Search results for: Privacy and Data Protection Law

Authors: Mustafa Mabruk

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Groups such as Al-Shabaab have managed to radicalize many individuals abroad, including the first American citizen to ever be radicalized. Yet the pathways of radicalization for these foreign individuals are understudied. Moreover, current measures to prevent foreign radicalization are ineffective, with privacy, screening and profiling implications that render current counter-radicalization efforts counterproductive. Such measures exhibit strictness, political bias, and harshness. As confirmed by recent studies, such counter-radicalization issues exacerbate existing grievances and channel fresh recruits to Al-Shabaab. Addressing these challenges is paramount, requiring alternative strategies to effectively reduce radicalization without triggering further harm. The development of counter-narratives emerges as a potential measure with minimal risk of exacerbating grievances, yet the development of such counter-narratives necessitates a thorough understanding of the radicalization pathways of foreign individuals that are understudied. This study investigates the success of Al-Shabaab in recruiting individuals abroad by analyzing their propaganda in conjunction with analyzing identity-focused theories of radicalization, including Framing Theory and Social Identity Theory. Qualitative content analysis is used to analyze various propaganda material, including tweets, speeches, and webpages. The analysis reveals that issues of identity are of major significance in the radicalization patterns identified and that grievances of Muslims worldwide are used to exploit identity-related grievances. Based on these findings, the paper argues that such evidence enhances our understanding of potential deradicalization pathways and present counter-narratives based on Islamic scripture.

Keywords: counter-narratives, foreign radicalization, identity grievances, propaganda analysis

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Authors: Rana Rimawi, Ayman Baklizi

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Skewed distributions are important models that are frequently used in applications. Generalized distributions form a class of skewed distributions and gain widespread use in applications because of their flexibility in data analysis. More specifically, the Generalized Logistic Distribution with its different types has received considerable attention recently. In this study, based on progressively type-II censored data, we will consider point estimation in type II Generalized Logistic Distribution (Type II GLD). We will develop several estimators for its unknown parameters, including maximum likelihood estimators (MLE), Bayes estimators and linear estimators (BLUE). The estimators will be compared using simulation based on the criteria of bias and Mean square error (MSE). An illustrative example of a real data set will be given.

Keywords: point estimation, type II generalized logistic distribution, progressive censoring, maximum likelihood estimation

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Authors: Emanuele A. Solagna, Ricardo S, Tozetto, Roberto dos S. Rabello

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Nowadays, physical processes are becoming digitized by the evolution of communication, sensing and storage technologies which promote the development of smart cities. The evolution of this technology has generated multiple challenges related to the generation of big data and the active participation of electronic devices in society. Thus, devices can send information that is captured and processed over large areas, but there is no guarantee that all the obtained data amount will be effectively stored and correctly persisted. Because, depending on the technology which is used, there are parameters that has huge influence on the full delivery of information. This article aims to characterize the project, currently under development, of a platform that based on data science will perform a performance and effectiveness evaluation of an industrial network that implements LoRaWAN technology considering its main parameters configuration relating these parameters to the information loss.

Keywords: Internet of Things, LoRa, LoRaWAN, smart cities

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Authors: Rebecca Johnson, Elizabeth Hoban

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Condom use among young men in Cambodia has declined between 2005 and 2014 which has public health implications such as increased risks of sexually transmitted infections, including HIV, and unplanned pregnancies. Conversations about sexual and reproductive health issues, including condom use, are not socially sanctioned in Cambodian society leaving young adults with limited knowledge of, and poor access to sexual and reproductive health services. Additionally, men play a dominant role in decision making regarding condom use within sexual partnerships. This study sought to fill a gap in knowledge by exploring young adult males’ attitudes, perceptions and behaviours regarding condom use. In February and March 2018, twenty young adult males, aged 18 to 24 years, were recruited from urban, peri urban and rural areas in Cambodia. The young adult males participated in a face-to-face semi structured interview that used an interview guide and photo elicitation method. The interview explored participants’ knowledge of sexual and reproductive health issues and efficacy, sexual behaviours, and use of condoms. Inductive thematic analysis was conducted and the following major themes emerged: understanding of reproduction, understanding of sexually transmitted infections, knowledge about condoms, condom use, access to condoms, and sexual behaviour. Participants’ knowledge of condoms and specific reasons for their use varied; most participants understood that condoms provide protection from sexually transmitted infections and prevent pregnancy. Stigma associated with condom access was consistently referred to as a problem and the main reason cited by young men for not using condoms during sexual intercourse. The perceived importance of condom use altered with partner type and relationship status, dependent upon the need for protection from sexually transmitted infections or pregnancy. Condoms were used for infection control in the context of multiple relationships, or as a contraceptive method for unmarried and some married couples. The majority of young men engaged in premarital sexual intercourse, of those men the many used condoms. The inconsistent use of condoms by young men in Cambodia is of public health concern because of the increased risk of sexually transmitted infections (including HIV), and unplanned pregnancy. Public health action is required in order to minimize long term health issues for individuals and the community. Health education is required to increase knowledge of condom use, sexually transmitted infections and HIV, and reduce the stigma associated with this topic. Sustainable health promotion programs are needed to increase ease of access to condoms for young people. Public health policy in Cambodia needs to be reviewed to improve sexual and reproductive health outcomes for young adults.

Keywords: Cambodia, condom use, sexual and reproductive health, young adult males

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Authors: Zhihong Luo, Guangbin Zhu, Lulu Guo, Zhujun Lyu, Kun Luo

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Cycling life has become the threshold for the prospective application of Li-O₂ batteries, and the protection of Li anode has recently regarded as the key factor to the performance. Herein, a simple low rate pre-activation (20 cycles at 0.5 Ag⁻¹ and a capacity of 200 mAh g⁻¹) was employed to effectively improve the performance and cyclability of Li-O₂ batteries. The charge/discharge cycles at 1 A g⁻¹ with a capacity of 1000 mAh g⁻¹ were maintained for up to 290 times versus 55 times for the cell without pre-activation. The ultimate battery capacity and high rate discharge property were also largely enhanced. Morphology, XRD and XPS analyses reveal that the performance improvement is in close association with the formation of the smooth and compact surface layer formed on the Li anode after low rate pre-activation, which apparently alleviated the corrosion of Li anode and the passivation of cathode during battery cycling, and the corresponding mechanism was also discussed.

Keywords: lithium oxygen battery, pre-activation, cyclability, capacity

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Authors: Yung-Chung Chuang

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The cultural layers of archaeological sites are mainly affected by surface land use, land cover, and root system of surface vegetation. For this reason, continuous monitoring of land use and land cover change is important for archaeological sites protection and management. However, in actual operation, on-site investigation and orthogonal photograph interpretation require a lot of time and manpower. For this reason, it is necessary to perform a good alternative for surface vegetation survey in an automated or semi-automated manner. In this study, we applied semi-automatic digital aerial survey technology and canopy characters classification with very high-resolution aerial photographs for surface vegetation interpretation of archaeological sites. The main idea is based on different landscape or forest type can easily be distinguished with canopy characters (e.g., specific texture distribution, shadow effects and gap characters) extracted by semi-automatic image classification. A novel methodology to classify the shape of canopy characters using landscape indices and multivariate statistics was also proposed. Non-hierarchical cluster analysis was used to assess the optimal number of canopy character clusters and canonical discriminant analysis was used to generate the discriminant functions for canopy character classification (seven categories). Therefore, people could easily predict the forest type and vegetation land cover by corresponding to the specific canopy character category. The results showed that the semi-automatic classification could effectively extract the canopy characters of forest and vegetation land cover. As for forest type and vegetation type prediction, the average prediction accuracy reached 80.3%~91.7% with different sizes of test frame. It represented this technology is useful for archaeological site survey, and can improve the classification efficiency and data update rate.

Keywords: digital aerial survey, canopy characters classification, archaeological sites, multivariate statistics

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Authors: Rezky Rifaini, Raden Bagus Fajriya Hakim

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This research was conducted at the Bolo primary health Care in Bima Regency. The purpose of the research is to find out the association pattern that is formed of medical record database from Bolo Primary health care’s patient. The data used is secondary data from medical records database PHC. Sequential pattern mining technique is the method that used to analysis. Transaction data generated from Patient_ID, Check_Date and diagnosis. Sequential Pattern Discovery Algorithms Using Equivalent Classes (SPADE) is one of the algorithm in sequential pattern mining, this algorithm find frequent sequences of data transaction, using vertical database and sequence join process. Results of the SPADE algorithm is frequent sequences that then used to form a rule. It technique is used to find the association pattern between items combination. Based on association rules sequential analysis with SPADE algorithm for minimum support 0,03 and minimum confidence 0,75 is gotten 3 association sequential pattern based on the sequence of patient_ID, check_Date and diagnosis data in the Bolo PHC.

Keywords: diagnosis, primary health care, medical record, data mining, sequential pattern mining, SPADE algorithm

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Authors: Aziez Ouahiba, Remini Boualem, Habi Mohamed

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The growth and the development of a pay are strongly related to the existence or the absence of water in this area, the sedentary lifestyle of the population makes that water demand is increasing and the different brandishing (dams, tablecloths or other) are increasingly solicited. In normal time rain and snow of the winter period reloads the slicks and the wadis that fill dams. Over these two decades, Global warming fact that temperature is increasingly high and rainfall is increasingly low, which induces a charge less and less important tablecloths, add to that the strong demand in irrigation. Our study will focus on the variation of rainfall and irrigation, Their effects on the degree of pollution of the groundwater in this area based on statistical analyses by the Xlstat (ACP, correlation...) software for a better explanation of these results and determine the hydrochemistry of different groups or polluted areas pou be able to offer adequate solutions for each area.

Keywords: water in the basement, legislation, over exploitation, pollution, water prices

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Authors: Reda Abdel Azim, Tariq Shehab

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The main objective of this study is to develop a subsurface fracture map of naturally fractured reservoirs by overcoming the limitations associated with different data sources in characterising fracture properties. Some of these limitations are overcome by employing a nested neuro-stochastic technique to establish inter-relationship between different data, as conventional well logs, borehole images (FMI), core description, seismic attributes, and etc. and then characterise fracture properties in terms of fracture density and fractal dimension for each data source. Fracture density is an important property of a system of fracture network as it is a measure of the cumulative area of all the fractures in a unit volume of a fracture network system and Fractal dimension is also used to characterize self-similar objects such as fractures. At the wellbore locations, fracture density and fractal dimension can only be estimated for limited sections where FMI data are available. Therefore, artificial intelligence technique is applied to approximate the quantities at locations along the wellbore, where the hard data is not available. It should be noted that Artificial intelligence techniques have proven their effectiveness in this domain of applications.

Keywords: naturally fractured reservoirs, artificial intelligence, fracture intensity, fractal dimension

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Authors: Yukinori Fuse, Masato Kawaguchi

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A quantitative risk assessment method was developed for fiber emissions from sprayed asbestos-containing materials (ACMs). In Japan, instead of being quantitative, these risk assessments have relied on the subjective judgment of skilled engineers, which may vary from one person to another. Therefore, this closed sampling method aims at avoiding any potential variability between assessments. This method was used to assess emissions from ACM sprayed in eleven buildings and the obtained results were compared with the subjective judgments of a skilled engineer. An approximate correlation tendency was found between both approaches. In spite of existing uncertainties, the closed sampling method is useful for public health protection. We firmly believe that this method may find application in the management and renovation decisions of buildings using friable and sprayed ACM.

Keywords: asbestos, renovation, risk assessment, maintenance

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Authors: E. Baltas, E. Feloni, G. Bariamis

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The operation of a network of hydrometeorological-hydrometric stations is basic infrastructure for the management of water resources, as well as, for flood protection. The assessment of water resources potential led to the necessity of adoption management practices including a multi-criteria analysis for the optimum design of the region’s station network. This research work aims at the optimisation of a new/existing network, using GIS methods. The planning of optimum network stations is based on the guidelines of international organizations such as World Meteorological Organization (WMO). The uniform spatial distribution of the stations, the drainage basin for the hydrometric stations and criteria concerning the low terrain slope, the accessibility to the stations and proximity to hydrological interest sites, were taken into consideration for its development. The abovementioned methodology has been implemented for two different areas the Florina municipality and the Argolis area in Greece, and comparison of the results has been conducted.

Keywords: GIS, hydrometeorological, hydrometric, network, optimisation

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Authors: U. Ali Rahoma, Nabil Esawy, Fawzia Ibrahim Moursy, A. H. Hassan, Samy A. Khalil, Ashraf S. Khamees

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The design of any solar energy conversion system requires the knowledge of solar radiation data obtained over a long period. Satellite data has been widely used to estimate solar energy where no ground observation of solar radiation is available, yet there are limitations on the temporal coverage of satellite data. Reanalysis is a “retrospective analysis” of the atmosphere parameters generated by assimilating observation data from various sources, including ground observation, satellites, ships, and aircraft observation with the output of NWP (Numerical Weather Prediction) models, to develop an exhaustive record of weather and climate parameters. The evaluation of the performance of reanalysis datasets (ERA-5) for North Africa against high-quality surface measured data was performed using statistical analysis. The estimation of global solar radiation (GSR) distribution over six different selected locations in North Africa during ten years from the period time 2011 to 2020. The root means square error (RMSE), mean bias error (MBE) and mean absolute error (MAE) of reanalysis data of solar radiation range from 0.079 to 0.222, 0.0145 to 0.198, and 0.055 to 0.178, respectively. The seasonal statistical analysis was performed to study seasonal variation of performance of datasets, which reveals the significant variation of errors in different seasons—the performance of the dataset changes by changing the temporal resolution of the data used for comparison. The monthly mean values of data show better performance, but the accuracy of data is compromised. The solar radiation data of ERA-5 is used for preliminary solar resource assessment and power estimation. The correlation coefficient (R2) varies from 0.93 to 99% for the different selected sites in North Africa in the present research. The goal of this research is to give a good representation for global solar radiation to help in solar energy application in all fields, and this can be done by using gridded data from European Centre for Medium-Range Weather Forecasts ECMWF and producing a new model to give a good result.

Keywords: solar energy, solar radiation, ERA-5, potential energy

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Authors: Cristina Diaz, Lucia Perez-Gandarillas, Gonzalo Garcia-Fuentes, Simone Visigalli, Roberto Canziani, Giuseppe Di Florio, Paolo Gronchi

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During their lifetime, industrial machines are often subjected to chemical, mechanical and thermal extreme conditions. In some cases, the loss of efficiency comes from the degradation of the surface as a result of its exposition to abrasive environments that can cause wear. This is a common problem to be solved in industries of diverse nature such as food, paper or concrete industries, among others. For this reason, a good selection of the material is of high importance. In the machine design context, stainless steels such as AISI 304 and 316 are widely used. However, the severity of the external conditions can require additional protection for the steel and sometimes coating solutions are demanded in order to extend the lifespan of these materials. Therefore, the development of effective coatings with high wear resistance is of utmost technological relevance. In this research, bilayer coatings made of Titanium-Tantalum, Titanium-Niobium, Titanium-Hafnium, and Titanium-Zirconium have been developed using magnetron sputtering configuration by PVD (Physical Vapor Deposition) technology. Their tribological behavior has been measured and evaluated under different environmental conditions. Two kinds of steels were used as substrates: AISI 304, AISI 316. For the comparison with these materials, titanium alloy substrate was also employed. Regarding the characterization, wear rate and friction coefficient were evaluated by a tribo-tester, using a pin-on-ball configuration with different lubricants such as tomato sauce, wine, olive oil, wet compost, a mix of sand and concrete with water and NaCl to approximate the results to real extreme conditions. In addition, topographical images of the wear tracks were obtained in order to get more insight of the wear behavior and scanning electron microscope (SEM) images were taken to evaluate the adhesion and quality of the coating. The characterization was completed with the measurement of nanoindentation hardness and elastic modulus. Concerning the results, thicknesses of the samples varied from 100 nm (Ti-Zr layer) to 1.4 µm (Ti-Hf layer) and SEM images confirmed that the addition of the Ti layer improved the adhesion of the coatings. Moreover, results have pointed out that these coatings have increased the wear resistance in comparison with the original substrates under environments of different severity. Furthermore, nanoindentation hardness results showed an improvement of the elastic strain to failure and a high modulus of elasticity (approximately 200 GPa). As a conclusion, Ti-Ta, Ti-Zr, Ti-Nb, and Ti-Hf are very promising and effective coatings in terms of tribological behavior, improving considerably the wear resistance and friction coefficient of typically used machine materials.

Keywords: coating, stainless steel, tribology, wear

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Authors: Fan Gao, Lior Pachter

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The primary tool currently used to pre-process 10X Chromium single-cell ATAC-seq data is Cell Ranger, which can take very long to run on standard datasets. To facilitate rapid pre-processing that enables reproducible workflows, we present a suite of tools called scATAK for pre-processing single-cell ATAC-seq data that is 15 to 18 times faster than Cell Ranger on mouse and human samples. Our tool can also calculate chromatin interaction potential matrices, and generate open chromatin signal and interaction traces for cell groups. We use scATAK tool to explore the chromatin regulatory landscape of a healthy adult human brain and unveil cell-type specific features, and show that it provides a convenient and computational efficient approach for pre-processing single-cell ATAC-seq data.

Keywords: single-cell, ATAC-seq, bioinformatics, open chromatin landscape, chromatin interactome

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Authors: Najibullah M, Soumendra Nath Kuiry

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Dams and reservoirs are perceived for their estimable alms to irrigation, water supply, flood control, electricity generation, etc. which civilize the prosperity and wealth of society across the world. Meantime the dam breach could cause devastating flood that can threat to the human lives and properties. Failures of large dams remain fortunately very seldom events. Nevertheless, a number of occurrences have been recorded in the world, corresponding in an average to one to two failures worldwide every year. Some of those accidents have caused catastrophic consequences. So it is decisive to predict the dam break flow for emergency planning and preparedness, as it poses high risk to life and property. To mitigate the adverse impact of dam break, modeling is necessary to gain a good understanding of the temporal and spatial evolution of the dam-break floods. This study will mainly deal with one-dimensional (1D) dam break modeling. Less commonly used in the hydraulic research community, another possible option for modeling the rapidly varied dam-break flows is the extended Boussinesq equations (BEs), which can describe the dynamics of short waves with a reasonable accuracy. Unlike the Shallow Water Equations (SWEs), the BEs taken into account the wave dispersion and non-hydrostatic pressure distribution. To capture the dam-break oscillations accurately it is very much needed of at least fourth-order accurate numerical scheme to discretize the third-order dispersion terms present in the extended BEs. The scope of this work is therefore to develop an 1D fourth-order accurate in both space and time Boussinesq model for dam-break flow analysis by using finite-volume / finite difference scheme. The spatial discretization of the flux and dispersion terms achieved through a combination of finite-volume and finite difference approximations. The flux term, was solved using a finite-volume discretization whereas the bed source and dispersion term, were discretized using centered finite-difference scheme. Time integration achieved in two stages, namely the third-order Adams Basforth predictor stage and the fourth-order Adams Moulton corrector stage. Implementation of the 1D Boussinesq model done using PYTHON 2.7.5. Evaluation of the performance of the developed model predicted as compared with the volume of fluid (VOF) based commercial model ANSYS-CFX. The developed model is used to analyze the risk of cascading dam failures similar to the Panshet dam failure in 1961 that took place in Pune, India. Nevertheless, this model can be used to predict wave overtopping accurately compared to shallow water models for designing coastal protection structures.

Keywords: Boussinesq equation, Coastal protection, Dam-break flow, One-dimensional model

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Authors: Z. Jovanovic, Z. Masonicic, S. Dragutinovic, Z. Sakota

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In this paper, a methodology for noise reduction of motor vehicles in use is presented. The methodology relies on synergic model of noise generation as a function of time. The arbitrary number of motor vehicle noise sources act in concert yielding the generation of the overall noise level of motor vehicle thereafter. The number of noise sources participating in the overall noise level of motor vehicle is subjected to the constraint of the calculation of the acoustic potential of each noise source under consideration. It is the prerequisite condition for the calculation of the acoustic potential of the whole vehicle. The recast form of pertinent set of equations describing the synergic model is laid down and solved by dint of Gauss method. The bunch of results emerged and some of them i.e. those ensuing from model application to MDD FAP Priboj motor vehicle in use are particularly elucidated.

Keywords: noise abatement, MV noise sources, noise source identification, muffler

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Authors: Dalma Varga, Nora Hubayne H.

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Nowadays, among the measures taken to offset the consequences of climate change, water resources management is one of the key tools, which can include excess water management. As a result of climate change’s effects and as a result of the frequent inappropriate landuse, more and more areas are affected by the excess water inundation. Hungary is located in the deepest part of the Pannonian Basin, which is exposed to water damage – especially lowland areas that are endangered by floods or excess waters. The periodical presence of excess water creates specific habitats in a given area, which have ecological, functional, and aesthetic values. Excess water inundation affects approximately 74% of Hungary’s lowland areas, of which about 46% is also under nature protection (such as national parks, protected landscape areas, nature conservation areas, Natura 2000 sites, etc.). These data prove that areas exposed to excess water inundation – which are predominantly characterized by agricultural land uses – have an important ecological role. Other research works have confirmed the presence of numerous rare and endangered plant species in drainage canals, on grasslands exposed to excess water, and on special agricultural fields with mud vegetation. The goal of this research is to define and analyze ecosystem services of areas exposed to excess water inundation. In addition to this, it is also important to determine the quantified indicators of these areas’ natural and landscape values besides the presence of protected species and the naturalness of habitats, so all in all, to analyze the various nature protections related to excess water. As a result, a practice-orientated assessment method has been developed that provides the ecological water demand, assimilates to ecological and habitat aspects, contributes to adaptive excess water management, and last but not least, increases or maintains the share of the green infrastructure network. In this way, it also contributes to reduce and mitigate the negative effects of climate change.

Keywords: ecosystem services, landscape architecture, excess water management, green infrastructure planning

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Authors: Haitham A. Haloush

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Debtors' imprisonment in Jordan is a problematic issue since it impinges upon required financial guarantees that are presumably offered by debtors on the one hand, and infringes flagrantly the International Covenant on Civil and Political Rights on the other hand. Jordan lacks regulatory provisions in this respect and debtors' imprisonment is indirectly exercised in Jordan without giving a special legal attention to this concern. From this perspective, this research reviews the available regulations, standard laws and codes of conduct that might guide the implementation of the International Covenant on Civil and Political Rights in the Jordanian context. Furthermore, this article will examine the suitability of the Jordanian legal system in providing sufficient protection for debtors. The author argues that there are serious obstacles in this aspect.

Keywords: the Jordanian civil code, the Jordanian execution law, imprisonment for debt, good faith, the Jordanian constitution, the international covenant on civil and political rights

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Authors: Jiangbo Shi, Zeyu Gao, Chen Li

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Nuclei segmentation is a fundamental task in digital pathology analysis and can be automated by deep learning-based methods. However, the development of such an automated method requires a large amount of data with precisely annotated masks which is hard to obtain. Training with weakly labeled data is a popular solution for reducing the workload of annotation. In this paper, we propose a novel meta-learning-based nuclei segmentation method which follows the label correction paradigm to leverage data with noisy masks. Specifically, we design a fully conventional meta-model that can correct noisy masks by using a small amount of clean meta-data. Then the corrected masks are used to supervise the training of the segmentation model. Meanwhile, a bi-level optimization method is adopted to alternately update the parameters of the main segmentation model and the meta-model. Extensive experimental results on two nuclear segmentation datasets show that our method achieves the state-of-the-art result. In particular, in some noise scenarios, it even exceeds the performance of training on supervised data.

Keywords: deep learning, histopathological image, meta-learning, nuclei segmentation, weak annotations

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Authors: A. Abdulkadir, A. A. Okhimamhe, Y. M. Bello, H. Ibrahim, D. H. Makun, M. T. Usman

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Household waste form a larger proportion of waste generated across the state, accumulation of organic waste is an apparent problem and the existing dump sites could be overstressed. Niger state has abundant arable land and water resources thus should be one of the highest producers of agricultural crops in the country. However, the major challenge to agricultural sector today is the loss of soil nutrient coupled with high cost of fertilizer. These have continued to increase the use of fertilizer and decomposed solid waste for enhancing agricultural yield, which have varying effects on the soil as well a threat to human livelihood. Consequently, vegetable yield samples from poultry droppings decomposed household waste manure, NPK treatments and control from each replication were subjected to proximate analysis to determine the nutritional and anti-nutritional component as well as heavy metal concentration. Data collected was analyzed using SPSS software and Randomized complete Block Design means were compared. The result shows that the treatments do not devoid the concentrations of any nutritional components while the anti-nutritional analysis proved that NPK had higher oxalate content than control and organic treats. The concentration of lead and cadmium are within safe permissible level while the mercury level exceeded the FAO/WHO maximum permissible limit for the entire treatments depicts the need for urgent intervention to minimize mercury levels in soil and manure in order to mitigate its toxic effect. Thus, eco-agriculture should be widely accepted and promoted by the stakeholders for soil amendment, higher yield, strategies for sustainable environmental protection, food security, poverty eradication, attainment of sustainable development and healthy livelihood.

Keywords: anti-nutritional, healthy livelihood, nutritional waste, organic waste

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Authors: Husen Ahmed Tura

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There are strong links between secure land rights and food security in Africa. However, as land is owned by governments, land users do not have adequate legislative protection. This article explores normative and implementation gaps in relation to small-scale farmers’ land rights under the Ethiopia’s law. It finds that the law facilitates eviction of small-scale farmers and indigenous peoples from their land without adequate alternative means of livelihood. It argues that as access to land and other natural resources is strongly linked to the right to adequate food, Ethiopia should reform its land laws in the light of its legal obligations under international human rights law to respect, protect and fulfill the right to adequate food and ensure freedom from hunger.

Keywords: smallholder, secure land rights , food security, right to food, land grabbing, forced evictions

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Authors: Christian Neunzig, Simon Fahle, Jürgen Schulz, Matthias Möller, Bernd Kuhlenkötter

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Manufacturing companies are facing global competition and enormous cost pressure. The use of machine learning applications can help reduce production costs and create added value. Predictive quality enables the securing of product quality through data-supported predictions using machine learning models as a basis for decisions on test results. Furthermore, machine learning methods are able to process large amounts of data, deal with unfavourable row-column ratios and detect dependencies between the covariates and the given target as well as assess the multidimensional influence of all input variables on the target. Real production data are often subject to highly fluctuating boundary conditions and unbalanced data sets. Changes in production data manifest themselves in trends, systematic shifts, and seasonal effects. Thus, Machine learning applications require intensive pre-processing and feature selection. Data preprocessing includes rule-based data cleaning, the application of dimensionality reduction techniques, and the identification of comparable data subsets. Within the used real data set of Bosch hydraulic valves, the comparability of the same production conditions in the production of hydraulic valves within certain time periods can be identified by applying the concept drift method. Furthermore, a classification model is developed to evaluate the feature importance in different subsets within the identified time periods. By selecting comparable and stable features, the number of features used can be significantly reduced without a strong decrease in predictive power. The use of cross-process production data along the value chain of hydraulic valves is a promising approach to predict the quality characteristics of workpieces. In this research, the ada boosting classifier is used to predict the leakage of hydraulic valves based on geometric gauge blocks from machining, mating data from the assembly, and hydraulic measurement data from end-of-line testing. In addition, the most suitable methods are selected and accurate quality predictions are achieved.

Keywords: classification, achine learning, predictive quality, feature selection

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Authors: Radostina Popova

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The analysis of the competitiveness of the innovation of furniture enterprises in Bulgaria requires distinguishing types of innovation and innovation activities to determine the results. Main object of the analysis are the results of innovative activities with a high degree of novelty that determine competitiveness and high innovation. It is focused on innovative research in the EU in the last three-year period and its level is directly related to the forms of protection of industrial property, which enterprises use. The results are from studies of innovation of furniture enterprises in Bulgaria during the period - 2006-2012 on a sample of more than 600 furniture companies. The results from studies are focused on product and process (technological) innovations with a high degree of novelty.

Keywords: innovations, competitiveness, furniture enterprises, Bulgaria

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Authors: Baikunthanath Sahoo, Santosh Kumar Sahu, Krishna Malakar

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With the essence of global environmental sustainability and green business management, the wind of business research moved towards Corporate Social Responsibility. In addition to international and national treaties, businesses have also started realising environmental protection and energy efficiency through CSR as part of business strategy in response to climate change. Considering the ambitious emission reduction target and rapid economic development of India, this study is an attempt to explore the effect of CSR on the energy efficiency management of manufacturing firms in India. By using firm-level data, the panel fixed effect model shows that the CSR dummy variable is negatively influencing the energy intensity or technically, they are energy efficient. The result demonstrates that in the presence of CSR, all the production economic variables are significant. The result also shows that doing environmental expenditure does not improve energy efficiency might be because very few firms are motivated to do such expenditure and also not common to all sectors. The interactive effect model result conforms that without considering CSR dummy as an intervening variable only Manufacturers of Chemical and Chemical products, Manufacturers of Pharmaceutical, medical chemical, and botanical products firms energy intensity low but after considering CSR in their business practices all six sub-sector firms become energy efficient. The empirical result also validate that firms are continuously engaged in CSR activities they are highly energy efficient. It is an important motivational factor for firms to become economically and environmentally sustainable in the corporate world. This analysis would help business practitioners to know how to manage today’s profitability and tomorrow’s sustainability to achieve a comparative advantage in the emerging market economy. The paper concludes that reducing energy consumption as part of their social responsibility to care for the environment, will need collaborative efforts of business society and policy bodies.

Keywords: CSR, Energy Efficiency, Indian manufacturing Sector, Business strategy

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Authors: Mohammad Ranjbar, Mohammad Bazyar, Blake Angell, Thomas Lung, Yibeltal Assefa

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Background: Current health insurance programs in Iran suffer from low enrolment and are not sufficient to attain the country to universal health coverage (UHC). We hypothesize that improving the enrollment rate and moving towards a more sustainable UHC can be achieved by improving the benefits package and providing new incentives. The objective of this study is to assess public preferences and willingness to pay (WTP) for social health insurance (SHI) in Iran. Methods: A discrete choice experiment (DCE) was conducted in 2021, using a self-administered questionnaire on 500 participants to estimate WTP and determine individual preferences for the SHI in Yazd, Iran. Respondents were presented with an eight-choice set and asked to select their preferred one. In each choice set, scenarios were described by eight attributes with varying levels. The conditional logit regression model was used to analyze the participants' preferences. Willingness to pay for each attribute was also calculated. Results: Most included attributes were significant predictors of the choice of a health insurance package. The maximum coverage of hospitalization costs in the private sector, ancillary services such as glasses, canes, etc., as well as coverage for hospitalization costs in the public sector and drug costs, were the most important determining factors for this choice. Coverage of preventive dental care did not significantly influence respondent choices. Estimating WTP showed that individuals are willing to pay more for higher financial protection, particularly against private sector costs; the WTP to increase the coverage of hospitalization costs in the private sector from 50% to 90% is estimated at 362,068 IR, Rials per month. Conclusion: This study identifies the key factors that the population value with regard to health insurance and the tradeoffs they are willing to make between them. Hospitalization, drugs, and ancillary services were the most important determining factors for their choice. The data suggest that additional resources coming into the Iranian health system might best be prioritized to cover hospitalization and drug costs and those associated with ancillary services.

Keywords: social health insurance, preferences, discrete choice experiment, willingness to pay

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Authors: Laura Butabayeva, Svetlana Ismagulova, Gulbarshin Nogaibayeva, Maiya Temirbayeva, Aidana Zhussip

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Over the years of independence, Kazakhstan has not only ratified international documents regulating the rights of children to Inclusive education, but also developed its own inclusive educational policy. Along with this, the state pays particular attention to high school students' preparedness for professional self-determination. However, a number of problematic issues in this field have been revealed, such as the lack of systemic mechanisms coordinating stakeholders’ actions in preparing schoolchildren for a conscious choice of in-demand profession, meeting their individual capabilities and special educational needs (SEN). The analysis of the state’s current situation indicates school graduates’ adaptation to the labor market does not meet existing demands of the society. According to the Ministry of Labor and Social Protection of the Population of the Republic of Kazakhstan, about 70 % of Kazakhstani school graduates find themselves difficult to choose a profession, 87 % of schoolchildren make their career choice under the influence of parents and school teachers, 90 % of schoolchildren and their parents have no idea about the most popular professions on the market. The results of the study conducted by KorlanSyzdykova in 2016 indicated the urgent need of Kazakhstani school graduates in obtaining extensive information about in- demand professions and receiving professional assistance in choosing a profession in accordance with their individual skills, abilities, and preferences. The results of the survey, conducted by Information and Analytical Center among heads of colleges in 2020, showed that despite significant steps in creating conditions for students with SEN, they face challenges in studying because of poor career guidance provided to them in schools. The results of the study, conducted by the Center for Inclusive Education of the National Academy of Education named after Y. Altynsarin in the state’s general education schools in 2021, demonstrated the lack of career guidance, pedagogical and psychological support for children with SEN. To investigate these issues, the further study was conducted to examine the state of students’ career guidance and socialization, taking into account their SEN. The hypothesis of this study proposed that to prepare school graduates for a conscious career choice, school teachers and specialists need to develop their competencies in early identification of students' interests, inclinations, SEN and ensure necessary support for them. The state’s 5 regions were involved in the study according to the geographical location. The triangulation approach was utilized to ensure the credibility and validity of research findings, including both theoretical (analysis of existing statistical data, legal documents, results of previous research) and empirical (school survey for students, interviews with parents, teachers, representatives of school administration) methods. The data were analyzed independently and compared to each other. The survey included questions related to provision of pedagogical support for school students in making their career choice. Ethical principles were observed in the process of developing the methodology, collecting, analyzing the data and distributing the results. Based on the results, methodological recommendations on students’ career guidance for school teachers and specialists were developed, taking into account the former’s individual capabilities and SEN.

Keywords: career guidance, children with special educational needs, inclusive education, Kazakhstan

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Authors: Chen Xi, Liu Xuebing, Lao Xueru, Kuan Sinman, Jiang Yike, Wang Hanwei, Yang Xiaolang, Zhou Junjie, Xie Jinpeng

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To further promote the development of smart cities, the microscopic "nerve endings" of the City Intelligent Model (CIM) are extended to be more sensitive. In this paper, we develop a pedestrian trajectory twin terminal based on the CIM and CNN technology. It also uses 5G networks, architectural and geoinformatics technologies, convolutional neural networks, combined with deep learning networks for human behavior recognition models, to provide empirical data such as 'pedestrian flow data and human behavioral characteristics data', and ultimately form spatial performance evaluation criteria and spatial performance warning systems, to make the empirical data accurate and intelligent for prediction and decision making.

Keywords: urban planning, urban governance, CIM, artificial intelligence, sustainable development

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Authors: Shalini Saini, Sharmila Ahuja

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Anaesthesia for caesarean section poses challenges unique to the obstetric patient due to changes in the airway and respiratory system. The choice of anaesthesia for caesarean section depends on various factors however general anaesthesia (GA) is necessary for certain situations. Supraglottic airway devices are an emerging method to secure airway, especially in difficult situations. Of these devices, proseal –LMA (PLMA) is designed to provide better protection of the airway. The use of PLMA has been reported successfully as a rescue device in difficult intubation situations and in patients undergoing elective caesarean section without any complications. The study was prospective and randomised and was designed to compare PLMA in patients undergoing elective lower segment caesarean section (LSCS) with the endotracheal tube (ETT). Patients undergoing LSCS under GA belonging to ASA grade 1 and 2 were included. Patients with the history of fewer than 6 hrs of fasting, known/predicted difficult airway, obesity, gastroesophageal reflux disease, hypertensive disorder were excluded. A standard anaesthesia protocol was followed. All patients received aspiration prophylaxis. The airway was secured with either PLMA or ETT. Parameters noted were- ease of insertion, adequacy of ventilation, hemodynamic changes at insertion and removal of device, incidence of regurgitation and aspiration. Data was analysed by unpaired t- test, Chi-square /Fisher’s test. The findings of our study indicated that PLMA was easy to insert (20.67±6.835 sec) with comparable insertion time to TT (18.33 ± 4.971, p 0.136) and adequate ventilation was achieved with very minimal hemodynamic changes seen with PLMA as compared to ETT at insertion and removal of devices (p 0.01). There was no incidence of regurgitation with the use of PLMA. The incidence of a postoperative sore throat was minimal (6.7%) with PLMA (p<0.05). PLMA appears to be a safe alternative to ETT for selected obstetric patients undergoing elective LSCS. Further study with a larger group of patients is required to establish the safety of PLMA in obstetric patients.

Keywords: caesarean section, general anaesthesia, proseal LMA, endotracheal tube

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Authors: Abdel Hadi Ebraheim

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This paper introduces a new extension of the Inverse Pareto distribution in the framework of Marshal-Olkin (1997) family of distributions. This model is capable of modeling various shapes of aging and failure data. The statistical properties of the new model are discussed. Several methods are used to estimate the parameters involved. Explicit expressions are derived for different types of moments of value in reliability analysis are obtained. Besides, the order statistics of samples from the new proposed model have been studied. Finally, the usefulness of the new model for modeling reliability data is illustrated using two real data sets with simulation study.

Keywords: pareto distribution, marshal-Olkin, reliability, hazard functions, moments, estimation

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Authors: Osiris Jorge Parcero, Néstor Gandelman, Flavia Roldán, Josef Montag

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This paper uses cross-country unbalanced panel data of up to 146 countries over the period 1996 to 2015 to be the first study to identify potential determinants of a country’s relative research output in Economics versus Business. More generally, it is also one of the first studies comparing Economics and Business. The results show that better policy-related data availability, higher income inequality, and lower ethnic fractionalization relatively favor economics. The findings are robust to two alternative fixed effects specifications, three alternative definitions of economics and business, two alternative measures of research output (publications and citations), and the inclusion of meaningful control variables. To the best of our knowledge, our paper is also the first to demonstrate the importance of policy-related data as drivers of economic research. Our regressions show that the availability of this type of data is the single most important factor associated with the prevalence of economics over business as a research domain. Thus, our work has policy implications, as the availability of policy-related data is partially under policy control. Moreover, it has implications for students, professionals, universities, university departments, and research-funding agencies that face choices between profiles oriented toward economics and those oriented toward business. Finally, the conclusions show potential lines for further research.

Keywords: research output, publication performance, bibliometrics, economics, business, policy-related data

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