Overview of Multi-Factor Prediction Using Deep Neural Networks, Machine Learning, and Their Open-Source Software

This chapter first provides an overview with examples of what neural networks (NN), machine learning (ML), and artificial intelligence (AI) are and their applications in biomedical and business situations. The characteristics of 29 types of neural networks are provided including their distinctive graphical illustrations. A survey of current open-source software (OSS) for neural networks, neural network software available for free trail download for limited time use, and open-source software (OSS) for machine learning (ML) are provided. Characteristics of artificial intelligence (AI) technologies for machine learning available as open source are discussed. Illustrations of applications of neural networks, machine learning, and artificial intelligence are presented as used in the daily operations of a large internationally-based software company for optimal configuration of their Helix Data Capacity system.

GRASP-Tabu Search Algorithms for the Route Planning Problem in Spatial Crowdsourcing

With the speedy progress of mobile devices, a lot of commercial enterprises have exploited crowdsourcing as a useful approach to gather information to develop their services. Thus, spatial crowdsourcing has appeared as a new platform in e-commerce and which implies procedures of requesters and workers. A requester submits spatial tasks request to the workers who choose and achieve them during a limited time. Thereafter, the requester pays only the worker for the well accomplished the task. In spatial crowdsourcing, each worker is required to physically move to the place to accomplish the spatial task and each task is linked with location and time. The objective of this article is to find an optimal route to the worker through maximizing her rewards with respecting some constraint, using an approach based on GRASP with Tabu. The proposed algorithm is used in the literature for benchmark instances. Computational results indicate that the proposed and the developed algorithm is competitive with other solution approaches.

Implementasi Algoritma Kruskal Dalam Menentukan Rute Terdekat Pada Tempat Pariwisata di Daerah Lombok Tengah

When visiting several tourist attractions at once with limited time and an irregular schedule, of course, visitors choose the closest route to be able to visit all the places to be visited at once. This study uses an algorithm, namely the Kruskal algorithm, which aims to find the closest route to visit the five tourist attractions at once in Central Lombok Regency. The tourist attractions in question are Tanjung Aan Beach, Kuta Mandalika Beach, Sukarara Village, Sade Hamlet, Benang Kelambu Waterfall. This type of research is applied research which is generally a type of descriptive research that encourages further research. This study applies a modified Kruskal algorithm so as to produce 4 alternative closest routes with different starting points to be able to visit the five tourist attractions at once in Central Lombok Regency, namely 1) If the journey starts from Tanjung Aan Beach or Benang Kelambu Waterfall, the closest route is 60,1 km; 2) If the journey starts from Kuta Mandalika Beach, the closest route is 73.6 km; 3) If the journey starts from Sade Hamlet, the closest route is 73.6 km; 4) If the journey starts from Sukarara Village, the closest route is 82.9 km

Automation in the Intralingual Subtitling Process

The demand for intralingual subtitles for television and video content is increasing. In Finland, major broadcasting companies are required to provide intralingual subtitles for all or a portion of their programming in Finnish and Swedish, excluding certain live events. To meet this need, technology could offer solutions in the form of automatic speech recognition and subtitle generation. Although fully automatic subtitles may not be of sufficient quality to be accepted by the target audience, they can be a useful tool for the subtitler. This article presents research conducted as part of the MeMAD project, where automatically generated subtitles for Finnish were tested in professional workflows with four subtitlers. We discuss observations regarding the effect of automation on productivity based on experiments where participants subtitled short video clips from scratch, by respeaking and by post-editing automatically generated subtitles, as well as the subtitlers’ experience based on feedback collected with questionnaires and interviews. Lay summary This article discusses how technology can help create subtitles for television programmes and videos. Subtitles in the same language as the content help the Deaf and the hard-of-hearing to access television programmes and videos. They are also useful for example for language learning or watching videos in noisy places. Demand for subtitles is growing and many countries also have laws that demand same-language subtitles. For example, major broadcasters in Finland must offer same-language subtitles for some programmes in Finnish and Swedish. However, broadcasters usually have limited time and money for subtitling. One useful tool could be speech recognition technology, which automatically converts speech to text. Subtitles made with speech recognition alone are not good enough yet, and need to be edited. We used speech recognition to automatically produce same-language subtitles in Finnish. Four professional subtitlers edited them to create subtitles for short videos. We measured the time and the number of keystrokes they needed for this task and compared whether this made subtitling faster. We also asked how the participants felt about using automatic subtitles in their work. This study shows that speech recognition can be a useful tool for subtitlers, but the quality and usability of technology are important.

A New Classical Greek Qualification

The Intermediate Certificate in Classical Greek (ICCG) is a new qualification being developed primarily for learners of Classical Greek on limited time for whom sitting the full GCSE is unrealistic. It is endorsed by the Classical Association and Classics for All.

SpotFuzz: Fuzzing Based on Program Hot-Spots

AFL is the most widely used coverage-guided fuzzer, which relies on rough execution information to assign seeds energy, which can lead to waste. We track the program executed by AFL and discover that the hit counts of each edge might vary greatly when using different seeds as inputs. Some seeds, which are continuously given too much energy, experience very high hit counts of several edges without new crashes or edges being explored, which results in invalid execution and waste of performance. We also define time-consuming edges and discover that they only occupy a small part of the program. In this paper, we define invalid execution edges and time-consuming edges as hot-spots and propose a fuzzing solution SpotFuzz to solve energy waste caused by the above hot-spot phenomenon. It allocates seeds with more hot-spots during execution and uses less energy to reduce energy waste. Moreover, it preferentially selects seeds with less time-consuming edges as test cases, allowing for more edges to be explored in a limited time. We implement an SpotFuzz prototype based on AFL and test it on several real programs for 600 CPU days. The experimental results show that minimizing the invalid and time-consuming execution of edges can improve the fuzzing efficiency. On average, SpotFuzz could find 42.96% more unique crashes and 14.25% more edges than AFL on GNU Binutils and tcpdump.

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A new approach to investigating shipwreck sites in littoral envirornments: Multi-technique geophysical investigations of Port Elliot, South Australia

A bipartite geophysical survey methodology has been developed in order to locate archaeological sites in littoral environments and to gain precise information on their location, size and physical properties. The initial reconnaissance phase establishes the presence of prospective anomalies with limited time and budget. The second phase provides comprehensive information on the anomaly as context for further investigation if necessary. This approach was tested at Port Elliot, South Australia to locate the remains of the cutter Lapwing. An anomaly discovered during reconnaissance phase investigations proved inconsequential in phase two, and follow-up work was not carried out. This outcome demonstrates the benefits of using this approach in terms of money and time saved.