bluuebunny/crossref_metadata_2025 huggingface dataset:
Sonic Rupture
Authors: Lacey Jordan
Published: November 2020

Sonic Rupture applies a practitioner-led approach to urban soundscape design, which foregrounds the importance of creative encounters in global cities. This presents an alternative to those urban soundscape design approaches concerned with managing the negative health impacts of noise. Instead, urban noise is considered to be a creative material and cultural expression that can be reshaped with citywide networks of sonic installations.

By applying affect theory the urban is imagined as an unfolding of the Affective Earth, and noise as its homogenous (and homogenizing) voice. It is argued that noise is an expressive material with which sonic practitioners can interface, to increase the creative possibilities of urban life. At the heart of this argument is the question of relationships: how do we augment and diversify those interconnections that weave together the imaginative life and the expressions of the land?

The book details seven sound installations completed by the author as part of a creative practice research process, in which the sonic rupture model was discovered. The sonic rupture model, which aims to diversify human experiences and urban environments, encapsulates five soundscape design approaches and ten practitioner intentions. Multiple works of international practitioners are explored in relation to the discussed approaches.

Sonic Rupture provides the domains of sound art, music, creative practice, urban design, architecture and environmental philosophy with a unique perspective for understanding those affective forces, which shape urban life. The book also provides a range of practical and conceptual tools for urban soundscape design that can be applied by the sonic practitioner.
Against Ambience and Other Essays
Authors: Kim-Cohen Seth
Published: November 2020

Against Ambience diagnoses - in order to cure – the art world’s recent turn toward ambience. Over the course of three short months – June to September, 2013 – the four most prestigious museums in New York indulged the ambience of sound and light: James Turrell at the Guggenheim, Soundings at MoMA, Robert Irwin at the Whitney, and Janet Cardiff at the Met. In addition, two notable shows at smaller galleries indicate that this is not simply a major-donor movement. Collectively, these shows constitute a proposal about what we wanted from art in 2013.

While we’re in the soft embrace of light, the NSA and Facebook are still collecting our data, the money in our bank accounts is still being used to fund who-knows-what without our knowledge or consent, the government we elected is still imprisoning and targeting people with whom we have no beef. We deserve an art that is the equal of our information age. Not one that parrots the age’s self-assertions or modes of dissemination, but an art that is hyper-aware, vigilant, active, engaged, and informed.

We are now one hundred years clear of Duchamp’s first readymades. So why should we find ourselves so thoroughly in thrall to ambience? Against Ambience argues for an art that acknowledges its own methods and intentions; its own position in the structures of cultural power and persuasion. Rather than the warm glow of light or the soothing wash of sound, Against Ambience proposes an art that cracks the surface of our prevailing patterns of encounter, initiating productive disruptions and deconstructions.
Beyond Unwanted Sound
Authors: Thompson Marie
Published: November 2020

Noise is so often a ‘stench in the ear’ – an unpleasant disturbance or an unwelcome distraction. But there is much more to noise than what greets the ear as unwanted sound.

Beyond Unwanted Sound is about noise and how we talk about it. Weaving together affect theory with cybernetics, media histories, acoustic ecology, geo-politics, sonic art practices and a range of noises, Marie Thompson critiques both the conservative politics of silence and transgressive poetics of noise music, each of which position noise as a negative phenomenon. Beyond Unwanted Sound instead aims to account for a broader spectrum of noise, ranging from the exceptional to the banal; the overwhelming to the inaudible; and the destructive to the generative. What connects these various and variable manifestations of noise is not negativity but affectivity. Building on the Spinozist assertion that to exist is to be affected, Beyond Unwanted Sound asserts that to exist is to be affected by noise.
Refrigerator
Authors: Rees Jonathan
Published: November 2020

Object Lessons is a series of short, beautifully designed books about the hidden lives of ordinary things.

It is responsible for a greater improvement in human diet and longevity than any other technology of the last two thousand years-but have you ever thought seriously about your refrigerator? That box humming in the background displays more than you might expect, even who you are and the society in which you live. Jonathan Rees examines the past, p resent, and future of the household refrigerator with the aim of preventing its users from ever taking it for granted again. No mere container for cold Cokes and celery stalks, the refrigerator acts as a mirror-and what it reflects is chilling indeed.

Object Lessons is published in partnership with an essay series in The Atlantic.
Veil
Authors: Zakaria Rafia
Published: November 2020

Object Lessons is a series of short, beautifully designed books about the hidden lives of ordinary things.

The veil can be an instrument of feminist empowerment, and veiled anonymity can confer power to women. Starting from her own marriage ceremony at which she first wore a full veil, Rafia Zakaria examines how veils do more than they get credit for.

Part memoir and part philosophical investigation, Veil questions that what is seen is always good and free, and that what is veiled can only signal servility and subterfuge. From personal encounters with the veil in France (where it is banned) to Iran (where it is compulsory), Zakaria shows how the garment's reputation as a pre-modern relic is fraught and up for grabs. The veil is an object in constant transformation, whose myriad meanings challenge the absolute truths of patriarchy.

Object Lessons is published in partnership with an essay series in The Atlantic.
Egg
Authors: Walker Nicole
Published: November 2020

Object Lessons is a series of short, beautifully designed books about the hidden lives of ordinary things. This book is about a strange object-strange in part because it is something that we all have been, and that many of us eat. Nicole Walker–s Egg relishes in sharp juxtapositions of seemingly fanciful or repellent topics, so that reproductive science and gustatory habits are considered alongside one another, and personal narrative and broad swaths of natural history jostle, like yolk and albumen. Mapping curious eggs across times, scales, and spaces, Egg draws together surprising perspectives on this common object-egg as food, as art object, as metaphor and feminist symbol, as cultural icon. Object Lessons is published in partnership with an essay series in The Atlantic.
Nick Cave and the Bad Seeds' Murder Ballads
Authors: Elijah Holley Santi
Published: November 2020

In a bar called The Bucket of Blood, a man shoots the bartender four times in the head. In the small town of Millhaven, a teenage girl secretly and gleefully murders her neighbors. A serial killer travels from home to home, quoting John Milton's Paradise Lost in his victims' blood.

Murder Ballads, the ninth studio album from Nick Cave and the Bad Seeds, is a gruesome, blood splattered reimagining of English ballads, American folk and blues music, and classic literature. Most of the stories told on Murder Ballads have been interpreted many times, but never before had they been so graphic or profane. Though earning the band their first Parental Advisory warning label, Murder Ballads, released in 1996, brought Nick Cave and the Bad Seeds their biggest critical and commercial success, thanks in part to the award-winning single “Where the Wild Roses Grow,” an unlikely duet with Australian pop singer Kylie Minogue. Closely examining each of the ten songs on the album, Santi Elijah Holley investigates the stories behind the songs, and the numerous ways these ballads have been interpreted through the years. Murder Ballads is a tour through the evolution of folk music, and a journey into the dark secrets of American history. Santi Elijah Holley is a journalist and essayist in Portland, Oregon, covering music, books, culture, and religion. His work has appeared in The Atlantic, The Guardian, VICE, Tin House, and elsewhere.
24-Carat Black's Ghetto: Misfortune’s Wealth
Authors: Schonfeld Zach
Published: November 2020

In 1973, the musical collective 24-Carat Black released an unheralded masterpiece on Stax Records—and then disappeared. Ghetto: Misfortune’s Wealth, a soul-funk concept album primarily written by the ex-Motown arranger Dale Warren, was too bleak, ambitious, or just outright bizarre to reach mainstream audiences. 24-Carat Black collapsed when Stax went bankrupt, and the group’s only completed album sank into cultural obscurity. With deep reporting elucidating an untold story full of cinematic details, this book traces how Ghetto went from commercial flop to enigmatic underground classic embraced by the hip-hop community. It also chronicles, in infuriating detail, how the music industry of the 1970s systematically exploited soul musicians and then left them struggling to get paid—and where 24-Carat Black fits into this broader injustice. This is a fascinating a nd multilayered story about a remarkable album nearly lost to history. It’s also a rare glimpse into what it’s like to have your music resurrected by rap samples decades after your career fell apart.
Popular Music in Japan
Authors: Mitsui Tōru
Published: November 2020

Popular music in Japan has been under the overwhelming influence of American, Latin American and European popular music remarkably since 1945, when Japan was defeated in World War II. Beginning with gunka and enka at the turn of the century, tracing the birth of hit songs in the record industry in the years preceding the War, and ranging to the adoption of Western genres after the War the rise of Japanese folk and rock, domestic exoticism as a new trend and J-Pop. Popular Music in Japan is a comprehensive discussion of the evolution of popular music in Japan. In eight revised and updated essays written in English by renowned Japanese scholar Toru Mitsui, this book tells the story of popular music in Japan since the late 19th century when Japan began positively embracing the West.
Walls Without Cinema
Authors: Dudenhoeffer Larrie
Published: November 2020

Walls without Cinema: State Security and Subjective Embodiment in Twenty-First Century U.S. Filmmaking closely examines the near-ubiquitous images of state security walls, domes, and other such defense enclosures flashing across movie screens since 2006, the year of the ratification of George W. Bush’s Secure Fence Act. This study shows that many of the films of this era enable us to imaginatively test the effects of these security mechanisms on citizens, immigrants, refugees, and other sovereign states, challenging our commitment to constructing them, maintaining them, staffing them, and subsidizing their enormous overheads. With case studies ranging from Atomic Blonde and Ready Player One to Black Panther and Elysium, Walls without Cinema serves a timely counterpoint to the xenophobic rhetoric and abusive, carceral security conditions that characterize the Trump administration’s management of the Mexico-U.S. border situation.
Beyond the Republican Revival
Authors: Ghosh Eric
Published: November 2020

This is the first book-length treatment of both the non-positive and the positive-liberty strands of the republican revival in political and constitutional theory. The republican revival, pursued especially over the last few decades, has presented republicanism as an exciting alternative to the dominant tradition of liberalism.

The book provides a sharply different interpretation of liberty from that found in the republican revival. It argues that this different interpretation is not only historically more faithful to some prominent writers identified with the republican tradition, but is also normatively more attractive. The normative advantages are revealed through discussion of some central concerns relating to democracy and constitutionalism, including the justification for democracy and the interpretation of constitutional rights.

The book also looks beyond republican liberty by drawing on the republican device of sortition (selection by lot). It proposes the use of large juries to decide bill-of-rights matters. This novel proposal indicates how democracy might be reconciled with constitutional review based on a bill of rights. Republicanism is not pitted against liberalism: the favoured values and institutions fit with liberal commitments.
Yugoslavia and Political Assassinations
Authors: Nielsen Christian Axboe
Published: November 2020

The first book to analyse how and why the Yugoslav State Security Service carried out multiple assassinations (and kidnappings) to ‘protect’ itself. Offering a complete history of the programme, from the inception of the State Security Service to the recent trials of individuals involved, it draws on Christian Axboe Nielsen’s unique wealth of experience and research as an academic and as an expert witness in criminal trials at the International Criminal Court.

The result is a ground-breaking contribution to the history of targeted assassinations, communist history, state security services, international human rights law and war crimes tribunals.
Arthur Jeffress
Authors: Hedley Gill
Published: November 2020

Arthur Jeffress was an art dealer and collector from a Virginian family who bequeathed his “subversive little collection” (Derek Hill) to Tate and Southampton City Art Gallery on his suicide in 1961. That suicide, a result of his expulsion from Venice, has been the subject of speculation in many memoirs.

Gill Hedley’s biography of Jeffress has benefited from access to many hundreds of unpublished letters written between Jeffress and Robert Melville, who ran Jeffress’ own gallery from 1955-1961. The letters were written largely while Jeffress was in Venice and reveal a vivid picture of the London gallery world as well as frank details of artists, collectors and the definitive story of his suicide.

Previously unpublished research reveals new information about the lives of Jeffress’ lover John Deakin, his business partner Erica Brausen, the French photographer André Ostier and Henry Clifford, and the way in which all of them influenced Jeffress’ first steps as a collector from the 1930s onwards.
The Cloud-Capped Star (Meghe Dhaka Tara)
Authors: Dass Manishita
Published: November 2020

Ritwik Ghatak’s The Cloud-Capped Star (Meghe Dhaka Tara, 1960) has been hailed as ‘one of the great classics of world cinema’ (Adrian Martin), and ‘one of the five or six greatest melodramas in cinema history’ (Serge Daney). A striking blend of modernist aesthetics and melodramatic force, it is arguably the best-known film by Ghatak, widely considered to be one of the most original, politically committed, and formally innovative film-makers from India. The film’s focus on a family uprooted by the Partition of India and its powerful exploration of displacement and historical trauma gives it a renewed relevance in the midst of a global refugee crisis.

Manishita Dass situates the film in its historical and cultural contexts and within Ghatak’s film-making career, and connects it to his theatrical work and his writings on film and theatre. Her close reading of the film locates its emotional and intellectual power in what she describes as its ‘cinematic theatricality,’ and brings into focus Ghatak’s modernist experiments with melodramatic devices, his deliberate departures from cinematic realism, and distinctive use of sound and music.

The book draws on extensive archival research, excavates new layers of meaning, and offers fresh insights into the cosmopolitan cinematic sensibility of a director described as ‘one of the most neglected major film-makers in the world’ (Jonathan Rosenbaum).
News Article Text Classification and Summary for Authors and Topics
Authors: J. Stein Aviel , Weerasinghe Janith , Mancoridis Spiros , Greenstadt Rachel
Published: November 2020

News articles are important for providing timely, historic information. However, the Internet is replete with text that may contain irrelevant or unhelpful information, therefore means of processing it and distilling content is important and useful to human readers as well as information extracting tools. Some common questions we may want to answer are “what is this article about?” and “who wrote it?”. In this work we compare machine learning models for evaluating two common NLP tasks, topic and authorship attribution, on the 2017 Vox Media dataset. Additionally, we use the models to classify on a subsection, about ~20%, of the original text which show to be better for classification than the provided blurbs. Because of the large number of topics, we take into account topic overlap and address it via top-n accuracy and hierarchical groupings of topics. We also consider edge cases in authorship by classifying on inter-topic and intra-topic author distributions. Our results show that both topics and authors readily identifiable consistently perform best when using neural networks rather than support vector, random forests, or naive Bayes classifiers, although the latter methods perform acceptably.
Semantic Management of Enterprise Information Systems through Ontologies
Authors: Casola Valentina , Catelli Rosario
Published: November 2020

This article introduces a model for cloud-aware enterprise governance with a focus on its semantic aspects. It considers the need for Business-IT/OT and Governance-Security alignments. The proposed model suggests the usage of ontologies as specific tools to address the governance of each IT/OT environment in a holistic way. The concrete utilization of ISO and NIST standards allows to correctly structure the ontological model: in fact, by using these wellknown international standards it is possible to significantly reduce terminological and conceptual inconsistencies already in the design phase of the ontology. This also brings a considerable advantage in the operational management phase of the company certifications, congruently aligned with the knowledge structured in this manner. The semantic support within the model suggests further possible applications in different departments of the company, with the aim of evaluating and managing projects in an optimal way, integrating different but important points of view of stakeholders.
Arabic Location Name Annotations and Applications
Authors: ASBAYOU Omar
Published: November 2020

This paper show how location named entity (LNE) extraction and annotation, which makes part of our named entity recognition (NER) systems, is an important task in managing the great amount of data. In this paper, we try to explain our linguistic approach in our rule-based LNE recognition and classification system based on syntactico-semantic patterns. To reach good results, we have taken into account morpho-syntactic information provided by morpho-syntactic analysis based on DIINAR database, and syntactico-semantic classification of both location name trigger words (TW) and extensions. Formally, different trigger word sense implies different syntactic entity structures. We also show the semantic data that our LNE recognition and classification system can provide to both information extraction (IE) and information retrieval(IR).The XML database output of the LNE system constituted an important resource for IE and IR. Future project will improve this processing output in order to exploit it in computerassisted Translation (CAT).
Domain-Transferable Method for Named Entity Recognition Task
Authors: Mikhailov Vladislav , Shavrina Tatiana
Published: November 2020

Named Entity Recognition (NER) is a fundamental task in the fields of natural language processing and information extraction. NER has been widely used as a standalone tool or an essential component in a variety of applications such as question answering, dialogue assistants and knowledge graphs development. However, training reliable NER models requires a large amount of labelled data which is expensive to obtain, particularly in specialized domains. This paper describes a method to learn a domain-specific NER model for an arbitrary set of named entities when domain-specific supervision is not available. We assume that the supervision can be obtained with no human effort, and neural models can learn from each other. The code, data and models are publicly available.
Chinese Medical Question Answer Matching based on Interactive Sentence Representation Learning
Authors: Cui Xiongtao , Han Jungang
Published: November 2020

Chinese medical question-answer matching is more challenging than the open-domain questionanswer matching in English. Even though the deep learning method has performed well in improving the performance of question-answer matching, these methods only focus on the semantic information inside sentences, while ignoring the semantic association between questions and answers, thus resulting in performance deficits. In this paper, we design a series of interactive sentence representation learning models to tackle this problem. To better adapt to Chinese medical question-answer matching and take the advantages of different neural network structures, we propose the Crossed BERT network to extract the deep semantic information inside the sentence and the semantic association between question and answer, and then combine with the multi-scale CNNs network or BiGRU network to take the advantage of different structure of neural networks to learn more semantic features into the sentence representation. The experiments on the cMedQA V2.0 and cMedQA V1.0 dataset show that our model significantly outperforms all the existing state-of-the-art models of Chinese medical question answer matching.
Multi-Layer Attention Approach for Aspect based Sentiment Analysis
Authors: Ai Xinzhi , Li Xiaoge , Hu Feixiong , Zhi Shuting , Hu Likun
Published: November 2020

Based on the aspect-level sentiment analysis is typical of fine-grained emotional classification that assigns sentiment polarity for each of the aspects in a review. For better handle the emotion classification task, this paper put forward a new model which apply Long Short-Term Memory network combine multiple attention with aspect context. Where multiple attention mechanism (i.e., location attention, content attention and class attention) refers to takes the factors of context location, content semantics and class balancing into consideration. Therefore, the proposed model can adaptively integrate location and semantic information between the aspect targets and their contexts into sentimental features, and overcome the model data variance introduced by the imbalanced training dataset. In addition, the aspect context is encoded on both sides of the aspect target, so as to enhance the ability of the model to capture semantic information. The Multi-Attention mechanism (MATT) and Aspect Context (AC) allow our model to perform better when facing reviews with more complicated structures. The result of this experiment indicate that the accuracy of the new model is up to 80.6% and 75.1% for two datasets in SemEval-2014 Task 4 respectively, While the accuracy of the data set on twitter 71.1%, and 81.6% for the Chinese automotive-domain dataset. Compared with some previous models for sentiment analysis, our model shows a higher accuracy.
A Topological Method for Comparing Document Semantics
Authors: Kong Yuqi , Meng Fanchao , Carterette Ben
Published: November 2020

Comparing document semantics is one of the toughest tasks in both Natural Language Processing and Information Retrieval. To date, on one hand, the tools for this task are still rare. On the other hand, most relevant methods are devised from the statistic or the vector space model perspectives but nearly none from a topological perspective. In this paper, we hope to make a different sound. A novel algorithm based on topological persistence for comparing semantics similarity between two documents is proposed. Our experiments are conducted on a document dataset with human judges’ results. A collection of state-of-the-art methods are selected for comparison. The experimental results show that our algorithm can produce highly human-consistent results, and also beats most state-of-the-art methods though ties with NLTK.
Unique Software Engineering Techniques: Panacea for Threat Complexities in Secure Multiparty Computation (MPC) with Big Data
Authors: Emejeamara Uchechukwu , Nwoduh Udochukwu , Madu Andrew
Published: November 2020

Most large corporations with big data have adopted more privacy measures in handling their sensitive/private data and as a result, employing the use of analytic tools to run across multiple sources has become ineffective. Joint computation across multiple parties is allowed through the use of secure multi-party computations (MPC). The practicality of MPC is impaired when dealing with large datasets as more of its algorithms are poorly scaled with data sizes. Despite its limitations, MPC continues to attract increasing attention from industry players who have viewed it as a better approach to exploiting big data. Secure MPC is however, faced with complexities that most times overwhelm its handlers, so the need for special software engineering techniques for resolving these threat complexities. This research presents cryptographic data security measures, garbed circuits protocol, optimizing circuits, and protocol execution techniques as some of the special techniques for resolving threat complexities associated with MPC’s. Honest majority, asymmetric trust, covert security, and trading off leakage are some of the experimental outcomes of implementing these special techniques. This paper also reveals that an essential approach in developing suitable mitigation strategies is having knowledge of the adversary type.
Inverse Space Filling Curve Partitioning Applied to Wide Area Graphs
Authors: Gottstein Cyprien , Parvedy Philippe Raipin , Hurfin Michel , Hassan Thomas , Coupaye Thierry
Published: November 2020

The most recent developments in graph partitioning research often consider scale-free graphs. Instead we focus on partitioning geometric graphs using a less usual strategy: Inverse Spacefilling Partitioning (ISP). ISP relies on a space filling curve to partition a graph and was previously applied to graphs essentially generated from Meshes. We extend ISP to apply it to a new context where the targets are now Wide Area Graphs. We provide an extended comparison with two state-of-the-art graph partitioning streaming strategies, namely LDG and FENNEL. We also propose customized metrics to better understand and identify the use cases for which the ISP partitioning solution is best suited. Experimentations show that in favourable contexts, edge-cuts can be drastically reduced, going from more 34% using FENNEL to less than 1% using ISP.
Energy Aware Routing with Computational Offloading for Wireless Sensor Networks
Authors: Barker Adam , Swany Martin
Published: November 2020

Wireless sensor networks (WSN) are characterized by a network of small, battery powered devices, operating remotely with no pre-existing infrastructure. The unique structure of WSN allow for novel approaches to data reduction and energy preservation. This paper presents a modification to the existing Q-routing protocol by providing an alternate action of performing sensor data reduction in place thereby reducing energy consumption, bandwidth usage, and message transmission time. The algorithm is further modified to include an energy factor which increases the cost of forwarding as energy reserves deplete. This encourages the network to conserve energy in favor of network preservation when energy reserves are low. Our experimental results show that this approach can, in periods of high network traffic, simultaneously reduce bandwidth, conserve energy, and maintain low message transition times.
Frustration Intensity Prediction in Customer Support Dialog Texts
Authors: Zuters Janis , Leonova Viktorija
Published: November 2020

This paper examines the evolution of emotion intensity in dialogs occurring on Twitter between customer support representatives and clients (“users”). We focus on a single emotion type— frustration, modelling the user's level of frustration (on scale of 0 to 4) for each dialog turn and attempting to predict change of intensity from turn to turn, based on the text of turns from both dialog participants. As the modelling data, we used a subset of the Kaggle Customer Support on Twitter dataset annotated with per-turn frustration intensity ratings. For the modelling, we used a machine learning classifier for which dialog turns were represented by specifically selected bags of words. Since in our experimental setup the prediction classes (i.e., ratings) are not independent, to assess the classification quality, we examined different levels of accuracy imprecision tolerance. We showed that for frustration intensity prediction of actual dialog turns we can achieve a level of accuracy significantly higher than a statistical baseline. However we found that, as the intensity of user’s frustration tends to be stable across turns of the dialog, customer support turns have only a very limited immediate effect on the customer's level of frustration, so using the additional information from customer support turns doesn't help to predict future frustration level.
An Automated Data-Driven Prediction of Product Pricing Based on Covid-19 Case Number using Data Mining and Machine Learning
Authors: Han Zhuoyang , Li Ang , Sun Yu
Published: November 2020

In early 2020, a global outbreak of Corona Disease Virus 2019 (Covid-19) emerged as an acute respiratory infectious Disease with high infectivity and incidence. China imposed a blockade on the worst affected city of Wuhan at the end of January 2020, and over time, covid19 spread rapidly around the world and was designated pandemic by the World Health Organization on March 11. As the epidemic spread, the number of confirmed cases and the number of deaths in countries around the world are changing day by day. Correspondingly, the price of face masks, as important epidemic prevention materials, is also changing with each passing day in international trade. In this project, we used machine learning to solve this problem. The project used python to find algorithms to fit daily confirmed cases in China, daily deaths, daily confirmed cases in the world, and daily deaths in the world, the recorded mask price was used to predict the effect of the number of cases on the mask price. Under such circumstances, the demand for face masks in the international trade market is enormous, and because the epidemic changes from day to day, the prices of face masks fluctuate from day to day and are very unstable. We would like to provide guidance to traders and the general public on the purchase of face masks by forecasting face mask prices.
Data Driven Soft Sensor for Condition Monitoring of Sample Handling System (SHS)
Authors: Pani Abhilash , Gugaliya Jinendra , Srinivas Mekapati
Published: November 2020

Gas sample is conditioned using sample handling system (SHS) to remove particulate matter and moisture content before sending it through Continuous Emission Monitoring (CEM) devices. The performance of SHS plays a crucial role in reliable operation of CEMs and therefore, sensor-based condition monitoring systems (CMSs) have been developed for SHSs. As sensor failures impact performance of CMSs, a data driven soft-sensor approach is proposed to improve robustness of CMSs in presence of single sensor failure. The proposed approach uses data of available sensors to estimate true value of a faulty sensor which can be further utilized by CMSs. The proposed approach compares multiple methods and uses support vector regression for development of soft sensors. The paper also considers practical challenges in building those models. Further, the proposed approach is tested on industrial data and the results show that the soft sensor values are in close match with the actual ones.
Improving Workload Estimation in Inexperienced Teams with Hybrid Agile Approach
Authors: S. Pires Fabiano , A. L Pahins Cícero , Fonseca Paulo
Published: November 2020

SCRUM framework is an agile technique that is widely used by development teams in order deliver incremental value to customers and dynamically react to project needs. SCRUM framework might be adapted to conform the development team specificities. In the context of an industry project, we have found that an inexperienced development team frequently faced difficulties with estimating the time needed to complete tasks, which led to missed deadlines in most of the projects. Such problem hampers the risk management and degrades the relationship with the customer. Upon closer analysis, it was identified that the main reason to this issue was the team's inability to breaking down a larger task into smaller sub-tasks and associate a realistic workload to each part. Then, based on traditional techniques, a structured approach to workload estimation was introduced in the SCRUM planning meeting to leverage the team's estimation skill. This approach was implemented in two development projects and increased the accuracy in the estimate defined by the team, yielding realistic schedules and increasing technical visibility.
Reviewing, Revising, and Reinventing the Undergraduate Marketing Curriculum at a Public University
Authors: Cobb-Walgren Cathy J. , Jr Hiram C. Barksdale , Boles James S.
Published: November 2020

The business community faces tremendous challenges in the 21st century and needs an educated workforce that can navigate the realities of empowered customers, new scientific and media technologies, growing environmental and social concerns, and global competition. Unfortunately, undergraduate business education, for the most part, continues to rely on 20th century theories and practices. Undergraduate marketing education, in particular, seems to have stagnated and continues to fall short on both relevance and rigor. This article presents the results of a two-year departmental initiative to review, revise, and reinvent the undergraduate marketing curriculum at a large public research university’s business school. After analyzing the internal and external forces that were the impetus for change, the article presents the process the marketing department used to reform the undergraduate program. Next, the articles discusses the results of six data collection projects among key constituency groups that revealed weaknesses in the undergraduate program and potential areas for improvement. The article concludes with the presentation of a transformed undergraduate marketing curriculum, along with initial assessment feedback. By engaging in continuous evaluation and improvement, the marketing faculty hope to provide undergraduate marketing students with a more rigorous and relevant academic experience that will enable them to succeed in the professional workforce of the 21st century.
The Epistemological Dilemma: Student Teachers Shared Experiences of Jamaica’s National Standards Curriculum (NSC)
Authors: Mayne Hope , Dixon Raymond A.
Published: November 2020

In this paper, we examined the epistemological dilemma embedded in Jamaica’s new National Standards Curriculum (NSC), as seen through student teachers' experience. A basic qualitative research design was used with a purposive sample of ten student teachers, eight females and two males. They were all in the final semester of their four-year teacher education program for a Bachelor of Education in Technical Vocational Education and Training (TVET). Findings indicated student teachers perceived the 5 E-Design process in the new National Standards Curriculum allows knowledge to be constructed through facilitation, conducting research in class, problem-solving, exploration, questioning, real-life experiences, and using active learning strategies. They also reported that resources were lacking in classrooms, some cooperating teachers were resistant to the 5E Methodology, readiness of students were lacking but over time students adopted to strategies used in the 5E approach and began to participate actively in class.
Research requirements related to the design of seismic resistant highway bridges
Authors: Jennings D. N.
Published: November 2020

The recent article by D. Hutchison (Volume 15, No. 2) raising some questions regarding the problems and needs in earthquake engineering for structures is timely and should create much discussion. Engineers  involved in the design of bridges have been aware of the need to look critically at their research activities and review the direction needed  for future efforts. During the visit of a group of sixteen American bridge designers and researchers in December 1981, the opportunity was taken to undertake this review in a semi-formal three day workshop held in Wairakei.
A note on the Hutt Valley strong-motion microzone network
Authors: Tyler R. G. , Hefford R. T.
Published: November 2020

A network of eight M02 strong-motion accelerographs was established in the Hutt Valley between the years 1966-70 with a view to determining the effect of the local geology on earthquake attack on structures. The location of the instruments is shown in Fig. 1 and a typical cross-section of the Valley in Fig. 2. The instruments are all owned by the Physics and Engineering Laboratory (PEL), DSIR, apart from the one at the Haywards Substation, which is owned by NZED but serviced by PEL.
N. Z. National Society for Earthquake Engineering
Authors: Editor
Published: November 2020

This Reconnaissance Team Manual is printed for the information of all members of the Society’s Team Leader and Team Member Pools.

Contents:

Section 1 Aims and Administration of the Reconnaissance Team Scheme.

Section 2 Initiation and Organization of a Reconnaissance.

Section 3 Engineering Reconnaissance Field Guide.
Adding Enriched Eggs in Ready-to-use foods Improve Recovery Rate in Malnourished Rats
Authors: Yepié Audrey Herbert , Cissé Ibrahima , Meité Alassane , Ahuéfa Nina Laurette , Aké-Tano Odile S. , Anin-Atchibri Anin L.
Published: November 2020

Ready-to-use foods (RUFs) using indigenous sources in developing countries is highly required to treat moderate acute malnutrition (MAM). However, incorporating an animal protein may affect their effectiveness. Thus, two local RUFs were produced without (LF-1) and with eggs (LF-2). The objective of this study was to assess and compare to Plumpy'Sup (PS), the impact of adding enriched eggs in cashew/soy/rice based RUF on the proximate composition, growth and blood biochemical parameters in malnourished Wistar rats by Anagobaka diet. Proximate composition revealed that, with the exception of fiber and ash contents, the two RUFs recorded protein, lipid, carbohydrate and energy values globally comparable to PS. They also met WFP's recommendations for foods to treat MAM. Results of growth parameters show that Anagobaka diet leads to the installation of a moderate emaciation, confirmed by an average weight loss of -17 %. Moreover, recovery diets showed higher weight gain and good palatability (DMI, TPI, FER and PER) in rats fed with PS followed by those fed with LF-2 and LF-1. For the serum biochemical parameters, the rats fed with LF-2 had on the whole a better functioning of blood metabolites (glucose, total proteins, albumin, urea, creatinine, ASAT, ALAT) as well as a better accumulation of blood lipids (total cholesterol, HDL-cholesterol, LDL-cholesterol and triglycerides) than those of rats fed with PS and LF-1. In conclusion, local RUFs which include enriched eggs present the best nutritional profile to treat MAM in Côte d'Ivoire but to sustain recovery a mineral supplementation will be needed.
Temporary part-time employment and future wages of male employees – a panel data analysis of the German labour market
Authors: Matuszak Piotr
Published: November 2020

The aim of this study is to assess the relationship between temporary part-time employment and the wages male employees receive in subsequent full-time employment within the first five and the first ten years from the date of starting their full-time employment. The study uses data from the German labour market, obtained from the Socio-Economic Panel for the years 1984–2014. The fixed effects estimator, which solves the unobserved heterogeneity issue by removing time-invariant individual effects by a ‘within’ transformation, was applied in the empirical analysis. The results indicate that having experience as a part-time worker is associated with lower future wages – a one-year increase in the number of years in part-time work in the last two to five years leads to a reduction in future wages in a full-time job by 4.4% on average, compared to having solely a full-time job experience. However, this relationship becomes statistically insignificant after five years of being employed full-time. The results are robust to different specifications and it is indicated that an inverse relationship between working below regular hours and future wages in full-time employment is related to working parttime in low- and medium-skilled occupations. At the same time, working part-time is less detrimental to future wages than periods of unemployment.
Forecasting missing data in time series with the application of hybrid models – theoretical and empirical approach
Authors: Zawadzki Jan
Published: November 2020

The main goal of the article is to present the possibilities of forecasting missing observations in time series for hourly data with the application of hybrid models. Hybrid time series models and regression models with complex seasonal fluctuations were used in the study. Complex fluctuations for hourly data can be either a sum or a product of fluctuations of annual, weekly and daily cycles, while fluctuations the length of a cycle expressed by an even number (12-month and 24-hour ones) can be described using regular hierarchical models.
The theoretical considerations were illustrated by an empirical analysis of the demand for electricity in hourly periods in a selected agglomeration. The statistical data covered three consecutive years of the first decade of the 2000s. The data were provided by an electricity distribution company and included in the Data Bank of the Department of Applied Mathematics in Economics of the West Pomeranian University of Technology in Szczecin. It was assumed that non-systematic gaps occur with regard to all types of seasonal fluctuations. The obtained results indicate the usefulness of hybrid models in forecasting economic phenomena subject to very frequent observations.
PBN ICAO program in the aspect of the effectiveness of airports
Authors: Fellner Andrzej , Paszyn Jarosław
Published: November 2020

Methods of the research on the effectiveness of airports in the course of analysis are allocating the area of the financial and technical effectiveness. In case of analysis of the technical effectiveness irrespective of whether we apply quota analyses (PFP, TFP), parametric (SFA) whether nonparametric (DEA) entrance/initial variables don't consider navigational systems as the factor. As a rule he is getting down up to the attention so as: number of employees, areas (of terminal, the apron area, the zone of departures and the like) number of parking spaces (planes, cars on car parks). The PBN ICAO program implemented in the global scale is determining changes in managing the airspace, contributing to increase the elasticity and the bandwidth in the global air traffic. However he/she requires the right infrastructure, of proper legal changes but in exchange offers specific benefits economic – financial. Implementation of the PBN ICAO program in the global scale it is also a profit in reducing the environmental decay by aviation. Right PBN procedures enable the performance diverse „of” offsets, thanks to which limiting emission of the exhaust fumes is possible and the noise. However not considering systems of the navigation is a problem in currently listed effectiveness of airports indicators.
Comparison of the Modification of Diet in Renal Disease Study and Chronic Kidney Disease Epidemiology Collaboration Equations for Detection of Cardiovascular Risk: Tehran Lipid and Glucose Study
Authors: Mousapour Pouria , Barzin Maryam , Valizadeh Majid , Mahdavi Maryam , Azizi Fereidoun , Hosseinpanah Farhad
Published: November 2020

Objectives: The study aimed to compare the Modification of Diet in Renal Disease Study (MDRD) and the Epidemiology Collaboration (CKD-EPI) equations for the detection of cardiovascular risk. Methods: Data of 9,970 Tehranian participants aged ≥ 20 years were analyzed. The prevalence of cardiovascular disease (CVD), its risk factors, and 10-year atherosclerotic cardiovascular disease (ASCVD) risk were compared across the categories of glomerular filtration rate based on the MDRD and CKD-EPI equations. Chronic kidney disease (CKD) was defined as the estimated Glomerular Filtration Rate (eGFR) < 60 mL/min/1.73 m2 according to each equation. Results: The prevalence of CKD weighted to the 2016 Tehranian urban population was 11.0% (95% confidence interval: 10.3 - 11.6) and 9.7% (9.1 - 10.2) according to the MDRD and CKD-EPI equations, respectively. Besides, 8.3% and 1.5% of the participants with CKDMDRD and non-CKDMDRD were reclassified to non-CKDCKD-EPI and CKDCKD-EPI categories, respectively. Participants with CKDCKD-EPI but without CKDMDRD were more likely to be male and older, and more frequently had diabetes, hypertension, dyslipidemia, and CVD, when compared to those without CKD according to both equations; they were also more likely to be male, older, and smokers, and had less dyslipidemia and more CVD, when compared to those with CKD by using both equations. In multivariate logistic regression analysis, compared to CKDMDRD, the odds of CKDCKD-EPI were significantly higher for older age and lower for the female gender. Conclusions: Compared to MDRD, the CKD-EPI equation provides more appropriate detection of cardiovascular risk, which is caused by the reclassification of older individuals and fewer females into lower eGFR categories.