Search results for: enhanced data encryption

Authors: Shael Brown, Reza Farivar

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Persistence diagrams capture valuable topological features of datasets that other methods cannot uncover. Still, their adoption in data pipelines has been limited due to the lack of publicly available tools in R (and python) for analyzing groups of them with machine learning and statistical inference. In an easy-to-use and scalable R package called TDApplied, we implement several applied analysis methods tailored to groups of persistence diagrams. The two main contributions of our package are comprehensiveness (most functions do not have implementations elsewhere) and speed (shown through benchmarking against other R packages). We demonstrate applications of the tools on simulated data to illustrate how easily practical analyses of any dataset can be enhanced with topological information.

Keywords: machine learning, persistence diagrams, R, statistical inference

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Authors: Ansah Iris Baffour, Dong-Ho Kim, Sung-Gyu Park

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The ongoing COVID-19 pandemic, caused by the SARS-CoV-2 virus and is gradually shifting to an endemic phase which implies the outbreak is far from over and will be difficult to eradicate. Global cooperation has led to unified precautions that aim to suppress epidemiological spread (e.g., through travel restrictions) and reach herd immunity (through vaccinations); however, the primary strategy to restrain the spread of the virus in mass populations relies on screening protocols that enable rapid on-site diagnosis of infections. Herein, we employed surface enhanced Raman spectroscopy (SERS) for the rapid detection of SARS-CoV-2 lysate on an Au-modified Au nanodimple(AuND)electrode. Through in situone-pot Au electrodeposition on the AuND electrode, Au-lysate nanocomposites were synthesized, generating3D internal hotspots for large SERS signal enhancements within 30 s of the deposition. The capture of lysate into newly generated plasmonic nanogaps within the nanocomposite structures enhanced metal-spike protein contact in 3D spaces and served as hotspots for sensitive detection. The limit of detection of SARS-CoV-2 lysate was 5 x 10-2 PFU/mL. Interestingly, ultrasensitive detection of the lysates of influenza A/H1N1 and respiratory syncytial virus (RSV) was possible, but the method showed ultimate selectivity for SARS-CoV-2 in lysate solution mixtures. We investigated the practical application of the approach for rapid on-site diagnosis by detecting SARS-CoV-2 lysate spiked in normal human saliva at ultralow concentrations. The results presented demonstrate the reliability and sensitivity of the assay for rapid diagnosis of COVID-19.

Keywords: label-free detection, nanocomposites, SARS-CoV-2, surface-enhanced raman spectroscopy

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Authors: M. Lghoul, N. El Goumi, M. Guernouche

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In order to predict the structural and tectonic framework of the Bahira basin and to have a 3D geological modeling of the basin, an integrated multidisciplinary work has been conducted using gravity, magnetic and geological data. The objective of the current study is delineating the subsurfacefeatures, faults, and geological limits, using airborne magnetic and gravity data analysis of the Bahira basin. To achieve our goal, we have applied different enhanced techniques on magnetic and gravity data: power spectral analysis techniques, reduction to pole (RTP), upward continuation, analytical signal, tilt derivative, total horizontal derivative, 3D Euler deconvolutionand source parameter imagining. The major lineaments/faults trend are: NE–SW, NW-SE, ENE–WSW, and WNW–ESE. The 3D Euler deconvolution analysis highlighted a number of fault trend, mainly in the ENE-WSW, WNW-ESE directions. The depth tothe top of the basement sources in the study area ranges between 200 m, in the southern and northern part of the Bahira basin, to 5000 m located in the Eastern part of the basin.

Keywords: magnetic, gravity, structural trend, depth to basement

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Authors: Hailemariam Getachew, John Sandi, Isata Dumbuya, Patricia Efe.Azikiwe, Evaline Nginge, Moses Mugisha, Eseoghene Dase, Foday Mandaray, Grace Moore

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Enhanced recovery after cesarean section (ERAC) is a standardized peri- operative care program that comprises the multidisciplinary team's collective efforts working in collaboration throughout the peri-operative period with the principal goal to improve quality of surgical care, decrease surgical related complications, and increasing patient satisfaction. Objective: The main objective of this project is to improve the implementation of enhanced recovery after cesarean section at Koidu Government hospital. Identified gap: Even though the hospital is providing comprehensive maternal and child care service, there are gaps in the implementation of ERAC. According to our survey, we found that there is low (13.3%) utilization of WHO surgical safety checklist, only limited (15.9%) patients get opioid free analgesia, pain was not recorded as a vital sign, there is no standardized checklist for hand over to and from Post Anesthesia care Unit(PACU). Furthermore, there is inconsistent evidence based post-operative care and there is no local consensus protocol and guideline as well. Implementation plan: we aimed at designing standardized protocol, checklist and guideline, provide training, build staff capacity, document pain as vital sign, perform regional analgesia, and provide evidence based post-operative care, monitoring and evaluation. Result: Data from 389 cesarean mothers showed that, Utilization of the WHO surgical safety check list found to be 95%, and pain assessment and documentation was done for all surgical patients. Oral feeding, ambulation and catheter removal was performed as per the ERAC standard for all patients. Postoperative complications drastically decreased from 13.6% to 8.1%. While, the rate of readmission was kept below 1%. Furthermore, the duration of hospital stay decreased from 4.64 days to 3.12 days. Conclusion The successful implementation of ERAC protocols demonstrates through this Quality Improvement Project that, the effectiveness of the protocols in improving recovery and patient outcome following cesarean section.

Keywords: cesarean delivery, enhanced recovery, quality improvement, patient outcome

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Authors: Adeleye Ebenezer Omotayo

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The main effects of tillage, poultry manure and interaction effects of tillage-poultry manure combinations on soil characteristics and yam yield were investigated in a factorial experiment involving four tillage techniques namely (ploughing (p), ploughing plus harrowing (PH), manual ridging (MR), manual heaping (MH) and poultry manure at two levels 0 t ha-1 and 10 t ha-1 arranged in split-plot design. Data obtained were subjected to analysis of variance using Statistical Analysis System (SAS) Institute Package. Soil moisture content, bulk density and total porosity were significantly (p>0.05) influenced by soil tillage techniques. Manually heaped and ridged plots had the lowest soil bulk density, moisture content and highest total porosity. The soil total N, exchangeable Mg, k, base saturation and CEC were better enhanced in manually tilled plots. Soil nutrients status declined at the end of the second cropping for all the tillage techniques in the order PH>P>MH>MR. Yam tuber yields were better enhanced in manually tilled plots than mechanically tilled plots. Poultry manure application reduced soil bulk density, temperature, increased total porosity and soil moisture content. It also improved soil organic matter, total N, available P, exchangeable Mg, Ca, K and lowered exchange acidity. It also increased yam tuber yield significantly. Tillage techniques plots amended with poultry manure enhanced yam tuber yield relative to tillage techniques plots without poultry manure application. It is concluded that yam production on alfisol in Southwest Nigeria requires loose soil structure for tuber development and that the use of poultry manure in combination with tillage is recommended as it will ensure stability of soil structure, improve soil organic matter status, nutrient availability and high yam tuber yield. Also, it will help to reduce the possible deleterious effects of tillage on soil properties and yam performance.

Keywords: ploughing, poultry manure, yam, yield

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Authors: Mahdiar Hosseinghadiry, Razali Ismail, F. Fotovati

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One of the most important and challenging tasks in testing network-on-chip based system-on-chips (NoC based SoCs) is to verify the communication entity. It is important because of its usage for transferring both data packets and test patterns for intellectual properties (IPs) during normal and test mode. Hence, ensuring of NoC reliability is required for reliable IPs functionality and testing. On the other hand, it is challenging due to the required time to test it and the way of transferring test patterns from the tester to the NoC components. In this paper, two testing techniques for mesh-based NoC interconnections are proposed. The first one is based on one-by-one testing and the second one divides NoC interconnects into three parts, horizontal links of switches in even columns, horizontal links of switches in odd columns and all vertical. A design for testability (DFT) architecture is represented to send test patterns directly to each switch under test and also support the proposed testing techniques by providing a loopback path in each switch. The simulation results shows the second proposed testing mechanism outperforms in terms of test time because this method test all the interconnects in only three phases, independent to the number of existed interconnects in the network, while test time of other methods are highly dependent to the number of switches and interconnects in the NoC.

Keywords: on chip, interconnection testing, horizontal-vertical testing, enhanced unicast

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Authors: P. Annapurna, Cecil Ross, Sudhir Krishna, Sweta Srivastava

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Irradiation plays a pivotal role in cervical cancer treatment, however some tumors exhibit resistance to therapy while some exhibit relapse, due to better repair and enhanced resistance mechanisms operational in their cells. The present study aims to understand the signaling mechanism operational in resistance phenotype and in the present study we report the role of Rho GTPase associated protein kinase (ROCK) signaling in cervical carcinoma radio-resistance. ROCK signaling has been implicated in several tumor progressions and is important for DNA repair. Irradiation of spheroid cultures of SiHa cervical carcinoma derived cell line at 6Gy resulted in generation of resistant cells in vitro which had better clonogenic abilities and formed larger and more colonies, in soft agar colony formation assay, as compared to the non-irradiated cells. These cells also exhibited an enhanced motility phenotype. Cell cycle profiling showed the cells to be blocked in G2M phase with enhanced pCDC2 levels indicating onset of possible DNA repair mechanism. Notably, 3 days post-irradiation, irradiated cells showed increased ROCK2 translocation to the nucleus with enhanced protein expression as compared to the non-irradiated cells. Radio-sensitization of the resistant cells was enhanced using Y27632, an inhibitor to ROCK signaling. The treatment of resistant cells with Y27632 resulted in increased cell death upon further irradiation. This observation has been confirmed using inhibitory antibodies to ROCK1/2. Result show that both ROCK1/2 have a functional contribution in radiation resistance of cervical cancer cells derived from cell lines. Interestingly enrichment of stem like cells (Hoechst negative cells) was also observed upon irradiation and these cells were markedly sensitive to Y27632 treatment. Our results thus suggest the role of ROCK signaling in radio-resistance in cervical carcinoma. Further studies with human biopsies, mice models and mechanistic of ROCK signaling in the context of radio-resistance will clarify the role of this molecule further and allow for therapeutics development.

Keywords: cervical carcinoma, radio-resistance, ROCK signaling, cancer treatment

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Authors: Bingjie Wang, Su-Yeon Kwon, Ik-Joong Kang

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A Surface-enhanced Raman Scattering (SERS) as the principle for enhancing Raman scattering by molecules adsorbed on rough metal surfaces or by nanostructures is used to detect the concentration change of γ-Aminobutyric Acid (GABA). As for the gold-chitosan nanoshell, it is made by using chitosan nanoparticles crosslinking with sodium tripolyphosphate(TPP) for the first step to form the chitosan nanoparticles, which would be covered with the gold sequentially. The size of the fabricated product was around 100nm. Based on the method that the sulfur end of the MPA linked to gold can form the very strong S–Au bond, and the carboxyl group, the other end of the MPA, can easily absorb the GABA. GABA is the mainly inhibitory neurotransmitter in the mammalian central nervous system in the human body. It plays such significant role in reducing neuronal excitability throughout the nervous system. When the system formed, it generated SERS, which made a clear difference in the intensity of Raman scattering within the range of GABA concentration. So it is obtained from the experiment that the calibration curve according to the GABA concentration relevant with the SERS scattering. In this study, DLS, SEM, FT-IR, UV, SERS were used to analyze the products to obtain the conclusion.

Keywords: chitosan-gold nanoshell, mercaptopropionic acid, γ-aminobutyric acid, surface-enhanced Raman scattering

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Authors: Farhan Sohail, Gul Shahnaz Irshad Hussain, Shoaib Sarwar, Ibrahim Javed, Zajif Hussain, Akhtar Nadhman

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The present study was aimed to develop a hybrid nanocarrier (NC) system with enhanced membrane permeability, bioavailability and targeted delivery of Docetaxel (DTX) in breast cancer. Hybrid NC’s based on folic acid (FA) grafted thiolated chitosan (TCS) enveloped liposomes were prepared with DTX and evaluated in-vitro and in-vivo for their enhanced permeability and bioavailability. Physicochemical characterization of NC’s including particle size, morphology, zeta potential, FTIR, DSC, PXRD, encapsulation efficiency and drug release from NC’s was determined in vitro. Permeation enhancement and p-gp inhibition were performed through everted sac method on freshly excised rat intestine which indicated that permeation was enhanced 5 times as compared to pure DTX and the hybrid NC’s were strongly able to inhibit the p-gp activity as well. In-vitro cytotoxicity and tumor targeting was done using MDA-MB-231 cell line. The stability study of the formulations performed for 3 months showed the improved stability of FA-TCS enveloped liposomes in terms of its particles size, zeta potential and encapsulation efficiency as compared to TCS NP’s and liposomes. The pharmacokinetic study was performed in vivo using rabbits. The oral bioavailability and AUC0-96 was increased 10.07 folds with hybrid NC’s as compared to positive control. Half-life (t1/2) was increased 4 times (58.76 hrs) as compared to positive control (17.72 hrs). Conclusively, it is suggested that FA-TCS enveloped liposomes have strong potential to enhance permeability and bioavailability of hydrophobic drugs after oral administration and tumor targeting.

Keywords: docetaxel, coated liposome, permeation enhancement, oral bioavailability

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Authors: Janet Wing-Chong Wai, Alex Chiu-Wing Lee, Hailey Hoi-Ching Tsang, Jeffrey Chiu, Kwok-Wing Tang

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Background: Mammography has limited sensitivity and specificity though it is the primary imaging technique for detection of early breast cancer. Ultrasound imaging and contrast-enhanced MRI are useful adjunct tools to mammography. The advantage of breast MRI is high sensitivity for invasive breast cancer. Therefore, indications for and use of breast magnetic resonance imaging have increased over the past decade. Objectives: 1. Cases demonstration on different indications for breast MR imaging. 2. To review of the common artifacts and pitfalls in breast MR imaging. Materials and Methods: This is a retrospective study including all patients underwent dynamic contrast-enhanced breast MRI examination in our centre, performed from Jan 2011 to Dec 2017. The clinical data and radiological images were retrieved from the EPR (electronic patient record), RIS (Radiology Information System) and PACS (Picture Archiving and Communication System). Results and Discussion: Cases including (1) Screening of the contralateral breast in patient with a new breast malignancy (2) Breast augmentation with free injection of unknown foreign materials (3) Finding of axillary adenopathy with an unknown site of primary malignancy (4) Neo-adjuvant chemotherapy: before, during, and after chemotherapy to evaluate treatment response and extent of residual disease prior to operation. Relevant images will be included and illustrated in the presentation. As with other types of MR imaging, there are different artifacts and pitfalls that can potentially limit interpretation of the images. Because of the coils and software specific to breast MR imaging, there are some other technical considerations that are unique to MR imaging of breast regions. Case demonstration images will be available in presentation. Conclusion: Breast MR imaging is a highly sensitive and reasonably specific method for the detection of breast cancer. Adherent to appropriate clinical indications and technical optimization are crucial for achieving satisfactory images for interpretation.

Keywords: MRI, breast, clinical, cancer

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Authors: Smita Krishnan, Krittika Chandran, Chandra Mohan Sinnathambi

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Produced water and its treatment and management are growing challenges in all producing regions. This water is generally considered as a nonrevenue product, but it can have significant value in enhanced oil recovery techniques if it meets the required quality standards. There is also an interest in the beneficial uses of produced water for agricultural and industrial applications. Advanced Oxidation Process is a chemical technology that has been growing recently in the wastewater treatment industry, and it is highly recommended for non-easily removal of organic compounds. The efficiency of AOPs is compound specific, therefore, the optimization of each process should be done based on different aspects.

Keywords: advanced oxidation process, photochemical processes, degradation, organic contaminants

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Authors: Ikechukwu Ogeze Ukeje, Chinyere Ori Elom, Chukwudum Collins Umoke

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This study explores the challenges in the integration of Artificial Intelligence (AI) and Information and Communication Technology (ICT) practices in enhancing governance and sustainable solution modeling in higher education, focusing on Alex Ekwueme Federal University Ndufu-Alike (AE-FUNAI), Nigeria. In the context of a developing country like Nigeria, leveraging AI and ICT tools presents a unique opportunity to improve teaching, learning, administrative processes, and governance. The research aims to evaluate how AI and ICT technologies can contribute to sustainable educational practices, enhance decision-making processes, and improve engagement among key stakeholders: students, lecturers, and administrative staff. Students are involved to provide insights into their interactions with AI and ICT tools, particularly in learning and participation in governance. Lecturers’ perspectives will offer a view into how these technologies influence teaching, research, and curriculum development. Administrative staff will provide a crucial understanding of how AI and ICT tools can streamline operations, support data-driven governance, and enhance institutional efficiency. This study will use a mixed-method approach to collect both qualitative and quantitative data. The finding of this study is geared towards shaping the future of education in Nigeria and beyond by developing an Inclusive AI-governance Integration Framework (I-AIGiF) for enhanced performance in the system. Examining the roles of these stakeholder groups, this research could guide the development of policies for more effective AI and ICT integration, leading to sustainable educational innovation and governance.

Keywords: university administration, AI, higher education governance, education sustainability, ICT challenges

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Authors: Navneet Kaur, Amarpreet Singh

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In Vehicular Adhoc Networks, Data Dissemination is a challenging task. There are number of techniques, types and protocols available for disseminating the data but in order to preserve limited bandwidth and to disseminate maximum data over networks makes it more challenging. There are broadcasting, multicasting and geocasting based protocols. Multicasting based protocols are found to be best for conserving the bandwidth. One such protocol named BEAM exists that improves the performance of Vehicular Adhoc Networks by reducing the number of in-network message transactions and thereby efficiently utilizing the bandwidth during an emergency situation. But this protocol may result in multicar chain collision as there was no V2V communication. So, this paper proposes a new protocol named Enhanced Bandwidth Efficient Cluster Based Multicasting Protocol (EBECM) that will overcome the limitations of existing BEAM protocol. And Simulation results will show the improved performance of EBECM in terms of Routing overhead, throughput and PDR when compared with BEAM protocol.

Keywords: BEAM, data dissemination, emergency situation, vehicular adhoc network

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Authors: Nizamuddin Zainuddin, Adam Mohd Saifudin, Ahmad Yusni Bahaudin, Mohd Hanizan Zalazilah, Roslan Jamaluddin

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Students’ enhanced experience through simulation is a crucial factor that brings reality to the classroom. The enhanced experience is all about developing, enriching and applications of a generic process flow in the field of logistics and transportations. As educational technology has improved, the effective use of simulations has greatly increased to the point where simulations should be considered a valuable, mainstream pedagogical tool. Additionally, in this era of ongoing (some say never-ending) assessment, simulations offer a rich resource for objective measurement and comparisons. Simulation is not just another in the long line of passing fads (or short-term opportunities) in educational technology. It is rather a real key to helping our students understand the world. It is a way for students to acquire experience about how things and systems in the world behave and react, without actually touching them. In short, it is about interactive pretending. Simulation is all about representing the real world which includes grasping the complex issues and solving intricate problems. Therefore, it is crucial before stimulate the real process of inbound and outbound logistics and transportation a generic process flow shall be developed. The paper will be focusing on the validization of the process flow by looking at the inputs gains from the sample. The sampling of the study focuses on multi-national and local manufacturing companies, third party companies (3PL) and government agency, which are selected in Peninsular Malaysia. A simulation flow chart was proposed in the study that will be the generic flow in logistics and transportation. A qualitative approach was mainly conducted to gather data in the study. It was found out from the study that the systems used in the process of outbound and inbound are System Application Products (SAP) and Material Requirement Planning (MRP). Furthermore there were some companies using Enterprises Resources Planning (ERP) and Electronic Data Interchange (EDI) as part of the Suppliers Own Inventories (SOI) networking as a result of globalized business between one countries to another. Computerized documentations and transactions were all mandatory requirement by the Royal Custom and Excise Department. The generic process flow will be the basis of developing a simulation program that shall be used in the classroom with the objective of further enhanced the students’ learning experience. Thus it will contributes to the body of knowledge on the enrichment of the student’s employability and also shall be one of the way to train new workers in the logistics and transportation filed.

Keywords: enhancement, simulation, process flow, logistics, transportation

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Authors: Rupali Verma, Maitreyee Dutta, Renu Vig

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Encryption and decryption in RSA are done by modular exponentiation which is achieved by repeated modular multiplication. Hence, efficiency of modular multiplication directly determines the efficiency of RSA cryptosystem. This paper designs a Modified Montgomery Modular multiplication in which addition of operands is computed by 4:2 compressor. The basic logic operations in addition are partitioned over two iterations such that parallel computations are performed. This reduces the critical path delay of proposed Montgomery design. The proposed design and RSA are implemented on Virtex 2 and Virtex 5 FPGAs. The two factors partitioning and parallelism have improved the frequency and throughput of proposed design.

Keywords: RSA, montgomery modular multiplication, 4:2 compressor, FPGA

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Authors: Reda Askouri, Mohamed Moussetad, Rhma Adhiri

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Reverse osmosis (RO) is one of the most widely used techniques for seawater desalination. However, the conversion rate of this method is generally limited to 35-45% due to the high-pressure capacity of the membranes. Additionally, the specific energy consumption (SEC) for seawater desalination is high, necessitating energy recovery systems to minimise energy consumption. This study aims to enhance the performance of seawater desalination by combining RO with a vibratory shear-enhanced processing (VSEP) technique. The RO unit in this study comprises two stages, each powered by a hydraulic turbocharger that increases the pressure in both stages. The concentrate from the second stage is then directly processed by VSEP technology. The results demonstrate that the permeate water obtained exhibits high quality and that the conversion rate is significantly increased, reaching high percentages with low SEC. Furthermore, the high concentration of total solids in the concentrate allows for potential exploitation within the environmental protection framework. By valorising the concentrated waste, it’s possible to reduce the environmental impact while increasing the overall efficiency of the desalination process.

Keywords: specific energy consumption, vibratory shear enhanced process, environmental challenge, water recovery

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Authors: Shilpa Balan

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Radio Frequency Identification, also popularly known as RFID is used to automatically identify and track tags attached to items. This study focuses on the application of RFID in healthcare. The adoption of RFID in healthcare is a crucial technology to patient safety and inventory management. Data from RFID tags are used to identify the locations of patients and inventory in real time. Medical errors are thought to be a prominent cause of loss of life and injury. The major advantage of RFID application in healthcare industry is the reduction of medical errors. The healthcare industry has generated huge amounts of data. By discovering patterns and trends within the data, big data analytics can help improve patient care and lower healthcare costs. The number of increasing research publications leading to innovations in RFID applications shows the importance of this technology. This study explores the current state of research of RFID in healthcare using a text mining approach. No study has been performed yet on examining the current state of RFID research in healthcare using a data mining approach. In this study, related articles were collected on RFID from healthcare journal and news articles. Articles collected were from the year 2000 to 2015. Significant keywords on the topic of focus are identified and analyzed using open source data analytics software such as Rapid Miner. These analytical tools help extract pertinent information from massive volumes of data. It is seen that the main benefits of adopting RFID technology in healthcare include tracking medicines and equipment, upholding patient safety, and security improvement. The real-time tracking features of RFID allows for enhanced supply chain management. By productively using big data, healthcare organizations can gain significant benefits. Big data analytics in healthcare enables improved decisions by extracting insights from large volumes of data.

Keywords: RFID, data mining, data analysis, healthcare

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Authors: Tina Wu, Andrew Martin

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The expansion of the Internet of Things (IoT) brings a new level of threat. Attacks on IoT are already being used by criminals to form botnets, launch Distributed Denial of Service (DDoS) and distribute malware. This opens a whole new digital forensic arena to develop forensic methodologies in order to have the capability to investigate IoT related crimes. However, existing proposed IoT forensic models are still premature requiring further improvement and validation, many lack details on the acquisition and analysis phase. This paper proposes an enhanced theoretical IoT digital forensic model focused on identifying and acquiring the main sources of evidence in a methodical way. In addition, this paper presents a theoretical acquisition framework of the different stages required in order to be capable of acquiring evidence from IoT devices.

Keywords: acquisition, Internet of Things, model, zoning

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Authors: Temesgen Geremew

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The excessive emission of heavy metal ions from industrial processes poses a serious threat to both the environment and human health. This study presents a distinct approach utilizing (PTh-MnS/CoS NPs) for the highly selective and sensitive detection of Hg²⁺ ions in water. Such detection is crucial for safeguarding human health, protecting the environment, and accurately assessing toxicity. The fabrication method employs a simple and efficient chemical precipitation technique, harmoniously combining polythiophene, MnS, and CoS NPs to create highly active substrates for SERS. The MnS@Hg²⁺ exhibits a distinct Raman shift at 1666 cm⁻¹, enabling specific identification and demonstrating the highest responsiveness among the studied semiconductor substrates with a detection limit of only 1 nM. This investigation demonstrates reliable and practical SERS detection for Hg²⁺ ions. Relative standard deviation (RSD) ranged from 0.49% to 9.8%, and recovery rates varied from 96% to 102%, indicating selective adsorption of Hg²⁺ ions on the synthesized substrate. Furthermore, this research led to the development of a remarkable set of substrates, including (MnS, CoS, MnS/CoS, and PTh-MnS/CoS) nanoparticles were created right there on SiO₂/Si substrate, all exhibiting sensitive, robust, and selective SERS for Hg²⁺ ion detection. These platforms effectively monitor Hg²⁺ concentrations in real environmental samples.

Keywords: surface-enhanced raman spectroscopy (SERS), sensor, mercury ions, nanoparticles, and polythiophene.

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Authors: Oluyomi Stephen Adeyemi, Kentaro Kato

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Toxoplasma gondii is the etiological agent of toxoplasmosis, a common parasitic disease capable of infecting a range of hosts, including nearly one-third of the human population. Current treatment options for toxoplasmosis patients are limited. In consequence, toxoplasmosis represents a large global burden that is further enhanced by the shortcomings of the current therapeutic options. These factors underscore the need for better anti-T. gondii agents and/or new treatment approach. In the present study, we sought to find out whether preparing and capping nanoparticles (NPs) in amino acids, would enhance specificity toward the parasite versus the host cell. The selection of amino acids was premised on the fact that T. gondii is auxotrophic for some amino acids. The amino acid-nanoparticles (amino-NPs) were synthesized, purified and characterized following established protocols. Next, we tested to determine the anti-T. gondii activity of the amino-NPs using in vitro experimental model of infection. Overall, our data show evidence that supports enhanced and excellent selective action against the parasite versus the host cells by amino-NPs. The findings are promising and provide additional support that warrants exploring the prospects of NPs as alternative anti-parasite agents. In addition, the anti-parasite action by amino-NPs indicates that nutritional requirement of parasite may represent a viable target in the development of better alternative anti-parasite agents. Furthermore, data suggest the anti-parasite mechanism of the amino-NPs involves multiple cellular processes including the production of reactive oxygen species (ROS), modulation of hypoxia-inducing factor-1 alpha (HIF-1α) as well as the activation of kynurenine pathway. Taken together, findings highlight further, the prospects of NPs as alternative source of anti-parasite agents.

Keywords: drug discovery, infectious diseases, mode of action, nanomedicine

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Authors: Atena Naeimi, Asghar Amiri, Zahra Ghasemi

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A stable suspension of nanocomposite simple manganese(III) meso-tetraphenylporphyrin nanoaggregates and Ag was prepared by a host–guest procedure, in which ethanol and water are used as ‘green’ solvents. The oxidation of alcohols by tetrabutylammonium Peroxomonosulfate(TP) were efficiently enhanced with excellent selectivity under the influence of simple Mn(TPP)OAc (TPP = meso-tetraphenylporphyrin) nanoparticles. Enhanced stabilities and activities were achieved with nanostructured Mn catalysts compared to those of the individual counterparts in solution according to turnover numbers and UV/Vis studies. The title nanocatalyst facilitates a greener reaction because the reaction solvent is water and TP is safe to use. The efficiency of the oxidation system depends critically upon the steric hindrances and electronic structures of both nitrogen donor ligand sand porphyrin nanoparticles.

Keywords: oxidation, nanoaggregates, porphyrinoids, silver

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Authors: Mukhtar Raban

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Nelson Mandela University subscribes to a humanizing pedagogy (HP), as housed under broader critical pedagogy, that underpins and informs learning and teaching activities at the institution. The investigation sought to explore the implications of humanizing and critical pedagogical considerations for a technology-enhanced language learning (TELL) environment in a university course. The paper inquires into the design of a learning resource in an online learning environment of an English communication module, that applied HP principles. With an objective of creating agentive spaces for foregrounding identity, student voice, critical self-reflection, and recognition of others’ humanity; a flexible and open 'My Presence' feature was added to the TELL environment that allowed students and lecturers to share elements of their backgrounds in a ‘mutually vulnerable’ manner as a way of establishing digital identity and a more ‘human’ presence in the online language learning encounter, serving as a catalyst for the recognition of the ‘other’. Following a qualitative research design, the study adopted an auto-ethnographic approach, complementing the critical inquiry nature embedded into the activity’s practices. The study’s findings provide critical reflections and deductions on the possibilities of leveraging digital human expression within a humanizing pedagogical framework to advance the realization of HP-adoption in language learning and teaching encounters. It was found that the consideration of humanizing pedagogical principles in the design of online learning was more effective when the critical outcomes were explicated to students and lecturers prior to the completion of the activities. The integration of humanizing pedagogy also led to a contextual advancement of ‘affective’ language learning. Upon critical reflection and analysis, student identity and agency can flourish in a technology-enhanced learning environment when humanizing, and critical pedagogy influences the learning design.

Keywords: critical reflection, humanizing pedagogy, student identity, technology-enhanced language learning

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Authors: Rosana Marar, Edward Jaser

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This paper presents a software solution to enhance the content and presentation of graphic design and animation related textbooks. Using augmented and virtual reality concepts, a mobile application is developed to improve the static material found in books. This allows users to interact with animated examples and tutorials using their mobile phones and stereoscopic 3D viewers which will enhance information delivery. The application is tested on Google Cardboard with visual content in 3D space. Evaluation of the proposed application demonstrates that it improved the readability of static content and provided new experiences to the reader.

Keywords: animation, augmented reality, google cardboard, interactive media, technology enhanced learning, virtual reality

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Authors: M. P. Sebastian

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Health for all is considered as a sign of well-being and inclusive growth. New healthcare technologies are contributing to the quality of human lives by promoting health education and awareness, leading to the prevention, early diagnosis and treatment of the symptoms of diseases. Healthcare technologies have now migrated from the medical and institutionalized settings to the home and everyday life. This paper explores these new technologies and investigates how they contribute to health education and awareness, promoting the objective of high-value health system for all. The methodology used for the research is literature review. The paper also discusses the opportunities and challenges with futuristic healthcare technologies. The combined advances in genomics medicine, wearables and the IoT with enhanced data collection in electronic health record (EHR) systems, environmental sensors, and mobile device applications can contribute in a big way to high-value health system for all. The promise by these technologies includes reduced total cost of healthcare, reduced incidence of medical diagnosis errors, and reduced treatment variability. The major barriers to adoption include concerns with security, privacy, and integrity of healthcare data, regulation and compliance issues, service reliability, interoperability and portability of data, and user friendliness and convenience of these technologies.

Keywords: big data, education, healthcare, information communication technologies (ICT), patients, technologies

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Authors: Salihah Alghamdi, Surajit Ray

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Space-time data can be observed over irregularly shaped manifolds, which might have complex boundaries or interior gaps. Most of the existing methods do not consider the shape of the data, and as a result, it is difficult to model irregularly shaped data accommodating the complex domain. We used a method that can deal with space-time data that are distributed over non-planner shaped regions. The method is based on partial differential equations and finite element analysis. The model can be estimated using a penalized least squares approach with a regularization term that controls the over-fitting. The model is regularized using two roughness penalties, which consider the spatial and temporal regularities separately. The integrated square of the second derivative of the basis function is used as temporal penalty. While the spatial penalty consists of the integrated square of Laplace operator, which is integrated exclusively over the domain of interest that is determined using finite element technique. In this paper, we applied a spatio-temporal regression model with partial differential equations regularization (ST-PDE) approach to analyze a remote sensing data measuring the greenness of vegetation, measure by an index called enhanced vegetation index (EVI). The EVI data consist of measurements that take values between -1 and 1 reflecting the level of greenness of some region over a period of time. We applied (ST-PDE) approach to irregular shaped region of the EVI data. The approach efficiently accommodates the irregular shaped regions taking into account the complex boundaries rather than smoothing across the boundaries. Furthermore, the approach succeeds in capturing the temporal variation in the data.

Keywords: irregularly shaped domain, partial differential equations, finite element analysis, complex boundray

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Authors: Thian Khoon Tan, Poi Sim Khiew, Wee Siong Chiu, Chin Hua Chia

Abstract:

This study investigates the efficacy of magnetically enhanced zinc oxide (MZnO) nanoparticles as a photocatalyst in the photodegradation of synthetic dyes, especially azo dyes. This magnetised zinc oxide has been simply fabricated by mechanical mixing through low-temperature calcination. This MZnO has been analysed through several analytical measurements, including FESEM, XRD, BET, EDX, and TEM, as well as VSM analysis which reflects successful fabrication. A high volume of azo dyes was found in industries effluent wastewater. They contribute to serious environmental stability and are very harmful to human health due to their high stability and carcinogenic properties. Therefore, five azo dyes, Reactive Red 120 (RR120), Disperse Blue 15 (DB15), Acid Brown 14 (AB14), Orange G (OG), and Acid Orange 7 (AO7), have been randomly selected to study their photodegradation property with reference to few characteristics, such as number of azo functional groups, benzene groups, molecular mass, and absorbance. The photocatalytic degradation efficiency was analysed by using a UV-vis spectrophotometer, where the reaction rate constant was obtained. It was found that azo dyes were significantly degraded through the first-order rate constant, which shows a higher kinetic constant as the number of azo functional groups and benzene group increases. However, the kinetic constant is inversely proportional to the molecular weight of these azo dyes.

Keywords: nanoparticles, photocatalyst, magnetically enhanced, wastewater, synthetic dyes, azo dyes

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Authors: Zhihao Zheng, Zhilin Wang, Linxin Liu

Abstract:

In the research of automated knowledge question-answering systems, accuracy and efficiency are critical challenges. This paper proposes a knowledge graph-enhanced Retrieval-Augmented Generation (RAG) method, combined with a Graph Neural Network (GNN) structure, to automatically determine the correctness of knowledge competition questions. First, a domain-specific knowledge graph was constructed from a large corpus of academic journal literature, with key entities and relationships extracted using Natural Language Processing (NLP) techniques. Then, the RAG method's retrieval module was expanded to simultaneously query both text databases and the knowledge graph, leveraging the GNN to further extract structured information from the knowledge graph. During answer generation, contextual information provided by the knowledge graph and GNN is incorporated to improve the accuracy and consistency of the answers. Experimental results demonstrate that the knowledge graph and GNN-enhanced RAG method perform excellently in determining the correctness of questions, achieving an accuracy rate of 95%. Particularly in cases involving ambiguity or requiring contextual information, the structured knowledge provided by the knowledge graph and GNN significantly enhances the RAG method's performance. This approach not only demonstrates significant advantages in improving the accuracy and efficiency of automated knowledge question-answering systems but also offers new directions and ideas for future research and practical applications.

Keywords: knowledge graph, graph neural network, retrieval-augmented generation, NLP

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Authors: Qudratullah Muradi

Abstract:

Geothermal energy is a renewable energy source that can be found in abundance on our planet. Only a small fraction of it is currently converted to electrical power, though in recent years installed geothermal capacity has increased considerably all over the world. In this paper, we assumed a model for designing of Enhanced Geothermal System, EGS. We used computer modeling group, CMG reservoir simulation software to create the typical Hot Dry Rock, HDR reservoir. In this research two wells, one injection of cold water and one production of hot water are included in the model. There are some hydraulic fractures created by the mentioned software. And cold water is injected in order to produce energy from the reservoir. The result of injecting cold water to the reservoir and extracting geothermal energy is defined by some graphs at the end of this research. The production of energy is quantified in a period of 10 years.

Keywords: geothermal energy, EGS, HDR, hydraulic fracturing

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Authors: Pauli P.Y. Lai

Abstract:

Students with Special Education Needs (SEN) face many challenges in learning. Various challenges include difficulty in handwriting, slow understanding and assimilation, difficulty in paying attention during class, and lack of communication skills. To engage students with Special Education Needs in class with general students, Blackboard Collaborate is used as a teaching and learning tool to deliver a lecture with interactive activities. Blackboard Collaborate provides a good platform to create and enhance active, collaborative and interactive learning experience whereby the SEN students can easily interact with their general peers and the instructor by using the features of drawing on a virtual whiteboard, file sharing, classroom chatter, breakout room, hand-raising feature, polling, etc. By integrating a blended learning approach with Blackboard Collaborate, the students with Special Education Needs could engage in interactive activities with ease in class. Our research aims at exploring and discovering the use of Blackboard Collaborate for inclusive education based on a qualitative design with in-depth interviews. Being served in a general education environment, three university students with different kinds of learning disabilities have participated in our study. All participants agreed that functions provided by Blackboard Collaborate have enhanced their learning experiences and helped them learn better. Their academic performances also showed that SEN students could perform well with the help of technology. This research studies different aspects of using Blackboard Collaborate to create an inclusive learning environment for SEN students.

Keywords: blackboard collaborate, enhanced learning experience, inclusive education, special education needs

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Authors: Nikat Parveen, M. Ananthi

Abstract:

Big data is one of the emerging technology, which collects the data from various sensors and those data will be used in many fields. Data retrieval is one of the major issue where there is a need to extract the exact data as per the need. In this paper, large amount of data set is processed by using the feature selection. Feature selection helps to choose the data which are actually needed to process and execute the task. The key value is the one which helps to point out exact data available in the storage space. Here the available data is streamed and R-Center is proposed to achieve this task.

Keywords: big data, key value, feature selection, retrieval, performance

Procedia PDF Downloads 340