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Relevant bibliographies by topics / Explosives – Detection – Technological innovations

Academic literature on the topic 'Explosives – Detection – Technological innovations'

Author: Grafiati

Published: 10 December 2022

Last updated: 29 January 2023

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Journal articles on the topic "Explosives – Detection – Technological innovations"

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F. Santarelli, Maria, Vincenzo Positano, Nicola Martini, Giuseppe Valvano, and Luigi Landini. "Technological Innovations in Magnetic Resonance for Early Detection of Cardiovascular Diseases." Current Pharmaceutical Design 22, no. 1 (December 21, 2015): 77–89. http://dx.doi.org/10.2174/1381612822666151109112240.

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Maziejuk, Mirosław, Monika Szyposzyńska, Aleksandra Spławska, Monika Wiśnik-Sawka, and Michał Ceremuga. "Detection of Triacetone Triperoxide (TATP) and Hexamethylene Triperoxide Diamine (HMTD) from the Gas Phase with Differential Ion Mobility Spectrometry (DMS)." Sensors 21, no. 13 (July 2, 2021): 4545. http://dx.doi.org/10.3390/s21134545.

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One of the significant problems in the modern world is the detection of improvised explosives made of materials synthesized at home. Such compounds include triacetone triperoxide (TATP) and hexamethylene triperoxide diamine (HMTD). An attempt was made to construct an instrument allowing for the simultaneous detection of both compounds despite the large difference of vapor pressure: very high for TATP and very low for HMTD. The developed system uses differential ion mobility spectrometry (DMS) in combination with a specially designed gas sample injection system. The created system of detectors allowed for the detection of a high concentration of TATP and a very low concentration of HMTD. TATP detection was possible despite the presence of impurities—acetone remaining from the technological process and formed as a coproduct of diacetone diperoxide (DADP) synthesis. Ammonia added to the carrier gas improved the possibility of detecting the abovementioned explosives, reducing the intensity of the acetone signal. The obtained results were then compared with the detection capabilities of drift tube ion mobility spectrometer (DT-IMS), which has not made possible such detection as DMS.

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Barrass, Lucy, Abigail Roberts, Oluwatomi Arisa, Emily Robertson, Aoife Oliver, Oshin Sharma, Janet Kinnersley, Dawn Craig, and Anne Oyewole. "OP57 The Identification Of Technological Innovations To Address The Challenge Of Antimicrobial Resistance Using Horizon Scanning Approaches." International Journal of Technology Assessment in Health Care 38, S1 (December 2022): S22. http://dx.doi.org/10.1017/s0266462322001106.

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IntroductionInappropriate prescribing of antibiotics is a significant driver of antimicrobial resistance (AMR) which is a global health challenge. Technological innovations present an opportunity to reduce demand for antimicrobials through infection prevention, detection, and management. The National Institute for Health and Care Research (NIHR) Innovation Observatory (IO) has developed horizon scanning methods to identify promising innovations (devices/diagnostics/digital) and anticipate technological trends. Together these insights build a comprehensive landscape and presents a significant opportunity for decision-makers and HTAs to consider the clinical, financial, infrastructural, and logistical provisions to improve preparedness for the potential adoption of these future innovations.MethodsThe IO developed a detailed dataset of technologies by formulating search strategies for AMR, based on a comprehensive list of terms and input from expert panels. Primary and secondary sources were systematically scanned using a combination of traditional scanning methods, automated and novel artificial intelligence (AI)/machine learning techniques. Sources included clinical trial registries, MedTech news, academic sources, funding agencies, commercial sites, and regulatory authorities.ResultsOur global dataset identified over 3000 innovative preventative, detection, and monitoring technologies mapped across AMR clinical pathways (including sepsis, respiratory tract infections). Development activity largely concentrated in the United States of America and United Kingdom. Emerging trends included the application of novel materials to prevent infections (e.g., catheter coatings) and novel analytical techniques (e.g., biosensors, microfluidics, breath analysis) to support optimal patient treatment. Data analysis revealed a high proportion of technologies were diagnostic innovations addressing unmet needs such as rapid and accurate detection (including drug-resistant infections).ConclusionsThe rapid development and application of technological interventions presents an opportunity to strengthen national AMR strategies worldwide, through the adoption of new innovations. Improvements in exiting technologies, along with technological advancements have the potential to support appropriate prescribing of antimicrobials and thus address the rise in AMR.

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MOWLAWI, ALI ASGHAR, and MAJED YAZDANI. "MONTE CARLO SIMULATION OF SOIL MOISTURE EFFECTS ON ANTI-TANK LANDMINES DETECTION BY NEUTRON BACKSCATTERING TECHNIQUE." International Journal of Modern Physics B 23, no. 32 (December 30, 2009): 5907–13. http://dx.doi.org/10.1142/s0217979209049735.

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The detection of landmines using available technologies is a time consuming, expensive, and extremely dangerous job, so that there is a need for technological breakthroughs in this field. One of the safest and most effective technologies to landmine and explosive detection is the neutron backscattering technique. The slowing-down of fast neutrons to the thermal energy is a direct measure of the concentration of hydrogen, one of the main elements present in explosive materials. The elastic scattering of fast neutrons is affected by the strong resonances in the cross-section of the three other elements of explosives: nitrogen, oxygen, and carbon. In this work, Monte Carlo estimations of the soil moisture effects on landmine detection are presented.

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Bogue, Robert. "Remote chemical sensing: a review of techniques and recent developments." Sensor Review 38, no. 4 (September 17, 2018): 453–57. http://dx.doi.org/10.1108/sr-12-2017-0267.

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Purpose This paper aims to provide technical details of the techniques used for the remote detection of chemical compounds in a number of applications and also to highlight key research themes. Design/methodology/approach Following a short introduction, this first considers remote gas detection using the DIAL technique. Remote gas cloud imaging is then discussed, and this is followed by a review of chemical warfare agent detection technologies. A selection of research activities and product developments aimed at remotely detecting explosives are considered and, finally, brief concluding comments are drawn. Findings Remote gas sensing is now a practical reality, and products are available which can remotely detect, identify, quantify and in some cases visualise a wide range of toxic and environmentally threatening gases. These satisfy numerous industrial, environmental and military applications. Remotely detecting explosives poses a significant technological challenge, and despite some commercialisation, it remains the topic of an extensive research effort, much involving LIBS and Raman techniques. Importantly, much of this work also has potential in non-military applications, with several developments being shown to detect various industrially important compounds. Originality/value This provides a technical insight into the techniques and products used in a range of remote chemical sensing applications.

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Sickle, G. A. Van. "A review of innovations in disease and insect management and control." Forestry Chronicle 68, no. 6 (December 1, 1992): 742–46. http://dx.doi.org/10.5558/tfc68742-6.

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Insects, diseases and fire annually cause losses equal to one-third of the allowable annual cut in British Columbia and can directly affect exports and movement of forest products. While salvage, at least partial, of the merchantable mortality has been the traditional practice, innovations in forecasting, detection and control are increasing forest management options. Examples are given of technological advances in nursery production, data analysis and interpretation using geographic information systems (GIS) and models, insect pheromones and biological controls, and quarantine requirements imposed by concerns for potential pests.

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Gouveia-Carvalho, Júlio, Wilson Talhão Antunes, Tiago Gonçalves, Victor Lobo, Filipe Duarte, Bernardino Veríssimo, Alfredo Baptista, and Mário Monteiro Marques. "Chemical and Radiological Sensors Integration in Unmanned Aerial Systems with ATEX Compliance." Key Engineering Materials 893 (July 20, 2021): 17–27. http://dx.doi.org/10.4028/www.scientific.net/kem.893.17.

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Chemical, biological, radiological and nuclear (CBRN) threats pose many challenges to address in terms of reconnaissance, detection, personnel protection and countermeasures comprising a common set of techniques and procedures that fit in the concept of “all hazard” approach. The scientific and technological developments that led to the use of unmanned aerial systems (UAS) in an ubiquitous manner, enables its integration in CBRN operations, as sensors platforms for detection. In this scope, the GammaEx project targets to validate the concepts of operation using a specifically developed UAS with ATmosphères EXplosives (ATEX) compliance, equipped with chemical and radiological sensors for detection in CBRN scenarios. This paper aims to review the main concepts and challenges involving the sensors integration in UAS for specific CBRN environments considering the ATEX compliance, followed by the GammaEx project description and the presentation of the preliminary results of the laboratory and field comparative assays concerning the specifically developed sensors for the project and the commercial of the shelf sensors, follow on activities and future trends.

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Oriana, Villarroel-Molina, De-Pablos-Heredero Carmen, Barba Cecilio, Rangel Jaime, and García Antón. "The Importance of Network Position in the Diffusion of Agricultural Innovations in Smallholders of Dual-Purpose Cattle in Mexico." Land 10, no. 4 (April 12, 2021): 401. http://dx.doi.org/10.3390/land10040401.

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The dual-purpose bovine production system (DP) is the most widespread small-scale model in Latin American tropics, where it constitutes a key tool in terms of food security. Most DPs are subsistence farms oriented to self-consumption, with a very low technology adoption rate. Hence, the main challenge is how to improve the technological level without compromising the system sustainability by applying land-sharing practices. Thus, through networks methodology, this paper analysed how farmers adopt reproductive technologies. The sample consisted of 383 very small farms of dual-purpose cattle. Seven reproduction technologies oriented to improve reproductive efficiency were evaluated: Breeding soundness evaluation in bulls, semen fertility evaluation, evaluation of female body condition, oestrus detection, pregnancy diagnosis, seasonal or continuous mating, and breeding policy. Social Network Analysis (SNA) allowed identifying adoption patterns, as the joint adoption of semen fertility evaluation, estrus detection, and pregnancy diagnosis, which were consider complementary technologies. Similarly, breeding soundness evaluation in bulls was found to be the most widely adopted technology. The results showed that these farmers presented a very low level of reproduction technology adoption rate and suggested that farmer’s affiliation with organizations such as the Livestock Groups for Technological Validation and Transfer (GGAVATT), and its network position had a significant impact on the level of technological adoption. In the first stage of adoption, this work highlighted the importance of centralized models from the GGAVATT to the farmers, related to the knowledge and absorption dynamic capabilities. In a later stage, decentralized models through technological leaders are a priority, related to integration and innovation dynamic capabilities.

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Johnson, J. Bruce, Susan D. Allen, Jonathan Merten, Lewis Johnson, Daniel Pinkham, and Scott W. Reeve. "Standoff Methods for the Detection of Threat Agents: A Review of Several Promising Laser-Based Techniques." Journal of Spectroscopy 2014 (2014): 1–13. http://dx.doi.org/10.1155/2014/613435.

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Detection of explosives, explosive precursors, or other threat agents presents a number of technological challenges for optical sensing methods. Certainly detecting trace levels of threat agents against a complex background is chief among these challenges; however, the related issues of multiple target distances (from standoff to proximity) and sampling time scales (from passive mines to rapid rate of march convoy protection) for different applications make it unlikely that a single technique will be ideal for all sensing situations. A number of methods for spanning the range of optical sensor technologies exist which, when integrated, could produce a fused sensor system possessing a high level of sensitivity to threat agents and a moderate standoff real-time capability appropriate for portal screening of personnel or vehicles. In this work, we focus on several promising, and potentially synergistic, laser-based methods for sensing threat agents. For each method, we have briefly outlined the technique and report on the current level of capability.

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Burhan, Nik Ahmad Sufian, Razli Che Razak, Saifuzzaman Ibrahim, Muhamad Rosli Selamat, and Muhamad Ridhwan Rosli. "Social Classes of Intelligence, Economic Growth and Technological Achievement: Robust Regression and Outlier Detection." Journal of Interdisciplinary Economics 30, no. 2 (March 29, 2018): 148–63. http://dx.doi.org/10.1177/0260107918761923.

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A previous study has shown that the intellectual class, which is represented by the 95th percentile intelligence quotient (IQ) at a normal distribution, displayed the strongest impact upon economic growth. Meanwhile, those with average ability (50th percentile IQ) exhibited the second strongest impact, and followed by the non-intellectual class (5th percentile IQ). In addition, the researchers discovered that only the intellectual class was significant for technological progress. As such, this article re-analysed the dataset employed in prior study via robust regression. As a result, after eliminating several outliers, the levels of IQ for the intellectual class and the average ability group displayed equal impacts on economic growth, and the impacts were larger than that of non-intellectual. Furthermore, the IQ of the average ability group was significant for technological achievement, although not as strong as the intellectual class. Besides, the number of professional researchers employed in the research and development (R&D) sector did not reflect similar paramount effects as the impact of the average ability IQ in generating technological development. Thus, based on the conclusions drawn, this study suggests that the R&D sector should employ professionals who possess not only high academic qualifications, but also exceptional levels of cognitive skills, especially to spark new innovations. JEL: J24, O31, O47, Z13

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Dissertations / Theses on the topic "Explosives – Detection – Technological innovations"

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Jakkula, Vikramaditya Reddy. "Enhancing smart home resident activity prediction and anomaly detection using temporal relations." Online access for everyone, 2007. http://www.dissertations.wsu.edu/Thesis/Fall2007/v_jakkula_102207.pdf.

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"An intelligent shoe system for health detection and enhancement." 2014. http://repository.lib.cuhk.edu.hk/en/item/cuhk-1291520.

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People are increasingly recognizing how their health affects their quality of life, and health is most easily tracked through the use of wearable devices. The goal of this study is to detect and monitor human motion via gait analysis to provide information that will help people enhance their health. After reviewing a range of wearable health-tracking devices, the shoe has been chosen as one of the best device for observing human motion.
Most measurement systems currently used for motion and gait detection are disadvantaged in that they monitor and analyze motion in limited environments and not in real time. Hence, they cannot be used for long-term monitoring and detection. The design of a new, inexpensive, compact and lightweight shoe-integrated platform is elaborated in this thesis. The intelligent shoe system comprises a suite of sensors, a microprocessor board and a wireless communication module. This ideal platform requires no specialized equipment or lab setup, meaning data can be collected not only in the narrow confines of a research lab, but essentially anywhere, whether indoors or outdoors.
Our everyday lives are shaped by a wide variety of motions, some of which can cause injury. Injuries suffered due to falls account for a significant portion of accidents and immediate help should be provided. The intelligent shoe system offers an approach of detecting the user’s motion, especially the movement and direction of a fall. This study used principle component analysis (PCA) to decrease the number of sensors in the prototype (eight pairs) by half (four pairs), so as to reduce computational cost and enhance real-time performance. The resultant system can learn the patterns necessary to detect fall directions from abundant tilted-standing data instead of actual fall data.
Fatigue can result in an abnormal gait, making injury more probable. Hence, detecting fatigue is very important. Experiments have been conducted to determine the relationship between fatigue and gait, and the resultant data are used to analyze the relationship between force information and foot attitude. These findings can help a user detect fatigue and avoid injury.
People carry various kinds of loads in their daily lives, and long-term load-bearing activities can result in motion deformation. Another objective of this study is to determine a load-carrying approach that will decrease such deformation to a great extent. Resampling is used to partition the related data cycle by cycle. A support vector machine (SVM) is adopted to model a user’s normal walking gait and abnormal gaits without loads, which allows for the determination of whether a gait is normal when a load is carried.
To enhance overall health, exercise is commonly adopted, but many forms of exercise are dull. The proposed system’s shoe-computer interface not only helps people obtain detailed lower-body feedback, but can also be used to promote everyday exercise. People are analyzed while sitting for long periods in the workplace, and two interfaces are designed as a result: the shoe-keyboard, in which the feet are used to type words into a computer, and the shoe-write system, in which the foot is used like a hand to write on the ground, with the words displayed on the computer screen. Both of these applications use back-propagation (BP) networks to classify the motions involved. The shoe-keyboard is based on logical coding to map the motion-to-word relationship, and the shoe-write system incorporates an optical tracker to translate motion into information.
人們現在越來越重視自己的生活質量，而健康方面是最為重要的。穿戴式設備是最好容易使用的檢測健康的設備。本文的目標是通過智能鞋，來檢測步態，對其進行分析和預測，已達到檢測和提高人們的健康水平的要求。
現在絕大多數的步態運動檢測系統都不是實時的且長時間工作的。在研究中，基於鞋子的智能系統被提出并得以實現，其具有便宜，緊湊，輕便等的優點。該系統包括壓力和加速度傳感器，處理芯片和無線傳輸模塊。這種設計將滿足日常步態信息的採集，并且把環境影響的因素放置最小，以達到室內室外都可長時間連續實時監測的要求。
在本論文中，對一系列日常生活的行為進行檢測和分類，尤其是最為危險的摔倒。本系統通過採用主成分分析，對已有的壓力傳感器進行的了分析，在保證了預測的準確性的前提下，將壓力傳感器由8對減少至4對，大大的降低了運算的次數，使得該系統實時性更好。同時本系統通過傾斜站立獲得的數據并應用于跌倒方向的檢測，並且有著良好的結果。
在本文中，對疲勞步態進行的分析，通過設計實驗，來區分不同疲勞程度下人們的步態。壓力信號較為明顯，同時加速度反映出每一步的劇烈程度。最終結果表明，壓力和加速度相輔相成，與疲勞程度的關係也很明顯，基於這種關係，本系統對疲勞程度進行了預測，通過壓力傳感器的信號，預測疲勞的程度，實驗結果也較為理想。
長時間的負責對身體的負擔很大，在本文中，著重的分析了在不同負重方式下，步態的變化，並且通過對比正常步態，採用支持向量機進行分類。在分類的過程中，通過重新採樣，將採集的數據轉變為一步為一組的數據，進行分類，最終得到的結果表明，平衡狀態下的負重是最好的。
對於健康而言，除了檢查受傷和疲勞，提升自身的身體素質也尤為重要。在本文中，介紹了兩種基於智能鞋的應用，在鍛煉下肢靈活度的同時，也避免了鍛煉的無聊。智能鞋鍵盤是通過腳踝的運動，基於一定的編碼方式，已達到在電腦上輸入文字的方式。智能鞋寫字系統是通過對下腳點的定位結合光電傳感器記錄位移，最終獲得文字輸入。應用BP神經網絡，對腳下點進行了分類，結合壓力傳感器和腿部建模，可以準確的區分30個的基本點的位置，從而獲得每筆的起點。最終完成寫字輸入。
Tao, Yanbo.
Thesis Ph.D. Chinese University of Hong Kong 2014.
Includes bibliographical references (leaves 134-141).
Abstracts also in Chinese.
Title from PDF title page (viewed on 12, October, 2016).
Detailed summary in vernacular field only.
Detailed summary in vernacular field only.
Detailed summary in vernacular field only.
Detailed summary in vernacular field only.
Detailed summary in vernacular field only.
Detailed summary in vernacular field only.

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Kalunga, Emmanuel K. "Development of a brain computer interface (BCI) based intention detection approach for persons with limited neuro-muscular control." 2013. http://encore.tut.ac.za/iii/cpro/DigitalItemViewPage.external?sp=1000733.

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M. Tech. Electrical Engineering
For the last 3 decades, interdisciplinary studies on the Brain Computer Interface (BCI) have grown in number. This common interest has been stirred up by recent developments in technology and opportunities seen in BCI. BCI systems provide an interface for communicating and controlling the physical environment, bypassing the normal neuromuscular pathways. They thus constitute an alternative means of control for the large population of people with limited to non-existent muscular abilities. Limitations in existing systems have prevented BCIs from being used in real life applications. New approaches are now being investigated with the aim of exporting BCI to home usage. This study investigates a BCI with realistic performances for practical home usage. It proposes a BCI to be used as a modality in a multimodal control of an exoskeleton.

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Solomon, Cleshain Theodore. "Driver attention and behaviour monitoring with the Microsoft Kinect sensor." Diss., 2015. http://hdl.handle.net/10500/21798.

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Modern vehicles are designed to protect occupants in the event of a crash with some vehicles better at this than others. However, passenger protection during an accident has shown to be not enough in many high impact crashes. Statistics have shown that the human error is the number one contributor to road accidents. This research study explores how driver error can be reduced through technology which observes driver behaviour and reacts when certain unwanted patterns in behaviour have been detected. Finally a system that detects driver fatigue and driver distraction has been developed using non-invasive machine vision concepts to monitor observable driver behaviour.
Electrical Engineering
M. Tech. (Electrical Engineering)

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Books on the topic "Explosives – Detection – Technological innovations"

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Aspects of explosives detection. Amsterdam: Elsevier, 2009.

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Hiltmar, Schubert, and Kuznetsov Andrey, eds. Detection of bulk explosives: Advanced techniques against terrorism. Dordrecht: Kluwer Academic Publishers, 2004.

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NATO Advanced Research Workshop on Detection of Liquid Explosives and Flammable Agents in Connection with Terrorism (2007 Saint Petersburg, Russia). Detection of liquid explosives and flammable agents in connection with terrorism. Dordrecht: Springer, 2008.

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Preventing the illegal use of explosive materials: A report to Congress on detecting, tagging, inactivating, and regulating explosive materials. [Washington, D.C.]: Bureau of Alcohol, Tobacco, Firearms and Explosives, Office of Enforcement Programs and Services, 2007.

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Office, General Accounting. Terrorism and drug trafficking: Technologies for detecting explosives and narcotics : report to Congressional requesters. Washington, D.C: The Office, 1996.

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Leveraging technology to improve aviation, part I and II: Hearing before the Subcommittee on Economic Security, Infrastructure Protection, and Cybersecurity of the Committee on Homeland Security, House of Representatives, One Hundred Ninth Congress, first session, July 13 and July 19, 2005. Washington: U.S. G.P.O., 2006.

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United States. Congress. Senate. Committee on Commerce, Science, and Transportation. Oversight on transportation security: Hearing before the Committee on Commerce, Science, and Transportation, United States Senate, One Hundred Eighth Congress, first session, September 9, 2003. Washington: U.S. Government Printing Office, 2014.

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Short, James M. Energetics science and technology in China. College Park, Maryland: CALCE, EPSC Press, 2010.

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Armstrong, Ronald W. Energetics science and technology in Central Europe. Edited by University of Maryland (College Park, Md.). Center for Advanced Life Cycle Engineering and University of Maryland (College Park, Md.). Center for Energetic Concepts Development. College Park, Maryland: CALCE, EPSC Press, 2012.

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Stotsky, Alexander A. Automotive engines: Control, estimation, statistical detection. Berlin: Springer, 2009.

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Book chapters on the topic "Explosives – Detection – Technological innovations"

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Kretser, Heidi, Emma Stokes, Serge Wich, David Foran, and Alexa Montefiore. "Technological Innovations Supporting Wildlife Crime Detection, Deterrence, and Enforcement." In Conservation Criminology, 155–77. Chichester, UK: John Wiley & Sons, Ltd, 2017. http://dx.doi.org/10.1002/9781119376866.ch9.

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Ortmann, Steffen, Michael Maaser, and Peter Langendoerfer. "Self-Adapting Event Configuration in Ubiquitous Wireless Sensor Networks." In Technological Innovations in Adaptive and Dependable Systems, 109–26. IGI Global, 2012. http://dx.doi.org/10.4018/978-1-4666-0255-7.ch007.

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Wireless Sensor Networks are the key-enabler for low cost ubiquitous applications in the area of homeland security, health-care, and environmental monitoring. A necessary prerequisite is reliable and efficient event detection in spite of sudden failures and environmental changes. Due to the fact that the sensors need to be low cost, they have only scarce resources leading to a certain level of failures of sensor nodes or sensing devices attached to the nodes. Available fault tolerant solutions are mainly customized approaches that revealed several shortcomings, particularly in adaptability and energy efficiency. The authors present a complete event detection concept including all necessary steps from formal event definition to autonomous device configuration. It features an event definition language that allows defining complex events as well as enhance the reliability by tailor-made voting schemes and application constraints. Based on that, this paper introduces a novel approach for self-adapting on-node and in-network processing, called Event Decision Tree (EDT). EDT autonomously adapts to available resources and environmental conditions, even though it requires to (re-)organize collaboration between neighboring nodes for evaluation. The authors’ approach achieves fine-grained event-related fault tolerance with configurable adaptation rate while enhancing maintainability and energy efficiency.

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Conference papers on the topic "Explosives – Detection – Technological innovations"

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Singh, Prabhat, Sakshi Kaur, Shivani Sharma, Gitika Sharma, Swati Vashisht, and Vinay Kumar. "Malware Detection Using Machine Learning." In 2021 International Conference on Technological Advancements and Innovations (ICTAI). IEEE, 2021. http://dx.doi.org/10.1109/ictai53825.2021.9673465.

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Agrawal, Harsh, Aditya Gupta, Aryan Sharma, and Prabhat Singh. "Road Pothole Detection Mechanism using Mobile Sensors." In 2021 International Conference on Technological Advancements and Innovations (ICTAI). IEEE, 2021. http://dx.doi.org/10.1109/ictai53825.2021.9673193.

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Chari, Harsha, Shailendra Aswale, Vijaykumar Naik Pawar, Pratiksha Shetgaonkar, and K. M. Chaman Kumar. "Advertisement Click Fraud Detection Using Machine Learning Techniques." In 2021 International Conference on Technological Advancements and Innovations (ICTAI). IEEE, 2021. http://dx.doi.org/10.1109/ictai53825.2021.9673199.

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Singh, Monika. "Analysis of Twitter Spam Detection Techniques-A Review." In 2021 International Conference on Technological Advancements and Innovations (ICTAI). IEEE, 2021. http://dx.doi.org/10.1109/ictai53825.2021.9673356.

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Puri, Digvijay, Kshamta Chauhan, Piyush Chauhan, and Anuj Gupta. "COVID Detection using X-Ray images through Machine Learning." In 2021 International Conference on Technological Advancements and Innovations (ICTAI). IEEE, 2021. http://dx.doi.org/10.1109/ictai53825.2021.9673362.

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Soni, Gaurav, Satnam Singh Saini, Simarjit Singh Malhi, Bhupinder Kaur Srao, Ashim Sharma, and Digvijay Puri. "Design and Implementation of Object Motion Detection Using Telegram." In 2021 International Conference on Technological Advancements and Innovations (ICTAI). IEEE, 2021. http://dx.doi.org/10.1109/ictai53825.2021.9673226.

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Shetgaonkar, Pratiksha, Jane Trinity Rodrigues, Shailendra Aswale, Vialli Luis Keji Gonsalves, Jane Crystal Rodrigues, and Aditya Naik. "Fake Review Detection Using Sentiment Analysis and Deep Learning." In 2021 International Conference on Technological Advancements and Innovations (ICTAI). IEEE, 2021. http://dx.doi.org/10.1109/ictai53825.2021.9673375.

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Bhardwaj, Shweta, Praveen Kumar, and Hima Bindu Maringanti. "Intrusion Detection in Internet of Things using Machine Learning Classifiers." In 2021 International Conference on Technological Advancements and Innovations (ICTAI). IEEE, 2021. http://dx.doi.org/10.1109/ictai53825.2021.9673449.

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Kumar, Vinit, Arvind Kumar, Abhinav Kumar Singh, and Ansh Pachauri. "Fake News Detection using Machine Learning and Natural Language Processing." In 2021 International Conference on Technological Advancements and Innovations (ICTAI). IEEE, 2021. http://dx.doi.org/10.1109/ictai53825.2021.9673378.

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Nagaraju, Jajam, and J. Vijaya. "Methodologies used for Customer Churn Detection in Customer Relationship Management." In 2021 International Conference on Technological Advancements and Innovations (ICTAI). IEEE, 2021. http://dx.doi.org/10.1109/ictai53825.2021.9673382.

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