In sequential circuits, the current output may depend on both past and current inputs. However, certain kinds of sequential circuits do not refer to all of the past inputs to generate the current output; they only refer to a subset of past inputs. This paper investigates which subset of past inputs a sequential circuit refers to, and proposes a new classification of sequential circuits based on this criterion. The conventional classification of sequential circuits distinguishes between synchronous and asynchronous circuits. In contrast, the new classification consolidates synchronous circuits and multiple clock domain circuits into the same category.
Agriculture is a huge domain where an enormous landscape of systems interact to support agricultural processes, which are becoming increasingly digital. From the perspective of agricultural service providers, a prominent challenge is interoperability. In the Fraunhofer lighthouse project Cognitive Agriculture (COGNAC), we investigated how the usage of Industry 4.0 digital twins (I4.0 DTs) can help overcome this challenge. This paper contributes architecture drivers and a solution concept using I4.0 DTs in the agricultural domain. Furthermore, we discuss the opportunities and limitations offered by I4.0 DTs for the agricultural domain.
Joanna Sendorek, Tomasz Szydlo, Mateusz Windak
et al.
Nowadays, Internet of Things plays a significant role in many domains. Especially, Industry 4.0 is making a great usage of concepts like smart sensors and big data analysis. IoT devices are commonly used to monitor industry machines and detect anomalies in their work. In this paper we present and describe a set of data streams coming from working 3D printer. Among others, it contains accelerometer data of printer head, intrusion power and temperatures of the printer elements. In order to gain data we lead to several printing malfunctions applied to the 3D model. Resulting dataset can therefore be used for anomalies detection research.
Financial fraud detection is one of the core technological assets of Fintech companies. It saves tens of millions of money fro m Chinese Fintech companies since the bad loan rate is more than 10%. HC Financial Service Group is the 3rd largest company in the Chinese P2P financial market. In this paper we illustrate how we tackle the fraud detection problem at HC Financial. We utilize two powerful workhorses in the machine learning field - random forest and gradient boosting decision tree to detect fraudulent users . We demonstrate that by carefully select features and tune model parameters , we could effectively filter out fraudulent users in the P2P market.
It is generally accepted that machines can replicate cognitive tasks performed by conscious agents as long as they are not based on the capacity of awareness. We consider several views on the nature of subjective awareness, which is fundamental for self-reflection and review, and present reasons why this property is not computable. We argue that consciousness is more than an epiphenomenon and assuming it to be a separate category is consistent with both quantum mechanics and cognitive science. We speak of two kinds of consciousness, little-C and big-C, and discuss the significance of this classification in analyzing the current academic debates in the field. The interaction between the system and the measuring apparatus of the experimenter is examined both from the perspectives of decoherence and the quantum Zeno effect. These ideas are used as context to address the question of limits to machine consciousness.
This paper presents a new analytical propagation delay model for deep submicron CMOS inverters. The model is inspired by the key observation that the inverter delay is a complicated function of several process parameters as well as load capacitance. These relationships are considered by fitting functions for each parameter derived from the Curve Fitting Toolbox in Matlab. Compared to SPICE simulations based on the BSIM4 transistor model, the analytical delay model shows very good accuracy with an average error less than 2% over a wide range of process parameters and output loads. Hence, the proposed model can be efficiently used for different technology nodes as well as statistical gate delay characterisation.
In Directed Self Assembly (DSA), poor printing of guiding templates can cause misassembly resulting in high defect probability. Therefore, hotspots should be avoided in the choice of the DSA groups. Accordingly, Directed Self-Assembly (DSA) technologies which use Multiple Patterning (MP) to print the guiding templates need to be aware of hotspots during the DSA grouping and MP Decomposition. In this paper, we present a hotspot-aware heuristic for DSA grouping and MP decomposition. Results show that that the proposed heuristic eliminates 78% of the hotspots and conflicts that result from using a hotspot-unaware grouping and decomposition algorithm. In comparison to the optimal solution using Integer Linear Programming, the proposed heuristic results in ~24% more violations.
The Automatic Identification System (AIS) tracks vessel movement by means of electronic exchange of navigation data between vessels, with onboard transceiver, terrestrial and/or satellite base stations. The gathered data contains a wealth of information useful for maritime safety, security and efficiency. This paper surveys AIS data sources and relevant aspects of navigation in which such data is or could be exploited for safety of seafaring, namely traffic anomaly detection, route estimation, collision prediction and path planning.
In this paper we present a new scheme for instrumentation, which has been inspired by the way small mammals sense their environment. We call this scheme Application Specific Instrumentation (ASIN). A conventional instrumentation system focuses on gathering as much information about the scene as possible. This, usually, is a generic system whose data can be used by another system to take a specific action. ASIN fuses these two steps into one. The major merit of the proposed scheme is that it uses low resolution sensors and much less computational overhead to give good performance for a highly specialised application
One of the most familiar SCADA (supervisory control and data acquisition) application protocols now is OPC protocol. This interface is supported by almost all SCADA, visualization, and process control systems. There are many research efforts tried to design and implement an approach to access an OPC DA server through the Internet. To achieve this goal they used diverse of modern IT technologies like XML, Web services, Java and AJAX. In this paper, we present a complete classification of the different approaches introduced in the literature. A comparative study is also introduced. Finally we study the feasibility of the realization of these approaches based on the real time constraints imposed by the nature of the problem.
A number of elements towards a classification of the quality of emergence in emergent collective systems are provided. By using those elements, several classes of emergent systems are exemplified, ranging from simple aggregations of simple parts up to complex organizations of complex collective systems. In so doing, the factors likely to play a a significant role in the persistence of emergence and its opposite are highlighted. From this, new elements for discussion are identified also considering elements from the System of Leibniz.
The ability to recognize students weakness and solve any problem that may confront them in timely fashion is always a target for all educational institutions. Thus, colleges and universities implement the so-called academic advising affairs. On the academic advisor relies the responsibility of solving any problem that may confront students learning progress. This paper shows how the adviser can benefit from data mining techniques, namely decision trees techniques. The C 4.5 algorithm is used as a method for building such trees. The output is evaluated based on the accuracy measure, Kappa measure, and ROC area. The difference between the registered and gained credit hours is considered as the main attribute on which advisor can rely
The era of Big Data is here now, which has brought both unprecedented opportunities and critical challenges. In this article, from a perspective of cognitive wireless networking, we start with a definition of Big Spectrum Data by analyzing its characteristics in terms of six Vs, i.e., volume, variety, velocity, veracity, viability, and value. We then present a high-level tutorial on research frontiers in Big Spectrum Data analytics to guide the development of practical algorithms. We also highlight Big Spectrum Data as the new resource for cognitive wireless networking by presenting the emerging use cases.
The development of computer science has contributed greatly for increasing of efficiency and effectively. Many areas are covered by computer science, included education. The purpose of this research is to introduce jawi a type of Indonesian letters. Jawis letter is one of the most popular letter in the past. But right now few people can read and understand it. Many documents in the past was written in Jawi. The writer develop or build the software using Pressman method, and tools such as Microsoft Visual Basic, and Microsoft Access. This software can introduce Jawi then people can learn it easily.
Claudiu-Florinel Bisu, Alain Gérard, Miron Zapciu
et al.
This paper proposes a method to vibration analysis in order to on-line monitoring of milling process quality. Adapting envelope analysis to characterize the milling tool materials is an important contribution to the qualitative and quantitative characterization of milling capacity and a step by modeling the three-dimensional cutting process. An experimental protocol was designed and developed for the acquisition, processing and analyzing three-dimensional signal. The vibration envelope analysis is proposed to detect the cutting capacity of the tool with the optimization application of cutting parameters. The research is focused on Hilbert transform optimization to evaluate the dynamic behavior of the machine/ tool/workpiece.
This paper describes an automatic switching of modulation method to reconfigure transceivers of Software Defined Radio (SDR) based wireless communication system. The programmable architecture of Software Radio promotes a flexible implementation of modulation methods. This flexibility also translates into adaptively, which is used here to optimize the throughput of a wireless network, operating under varying channel conditions. It is robust and efficient with processing time overhead that still allows the SDR to maintain its real-time operating objectives. This technique is studied for digital wireless communication systems. Tests and simulations using an AWGN channel show that the SNR threshold is 5dB for the case study.
Abdessalem Hassani, Nizar Aifaoui, Abdelmajid Benamara
et al.
The tolerancing step has a great importance in the design process. It characterises the relationship between the different sectors of the product life cycle: Design, Manufacturing and Control. We can distinguish several methods to assist the tolerancing process in the design. Based on arithmetic and statistical method, this paper presents a new approach of analysis and verification of tolerances. The chosen approach is based on the Worst Case Method as an arithmetic method and Monte Carlo method as a statistical method. In this paper, we compare these methods and we present our main approach, which is validated using an example of 1 D tolerancing.