, texture, standard deviation (SD) and wavelet) the AUC values were found %50-%86. Conclusions: In conclusion, the accuracy of radiomics analysis is a little higher than semantic in prognosis of EGFR mutation in NSCLC.

Keywords: lung cancer, radiomics, computer tomography, mutation

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Authors: Dibyendu Roy, V. Ramu Reddy, Parijat Deshpande, Ranjan Dasgupta

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Imaging of underwater objects is primarily conducted by acoustic imagery due to the severe attenuation of electro-magnetic waves in water. Acoustic imagery underwater has varied range of significant applications such as side-scan sonar, mine hunting sonar. It also finds utility in other domains such as imaging of body tissues via ultrasonography and non-destructive testing of objects. In this paper, we explore the feasibility of using active acoustic imagery in air and simulate phased array beamforming techniques available in literature for various array designs to achieve a suitable acoustic sensor array design for a portable mobile robot which can be applied to detect the presence/absence of anomalous objects in a room. The multi-path reflection effects especially in enclosed rooms and environmental noise factors are currently not simulated and will be dealt with during the experimental phase. The related hardware is designed with the same feasibility criterion that the developed system needs to be deployed on a portable mobile robot. There is a trade of between image resolution and range with the array size, number of elements and the imaging frequency and has to be iteratively simulated to achieve the desired acoustic sensor array design. The designed acoustic imaging array system is to be mounted on a portable mobile robot and targeted for use in surveillance missions for intruder alerts and imaging objects during dark and smoky scenarios where conventional optic based systems do not function well.

Keywords: acoustic sensor array, acoustic imagery, anomaly detection, phased array beamforming

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Authors: P. Siriarchawatana, K. Leungchavaphongse, N. Covavisaruch, K. Rojananuangnit, P. Boondaeng, N. Panyayingyong

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Glaucoma is a disease that causes visual loss in adults. Glaucoma causes damage to the optic nerve and its overall pathophysiology is still not fully understood. Vasculopathy may be one of the possible causes of nerve damage. Photographic imaging of retinal vessels by fundus camera during eye examination may complement clinical management. This paper presents an innovation for measuring central light reflex width-to-retinal vessel diameter ratio (CRR) from digital retinal photographs. Using our edge detection technique, CRRs from glaucoma and normal eyes were compared to examine differences and associations. CRRs were evaluated on fundus photographs of participants from Mettapracharak (Wat Raikhing) Hospital in Nakhon Pathom, Thailand. Fifty-five photographs from normal eyes and twenty-one photographs from glaucoma eyes were included. Participants with hypertension were excluded. In each photograph, CRRs from four retinal vessels, including arteries and veins in the inferotemporal and superotemporal regions, were quantified using edge detection technique. From our finding, mean CRRs of all four retinal arteries and veins were significantly higher in persons with glaucoma than in those without glaucoma (0.34 vs. 0.32, p < 0.05 for inferotemporal vein, 0.33 vs. 0.30, p < 0.01 for inferotemporal artery, 0.34 vs. 0.31, p < 0.01 for superotemporal vein, and 0.33 vs. 0.30, p < 0.05 for superotemporal artery). From these results, an increase in CRRs of retinal vessels, as quantitatively measured from fundus photographs, could be associated with glaucoma.

Keywords: glaucoma, retinal vessel, central light reflex, image processing, fundus photograph, edge detection

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Authors: Rômulo Eustáquio Martins de Souza, Paulo Alexandre Rodrigues de Vasconcelos Figueiredo

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In recent years, there has been a surge in interest in applying artificial intelligence techniques, particularly machine learning algorithms. Machine learning is a data-analysis technique that automates the creation of analytical models, making it especially useful for designing complex situations. As a result, this technology aids in reducing human intervention while producing accurate results. This methodology is also extensively used in aerospace engineering since this is a field that encompasses several high-complexity operations, such as rocket propulsion. Rocket propulsion is a high-risk operation in which engine failure could result in the loss of life. As a result, it is critical to use computational methods capable of precisely representing the spacecraft's analytical model to guarantee its security and operation. Thus, this paper describes the use of machine learning algorithms for rocket propulsion to aid the realization that this technique is an efficient way to deal with challenging and restrictive aerospace engineering activities. The paper focuses on three machine-learning-aided rocket propulsion applications: set-point control of an expander-bleed rocket engine, supersonic retro-propulsion of a small-scale rocket, and leak detection and isolation on rocket engine data. This paper describes the data-driven methods used for each implementation in depth and presents the obtained results.

Keywords: data analysis, modeling, machine learning, aerospace, rocket propulsion

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Authors: Rishabh Ambavanekar

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Expressive Aphasia (EA) is an oral disability, common among stroke victims, in which the Broca’s area of the brain is damaged, interfering with verbal communication abilities. EA currently has no technological solutions and its only current viable solutions are inefficient or only available to the affluent. This prompts the need for an affordable, innovative solution to facilitate recovery and assist in speech generation. This project proposes a novel concept: using a wearable low-cost electroencephalography (EEG) device-based brain-computer interface (BCI) to translate a user’s inner dialogue into words. A low-cost EEG device was developed and found to be 10 to 100 times less expensive than any current EEG device on the market. As part of the BCI, a machine learning (ML) model was developed and trained using the EEG data. Two stages of testing were conducted to analyze the effectiveness of the device: a proof-of-concept and a final solution test. The proof-of-concept test demonstrated an average accuracy of above 90% and the final solution test demonstrated an average accuracy of above 75%. These two successful tests were used as a basis to demonstrate the viability of BCI research in developing lower-cost verbal communication devices. Additionally, the device proved to not only enable users to verbally communicate but has the potential to also assist in accelerated recovery from the disorder.

Keywords: neurotechnology, brain-computer interface, neuroscience, human-machine interface, BCI, HMI, aphasia, verbal disability, stroke, low-cost, machine learning, ML, image recognition, EEG, signal analysis

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Authors: Ahmad Al-Turki

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Composting is the suitable way of recycling organic waste for agricultural application and environment protection. In Saudi Arabia, several composting facilities are available and producing high quantity of composts. The aim of this study is to evaluate the physical characteristics of composts manufactured in Saudi Arabia and acquire a comprehensive image of its quality through the comparative with international standards of compost quality such as CCQC and PAS-100. In the present study different locally produced compost were identified and most of the producing factories were visited during the manufacturing of composts. Representative samples of different compost production stage were collected and Physical characteristics were determined, which included moisture content, bulk density, percentage of sand and the size of distribution of the compost particles. Results showed wide variations in all parameters investigated. Results of the study indicated generally that there is a wide variation in the physical characteristics of the types of compost under study. The initial moister contents in composts were generally low, it was less than 60% in most samples and not sufficient for microbial activities for biodegradation in 96% of the 96% of the types of compost and this will impede the decomposition of organic materials. The initial bulk density values ranged from 117 gL-1 to 1110.0 gL-1, while the final apparent bulk density ranged from 340.0 gL-1 to 1000gL-1 and about 45.4 % did not meet the ideal bulk density value. Sand percents in composts were between 3.3 % and 12.5%. This study has confirmed the need for a standard specification for compost manufactured in Saudi Arabia for agricultural use based on international standards for compost and soil characteristics and climatic conditions in Saudi Arabia.

Keywords: compost, maturity, Saudi Arabia, organic material

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Authors: A. Chandra, M. Arthur, L. Mize, A. Pomeroy-Stevens

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Background: Lower and middle-income countries (LMICs) in Asia face rapid urbanization resulting in both economic opportunities (the urban advantage) and emerging health challenges. Urban health risks are magnified in informal settlements and include infectious disease outbreaks, inadequate access to health services, and poor air quality. Over the coming years, urban spaces in Asia will face accelerating public health risks related to migration, climate change, and environmental health. These challenges are complex and require multi-sectoral and multi-stakeholder solutions. The Building Health Cities (BHC) program is funded by the United States Agency for International Development (USAID) to work with smart city initiatives in the Asia region. BHC approaches urban health challenges by addressing policies, planning, and services through a health equity lens, with a particular focus on informal settlements and migrant communities. The program works to develop data-driven decision-making, build inclusivity through stakeholder engagement, and facilitate the uptake of appropriate technology. Methodology: The BHC program has partnered with the smart city initiatives of Indore in India, Makassar in Indonesia, and Da Nang in Vietnam. Implementing partners support municipalities to improve health delivery and equity using two key approaches: political economy analysis and participatory systems mapping. Political economy analyses evaluate barriers to collective action, including corruption, security, accountability, and incentives. Systems mapping evaluates community health challenges using a cross-sectoral approach, analyzing the impact of economic, environmental, transport, security, health system, and built environment factors. The mapping exercise draws on the experience and expertise of a diverse cohort of stakeholders, including government officials, municipal service providers, and civil society organizations. Results: Systems mapping and political economy analyses identified significant barriers for health care in migrant populations. In Makassar, migrants are unable to obtain the necessary card that entitles them to subsidized health services. This finding is being used to engage with municipal governments to mitigate the barriers that limit migrant enrollment in the public social health insurance scheme. In Indore, the project identified poor drainage of storm and wastewater in migrant settlements as a cause of poor health. Unsafe and inadequate infrastructure placed residents of these settlements at risk for both waterborne diseases and injuries. The program also evaluated the capacity of urban primary health centers serving migrant communities, identifying challenges related to their hours of service and shortages of health workers. In Da Nang, the systems mapping process has only recently begun, with the formal partnership launched in December 2019. Conclusion: This paper explores lessons learned from BHC’s systems mapping, political economy analyses, and stakeholder engagement approaches. The paper shares progress related to the health of migrants in informal settlements. Case studies feature barriers identified and mitigating steps, including governance actions, taken by local stakeholders in partner cities. The paper includes an update on ongoing progress from Indore and Makassar and experience from the first six months of program implementation from Da Nang.

Keywords: informal settlements, migration, stakeholder engagement mapping, urban health

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Authors: Busari Moshood Olanyi

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Good governance remains the expectation of every political party in power, especially in this democratic dispensation of the Nigerian Nation. The need to ensure that the citizenry enjoys the dividends of democracy as often promised during various electioneering campaigns is envisioned to be the motif for different agendas and political slogans by different administrations. Unfortunately, different political agendas towards the security of lives and properties, halting the pillage of the economy by corrupt public officials and creation of employment opportunities for the youths, have a record of setback in the history of political leadership and governance in Nigeria. Therefore, the paper examined the principles of Islamic theocracy in its advocacy for a paradigm shift in the Nigerian political system, with a view to engendering good governance. Islamic political terms such as Shūrā (mutual consultation), ‘Adālah (equality and justice), Khilāfah (succession and stewardship) Majlis ash-Shūrā (consultative forum) and Muḥāsabah (accountability) were espoused as sacrosanct to implementing Islamic theocracy as an alternative system of government in Nigeria. The paper concluded by being flexible on the nomenclature of the suggested political system, considering the multi-religious nature of the country as a political entity. Among other recommendations, infusion of politics into our moral/religious system and not the other way round was considered a good step in the direction of a political paradigm shift for ensuring good governance and guaranteeing its sustainability in Nigeria.

Keywords: Nigerian nation, democracy, good governance, Islamic theocracy, paradigm shift

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Authors: Mahmood Seyyed, Akram Salehi Heykoei, Hamidreza Safakish Kashani

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Among the remaining resource of the past, coins considered as an authentic documents among the most important documentary sources. The coins were minted in a place that called mint. The number and position of the mints in each period reflects the amount of economic power, political security and business growth, which was always fluctuated its position with changing the political and economic condition. Considering that, trade has more growth during the Safavid period than previous ones, the mint also has been in greater importance. It seems the one hand, the growth of economic in Safavid period has a direct link with the number and places of the mints at that time and in the other hand, the mints have been formed in some places because of the specific characteristic of cities and regions. Increasing the number of mints in the north of the country due to the growth of silk trade and in the west and northwest due to the political and commercial relation with Ottoman Empire, also the characteristics such as existence of mines, located in the Silk Road and communication ways, all are the results of this investigation. Accordingly, in this article researcher tries to examine the characteristics that give priority to a city for having mint. With considering that in the various historical periods, the mints were based in the most important cities in terms of political and social, at that time, this article examines the cities specific characteristics in the formation of the mints in Safavid period.

Keywords: documentary sources, coins, mint, city, Safavid

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Authors: Abdoulaye Diop, Nahid Emad, Thierry Winter, Mohamed Hilia

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Data assets protection is a crucial issue in the cybersecurity field. Companies use logical access control tools to vault their information assets and protect them against external threats, but they lack solutions to counter insider threats. Nowadays, insider threats are the most significant concern of security analysts. They are mainly individuals with legitimate access to companies information systems, which use their rights with malicious intents. In several fields, behavior anomaly detection is the method used by cyber specialists to counter the threats of user malicious activities effectively. In this paper, we present the step toward the construction of a user and entity behavior analysis framework by proposing a behavior anomaly detection model. This model combines machine learning classification techniques and graph-based methods, relying on linear algebra and parallel computing techniques. We show the utility of an ensemble learning approach in this context. We present some detection methods tests results on an representative access control dataset. The use of some explored classifiers gives results up to 99% of accuracy.

Keywords: cybersecurity, data protection, access control, insider threat, user behavior analysis, ensemble learning, high performance computing

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Authors: Porntip Ruengtam

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This article is an extension of previous research presenting the relevant factors related to environmental perceptions, residential community, and the design of a healing environment, which have effects on the well-being and requirements of Thai elderly. Research methodology began with observations and interviews in three case studies in terms of the management processes and environment design of similar existing projects in Thailand. The interview results were taken to summarize with related theories and literature. A questionnaire survey was designed for data collection to confirm the factors of requirements in a residential community intended for the Thai elderly. A structural equation model (SEM) was formulated to explain the cause-effect factors for the requirements of a residential community for Thai elderly. The research revealed that the requirements of a residential community for Thai elderly were classified into three groups when utilizing a technique for exploratory factor analysis. The factors were comprised of (1) requirements for general facilities and activities, (2) requirements for facilities related to health and security, and (3) requirements for facilities related to physical exercise in the residential community. The results from the SEM showed the background of elderly people had a direct effect on their requirements for a residential community from various aspects. The results should lead to the formulation of policies for design and management of residential communities for the elderly in order to enhance quality of life as well as both the physical and mental health of the Thai elderly.

Keywords: elderly, environmental design, residential community, structural equation modeling

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Authors: I-Huan Chiu, Kazuhiko Ninomiya, Shin’ichiro Takeda, Meito Kajino, Miho Katsuragawa, Shunsaku Nagasawa, Atsushi Shinohara, Tadayuki Takahashi, Ryota Tomaru, Shin Watanabe, Goro Yabu

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In recent years, a nondestructive elemental analysis method based on muonic X-ray measurements has been developed and applied for various samples. Muonic X-rays are emitted after the formation of a muonic atom, which occurs when a negatively charged muon is captured in a muon atomic orbit around the nucleus. Because muonic X-rays have higher energy than electronic X-rays due to the muon mass, they can be measured without being absorbed by a material. Thus, estimating the two-dimensional (2D) elemental distribution of a sample became possible using an X-ray imaging detector. In this work, we report a non-destructive imaging experiment using muonic X-rays at Japan Proton Accelerator Research Complex. The irradiated target consisted of polypropylene material, and a double-sided silicon strip detector, which was developed as an imaging detector for astronomical observation, was employed. A peak corresponding to muonic X-rays from the carbon atoms in the target was clearly observed in the energy spectrum at an energy of 14 keV, and 2D visualizations were successfully reconstructed to reveal the projection image from the target. This result demonstrates the potential of the non-destructive elemental imaging method that is based on muonic X-ray measurement. To obtain a higher position resolution for imaging a smaller target, a new detector system will be developed to improve the statistical analysis in further research.

Keywords: DSSD, muon, muonic X-ray, imaging, non-destructive analysis

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Authors: Malik Takreem Ahmad, Pablo Lamata, Rasi Mizori

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Background: In recent years, mobile health apps have grown in popularity as a means for people to track and manage their health. While there is increasing worry that these applications may potentially contribute to the emergence of health anxiety, they can also help to encourage healthy behaviours and provide access to health information. Objective: The objective of this literature review is to look at available mhealth apps and critically evaluate the compromise between reassurance and anxiety. Methodology: A literature review was carried out to analyse the effects of mhealth apps on the creation of health anxiety within the general population. PubMed and SCOPUS were used to search for relevant articles, and abstracts were screened using inclusion criteria of the terms: mhealth apps; e-Health; healthcare apps; cyberchondria; Health anxiety; illness anxiety disorder. A total of 27 studies were included in the review. Results and discussion: The findings suggest a direct relationship between mobile health app use and health anxiety. The impact of mobile health apps on health anxiety may depend on how they are used - individuals receiving a constant stream of health-related information may trigger unnecessary concern about one's health. The need for more regulation and oversight is identified, which can lead to app quality and safety consistency. There are also concerns about data security and privacy and the resulting "digital gap" for individuals without mobiles or internet access. Conclusion: While health apps can be valuable tools for managing and tracking health, individuals need to use them in a balanced and informed way to avoid increased anxiety.

Keywords: mobile health, mhealth apps, cyberchondria, health anxiety

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Authors: Chih-Hung Chen, Yih-Shyang Cheng, Yu-Hsin Tu

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Holographic optical elements (HOEs) have recently been one of the most suitable components in optoelectronic technology owing to the requirement of the product system with compact size. Computer-generated holography (CGH) is a well-known technology for HOEs production. In some cases, a well-designed diffractive optical element with multifunctional components is also an important issue and needed for an advanced optoelectronic system. Spatial light modulator (SLM) is one of the key components that has great capability to display CGH pattern and is widely used in various applications, such as an image projection system. As mentioned to multifunctional components, such as phase and amplitude modulation of light, high-resolution hologram with multiple-exposure procedure is also one of the suitable candidates. However, holographic recording under multiple exposures, the diffraction efficiency of the final hologram is inevitably lower than that with single exposure process. In this study, a two-step holographic recording method, including the master hologram fabrication and the replicated hologram production, will be designed. Since there exist a reduction factor M² of diffraction efficiency in multiple-exposure holograms (M multiple exposures), so it seems that single exposure would be more efficient for holograms replication. In the second step of holographic replication, a stable optical system with one-shot copying is introduced. For commercial application, one may utilize this concept of holographic copying to obtain duplications of HOEs with higher optical performance.

Keywords: holographic replication, holography, one-shot copying, optical element

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Authors: Karl-Erich Lindenschmidt, Apurba Das, Joel Trudell, Keanne Russell

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In this presentation, we explore options for mitigating ice-jam flooding along the Athabasca River in western Canada. Not only flood hazard, expressed in this case as the probability of flood depths and extents being exceeded, but also flood risk, in which annual expected damages are calculated. Flood risk is calculated, which allows a cost-benefit analysis to be made so that decisions on the best mitigation options are not based solely on flood hazard but also on the costs related to flood damages and the benefits of mitigation. The river ice model is used to simulate extreme ice-jam flood events with which scenarios are run to determine flood exposure and damages in flood-prone areas along the river. We will concentrate on three mitigation options – the placement of a dike, artificial breakage of the ice cover along the river, the installation of an ice-control structure, and the construction of a reservoir. However, any mitigation option is not totally failsafe. For example, dikes can still be overtopped and breached, and ice jams may still occur in areas of the river where ice covers have been artificially broken up. Hence, for all options, it is recommended that zoning of building developments away from greater flood hazard areas be upheld. Flood mitigation can have a negative effect of giving inhabitants a false sense of security that flooding may not happen again, leading to zoning policies being relaxed. (Text adapted from Lindenschmidt [2022] "Ice Destabilization Study - Phase 2", submitted to the Regional Municipality of Wood Buffalo, Alberta, Canada)

Keywords: ice jam, flood hazard, flood risk river ice modelling, flood risk

Procedia PDF Downloads 179

Authors: Raihan Zahirah Mauludy Ridwan, Frisca Devi Choirina

Abstract:

Indonesia with its former presidents has enhanced the bilateral cooperation also multilateral cooperation in terms of economy but the result was not significant towards eradicating poverty, unemployment, income inequality, and economic growth. To eradicate these problems, President Joko Widodo through his several points of Nawacita wants to boost Indonesia’s economic relationship and cooperation which manifested in “Economic Diplomacy” as one of Indonesia’s foreign policy priority and he pitches it in international forums. The economic diplomacy does not only attracts prospective countries but also attracts the foreign businessman and investors. The economic diplomacy includes four sectors which are vital for economic growth, one of them is investment. This paper would like to answer how economic diplomacy can have significant impact towards social welfare, equity and economic growth especially in Indonesia. The purpose of this paper is to explore the role of economic diplomacy and its impact toward Indonesia’s welfare, equity, and economic growth. This paper uses the theory of economic diplomacy to link the current international political economic sphere and the impact of economic diplomacy for Indonesia through case study method. The paper affirms that economic diplomacy in investment sector does have significant impact, especially in the development of infrastructures, foreign direct investment in several sectors, and food security.

Keywords: economic diplomacy, economic growth, equity, Indonesia, Joko Widodo, social welfare

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Authors: Maryam Rasool, Farhan Munir, Fahad Nawaz, Saad Ahmad

Abstract:

A patch antenna operating in the Ultra-Wide Band of frequency (3.1 GHz – 10.6 GHz) is designed with enhanced security from interference from other applications by incorporating the notching technique. Patch antennas in the Ultra-Wide Band are becoming widely famous due to their low power, light weight and high data rate capability. Micro strip patch antenna’s patch can be altered to increase its bandwidth and introduce UWB character in it. The designed antenna is a patch antenna consisting of a conductive sheet of metal mounted over a large sheet of metal called the ground plane with a substrate separating the two. Notched bands are public safety WLAN, WLAN and FSS. Different techniques used to implement the UWB antenna were individually implemented and there results were examined. V shaped patch was then chosen and modified to an arrow shaped patch to give the optimized results operating on the entire UWB region with considerable return loss. The frequency notch prevents the operation of the antenna at a particular range of frequency, hence minimizing interference from other systems. There are countless techniques for introducing the notch but we have used inverted C-shaped slots in the UWB patch to get the notch characteristics as output and also wavelength resonators to introduce notch in UWB band. The designed antenna is simulated in High Frequency Structural Simulator (HFSS) 13.0 by Ansoft.

Keywords: HFSS, Notch, UWB, WLAN

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Authors: Pooja Khanal, Huaming Zhang

Abstract:

Labeling of issues/bugs, also known as bug classification, plays a vital role in software engineering. Some known labels/classes of bugs are 'User Interface', 'Security', and 'API'. Most of the time, when a reporter reports a bug, they try to assign some predefined label to it. Those issues are reported for a project, and each project is a repository in GitHub/GitLab, which contains multiple issues. There are many software project repositories -ranging from individual projects to commercial projects. The labels assigned for different repositories may be dependent on various factors like human instinct, generalization of labels, label assignment policy followed by the reporter, etc. While the reporter of the issue may instinctively give that issue a label, another person reporting the same issue may label it differently. This way, it is not known mathematically if a label in one repository is similar or different to the label in another repository. Hence, the primary goal of this research is to find the semantic differences between bug labeling of different repositories via machine learning. Independent optimal classifiers for individual repositories are built first using the text features from the reported issues. The optimal classifiers may include a combination of multiple classifiers stacked together. Then, those classifiers are used to cross-test other repositories which leads the result to be deduced mathematically. The produce of this ongoing research includes a formalized open-source GitHub issues database that is used to deduce the similarity of the labels pertaining to the different repositories.

Keywords: bug classification, bug labels, GitHub issues, semantic differences

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Authors: Paul Barasa Wanyama, Tom Wanyama

Abstract:

Governments and development partners in low-income countries often prioritize building Water Sanitation and Hygiene (WaSH) infrastructure of healthcare facilities to improve maternal healthcare outcomes. However, the operation, maintenance, and utilization of this infrastructure is almost never considered. Many healthcare facilities in these countries use untreated water that is not monitored for quality or quantity. Consequently, it is common to run out of water with a patient is on their way to, or in, the operating theater. Further, the handwashing stations in healthcare facilities regularly run out of water or soap for months, and the latrines are typically not clean, in part due to the lack of water. In this chapter, we present a system that uses Internet of Things (IoT), big data, cloud computing and AI to initiate WaSH security in healthcare facilities, with a specific focus on maternal health. We have implemented smart sensors and actuators to monitor and control WaSH systems from afar to ensure their objectives are achieved. We have also developed a cloud-based system to analyze WaSH data in real time and communicate relevant information back to the healthcare facilities and their stakeholders (e.g., medical personnel, NGOs, ministry of health officials, facilities managers, community leaders, pregnant women, and new mothers and their families) to avert or mitigate problems before they occur.

Keywords: WaSH, internet of things, artificial intelligence, maternal health, rural communities, healthcare facilities

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Authors: Sheikh Shams Azam, Manoj Raju, Venkatesh Pagidimarri, Vamsi Kasivajjala

Abstract:

Over the past decade, there has been a steep rise in the data-driven analysis in major areas of medicine, such as clinical decision support system, survival analysis, patient similarity analysis, image analytics etc. Most of the data in the field are well-structured and available in numerical or categorical formats which can be used for experiments directly. But on the opposite end of the spectrum, there exists a wide expanse of data that is intractable for direct analysis owing to its unstructured nature which can be found in the form of discharge summaries, clinical notes, procedural notes which are in human written narrative format and neither have any relational model nor any standard grammatical structure. An important step in the utilization of these texts for such studies is to transform and process the data to retrieve structured information from the haystack of irrelevant data using information retrieval and data mining techniques. To address this problem, the authors present Q-Map in this paper, which is a simple yet robust system that can sift through massive datasets with unregulated formats to retrieve structured information aggressively and efficiently. It is backed by an effective mining technique which is based on a string matching algorithm that is indexed on curated knowledge sources, that is both fast and configurable. The authors also briefly examine its comparative performance with MetaMap, one of the most reputed tools for medical concepts retrieval and present the advantages the former displays over the latter.

Keywords: information retrieval, unified medical language system, syntax based analysis, natural language processing, medical informatics

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Authors: Junbeom Lee, Jaehyuck Cho, Wookyeong Jeong, Jonghan Won, Jungmin Hwang, Youngseok Song, Taikyeong Jeong

Abstract:

This paper investigates and analyzes meta-learning technologies that use multiple-cameras to monitor and check abnormal behavior in people in real-time in the area of healthcare fields. Advances in artificial intelligence and computer vision technologies have confirmed that cameras can be useful for individual health monitoring and abnormal behavior detection. Through this, it is possible to establish a system that can respond early by automatically detecting abnormal behavior of the elderly, such as patients and the elderly. In this paper, we use a technique called meta-learning to analyze image data collected from cameras and develop a commercial product to determine abnormal behavior. Meta-learning applies machine learning algorithms to help systems learn and adapt quickly to new real data. Through this, the accuracy and reliability of the abnormal behavior discrimination system can be improved. In addition, this study proposes a meta-learning-based abnormal behavior detection system that includes steps such as data collection and preprocessing, feature extraction and selection, and classification model development. Various healthcare scenarios and experiments analyze the performance of the proposed system and demonstrate excellence compared to other existing methods. Through this study, we present the possibility that camera-based meta-learning technology can be useful for monitoring and testing abnormal behavior in the healthcare area.

Keywords: artificial intelligence, abnormal behavior, early detection, health monitoring

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Authors: Benyelles Zakaria, Yousfi Djaafar, Karoui Moussa Sofiane

Abstract:

Agriculture is fundamental and remains an important objective in the Algerian economy, based on traditional techniques and structures, it generally has a purpose of consumption. Collection of agricultural statistics in Algeria is done using traditional methods, which consists of investigating the use of land through survey and field survey. These statistics suffer from problems such as poor data quality, the long delay between collection of their last final availability and high cost compared to their limited use. The objective of this work is to develop a processing chain for a reliable inventory of agricultural land by trying to develop and implement a new method of extracting information. Indeed, this methodology allowed us to combine data from remote sensing and field data to collect statistics on areas of different land. The contribution of remote sensing in the improvement of agricultural statistics, in terms of area, has been studied in the wilaya of Sidi Bel Abbes. It is in this context that we applied a method for extracting information from satellite images. This method is called the non-negative matrix factorization, which does not consider the pixel as a single entity, but will look for components the pixel itself. The results obtained by the application of the MNF were compared with field data and the results obtained by the method of maximum likelihood. We have seen a rapprochement between the most important results of the FMN and those of field data. We believe that this method of extracting information from satellite data leads to interesting results of different types of land uses.

Keywords: blind source separation, hyper-spectral image, non-negative matrix factorization, remote sensing

Procedia PDF Downloads 418