Auswahl der wissenschaftlichen Literatur zum Thema „Howe Machine Co“

There was a place in my life where I had the time and space to reflect more deeply on the intricacies of home. Here my sense of where I was shifted and stirred, along with my relationship with some of the ‘things’ that made up my home. The washing machine that seemingly existed as a complete, discrete ‘thing’ prior to arriving in my home transgressed into my washing machine. It became, as I describe below, co-produced within my home life – a co-production constituted through a myriad of near and far relationalities. This ‘thing’ lost its place as a machine conveniently located within the kitchen and became places.

This study presents the development of a drilling technique for an innovative tabletop drilling machine that combines micro-EDM with drilling to fabricate micro-holes in diamond-tool. The mechanisms designs of double V-shaped bearings and double spindles which provide a precision clamping and vertical alignment for diamond-tool and micro-tube are devised to enable to machine a co-centric micro-hole for micro-tool. A diamond-tool, made with copper-based sintered alloy, is drilled by using the developed technique of co-centric micro-hole EDM-drilling into a hollow shaft which can create equilibrium of drilling forces, prevent a drilling squeezing to be occurred and enable to offer a temporary storing space for drilling chips. Relative experiments including the determinations of drilling ratio and discharge capacitance are carried out via this established machine. Experimental results show that excellent geometric and dimensional accuracy of micro-holes on the diamond-tool can be achieved.

Abstract Independent component analysis (ICA) of bacterial transcriptomes has emerged as a powerful tool for obtaining co-regulated, independently-modulated gene sets (iModulons), inferring their activities across a range of conditions, and enabling their association to known genetic regulators. By grouping and analyzing genes based on observations from big data alone, iModulons can provide a novel perspective into how the composition of the transcriptome adapts to environmental conditions. Here, we present iModulonDB (imodulondb.org), a knowledgebase of prokaryotic transcriptional regulation computed from high-quality transcriptomic datasets using ICA. Users select an organism from the home page and then search or browse the curated iModulons that make up its transcriptome. Each iModulon and gene has its own interactive dashboard, featuring plots and tables with clickable, hoverable, and downloadable features. This site enhances research by presenting scientists of all backgrounds with co-expressed gene sets and their activity levels, which lead to improved understanding of regulator-gene relationships, discovery of transcription factors, and the elucidation of unexpected relationships between conditions and genetic regulatory activity. The current release of iModulonDB covers three organisms (Escherichia coli, Staphylococcus aureus and Bacillus subtilis) with 204 iModulons, and can be expanded to cover many additional organisms.

Evolution sculpts both the body plans and nervous systems of agents together over time. By contrast, in artificial intelligence and robotics, a robot's body plan is usually designed by hand, and control policies are then optimized for that fixed design. The task of simultaneously co-optimizing the morphology and controller of an embodied robot has remained a challenge. In psychology, the theory of embodied cognition posits that behaviour arises from a close coupling between body plan and sensorimotor control, which suggests why co-optimizing these two subsystems is so difficult: most evolutionary changes to morphology tend to adversely impact sensorimotor control, leading to an overall decrease in behavioural performance. Here, we further examine this hypothesis and demonstrate a technique for ‘morphological innovation protection’, which temporarily reduces selection pressure on recently morphologically changed individuals, thus enabling evolution some time to ‘readapt’ to the new morphology with subsequent control policy mutations. We show the potential for this method to avoid local optima and converge to similar highly fit morphologies across widely varying initial conditions, while sustaining fitness improvements further into optimization. While this technique is admittedly only the first of many steps that must be taken to achieve scalable optimization of embodied machines, we hope that theoretical insight into the cause of evolutionary stagnation in current methods will help to enable the automation of robot design and behavioural training—while simultaneously providing a test bed to investigate the theory of embodied cognition.

Abstract: The quality of indoor air is a critical determinant of health and well-being, particularly Given the considerable amount of time individuals invest indoors. Recognizing the pivotal role of air quality, this paper introduces a novel Home Air Quality Monitoring System (HAQMS) designed to provide real-time, accurate assessments of air quality within residential environments. The HAQMS integrates advanced sensors and IoT (Internet of Things) technologies to detect and quantify a wide range of air pollutants, including particulate matter (PM2.5 and PM10), volatile organic compounds (VOCs), carbon dioxide (CO2), carbon monoxide (CO), and ozone (O3).The system architecture is delineated into three primary components: the sensor array for pollutant detection, a data processing unit employing advanced algorithms for real-time data analysis, and a user interface for displaying air quality metrics and providing health recommendations. Utilizing machine learning techniques, the system not only reports currentair quality but also predicts future air quality levels based on historical data and trend analysis. This predictive feature is pivotal for proactive measures in maintaining indoor air quality.

A generative text is a system constituted by non-conscious and conscious cognizers, digital and analogue processes, and mathematical and linguistic modes of representation. But how do algorithms cognize? And how is meaning constructed in a system where authorial intentions and readers’ experiences and interpretations are mediated by algorithmic agents? Through the analysis of How It Is In Common Tongues (Cayley and Howe, 2012), I intend to discuss the tensions that arise from the encounter between algorithmic and human cognition, and between the regimes of information and expression. Drawing on Katherine Hayles’ view on the cognitive non-conscious and Claude Shannon’s information theory I will start by establishing a distinction between information and meaning, between communication and expression, and between the regimes of information and of the literary. To reflect on the political ecology of digital mediation (situated in the informational regime of cybernetics), I will consider Matteo Pasquinelli’s perspective on the co-evolution of technology and economics, and discuss how algorithmic cognitive processes embody and reinforce the structures of contemporary cognitive capitalism. Finally, I will discuss the strategies of resistance enabled by aesthetic approaches to computation, such as the ones explored in this case study.

Environment perception is one of the important issues for unmanned ground vehicle (UGV). It is necessary to develop waters hole detection and tracking method in cross-country environment. This paper is related to the waters hole detection and tracking by using visual information. Image processing strategies based on support vector machine (SVM) and speeded up robust feature (SURF) methods are employed to detect and track waters hole. It focuses on how to extract the waters feature descriptor by exploring the machine learning algorithm. Based on the S/V color features and Gray Level Co-occurrence Matrix, the waters feature descriptor is extracted. The radial basis function (RBF) kernel function and the sampling-window size are determined by using the SVM classifier. The optimal parameters are obtained under the cross-validation conditions by the grid method. In terms of waters tracking, SURF feature matching method is applied to extract the remarkable feature points, then to observe the relation between feature point movement of adjacent frames and scale change ratio. Experiments show that SURF algorithm can still be effective to detect and match the remarkable feature points, against the negative effects of waters scale transformation and affine transform. The conclusion is that the computing speed of SURF algorithm is about three times faster than that of scale-invariant feature transform (SIFT) algorithm, and the comprehensive performance of SURF algorithm is better.

Home fire disasters are still common around us. This problem is a challenge in order to be able to find a solution. One solution to secure a home from a potential fire is to apply smarthome technology. Based on this problem, the idea arose to make an automatic fire extinguisher that can spray water with a water pump when it detects smoke (CO) due to a fire and circulates air in the room with an exhaust fan when an LPG gas cylinder leak is detected in the house so as to prevent a house fire. This tool is planned to be connected to the GSM module so that wherever we are we can find out if there is a fire in our home. This tool is made by utilizing the Smoke Gas Sensor (MQ 2), Temperature Sensor (LM35), Arduino Uno, GSM SIM 900 Module, Relay, Buzer, Exhaust Fan and Water Pump as its main components. Arduino Uno is used as the controller of this machine. The GSM SIM 900 Shield module is used for connection via SMS as a remote notification notification, LM35 as a temperature detector, and MQ 2 as a butane gas detector when there is a leak of LPG gas cylinders and fire smoke (CO) when a fire occurs. This tool can extinguish fires using a water pump from the detection of smoke (CO) and temperatures when more than 500 ppm and 40oC and circulate air using an exhaust fan with additional safety features when there is an LPG gas leak when gas is detected 500 ppm and send it with notification notification via SMS using the GSM SIM 900 module Shield. The measured voltage of the MQ2 sensor when clean air reaches 189.3 mV and the percent error of the LM35 reaches 0.88423%.

The new developed metal/composite co-cured material composed of carbon fiber–reinforced plastic and Al phases has been increasingly applied for manufacturing of attitude control flywheel in aerospace industry. However, drilling of co-cured material is still a challenging task to produce holes with high quality and low cost in the assembly chain and dynamic balance debugging of attitude control flywheel. In other words, the relevant mechanisms and experimental findings involved in the drilling process of carbon fiber–reinforced plastic/Al co-cured material is not clearly defined, which impedes the progress of attitude control flywheel production. To this end, this article specially addresses the experimental studies on the drilling process of carbon fiber–reinforced plastic/Al co-cured material with standard TiAlN-coated cemented carbide twist drill. The significance of this work aims to reveal the regardful cutting responses of the hole characteristics and tool wear modes during the practical drilling process of co-cured material. A full factorial experiment including three levels of feed rate and four levels of cutting speed was performed. The hole diameter shows different values in different positions while it indicates consistent pattern regardless of the cutting variables: the largest in the Al phase, followed by the upper and lower carbon fiber–reinforced plastic phases, respectively. Grooves and matrix degradation are the major machining defects for carbon fiber–reinforced plastic layers, while a great chip debris adhered to the machined surface is the case for Al layer. Subsequent wear analysis showed that abrasion was mainly maintained at the vicinity of major/minor cutting edges and drill edge corner, followed by chip adhesion on the chisel edge region. Carbide substrate of drill flank face is exposed, and thereafter cavities are formed under the strong mechanical abrasion. These results could provide several implications for industrial manufacturers during the attitude control flywheel production.

Il termine “Robotica” raccoglie un gran numero di concetti che vengono principalmente dalla Meccanica, Elettronica, Scienze del controllo e Tecnologie del Software. Questa scienza si è iniziata a sviluppare durante gli anni ’50 ma per un suo vasto utilizzo in campo industriale si sono dovuti attendere gli anni ’80. Inizialmente, si è cercato di automatizzare le operazioni maggiormente rischiose per l’uomo e in cui non vi fosse contatto fra robot e ambiente come ad esempio la saldatura con elettrodi e la verniciatura. Negli ultimi anni, si stanno cercando di automatizzare le operazioni più complicate effettuate in ambienti meno strutturati come ad esempio celle di lavoro dove è necessario la collaborazione tra lavoratori e robot. Pertanto, è sempre necessario gestire il contatto tra robot e ambiente, al fine di consentire la cooperazione tra robot e tra questi e i lavoratori. Il presente lavoro si inserisce in questa direzione con l’obiettivo di descrivere una collaborazione tra due robot per realizzare una operazione di peg – in – hole. I robot utilizzati sono I.Ca.Ro. acronimo di Innovative Cartesian Robot e Sphe.I.Ro. acronimo di Spherical Innovative Robot ed entrambi sono prototipi costruiti dal gruppo di Meccanica Applicata dell’ Università Politecnica delle Marche. Il presente lavoro descrive gli aspetti teorici del peg – in – hole, l’integrazione tra due robot, i controlli utilizzati e i risultati sperimentali ottenuti.
The word “Robotics” gathers a wide range of concepts which come mainly from Mechanics, Electronics, Control sciences and Software technologies. This science begun to develop during the 50s, but for its wide use in industry it had to wait until the 80s. Initially, it was used to automate risky operations where there were no contacts between robot and environment, such as welding with electrodes and spray painting. In recent years, it has been used to automate more demanding operations carried out in less structured environments, such as work cells where collaboration between humans and robots is required. Therefore, it is increasingly necessary to manage the contact between robot and environment in order to permit cooperation between robots or between robot and workers. The dissertation presented goes through the fields mentioned with the aim of describing how to implement a peg – in – hole operation using two robots. The robots used are I.Ca.Ro., the acronym of Innovative Cartesian Robot, and Sphe.I.Ro.. the acronym of Spherical Innovative Robot, and they are both prototypes of the Group of Machine Mechanics of the Polytechnic University of Marche. The present thesis describes the theoretical aspects of peg – in – hole, the integration of robots, the control used and the experimental results obtained.

碩士
國立臺灣科技大學
管理學院MBA
101
After stages of evolution in E-business the norm currently is a market of relentless saturated competition. Every industry now faces the same issue in internet marketing; incurring minimum cost while achieving an increase in competitive strength and company awareness. This study takes the first step by focusing on Taiwan's main economic pillars, which are the small and mid-sized corporations. One example is the well known successful food processing machinery limited company called Anko, which is the standard to based upon here in this report. The purpose is to find the best way of utilizing E-business tools to spread business into the world, increase sales potential and build effective business connections. Study's finding suggests the effect of utilizing the concept of localization. In terms of communicating with the outsides, one should activate multiple languages and multi-channel linkage; market with effective key words, so as to draw more potential clients. A company's internal innovativeness and consistent breakthrough in creations are the main criterion to sustaining corporate competitiveness.

Consciousness Mattering presents a contemporary Buddhist theory in which brains, bodies, environments, and cultures are relational infrastructures for human consciousness. Drawing on insights from meditation, neuroscience, physics, and evolutionary theory, it demonstrates that human consciousness is not something that occurs only in our heads and consists in the creative elaboration of relations among sensed and sensing presences, and more fundamentally between matter and what matters. Hershock argues that without consciousness there would only be either unordered sameness or nothing at all. Evolution is consciousness mattering. Shedding new light on the co-emergence of subjective awareness and culture, the possibility of machine consciousness, the risks of algorithmic consciousness hacking, and the potentials of intentionally altered states of consciousness, Hershock invites us to consider how freely, wisely, and compassionately consciousness matters.

In Person: Reenactment in Postwar and Contemporary Cinema delineates a new performative genre based on replay and self-awareness. The book argues that in-person reenactment, an actual person reenacting her past on camera, departs radically from other modes of mimetic reconstruction. In Person theorizes this figure’s protean temporality and revisionist capabilities, and it considers its import in terms of social representativity and exemplarity. Close readings of select, historicized examples define an alternate, confessional-performative vein to understand the self-reflexive nature of postwar and post-Holocaust testimonial cinemas. The book contextualizes Zavattini’s proposal that in neorealism everyone should act his own story in a sort of anti-individualist, public display (Love in the City and We the Women). It checks the convergence between verité experiments, a heightened self-critique in France, and the reception of psychodrama in France (Chronicle of a Summer and The Human Pyramid) in the late 1950s. And, through Bazin, it reflects on the quandaries of celebrity biopics: how the circularity of the star’s iconography is checked by her corporeal limits (Sophia: Her Own Story and the docudrama Torero!). In Person traces a shift from the exemplary and transformative ethos of 1950s reenactment toward the unredemptive stance of contemporary reenactment films such as Lanzmann’s Shoah, Zhang Yuan’s Sons, and Andrea Tonacci’s Hills of Chaos. It defines continuities between verité testimony (Chronicle and Moi un Noir) and later parajuridical films such as The Karski Report and Rithy Panh’s S21: The Khmer Rouge Killing Machine, suggesting the power of co-presence and in-person actualization for an ethics of viewership.

Nationalism: Past as Prologue began as a single volume being compiled by Ad Akande, a scholar from South Africa, who proposed it to me as co-author about two years ago. The original idea was to examine how the damaging roots of nationalism have been corroding political systems around the world, and creating dangerous obstacles for necessary international cooperation. Since I (Bruce E. Johansen) has written profusely about climate change (global warming, a.k.a. infrared forcing), I suggested a concerted effort in that direction. This is a worldwide existential threat that affects every living thing on Earth. It often compounds upon itself, so delays in reducing emissions of fossil fuels are shortening the amount of time remaining to eliminate the use of fossil fuels to preserve a livable planet. Nationalism often impedes solutions to this problem (among many others), as nations place their singular needs above the common good. Our initial proposal got around, and abstracts on many subjects arrived. Within a few weeks, we had enough good material for a 100,000-word book. The book then fattened to two moderate volumes and then to four two very hefty tomes. We tried several different titles as good submissions swelled. We also discovered that our best contributors were experts in their fields, which ranged the world. We settled on three stand-alone books:” 1/ nationalism and racial justice. Our first volume grew as the growth of Black Lives Matter following the brutal killing of George Floyd ignited protests over police brutality and other issues during 2020, following the police assassination of Floyd in Minneapolis. It is estimated that more people took part in protests of police brutality during the summer of 2020 than any other series of marches in United States history. This includes upheavals during the 1960s over racial issues and against the war in Southeast Asia (notably Vietnam). We choose a volume on racism because it is one of nationalism’s main motive forces. This volume provides a worldwide array of work on nationalism’s growth in various countries, usually by authors residing in them, or in the United States with ethnic ties to the nation being examined, often recent immigrants to the United States from them. Our roster of contributors comprises a small United Nations of insightful, well-written research and commentary from Indonesia, New Zealand, Australia, China, India, South Africa, France, Portugal, Estonia, Hungary, Russia, Poland, Kazakhstan, Georgia, and the United States. Volume 2 (this one) describes and analyzes nationalism, by country, around the world, except for the United States; and 3/material directly related to President Donald Trump, and the United States. The first volume is under consideration at the Texas A & M University Press. The other two are under contract to Nova Science Publishers (which includes social sciences). These three volumes may be used individually or as a set. Environmental material is taken up in appropriate places in each of the three books. * * * * * What became the United States of America has been strongly nationalist since the English of present-day Massachusetts and Jamestown first hit North America’s eastern shores. The country propelled itself across North America with the self-serving ideology of “manifest destiny” for four centuries before Donald Trump came along. Anyone who believes that a Trumpian affection for deportation of “illegals” is a new thing ought to take a look at immigration and deportation statistics in Adam Goodman’s The Deportation Machine: America’s Long History of Deporting Immigrants (Princeton University Press, 2020). Between 1920 and 2018, the United States deported 56.3 million people, compared with 51.7 million who were granted legal immigration status during the same dates. Nearly nine of ten deportees were Mexican (Nolan, 2020, 83). This kind of nationalism, has become an assassin of democracy as well as an impediment to solving global problems. Paul Krugman wrote in the New York Times (2019:A-25): that “In their 2018 book, How Democracies Die, the political scientists Steven Levitsky and Daniel Ziblatt documented how this process has played out in many countries, from Vladimir Putin’s Russia, to Recep Erdogan’s Turkey, to Viktor Orban’s Hungary. Add to these India’s Narendra Modi, China’s Xi Jinping, and the United States’ Donald Trump, among others. Bit by bit, the guardrails of democracy have been torn down, as institutions meant to serve the public became tools of ruling parties and self-serving ideologies, weaponized to punish and intimidate opposition parties’ opponents. On paper, these countries are still democracies; in practice, they have become one-party regimes….And it’s happening here [the United States] as we speak. If you are not worried about the future of American democracy, you aren’t paying attention” (Krugmam, 2019, A-25). We are reminded continuously that the late Carl Sagan, one of our most insightful scientific public intellectuals, had an interesting theory about highly developed civilizations. Given the number of stars and planets that must exist in the vast reaches of the universe, he said, there must be other highly developed and organized forms of life. Distance may keep us from making physical contact, but Sagan said that another reason we may never be on speaking terms with another intelligent race is (judging from our own example) could be their penchant for destroying themselves in relatively short order after reaching technological complexity. This book’s chapters, introduction, and conclusion examine the worldwide rise of partisan nationalism and the damage it has wrought on the worldwide pursuit of solutions for issues requiring worldwide scope, such scientific co-operation public health and others, mixing analysis of both. We use both historical description and analysis. This analysis concludes with a description of why we must avoid the isolating nature of nationalism that isolates people and encourages separation if we are to deal with issues of world-wide concern, and to maintain a sustainable, survivable Earth, placing the dominant political movement of our time against the Earth’s existential crises. Our contributors, all experts in their fields, each have assumed responsibility for a country, or two if they are related. This work entwines themes of worldwide concern with the political growth of nationalism because leaders with such a worldview are disinclined to co-operate internationally at a time when nations must find ways to solve common problems, such as the climate crisis. Inability to cooperate at this stage may doom everyone, eventually, to an overheated, stormy future plagued by droughts and deluges portending shortages of food and other essential commodities, meanwhile destroying large coastal urban areas because of rising sea levels. Future historians may look back at our time and wonder why as well as how our world succumbed to isolating nationalism at a time when time was so short for cooperative intervention which is crucial for survival of a sustainable earth. Pride in language and culture is salubrious to individuals’ sense of history and identity. Excess nationalism that prevents international co-operation on harmful worldwide maladies is quite another. As Pope Francis has pointed out: For all of our connectivity due to expansion of social media, ability to communicate can breed contempt as well as mutual trust. “For all our hyper-connectivity,” said Francis, “We witnessed a fragmentation that made it more difficult to resolve problems that affect us all” (Horowitz, 2020, A-12). The pope’s encyclical, titled “Brothers All,” also said: “The forces of myopic, extremist, resentful, and aggressive nationalism are on the rise.” The pope’s document also advocates support for migrants, as well as resistance to nationalist and tribal populism. Francis broadened his critique to the role of market capitalism, as well as nationalism has failed the peoples of the world when they need co-operation and solidarity in the face of the world-wide corona virus pandemic. Humankind needs to unite into “a new sense of the human family [Fratelli Tutti, “Brothers All”], that rejects war at all costs” (Pope, 2020, 6-A). Our journey takes us first to Russia, with the able eye and honed expertise of Richard D. Anderson, Jr. who teaches as UCLA and publishes on the subject of his chapter: “Putin, Russian identity, and Russia’s conduct at home and abroad.” Readers should find Dr. Anderson’s analysis fascinating because Vladimir Putin, the singular leader of Russian foreign and domestic policy these days (and perhaps for the rest of his life, given how malleable Russia’s Constitution has become) may be a short man physically, but has high ambitions. One of these involves restoring the old Russian (and Soviet) empire, which would involve re-subjugating a number of nations that broke off as the old order dissolved about 30 years ago. President (shall we say czar?) Putin also has international ambitions, notably by destabilizing the United States, where election meddling has become a specialty. The sight of Putin and U.S. president Donald Trump, two very rich men (Putin $70-$200 billion; Trump $2.5 billion), nuzzling in friendship would probably set Thomas Jefferson and Vladimir Lenin spinning in their graves. The road of history can take some unanticipated twists and turns. Consider Poland, from which we have an expert native analysis in chapter 2, Bartosz Hlebowicz, who is a Polish anthropologist and journalist. His piece is titled “Lawless and Unjust: How to Quickly Make Your Own Country a Puppet State Run by a Group of Hoodlums – the Hopeless Case of Poland (2015–2020).” When I visited Poland to teach and lecture twice between 2006 and 2008, most people seemed to be walking on air induced by freedom to conduct their own affairs to an unusual degree for a state usually squeezed between nationalists in Germany and Russia. What did the Poles then do in a couple of decades? Read Hlebowicz’ chapter and decide. It certainly isn’t soft-bellied liberalism. In Chapter 3, with Bruce E. Johansen, we visit China’s western provinces, the lands of Tibet as well as the Uighurs and other Muslims in the Xinjiang region, who would most assuredly resent being characterized as being possessed by the Chinese of the Han to the east. As a student of Native American history, I had never before thought of the Tibetans and Uighurs as Native peoples struggling against the Independence-minded peoples of a land that is called an adjunct of China on most of our maps. The random act of sitting next to a young woman on an Air India flight out of Hyderabad, bound for New Delhi taught me that the Tibetans had something to share with the Lakota, the Iroquois, and hundreds of other Native American states and nations in North America. Active resistance to Chinese rule lasted into the mid-nineteenth century, and continues today in a subversive manner, even in song, as I learned in 2018 when I acted as a foreign adjudicator on a Ph.D. dissertation by a Tibetan student at the University of Madras (in what is now in a city called Chennai), in southwestern India on resistance in song during Tibet’s recent history. Tibet is one of very few places on Earth where a young dissident can get shot to death for singing a song that troubles China’s Quest for Lebensraum. The situation in Xinjiang region, where close to a million Muslims have been interned in “reeducation” camps surrounded with brick walls and barbed wire. They sing, too. Come with us and hear the music. Back to Europe now, in Chapter 4, to Portugal and Spain, we find a break in the general pattern of nationalism. Portugal has been more progressive governmentally than most. Spain varies from a liberal majority to military coups, a pattern which has been exported to Latin America. A situation such as this can make use of the term “populism” problematic, because general usage in our time usually ties the word into a right-wing connotative straightjacket. “Populism” can be used to describe progressive (left-wing) insurgencies as well. José Pinto, who is native to Portugal and also researches and writes in Spanish as well as English, in “Populism in Portugal and Spain: a Real Neighbourhood?” provides insight into these historical paradoxes. Hungary shares some historical inclinations with Poland (above). Both emerged from Soviet dominance in an air of developing freedom and multicultural diversity after the Berlin Wall fell and the Soviet Union collapsed. Then, gradually at first, right wing-forces began to tighten up, stripping structures supporting popular freedom, from the courts, mass media, and other institutions. In Chapter 5, Bernard Tamas, in “From Youth Movement to Right-Liberal Wing Authoritarianism: The Rise of Fidesz and the Decline of Hungarian Democracy” puts the renewed growth of political and social repression into a context of worldwide nationalism. Tamas, an associate professor of political science at Valdosta State University, has been a postdoctoral fellow at Harvard University and a Fulbright scholar at the Central European University in Budapest, Hungary. His books include From Dissident to Party Politics: The Struggle for Democracy in Post-Communist Hungary (2007). Bear in mind that not everyone shares Orbán’s vision of what will make this nation great, again. On graffiti-covered walls in Budapest, Runes (traditional Hungarian script) has been found that read “Orbán is a motherfucker” (Mikanowski, 2019, 58). Also in Europe, in Chapter 6, Professor Ronan Le Coadic, of the University of Rennes, Rennes, France, in “Is There a Revival of French Nationalism?” Stating this title in the form of a question is quite appropriate because France’s nationalistic shift has built and ebbed several times during the last few decades. For a time after 2000, it came close to assuming the role of a substantial minority, only to ebb after that. In 2017, the candidate of the National Front reached the second round of the French presidential election. This was the second time this nationalist party reached the second round of the presidential election in the history of the Fifth Republic. In 2002, however, Jean-Marie Le Pen had only obtained 17.79% of the votes, while fifteen years later his daughter, Marine Le Pen, almost doubled her father's record, reaching 33.90% of the votes cast. Moreover, in the 2019 European elections, re-named Rassemblement National obtained the largest number of votes of all French political formations and can therefore boast of being "the leading party in France.” The brutality of oppressive nationalism may be expressed in personal relationships, such as child abuse. While Indonesia and Aotearoa [the Maoris’ name for New Zealand] hold very different ranks in the United Nations Human Development Programme assessments, where Indonesia is classified as a medium development country and Aotearoa New Zealand as a very high development country. In Chapter 7, “Domestic Violence Against Women in Indonesia and Aotearoa New Zealand: Making Sense of Differences and Similarities” co-authors, in Chapter 8, Mandy Morgan and Dr. Elli N. Hayati, from New Zealand and Indonesia respectively, found that despite their socio-economic differences, one in three women in each country experience physical or sexual intimate partner violence over their lifetime. In this chapter ther authors aim to deepen understandings of domestic violence through discussion of the socio-economic and demographic characteristics of theit countries to address domestic violence alongside studies of women’s attitudes to gender norms and experiences of intimate partner violence. One of the most surprising and upsetting scholarly journeys that a North American student may take involves Adolf Hitler’s comments on oppression of American Indians and Blacks as he imagined the construction of the Nazi state, a genesis of nationalism that is all but unknown in the United States of America, traced in this volume (Chapter 8) by co-editor Johansen. Beginning in Mein Kampf, during the 1920s, Hitler explicitly used the westward expansion of the United States across North America as a model and justification for Nazi conquest and anticipated colonization by Germans of what the Nazis called the “wild East” – the Slavic nations of Poland, the Baltic states, Ukraine, and Russia, most of which were under control of the Soviet Union. The Volga River (in Russia) was styled by Hitler as the Germans’ Mississippi, and covered wagons were readied for the German “manifest destiny” of imprisoning, eradicating, and replacing peoples the Nazis deemed inferior, all with direct references to events in North America during the previous century. At the same time, with no sense of contradiction, the Nazis partook of a long-standing German romanticism of Native Americans. One of Goebbels’ less propitious schemes was to confer honorary Aryan status on Native American tribes, in the hope that they would rise up against their oppressors. U.S. racial attitudes were “evidence [to the Nazis] that America was evolving in the right direction, despite its specious rhetoric about equality.” Ming Xie, originally from Beijing, in the People’s Republic of China, in Chapter 9, “News Coverage and Public Perceptions of the Social Credit System in China,” writes that The State Council of China in 2014 announced “that a nationwide social credit system would be established” in China. “Under this system, individuals, private companies, social organizations, and governmental agencies are assigned a score which will be calculated based on their trustworthiness and daily actions such as transaction history, professional conduct, obedience to law, corruption, tax evasion, and academic plagiarism.” The “nationalism” in this case is that of the state over the individual. China has 1.4 billion people; this system takes their measure for the purpose of state control. Once fully operational, control will be more subtle. People who are subject to it, through modern technology (most often smart phones) will prompt many people to self-censor. Orwell, modernized, might write: “Your smart phone is watching you.” Ming Xie holds two Ph.Ds, one in Public Administration from University of Nebraska at Omaha and another in Cultural Anthropology from the Chinese Academy of Social Sciences, Beijing, where she also worked for more than 10 years at a national think tank in the same institution. While there she summarized news from non-Chinese sources for senior members of the Chinese Communist Party. Ming is presently an assistant professor at the Department of Political Science and Criminal Justice, West Texas A&M University. In Chapter 10, analyzing native peoples and nationhood, Barbara Alice Mann, Professor of Honours at the University of Toledo, in “Divide, et Impera: The Self-Genocide Game” details ways in which European-American invaders deprive the conquered of their sense of nationhood as part of a subjugation system that amounts to genocide, rubbing out their languages and cultures -- and ultimately forcing the native peoples to assimilate on their own, for survival in a culture that is foreign to them. Mann is one of Native American Studies’ most acute critics of conquests’ contradictions, and an author who retrieves Native history with a powerful sense of voice and purpose, having authored roughly a dozen books and numerous book chapters, among many other works, who has traveled around the world lecturing and publishing on many subjects. Nalanda Roy and S. Mae Pedron in Chapter 11, “Understanding the Face of Humanity: The Rohingya Genocide.” describe one of the largest forced migrations in the history of the human race, the removal of 700,000 to 800,000 Muslims from Buddhist Myanmar to Bangladesh, which itself is already one of the most crowded and impoverished nations on Earth. With about 150 million people packed into an area the size of Nebraska and Iowa (population less than a tenth that of Bangladesh, a country that is losing land steadily to rising sea levels and erosion of the Ganges river delta. The Rohingyas’ refugee camp has been squeezed onto a gigantic, eroding, muddy slope that contains nearly no vegetation. However, Bangladesh is majority Muslim, so while the Rohingya may starve, they won’t be shot to death by marauding armies. Both authors of this exquisite (and excruciating) account teach at Georgia Southern University in Savannah, Georgia, Roy as an associate professor of International Studies and Asian politics, and Pedron as a graduate student; Roy originally hails from very eastern India, close to both Myanmar and Bangladesh, so he has special insight into the context of one of the most brutal genocides of our time, or any other. This is our case describing the problems that nationalism has and will pose for the sustainability of the Earth as our little blue-and-green orb becomes more crowded over time. The old ways, in which national arguments often end in devastating wars, are obsolete, given that the Earth and all the people, plants, and other animals that it sustains are faced with the existential threat of a climate crisis that within two centuries, more or less, will flood large parts of coastal cities, and endanger many species of plants and animals. To survive, we must listen to the Earth, and observe her travails, because they are increasingly our own.

Reading engagement is presented as an affect that organizes the relationships between children and books. The OECD-PISA reading framework has co-opted engagement as an attentive, involved, and joyful relationship with literature. A reading assemblage is offered to explain how engagement is instrumental to producing readers as bodies with potential for human capital, that is, children. The author uses a literary encounter to propose weird readings as an affect that breaks into the reading assemblage, complicating joy and pleasure, and as the affect that precludes the possibilities of creating relationships with materialities (books) from outside a reading assemblage.

AbstractCrowdwork platforms such as Amazon Mechanical Turk (AMT) are a crucial infrastructural component of our global data assemblage. Through these platforms, low-paid crowdworkers perform the vital labour of manually labelling large-scale and complex datasets, labels that are needed to train machine learning and AI models (Tubaro et al., Big Data & Society, 7(1), 2020) and which enable the functioning of much digital technology, from niche applications to global platforms such as Google, Amazon and Facebook.In this chapter, we reflect on how a ‘design justice’ approach might be valuable to build on insights gained from a series of exploratory discussions we have engaged in with US-based crowdworkers about how a crowdworker co-operative might work in practice, and begin to sketch out a potential software architecture that could form the basis of future participative approaches to the design and development of a crowdworker co-operative.We begin by describing and reflecting on our own evolving methodology and how it fits with the ‘design justice’ lens we propose for future work. Following this, we present findings from our discussions with crowdworkers about how a crowdwork co-operative might work in practice, including what values workers would like to see embedded in the design. We then finish with the outline of a prototype software architecture for a crowdworker co-operative that could be used as a starting point in future design work in collaboration with crowdworkers.

AbstractThe role of artificial intelligence in US education is expanding. As education moves toward providing customized learning paths, the use of artificial intelligence (AI) and machine learning (ML) algorithms in learning systems increases. This can be viewed as growing metaphorical exoskeletons for instructors, enabling them to provide a higher level of guidance, feedback, and autonomy to learners. In turn, the instructor gains time to sense student needs and support authentic learning experiences that go beyond what AI and ML can provide. Applications of AI-based education technology support learning through automated tutoring, personalizing learning, assessing student knowledge, and automating tasks normally performed by the instructor. This technology raises questions about how it is best used, what data provides evidence of the impact of AI and ML on learning, and future directions in interactive learning systems. Exploration of the use of AI and ML for both co-curricular and independent learnings in content presentation and instruction; interactions, communications, and discussions; learner activities; assessment and evaluation; and co-curricular opportunities provide guidance for future research.

AbstractThis chapter examines how the processes of human enhancement that have been brought about by the digital revolution (including AI and robotics, besides ICTs) have given rise to new social identities and relationships. The central question consists in asking how the Digital Technological Matrix, understood as a cultural code that supports artificial intelligence and related technologies, causes a hybridisation between the human and the non-human, and to what extent such hybridisation promotes or puts human dignity at risk. Hybridisation is defined here as entanglements and interchanges between digital machines, their ways of operating, and human elements in social practices. The issue is not whether AI or robots can assume human-like characteristics, but how they interact with humans and affect their social identities and relationships, thereby generating a new kind of society.

AbstractThis chapter proceeds in two parts. First, it situates the way that digital geographies render value by creating new markets for the creation, extraction, and capture of that value. Two digital geographies are highlighted: geofences/geoframing and cryptocurrencies on the blockchain. Drawing on the renewed interest in theorizing the digital urban growth machine, I analyze these new markets as forms of toxic innovation dominated by a focus on growth and extractive value. Second, I examine the possibilities for alternative responsible innovation that creates social value, which I call the Slow Data Economy. Inspired by the ethics of slowness, slow data centers accountability, the human-in-the-loop, local co-design, and vision making for the future city. By working with the possibilities of responsible innovation, I explore how the Slow Data Economy can be a form of “capital switching” in which investment is switched from a focus on growth and extraction to care and repair.

AbstractThe assumption of digital humanism that a human-centered approach is possible in the design, use, and further development of AI entails an alignment with human values. If the more ambitious goal of building a good digital society along the co-evolutionary path between humans and the digital machines invented by them is to be reached, inherent tensions need to be confronted. Some of them are the result of already existing inequalities and divergent economic, social, and political interests, exacerbated by the impact of digital technologies. Others arise from the question what makes us human and how our interaction with digital machines changes our identity and relations to each other. If digital humanism is to succeed, a widely shared set of practices and attitudes is needed that sensitize us to the diversity of social contexts in which digital technologies are deployed and how to deal with complex, non-linear systems.

In this article, Yannick Hofmann and Cecilia Preiß discuss the use of AI technologies in art by means of the interactive installation 'Wishing Well'. 'Wishing Well' by media artist Yannick Hofmann uses generative AI to transform the dreams, wishes, and fantasies expressed by exhibition visitors into images. Central aspects addressed are the use of AI technologies in art and the challenged identity of art in the face of new technical tools. The text discusses how co-creativity between humans and machines can be facilitated, as well as conveying ethical dilemmas that are to be expected in any use of generative AI. In this way, 'Wishing Well' is representative of the 'intelligent.museum' project, within whose framework it was developed.

AbstractResearch at the intersection between Science and Technology Studies (STS) and Public Communication of Science and Technology (PCST) investigates the role of science in society and how it is publicly perceived. An increasing attention has been paid to coverage of Science and Technology (S&T) issues in newspapers. Because of the availability of a huge amount of digitized news contents, the variety of the issues and their dynamic nature, new opportunities are offered to carry out STS and PCST investigations. The main contribution of this paper is a methodology and a system called TIPS that was co-shaped by sociologists and computer scientists in order to monitor the coverage of S&T issues in the news and to study how they are represented. The methodology relies on machine learning, information retrieval and data analytics approaches which aim at supporting expert users, e.g. sociologists, in the investigation of their research hypotheses.

Cloud computing brings convenience and cost efficiency to users, but multiplexing virtual machines (VMs) on a single physical machine (PM) results in various cybersecurity risks. For example, a co-resident attack could occur when malicious VMs use shared resources on the hosting PM to control or gain unauthorized access to other benign VMs. Most task schedulers do not contribute to both resource management and risk control. This article studies how to minimize the co-resident risks while optimizing the VM completion time through designing efficient VM allocation policies. A zero-trust threat model is defined with a set of co-resident risk mitigation parameters to support this argument and assume that all VMs are malicious. In order to reduce the chances of co-residency, deep reinforcement learning (DRL) is adopted to decide the VM allocation strategy. An effective cost function is developed to guide the reinforcement learning (RL) policy training. Compared with other traditional scheduling paradigms, the proposed system achieves plausible mitigation of co-resident attacks with a relatively small VM slowdown ratio.

Combinatorial optimization (CO) problems have many important application domains, including social networks, manufacturing, and transportation. However, as an NP-hard problem, the traditional CO problem-solvers require domain knowledge and hand-crafted heuristics. Facing big data challenges, can we solve these challenging problems with a learning structure within a short time? This article will demonstrate how to solve the combinatorial optimization problems with the deep reinforcement learning (DRL) method. Reinforcement learning (RL) is a subfield of machine learning (ML) that learns the optimal policy over time. Building on Markov decision process, RL has the solid theoretical foundation to obtain the optimal solution. Once parameters of DRL are trained, a new problem case can be solved quickly. Moreover, DRL learns the optimal solution without labels by maximizing the accumulative discounted reward received from the environment. This article will discuss three typical CO problems and present the advantages of DRL over other traditional methods.

Classical co-processors are an important component of any full quantum stack. We shall discuss how the Quantinuum System Model H1 machine interacts with a classical co-processor to implement crucial features of quantum error correction.

Artificial Intelligence (AI) is universally reaching every industry thus far, it is coming to the fore in construction industry by redesigning project world and altering the role of project managers. It provides the ability for computers to simulate human-like thinking and is comprised of machine learning, Internet of things (IoT), automation, natural language processing and robotics. In construction industry, AI is affecting project planning, time and cost management, optimization of resources as well as post-construction activities. Along with assessing teamwork patterns and making recommendations, it also has an impact on the workforce and how individuals handle projects. Despite a broad range of research papers written about this theme there are still not so much of practical applications conducted in practice. Therefore, the aim of this study is to provide an overview of using AI in Project Management and to show how it is affecting construction industry along with exhibiting future trends. This article will also show positive and negative sides of AI in Project Management and how does it manage competencies. It will propose possible utilitarian solutions including a critical review over the research topic. The outcomes of this study contribute to the body of knowledge on AI in project management through a comprehensive investigation of literature and provide guidelines for further research on the phenomenon of AI in project management.

Nowadays, the rapid development of technology increase fiber laser cutting machine’s cutting dynamics day by day, these dynamics, such as speed, acceleration, and jerk, refer to the quantitative measures used to describe the motion of an object. In order to enhance these dynamics, it is imperative to modify the design of the motion mechanism. We can employ more powerful electrical or magnetic motor for motion system however dimensional constraints limits this implementation. The aim of this study evolves mechanical design and manufacturing material of Y axis. “Y axis” significant part of the machine which assembly “fiber cutting head” resemblance bridge over the machine main body. Steel alloys predominantly recognize as preferred manufacturing alloy material for this part on account of manufacturing in addition processing of steel parts comparatively effortless than aluminum-based alloys additionally welding and assembly process require more knowledge than production of steel alloys-based material. Aluminum is an economically viable and lightweight metal with the ability to undergo heat treatment and withstand relatively high levels of stress. It ranks among the easily produced high-performance materials, thereby contributing to reduced manufacturing and maintenance costs. Aluminum production process known higher level carbon dioxide emission. “Aluminum Institute reported 11.2 t CO₂/t Al through primary aluminum production and 0.2 t CO₂/t Al through secondary aluminum production.” “World Steel Association, in the year 2020 data's when examining the average emissions per unit of steel produced in 2020, it is each metric ton of steel contributed to the release of approximately 1.89 t CO₂/t into the atmosphere." Based on the presented data, it is evident that the carbon dioxide emissions associated with the production of 1 ton of aluminum are approximately six times higher than the carbon dioxide emissions from steel production. The incorporation of an aluminum-based Y-axis in the machinery has led to a notable reduction in weight. Consequently, the two servo motors responsible for actuating this component will consume less electrical current during its operation throughout the machinery's operational lifespan. This decrease in electrical power consumption is expected to translate into a discernible advantage in terms of CO2 emissions over a specific timeframe, thereby will make aluminum bridge a probably more environmentally favorable choice. This article provides of how to enhance of machine dynamics with using aluminum based “Y axis” in addition that such as carbon footprint, manufacturing process. Upon the conclusion of the research, a comprehensive analysis will be provided regarding the advantages and disadvantages of employing an aluminum “Y axis” rather than a steel “Y axis” in terms of design considerations.

To best assist human designers with different styles, Machine Learning (ML) systems need to be able to adapt to them. However, there has been relatively little prior work on how and when to best adapt an ML system to a co-designer. In this paper we present threshold designer adaptation: a novel method for adapting a creative ML model to an individual designer. We evaluate our approach with a human subject study using a co-creative rhythm game design tool. We find that designers prefer our proposed method and produce higher quality content in comparison to an existing baseline.

The goal of this research work is to reduce wait time of HPC (high performance computing) applications in schedulers queue by applying a co-scheduling strategy. This strategy allows the execution of more than one task with different non-overlapping requirements for computational resources simultaneously. Co-scheduling strategy reduces task queue wait time and improves utilization of cluster resources when compared to the scheduling strategies that do not allow for parallel task execution on the same machine. We have proposed a method for measuring application processing speed in its run-time, which can be used as a feedback for scheduling strategies. In this work, we have formalized the co-scheduling problem and proposed strategies for solving it. For some strategies we have shown analytically the upper bounds values of their competitive ratios. Besides that for the proposed scheduling strategies we ran numerical experiments using imitation models to show how they compare to the optimal strategy.

Recent work in multi-agent intention scheduling has shown that enabling agents to predict the actions of other agents when choosing their own actions can be beneficial. However existing approaches to 'intention-aware' scheduling assume that the programs of other agents are known, or are "similar" to that of the agent making the prediction. While this assumption is reasonable in some circumstances, it is less plausible when the agents are not co-designed. In this paper, we present a new approach to multi-agent intention scheduling in which agents predict the actions of other agents based on a high-level specification of the tasks performed by an agent in the form of a reward machine (RM) rather than on its (assumed) program. We show how a reward machine can be used to generate tree and rollout policies for an MCTS-based scheduler. We evaluate our approach in a range of multi-agent environments, and show that RM-based scheduling out-performs previous intention-aware scheduling approaches in settings where agents are not co-designed

Feature attribution methods are typically used post-training to judge if a deep learning classifier is using meaningful concepts in an input image when making classifications. In this study, we propose using feature attribution methods to give a classifier automated feedback throughout the training process via a novel loss function. We call such a loss function, a heatmap loss function. Heatmap loss functions enable us to incentivize a model to rely on relevant sections of the input image when making classifications. Two groups of models were trained, one group with a heatmap loss function and the other using categorical cross entropy (CCE). Models trained with the heatmap loss function were capable of achieving equivalent classification accuracies on a test dataset of synthesised cardiac MRI slices. Moreover, HiResCAM heatmaps suggest that these models relied to a greater extent on regions of the MRI slices within the heart. A further experiment demonstrated how heatmap loss functions can be used to prevent deep learning classifiers from using noncausal concepts that disproportionately co-occur with images of a certain class when making classifications. This suggests that heatmap loss functions could be used to prevent models from learning dataset biases by directing where the model should be looking when making classifications.

In a high thrust-weight-ratio aero-engine, turbine blades are exposed to extremely high temperature and pressure which sets higher demands in the blade cooling technology. The mainstream types of cooling include internal airflow cooling, film cooling, and thermal barrier coating. Cooling efficiency is substantially subject to the machining accuracy of blades, more specifically the film-cooling holes on them. A coordinate measuring machine(CMM) is extensively used in the measurement and inspection of turbine blades which enables measuring blade patterns and building geometric models. However, the probes utilized by a CMM are similar in scale to that of a film-cooling hole, making it almost impossible for a CMM to measure film-cooling holes. The probes are prone to damage and the measurement accuracy cannot be guaranteed. This paper proposed a non-contact measuring technique to cope with the inspection of turbine blades. The technique is based on light-field imaging. A light-field camera with a high magnification lens is applied to caperture images of film-cooling holes and their neighborhood which are then inputted to a 3D reconstruction algorithm. A point cloud is derived by the algorithm and fundamental parameters are extracted. The whole inspection requires only one platform and is able to measure shaped film-cooling holes.

Abstract Laser Powder Bed Fusion (LPBF) is one of the most promising forms of Additive Manufacturing (AM), allowing easily customized metal manufactured parts. Industry use is currently limited due to the often unknown and unreliable part quality, which is largely caused by the complex relationships between process parameters that include laser power, laser speed, scan strategy, and other machine settings. Melt pools can be monitored with a camera aligned co-axially with the laser to monitor part quality. However, the number of images acquired can be large, exceeding hundreds of thousands for a single part. This paper investigates how the K-Means algorithm, an unsupervised machine learning method, can be used to cluster images of melt pools based on their shape, including undesirable anomalous melt pools. Another unsupervised learning method in this paper is the U-Net autoencoder, which identifies anomalous melt pools by identifying images with a large reconstruction loss. The K-Means clustering or autoencoder provides labels that can be used for training a convolutional neural network image classifier. The image classifier can then be used to identify anomalous melt pools during the LPBF process. This paper provides a first step for real-time process control of the LPBF process by demonstrating how anomalous melt pools can be automatically identified in real-time.

Automated vehicles (AVs)—and the automated driving systems (ADSs) that enable them—are increasing in prevalence but remain far from ubiquitous. Progress has occurred in spurts, followed by lulls, while the motor transportation system learns to design, deploy, and regulate AVs. Automated Vehicles: A Human/Machine Co-learning Experience focuses on how engineers, regulators, and road users are all learning about a technology that has the potential to transform society. Those engaged in the design of ADSs and AVs may find it useful to consider that the spurts and lulls and stakeholder tussles are a normal part of technology transformations; however, this report will provide suggestions for effective stakeholder engagement.

Crossref, DataCite, and ORCID work together to provide foundational open infrastructure that is integral to the global research ecosystem. We offer unique, persistent identifiers (PIDs) — Crossref and DataCite DOIs for research outputs and ORCID iDs for people — alongside collecting comprehensive, open metadata that is non-proprietary, accessible, interoperable, and available across borders, disciplines, and time. As sustainable community-driven scholarly infrastructure providers ORCID, Crossref and Datacite, guarantee data provenance and machine-readability. Persistent identifiers combined with open, standardized, and machine-readable metadata enable reliable and robust connections to be made between research outputs, organizations, individuals, and much more, as well as being beneficial to others who build services and tools on top of the open infrastructure we provide making content more discoverable. In this webinar we discuss: - Who we are - What we mean by Open Scholarly Infrastructure - How our organizations work together for the benefit of the scholarly community - How the Principles of Open Scholarly Infrastructure (POSI) help to build trust and accountability as well as ensure we are around for the long term. This is the first of the joint webinar series co-organized by Crossref, DataCite, and ORCID for the Open Science community in the APAC region. The webinar is presented in English and lasts 90 minutes including time for Q&A. This webinar took place on 27 June 2022 at 7am UTC/ 9am CEST / 5pm AEST.

Managing the ever-growing volume and velocity of data across the battlefield is a critical problem for warfighters. Solving this problem will require a fundamental change in how battlefield analyses are performed. A new approach to making decisions on the battlefield will eliminate data transport delays by moving the analytical capabilities closer to data sources. Decision cycles depend on the speed at which data can be captured and converted to actionable information for decision making. Real-time situational awareness is achieved by locating computational assets at the tactical edge. Accelerating the tactical decision process leverages capabilities in three technology areas: (1) High-Performance Computing (HPC), (2) Machine Learning (ML), and (3) Internet of Things (IoT). Exploiting these areas can reduce network traffic and shorten the time required to transform data into actionable information. Faster decision cycles may revolutionize battlefield operations. Presented is an overview of an artificial intelligence (AI) system design for near-real-time analytics in a tactical operational environment executing on co-located, mobile HPC hardware. The report contains the following sections, (1) an introduction describing motivation, background, and state of technology, (2) descriptions of tactical decision process leveraging HPC problem definition and use case, and (3) HPC tactical data analytics framework design enabling data to decisions.

The report provides a review of how risk is conceived of, modelled, and mapped in studies of infectious water, sanitation, and hygiene (WASH) related diseases. It focuses on spatial epidemiology of cholera, malaria and dengue to offer recommendations for the field of WASH-related disease risk mapping. The report notes a lack of consensus on the definition of disease risk in the literature, which limits the interpretability of the resulting analyses and could affect the quality of the design and direction of public health interventions. In addition, existing risk frameworks that consider disease incidence separately from community vulnerability have conceptual overlap in their components and conflate the probability and severity of disease risk into a single component. The report identifies four methods used to develop risk maps, i) observational, ii) index-based, iii) associative modelling and iv) mechanistic modelling. Observational methods are limited by a lack of historical data sets and their assumption that historical outcomes are representative of current and future risks. The more general index-based methods offer a highly flexible approach based on observed and modelled risks and can be used for partially qualitative or difficult-to-measure indicators, such as socioeconomic vulnerability. For multidimensional risk measures, indices representing different dimensions can be aggregated to form a composite index or be considered jointly without aggregation. The latter approach can distinguish between different types of disease risk such as outbreaks of high frequency/low intensity and low frequency/high intensity. Associative models, including machine learning and artificial intelligence (AI), are commonly used to measure current risk, future risk (short-term for early warning systems) or risk in areas with low data availability, but concerns about bias, privacy, trust, and accountability in algorithms can limit their application. In addition, they typically do not account for gender and demographic variables that allow risk analyses for different vulnerable groups. As an alternative, mechanistic models can be used for similar purposes as well as to create spatial measures of disease transmission efficiency or to model risk outcomes from hypothetical scenarios. Mechanistic models, however, are limited by their inability to capture locally specific transmission dynamics. The report recommends that future WASH-related disease risk mapping research: - Conceptualise risk as a function of the probability and severity of a disease risk event. Probability and severity can be disaggregated into sub-components. For outbreak-prone diseases, probability can be represented by a likelihood component while severity can be disaggregated into transmission and sensitivity sub-components, where sensitivity represents factors affecting health and socioeconomic outcomes of infection. -Employ jointly considered unaggregated indices to map multidimensional risk. Individual indices representing multiple dimensions of risk should be developed using a range of methods to take advantage of their relative strengths. -Develop and apply collaborative approaches with public health officials, development organizations and relevant stakeholders to identify appropriate interventions and priority levels for different types of risk, while ensuring the needs and values of users are met in an ethical and socially responsible manner. -Enhance identification of vulnerable populations by further disaggregating risk estimates and accounting for demographic and behavioural variables and using novel data sources such as big data and citizen science. This review is the first to focus solely on WASH-related disease risk mapping and modelling. The recommendations can be used as a guide for developing spatial epidemiology models in tandem with public health officials and to help detect and develop tailored responses to WASH-related disease outbreaks that meet the needs of vulnerable populations. The report’s main target audience is modellers, public health authorities and partners responsible for co-designing and implementing multi-sectoral health interventions, with a particular emphasis on facilitating the integration of health and WASH services delivery contributing to Sustainable Development Goals (SDG) 3 (good health and well-being) and 6 (clean water and sanitation).