Abstract: A device includes a processor configured to obtain flight data of one or more aircraft of an aircraft type. The processor is configured to identify a first portion of the flight data as first phase flight data associated with a first phase of one or more flights of the one or more aircraft, and to apply a first aircraft performance model to the first phase flight data to determine first parameter values. The processor is configured to identify a second portion of the flight data as second phase flight data associated with a second phase of the one or more flights, and to apply the first aircraft performance model to the second phase flight data to determine second parameter values. The processor is configured to generate, based on the first parameter values and the second parameter values, a second aircraft performance model of a particular aircraft of the aircraft type.

Abstract: Systems, devices, and methods of protecting electronic or Internet-connected devices against fraudulent and malicious activities. A Data Collector and Mediator Unit monitors network traffic, and generates datasets of network traffic; each dataset includes network traffic monitored within a time-slot having a particular fixed time-length. A Predictor Unit includes a Features Extractor, to extract features from the datasets; and a Machine Learning (ML) unit, to run the extracted features through a ML model and to classify a particular traffic-portion as being either (I) an anomalous traffic-portion that is associated with fraudulent or malicious activity, or (II) a non-anomalous traffic-portion that is not-associated with fraudulent or malicious activity. The ML unit operates on both (i) anomalies in traffic patterns, and (ii) anomalies of user behavior and/or device behavior.

Abstract: A vehicle window including a panel having a first surface and a second surface and at least a window holder for firmly retaining the panel to a lifting system including an inner member having a bonding part to be bonded to a first surface of the panel, an outer member having a fixing part to be fixed to the lifting system and an assembling means. The bonding part of the inner member is bonded with a bonding material to the first surface and the outer member is assembled to the inner member via the assembling means to clutch the panel.

Abstract: Presented is a Picture frame for visually displaying a picture template. The picture frame includes a base, a top cover, an internal backing, and a mat. The base includes a first side, a second side disposed opposite to the first side, and a peripheral portion extending along the entire perimeter of the first side and the second side. The first side of the base includes raised projections. An internal backing is positioned on the raised projections and the internal backing is removably connected to a magnet. The mat includes a plurality of locking tabs for releasably holding the picture template. The mat further includes a ferromagnetic metal plate. The picture frame enables quick and easy picture template replacement of picture template and the picture in the picture frame.

Abstract: Systems, devices, and methods of classifying encrypted network communications. A Traffic Monitoring Unit operates to monitor network traffic, and to capture HTTPS-encrypted packets that are exchanged over an HTTPS connection between an end-user device and a web server. An HTTPS Traffic Classification Unit operates to detect discrete HTTPS-encrypted objects within that HTTPS connection, and to classify those discrete HTTPS-encrypted objects based on at least one of: a first Analysis Model that classifies HTTPS-encrypted objects based on a type of content that is represented in the HTTPS-encrypted object; a second Analysis Model that classifies HTTPS-encrypted objects based on a type of server-side application that is associated with the HTTPS-encrypted object. Each Analysis Model utilizes Machine Learning (ML), Deep Learning (DL), Artificial Intelligence (AI), or Statistical and Mathematical Analysis (SMA).

Abstract: Systems, devices, and methods of classifying encrypted network communications. A Traffic Monitoring Unit operates to monitor network traffic, and to capture HTTPS-encrypted packets that are exchanged over an HTTPS connection between an end-user device and a web server. An HTTPS Traffic Classification Unit operates to detect discrete HTTPS-encrypted objects within that HTTPS connection, and to classify those discrete HTTPS-encrypted objects based on at least one of: a first Analysis Model that classifies HTTPS-encrypted objects based on a type of content that is represented in the HTTPS-encrypted object; a second Analysis Model that classifies HTTPS-encrypted objects based on a type of server-side application that is associated with the HTTPS-encrypted object. Each Analysis Model utilizes Machine Learning (ML), Deep Learning (DL), Artificial Intelligence (AI), or Statistical and Mathematical Analysis (SMA).

Abstract: Systems, devices, and methods of protecting electronic or Internet-connected devices against fraudulent and malicious activities. A Data Collector and Mediator Unit monitors network traffic, and generates datasets of network traffic; each dataset includes network traffic monitored within a time-slot having a particular fixed time-length. A Predictor Unit includes a Features Extractor, to extract features from the datasets; and a Machine Learning (ML) unit, to run the extracted features through a ML model and to classify a particular traffic-portion as being either (I) an anomalous traffic-portion that is associated with fraudulent or malicious activity, or (II) a non-anomalous traffic-portion that is not-associated with fraudulent or malicious activity. The ML unit operates on both (i) anomalies in traffic patterns, and (ii) anomalies of user behavior and/or device behavior.

Abstract: System, device, and method of detecting and mitigating Domain Name Server (DNS) tunneling attacks in a communication network. A system includes a Data Collector Unit, to monitor outbound Domain Name System (DNS) queries that are outgoing from a communication network or from an end-user device, towards an entry node of the Internet or towards a firewall unit or towards a trusted DNS server. The Data Collector Unit generates datasets of outbound DNS queries, each dataset corresponding to outbound DNS queries that are associated with a particular time-slot. A DNS Tunneling Attack Detector Unit includes a feature extractor, to extract Machine Learning (ML) features from each dataset of outbound DNS queries; and also a ML unit, to run the extracted features through a ML model, and to classify a particular outbound DNS query as belonging to a DNS tunneling attack based on ML-based analysis and classification of the extracted features.

Abstract: A garment is disclosed. The garment includes a loose fitting cowl; wherein the cowl covers the nose and mouth when deployed in an up position and drapes loosely in the front of the garment when in a relaxed position; wherein the cowl can be used as a face covering.

Abstract: The disclosure relates to photovoltaic modules comprising one or more photovoltaic cells embedded in a fiber-reinforced composite thermosetting material, wherein at a front side of the photovoltaic cells, the fiber-reinforced composite material comprises a substantially transparent resin, and substantially transparent fibers, and wherein the refractive indices of the resin and the glass fibers are substantially the same. In particular, the fibers can be glass fibers treated with aminosilane coupling agents and the resin can be an epoxy resin. Further disclosed are methods of manufacture of photovoltaic modules comprising one or more crystalline silicon photovoltaic cells comprising: providing a mold, one or more photovoltaic cells in the mold, and reinforcement fibers in the mold and positioning a bag surrounding the mold cavity. Then a vacuum is created in the bag substantially gradually, and the resin is infused with the mold due to the created vacuum.

Abstract: The present invention provides a nucleotide sequence encoding carbamoyl phosphate synthetase II of Plasmodium falciparum. Carbamoyl phosphate synthetase II catalyses the first committed and rate-limiting step in the de novo pyrimidine biosynthetic pathway. P. falciparum relies exclusively on pyrimidine synthesis de novo because of its inability to salvage pyrimidines. Mature human red blood cells, however, have no recognised requirement for a pyrimidine nucleotide. Accordingly, this enzyme represents a prime chemotherapeutic locus. The present invention relates to the use of the sequence encoding carbamoyl phosphate synthetase II in the recombinant production of carbamoyl phosphate synthetase II and to antisense molecules, ribozymes and other gene inactivation agents designed from this sequence.