Search results for: threats identification

Authors: Djebbar Atmani, Aghiles Karim Aissat, Nadjet Debbache-Benaida, Nassima Chaher-Bazizi, Dina Atmani-Kilani, Meriem Rahmani-Berboucha, Naima Saidene, Malika Benloukil, Lila Azib

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Medicinal plants are believed to be an important source for the discovery of potential antioxidant, anti-inflammatory and anti-diabetic substances. The present study was designed to investigate the neuroprotective, anti-inflammatory, anti-diabetic and anti-hyperuricemic potential of Pistacia lentiscus, as well as the identification of active compounds. The antioxidant potential of plant extracts against known radicals was measured using various standard in vitro methods. Anti-inflammatory activity was determined using the paw edema model in mice and by measuring the secretion of the pro-inflammatory cytokine, whereas the anti-diabetic effect was assessed in vivo on streptozotocin-induced diabetic rats and in vitro by inhibition of alpha-amylase. The anti-hyperuricemic activity was evaluated using the xanthine oxidase assay, whereas neuroprotective activity was investigated using an Aluminum-induced toxicity test. Pistacia lentiscus extracts and fractions exhibited high scavenging capacity against DPPH, NO. and ABTS+ radicals in a dose-dependent manner and restored blood glucose levels, in vivo, to normal values, in agreement with the in vitro anti-diabetic effect. Oral administration of plant extracts significantly decreased carrageenan-induced mice paw oedema, similar to the standard drug, diclofenac, was effective in reducing IL-1β levels in cell culture and induced a significant increase in urinary volume in mice, associated to a promising anti-hyperuricemic activity. Plant extracts showed good neuroprotection and restoration of cognitive functions in mice. HPLC-MS and NMR analyses allowed the identification of known and new phenolic compounds that could be responsible for the observed activities. Therefore, Pistacia lentiscus could be beneficial in the treatment of inflammatory conditions and diabetes complications and the enhancement of cognitive functions.

Keywords: Pistacia lentiscus, anti-inflammatory, antidiabetic, flavanols, neuroprotective

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Authors: Sahar Nasr, Lin Li, Edwin Wang

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Bladder cancer (BLCA) is known as the 13th cause of death among cancer patients worldwide, and ~575,000 new BLCA cases are diagnosed each year. Urothelial carcinoma (UC) is the most prevalent subtype among BLCA patients, which can be categorized into muscle-invasive bladder cancer (MIBC) and non-muscle-invasive bladder cancer (NMIBC). Currently, various therapeutic options are available for UC patients, including (1) transurethral resection followed by intravesical instillation of chemotherapeutics or Bacillus Calmette-Guérin for NMIBC patients, (2) neoadjuvant platinum-based chemotherapy (NAC) plus radical cystectomy is the standard of care for localized MIBC patients, and (3) systematic chemotherapy for metastatic UC. However, conventional treatments may lead to several challenges for treating patients. As an illustration, some patients may suffer from recurrence of the disease after the first line of treatment. Recently, immune checkpoint therapy (ICT) has been introduced as an alternative treatment strategy for the first or second line of treatment in advanced or metastatic BLCA patients. Although ICT showed lucrative results for a fraction of BLCA patients, ~80% of patients were not responsive to it. Therefore, novel treatment methods are required to augment the ICI response rate within BLCA patients. It has been shown that the infiltration of T-cells into the tumor microenvironment (TME) is positively correlated with the response to ICT within cancerous patients. Therefore, the goal of this study is to enhance the infiltration of cytotoxic T-cells into TME through the identification of target genes within the tumor that are responsible for the non-T-cell inflamed TME and their inhibition. BLCA bulk RNA-sequencing data from The Cancer Genome Atlas (TCGA) and immune score for TCGA samples were used to determine the Pearson correlation score between the expression of different genes and immune score for each sample. The genes with strong negative correlations were selected (r < -0.2). Thereafter, the correlation between the expression of each gene and survival in BLCA patients was calculated using the TCGA data and Cox regression method. The genes that are common in both selected gene lists were chosen for further analysis. Afterward, BLCA bulk and single-cell RNA-sequencing data were ranked based on the expression of each selected gene and the top and bottom 25% samples were used for pathway enrichment analysis. If the pathways related to the T-cell infiltration (e.g., antigen presentation, interferon, or chemokine pathways) were enriched within the low-expression group, the gene was included for downstream analysis. Finally, the selected genes will be used to calculate the correlation between their expression and the infiltration rate of the activated CD+8 T-cells, natural killer cells and the activated dendric cells. A list of potential target genes has been identified and ranked based on the above-mentioned analysis and criteria. SUN-1 got the highest score within the gene list and other identified genes in the literature as benchmarks. In conclusion, inhibition of SUN1 may increase the tumor-infiltrating lymphocytes and the efficacy of ICI in BLCA patients. BLCA tumor cells with and without SUN-1 CRISPR/Cas9 knockout will be injected into the syngeneic mouse model to validate the predicted SUN-1 effect on increasing tumor-infiltrating lymphocytes.

Keywords: data analysis, gene expression analysis, gene identification, immunoinformatic, functional genomics, transcriptomics

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Authors: Syahidah N. Zulkifli, Herlina A. Rahim, Nurul A. M. Subha

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Sustaining water quality is critical in order to avoid any harmful health consequences for end-user consumers. The detection of microbial impurities at the household level is the foundation of water security. Water quality is now monitored only at water utilities or infrastructure, such as water treatment facilities or reservoirs. This research provides a first-hand scientific understanding of microbial composition presence in Malaysia’s household point-of-use (POUs) water supply influenced by seasonal fluctuations, standstill periods, and flow dynamics by using the NIR-Raman spectroscopic technique. According to the findings, 20% of water samples were contaminated by pathogenic bacteria, which are Legionella and Salmonella cells. A comparison of the spectra reveals significant signature peaks (420 cm⁻¹ to 1800 cm⁻¹), including species-specific bands. This demonstrates the importance of regularly monitoring POUs water quality to provide a safe and clean water supply to homeowners. Conventional Raman spectroscopy, up-to-date, is no longer suited for real-time monitoring. Therefore, this study introduced an alternative micro-spectrometer to give a rapid and sustainable way of monitoring POUs water quality. Assessing microbiological threats in water supply becomes more reliable and efficient by leveraging IoT protocol.

Keywords: microbial contaminants, water quality, water monitoring, Raman spectroscopy

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Authors: Nkosingiphile Mbusozayo Zungu

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The purpose of the current study is to adopt informetrics methods to analyse the research on phishing from 2012 to 2021 in three selected databases in order to contribute to global cybersecurity through impactful research. The study follows a quantitative research methodology. We opted for the positivist epistemology and objectivist ontology. The analysis focuses on: (i) the productivity of individual authors, institutions, and countries; (ii) the research contributions, using co-authorship as a measure of collaboration; (iii) the altmetrics of selected research contributions; (iv) the citation patterns and research impact of research on phishing; and (v) research contributions by keywords, to discover the concepts that are related to phishing. The preliminary findings favour developed countries in terms of quantity and quality of research in the domain. There are unique research trends and patterns in the developing countries, including those in Africa, that provide opportunities for research development in the domain in the region. This study explores an important research domain by using unexplored method in the region. The study supports the SDG Agenda 2030, such as ending abuse, exploitation, trafficking, and all other forms of violence and torture of children through the use of cyberspace (SDG 16). Further, the results from this study can inform research, teaching, and learning largely in Africa. Invariably, the study contributes to cybersecurity awareness that will mitigate cybersecurity threats against vulnerable communities.

Keywords: phishing, cybersecurity, informetrics, information security

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Authors: Sabahat Zahra

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The purpose of this research is to present the changing global environment and its potential impacts on sustainable food and energy production at global level, particularly in Pakistan. The food and energy related-economic sector has been subjected to negative consequences due to recent extreme changes in weather conditions, particularly in developing countries. Besides continuous modifications in weather, population is also increasing by time, therefore it is necessary to take special steps and start effective initiatives to cope with the challenges of food and energy security to fight hunger and for economic stability of country. Severe increase in temperature and heat waves has also negative impacts on food production as well as energy sustainability. Energy (in terms of electricity) consumption has grown up than the production potential of the country as a consequence of increasing warm weather. Ultimately prices gone up when there is more consumption than production. Therefore, all these aspects of climate change are interrelated with socio-economic issues. There is a need to develop long-term policies on regional and national levels for maintainable economic growth. This research presents a framework-plan and recommendations for implementation needed to mitigate the potential threats due to global climate change sustainable food and energy production under climate change in the country.

Keywords: climate changes, energy security, food security, global climate change

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Authors: K. Frahtia, I. Mihoubi, S. Picot

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Leishmaniasis is a group of parasitic disease with a varied clinical expression caused by flagellate protozoa of the Leishmania genus. These diseases are transmitted to humans and animals by the sting of a vector insect, the female sandfly. Among the groups of dipteral disease vectors, Phlebotominae occupy a prime position and play a significant role in human pathology, such as leishmaniasis that affects nearly 350 million people worldwide. The vector control operation launched by health services throughout the country proves to be effective since despite the prevalence of the disease remains high especially in rural areas, leishmaniasis appears to be declining in Algeria. In this context, this study mainly concerns molecular detection of Leishmania from the vector. Furthermore, a molecular diagnosis has also been made on skin samples taken from patients in the region of Constantine, located in the North-East of Algeria. Concerning the vector, 5858 sandflies were captured, including 4360 males and 1498 females. Male specimens were identified based on their morphological. The morphological identification highlighted the presence of the Phlebotomus genus with a prevalence of 93% against 7% represented by the Sergentomyia genus. About the identified species, P. perniciosus is the most abundant with 59.4% of the male identified population followed by P. longicuspis with 24.7% of the workforce. P. perfiliewi is poorly represented by 6.7% of specimens followed by P. papatasi with 2.2% and 1.5% S. dreyfussi. Concerning skin samples, 45/79 (56.96%) collected samples were found positive by real-time PCR. This rate appears to be in sharp decline compared to previous years (alert peak of 30,227 cases in 2005). Concerning the detection of Leishmania from sandflies by RT-PCR, the results show that 3/60 PCR performed genus are positive with melting temperatures corresponding to that of the reference strain (84.1 +/- 0.4 ° C for L. infantum). This proves that the vectors were parasitized. On the other side, identification by RT-PCR species did not give any results. This could be explained by the presence of an insufficient amount of leishmanian DNA in the vector, and therefore support the hypothesis of the regression of leishmaniasis in Constantine.

Keywords: Algeria, molecular diagnostic, phlebotomus, real time PCR

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Authors: Kenneth Azaigba

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The history of post-colonial African States has been dubbed a history of endemic warfare in existing literature. Indeed, Africa political environment is characterized by a multiplicity of threats to peace and security. Africa's leading drivers of conflict include abundant (especially mineral) resources, personal rule and attendant political authoritarianism, manipulation of identity politics across ethnicity, marginalization of communities, as well as electoral mal-practices resulting in contested legitimacy and resultant violence. However, the character of armed conflicts in Africa is changing. This paper attempts to reconstruct the trajectory of armed conflicts in Africa and explain the changing pattern of armed conflict. The paper contends that large scale political violence in Africa is on the decline rendering the endemic thesis an inappropriate paradigm in explaining political conflicts in Africa. The paper also posits that though small scale conflicts are springing up and exhibiting trans-border dimensions, these patterns of armed conflicts are not peculiar to Africa but emerging waves of global conflicts. The paper explains that the shift in the scale of warfare in Africa is a function of a multiplicity of post-cold war global contradictions. Inclusive governance, social justice and economic security are articulated as workable panaceas for mitigating warfare in Africa.

Keywords: Africa, conflicts, pattern, war

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Authors: Jamie Lee Harder

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In the context of rapidly changing social and economic circumstances in the developing world, this paper analyses access to public healthcare for poor people with disabilities in Cambodia. Like other countries of South East Asia, Cambodia is developing at rapid pace. The historical past of Cambodia, however, has set former social policy structures to zero. This past forces Cambodia and its citizens to implement new public health policies to align with the needs of social care, healthcare, and urban planning. In this context, the role of people with disabilities (PwDs) is crucial as new developments should and can take into consideration their specific needs from the beginning onwards. This paper is based on qualitative research with expert interviews and focus group discussions in Cambodia. During the field work it became clear that the identification tool for the poorest households (HHs) does not count disability as a financial risk to fall into poverty neither when becoming sick nor because of higher health expenditures and/or lower income because of the disability. The social risk group of poor PwDs faces several barriers in accessing public healthcare. The urbanization, the socio-economic health status, and opportunities for education; all influence social status and have an impact on the health situation of these individuals. Cambodia has various difficulties with providing access to people with disabilities, mostly due to barriers regarding finances, geography, quality of care, poor knowledge about their rights and negative social and cultural beliefs. Shortened budgets and the lack of prioritizations lead to the need for reorientation of local communities, international and national non-governmental organizations and social policy. The poorest HHs are identified with a questionnaire, the IDPoor program, for which the Ministry of Planning is responsible. The identified HHs receive an ‘Equity Card’ which provides access free of charge to public healthcare centers and hospitals among other benefits. The dataset usually does not include information about the disability status. Four focus group discussions (FGD) with 28 participants showed various barriers in accessing public healthcare. These barriers go far beyond a missing ramp to access the healthcare center. The contents of the FGDs were ratified and repeated during the expert interviews with the local Ministries, NGOs, international organizations and private persons working in the field. The participants of the FGDs faced and continue to face high discrimination, low capacity to work and earn an own income, dependency on others and less social competence in their lives. When discussing their health situation, we identified, a huge difference between those who are identified and hold an Equity Card and those who do not. Participants reported high costs without IDPoor identification, positive experiences when going to the health center in terms of attitude and treatment, low satisfaction with specific capacities for treatments, negative rumors, and discrimination with the consequence of fear to seek treatment in many cases. The problem of accessing public healthcare by risk groups can be adapted to situations in other countries.

Keywords: access, disability, health, inequality, Cambodia

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Authors: Shashank Tiwari

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The most common method of drug delivery is the oral solid dosage form, of which tablets and capsules are predominant. The tablet is more widely accepted and used compared to capsules for a number of reasons, such as cost/price, tamper resistance, ease of handling and packaging, ease of identification, and manufacturing efficiency. Over the past several years, the issue of tamper resistance has resulted in the conversion of most over-the-counter (OTC) drugs from capsules to predominantly all tablets.

Keywords: capsule, drug delivery, dosages, solid, tablet

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Authors: Zhiwen Pan, Jesus Pacheco, Salim Hariri, Yiqiang Chen, Bozhi Liu

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The Internet of Things (IoT) will lead to the development of advanced Smart Home services that are pervasive, cost-effective, and can be accessed by home occupants from anywhere and at any time. However, advanced smart home applications will introduce grand security challenges due to the increase in the attack surface. Current approaches do not handle cybersecurity from a holistic point of view; hence, a systematic cybersecurity mechanism needs to be adopted when designing smart home applications. In this paper, we present a generic intrusion detection methodology to detect and mitigate the anomaly behaviors happened in Smart Home Systems (SHS). By utilizing our Smart Home Context Data Structure, the heterogeneous information and services acquired from SHS are mapped in context attributes which can describe the context of smart home operation precisely and accurately. Runtime models for describing usage patterns of home assets are developed based on characterization functions. A threat-aware action management methodology, used to efficiently mitigate anomaly behaviors, is proposed at the end. Our preliminary experimental results show that our methodology can be used to detect and mitigate known and unknown threats, as well as to protect SHS premises and services.

Keywords: Internet of Things, network security, context awareness, intrusion detection

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Authors: Mohammad A. U. Khan, Tariq M. Khan, Yinan Kong

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Fingerprint image enhancement is one of the most important step in an automatic fingerprint identification recognition (AFIS) system which directly affects the overall efficiency of AFIS. The conventional fingerprint enhancement like Gabor and Anisotropic filters do fill the gaps in ridge lines but they fail to tackle scar lines. To deal with this problem we are proposing a method for enhancing the ridges and valleys with scar so that true minutia points can be extracted with accuracy. Our results have shown an improved performance in terms of enhancement.

Keywords: fingerprint image enhancement, removing noise, coherence, enhanced diffusion

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Authors: Yasir E. Mohieldeen

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Qatar is one of the most water scarce countries in the World. In 2014, the average per capita rainfall was less than 29 m3/y/ca, while the global average is 6,000 m3/y/ca. However, the per capita water consumption in Qatar is among the highest in the World: more than 500 liters per person per day, whereas the global average is 160 liters per person per day. Since the early 2000s, Qatar has been relying heavily on desalinated water from the Arabian Gulf as the main source of fresh water. In 2009, about 99.9% of the total potable water produced was desalinated. Reliance on desalinated water makes Qatar very vulnerable to water related natural disasters, such as the red-tide phenomenon. Qatar’s strategic water reserve lasts for only 7 days. In case of red-tide outbreak, the country would not be able to desalinate water for days, let alone the months that this disaster would bring about (as it clogs the desalination equipment). The 2008-09 red-tide outbreak, for instance, lasted for more than eight months and forced the closure of desalination plants in the region for weeks. This study aims at identifying favorite conditions for red-tide outbreaks, using satellite data along with in-situ measurements. This identification would allow the prediction of these outbreaks and their hotspots. Prediction and monitoring of outbreaks are crucial to water security in the country, as different measures could be put in place in advance to prevent an outbreak and mitigate its impact if it happened. Red-tide outbreaks are detected using different algorithms for chlorophyll concentration in the Gulf waters. Vegetation indices, such as Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) were used along with Surface Algae Bloom Index (SABI) to detect known outbreaks. MODIS (or Moderate Resolution Imaging Spectroradiometer) bands are used to calculate these indices. A red-tide outbreaks atlas in the Arabian Gulf is being produced. Prediction of red-tide outbreaks ahead of their occurrences would give critical information on possible water-shortage in the country. Detecting known outbreaks in the past few decades and related parameters (e.g. water salinity, water surface temperature, nutrition, sandstorms, … etc) enables the identification of favorite conditions of red-tide outbreak that are key to the prediction of these outbreaks.

Keywords: Arabian Gulf, MODIS, red-tide detection, strategic water reserve, water desalination

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Authors: Zahid Ullah, Atlas Khan

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This abstract focuses on the advancements in mathematical modeling and optimization techniques that play a crucial role in enhancing the efficiency, reliability, and performance of these systems. In this era of rapidly evolving technology, mathematical modeling and optimization offer powerful tools to tackle the complex challenges faced by control, signal processing, and energy systems. This abstract presents the latest research and developments in mathematical methodologies, encompassing areas such as control theory, system identification, signal processing algorithms, and energy optimization. The abstract highlights the interdisciplinary nature of mathematical modeling and optimization, showcasing their applications in a wide range of domains, including power systems, communication networks, industrial automation, and renewable energy. It explores key mathematical techniques, such as linear and nonlinear programming, convex optimization, stochastic modeling, and numerical algorithms, that enable the design, analysis, and optimization of complex control and signal processing systems. Furthermore, the abstract emphasizes the importance of addressing real-world challenges in control, signal processing, and energy systems through innovative mathematical approaches. It discusses the integration of mathematical models with data-driven approaches, machine learning, and artificial intelligence to enhance system performance, adaptability, and decision-making capabilities. The abstract also underscores the significance of bridging the gap between theoretical advancements and practical applications. It recognizes the need for practical implementation of mathematical models and optimization algorithms in real-world systems, considering factors such as scalability, computational efficiency, and robustness. In summary, this abstract showcases the advancements in mathematical modeling and optimization techniques for control, signal processing, and energy systems. It highlights the interdisciplinary nature of these techniques, their applications across various domains, and their potential to address real-world challenges. The abstract emphasizes the importance of practical implementation and integration with emerging technologies to drive innovation and improve the performance of control, signal processing, and energy.

Keywords: mathematical modeling, optimization, control systems, signal processing, energy systems, interdisciplinary applications, system identification, numerical algorithms

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Authors: S. N. Al-Bahry, Y. M. Al-Wahaibi, S. J. Joshi, E. A. Elshafie, A. S. Al-Bimani

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Oman is one of the oil producing countries in the Arabian Peninsula and the Gulf region. About 30-40 % of oil produced from the Gulf is transported globally along the seacoast of Oman. Oil pollution from normal tanker operations, ballast water, illegal discharges and accidental spills are always serious threats to terrestrial and marine habitats. Due to Oman’s geographical location at arid region where the temperature ranges between high 40s and low 50s Celsius in summers with low annual rainfall, the main source of fresh water is desalinated sea and brackish water. Oil pollution, therefore, pose a major threat to drinking water. Biosurfactants are secondary metabolites produced by microorganisms in hydrophobic environments to release nutrients from solid surfaces, such as oil. In this study, indigenous oil degrading thermophilic spore forming bacteria were isolated from oil fields contaminated soil. The isolates were identified using MALDI-TOF biotyper and 16s RNA. Their growth conditions were optimized for the production of biosurfactant. Surface tension, interfacial tensions and microbial oil biodegradation capabilities were tested. Some thermophilic bacteria degraded either completely or partially heavy crude oil (API 10-15) within 48h suggesting their high potential in oil spill bioremediation and avoiding the commonly used physical and chemical methods which usually lead to other environmental pollution.

Keywords: bacteria, bioremediation, biosurfactant, crude-oil-pollution

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Authors: Pema Choejey, David Murray, Chun Che Fung

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Bhutan is becoming increasingly dependent on Information and Communications Technologies (ICTs), especially the Internet for performing the daily activities of governments, businesses, and individuals. Consequently, information systems and networks are becoming more exposed and vulnerable to cybersecurity threats. This paper highlights the findings of the survey study carried out to understand the perceptions of cybersecurity implementation among government organizations in Bhutan. About 280 ICT personnel were surveyed about the effectiveness of cybersecurity implementation in their organizations. A questionnaire based on a 5 point Likert scale was used to assess the perceptions of respondents. The questions were asked on cybersecurity practices such as cybersecurity policies, awareness and training, and risk management. The survey results show that less than 50% of respondents believe that the cybersecurity implementation is effective: cybersecurity policy (40%), risk management (23%), training and awareness (28%), system development life cycle (34%); incident management (26%), and communications and operational management (40%). The findings suggest that many of the cybersecurity practices are inadequately implemented and therefore, there exist a gap in achieving a required cybersecurity posture. This study recommends government organizations to establish a comprehensive cybersecurity program with emphasis on cybersecurity policy, risk management, and awareness and training. In addition, the research study has practical implications to both government and private organizations for implementing and managing cybersecurity.

Keywords: awareness and training, cybersecurity policy, risk management, security risks

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Authors: M. Moslehpour, S. Khorsandi

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Due to shortage in IPv4 addresses, transition to IPv6 has gained significant momentum in recent years. Like Address Resolution Protocol (ARP) in IPv4, Neighbor Discovery Protocol (NDP) provides some functions like address resolution in IPv6. Besides functionality of NDP, it is vulnerable to some attacks. To mitigate these attacks, Internet Protocol Security (IPsec) was introduced, but it was not efficient due to its limitation. Therefore, SEND protocol is proposed to automatic protection of auto-configuration process. It is secure neighbor discovery and address resolution process. To defend against threats on NDP’s integrity and identity, Cryptographically Generated Address (CGA) and asymmetric cryptography are used by SEND. Besides advantages of SEND, its disadvantages like the computation process of CGA algorithm and sequentially of CGA generation algorithm are considerable. In this paper, we parallel this process between network resources in order to improve it. In addition, we compare the CGA generation time in self-computing and distributed-computing process. We focus on the impact of the malicious nodes on the CGA generation time in the network. According to the result, although malicious nodes participate in the generation process, CGA generation time is less than when it is computed in a one-way. By Trust Management System, detecting and insulating malicious nodes is easier.

Keywords: NDP, IPsec, SEND, CGA, modifier, malicious node, self-computing, distributed-computing

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Authors: Rogerio Vieira Dos Reis

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Countries like Brazil that despite fighting hard against corruption are not improving their corruption perception, especially due to systemic political corruption, should review their corruption prevention strategies. This thesis brings a case study based on an alternative way of preventing corruption: addressing the corruption drivers in public policies that lead to poor economic performance. After discussing the Brazilian industrial policies adopted recently, especially the measures towards the automotive sector, two corruption issues in this sector are analyzed: facilitating payment for fiscal benefits and buying the extension of fiscal benefits. In-depth interviews conducted with a policymaker and an executive of the automobile sector provide insights for identifying three main corruption drivers: excessive and unnecessary bureaucracy, a complex tax system and the existence of a closed market without setting performance requirements to be achieved by the benefited firms. Both the identification of the drivers of successful industrial policies and the proposal of anti-corruption strategies to ensure developmental outcomes are based on the economic perspective of industrial policy advocated by developmental authors and on the successful South Korean economic development experience. Structural anti-corruption measures include tax reform, the regulation of lobbying and legislation to allow corporate political contribution. Besides improving policymakers’ technical capabilities, measures at the ministry level include redesigning the automotive regimes as long-term policies focused on national investment with simple and clear rules and making fiscal benefits conditional upon performance targets focused on suppliers. This case study is of broader interest because it recommends the importance of adapting performance audits conducted by anti-corruption agencies, to focus not only on the delivery of public services, but also on the identification of potentially highly damaging corruption drivers in public policies that grant fiscal benefits to achieve developmental outcomes.

Keywords: Brazilian automotive sector, corruption, economic development, industrial policy, Inovar-Auto

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Authors: Tydra Preyear, Victor Clincy

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Quantum computing presents many computational advantages over classical computing methods due to the utilization of quantum mechanics. The capability of this computing infrastructure poses threats to standard cryptographic systems such as RSA and AES, which are designed for classical computing environments. This paper discusses the impact that quantum computing has on cryptography, while focusing on the evolution from classical cryptographic concepts to quantum and post-quantum cryptographic concepts. Standard Cryptography is essential for securing data by utilizing encryption and decryption methods, and these methods face vulnerability problems due to the advancement of quantum computing. In order to counter these vulnerabilities, the methods that are proposed are quantum cryptography and post-quantum cryptography. Quantum cryptography uses principles such as the uncertainty principle and photon polarization in order to provide secure data transmission. In addition, the concept of Quantum key distribution is introduced to ensure more secure communication channels by distributing cryptographic keys. There is the emergence of post-quantum cryptography which is used for improving cryptographic algorithms in order to be more secure from attacks by classical and quantum computers. Throughout this exploration, the paper mentions the critical role of the advancement of cryptographic methods to keep data integrity and privacy safe from quantum computing concepts. Future research directions that would be discussed would be more effective cryptographic methods through the advancement of technology.

Keywords: quantum computing, quantum cryptography, cryptography, data integrity and privacy

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Authors: Awad A. Younis, Elise Stronberg, Shifa Noor

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Malware attacks due to end-user vulnerabilities have been noticeably increased in the past few years. Investigating the factors that make an end-user vulnerable to those attacks is critical because they can be utilized to set up proactive strategies such as awareness and education to mitigate the impacts of those attacks. Some existing studies investigated demographic, behavioral, and cultural factors that make an end-user susceptible to malware attacks. However, it has been challenging to draw more general conclusions from individual studies due to the varieties in the type of end-users and different types of malware. Therefore, we conducted a systematic literature review (SLR) of the existing research for end-user susceptibility factors to malware attacks. The results showed while some demographic factors are mostly associated with malware infection regardless of the end users' type, age, and gender are not consistent among the same and different types of end-users. Besides, the association of culture and personality factors with malware infection are consistent in most of the selected studies and for all type of end-users. Moreover, malware infection varies based on age, geographic location, and host types. We propose that future studies should carefully take into consideration the type of end-users because different end users may be exposed to different threats or be targeted based on their user domains’ characteristics. Additionally, as different types of malware use different tactics to trick end-users, taking the malware types into consideration is important.

Keywords: cybersecurity, malware, end-users, demographics, personality, culture, systematic literature review

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Authors: Altayeb Abdalla Ahmed

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Skeletal phenotype is a product of a balanced interaction between genetics and environmental factors throughout different life stages. Therefore, interlimb proportions are variable between populations. Although interlimb proportion indices have been used in anthropology in assessing the influence of various environmental factors on limbs, an extensive literature review revealed that there is a paucity of published research assessing interlimb part correlations and possibility of reconstruction. Hence, this study aims to assess the relationships between upper and lower limb parts and develop regression formulae to reconstruct the parts from one another. The left upper arm length, ulnar length, wrist breadth, hand length, hand breadth, tibial length, bimalleolar breadth, foot length, and foot breadth of 376 right-handed subjects, comprising 187 males and 189 females (aged 25-35 years), were measured. Initially, the data were analyzed using basic univariate analysis and independent t-tests; then sex-specific simple and multiple linear regression models were used to estimate upper limb parts from lower limb parts and vice-versa. The results of this study indicated significant sexual dimorphism for all variables. The results indicated a significant correlation between the upper and lower limbs parts (p < 0.01). Linear and multiple (stepwise) regression equations were developed to reconstruct the limb parts in the presence of a single or multiple dimension(s) from the other limb. Multiple stepwise regression equations generated better reconstructions than simple equations. These results are significant in forensics as it can aid in identification of multiple isolated limb parts particularly during mass disasters and criminal dismemberment. Although a DNA analysis is the most reliable tool for identification, its usage has multiple limitations in undeveloped countries, e.g., cost, facility availability, and trained personnel. Furthermore, it has important implication in plastic and orthopedic reconstructive surgeries. This study is the only reported study assessing the correlation and prediction capabilities between many of the upper and lower dimensions. The present study demonstrates a significant correlation between the interlimb parts in both sexes, which indicates a possibility to reconstruction using regression equations.

Keywords: anthropometry, correlation, limb, Sudanese

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Authors: Htay Htay Yi, Zin May Aye

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Network security is role of the ICT environment because malicious users are continually growing that realm of education, business, and then related with ICT. The network security contravention is typically described and examined centrally based on a security event management system. The firewalls, Intrusion Detection System (IDS), and Intrusion Prevention System are becoming essential to monitor or prevent of potential violations, incidents attack, and imminent threats. In this system, the firewall rules are set only for where the system policies are needed. Dataset deployed in this system are derived from the testbed environment. The traffic as in DoS and PortScan traffics are applied in the testbed with firewall and IDS implementation. The network traffics are classified as normal or attacks in the existing testbed environment based on six machine learning classification methods applied in the system. It is required to be tested to get datasets and applied for DoS and PortScan. The dataset is based on CICIDS2017 and some features have been added. This system tested 26 features from the applied dataset. The system is to reduce false positive rates and to improve accuracy in the implemented testbed design. The system also proves good performance by selecting important features and comparing existing a dataset by machine learning classifiers.

Keywords: false negative rate, intrusion detection system, machine learning methods, performance

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Authors: Cai Qianyi

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In the midst of global digital revolution, the flow of data poses security threats that call China's existing legislative framework for protecting personal information into question. As a preliminary procedure for risk analysis and prevention, the risk assessment of personal data transmission lacks detailed guidelines for support. Existing provisions reveal unclear responsibilities for network operators and weakened rights for data subjects. Furthermore, the regulatory system's weak operability and a lack of industry self-regulation heighten data transmission hazards. This paper aims to compare the regulatory pathways for data information transmission risks between China and Europe from a legal framework and content perspective. It draws on the “Data Protection Impact Assessment Guidelines” to empower multiple stakeholders, including data processors, controllers, and subjects, while also defining obligations. In conclusion, this paper intends to solve China's digital security shortcomings by developing a more mature regulatory framework and industry self-regulation mechanisms, resulting in a win-win situation for personal data protection and the development of the digital economy.

Keywords: personal information data transmission, risk assessment, DPIA, internet service provider, personal information data transimission, risk assessment

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Authors: María Laura Guevara Campos

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The increasing number of vending machines makes it easy for people to find them more frequently in stores, universities, workplaces, and even hospitals. These machines usually offer products with high contents of sugar and fat, which, if consumed regularly, can result in serious health threats, as overweight and obesity. Additionally, the energy consumption of these machines tends to be high, which has an impact on the environment as well. In order to promote the consumption of healthy food, a vending machine was designed to give the customer the opportunity to choose between a customized fruit salad and a customized fruit juice, both of them prepared instantly with the ingredients selected by the customer. The main parameters considered to design the machine were: the storage of the preferred fruits in a salad and/or in a juice according to a survey, the size of the machine, the use of ecologic recipients, and the overall energy consumption. The methodology used for the design was the one proposed by the German Association of Engineers for mechatronics systems, which breaks the design process in several stages, from the elaboration of a list of requirements through the establishment of the working principles and the design concepts to the final design of the machine, which was done in a 3D modelling software. Finally, with the design of this machine, the aim is to contribute to the development and implementation of healthier vending machines that offer freshly-made products, which is not being widely attended at present.

Keywords: design, design methodology, mechatronics systems, vending machines

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Authors: Rida Kanwal, Wang Yuhui, Song Weiguo

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Wildfires are one of the most prominent threats to ecosystems, human health, and economic activities, with wind acting as a critical driving factor. This study combines machine learning (ML) and remote sensing (RS) to assess the effects of wind on wildfires in Chongqing Province from August 16-23, 2022. Landsat 8 satellite images were used to estimate the difference normalized burn ratio (dNBR), representing prefire and postfire vegetation conditions. Wind data was analyzed through geographic information system (GIS) mapping. Correlation analysis between wind speed and fire radiative power (FRP) revealed a significant relationship. An autoregressive integrated moving average (ARIMA) model was developed for wind forecasting, and linear regression was applied to determine the effect of wind speed on FRP. The results identified high wind speed as a key factor contributing to the surge in FRP. Wind-rose plots showed winds blowing to the northwest (NW), aligning with the wildfire spread. This model was further validated with data from other provinces across China. This study integrated ML, RS, and GIS to analyze wildfire behavior, providing effective strategies for prediction and management.

Keywords: wildfires, machine learning, remote sensing, wind speed, GIS, wildfire behavior

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Authors: Jularat Chumnaul

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In forensic science, corpses from various homicides are different; there are both complete and incomplete, depending on causes of death or forms of homicide. For example, some corpses are cut into pieces, some are camouflaged by dumping into the river, some are buried, some are burned to destroy the evidence, and others. If the corpses are incomplete, it can lead to the difficulty of personally identifying because some tissues and bones are destroyed. To specify gender of the corpses from skeletal remains, the most precise method is DNA identification. However, this method is costly and takes longer so that other identification techniques are used instead. The first technique that is widely used is considering the features of bones. In general, an evidence from the corpses such as some pieces of bones, especially the skull and pelvis can be used to identify their gender. To use this technique, forensic scientists are required observation skills in order to classify the difference between male and female bones. Although this technique is uncomplicated, saving time and cost, and the forensic scientists can fairly accurately determine gender by using this technique (apparently an accuracy rate of 90% or more), the crucial disadvantage is there are only some positions of skeleton that can be used to specify gender such as supraorbital ridge, nuchal crest, temporal lobe, mandible, and chin. Therefore, the skeletal remains that will be used have to be complete. The other technique that is widely used for gender specifying in forensic science and archeology is skeletal measurements. The advantage of this method is it can be used in several positions in one piece of bones, and it can be used even if the bones are not complete. In this study, the classification and cluster analysis are applied to this technique, including the Kth Nearest Neighbor Classification, Classification Tree, Ward Linkage Cluster, K-mean Cluster, and Two Step Cluster. The data contains 507 particular individuals and 9 skeletal measurements (diameter measurements), and the performance of five methods are investigated by considering the apparent error rate (APER). The results from this study indicate that the Two Step Cluster and Kth Nearest Neighbor method seem to be suitable to specify gender from human skeletal remains because both yield small apparent error rate of 0.20% and 4.14%, respectively. On the other hand, the Classification Tree, Ward Linkage Cluster, and K-mean Cluster method are not appropriate since they yield large apparent error rate of 10.65%, 10.65%, and 16.37%, respectively. However, there are other ways to evaluate the performance of classification such as an estimate of the error rate using the holdout procedure or misclassification costs, and the difference methods can make the different conclusions.

Keywords: skeletal measurements, classification, cluster, apparent error rate

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Authors: Fathi M. O. Hamed, Salma F. Elkofhaifee

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The aim of this work is to detect geometrical shape objects in an image. In this paper, the object is considered to be as a circle shape. The identification requires find three characteristics, which are number, size, and location of the object. To achieve the goal of this work, this paper presents an algorithm that combines from some of statistical approaches and image analysis techniques. This algorithm has been implemented to arrive at the major objectives in this paper. The algorithm has been evaluated by using simulated data, and yields good results, and then it has been applied to real data.

Keywords: image processing, median filter, projection, scale-space, segmentation, threshold

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Authors: Recep Kesli, Gulşah Asik, Cengiz Demir, Onur Turkyilmaz

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Objective: Acinetobacter baumannii (A. baumannii) can cause health-care associated infections, such as bacteremia, urinary tract and wound infections, endocarditis, meningitis, and pneumonia, particularly in intensive care unit patients. In this study, we aimed to evaluate A. baumannii production in sputum and bronchoalveolar lavage and susceptibilities for antibiotics in a 24 months period. Methods: Between October 2013 and September 2015, Acinetobacter baumannii isolated from respiratory tract speciments were evaluated retrospectively. The strains were isolated from the different intensive care units patients. A. baumannii strains were identified by both the conventional methods and aoutomated identification system -VITEK 2 (bio-Merieux, Marcy l’etoile, France). Antibiotic resistance testing was performed by Kirby-Bauer disc diffusion method according to CLSI criteria. Results: All the ninety isolates included in the study were from respiratory tract specimens. While of all the isolated 90 Acinetobacter baumannii strains were found to be resistant (100%), against ceftriaxone, ceftazidime, ciprofloxacin and piperacillin/ tazobactam, resistance rates against other tested antibiotics found as follows; meropenem 77, 86%, imipenem 75, 83%, trimethoprim-sulfamethoxazole (TMP-STX) 69, 76,6%, gentamicin 51, 56,6% and amikacin 48, 53,3%. Colistin was found as the most effective antibiotic against Acinetobacter baumannii, and there were not found any resistant (0%) strain against colistin. Conclusion: This study demonstrated that the no resistance was found in Acinetobacter baumannii against to colistin. High rates of resistance to carbapenems (imipenem and meropenem) and other tested antibiotics (ceftiaxone, ceftazidime, ciprofloxacine, piperacilline-tazobactam, TMP-STX gentamicin and amikacin) also have remarkable resistance rates. There was a significant relationship between demographic features of patients such as age, undergoing mechanical ventilation, length of hospital stay with resistance rates. High resistance rates against antibiotics require implementation of the infection control program and rational use of antibiotics. In the present study, while there were not found colistin resistance, panresistance were found against to ceftriaxone, ceftazidime, ciprofloxacin and piperacillin/ tazobactam.

Keywords: acinetobacter baumannii, antibiotic resistance, multi drug resistance, intensive care unit

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Authors: Jakub Młoźniak, Adam Szymański, Gabriela Stondzik, Dagny Krankowska, Tomasz Mikuła

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Nontuberculous mycobacteria (NTM) are bacterial species that cause diversely manifesting diseases mainly in immunocompromised patients. In people with HIV, NTM infection is an AIDS-defining disease and usually appears when the lymphocyte T CD4 count is below 50 cells/μl. The usage of antiretroviral therapy has decreased the prevalence of NTM among people with HIV, but the disease can still be observed especially among patients with late HIV diagnosis. Common presence in environment, human colonization, clinical similarity with tuberculosis and slow growth on culture makes NTM especially hard to diagnose. The study aimed to analyze the epidemiology and clinical course of NTM among patients with HIV. This study included patients with NTM and HIV admitted to our department between 2017 and 2023. Medical records of patients were analyzed and data on age, sex, median time from HIV diagnosis to identification of NTM infection, median CD4 count at NTM diagnosis, methods of determining NTM infection, type of species of mycobacteria identified, clinical symptoms and treatment course were gathered. Twenty-four patients (20 men, 4 women) with identified NTM were included in this study. Among them, 20 were HIV late presenters. The patients' median age was 40. The main symptoms which patients presented were fever, weight loss and cough. Pulmonary disease confirmed with positive cultures from sputum/bronchoalveolar lavage was present in 18 patients. M. avium was the most common species identified. M. marinum caused disseminated skin lesions in 1 patient. Out of all, 5 people were not treated for NTM caused by lack of symptoms and suspicion of colonization with mycobacterium. Concomitant tuberculosis was present in 6 patients. The median diagnostic time from HIV to NTM infections was 3.5 months. The median CD4 count at NTM identification was 69.5 cells/μl. Median NTM treatment time was 16 months but 7 patients haven’t finished their treatment yet. The most commonly used medications were ethambutol and clarithromycin. Among analyzed patients, 4 of them have died. NTM infections are still an important disease among patients who are HIV late presenters. This disease should be taken into consideration during the differential diagnosis of fever, weight loss and cough in people with HIV with lymphocyte T CD4 count <100 cells/μl. Presence of tuberculosis does not exclude nontuberculous mycobacterium coinfection.

Keywords: mycobacteriosis, HIV, late presenter, epidemiology

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Authors: Amanda T. Badaró, Douglas F. Barbin, Sofia T. Garcia, Maria Teresa P. S. Clerici, Amanda R. Ferreira

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Food fortification is the intentional addition of a nutrient in a food matrix and has been widely used to overcome the lack of nutrients in the diet or increasing the nutritional value of food. Fortified food must meet the demand of the population, taking into account their habits and risks that these foods may cause. Wheat and its by-products, such as semolina, has been strongly indicated to be used as a food vehicle since it is widely consumed and used in the production of other foods. These products have been strategically used to add some nutrients, such as fibers. Methods of analysis and quantification of these kinds of components are destructive and require lengthy sample preparation and analysis. Therefore, the industry has searched for faster and less invasive methods, such as Near-Infrared Spectroscopy (NIR). NIR is a rapid and cost-effective method, however, it is based on indirect measurements, yielding high amount of data. Therefore, NIR spectroscopy requires calibration with mathematical and statistical tools (Chemometrics) to extract analytical information from the corresponding spectra, as Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA). PCA is well suited for NIR, once it can handle many spectra at a time and be used for non-supervised classification. Advantages of the PCA, which is also a data reduction technique, is that it reduces the data spectra to a smaller number of latent variables for further interpretation. On the other hand, LDA is a supervised method that searches the Canonical Variables (CV) with the maximum separation among different categories. In LDA, the first CV is the direction of maximum ratio between inter and intra-class variances. The present work used a portable infrared spectrometer (NIR) for identification and classification of pure and fiber-fortified semolina samples. The fiber was added to semolina in two different concentrations, and after the spectra acquisition, the data was used for PCA and LDA to identify and discriminate the samples. The results showed that NIR spectroscopy associate to PCA was very effective in identifying pure and fiber-fortified semolina. Additionally, the classification range of the samples using LDA was between 78.3% and 95% for calibration and 75% and 95% for cross-validation. Thus, after the multivariate analysis such as PCA and LDA, it was possible to verify that NIR associated to chemometric methods is able to identify and classify the different samples in a fast and non-destructive way.

Keywords: Chemometrics, fiber, linear discriminant analysis, near-infrared spectroscopy, principal component analysis, semolina

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Authors: Muhammad Shahid Shah, Akram Maqbool, Samina Ashraf

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Since start of this century, world has adopted inclusion as a trend in special education. To meet the challenges of inclusion response, the Punjab government has developed a progressive policy to implement inclusive education. The objectives of this research were to analyze the administration and implementation process by consideration on the management, student’s admission process, screening and assessment, adaptations in curriculum and instruction along with an evaluation, government and nonprofit organizations support. The sample consisted of 50 schools both public and private with a total of 3000 students, 9 percent of which (270) were students with disabilities. Among all the students with disabilities, 63 percent (170) were male and 37 percent (100) were female. The concluded remarks regarding management revealed that a large number of inclusive schools was lacking in terms of developing a certain model for inclusion, including the managerial breakup of staff, the involvement of stakeholders, and conducted frequent meetings. Many of schools are not able to restructure their school organizations due to lack of financial resources, consultations, and backup. As for as student’s admission/identification/assessment was concerned, only 12 percent schools applied a selection process regarding student admission, half of which used different procedures for disable candidates. Approximately 5 percent of inclusive schools had modified their curriculum, including a variety of standards. In terms of instruction, 25 percent of inclusive schools reported that they modified their instructional process. Only a few schools, however, provided special equipment for students with visual impairment, physical impairment, speech and hearing problems, students with mild intellectual disabilities, and autism. In a student evaluation, more than 45 percent reported that test items, administration, time allocations, and students’ reports were modified. For the primary board examination conducted by the Education Department of Government of Punjab, this number decreased dramatically. Finally, government and nonprofit organizations support in the forms of funding, coaching, and facilities were mostly provided by provincial governments and by Ghazali Education Trust.

Keywords: inclusion, identification, assessment, funding, facilities, evaluation

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