Search results for: hybrid hierarchical clustering

Authors: Djallel Bouamama, Yasser R. Haddadi

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Accurate brain tumor segmentation is crucial for diagnosis and treatment planning, yet it remains a challenging task due to the variability in tumor shapes and intensities. This paper introduces a distinct approach to brain tumor image segmentation by leveraging an advanced architecture known as Mamba-Unet. Building on the well-established U-Net framework, Mamba-Unet incorporates distinct design enhancements to improve segmentation performance. Our proposed method integrates a multi-scale attention mechanism and a hybrid loss function to effectively capture fine-grained details and contextual information in brain MRI scans. We demonstrate that Mamba-Unet significantly enhances segmentation accuracy compared to conventional U-Net models by utilizing a comprehensive dataset of annotated brain MRI scans. Quantitative evaluations reveal that Mamba-Unet surpasses traditional U-Net architectures and other contemporary segmentation models regarding Dice coefficient, sensitivity, and specificity. The improvements are attributed to the method's ability to manage class imbalance better and resolve complex tumor boundaries. This work advances the state-of-the-art in brain tumor segmentation and holds promise for improving clinical workflows and patient outcomes through more precise and reliable tumor detection.

Keywords: brain tumor classification, image segmentation, CNN, U-NET

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Authors: Neetu Manocha

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Image segmentation is a technique where a picture is parted into distinct parts having similar features which have a place with similar items. Various segmentation strategies have been proposed as of late by prominent analysts. But, after ultimate thorough research, the novelists have analyzed that generally, the old methods do not decrease the segmentation error rate. Then author finds the technique HIST-SI to decrease the segmentation error rates. In this technique, cluster-based and threshold-based segmentation techniques are merged together. After then, to improve the result of HIST-SI, the authors added the method of filtering and linking in this technique named Imp_HIST-SI to decrease the segmentation error rates. The goal of this research is to find a new technique to decrease the segmentation error rates and produce much better results than the HIST-SI technique. For testing the proposed technique, a dataset of Bhuvan – a National Geoportal developed and hosted by ISRO (Indian Space Research Organisation) is used. Experiments are conducted using Scikit-image & OpenCV tools of Python, and performance is evaluated and compared over various existing image segmentation techniques for several matrices, i.e., Mean Square Error (MSE) and Peak Signal Noise Ratio (PSNR).

Keywords: satellite image, image segmentation, edge detection, error rate, MSE, PSNR, HIST-SI, linking, filtering, imp_HIST-SI

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Authors: Mohammad Vahed, Ana Sadeghitohidi, Majid Vahed, Hiroki Takahashi

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In the genomics field, the huge amounts of data have produced by the next-generation sequencers (NGS). Data volumes are very rapidly growing, as it is postulated that more than one billion bases will be produced per year in 2020. The growth rate of produced data is much faster than Moore's law in computer technology. This makes it more difficult to deal with genomics data, such as storing data, searching information, and finding the hidden information. It is required to develop the analysis platform for genomics big data. Cloud computing newly developed enables us to deal with big data more efficiently. Hadoop is one of the frameworks distributed computing and relies upon the core of a Big Data as a Service (BDaaS). Although many services have adopted this technology, e.g. amazon, there are a few applications in the biology field. Here, we propose a new algorithm to more efficiently deal with the genomics big data, e.g. sequencing data. Our algorithm consists of two parts: First is that BDaaS is applied for handling the data more efficiently. Second is that the hybrid method of MapReduce and Fuzzy logic is applied for data processing. This step can be parallelized in implementation. Our algorithm has great potential in computational analysis of genomics big data, e.g. de novo genome assembly and sequence similarity search. We will discuss our algorithm and its feasibility.

Keywords: big data, fuzzy logic, MapReduce, Hadoop, cloud computing

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Authors: Sajjad Baghernezhad

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Meta-heuristic and hybrid algorithms have high adeer in modeling medical problems. In this study, a neural network was used to predict covid-19 among high-risk and low-risk patients. This study was conducted to collect the applied method and its target population consisting of 550 high-risk and low-risk patients from the Kerman University of medical sciences medical center to predict the coronavirus. In this study, the memetic algorithm, which is a combination of a genetic algorithm and a local search algorithm, has been used to update the weights of the neural network and develop the accuracy of the neural network. The initial study showed that the accuracy of the neural network was 88%. After updating the weights, the memetic algorithm increased by 93%. For the proposed model, sensitivity, specificity, positive predictivity value, value/accuracy to 97.4, 92.3, 95.8, 96.2, and 0.918, respectively; for the genetic algorithm model, 87.05, 9.20 7, 89.45, 97.30 and 0.967 and for logistic regression model were 87.40, 95.20, 93.79, 0.87 and 0.916. Based on the findings of this study, neural network models have a lower error rate in the diagnosis of patients based on individual variables and vital signs compared to the regression model. The findings of this study can help planners and health care providers in signing programs and early diagnosis of COVID-19 or Corona.

Keywords: COVID-19, decision support technique, neural network, genetic algorithm, memetic algorithm

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Authors: Amir Rashid

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Cloud Computing frameworks empower organizations to cut expenses by outsourcing computation resources on-request. As of now, customers of Cloud service providers have no methods for confirming the privacy and ownership of their information and data. To address this issue we propose the platform of a trusted cloud computing program (TCCP). TCCP empowers Infrastructure as a Service (IaaS) suppliers, for example, Amazon EC2 to give a shout box execution condition that ensures secret execution of visitor virtual machines. Also, it permits clients to bear witness to the IaaS supplier and decide if the administration is secure before they dispatch their virtual machines. This paper proposes a Trusted Cloud Computing Platform (TCCP) for guaranteeing the privacy and trustworthiness of computed data that are outsourced to IaaS service providers. The TCCP gives the deliberation of a shut box execution condition for a client's VM, ensuring that no cloud supplier's authorized manager can examine or mess up with its data. Furthermore, before launching the VM, the TCCP permits a client to dependably and remotely acknowledge that the provider at backend is running a confided in TCCP. This capacity extends the verification of whole administration, and hence permits a client to confirm the data operation in secure mode.

Keywords: cloud security, IaaS, cloud data privacy and integrity, hybrid cloud

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Authors: Nisha Nandlal Sharma, Julaluk Carmai, Saiprasit Koetniyom, Bernd Markert

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Whiplash Injuries are mostly experienced in car accidents. Symptoms of whiplash are commonly reported in studies, neck pain and headaches are two most common symptoms observed. The whiplash Injury mechanism is poorly understood. In present study, hybrid neck muscle model were developed with a combination of solid tetrahedral elements and 1D beam elements. Solid tetrahedral elements represents passive part of the muscle whereas, 1D beam elements represents active part. To simulate the active behavior of the muscle, Hill-type muscle model was applied to beam elements. To simulate non-linear passive properties of muscle, solid elements were modeled with rubber/foam material model. Some important muscles were then inserted into THUMS (Total Human Model for Safety) THUMS was given a boundary conditions similar to experimental tests. The model was exposed to 4g and 7g rear impacts as these load impacts are close to low speed impacts causing whiplash. The effect of muscle activation level on occupant kinematics during whiplash was analyzed.

Keywords: finite element model, muscle activation, THUMS, whiplash injury mechanism

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Authors: Yu Zhao, Mengqin Sun, Yahui Zhang

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Apparel products (or apparel) with the sense of aesthetics, usability (ergonomics) and function are fundamental and varied in people’s daily life. The numerous apparel thus produced by apparel industry, have been triggered many issues, such as the waste of sources and the environmental pollutions. In this study, a hybrid architecture called modular architecture of apparel (MAA) has been proposed to deal with the variety of apparel, and thus to overcome the aforementioned issues. Generally, the establishment of MAA takes advantage of the modular design of a general product that a product is assembled with many modules through their modular interface connector. The development of MAA is to first analyze the structure of apparel in terms of the necessity to form an apparel and the aesthetics, ergonomics, and function of apparel; then to divide apparel into many segments (or module in product design) based on the structure of apparel; to develop modular interfaces and modular interface connectors in terms of the features of apparel’s modules. It is noted that in the general product design, modules of a product are only about the function and ergonomics, but in MAA, the module of aesthetics is developed. Further, an apparel design with employing the MAA is carried out to validate its usefulness and efficiency. There are three contributions out of this study, the first is to overcome the aforementioned issues (i.e. waste of source and environmental pollutions); the second is the improvement of the modular design for product by considering aesthetics; the third is to add the value in realizing the personalized mass production of apparel in the near future.

Keywords: apparel, architecture, modular design, segment

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Authors: Sidi Ahmed Maouloud, Cheikh Ba

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Much of West Africa’s cultural heritage is written in the Al-Soudani Arabic script, which was widely used in West Africa before the time of European colonization. This Al-Soudani Arabic script is an African version of the Maghrebi script, in particular, the Al-Mebssout script. However, the local African qualities were incorporated into the Al-Soudani script in a way that gave it a unique African diversity and character. Despite the existence of several Arabic datasets in Oriental script, allowing for the analysis, layout, and recognition of texts written in these calligraphies, many Arabic scripts and written traditions remain understudied. In this paper, we present a dataset of words from Al-Soudani calligraphy scripts. This dataset consists of 100 images selected from three different manuscripts written in Al-Soudani Arabic script by different copyists. The primary source for this database was the libraries of Boston University and Cambridge University. This dataset highlights the unique characteristics of the Al-Soudani Arabic script as well as the new challenges it presents in terms of automatic word recognition of Arabic manuscripts. An HTR system based on a hybrid ANN (CRNN-CTC) is also proposed to test this dataset. SAMRA is a dataset of annotated Arabic manuscript words in the Al-Soudani script that can help researchers automatically recognize and analyze manuscript words written in this script.

Keywords: dataset, CRNN-CTC, handwritten words recognition, Al-Soudani Arabic script, HTR, manuscripts

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Authors: Jun Wang, Tingcun Wei

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The digital pulse width modulator (DPWM) is the crucial building block for digitally-controlled DC-DC switching converter, which converts the digital duty ratio signal into its analog counterpart to control the power MOSFET transistors on or off. With the increase of switching frequency of digitally-controlled DC-DC converter, the DPWM with higher time resolution is required. In this paper, a 15-bits DPWM with three-level hybrid structure is presented; the first level is composed of a7-bits counter and a comparator, the second one is a 5-bits delay line, and the third one is a 3-bits digital dither. The presented DPWM is designed and implemented using the PLL megafunction of FPGA (Field Programmable Gate Arrays), and the required frequency of clock signal is 128 times of switching frequency. The simulation results show that, for the switching frequency of 2 MHz, a DPWM which has the time resolution of 15 ps is achieved using a maximum clock frequency of 256MHz. The designed DPWM in this paper is especially useful for high-frequency digitally-controlled DC-DC switching converters.

Keywords: DPWM, digitally-controlled DC-DC switching converter, FPGA, PLL megafunction, time resolution

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Authors: Maad Kamal Al-Anni

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This study is about an algorithmic dependence of Artificial Neural Network on Multilayer Perceptron (MPL) pertaining to the classification and clustering presentations for Mobile Adhoc Network vulnerabilities. Moreover, mobile ad hoc network (MANET) is ubiquitous intelligent internetworking devices in which it has the ability to detect their environment using an autonomous system of mobile nodes that are connected via wireless links. Security affairs are the most important subject in MANET due to the easy penetrative scenarios occurred in such an auto configuration network. One of the powerful techniques used for inspecting the network packets is Intrusion Detection System (IDS); in this article, we are going to show the effectiveness of artificial neural networks used as a machine learning along with stochastic approach (information gain) to classify the malicious behaviors in simulated network with respect to different IDS techniques. The monitoring agent is responsible for detection inference engine, the audit data is collected from collecting agent by simulating the node attack and contrasted outputs with normal behaviors of the framework, whenever. In the event that there is any deviation from the ordinary behaviors then the monitoring agent is considered this event as an attack , in this article we are going to demonstrate the  signature-based IDS approach in a MANET by implementing the back propagation algorithm over ensemble-based Traffic Table (TT), thus the signature of malicious behaviors or undesirable activities are often significantly prognosticated and efficiently figured out, by increasing the parametric set-up of Back propagation algorithm during the experimental results which empirically shown its effectiveness  for the ratio of detection index up to 98.6 percentage. Consequently it is proved in empirical results in this article, the performance matrices are also being included in this article with Xgraph screen show by different through puts like Packet Delivery Ratio (PDR), Through Put(TP), and Average Delay(AD).

Keywords: Intrusion Detection System (IDS), Mobile Adhoc Networks (MANET), Back Propagation Algorithm (BPA), Neural Networks (NN)

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Authors: Diandra Cristache

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The transition of traditional manuscript studies into the digital framework closely affects the methodological premises upon which manuscript descriptions are modeled, created, and questioned for the purpose of research. This paper intends to explore the issue by presenting a methodological investigation into the process of modeling, creating, and questioning manuscript metadata. The investigation is founded on a close observation of the Polonsky Greek Manuscripts Project, a collaboration between the Universities of Cambridge and Heidelberg. More than just providing a realistic ground for methodological exploration, along with a complete metadata set for computational demonstration, the case study also contributes to a broader purpose: outlining general methodological principles for making the most out of manuscript metadata by means of research-oriented digital outputs. The analysis mainly focuses on the scholarly approach to manuscript descriptions, in the specific instance where the act of metadata recording does not have a programmatic research purpose. Close attention is paid to the encounter of 'traditional' practices in manuscript studies with the formal constraints of the digital framework: does the shift in practices (especially from the straight narrative of free writing towards the hierarchical constraints of the TEI encoding model) impact the structure of metadata and its capability to respond specific research questions? It is argued that flexible structure of TEI and traditional approaches to manuscript description lead to a proliferation of markup: does an 'encyclopedic' descriptive approach ensure the epistemological relevance of the digital outputs to metadata? To provide further insight on the computational approach to manuscript metadata, the metadata of the Polonsky project are processed with techniques of distant reading and data networking, thus resulting in a new group of digital outputs (relational graphs, geographic maps). The computational process and the digital outputs are thoroughly illustrated and discussed. Eventually, a retrospective analysis evaluates how the digital outputs respond to the scientific expectations of research, and the other way round, how the requirements of research questions feed back into the creation and enrichment of metadata in an iterative loop.

Keywords: digital manuscript studies, digital outputs to manuscripts metadata, metadata interoperability, methodological issues

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Authors: Vahid Ebrahimipour

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Word representation and context meaning of text-based documents play an essential role in knowledge modeling. Business procedures written in natural language are meant to store technical and engineering information, management decision and operation experience during the production system life cycle. Context meaning representation is highly dependent upon word sense, lexical relativity, and sematic features of the argument. This paper proposes a method for lexical semantic analysis and context meaning representation of maintenance activity in a mass production system. Our approach constructs a straightforward lexical semantic approach to analyze facilitates semantic and syntactic features of context structure of maintenance report to facilitate translation, interpretation, and conversion of human-readable interpretation into computer-readable representation and understandable with less heterogeneity and ambiguity. The methodology will enable users to obtain a representation format that maximizes shareability and accessibility for multi-purpose usage. It provides a contextualized structure to obtain a generic context model that can be utilized during the system life cycle. At first, it employs a co-occurrence-based clustering framework to recognize a group of highly frequent contextual features that correspond to a maintenance report text. Then the keywords are identified for syntactic and semantic extraction analysis. The analysis exercises causality-driven logic of keywords’ senses to divulge the structural and meaning dependency relationships between the words in a context. The output is a word contextualized representation of maintenance activity accommodating computer-based representation and inference using OWL/RDF.

Keywords: lexical semantic analysis, metadata modeling, contextual meaning extraction, ontology modeling, knowledge representation

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Authors: Abdelli Soulaima, Belhadj Besma

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The paper examines the choice of the central bank toward the movements of the nominal exchange rate and evaluates its effects on the volatility of the output growth and the inflation. The novel hybrid method of the dynamic stochastic general equilibrium called the DSGE-VAR is proposed for analyzing this policy experiment in a small scale open economy in particular Tunisia. The contribution is provided to the empirical literature as we apply the Tunisian data with this model, which is rarely used in this context. Note additionally that the issue of treating the degree of response of the central bank to the exchange rate in Tunisia is special. To ameliorate the estimation, the Bayesian technique is carried out for the sample 1980:q1 to 2011 q4. Our results reveal that the central bank should not react or softly react to the exchange rate. The variance decomposition displayed that the overall inflation volatility is more pronounced with the fixed exchange rate regime for most of the shocks except for the productivity and the interest rate. The output volatility is also higher with this regime with the majority of the shocks exempting the foreign interest rate and the interest rate shocks.

Keywords: DSGE-VAR modeling, exchange rate, monetary policy, Bayesian estimation

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Authors: Hediyeh Talebi, Shokoofeh Ghiam, Changiz Eslahchi

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Traditionally, Alzheimer’s disease research has focused on genes with significant fold changes, potentially neglecting subtle but biologically important alterations. Our study introduces an integrative approach that highlights genes crucial to underlying biological processes, regardless of their fold change magnitude. Alzheimer's Single-cell RNA-seq data related to the peripheral blood mononuclear cells (PBMC) was extracted from the Gene Expression Omnibus (GEO). After quality control, normalization, scaling, batch effect correction, and clustering, differentially expressed genes (DEGs) were identified with adjusted p-values less than 0.05. These DEGs were categorized based on cell-type, resulting in four datasets, each corresponding to a distinct cell type. To distinguish between cells from healthy individuals and those with Alzheimer's, an adversarial autoencoder with a classifier was employed. This allowed for the separation of healthy and diseased samples. To identify the most influential genes in this classification, the weight matrices in the network, which includes the encoder and classifier components, were multiplied, and focused on the top 20 genes. The analysis revealed that while some of these genes exhibit a high fold change, others do not. These genes, which may be overlooked by previous methods due to their low fold change, were shown to be significant in our study. The findings highlight the critical role of genes with subtle alterations in diagnosing Alzheimer's disease, a facet frequently overlooked by conventional methods. These genes demonstrate remarkable discriminatory power, underscoring the need to integrate biological relevance with statistical measures in gene prioritization. This integrative approach enhances our understanding of the molecular mechanisms in Alzheimer’s disease and provides a promising direction for identifying potential therapeutic targets.

Keywords: alzheimer's disease, single-cell RNA-seq, neural networks, blood biomarkers

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Authors: Yu-Wen Huang, Yi-Cheng Chiang

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With urban development, lots of buildings are built around the city. The buildings always affect the urban wind environment. The accelerative situation of wind caused of buildings often makes pedestrians uncomfortable, even causes the accidents and dangers. Factors influencing pedestrian level wind including atmospheric boundary layer, wind direction, wind velocity, planting, building volume, geometric shape of the buildings and adjacent interference effects, etc. Planting has many functions including scraping and slowing urban heat island effect, creating a good visual landscape, increasing urban green area and improve pedestrian level wind. On the other hand, urban square is an important space element supporting the entrance to buildings, city landmarks, and activity collections, etc. The appropriateness of urban square environment usually dominates its success. This research focuses on the effect of tree-planting on the wind environment of urban square. This research studied the square belt of Taichung City Hall. Taichung City Hall is a cuboid building with a large mass opening. The square belt connects the front square, the central opening and the back square. There is often wind draft on the square belt. This phenomenon decreases the activities on the squares. This research applies tree-planting to improve the wind environment and evaluate the effects of two types of planting configuration. The Computational Fluid Dynamics (CFD) simulation analysis and extensive field measurements are applied to explore the improve efficiency of planting configuration on wind environment. This research compares efficiencies of different kinds of planting configuration, including the clustering array configuration and the dispersion, and evaluates the efficiencies by the SET*.

Keywords: micro-climate, wind environment, planting configuration, comfortableness, computational fluid dynamics (CFD)

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Authors: C. Iraklis, G. Evmiridis, A. Iraklis

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Renewable energy sources and distributed power generation units already have an important role in electrical power generation. A mixture of different technologies penetrating the electrical grid, adds complexity in the management of distribution networks. High penetration of distributed power generation units creates node over-voltages, huge power losses, unreliable power management, reverse power flow and congestion. This paper presents an optimization algorithm capable of reducing congestion and power losses, both described as a function of weighted sum. Two factors that describe congestion are being proposed. An upgraded selective particle swarm optimization algorithm (SPSO) is used as a solution tool focusing on the technique of network reconfiguration. The upgraded SPSO algorithm is achieved with the addition of a heuristic algorithm specializing in reduction of power losses, with several scenarios being tested. Results show significant improvement in minimization of losses and congestion while achieving very small calculation times.

Keywords: congestion, distribution networks, loss reduction, particle swarm optimization, smart grid

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Authors: A. C. Obosi, H. O. Osinowo, L. I. Okeke

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Benign prostatic hyperplasia (BPH) is one among other prostate diseases with an increasing public health concern. The prevalence and increased psychological distress of BPH among men negatively impact on their health-related quality of life (HRQoL). Although several biomedical factors have been implicated in poor HRQoL among people with BPH, there is a dearth of research on the psychosocial factors predicting HRQoL among them especially in developing climes. This study, therefore, examined the psychosocial (knowledge, perceived stigma, depression, anxiety, perceived social support and illness acceptance) predictors of health-related quality of life among persons living with BPH in Ibadan, Nigeria. Biopsychosocial model and Health-related Quality of life guided this study which utilized ex-post facto design. Eighty-seven males living with BPH were purposively selected and actively participated in the study. Participants’ mean age was 61.77 ± 15.80 years. A standardized questionnaire comprising Socio-demographics and measures of health-related quality of life (α = 0.47); knowledge (α = 0.72); psychological distress (α = 0.95); perceived social support (α = 0.96) and Illness acceptance (α = 0.89) scales was utilized in the study. Data were content analysed, while bivariate correlation, hierarchical multiple regression and t-test for independent samples were computed at p < 0.05. Results revealed that 42.5% of the respondents reported poor HRQoL. Furthermore, age, length of illness, perceived stigma, depression, anxiety, knowledge, perceived social support and illness acceptance jointly predicted HRQoL significantly (R2=0.33, F(9,75)=4.05) and accounted for 33% variance in the total observed variance on HRQoL, while Illness acceptance (β=0.43), anxiety (β=-0.54), and perceived social support (β=0.16) had significant independent contributions to the observed variance on HRQoL. Illness acceptance, knowledge, perceived social support and psychological distress such as anxiety, depression and perceived stigma are important predictors of HRQoL. Therefore, it was recommended that urgent psychological intervention targeted at improving the quality of life of these persons be undertaken.

Keywords: benign prostatic hyperplasia, Health-related quality of life, prostate disorders, psychosocial factors

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Authors: Diogo José Morgado Rebelo, Francisco António Carneiro Pacheco de Andrade, Paulo Jorge Freitas de Oliveira Novais

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Not everything in AI-power consumer credit scoring turns out to be a wonder. When using AI in Creditworthiness Assessment (CWA), opacity and unfairness ‘sins’ must be considered to the task be deemed Responsible. AI software is not always 100% accurate, which can lead to misclassification. Discrimination of some groups can be exponentiated. A hetero personalized identity can be imposed on the individual(s) affected. Also, autonomous CWA sometimes lacks transparency when using black box models. However, for this intended purpose, human analysts ‘on-the-loop’ might not be the best remedy consumers are looking for in credit. This study seeks to explore the legality of implementing a Multi-Agent System (MAS) framework in consumer CWA to ensure compliance with the regulation outlined in Article 14(4) of the Proposal for an Artificial Intelligence Act (AIA), dated 21 April 2021 (as per the last corrigendum by the European Parliament on 19 April 2024), Especially with the adoption of Art. 18(8)(9) of the EU Directive 2023/2225, of 18 October, which will go into effect on 20 November 2026, there should be more emphasis on the need for hybrid oversight in AI-driven scoring to ensure fairness and transparency. In fact, the range of EU regulations on AI-based consumer credit will soon impact the AI lending industry locally and globally, as shown by the broad territorial scope of AIA’s Art. 2. Consequently, engineering the law of consumer’s CWA is imperative. Generally, the proposed MAS framework consists of several layers arranged in a specific sequence, as follows: firstly, the Data Layer gathers legitimate predictor sets from traditional sources; then, the Decision Support System Layer, whose Neural Network model is trained using k-fold Cross Validation, provides recommendations based on the feeder data; the eXplainability (XAI) multi-structure comprises Three-Step-Agents; and, lastly, the Oversight Layer has a 'Bottom Stop' for analysts to intervene in a timely manner. From the analysis, one can assure a vital component of this software is the XAY layer. It appears as a transparent curtain covering the AI’s decision-making process, enabling comprehension, reflection, and further feasible oversight. Local Interpretable Model-agnostic Explanations (LIME) might act as a pillar by offering counterfactual insights. SHapley Additive exPlanation (SHAP), another agent in the XAI layer, could address potential discrimination issues, identifying the contribution of each feature to the prediction. Alternatively, for thin or no file consumers, the Suggestion Agent can promote financial inclusion. It uses lawful alternative sources such as the share of wallet, among others, to search for more advantageous solutions to incomplete evaluation appraisals based on genetic programming. Overall, this research aspires to bring the concept of Machine-Centered Anthropocentrism to the table of EU policymaking. It acknowledges that, when put into service, credit analysts no longer exert full control over the data-driven entities programmers have given ‘birth’ to. With similar explanatory agents under supervision, AI itself can become self-accountable, prioritizing human concerns and values. AI decisions should not be vilified inherently. The issue lies in how they are integrated into decision-making and whether they align with non-discrimination principles and transparency rules.

Keywords: creditworthiness assessment, hybrid oversight, machine-centered anthropocentrism, EU policymaking

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Authors: Shivam Dwivedi, Sumit Prakash Gupta, Durga Toshniwal

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It is a challenging task in today’s date to keep defence forces in the highest state of combat readiness with budgetary constraints. A huge amount of time and money is squandered in the unnecessary and expensive traditional maintenance activities. To overcome this limitation Defence Intelligent Mission Readiness and Maintenance Scheduling System has been proposed, which ameliorates the maintenance system by diagnosing the condition and predicting the maintenance requirements. Based on new data mining algorithms, this system intelligently optimises mission readiness for imminent operations and maintenance scheduling in repair echelons. With modified data mining algorithms such as Weighted Feature Ranking Genetic Algorithm and SVM-Random Forest Linear ensemble, it improves the reliability, availability and safety, alongside reducing maintenance cost and Equipment Out of Action (EOA) time. The results clearly conclude that the introduced algorithms have an edge over the conventional data mining algorithms. The system utilizing the intelligent condition-based maintenance approach improves the operational and maintenance decision strategy of the defence force.

Keywords: condition based maintenance, data mining, defence maintenance, ensemble, genetic algorithms, maintenance scheduling, mission capability

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Authors: César M. Moreira, Marco A. Pazmiño-Hernández, Marco A. Pazmiño-Barreno, Kyle Griffin, Pratap Pullammanappallil

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An anaerobic digestion system that was completely operated on solar power (both photovoltaic and solar thermal energy), and mounted on a trailer to make it mobile, was designed and constructed. A 55-gallon batch digester was placed within a chamber that was heated by hot water pumped through a radiator. Hot water was produced by a solar thermal collector and photovoltaic panels charged a battery which operated pumps for recirculating water. It was found that the temperature in the heating chamber was maintained above ambient temperature but it follows the same trend as ambient temperature. The temperature difference between the chamber and ambient values was not constant but varied with time of day. Advantageously, the temperature difference was highest during night and early morning and lowest near noon. In winter, when ambient temperature dipped to 2 °C during early morning hours, the chamber temperature did not drop below 10 °C. Model simulations showed that even if the digester is subjected to diurnal variations of temperature (as observed in winter of a subtropical region), about 63 % of the waste that would have been processed under constant digester temperature of 38 °C, can still be processed. The cost of the digester system without the trailer was $1,800.

Keywords: anaerobic digestion, solar-mobile, rural communities, solar, hybrid

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Authors: Theddeus Tochukwu Akano, Omotayo Abayomi Fakinlede

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Proper understanding of the behavior of compliant mechanisms use by athletes is important in order to avoid catastrophic failure. Such compliant mechanisms like the flex-run require the knowledge of their dynamic response and deformation behavior under quickly varying loads. The modeling of finite deformations of the compliant athletic system is described by Neo-Hookean model under contact-impact conditions. The dynamic impact-contact governing equations for both the target and impactor are derived based on the updated Lagrangian approach. A method where contactor and target are considered as a united body is applied in the formulation of the principle of virtual work for the bodies. In this paper, methods of continuum mechanics and nonlinear finite element method were deployed to develop a model that could capture the behavior of the compliant athletic system under quickly varying loads. A hybrid system of symbolic algebra (AceGEN) and a compiled back end (AceFEM) were employed, leveraging both ease of use and computational efficiency. The simulated results reveal the effect of the various contact-impact conditions on the deformation behavior of the impacting compliant mechanism.

Keywords: eigenvalue problems, finite element method, robin boundary condition, sturm-liouville problem

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Authors: Ikediobi Lottanna Samuel

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Days are gone when perpetrators of core international crimes hide under the cloak of sovereignty to go with impunity. The principle of international criminal responsibility is a reality. This move to end impunity for violation of human rights has led to the creation of international and hybrid tribunals, a permanent international criminal court, and increased prosecution of human rights violations in domestic courts. This article examines the attempts by the international community to bring perpetrators of heinous crimes to book. The work reveals the inadequacy of the current international mechanism for prosecuting core international crimes in order to end the culture of impunity and entrench the culture of accountability. It also identifies that ad hoc international criminal tribunals and the international criminal court face similar challenges ranging from lack of cooperation by nation states, non-existence of hierarchy of crimes, lack of effective enforcement mechanism, limited prosecutorial capacity and agenda, difficulty in apprehending suspects, difficulty in blending different legal tradition, absence of a coherent sentencing guideline, distant location of courts, selective indictment, etc. These challenges adversely affect the functioning of these courts. It is suggested that a more helpful way to end impunity would be to have a more robust and synergistic relationship between national, regional, and international approaches to prosecuting core international crimes.

Keywords: prosecution, criminal, international, tribunal, justice, ad hoc

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Authors: Jonix Owino

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Aging Out of Place refers to the physical and emotional experience of growing older in a foreign or unfamiliar environment. Refugees flee their home countries and migrate to foreign countries such as the United States for safety. The emotional and psychological distress experienced by refugees who are compelled to leave their home countries can compromise their ability to adapt to new countries, thereby affecting their well-being. In particular, implications of immigration may be felt more acutely in later life stages, especially when life-long attachments have been made in the country of origin. However, aging studies in the United States have failed to conceptualize refugee aging experiences, more so for refugees who entered the country as adults. Specifically, little is known about the quality of life among aging refugees. Research studies on whether the quality of life varies among refugees by sociodemographic factors are limited. Research studies examining the role of social connectedness in aging refugees’ quality of life are also sparse. As such, the present study seeks to investigate the sociodemographic (i.e., age, sex, country of origin, and length of residence) and social connection factors associated with quality of life among aging refugees. The study consisted of a total of 108 participants from ages 50 years and above. The refugees represented in the study were from Bhutan, Burundi, and Somalia and were recruited from an upper Midwestern region of the United States. The participants completed an in-depth survey assessing social factors and well-being. Hierarchical regression was used for analysis. The results showed that females, older individuals, and refugees who were from Africa reported lower quality of life. Length of residence was not associated with quality of life. Furthermore, when controlling for sociodemographic factors, greater social integration was significantly associated with a higher quality of life, whereas lower loneliness was significantly associated with a higher quality of life. The results also indicated a significant interaction between loneliness and sex in predicting quality of life. This suggests that greater loneliness was associated with reduced quality of life for female refugees but not males. The present study highlights cultural variations within refugee groups which is important in determining how host communities can best support aging refugees’ well-being and develop social programs that can effectively cater to issues of aging among refugees.

Keywords: aging refugees, quality of life, social integration, migration and integration

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Authors: José Luis Gallizo, Pilar Gargallo, Ramon Saladrigues, Manuel Salvador

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This study offers an exploratory statistical analysis of the persistence of annual profits across a sample of firms from different European Union (EU) countries. To this end, a hierarchical Bayesian dynamic model has been used which enables the annual behaviour of those profits to be broken down into a permanent structural and a transitory component, while also distinguishing between general effects affecting the industry as a whole to which each firm belongs and specific effects affecting each firm in particular. This breakdown enables the relative importance of those fundamental components to be more accurately evaluated by country and sector. Furthermore, Bayesian approach allows for testing different hypotheses about the homogeneity of the behaviour of the above components with respect to the sector and the country where the firm develops its activity. The data analysed come from a sample of 23,293 firms in EU countries selected from the AMADEUS data-base. The period analysed ran from 1999 to 2007 and 21 sectors were analysed, chosen in such a way that there was a sufficiently large number of firms in each country sector combination for the industry effects to be estimated accurately enough for meaningful comparisons to be made by sector and country. The analysis has been conducted by sector and by country from a Bayesian perspective, thus making the study more flexible and realistic since the estimates obtained do not depend on asymptotic results. In general terms, the study finds that, although the industry effects are significant, more important are the firm specific effects. That importance varies depending on the sector or the country in which the firm carries out its activity. The influence of firm effects accounts for around 81% of total variation and display a significantly lower degree of persistence, with adjustment speeds oscillating around 34%. However, this pattern is not homogeneous but depends on the sector and country analysed. Industry effects depends also on sector and country analysed have a more marginal importance, being significantly more persistent, with adjustment speeds oscillating around 7-8% with this degree of persistence being very similar for most of sectors and countries analysed.

Keywords: dynamic models, Bayesian inference, MCMC, abnormal returns, persistence of profits, return on assets

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Authors: Freddy Munzhelele

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Setting: the empirical research has shown that the life cycle theory has an impact on the firms’ financing decisions, particularly the dividend pay-outs. Accordingly, the life cycle theory posits that as a firm matures, it gets to a level and capacity where it distributes more cash as dividends. On the other hand, the young firms prioritise investment opportunities sets and their financing; thus, they pay little or no dividends. The research on firms’ financing decisions also demonstrated, among others, the adoption of trade-off and pecking order theories on the dynamics of firms capital structure. The trade-off theory talks to firms holding a favourable position regarding debt structures particularly as to the cost and benefits thereof; and pecking order is concerned with firms preferring a hierarchical order as to choosing financing sources. The case of life cycle hypothesis explaining the financial managers’ decisions as regards the firms’ capital structure dynamics appears to be an interesting link, yet this link has been neglected in corporate finance research. If this link is to be explored as an empirical research, the financial decision-making alternatives will be enhanced immensely, since no conclusive evidence has been found yet as to the dynamics of capital structure. Aim: the aim of this study is to examine the impact of life cycle theory on the capital structure dynamics trade-off and pecking order theories of firms listed in retail, industrial and mining sectors of the JSE. These sectors are among the key contributors to the GDP in the South African economy. Design and methodology: following the postpositivist research paradigm, the study is quantitative in nature and utilises secondary data obtainable from the financial statements of sampled firm for the period 2010 – 2022. The firms’ financial statements will be extracted from the IRESS database. Since the data will be in panel form, a combination of the static and dynamic panel data estimators will used to analyse data. The overall data analyses will be done using STATA program. Value add: this study directly investigates the link between the life cycle theory and the dynamics of capital structure decisions, particularly the trade-off and pecking order theories.

Keywords: life cycle theory, trade-off theory, pecking order theory, capital structure, JSE listed firms

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Authors: Dalhat Binta Dan - Ali

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The reality of the new world economic order and the ever increasing importance of biotechnology in the global economy have necessitated the ratification of the Cartagena Protocol on Biosafety and the recent promulgation of Biosafety Act in Nigeria 2015. The legal regimes are anchored on the need to create an enabling environment for the flourishing of bio-trade and also to ensure the safety of the environment and human health. This paper critically examines the legal framework on biosafety by taking a cursory look at its philosophical foundation, key issues and milestones. The paper argues that the extant laws, though a giant leap in the establishment of a legal framework on biosafety, it posits that the legal framework raises debate and controversy on the difficulties of risk assessment on biodiversity and human health, other challenges includes lack of sound institutional capacity and the regimes direction of a hybrid approach between environmental conservation and trade issues. The paper recommend the need for the country to do more in the area of stimulating awareness and establishment of a sound institutional capacity to enable the law ensure adequate level of protection in the field of safe transfer, handling, and use of genetically modified organisms (GMOs) in Nigeria.

Keywords: Cartagena protocol, biosafety, issues, challenges, biotrade, genetically modified organism (GMOs), environment

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Authors: Arifa Batool, Ghulam Hussain Bhatti, Syed Mujtaba Shah

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Inorganic n-type (TiO2, CdO) and p-type (NiO, CuO) metal oxide nanoparticles were synthesized by a facile wet chemical method at room temperature. The morphological, compositional, structural and optical properties were investigated by scanning electron microscopy, energy dispersive X-ray spectroscopy, FT-IR, XRD analysis, UV/Visible and fluorescence spectroscopy. All semiconducting nanoparticles were photosensitized with Ru (II) based Z907 dye in ethanol solvent by grafting. Grafting of dye on the surface of nanoparticles was confirmed by UV/Visible and FT-IR spectroscopy. The synthesized photo-active nanohybrid was thoroughly blended with P3HT, a solid electrolyte and I-V measurements under solar stimulated radiations 1000 W/m2 (AM 1.5) were recorded. Maximum incident photon to current conversion efficiency (IPCE) of 0.9% was achieved with dye functionalized Z907-TiO2 hybrid, IPCE of 0.72% was achieved with bulk-heterojunction of TiO2-Z907-CuO and IPCE of 0.68% was attained with nanocomposite of TiO2-CdO. TiO2 based Solar cells have maximum Jscvalue i.e.4.63 mA/cm2. Dye-functionalized TiO2-based photovoltaic devices were found more efficient than the reference device but the morphology of the device was a major check in progress.

Keywords: solar cell, bulk heterojunction, nanocomposites, photosensitization, dye sensitized solar cell

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Authors: Ali Kadivar, Kaveh Niayesh

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MVDC markets for green power generations, Navy, subsea oil and gas electrification, and transportation electrification are extending rapidly. The lack of fast and powerful DC circuit breakers (CB) is the most significant barrier to realizing the medium voltage DC (MVDC) networks. A concept of hybrid circuit breakers (HCBs) benefiting from ultrafast disconnectors (UFD) is proposed. A set of mechanical switches substitute the power electronic commutation switches to reduce the losses during normal operation in HCB. The success of current commutation in such breakers relies on the behaviour of elongated, wall constricted arcs during the opening across the contacts inside the UFD. The arc voltage dependencies on the contact speed of UFDs is discussed through multiphysics simulations contact opening speeds of 10, 20 and 40 m/s. The arc voltage at a given current increases exponentially with the contact opening velocity. An empirical equation for the dynamic arc characteristics is presented for the tested UFD, and the experimentally verfied characteristics for voltage-current are utilized for the current commutation simulation prior to apply on a 14 kV experimental setup. Different failures scenarios due to the current commutation are investigated

Keywords: MVDC breakers, DC circuit breaker, fast operating breaker, ultra-fast elongated arc

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Authors: N. Casado-Sanz, B. Guirao

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The population aged 65 and over is projected to double in the coming decades. Due to this increase, driver population is expected to grow and in the near future, all countries will be faced with population aging of varying intensity and in unique time frames. This is the greatest challenge facing industrialized nations and due to this fact, the study of the relationships of dependency between population aging and road safety is becoming increasingly relevant. Although the deterioration of driving skills in the elderly has been analyzed in depth, to our knowledge few research studies have focused on the road infrastructure and the mobility of this particular group of users. In Spain, crosstown roads have one of the highest fatality rates. These rural routes have a higher percentage of elderly people who are more dependent on driving due to the absence or limitations of urban public transportation. Analysing road safety in these routes is very complex because of the variety of the features, the dispersion of the data and the complete lack of related literature. The objective of this paper is to identify key factors that cause traffic accidents. The individuals under study were the accidents with killed or seriously injured in Spanish crosstown roads during the period 2006-2015. Latent cluster analysis was applied as a preliminary tool for segmentation of accidents, considering population aging as the main input among other socioeconomic indicators. Subsequently, a linear regression analysis was carried out to estimate the degree of dependence between the accident rate and the variables that define each group. The results show that segmenting the data is very interesting and provides further information. Additionally, the results revealed the clear influence of the aging variable in the clusters obtained. Other variables related to infrastructure and mobility levels, such as the crosstown roads layout and the traffic intensity aimed to be one of the key factors in the causality of road accidents.

Keywords: cluster analysis, population ageing, rural roads, road safety

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Authors: John Faucett, Hao Wu, Bruce Moore, Sean Nadji

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The demands of the ministry often conflict with responsibilities at home, and clergy often experience domain ambiguity between the domains of work and family. However, the unique level of family involvement in the pastor’s profession might enrich the pastor’s ministry as well as the functioning of the family unit. Life in the church family might offer clergy family members a sense of meaning and purpose, social support, and a feeling of belonging. Church activities can offer enhanced opportunities for family interaction. The purpose of this study was to investigate the relationships of work/family enrichment to clergy job satisfaction, burnout, engagement, and withdrawal. Method: Participants were clergy serving within a state conference of the United Methodist Church. A survey was administered electronically, with e-mails and the United Methodist Church (UMC) Facebook page used as access points to the survey. Usable responses for this portion of the survey were obtained from 132 clergy. Participants completed The Work-Family Enrichment Scales, The Utrecht Work Engagement Scale, The Scale of Emotional Exhaustion in Ministry, The Satisfaction in Ministry Scale, and a scale of withdrawal developed for the present study. They also answered questions relating to how involved their spouses are in their ministry and the degree to which spouse involvement in church ministry strengthens church ministry. Findings: Higher scores for work to family enrichment correlated positively with job satisfaction (r = - .69, p < .01) and engagement (r = .50, p < .01), and negatively with burnout (r = -.48, p < .01) and withdrawal (r = -.46, p < .01). Higher scores for family to work enrichment correlated positively with job satisfaction (r = .29, p = .01) and engagement (.24, p < .05), and negatively with burnout (r = -.48, p < .01), and withdrawal (r = -.46, p < .01). Hierarchical regression analysis suggested that clergy perceptions concerning the degree to which spouse involvement in church ministry strengthens church ministry moderates the relationship between degree of spouse involvement in church activities and clergy withdrawal. To the degree that spouse involvement is believed to strengthen ministry, high spouse involvement is related to less clergy withdrawal (Multiple R-Squared = .068, Adj. R-Squared = .043, F = 2.69 on 3 & 110 DF, p = .05). Concluding Statement: Clergy job attitudes are related to work/family enrichment. Spouse involvement in parish ministry is associated with less clergy withdrawal, as long as clergy believe spouse involvement strengthens their ministry.

Keywords: clergy, emotional exhaustion, job engagement, job satisfaction, work/family enrichment

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