High Dimensional Data Clustering using Self-Organized Map

As the population grows and e economic development, houses could be one of basic needs of every family. Therefore, housing investment has promising value in the future. This research implements the Self-Organized Map (SOM) algorithm to cluster house data for providing several house groups based on the various features. K-means is used as the baseline of the proposed approach. SOM has higher silhouette coefficient (0.4367) compared to its comparison (0.236). Thus, this method outperforms k-means in terms of visualizing high-dimensional data cluster. It is also better in the cluster formation and regulating the data distribution

INQUIRIES IN INTELLIGENT INFORMATION SYSTEMS: NEW TRAJECTORIES AND PARADIGMS

Rapid Digital transformation drives organizations to continually revitalize their business models so organizations can excel in such aggressive global competition. Intelligent Information Systems (IIS) have enabled organizations to achieve many strategic and market leverages. Despite the increasing intelligence competencies offered by IIS, they are still limited in many cognitive functions. Elevating the cognitive competencies offered by IIS would impact the organizational strategic positions. With the advent of Deep Learning (DL), IoT, and Edge Computing, IISs has witnessed a leap in their intelligence competencies. DL has been applied to many business areas and many industries such as real estate and manufacturing. Moreover, despite the complexity of DL models, many research dedicated efforts to apply DL to limited computational devices, such as IoTs. Applying deep learning for IoTs will turn everyday devices into intelligent interactive assistants. IISs suffer from many challenges that affect their service quality, process quality, and information quality. These challenges affected, in turn, user acceptance in terms of satisfaction, use, and trust. Moreover, Information Systems (IS) has conducted very little research on IIS development and the foreseeable contribution for the new paradigms to address IIS challenges. Therefore, this research aims to investigate how the employment of new AI paradigms would enhance the overall quality and consequently user acceptance of IIS. This research employs different AI paradigms to develop two different IIS. The first system uses deep learning, edge computing, and IoT to develop scene-aware ridesharing mentoring. The first developed system enhances the efficiency, privacy, and responsiveness of current ridesharing monitoring solutions. The second system aims to enhance the real estate searching process by formulating the search problem as a Multi-criteria decision. The system also allows users to filter properties based on their degree of damage, where a deep learning network allocates damages in 12 each real estate image. The system enhances real-estate website service quality by enhancing flexibility, relevancy, and efficiency. The research contributes to the Information Systems research by developing two Design Science artifacts. Both artifacts are adding to the IS knowledge base in terms of integrating different components, measurements, and techniques coherently and logically to effectively address important issues in IIS. The research also adds to the IS environment by addressing important business requirements that current methodologies and paradigms are not fulfilled. The research also highlights that most IIS overlook important design guidelines due to the lack of relevant evaluation metrics for different business problems

Organizational Posthumanism

Building on existing forms of critical, cultural, biopolitical, and sociopolitical posthumanism, in this text a new framework is developed for understanding and guiding the forces of technologization and posthumanization that are reshaping contemporary organizations. This ‘organizational posthumanism’ is an approach to analyzing, creating, and managing organizations that employs a post-dualistic and post-anthropocentric perspective and which recognizes that emerging technologies will increasingly transform the kinds of members, structures, systems, processes, physical and virtual spaces, and external ecosystems that are available for organizations to utilize. It is argued that this posthumanizing technologization of organizations will especially be driven by developments in three areas: 1) technologies for human augmentation and enhancement, including many forms of neuroprosthetics and genetic engineering; 2) technologies for synthetic agency, including robotics, artificial intelligence, and artificial life; and 3) technologies for digital-physical ecosystems and networks that create the environments within which and infrastructure through which human and artificial agents will interact. Drawing on a typology of contemporary posthumanism, organizational posthumanism is shown to be a hybrid form of posthumanism that combines both analytic, synthetic, theoretical, and practical elements. Like analytic forms of posthumanism, organizational posthumanism recognizes the extent to which posthumanization has already transformed businesses and other organizations; it thus occupies itself with understanding organizations as they exist today and developing strategies and best practices for responding to the forces of posthumanization. On the other hand, like synthetic forms of posthumanism, organizational posthumanism anticipates the fact that intensifying and accelerating processes of posthumanization will create future realities quite different from those seen today; it thus attempts to develop conceptual schemas to account for such potential developments, both as a means of expanding our theoretical knowledge of organizations and of enhancing the ability of contemporary organizational stakeholders to conduct strategic planning for a radically posthumanized long-term future

High-Density Solid-State Memory Devices and Technologies

This Special Issue aims to examine high-density solid-state memory devices and technologies from various standpoints in an attempt to foster their continuous success in the future. Considering that broadening of the range of applications will likely offer different types of solid-state memories their chance in the spotlight, the Special Issue is not focused on a specific storage solution but rather embraces all the most relevant solid-state memory devices and technologies currently on stage. Even the subjects dealt with in this Special Issue are widespread, ranging from process and design issues/innovations to the experimental and theoretical analysis of the operation and from the performance and reliability of memory devices and arrays to the exploitation of solid-state memories to pursue new computing paradigms

Predicción del precio en el mercado de viviendas en la ciudad de Valencia mediante redes neuronales en el año 2020

[ES] Las redes neuronales artificiales permiten capturar las relaciones entre las variables decisivas para la fijación del valor del mercado de la vivienda. En este TFG se construye, a partir de la web idealista, una base de datos de precios de oferta y características (ubicación, superficie, habitaciones, planta y ascensor) de viviendas en la ciudad de Valencia, a partir de la cual se diseña, aplica y optimiza un modelo para la predicción del precio de oferta de una vivienda en base a sus características, basado en redes neuronales artificiales. A fin de valorar la precisión del modelo, se mide el error mediante el error absoluto medio, a partir de un esquema de validación cruzada empleando subconjuntos de entrenamiento, validación y test.[EN] Artificial neural networks are able to capture the relationships between the most relevant variables in market pricing of properties. In the present bachelor¿s thesis, a database containing offer prices and features (location, surface area, rooms, floor and elevator) of properties located in Valencia city is built, using idealista web as the source. With this database, an offer price predictive model using the properties¿ features as an input, and based in neural networks is designed, built, and optimized. In order to assess its performance, mean absolute error is measured within a cross-validation scheme, in which training, validation and test subsets are used.Antón Ruiz, A. (2020). Predicción del precio en el mercado de viviendas en la ciudad de Valencia mediante redes neuronales en el año 2020. http://hdl.handle.net/10251/152158TFG

Digital anthropology

The textbook supplements the lecture material with topical issues of the philosophy of neural technologies. The material belongs to the section "Philosophy of natural science and technology" of the lecture course on the philosophy and methodology of science. The natural-science aspects of human conscious-ness and technological trends in the evolution of convergent structures of digital ecosystems are described. The evolution of system computer engineering is analyzed

Practical English Course for Engineering Students

Представляет собой систематизированный практический курс английского языка, целью которого является совершенствование навыков, а также развитие умений чтения и понимания англоязычной научно-технической литературы во взаимосвязи с другими видами речевой деятельности: говорением, аудированием и письмом. Состоит из четырех модулей: Electronics; Telecommunications; Information Technologies; Artificial Intelligence. Разработанная на основе модульного подхода структура, организация и изложение учебного материала позволяют использовать пособие как для аудиторной, так и для самостоятельной работы. Предназначено для студентов I ступени высшего образования, изучающих учебную дисциплину «Иностранный язык». Может быть полезно широкому кругу читателей, желающих совершенствовать навыки и развивать умения чтения и понимания англоязычной научно-технической литературы