Search results for: community-based monitoring

Authors: Laura Valdés-Santiago, José Luis Castro-Guillén, Jorge Noé García-Chávez, Rosalba Alonso-Rodríguez, Rafael Vargas-Bernal

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The quality and availability of the water contained in dams (artificial bodies of water) are at risk due to the presence of uncontrolled growths of cyanobacteria capable of producing cyanotoxins that affect the ecosystem and harm the health of humans and animals. The physicochemical properties were measured, and the degree of eutrophy of four dams from Guanajuato was determined. They presented a pH of 6.1 to 8.4, conductivity of 121 to 415 μS/cm², chlorophyll of 0.43-42.43 μg/L, NO₃- 0-1.2 mg/L and PO₄3- 0.11 to 0.84 mg/L; considering these parameters, the prey most prone to the development of cyanobacterial blooms were El Palote dam, La Purísima dam, and Allende dam, but not El Conejo dam. The potentially toxic cyanobacteria identified were Planktothrix agardhii, Oscillatoria sp., Raphidiopsis sp., and Microcystis sp., Microcystin-LR, Nodularin, and Cylindrospermopsin were quantified, presenting values between 0.08-0.42 and 0.02-2.05 ppb, respectively, the water bodies with the highest concentration were El Palote dam and La Purísima dam. Microcystin-LR and/or Nodularin levels are within the guideline values for human consumption in drinking water established by the World Health Organization for Microcystin-LR and for Cylindrospermopsin by the Oregon Health Authority (OHA) in all dams. This work is relevant due to the use of these bodies of water for agriculture and human consumption in the state, and the presence of toxin-producing cyanobacteria can represent an environmental, ecotoxicological, and health problem, so it is recommended to establish a program of frequent monitoring of cyanobacteria and cyanotoxins in the state's dams.

Keywords: Planktrothrix agardhii, Raphidiopsis sp., Microcystis sp., Cyanobacterial blooms, Cyanotoxins

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Authors: Goodness Onwuka, Khaled Abou-El-Hossein

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Borosilicate-crown (BK7) glass has found broad application in the optic and automotive industries and the growing demands for nanometric surface finishes is becoming a necessity in such applications. Thus, it has become paramount to optimize the parameters influencing the surface roughness of this precision lens. The research was carried out on a 4-axes Nanoform 250 precision lathe machine with an ultra-high precision grinding spindle. The experiment varied the machining parameters of feed rate, wheel speed and depth of cut at three levels for different combinations using Box Behnken design of experiment and the resulting surface roughness values were measured using a Taylor Hobson Dimension XL optical profiler. Acoustic emission monitoring technique was applied at a high sampling rate to monitor the machining process while further signal processing and feature extraction methods were implemented to generate the input to a neural network algorithm. This paper highlights the training and development of a back propagation neural network prediction algorithm through careful selection of parameters and the result show a better classification accuracy when compared to a previously developed response surface model with very similar machining parameters. Hence artificial neural network algorithms provide better surface roughness prediction accuracy in the ultra-high precision grinding of BK7 glass.

Keywords: acoustic emission technique, artificial neural network, surface roughness, ultra-high precision grinding

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Authors: Sezen Gurdag, Ayse Ebru Akin

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There is a growing concern all over the world on the health effect of the formaldehyde emission coming from the adhesive used in the MDF production. In this research, we investigated the effect of nanoparticle addition such as nanoclay and halloysite into urea-formadehyde resin on the total emitted formaldehyde from MDF plates produced using the resin modified as such. First, the curing behavior of the resin was studied by monitoring the pH, curing time, solid content, density and viscosity of the modified resin in comparison to the reference resin with no added nanoparticle. The dosing of the nanoparticle in the dry resin was kept at 1wt%, 3wt% or 5wt%. Consecutively, the resin was used in the production of 50X50 cm MDF samples using laboratory scale press line with full automation system. Modulus of elasticity, bending strength, internal bonding strength, water absorption were also measured in addition to the main interested parameter formaldehyde emission levels which is determined via spectrometric technique following an extraction procedure. Threshold values for nanoparticle dosing levels were determined to be 5wt% for both nanoparticles. However, the reinforcing behavior was observed to be occurring at different levels in comparison to the reference plates with each nanoparticle such that the level of reinforcement with nanoclay was shown to be more favorable than the addition of halloysite due to higher surface area available with the former. In relation, formaldehyde emission levels were observed to be following a similar trend where addition of 5wt% nanoclay into the urea-formaldehyde adhesive helped decrease the formaldehyde emission up to 40% whereas addition of halloysite at its threshold level demonstrated as the same level, i.e., 5wt%, produced an improvement of 18% only.

Keywords: halloysite, nanoclay, fiberboard, urea-formaldehyde adhesive

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Authors: Mohsen Akhlaghi, Tahereh Ebrahimi

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Pricing strategy is a vital component in achieving the balance between customer value and business profitability. The aim of this study is to provide insights into the factors, techniques, and approaches involved in pricing decisions. The study utilizes a descriptive approach to discuss various aspects of pricing strategy in marketing, drawing on concepts from market research, consumer psychology, competitive analysis, and adaptability. This approach presents a comprehensive view of pricing decisions. The result of this exploration is a framework that highlights key factors influencing pricing decisions. The study examines how factors such as market positioning, product differentiation, and brand image shape pricing strategies. Additionally, it emphasizes the role of consumer psychology in understanding price elasticity, perceived value, and price-quality associations that influence consumer behavior. Various pricing techniques, including charm pricing, prestige pricing, and bundle pricing, are mentioned as methods to enhance sales by influencing consumer perceptions. The study also underscores the importance of adaptability in responding to market dynamics through regular price monitoring, dynamic pricing, and promotional strategies. It recognizes the role of digital platforms in enabling personalized pricing and dynamic pricing models. In conclusion, the study emphasizes that effective pricing strategies strike a balance between customer value and business profitability, ultimately driving sales, enhancing brand perception, and fostering lasting customer relationships.

Keywords: business, customer benefits, marketing, pricing

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Authors: Mariia Zhuldybina, Ahmed Moulay, Mirko Torres, Mike Rozel, Ngoc-Duc Trinh, Chloé Bois

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To reduce the global waste of perishable goods, a solution for monitoring and traceability of their environmental conditions is needed. Temperature is the most controllable environmental parameter determining the kinetics of physical, chemical, and microbial spoilage in food products. To store the time-temperature information, time-temperature indicator (TTI) is a promising solution. Printed electronics (PE) has shown a great potential to produce customized electronic devices using flexible substrates and inks with different functionalities. We propose to fabricate a hybrid printed TTI using environmentally friendly materials. The real-time TTI profile can be stored and transmitted to the smartphone via Near Field Communication (NFC). To ensure environmental performance, Canadian Green Electronics NSERC Network is developing green materials for the ink formulation with different functionalities. In terms of substrate, paper-based electronics has gained the great interest for utilization in a wide area of electronic systems because of their low costs in setup and methodology, as well as their eco-friendly fabrication technologies. The main objective is to deliver a prototype of TTI using small-scale printed techniques under typical printing conditions. All sub-components of the smart labels, including a memristor, a battery, an antenna compatible with NFC protocol, and a circuit compatible with integration performed by an offsite supplier will be fully printed with flexography or flat-bed screen printing.

Keywords: NFC, printed electronics, time-temperature indicator, hybrid electronics

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Authors: Mst Ilme Faridatul, Bo Wu

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Multi-temporal urban land cover mapping is of paramount importance for monitoring urban sprawl and managing the ecological environment. For diversified urban activities, it is challenging to map land covers in a complex urban environment. Spectral indices have proved to be effective for mapping urban land covers. To improve multi-temporal urban land cover classification and mapping, we evaluate the performance of three spectral indices, e.g. modified normalized difference bare-land index (MNDBI), tasseled cap water and vegetation index (TCWVI) and shadow index (ShDI). The MNDBI is developed to evaluate its performance of enhancing urban impervious areas by separating bare lands. A tasseled cap index, TCWVI is developed to evaluate its competence to detect vegetation and water simultaneously. The ShDI is developed to maximize the spectral difference between shadows of skyscrapers and water and enhance water detection. First, this paper presents a comparative analysis of three spectral indices using Landsat Enhanced Thematic Mapper (ETM), Thematic Mapper (TM) and Operational Land Imager (OLI) data. Second, optimized thresholds of the spectral indices are imputed to classify land covers, and finally, their performance of enhancing multi-temporal urban land cover mapping is assessed. The results indicate that the spectral indices are competent to enhance multi-temporal urban land cover mapping and achieves an overall classification accuracy of 93-96%.

Keywords: land cover, mapping, multi-temporal, spectral indices

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Authors: Yi-Fung Lin, Yuan-Mei Liao

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Background: Pain is common among patients with cancer and is also one of the most disturbing symptoms. As this suffering is subjective, if patients proactively participate in their pain self-management, pain could be alleviated effectively. However, not everyone can carry out self-management very well because human behavior is a product of the cognition process. In this process, we can see that "self-efficacy" plays an essential role in affecting human behaviors. Methods: We used the eight steps of concept analysis proposed by Walker and Avant to clarify the concept of “self-efficacy for cancer pain management.” A comprehensive literature review was conducted for relevant publications that were published during the period of 1977 to 2021. We used several keywords, including self-efficacy, self-management, concept analysis, conceptual framework, and cancer pain, to search the following databases: PubMed, CINAHL, Web of Science, and Embase. Results: We identified three defining attributes for the concept of self-efficacy for cancer pain management, including pain management abilities, confidence, and continuous pain monitoring, and recognized six skills related to pain management abilities: problem-solving, decision-making, resource utilization, forming partnerships between medical professionals and patients, planning actions, and self-regulation. Five antecedents for the concept of self-efficacy for cancer pain management were identified: pain experience, existing cancer pain, pain-related knowledge, a belief in pain management, and physical/mental state. Consequences related to self-efficacy for cancer pain management were achievement of pain self-management, well pain control, satisfying quality of life, and containing motivation. Conclusions: This analysis provides researchers with a clearer understanding of the concept of “self-efficacy for cancer pain management.” The findings presented here provide a foundation for future research and nursing interventions to enhance self-efficacy for cancer pain management.

Keywords: cancer pain, concept analysis, self-efficacy, self-management

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Authors: Ki-Ho Nam, Haksoo Han

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Tetrapod zinc oxide whiskers (TZnO-Ws) were successfully synthesized by a thermal oxidation method. A series of transparent polyimide (PI)/TZnO-W composites were successfully synthesized via a solution-blending method. The structural and morphological features of TZnO-Ws and PI/TZnO-W composites were characterized by Fourier transform infrared spectroscopy (FT-IR), wide-angle X-Ray diffraction (WAXD), and field emission scanning electron microscope (FE-SEM). Dynamic stress behaviors were investigated in-situ during thermal imidization of the soft-baked PI/TZnO-W composite precursor and thermally cured composite films using a thin film stress analyzer (TFSA) by wafer bending technique. The PI/TZnO-W composite films exhibited an optical transparency greater than 80% at 550 nm (≤ 0.5 wt% TZnO-W content), a low coefficient of thermal expansion (CTE), and enhanced glass transition temperature. However, the thermal decomposition temperature decreased as the TZnO-W content increased. The water diffusion coefficient and water uptake of the PI/TZNO-W composite films were obtained by best fits to a Fickian diffusion model. The water resistance capacity of PI was greatly enhanced and moisture diffusion in the pure PI was retarded by incorporating the TZnO-W. The PI composite films based on TZNO-W resultantly may have potential applications in optoelectronic manufacturing processes as a flexible transparent substrate.

Keywords: polyimide (PI), tetrapod ZnO whisker (TZnO-W), transparent, dynamic stress behavior, water resistance

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Authors: Usama Shahid, Muhammad Zunnurain Hussain

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This research paper presents a comprehensive analysis of a sentiment analysis approach that employs valence and arousal as its foundational pillars, in comparison to traditional techniques. Sentiment analysis is an indispensable task in natural language processing that involves the extraction of opinions and emotions from textual data. The valence and arousal dimensions, representing the intensity and positivity/negativity of emotions, respectively, enable the creation of four quadrants, each representing a specific emotional state. The study seeks to determine the impact of utilizing these quadrants to identify distinct emotional states on the accuracy and efficiency of sentiment analysis, in comparison to traditional techniques. The results reveal that the valence and arousal-based approach outperforms other approaches, particularly in identifying nuanced emotions that may be missed by conventional methods. The study's findings are crucial for applications such as social media monitoring and market research, where the accurate classification of emotions and opinions is paramount. Overall, this research highlights the potential of using valence and arousal as a framework for sentiment analysis and offers invaluable insights into the benefits of incorporating specific types of emotions into the analysis. These findings have significant implications for researchers and practitioners in the field of natural language processing, as they provide a basis for the development of more accurate and effective sentiment analysis tools.

Keywords: sentiment analysis, valence and arousal, emotional states, natural language processing, machine learning, text analysis, sentiment classification, opinion mining

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Authors: Ugochukwu Ejike Akpudo, Jank-Wook Hur

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The increasing demand for improved productivity, maintainability, and reliability has prompted rapidly increasing research studies on the emerging condition-based maintenance concept- Prognostics and health management (PHM). Varieties of fuel pumps serve critical functions in several hydraulic systems; hence, their failure can have daunting effects on productivity, safety, etc. The need for condition monitoring and assessment of these pumps cannot be overemphasized, and this has led to the uproar in research studies on standard feature extraction techniques for optimized condition assessment of fuel pumps. By extracting time-based, frequency-based and the more robust time-frequency based features from these vibrational signals, a more comprehensive feature assessment (and selection) can be achieved for a more accurate and reliable condition assessment of these pumps. With the aid of emerging deep classification and regression algorithms like the locally linear embedding (LLE), we propose a method for comprehensive condition assessment of electromagnetic fuel pumps (EMFPs). Results show that the LLE as a comprehensive feature extraction technique yields better feature fusion/dimensionality reduction results for condition assessment of EMFPs against the use of single features. Also, unlike other feature fusion techniques, its capabilities as a fault classification technique were explored, and the results show an acceptable accuracy level using standard performance metrics for evaluation.

Keywords: electromagnetic fuel pumps, comprehensive feature extraction, condition assessment, locally linear embedding, feature fusion

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Authors: Hang Ju, Changmin Zhu

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The development level of the BeiDou Navigation Satellite System (BDS) can strongly reflect national defense strength as an important spatial information infrastructure. BDS can be not only used for military purposes, such as intelligence gathering, nuclear explosion monitoring, emergency communications, but also for location services, transportation, mapping, precision agriculture. In order to ensure the national defense security and the wide application of BDS in civil and military areas, BDS must be autonomous and controllable. As a complex system of knowledge-intensive, knowledge transformation runs through the whole process of research and development, production, operation, and maintenance of BDS. Based on the perspective of knowledge transformation, this paper expounds on the meaning of socialization, externalization, combination, and internalization of knowledge transformation, and the coupling relationship of autonomy and control on the basis of analyzing the status quo and problems of the autonomy and control of BDS. The autonomous and controllable framework of BDS based on knowledge transformation is constructed from six dimensions of management capability, R&D capability, technical capability, manufacturing capability, service support capability, and application capability. It can provide support for the smooth implementation of information security policy, provide a reference for the autonomy and control of the upstream and downstream industrial chains in Beidou, and provide a reference for the autonomous and controllable research of aerospace components, military measurement test equipment, and other related industries.

Keywords: knowledge transformation, BeiDou Navigation Satellite System, autonomy and control, framework

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Authors: Abha Cherkani Hassani, Imane Ghanname, Nezha Mouane

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Background: This is the first systematic review summarizing 43 years of research from 36 countries in the assessment of cadmium in breast milk; a suitable matrix in human biomonitoring. Objectives: To report from the published literature the levels of cadmium in breast milk and the affecting factors causing the increase of cadmium concentrations; also to gather several quantitative data which might be useful to evaluate the international degrees of maternal and infant exposure. Methods: We reviewed the literature for studies reporting quantitative data about cadmium levels in human breast milk in the world that have been published between 1971 and 2014 and that are available on Pubmed, Science direct and Google scholar. The aim of the study, country, period of samples collection, size of samples, sampling method, time of lactation, mother’s age, area of residence, cadmium concentration and other information were extracted. Results: 67 studies were selected and included in this systematic review. Some concentrations greatly exceed the limit of the WHO, However about 50% of the studies had less than 1 µg/l cadmium concentration (the recommendation of the WHO); as well many factors have shown their implication in breast milk contamination by Cadmium as lactation stage, smoking, diet, supplement intake, interaction with other mineral elements, age of mothers, parity and other parameters. Conclusion: Breast milk is a pathway of maternal excretion of cadmium. It is also a biological indicator of the degree of environmental pollution and cadmium exposure of the lactating women and the nourished infant. Therefore preventive measures and continuous monitoring are necessary.

Keywords: breast milk, cadmium level, factors, systematic review

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Authors: Baker Ssekitto, Ambrose Mbogo

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The study reveals that indeed agriculture employs over 70% of Uganda’s population, of which majority are youth and women. The study further reveals that over 70% of the farmers are smallholder farmers based in rural areas, whose operations are greatly affected by; climate change, weak digital skills, limited access to productivity knowledge along value chains, limited access to quality farm inputs, weak logistics systems, limited access to quality extension services, weak business intelligence, limited access to quality markets among others. It finds that the emerging 4th industrial revolution powered by artificial intelligence, 5G and data science will provide possibilities of addressing some of these challenges. Furthermore, the study finds that despite rapid development of ICT4Agric Innovation, their uptake is constrained by a number of factors including; limited awareness of these innovations, low internet and smart phone penetration especially in rural areas, lack of appropriate digital skills, inappropriate programmes implementation models which are project and donor driven, limited articulation of value addition to various stakeholders among others. Majority of farmers and other value chain actors lacked knowledge and skills to harness the power of ICTs, especially their application of ICTs in monitoring and evaluation on quality of service in the extension system and farm level processes.

Keywords: artificial intelligence, productivity, ICT4agriculture, value chain, logistics

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Authors: Arash M. Shahidi, Tilak Dias, Gayani K. Nandasiri

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While graduated compression is the foundation of treatment and management of many medical complications such as leg ulcer, varicose veins, and lymphedema, monitoring the interface pressure has been conducted using different sensors that operate based on diverse approaches. The variations existed from the pressure readings collected using different interface pressure measurement systems would cause difficulties in taking a decision regarding the compression therapy. It is crucial to acknowledge the differences existing between direct and indirect pressure measurement systems while considering the commercially available systems such as AMI, Picopress and OPM which are under direct measurements systems, and HATRA (BSI), HOSY (RAL-GZ) and FlexiForce which comes under the indirect measurement system. Furthermore, Piezo-resistive sensors (Flexiforce) can measure the changes in resistance corresponding to the applied force on the sensing area. Direct pressure measuring systems are capable of measuring interface pressure on the three-dimensional states, while the indirect pressure measuring systems stretch the fabric in the two-dimensional direction and extrapolate pressure from surface tension measured on the device and neglect the vital factor which is the radius of curvature. In this study, a leg mannequin of known dimensions is selected with a knitted class 3 compression stocking. It has been decided to evaluate the data collected from different available systems (AMI, PicoPress, FlexiForce, and HATRA) and compare the results. The results showed a discrepancy between Hatra, AMI, Picopress, and Flexiforce against the pressure standard used to generate class 3 compression stocking. As predicted a higher pressure value with direct interface measuring systems were monitored against HATRA due to the effect of the radius of curvature.

Keywords: AMI, FlexiForce, graduated compression, HATRA, interface pressure, PicoPress

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Authors: Azizollah Khodakaram- Tafti, Ali Mohammadi, Ghasem Farjanikish

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Bovine viral diarrhea virus (BVDV) is one of the most important viral pathogens of cattle worldwide caused by Pestivirus genus, Flaviviridae family.The aim of the present study was to comparison several diagnostic methods and determine the prevalence of BVDV infection for the first time in dairy herds of Fars province, Iran. For initial screening, a total of 400 blood samples were randomly collected from 12 industrial dairy herds and analyzed using reverse transcription (RT)-PCR on the buffy coat. In the second step, blood samples and also ear notch biopsies were collected from 100 cattle of infected farms and tested by antigen capture ELISA (ACE), RT-PCR and immunohistochemistry (IHC). The results of nested RT-PCR (outer primers 0I100/1400R and inner primers BD1/BD2) was successful in 16 out of 400 buffy coat samples (4%) as acute infection in initial screening. Also, 8 out of 100 samples (2%) were positive as persistent infection (PI) by all of the diagnostic tests similarly including RT-PCR, ACE and IHC on buffy coat, serum and skin samples, respectively. Immunoreactivity for bovine BVDV antigen as brown, coarsely to finely granular was observed within the cytoplasm of epithelial cells of epidermis and hair follicles and also subcutaneous stromal cells. These findings confirm the importance of monitoring BVDV infection in cattle of this region and suggest detection and elimination of PI calves for controlling and eradication of this disease.

Keywords: antigen capture ELISA, bovine viral diarrhea virus, immunohistochemistry, RT-PCR, cattle

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Authors: Mohamed Ziyaina, Ahlam Rajab, Khadija Alkhweldi, Wafia Algami, Omer Al. Toumi, Barbara Rasco1

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In recent years, there has been a growing interest in monitoring heavy metal contamination in food products. Spices can improve the taste of food and can also be a source of many bioactive compounds but can unfortunately, also be contaminated with dangerous materials, potentially heavy metals. This study was conducted to investigate lead (Pb) and cadmium (Cd) contamination in selected spices commonly consumed in Libya including Capsicum frutescens (chili pepper) Piper nigrum, (black pepper), Curcuma longa (turmeric), and mixed spices (HRARAT) which consist of a combination of: Alpinia officinarum, Zingiber officinale and Cinnamomum zeylanicum. Spices were analyzed by atomic absorption spectroscopy after digestion with nitric acid/hydrogen peroxide. The highest level of lead (Pb) was found in Curcuma longa and Capsicum frutescens in wholesale markets (1.05 ± 0.01 mg/kg, 0.96 ± 0.06 mg/kg). Cadmium (Cd) levels exceeded FAO/WHO permissible limit. Curcuma longa and Piper nigrum sold in retail markets had a high concentration of Cd (0.36 ± 0.09, 0.35 ± 0.07 mg/kg, respectively) followed by (0.32 ± 0.04 mg/kg) for Capsicum frutescens. Mixed spices purchased from wholesale markets also had high levels of Cd (0.31 ± 0.08 mg/kg). Curcuma longa and Capsicum frutescens may pose a food safety risk due to high levels of lead and cadmium. Cadmium levels exceeded FAO/WHO recommendations (0.2 ppm) for Piper nigrum, Curcuma longa, and mixed spices (HRARAT).

Keywords: heavy metals, lead, cadmium determination, spice

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Authors: Abdelrahman Elsehsah, Abdelazim Negm, Eid Ashour, Mohamed Elsahabi

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Water resources management is a critical field that encompasses the planning, development, conservation, and allocation of water resources to meet societal needs while ensuring environmental sustainability. This paper reviews the key concepts and challenges in water resources management, emphasizing the significance of a holistic approach that integrates social, economic, and environmental factors. Traditional water management practices, characterized by supply-oriented strategies and centralized control, are increasingly inadequate in addressing contemporary challenges such as water scarcity, climate change impacts, and ecosystem degradation. Emerging technologies, particularly machine learning and remote sensing, offer innovative solutions to enhance decision-making processes in water management. Machine learning algorithms facilitate accurate water demand forecasting, quality monitoring, and leak detection, while remote sensing technologies provide vital data for assessing water availability and quality. This review highlights the need for integrated water management strategies that leverage these technologies to promote sustainable practices and foster resilience in water systems. Future research should focus on improving data quality, accessibility, and the integration of diverse datasets to optimize the benefits of these technological advancements.

Keywords: water resources management, water scarcity, climate change, machine learning, remote sensing, water quality, water governance, sustainable practices, ecosystem management

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Authors: Tukundane Hillary

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This research paper analytically evaluates the project control practice levels used by the building construction companies within Kampala, Uganda. The research also assesses the outcome of project control practices on the productivity of the companies. The research was performed to ascertain the current control practices among 160 respondents from various construction companies registered with the Uganda Registration Services Bureau. This research used amalgamation from multiple literature to obtain the variables. The research adopts 34 standard control practices from four vital project control duties: planning, monitoring, analyzing, and reporting. These project control tasks were organized using mean response ratings grounded on their relevance to the construction companies. Results showed that evaluating performance with the use of curves (4.32), timely access to information and encouragement (4.55), report representation using quantitative tools 4.75, and cost value comparison application during analysis (4.76) were rated least among the control practices. On the other hand, the top project control practices included formulation of the project schedule (8.88), Project feasibility validation (8.86), Budgeting for each activity (8.84), Key project route definition (8.81), Team awareness of the budget (8.77), Setting realistic targets for projects (8.50) and Consultation from subcontractors (8.74). From the results obtained by the sample respondents specified, it can be concluded that planning is the most vital project control task practiced in the building construction industry in Uganda. In addition, this research ascertained a substantial relationship between project control practices and the performance of building construction companies. Accordingly, this research recommends that project control practices be effectively observed by both contracting and consulting companies to enhance their overall performance and governance.

Keywords: cost value, project control, cost control, time control, project performance, control practices

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Authors: Yulin Rao, Zhixuan Li, Burra Venkata Durga Kumar

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Intrusion detection refers to monitoring the actions of internal and external intruders on the system and detecting the behaviours that violate security policies in real-time. In intrusion detection, there has been much discussion about the application of neural network technology and artificial immune system (AIS). However, many solutions use static methods (signature-based and stateful protocol analysis) or centralized intrusion detection systems (CIDS), which are unsuitable for real-time intrusion detection systems that need to process large amounts of data and detect unknown intrusions. This article proposes a framework for a distributed intrusion detection system (DIDS) with multi-agents based on the concept of AIS and neural network technology to detect anomalies and intrusions. In this framework, multiple agents are assigned to each host and work together, improving the system's detection efficiency and robustness. The trainer agent in the central server of the framework uses the artificial neural network (ANN) rather than the negative selection algorithm of AIS to generate mature detectors. Mature detectors can distinguish between self-files and non-self-files after learning. Our analyzer agents use genetic algorithms to generate memory cell detectors. This kind of detector will effectively reduce false positive and false negative errors and act quickly on known intrusions.

Keywords: artificial immune system, distributed artificial intelligence, multi-agent, intrusion detection system, neural network

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Authors: Adnan Ahmad, Yusri Kamin, Asnol Dahar Minghat, Mohd. Khir Nordin, Dayana Farzeha, Ahmad Nabil

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The purpose of this study is to identify the teaching method practices of the practical work subject in Vocational Secondary School. This study examined the practice of Vocational Teaching Method in Automotive Practical Work. The quantitative method used the sets of the questionnaire. 283 students and 63 teachers involved from ten VSS involved in this research. Research finding showed in conducting the introduction session teachers prefer used the demonstration method and questioning technique. While in deliver the content of practical task, teachers applied group monitoring and problem-solving approach. To conclude the task of automotive practical work, teachers choose re-explain and report writing to make sure students really understand all the process of teaching. VTM-APW also involved the competency-based concept to embed in the model. Derived from factors investigated, research produced the combination of elements in teaching skills and vocational skills which could be used as the best teaching method in automotive practical work for school level. As conclusion this study has concluded that the VTM-APW model is able to apply in teaching to make an improvement with current practices in Vocational Secondary School. Hence, teachers are suggested to use this method to enhance student's knowledge in Automotive and teachers will deliver skills to the current and future workforce relevant with the required competency skilled in workplace.

Keywords: vocational teaching method, practical task, teacher preferences, student preferences

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Authors: Tebogo Emma Makaba, Barnabas Ndlovu Gatsheni

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The cities of Johannesburg and Pretoria both located in the Gauteng province are separated by a distance of 58 km. The traffic queues on the Ben Schoeman freeway which connects these two cities can stretch for almost 1.5 km. Vehicle traffic congestion impacts negatively on the business and the commuter’s quality of life. The goal of this paper is to identify variables that influence the flow of traffic and to design a vehicle traffic prediction model, which will predict the traffic flow pattern in advance. The model will unable motorist to be able to make appropriate travel decisions ahead of time. The data used was collected by Mikro’s Traffic Monitoring (MTM). Multi-Layer perceptron (MLP) was used individually to construct the model and the MLP was also combined with Bagging ensemble method to training the data. The cross—validation method was used for evaluating the models. The results obtained from the techniques were compared using predictive and prediction costs. The cost was computed using combination of the loss matrix and the confusion matrix. The predicted models designed shows that the status of the traffic flow on the freeway can be predicted using the following parameters travel time, average speed, traffic volume and day of month. The implications of this work is that commuters will be able to spend less time travelling on the route and spend time with their families. The logistics industry will save more than twice what they are currently spending.

Keywords: bagging ensemble methods, confusion matrix, multi-layer perceptron, vehicle traffic flow

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Authors: Siwanit Autthawuttikul, Prakob Koraneekid, Sayamon Insa-ard

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The purposes of this research were to development creatively integrated teaching skills using Information and Communication Technology (ICT) for professional teacher in schools under the education area of the basic education commission, ministry of education both schools under the office of primary education and those under The office of secondary education in eight western region provinces of Thailand. This is useful in defining a vision for the school strategy and restructuring schools in addition, teachers will have developed skills in teaching creative integrated ICT. The research methodology comprises quantitative and qualitative data collection. The Baseline Survey, focus group for discussions and then the model was developed creatively integrated teaching skills using ICT. The findings showed that 7 elements were important: (1) Academy Transformation (2) Information Technology Infrastructure (3) Personal Development (4) Supervision, Monitoring and Evaluation (5) Motivating and Rewarding (6) Important factor affecting the success of teaching integrated with ICT were knowledge, skills, attitudes and (7) The role of the individual concerned. The comparison creatively integrated teaching skills before and after participating in the overall shows that the average creatively integrated teaching skills using ICT after attending the event is 3.27, and standard deviation was 0.56, higher than before which is 2.60 and the standard deviation was 0.56. There are significant differences significant statistically level of .05. The final average score of the evaluation plan design creatively integrated teaching skills using ICT teachers' average score was 26.94 at the high levels.

Keywords: integrated curriculum, information and communications technology, teachers in the western region, schools

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Authors: Issam Jebreen, Eman Al-Qbelat

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Outsourcing software development projects can be challenging, and there are several common challenges that organizations face. A study was conducted with a sample of 46 papers on outsourcing challenges, and the results show that there are several common challenges faced by organizations when outsourcing software development projects. Poor outsourcing relationship was identified as the most significant challenge, with 35% of the papers referencing it. Lack of quality was the second most significant challenge, with 33% of the papers referencing it. Language and cultural differences were the third most significant challenge, with 24% of the papers referencing it. Non-competitive price was another challenge faced by organizations, with 21% of the papers referencing it. Poor coordination and communication were also identified as a challenge, with 21% of the papers referencing it. Opportunistic behavior, lack of contract negotiation, inadequate user involvement, and constraints due to time zone were also challenges faced by organizations. Other challenges faced by organizations included poor project management, lack of technical capabilities, vendor employee high turnover, poor requirement specification, IPR issues, poor management of budget, schedule, and delay, geopolitical and country instability, the difference in development methodologies, failure to manage end-user expectations, and poor monitoring and control. In conclusion, outsourcing software development projects can be challenging, but organizations can mitigate these challenges by selecting the right outsourcing partner, having a well-defined contract and clear communication, having a clear understanding of the requirements, and implementing effective project management practices.

Keywords: software outsourcing, vendor, outsourcing challenges, quality model, continent, country, global outsourcing, IT workforce outsourcing.

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Authors: Sandeep Thakur, Ismail Mondal, Phani Bhusan Ghosh, Papita Das, Tarun Kumar De

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Sundarbans Reserve forest of India has been undergoing major transformations in the recent past owing to population pressure and related changes. This has brought about major changes in the spatial landscape of the region especially in the western parts. This study attempts to assess the impacts of the Landcover changes on the mangrove habitats. Time series imageries of Landsat were used to analyze the Normalized Differential Vegetation Index (NDVI) patterns over the western parts of Indian Sundarbans forest in order to assess the heath of the mangroves in the region. The images were subjected to Land use Land cover (LULC) classification using sub-pixel classification techniques in ERDAS Imagine software and the changes were mapped. The spatial proliferation of aquaculture farms during the study period was also mapped. A multivariate regression analysis was carried out between the obtained NDVI values and the LULC classes. Similarly, the observed meteorological data sets (time series rainfall and minimum and maximum temperature) were also statistically correlated for regression. The study demonstrated the application of NDVI in assessing the environmental status of mangroves as the relationship between the changes in the environmental variables and the remote sensing based indices felicitate an efficient evaluation of environmental variables, which can be used in the coastal zone monitoring and development processes.

Keywords: aquaculture farms, LULC, Mangrove, NDVI

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Authors: Aljon Pangan

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The Philippines being an archipelagic country, is surrounded by coastlines (36,289 km), coastal waters (226,000 km²), oceanic waters (1.93 million km²) and territorial waters (2.2 million km²). Studies show that the Philippine coastal ecosystems are the most productive and biologically diverse in the world, however, plagued by degradation problems due to over-exploitation and illegal activities. The existence of coastal degradation issues in the country led to the emergence of Coastal Resource Management (CRM) as an approach to both national and local government in providing solutions for sustainable coastal resource utilization. CRM applies the idea of planning, implementing and monitoring through the lens of collaborative governance. It utilizes collective action and decision-making to achieve sustainable use of coastal resources. The Municipality of Bagac in Bataan is one of the coastal municipalities in the country who crafts its own CRM Program as a solution to coastal resource degradation and problems. Information and Communications Technology (ICT), particularly Integrated Imaging Management System (IIMS) is one approach that can be applied in the formula of collaborative governance which entails the Government, Private Sector, and Civil Society. IIMS can help policymakers, managers, and citizens in managing coastal resources through analyzed spatial data describing the physical, biological, and socioeconomic characteristics of the coastal areas. Moreover, this study will apply the qualitative approach in deciphering possible impacts of the application of IIMS in the Coastal Resource Management policy making and implementation of the Municipality of Bagac.

Keywords: coastal resource management, collaborative governance, integrated imaging management system, information and communication technology

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Authors: Nabaweesi Josephine, Namwanje Regina Germina

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Antenatal care is referred to as the totality of care given to pregnant women from conception to delivery from a certified health care setting. A number of 8 contacts is recommended throughout pregnancy, according to WHO, 2016. Antenatal services are free in Uganda courtesy of the government of Uganda, though attendance is still very low, which has continued to cause maternal and infant mortality and morbidity from preventable causes. Early booking has an advantage for proper pregnancy information sharing and pregnancy monitoring. The purpose of this study was to determine pregnant women's knowledge, attitudes, and practices towards attendance of antenatal care at Mukono General Hospital. A sample of 60 pregnant women was used, and a descriptive quantitative design was employed. Data was collected using a structured questionnaire consisting of questions about socio-demographic factors, knowledge, attitude, and practice, and this was affected using the structured interview method. Pregnant women had good practice at 90.2%, a positive attitude of 94.6%, and slightly less knowledge of 66.7%. Only 12% were knowledgeable about the number of antenatal care visits recommended, 45% had knowledge about when to initiate first antenatal care visit, and 79% had a positive attitude towards the early booking. We recommend that pregnant women are given all the necessary information regarding antenatal care with special emphasis on the recommended number of visits and when to initiate their first visit and encourage early booking in order to achieve the 8 contacts WHO policy for antenatal care since when we increase knowledge, we increase antenatal care utilization according to Anderson's behavioral model.

Keywords: ANC- antenatal care, contacts, mortality, morbidity

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Authors: Richard Molyneux, Christopher Parrott, Kirill Horoshenkov

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This paper aims to demonstrate how various algorithms can be implemented within swarms of autonomous robots to provide continuous inspection within underground pipeline networks. Current methods of fault detection within pipes are costly, time consuming and inefficient. As such, solutions tend toward a more reactive approach, repairing faults, as opposed to proactively seeking leaks and blockages. The paper presents an efficient inspection method, showing that autonomous swarm robotics is a viable way of monitoring underground infrastructure. Tailored adaptations of various Vehicle Routing Problems (VRP) and path-planning algorithms provide a customised inspection procedure for complicated networks of underground pipes. The performance of multiple algorithms is compared to determine their effectiveness and feasibility. Notable inspirations come from ant colonies and stigmergy, graph theory, the k-Chinese Postman Problem ( -CPP) and traffic theory. Unlike most swarm behaviours which rely on fast communication between agents, underground pipe networks are a highly challenging communication environment with extremely limited communication ranges. This is due to the extreme variability in the pipe conditions and relatively high attenuation of acoustic and radio waves with which robots would usually communicate. This paper illustrates how to optimise the inspection process and how to increase the frequency with which the robots pass each other, without compromising the routes they are able to take to cover the whole network.

Keywords: autonomous inspection, buried pipes, stigmergy, swarm intelligence, vehicle routing problem

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Authors: Zhu Weimin, Allegorico Carmine, Ruggiero Gionata

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During decades of Baker Hughes (BH) iCenter experience, it is demonstrated that in addition to conventional insights on equipment steady operation conditions, insights on transient conditions can add significant and exclusive value for anomaly detection, downtime saving, and predictive maintenance. Our work shows examples from the BH iCenter experience to introduce the advantages and features of using transient condition analytics: (i) Operation under critical engine conditions: e.g., high level or high change rate of temperature, pressure, flow, vibration, etc., that would not be reachable in normal operation, (ii) Management of dedicated sub-systems or components, many of which are often bottlenecks for reliability and maintenance, (iii) Indirect detection of anomalies in the absence of instrumentation, (iv) Repetitive sequences: if data is properly processed, the engineering features of transients provide not only anomaly detection but also problem characterization and prognostic indicators for predictive maintenance, (v) Engine variables accounting for fatigue analysis. iCenter has been developing and deploying a series of analytics based on transient conditions. They are contributing to exclusive value adding in the following areas: (i) Reliability improvement, (ii) Startup reliability improvement, (iii) Predictive maintenance, (iv) Repair/overhaul cost down. Illustrative examples for each of the above areas are presented in our study, focusing on challenges and adopted techniques ranging from purely statistical approaches to the implementation of machine learning algorithms. The obtained results demonstrate how the value is obtained using transient condition analytics in the BH iCenter experience.

Keywords: analytics, diagnostics, monitoring, turbomachinery

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Authors: Abdessalam Hijab, Hafida Boulekbache, Eric Henry

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According to several research studies, the city as a whole is a complex, spatially organized system; its modeling must take into account several factors, socio-economic, and political, or geographical, acting at multiple scales of observation according to varied temporalities. Sustainable management and protection of the environment in this complex system require significant human and technical investment, particularly for monitoring and maintenance. The objective of this paper is to propose an intelligent approach based on the coupling of Geographic Information System (GIS) and Information and Communications Technology (ICT) tools in order to integrate the inhabitants in the processes of sustainable management and protection of the urban environment, specifically in the processes of household waste collection in urban areas. We are discussing a collaborative 'city/inhabitant' space. Indeed, it is a geo-collaborative approach, based on the spatialization and real-time geo-localization of topological and multimedia data taken by the 'active' inhabitant, in the form of geo-localized alerts related to household waste issues in their city. Our proposal provides a good understanding of the extent to which civil society (inhabitants) can help and contribute to the development of complementary solutions for the collection of household waste and the protection of the urban environment. Moreover, it allows the inhabitant to contribute to the enrichment of a data bank for future uses. Our geo-collaborative model will be tested in the Lamkansa sampling district of the city of Casablanca in Morocco.

Keywords: geographic information system, GIS, information and communications technology, ICT, geo-collaboration, inhabitants, city

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Authors: Ateeth Shetty, K. S. Jayappa, Ratheesh Ramakrishnan, A. S. Rajawat

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Suspended Sediment Concentration (SSC) was estimated for the period of four months (November, 2013 to February 2014) using Oceansat-2 (Ocean Colour Monitor) satellite images to understand the coastal dynamics and regional sediment transport, especially distribution and budgeting in coastal waters. The coastal zone undergoes continuous changes due to natural processes and anthropogenic activities. The importance of the coastal zone, with respect to safety, ecology, economy and recreation, demands a management strategy in which each of these aspects is taken into account. Monitoring and understanding the sediment dynamics and suspended sediment transport is an important issue for coastal engineering related activities. A study of the transport mechanism of suspended sediments in the near shore environment is essential not only to safeguard marine installations or navigational channels, but also for the coastal structure design, environmental protection and disaster reduction. Such studies also help in assessment of pollutants and other biological activities in the region. An accurate description of the sediment transport, caused by waves and tidal or wave-induced currents, is of great importance in predicting coastal morphological changes. Satellite-derived SSC data have been found to be useful for Indian coasts because of their high spatial (360 m), spectral and temporal resolutions. The present paper outlines the applications of state‐of‐the‐art operational Indian Remote Sensing satellite, Oceansat-2 to study the dynamics of sediment transport.

Keywords: suspended sediment concentration, ocean colour monitor, sediment transport, case – II waters

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